Sample records for target registration errors

  1. Incorporating target registration error into robotic bone milling

    NASA Astrophysics Data System (ADS)

    Siebold, Michael A.; Dillon, Neal P.; Webster, Robert J.; Fitzpatrick, J. Michael

    2015-03-01

    Robots have been shown to be useful in assisting surgeons in a variety of bone drilling and milling procedures. Examples include commercial systems for joint repair or replacement surgeries, with in vitro feasibility recently shown for mastoidectomy. Typically, the robot is guided along a path planned on a CT image that has been registered to the physical anatomy in the operating room, which is in turn registered to the robot. The registrations often take advantage of the high accuracy of fiducial registration, but, because no real-world registration is perfect, the drill guided by the robot will inevitably deviate from its planned path. The extent of the deviation can vary from point to point along the path because of the spatial variation of target registration error. The allowable deviation can also vary spatially based on the necessary safety margin between the drill tip and various nearby anatomical structures along the path. Knowledge of the expected spatial distribution of registration error can be obtained from theoretical models or experimental measurements and used to modify the planned path. The objective of such modifications is to achieve desired probabilities for sparing specified structures. This approach has previously been studied for drilling straight holes but has not yet been generalized to milling procedures, such as mastoidectomy, in which cavities of more general shapes must be created. In this work, we present a general method for altering any path to achieve specified probabilities for any spatial arrangement of structures to be protected. We validate the method via numerical simulations in the context of mastoidectomy.

  2. Incorporating Target Registration Error Into Robotic Bone Milling

    PubMed Central

    Siebold, Michael A.; Dillon, Neal P.; Webster, Robert J.; Fitzpatrick, J. Michael

    2015-01-01

    Robots have been shown to be useful in assisting surgeons in a variety of bone drilling and milling procedures. Examples include commercial systems for joint repair or replacement surgeries, with in vitro feasibility recently shown for mastoidectomy. Typically, the robot is guided along a path planned on a CT image that has been registered to the physical anatomy in the operating room, which is in turn registered to the robot. The registrations often take advantage of the high accuracy of fiducial registration, but, because no real-world registration is perfect, the drill guided by the robot will inevitably deviate from its planned path. The extent of the deviation can vary from point to point along the path because of the spatial variation of target registration error. The allowable deviation can also vary spatially based on the necessary safety margin between the drill tip and various nearby anatomical structures along the path. Knowledge of the expected spatial distribution of registration error can be obtained from theoretical models or experimental measurements and used to modify the planned path. The objective of such modifications is to achieve desired probabilities for sparing specified structures. This approach has previously been studied for drilling straight holes but has not yet been generalized to milling procedures, such as mastoidectomy, in which cavities of more general shapes must be created. In this work, we present a general method for altering any path to achieve specified probabilities for any spatial arrangement of structures to be protected. We validate the method via numerical simulations in the context of mastoidectomy. PMID:26692630

  3. Hand-eye calibration using a target registration error model.

    PubMed

    Chen, Elvis C S; Morgan, Isabella; Jayarathne, Uditha; Ma, Burton; Peters, Terry M

    2017-10-01

    Surgical cameras are prevalent in modern operating theatres and are often used as a surrogate for direct vision. Visualisation techniques (e.g. image fusion) made possible by tracking the camera require accurate hand-eye calibration between the camera and the tracking system. The authors introduce the concept of 'guided hand-eye calibration', where calibration measurements are facilitated by a target registration error (TRE) model. They formulate hand-eye calibration as a registration problem between homologous point-line pairs. For each measurement, the position of a monochromatic ball-tip stylus (a point) and its projection onto the image (a line) is recorded, and the TRE of the resulting calibration is predicted using a TRE model. The TRE model is then used to guide the placement of the calibration tool, so that the subsequent measurement minimises the predicted TRE. Assessing TRE after each measurement produces accurate calibration using a minimal number of measurements. As a proof of principle, they evaluated guided calibration using a webcam and an endoscopic camera. Their endoscopic camera results suggest that millimetre TRE is achievable when at least 15 measurements are acquired with the tracker sensor ∼80 cm away on the laparoscope handle for a target ∼20 cm away from the camera.

  4. Hand–eye calibration using a target registration error model

    PubMed Central

    Morgan, Isabella; Jayarathne, Uditha; Ma, Burton; Peters, Terry M.

    2017-01-01

    Surgical cameras are prevalent in modern operating theatres and are often used as a surrogate for direct vision. Visualisation techniques (e.g. image fusion) made possible by tracking the camera require accurate hand–eye calibration between the camera and the tracking system. The authors introduce the concept of ‘guided hand–eye calibration’, where calibration measurements are facilitated by a target registration error (TRE) model. They formulate hand–eye calibration as a registration problem between homologous point–line pairs. For each measurement, the position of a monochromatic ball-tip stylus (a point) and its projection onto the image (a line) is recorded, and the TRE of the resulting calibration is predicted using a TRE model. The TRE model is then used to guide the placement of the calibration tool, so that the subsequent measurement minimises the predicted TRE. Assessing TRE after each measurement produces accurate calibration using a minimal number of measurements. As a proof of principle, they evaluated guided calibration using a webcam and an endoscopic camera. Their endoscopic camera results suggest that millimetre TRE is achievable when at least 15 measurements are acquired with the tracker sensor ∼80 cm away on the laparoscope handle for a target ∼20 cm away from the camera. PMID:29184657

  5. Error estimation of deformable image registration of pulmonary CT scans using convolutional neural networks.

    PubMed

    Eppenhof, Koen A J; Pluim, Josien P W

    2018-04-01

    Error estimation in nonlinear medical image registration is a nontrivial problem that is important for validation of registration methods. We propose a supervised method for estimation of registration errors in nonlinear registration of three-dimensional (3-D) images. The method is based on a 3-D convolutional neural network that learns to estimate registration errors from a pair of image patches. By applying the network to patches centered around every voxel, we construct registration error maps. The network is trained using a set of representative images that have been synthetically transformed to construct a set of image pairs with known deformations. The method is evaluated on deformable registrations of inhale-exhale pairs of thoracic CT scans. Using ground truth target registration errors on manually annotated landmarks, we evaluate the method's ability to estimate local registration errors. Estimation of full domain error maps is evaluated using a gold standard approach. The two evaluation approaches show that we can train the network to robustly estimate registration errors in a predetermined range, with subvoxel accuracy. We achieved a root-mean-square deviation of 0.51 mm from gold standard registration errors and of 0.66 mm from ground truth landmark registration errors.

  6. Quantitative evaluation for accumulative calibration error and video-CT registration errors in electromagnetic-tracked endoscopy.

    PubMed

    Liu, Sheena Xin; Gutiérrez, Luis F; Stanton, Doug

    2011-05-01

    Electromagnetic (EM)-guided endoscopy has demonstrated its value in minimally invasive interventions. Accuracy evaluation of the system is of paramount importance to clinical applications. Previously, a number of researchers have reported the results of calibrating the EM-guided endoscope; however, the accumulated errors of an integrated system, which ultimately reflect intra-operative performance, have not been characterized. To fill this vacancy, we propose a novel system to perform this evaluation and use a 3D metric to reflect the intra-operative procedural accuracy. This paper first presents a portable design and a method for calibration of an electromagnetic (EM)-tracked endoscopy system. An evaluation scheme is then described that uses the calibration results and EM-CT registration to enable real-time data fusion between CT and endoscopic video images. We present quantitative evaluation results for estimating the accuracy of this system using eight internal fiducials as the targets on an anatomical phantom: the error is obtained by comparing the positions of these targets in the CT space, EM space and endoscopy image space. To obtain 3D error estimation, the 3D locations of the targets in the endoscopy image space are reconstructed from stereo views of the EM-tracked monocular endoscope. Thus, the accumulated errors are evaluated in a controlled environment, where the ground truth information is present and systematic performance (including the calibration error) can be assessed. We obtain the mean in-plane error to be on the order of 2 pixels. To evaluate the data integration performance for virtual navigation, target video-CT registration error (TRE) is measured as the 3D Euclidean distance between the 3D-reconstructed targets of endoscopy video images and the targets identified in CT. The 3D error (TRE) encapsulates EM-CT registration error, EM-tracking error, fiducial localization error, and optical-EM calibration error. We present in this paper our

  7. In vivo estimation of target registration errors during augmented reality laparoscopic surgery.

    PubMed

    Thompson, Stephen; Schneider, Crispin; Bosi, Michele; Gurusamy, Kurinchi; Ourselin, Sébastien; Davidson, Brian; Hawkes, David; Clarkson, Matthew J

    2018-06-01

    Successful use of augmented reality for laparoscopic surgery requires that the surgeon has a thorough understanding of the likely accuracy of any overlay. Whilst the accuracy of such systems can be estimated in the laboratory, it is difficult to extend such methods to the in vivo clinical setting. Herein we describe a novel method that enables the surgeon to estimate in vivo errors during use. We show that the method enables quantitative evaluation of in vivo data gathered with the SmartLiver image guidance system. The SmartLiver system utilises an intuitive display to enable the surgeon to compare the positions of landmarks visible in both a projected model and in the live video stream. From this the surgeon can estimate the system accuracy when using the system to locate subsurface targets not visible in the live video. Visible landmarks may be either point or line features. We test the validity of the algorithm using an anatomically representative liver phantom, applying simulated perturbations to achieve clinically realistic overlay errors. We then apply the algorithm to in vivo data. The phantom results show that using projected errors of surface features provides a reliable predictor of subsurface target registration error for a representative human liver shape. Applying the algorithm to in vivo data gathered with the SmartLiver image-guided surgery system shows that the system is capable of accuracies around 12 mm; however, achieving this reliably remains a significant challenge. We present an in vivo quantitative evaluation of the SmartLiver image-guided surgery system, together with a validation of the evaluation algorithm. This is the first quantitative in vivo analysis of an augmented reality system for laparoscopic surgery.

  8. SU-D-BRA-03: Analysis of Systematic Errors with 2D/3D Image Registration for Target Localization and Treatment Delivery in Stereotactic Radiosurgery

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Xu, H; Chetty, I; Wen, N

    Purpose: Determine systematic deviations between 2D/3D and 3D/3D image registrations with six degrees of freedom (6DOF) for various imaging modalities and registration algorithms on the Varian Edge Linac. Methods: The 6DOF systematic errors were assessed by comparing automated 2D/3D (kV/MV vs. CT) with 3D/3D (CBCT vs. CT) image registrations from different imaging pairs, CT slice thicknesses, couch angles, similarity measures, etc., using a Rando head and a pelvic phantom. The 2D/3D image registration accuracy was evaluated at different treatment sites (intra-cranial and extra-cranial) by statistically analyzing 2D/3D pre-treatment verification against 3D/3D localization of 192 Stereotactic Radiosurgery/Stereotactic Body Radiation Therapy treatmentmore » fractions for 88 patients. Results: The systematic errors of 2D/3D image registration using kV-kV, MV-kV and MV-MV image pairs using 0.8 mm slice thickness CT images were within 0.3 mm and 0.3° for translations and rotations with a 95% confidence interval (CI). No significant difference between 2D/3D and 3D/3D image registrations (P>0.05) was observed for target localization at various CT slice thicknesses ranging from 0.8 to 3 mm. Couch angles (30, 45, 60 degree) did not impact the accuracy of 2D/3D image registration. Using pattern intensity with content image filtering was recommended for 2D/3D image registration to achieve the best accuracy. For the patient study, translational error was within 2 mm and rotational error was within 0.6 degrees in terms of 95% CI for 2D/3D image registration. For intra-cranial sites, means and std. deviations of translational errors were −0.2±0.7, 0.04±0.5, 0.1±0.4 mm for LNG, LAT, VRT directions, respectively. For extra-cranial sites, means and std. deviations of translational errors were - 0.04±1, 0.2±1, 0.1±1 mm for LNG, LAT, VRT directions, respectively. 2D/3D image registration uncertainties for intra-cranial and extra-cranial sites were comparable. Conclusion

  9. Analysis of Point Based Image Registration Errors With Applications in Single Molecule Microscopy

    PubMed Central

    Cohen, E. A. K.; Ober, R. J.

    2014-01-01

    We present an asymptotic treatment of errors involved in point-based image registration where control point (CP) localization is subject to heteroscedastic noise; a suitable model for image registration in fluorescence microscopy. Assuming an affine transform, CPs are used to solve a multivariate regression problem. With measurement errors existing for both sets of CPs this is an errors-in-variable problem and linear least squares is inappropriate; the correct method being generalized least squares. To allow for point dependent errors the equivalence of a generalized maximum likelihood and heteroscedastic generalized least squares model is achieved allowing previously published asymptotic results to be extended to image registration. For a particularly useful model of heteroscedastic noise where covariance matrices are scalar multiples of a known matrix (including the case where covariance matrices are multiples of the identity) we provide closed form solutions to estimators and derive their distribution. We consider the target registration error (TRE) and define a new measure called the localization registration error (LRE) believed to be useful, especially in microscopy registration experiments. Assuming Gaussianity of the CP localization errors, it is shown that the asymptotic distribution for the TRE and LRE are themselves Gaussian and the parameterized distributions are derived. Results are successfully applied to registration in single molecule microscopy to derive the key dependence of the TRE and LRE variance on the number of CPs and their associated photon counts. Simulations show asymptotic results are robust for low CP numbers and non-Gaussianity. The method presented here is shown to outperform GLS on real imaging data. PMID:24634573

  10. Local-search based prediction of medical image registration error

    NASA Astrophysics Data System (ADS)

    Saygili, Görkem

    2018-03-01

    Medical image registration is a crucial task in many different medical imaging applications. Hence, considerable amount of work has been published recently that aim to predict the error in a registration without any human effort. If provided, these error predictions can be used as a feedback to the registration algorithm to further improve its performance. Recent methods generally start with extracting image-based and deformation-based features, then apply feature pooling and finally train a Random Forest (RF) regressor to predict the real registration error. Image-based features can be calculated after applying a single registration but provide limited accuracy whereas deformation-based features such as variation of deformation vector field may require up to 20 registrations which is a considerably high time-consuming task. This paper proposes to use extracted features from a local search algorithm as image-based features to estimate the error of a registration. The proposed method comprises a local search algorithm to find corresponding voxels between registered image pairs and based on the amount of shifts and stereo confidence measures, it predicts the amount of registration error in millimetres densely using a RF regressor. Compared to other algorithms in the literature, the proposed algorithm does not require multiple registrations, can be efficiently implemented on a Graphical Processing Unit (GPU) and can still provide highly accurate error predictions in existence of large registration error. Experimental results with real registrations on a public dataset indicate a substantially high accuracy achieved by using features from the local search algorithm.

  11. Supervised local error estimation for nonlinear image registration using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Eppenhof, Koen A. J.; Pluim, Josien P. W.

    2017-02-01

    Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation of a registration error map for nonlinear image registration. The method is based on a convolutional neural network that estimates the norm of the residual deformation from patches around each pixel in two registered images. This norm is interpreted as the registration error, and is defined for every pixel in the image domain. The network is trained using a set of artificially deformed images. Each training example is a pair of images: the original image, and a random deformation of that image. No manually labeled ground truth error is required. At test time, only the two registered images are required as input. We train and validate the network on registrations in a set of 2D digital subtraction angiography sequences, such that errors up to eight pixels can be estimated. We show that for this range of errors the convolutional network is able to learn the registration error in pairs of 2D registered images at subpixel precision. Finally, we present a proof of principle for the extension to 3D registration problems in chest CTs, showing that the method has the potential to estimate errors in 3D registration problems.

  12. Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles.

    PubMed

    Lu, Xiaodong; Xie, Yuting; Zhou, Jun

    2018-05-27

    Inspired by the problem that the current spatial registration methods are unsuitable for three-dimensional (3-D) sensor on high-dynamic platform, this paper focuses on the estimation for the registration errors of cooperative missiles and motion states of maneuvering target. There are two types of errors being discussed: sensor measurement biases and attitude biases. Firstly, an improved Kalman Filter on Earth-Centered Earth-Fixed (ECEF-KF) coordinate algorithm is proposed to estimate the deviations mentioned above, from which the outcomes are furtherly compensated to the error terms. Secondly, the Pseudo Linear Kalman Filter (PLKF) and the nonlinear scheme the Unscented Kalman Filter (UKF) with modified inputs are employed for target tracking. The convergence of filtering results are monitored by a position-judgement logic, and a low-pass first order filter is selectively introduced before compensation to inhibit the jitter of estimations. In the simulation, the ECEF-KF enhancement is proven to improve the accuracy and robustness of the space alignment, while the conditional-compensation-based PLKF method is demonstrated to be the optimal performance in target tracking.

  13. Optimal full motion video registration with rigorous error propagation

    NASA Astrophysics Data System (ADS)

    Dolloff, John; Hottel, Bryant; Doucette, Peter; Theiss, Henry; Jocher, Glenn

    2014-06-01

    Optimal full motion video (FMV) registration is a crucial need for the Geospatial community. It is required for subsequent and optimal geopositioning with simultaneous and reliable accuracy prediction. An overall approach being developed for such registration is presented that models relevant error sources in terms of the expected magnitude and correlation of sensor errors. The corresponding estimator is selected based on the level of accuracy of the a priori information of the sensor's trajectory and attitude (pointing) information, in order to best deal with non-linearity effects. Estimator choices include near real-time Kalman Filters and batch Weighted Least Squares. Registration solves for corrections to the sensor a priori information for each frame. It also computes and makes available a posteriori accuracy information, i.e., the expected magnitude and correlation of sensor registration errors. Both the registered sensor data and its a posteriori accuracy information are then made available to "down-stream" Multi-Image Geopositioning (MIG) processes. An object of interest is then measured on the registered frames and a multi-image optimal solution, including reliable predicted solution accuracy, is then performed for the object's 3D coordinates. This paper also describes a robust approach to registration when a priori information of sensor attitude is unavailable. It makes use of structure-from-motion principles, but does not use standard Computer Vision techniques, such as estimation of the Essential Matrix which can be very sensitive to noise. The approach used instead is a novel, robust, direct search-based technique.

  14. A method to map errors in the deformable registration of 4DCT images1

    PubMed Central

    Vaman, Constantin; Staub, David; Williamson, Jeffrey; Murphy, Martin J.

    2010-01-01

    Purpose: To present a new approach to the problem of estimating errors in deformable image registration (DIR) applied to sequential phases of a 4DCT data set. Methods: A set of displacement vector fields (DVFs) are made by registering a sequence of 4DCT phases. The DVFs are assumed to display anatomical movement, with the addition of errors due to the imaging and registration processes. The positions of physical landmarks in each CT phase are measured as ground truth for the physical movement in the DVF. Principal component analysis of the DVFs and the landmarks is used to identify and separate the eigenmodes of physical movement from the error eigenmodes. By subtracting the physical modes from the principal components of the DVFs, the registration errors are exposed and reconstructed as DIR error maps. The method is demonstrated via a simple numerical model of 4DCT DVFs that combines breathing movement with simulated maps of spatially correlated DIR errors. Results: The principal components of the simulated DVFs were observed to share the basic properties of principal components for actual 4DCT data. The simulated error maps were accurately recovered by the estimation method. Conclusions: Deformable image registration errors can have complex spatial distributions. Consequently, point-by-point landmark validation can give unrepresentative results that do not accurately reflect the registration uncertainties away from the landmarks. The authors are developing a method for mapping the complete spatial distribution of DIR errors using only a small number of ground truth validation landmarks. PMID:21158288

  15. Ultrasound fusion image error correction using subject-specific liver motion model and automatic image registration.

    PubMed

    Yang, Minglei; Ding, Hui; Zhu, Lei; Wang, Guangzhi

    2016-12-01

    Ultrasound fusion imaging is an emerging tool and benefits a variety of clinical applications, such as image-guided diagnosis and treatment of hepatocellular carcinoma and unresectable liver metastases. However, respiratory liver motion-induced misalignment of multimodal images (i.e., fusion error) compromises the effectiveness and practicability of this method. The purpose of this paper is to develop a subject-specific liver motion model and automatic registration-based method to correct the fusion error. An online-built subject-specific motion model and automatic image registration method for 2D ultrasound-3D magnetic resonance (MR) images were combined to compensate for the respiratory liver motion. The key steps included: 1) Build a subject-specific liver motion model for current subject online and perform the initial registration of pre-acquired 3D MR and intra-operative ultrasound images; 2) During fusion imaging, compensate for liver motion first using the motion model, and then using an automatic registration method to further correct the respiratory fusion error. Evaluation experiments were conducted on liver phantom and five subjects. In the phantom study, the fusion error (superior-inferior axis) was reduced from 13.90±2.38mm to 4.26±0.78mm by using the motion model only. The fusion error further decreased to 0.63±0.53mm by using the registration method. The registration method also decreased the rotation error from 7.06±0.21° to 1.18±0.66°. In the clinical study, the fusion error was reduced from 12.90±9.58mm to 6.12±2.90mm by using the motion model alone. Moreover, the fusion error decreased to 1.96±0.33mm by using the registration method. The proposed method can effectively correct the respiration-induced fusion error to improve the fusion image quality. This method can also reduce the error correction dependency on the initial registration of ultrasound and MR images. Overall, the proposed method can improve the clinical practicability of

  16. Localization accuracy from automatic and semi-automatic rigid registration of locally-advanced lung cancer targets during image-guided radiation therapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Robertson, Scott P.; Weiss, Elisabeth; Hugo, Geoffrey D.

    2012-01-15

    Purpose: To evaluate localization accuracy resulting from rigid registration of locally-advanced lung cancer targets using fully automatic and semi-automatic protocols for image-guided radiation therapy. Methods: Seventeen lung cancer patients, fourteen also presenting with involved lymph nodes, received computed tomography (CT) scans once per week throughout treatment under active breathing control. A physician contoured both lung and lymph node targets for all weekly scans. Various automatic and semi-automatic rigid registration techniques were then performed for both individual and simultaneous alignments of the primary gross tumor volume (GTV{sub P}) and involved lymph nodes (GTV{sub LN}) to simulate the localization process in image-guidedmore » radiation therapy. Techniques included ''standard'' (direct registration of weekly images to a planning CT), ''seeded'' (manual prealignment of targets to guide standard registration), ''transitive-based'' (alignment of pretreatment and planning CTs through one or more intermediate images), and ''rereferenced'' (designation of a new reference image for registration). Localization error (LE) was assessed as the residual centroid and border distances between targets from planning and weekly CTs after registration. Results: Initial bony alignment resulted in centroid LE of 7.3 {+-} 5.4 mm and 5.4 {+-} 3.4 mm for the GTV{sub P} and GTV{sub LN}, respectively. Compared to bony alignment, transitive-based and seeded registrations significantly reduced GTV{sub P} centroid LE to 4.7 {+-} 3.7 mm (p = 0.011) and 4.3 {+-} 2.5 mm (p < 1 x 10{sup -3}), respectively, but the smallest GTV{sub P} LE of 2.4 {+-} 2.1 mm was provided by rereferenced registration (p < 1 x 10{sup -6}). Standard registration significantly reduced GTV{sub LN} centroid LE to 3.2 {+-} 2.5 mm (p < 1 x 10{sup -3}) compared to bony alignment, with little additional gain offered by the other registration techniques. For simultaneous target alignment, centroid LE

  17. A finite element method to correct deformable image registration errors in low-contrast regions

    NASA Astrophysics Data System (ADS)

    Zhong, Hualiang; Kim, Jinkoo; Li, Haisen; Nurushev, Teamour; Movsas, Benjamin; Chetty, Indrin J.

    2012-06-01

    Image-guided adaptive radiotherapy requires deformable image registration to map radiation dose back and forth between images. The purpose of this study is to develop a novel method to improve the accuracy of an intensity-based image registration algorithm in low-contrast regions. A computational framework has been developed in this study to improve the quality of the ‘demons’ registration. For each voxel in the registration's target image, the standard deviation of image intensity in a neighborhood of this voxel was calculated. A mask for high-contrast regions was generated based on their standard deviations. In the masked regions, a tetrahedral mesh was refined recursively so that a sufficient number of tetrahedral nodes in these regions can be selected as driving nodes. An elastic system driven by the displacements of the selected nodes was formulated using a finite element method (FEM) and implemented on the refined mesh. The displacements of these driving nodes were generated with the ‘demons’ algorithm. The solution of the system was derived using a conjugated gradient method, and interpolated to generate a displacement vector field for the registered images. The FEM correction method was compared with the ‘demons’ algorithm on the computed tomography (CT) images of lung and prostate patients. The performance of the FEM correction relating to the ‘demons’ registration was analyzed based on the physical property of their deformation maps, and quantitatively evaluated through a benchmark model developed specifically for this study. Compared to the benchmark model, the ‘demons’ registration has the maximum error of 1.2 cm, which can be corrected by the FEM to 0.4 cm, and the average error of the ‘demons’ registration is reduced from 0.17 to 0.11 cm. For the CT images of lung and prostate patients, the deformation maps generated by the ‘demons’ algorithm were found unrealistic at several places. In these places, the displacement

  18. Evaluation of 4D-CT lung registration.

    PubMed

    Kabus, Sven; Klinder, Tobias; Murphy, Keelin; van Ginneken, Bram; van Lorenz, Cristian; Pluim, Josien P W

    2009-01-01

    Non-rigid registration accuracy assessment is typically performed by evaluating the target registration error at manually placed landmarks. For 4D-CT lung data, we compare two sets of landmark distributions: a smaller set primarily defined on vessel bifurcations as commonly described in the literature and a larger set being well-distributed throughout the lung volume. For six different registration schemes (three in-house schemes and three schemes frequently used by the community) the landmark error is evaluated and found to depend significantly on the distribution of the landmarks. In particular, lung regions near to the pleura show a target registration error three times larger than near-mediastinal regions. While the inter-method variability on the landmark positions is rather small, the methods show discriminating differences with respect to consistency and local volume change. In conclusion, both a well-distributed set of landmarks and a deformation vector field analysis are necessary for reliable non-rigid registration accuracy assessment.

  19. A Finite Element Method to Correct Deformable Image Registration Errors in Low-Contrast Regions

    PubMed Central

    Zhong, Hualiang; Kim, Jinkoo; Li, Haisen; Nurushev, Teamour; Movsas, Benjamin; Chetty, Indrin J.

    2012-01-01

    Image-guided adaptive radiotherapy requires deformable image registration to map radiation dose back and forth between images. The purpose of this study is to develop a novel method to improve the accuracy of an intensity-based image registration algorithm in low-contrast regions. A computational framework has been developed in this study to improve the quality of the “demons” registration. For each voxel in the registration’s target image, the standard deviation of image intensity in a neighborhood of this voxel was calculated. A mask for high-contrast regions was generated based on their standard deviations. In the masked regions, a tetrahedral mesh was refined recursively so that a sufficient number of tetrahedral nodes in these regions can be selected as driving nodes. An elastic system driven by the displacements of the selected nodes was formulated using a finite element method (FEM) and implemented on the refined mesh. The displacements of these driving nodes were generated with the “demons” algorithm. The solution of the system was derived using a conjugated gradient method, and interpolated to generate a displacement vector field for the registered images. The FEM correction method was compared with the “demons” algorithm on the CT images of lung and prostate patients. The performance of the FEM correction relating to the “demons” registration was analyzed based on the physical property of their deformation maps, and quantitatively evaluated through a benchmark model developed specifically for this study. Compared to the benchmark model, the “demons” registration has the maximum error of 1.2 cm, which can be corrected by the FEM method to 0.4 cm, and the average error of the “demons” registration is reduced from 0.17 cm to 0.11 cm. For the CT images of lung and prostate patients, the deformation maps generated by the “demons” algorithm were found unrealistic at several places. In these places, the displacement differences

  20. New Protocol for Skin Landmark Registration in Image-Guided Neurosurgery: Technical Note.

    PubMed

    Gerard, Ian J; Hall, Jeffery A; Mok, Kelvin; Collins, D Louis

    2015-09-01

    Newer versions of the commercial Medtronic StealthStation allow the use of only 8 landmark pairs for patient-to-image registration as opposed to 9 landmarks in older systems. The choice of which landmark pair to drop in these newer systems can have an effect on the quality of the patient-to-image registration. To investigate 4 landmark registration protocols based on 8 landmark pairs and compare the resulting registration accuracy with a 9-landmark protocol. Four different protocols were tested on both phantoms and patients. Two of the protocols involved using 4 ear landmarks and 4 facial landmarks and the other 2 involved using 3 ear landmarks and 5 facial landmarks. Both the fiducial registration error and target registration error were evaluated for each of the different protocols to determine any difference between them and the 9-landmark protocol. No difference in fiducial registration error was found between any of the 8-landmark protocols and the 9-landmark protocol. A significant decrease (P < .05) in target registration error was found when using a protocol based on 4 ear landmarks and 4 facial landmarks compared with the other protocols based on 3 ear landmarks. When using 8 landmarks to perform the patient-to-image registration, the protocol using 4 ear landmarks and 4 facial landmarks greatly outperformed the other 8-landmark protocols and 9-landmark protocol, resulting in the lowest target registration error.

  1. Multimodality Non-Rigid Image Registration for Planning, Targeting and Monitoring during CT-guided Percutaneous Liver Tumor Cryoablation

    PubMed Central

    Elhawary, Haytham; Oguro, Sota; Tuncali, Kemal; Morrison, Paul R.; Tatli, Servet; Shyn, Paul B.; Silverman, Stuart G.; Hata, Nobuhiko

    2010-01-01

    Rationale and Objectives To develop non-rigid image registration between pre-procedure contrast enhanced MR images and intra-procedure unenhanced CT images, to enhance tumor visualization and localization during CT-guided liver tumor cryoablation procedures. Materials and Methods After IRB approval, a non-rigid registration (NRR) technique was evaluated with different pre-processing steps and algorithm parameters and compared to a standard rigid registration (RR) approach. The Dice Similarity Coefficient (DSC), Target Registration Error (TRE), 95% Hausdorff distance (HD) and total registration time (minutes) were compared using a two-sided Student’s t-test. The entire registration method was then applied during five CT-guided liver cryoablation cases with the intra-procedural CT data transmitted directly from the CT scanner, with both accuracy and registration time evaluated. Results Selected optimal parameters for registration were section thickness of 5mm, cropping the field of view to 66% of its original size, manual segmentation of the liver, B-spline control grid of 5×5×5 and spatial sampling of 50,000 pixels. Mean 95% HD of 3.3mm (2.5x improvement compared to RR, p<0.05); mean DSC metric of 0.97 (13% increase); and mean TRE of 4.1mm (2.7x reduction) were measured. During the cryoablation procedure registration between the pre-procedure MR and the planning intra-procedure CT took a mean time of 10.6 minutes, the MR to targeting CT image took 4 minutes and MR to monitoring CT took 4.3 minutes. Mean registration accuracy was under 3.4mm. Conclusion Non-rigid registration allowed improved visualization of the tumor during interventional planning, targeting and evaluation of tumor coverage by the ice ball. Future work is focused on reducing segmentation time to make the method more clinically acceptable. PMID:20817574

  2. Development and application of pulmonary structure-function registration methods: towards pulmonary image-guidance tools for improved airway targeted therapies and outcomes

    NASA Astrophysics Data System (ADS)

    Guo, Fumin; Pike, Damien; Svenningsen, Sarah; Coxson, Harvey O.; Drozd, John J.; Yuan, Jing; Fenster, Aaron; Parraga, Grace

    2014-03-01

    Objectives: We aimed to develop a way to rapidly generate multi-modality (MRI-CT) pulmonary imaging structurefunction maps using novel non-rigid image registration methods. This objective is part of our overarching goal to provide an image processing pipeline to generate pulmonary structure-function maps and guide airway-targeted therapies. Methods: Anatomical 1H and functional 3He MRI were acquired in 5 healthy asymptomatic ex-smokers and 7 ex-smokers with chronic obstructive pulmonary disease (COPD) at inspiration breath-hold. Thoracic CT was performed within ten minutes of MRI using the same breath-hold volume. Landmark-based affine registration methods previously validated for imaging of COPD, was based on corresponding fiducial markers located in both CT and 1H MRI coronal slices and compared with shape-based CT-MRI non-rigid registration. Shape-based CT-MRI registration was developed by first identifying the shapes of the lung cavities manually, and then registering the two shapes using affine and thin-plate spline algorithms. We compared registration accuracy using the fiducial localization error (FLE) and target registration error (TRE). Results: For landmark-based registration, the TRE was 8.4±5.3 mm for whole lung and 7.8±4.6 mm for the R and L lungs registered independently (p=0.4). For shape-based registration, the TRE was 8.0±4.6 mm for whole lung as compared to 6.9±4.4 mm for the R and L lung registered independently and this difference was significant (p=0.01). The difference for shape-based (6.9±4.4 mm) and landmark-based R and L lung registration (7.8±4.6 mm) was also significant (p=.04) Conclusion: Shape-based registration TRE was significantly improved compared to landmark-based registration when considering L and R lungs independently.

  3. Consistency-based rectification of nonrigid registrations

    PubMed Central

    Gass, Tobias; Székely, Gábor; Goksel, Orcun

    2015-01-01

    Abstract. We present a technique to rectify nonrigid registrations by improving their group-wise consistency, which is a widely used unsupervised measure to assess pair-wise registration quality. While pair-wise registration methods cannot guarantee any group-wise consistency, group-wise approaches typically enforce perfect consistency by registering all images to a common reference. However, errors in individual registrations to the reference then propagate, distorting the mean and accumulating in the pair-wise registrations inferred via the reference. Furthermore, the assumption that perfect correspondences exist is not always true, e.g., for interpatient registration. The proposed consistency-based registration rectification (CBRR) method addresses these issues by minimizing the group-wise inconsistency of all pair-wise registrations using a regularized least-squares algorithm. The regularization controls the adherence to the original registration, which is additionally weighted by the local postregistration similarity. This allows CBRR to adaptively improve consistency while locally preserving accurate pair-wise registrations. We show that the resulting registrations are not only more consistent, but also have lower average transformation error when compared to known transformations in simulated data. On clinical data, we show improvements of up to 50% target registration error in breathing motion estimation from four-dimensional MRI and improvements in atlas-based segmentation quality of up to 65% in terms of mean surface distance in three-dimensional (3-D) CT. Such improvement was observed consistently using different registration algorithms, dimensionality (two-dimensional/3-D), and modalities (MRI/CT). PMID:26158083

  4. WE-AB-BRA-01: 3D-2D Image Registration for Target Localization in Spine Surgery: Comparison of Similarity Metrics Against Robustness to Content Mismatch

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    De Silva, T; Ketcha, M; Siewerdsen, J H

    Purpose: In image-guided spine surgery, mapping 3D preoperative images to 2D intraoperative images via 3D-2D registration can provide valuable assistance in target localization. However, the presence of surgical instrumentation, hardware implants, and soft-tissue resection/displacement causes mismatches in image content, confounding existing registration methods. Manual/semi-automatic methods to mask such extraneous content is time consuming, user-dependent, error prone, and disruptive to clinical workflow. We developed and evaluated 2 novel similarity metrics within a robust registration framework to overcome such challenges in target localization. Methods: An IRB-approved retrospective study in 19 spine surgery patients included 19 preoperative 3D CT images and 50 intraoperativemore » mobile radiographs in cervical, thoracic, and lumbar spine regions. A neuroradiologist provided truth definition of vertebral positions in CT and radiography. 3D-2D registration was performed using the CMA-ES optimizer with 4 gradient-based image similarity metrics: (1) gradient information (GI); (2) gradient correlation (GC); (3) a novel variant referred to as gradient orientation (GO); and (4) a second variant referred to as truncated gradient correlation (TGC). Registration accuracy was evaluated in terms of the projection distance error (PDE) of the vertebral levels. Results: Conventional similarity metrics were susceptible to gross registration error and failure modes associated with the presence of surgical instrumentation: for GI, the median PDE and interquartile range was 33.0±43.6 mm; similarly for GC, PDE = 23.0±92.6 mm respectively. The robust metrics GO and TGC, on the other hand, demonstrated major improvement in PDE (7.6 ±9.4 mm and 8.1± 18.1 mm, respectively) and elimination of gross failure modes. Conclusion: The proposed GO and TGC similarity measures improve registration accuracy and robustness to gross failure in the presence of strong image content mismatch

  5. A comparison of registration errors with imageless computer navigation during MIS total knee arthroplasty versus standard incision total knee arthroplasty: a cadaveric study.

    PubMed

    Davis, Edward T; Pagkalos, Joseph; Gallie, Price A M; Macgroarty, Kelly; Waddell, James P; Schemitsch, Emil H

    2015-01-01

    Optimal component alignment in total knee arthroplasty has been associated with better functional outcome as well as improved implant longevity. The ability to align components optimally during minimally invasive (MIS) total knee replacement (TKR) has been a cause of concern. Computer navigation is a useful aid in achieving the desired alignment although it is limited by the error during the manual registration of landmarks. Our study aims to compare the registration process error between a standard and a MIS surgical approach. We hypothesized that performing the registration error via an MIS approach would increase the registration process error. Five fresh frozen lower limbs were routinely prepared and draped. The registration process was performed through an MIS approach. This was then extended to the standard approach and the registration was performed again. Two surgeons performed the registration process five times with each approach. Performing the registration process through the MIS approach was not associated with higher error compared to the standard approach in the alignment parameters of interest. This rejects our hypothesis. Image-free navigated MIS TKR does not appear to carry higher risk of component malalignment due to the registration process error. Navigation can be used during MIS TKR to improve alignment without reduced accuracy due to the approach.

  6. 3D-2D registration for surgical guidance: effect of projection view angles on registration accuracy

    NASA Astrophysics Data System (ADS)

    Uneri, A.; Otake, Y.; Wang, A. S.; Kleinszig, G.; Vogt, S.; Khanna, A. J.; Siewerdsen, J. H.

    2014-01-01

    An algorithm for intensity-based 3D-2D registration of CT and x-ray projections is evaluated, specifically using single- or dual-projection views to provide 3D localization. The registration framework employs the gradient information similarity metric and covariance matrix adaptation evolution strategy to solve for the patient pose in six degrees of freedom. Registration performance was evaluated in an anthropomorphic phantom and cadaver, using C-arm projection views acquired at angular separation, Δθ, ranging from ˜0°-180° at variable C-arm magnification. Registration accuracy was assessed in terms of 2D projection distance error and 3D target registration error (TRE) and compared to that of an electromagnetic (EM) tracker. The results indicate that angular separation as small as Δθ ˜10°-20° achieved TRE <2 mm with 95% confidence, comparable or superior to that of the EM tracker. The method allows direct registration of preoperative CT and planning data to intraoperative fluoroscopy, providing 3D localization free from conventional limitations associated with external fiducial markers, stereotactic frames, trackers and manual registration.

  7. Registration of MRI to Intraoperative Radiographs for Target Localization in Spinal Interventions

    PubMed Central

    De Silva, T; Uneri, A; Ketcha, M D; Reaungamornrat, S; Goerres, J; Jacobson, M W; Vogt, S; Kleinszig, G; Khanna, A J; Wolinsky, J-P; Siewerdsen, J H

    2017-01-01

    Purpose Decision support to assist in target vertebra localization could provide a useful aid to safe and effective spine surgery. Previous solutions have shown 3D-2D registration of preoperative CT to intraoperative radiographs to reliably annotate vertebral labels for assistance during level localization. We present an algorithm (referred to as MR-LevelCheck) to perform 3D-2D registration based on a preoperative MRI to accommodate the increasingly common clinical scenario in which MRI is used instead of CT for preoperative planning. Methods Straightforward adaptation of gradient/intensity-based methods appropriate to CT-to-radiograph registration is confounded by large mismatch and noncorrespondence in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simple vertebrae segmentation step using vertebra centroids as seed points (automatically defined within existing workflow). Forwards projections are computed using segmented MRI and registered to radiographs via gradient orientation (GO) similarity and the CMA-ES (Covariance-Matrix-Adaptation Evolutionary-Strategy) optimizer. The method was tested in an IRB-approved study involving 10 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. Results The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch and large capture range. Robust registration performance was achieved with projection distance error (PDE) (median ± iqr) = 4.3 ± 2.6 mm (median ± iqr) and 0% failure rate. Segmentation accuracy for the continuous max-flow method yielded Dice coefficient = 88.1 ± 5.2, Accuracy = 90.6 ± 5.7, RMSE = 1.8 ± 0.6 mm, and contour affinity ratio (CAR) = 0.82 ± 0.08. Registration performance was found to be robust for segmentation methods exhibiting RMSE < 3 mm and CAR > 0.50. Conclusion The MR-LevelCheck method provides a

  8. Splint sterilization--a potential registration hazard in computer-assisted surgery.

    PubMed

    Figl, Michael; Weber, Christoph; Assadian, Ojan; Toma, Cyril D; Traxler, Hannes; Seemann, Rudolf; Guevara-Rojas, Godoberto; Pöschl, Wolfgang P; Ewers, Rolf; Schicho, Kurt

    2012-04-01

    Registration of preoperative targeting information for the intraoperative situation is a crucial step in computer-assisted surgical interventions. Point-to-point registration using acrylic splints is among the most frequently used procedures. There are, however, no generally accepted recommendations for sterilization of the splint. An appropriate method for the thermolabile splint would be hydrogen peroxide-based plasma sterilization. This study evaluated the potential deformation of the splint undergoing such sterilization. Deformation was quantified using image-processing methods applied to computed tomographic (CT) volumes before and after sterilization. An acrylic navigation splint was used as the study object. Eight metallic markers placed in the splint were used for registration. Six steel spheres in the mouthpiece were used as targets. Two CT volumes of the splint were acquired before and after 5 sterilization cycles using a hydrogen peroxide sterilizer. Point-to-point registration was applied, and fiducial and target registration errors were computed. Surfaces were extracted from CT scans and Hausdorff distances were derived. Effectiveness of sterilization was determined using Geobacillus stearothermophilus. Fiducial-based registration of CT scans before and after sterilization resulted in a mean fiducial registration error of 0.74 mm; the target registration error in the mouthpiece was 0.15 mm. The Hausdorff distance, describing the maximal deformation of the splint, was 2.51 mm. Ninety percent of point-surface distances were shorter than 0.61 mm, and 95% were shorter than 0.73 mm. No bacterial growth was found after the sterilization process. Hydrogen peroxide-based low-temperature plasma sterilization does not deform the splint, which is the base for correct computer-navigated surgery. Copyright © 2012 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

  9. SU-E-J-87: Building Deformation Error Histogram and Quality Assurance of Deformable Image Registration.

    PubMed

    Park, S B; Kim, H; Yao, M; Ellis, R; Machtay, M; Sohn, J W

    2012-06-01

    To quantify the systematic error of a Deformable Image Registration (DIR) system and establish Quality Assurance (QA) procedure. To address the shortfall of landmark approach which it is only available at the significant visible feature points, we adapted a Deformation Vector Map (DVM) comparison approach. We used two CT image sets (R and T image sets) taken for the same patient at different time and generated a DVM, which includes the DIR systematic error. The DVM was calculated using fine-tuned B-Spline DIR and L-BFGS optimizer. By utilizing this DVM we generated R' image set to eliminate the systematic error in DVM,. Thus, we have truth data set, R' and T image sets, and the truth DVM. To test a DIR system, we use R' and T image sets to a DIR system. We compare the test DVM to the truth DVM. If there is no systematic error, they should be identical. We built Deformation Error Histogram (DEH) for quantitative analysis. The test registration was performed with an in-house B-Spline DIR system using a stochastic gradient descent optimizer. Our example data set was generated with a head and neck patient case. We also tested CT to CBCT deformable registration. We found skin regions which interface with the air has relatively larger errors. Also mobile joints such as shoulders had larger errors. Average error for ROIs were as follows; CTV: 0.4mm, Brain stem: 1.4mm, Shoulders: 1.6mm, and Normal tissues: 0.7mm. We succeeded to build DEH approach to quantify the DVM uncertainty. Our data sets are available for testing other systems in our web page. Utilizing DEH, users can decide how much systematic error they would accept. DEH and our data can be a tool for an AAPM task group to compose a DIR system QA guideline. This project is partially supported by the Agency for Healthcare Research and Quality (AHRQ) grant 1R18HS017424-01A2. © 2012 American Association of Physicists in Medicine.

  10. Registration of MRI to intraoperative radiographs for target localization in spinal interventions

    NASA Astrophysics Data System (ADS)

    De Silva, T.; Uneri, A.; Ketcha, M. D.; Reaungamornrat, S.; Goerres, J.; Jacobson, M. W.; Vogt, S.; Kleinszig, G.; Khanna, A. J.; Wolinsky, J.-P.; Siewerdsen, J. H.

    2017-01-01

    Decision support to assist in target vertebra localization could provide a useful aid to safe and effective spine surgery. Previous solutions have shown 3D-2D registration of preoperative CT to intraoperative radiographs to reliably annotate vertebral labels for assistance during level localization. We present an algorithm (referred to as MR-LevelCheck) to perform 3D-2D registration based on a preoperative MRI to accommodate the increasingly common clinical scenario in which MRI is used instead of CT for preoperative planning. Straightforward adaptation of gradient/intensity-based methods appropriate to CT-to-radiograph registration is confounded by large mismatch and noncorrespondence in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simple vertebrae segmentation step using vertebra centroids as seed points (automatically defined within existing workflow). Forwards projections are computed using segmented MRI and registered to radiographs via gradient orientation (GO) similarity and the CMA-ES (covariance-matrix-adaptation evolutionary-strategy) optimizer. The method was tested in an IRB-approved study involving 10 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch and large capture range. Robust registration performance was achieved with projection distance error (PDE) (median  ±  IQR)  =  4.3  ±  2.6 mm (median  ±  IQR) and 0% failure rate. Segmentation accuracy for the continuous max-flow method yielded dice coefficient  =  88.1  ±  5.2, accuracy  =  90.6  ±  5.7, RMSE  =  1.8  ±  0.6 mm, and contour affinity ratio (CAR)  =  0.82  ±  0.08. Registration performance was found to be robust for

  11. An Automatic Multi-Target Independent Analysis Framework for Non-Planar Infrared-Visible Registration.

    PubMed

    Sun, Xinglong; Xu, Tingfa; Zhang, Jizhou; Zhao, Zishu; Li, Yuankun

    2017-07-26

    In this paper, we propose a novel automatic multi-target registration framework for non-planar infrared-visible videos. Previous approaches usually analyzed multiple targets together and then estimated a global homography for the whole scene, however, these cannot achieve precise multi-target registration when the scenes are non-planar. Our framework is devoted to solving the problem using feature matching and multi-target tracking. The key idea is to analyze and register each target independently. We present a fast and robust feature matching strategy, where only the features on the corresponding foreground pairs are matched. Besides, new reservoirs based on the Gaussian criterion are created for all targets, and a multi-target tracking method is adopted to determine the relationships between the reservoirs and foreground blobs. With the matches in the corresponding reservoir, the homography of each target is computed according to its moving state. We tested our framework on both public near-planar and non-planar datasets. The results demonstrate that the proposed framework outperforms the state-of-the-art global registration method and the manual global registration matrix in all tested datasets.

  12. Clinical determination of target registration error of an image-guided otologic surgical system using patients with bone-anchored hearing aids

    NASA Astrophysics Data System (ADS)

    Balachandran, Ramya; Labadie, Robert F.; Fitzpatrick, J. Michael

    2007-03-01

    Image guidance in otologic surgery has been thwarted by the need for a non-invasive fiducial system with target registration error (TRE) at the inner ear below 1.5mm. We previously presented a fiducial frame for this purpose that attaches to the upper dentition via patient-specific bite blocks and demonstrated a TRE of 0.73mm (+/-0.23mm) on cadaveric skulls. In that study, TRE measurement depended upon placement of bone-implanted, intracranial target fiducials-clearly impossible to repeat clinically. Using cadaveric specimens, we recently presented a validation method based on an auditory implant system (BAHA System® Cochlear Corp., Denver, CO). That system requires a skull-implanted titanium screw behind the ear upon which a bone-anchored hearing aid (BAHA) is mounted. In our validation, we replace the BAHA with a fiducial marker to permit measurement of TRE. That TRE is then used to estimate TRE at an internal point. While the method can be used to determine accuracy at any point within the head, we focus in this study on the inner ear, in particular the cochlea, and we apply the method to patients (N=5). Physical localizations were performed after varying elapsed times since bite-block fabrication, and TRE at the cochlea was estimated. We found TRE to be 0.97mm at the cochlea within one month and 2.5mm after seven months. Thus, while accuracy deteriorates considerably with delays of seven months or more, if this frame is used within one month of the fabrication of the bite-block, it achieves the goal and in fact exhibits submillimetric accuracy.

  13. MR-CT registration using a Ni-Ti prostate stent in image-guided radiotherapy of prostate cancer.

    PubMed

    Korsager, Anne Sofie; Carl, Jesper; Østergaard, Lasse Riis

    2013-06-01

    In image-guided radiotherapy of prostate cancer defining the clinical target volume often relies on magnetic resonance (MR). The task of transferring the clinical target volume from MR to standard planning computed tomography (CT) is not trivial due to prostate mobility. In this paper, an automatic local registration approach is proposed based on a newly developed removable Ni-Ti prostate stent. The registration uses the voxel similarity measure mutual information in a two-step approach where the pelvic bones are used to establish an initial registration for the local registration. In a phantom study, the accuracy was measured to 0.97 mm and visual inspection showed accurate registration of all 30 data sets. The consistency of the registration was examined where translation and rotation displacements yield a rotation error of 0.41° ± 0.45° and a translation error of 1.67 ± 2.24 mm. This study demonstrated the feasibility for an automatic local MR-CT registration using the prostate stent.

  14. Target size matters: target errors contribute to the generalization of implicit visuomotor learning.

    PubMed

    Reichenthal, Maayan; Avraham, Guy; Karniel, Amir; Shmuelof, Lior

    2016-08-01

    The process of sensorimotor adaptation is considered to be driven by errors. While sensory prediction errors, defined as the difference between the planned and the actual movement of the cursor, drive implicit learning processes, target errors (e.g., the distance of the cursor from the target) are thought to drive explicit learning mechanisms. This distinction was mainly studied in the context of arm reaching tasks where the position and the size of the target were constant. We hypothesize that in a dynamic reaching environment, where subjects have to hit moving targets and the targets' dynamic characteristics affect task success, implicit processes will benefit from target errors as well. We examine the effect of target errors on learning of an unnoticed perturbation during unconstrained reaching movements. Subjects played a Pong game, in which they had to hit a moving ball by moving a paddle controlled by their hand. During the game, the movement of the paddle was gradually rotated with respect to the hand, reaching a final rotation of 25°. Subjects were assigned to one of two groups: The high-target error group played the Pong with a small ball, and the low-target error group played with a big ball. Before and after the Pong game, subjects performed open-loop reaching movements toward static targets with no visual feedback. While both groups adapted to the rotation, the postrotation reaching movements were directionally biased only in the small-ball group. This result provides evidence that implicit adaptation is sensitive to target errors. Copyright © 2016 the American Physiological Society.

  15. Target motion tracking in MRI-guided transrectal robotic prostate biopsy.

    PubMed

    Tadayyon, Hadi; Lasso, Andras; Kaushal, Aradhana; Guion, Peter; Fichtinger, Gabor

    2011-11-01

    MRI-guided prostate needle biopsy requires compensation for organ motion between target planning and needle placement. Two questions are studied and answered in this paper: 1) is rigid registration sufficient in tracking the targets with an error smaller than the clinically significant size of prostate cancer and 2) what is the effect of the number of intraoperative slices on registration accuracy and speed? we propose multislice-to-volume registration algorithms for tracking the biopsy targets within the prostate. Three orthogonal plus additional transverse intraoperative slices are acquired in the approximate center of the prostate and registered with a high-resolution target planning volume. Both rigid and deformable scenarios were implemented. Both simulated and clinical MRI-guided robotic prostate biopsy data were used to assess tracking accuracy. average registration errors in clinical patient data were 2.6 mm for the rigid algorithm and 2.1 mm for the deformable algorithm. rigid tracking appears to be promising. Three tracking slices yield significantly high registration speed with an affordable error.

  16. Improving oncoplastic breast tumor bed localization for radiotherapy planning using image registration algorithms

    NASA Astrophysics Data System (ADS)

    Wodzinski, Marek; Skalski, Andrzej; Ciepiela, Izabela; Kuszewski, Tomasz; Kedzierawski, Piotr; Gajda, Janusz

    2018-02-01

    Knowledge about tumor bed localization and its shape analysis is a crucial factor for preventing irradiation of healthy tissues during supportive radiotherapy and as a result, cancer recurrence. The localization process is especially hard for tumors placed nearby soft tissues, which undergo complex, nonrigid deformations. Among them, breast cancer can be considered as the most representative example. A natural approach to improving tumor bed localization is the use of image registration algorithms. However, this involves two unusual aspects which are not common in typical medical image registration: the real deformation field is discontinuous, and there is no direct correspondence between the cancer and its bed in the source and the target 3D images respectively. The tumor no longer exists during radiotherapy planning. Therefore, a traditional evaluation approach based on known, smooth deformations and target registration error are not directly applicable. In this work, we propose alternative artificial deformations which model the tumor bed creation process. We perform a comprehensive evaluation of the most commonly used deformable registration algorithms: B-Splines free form deformations (B-Splines FFD), different variants of the Demons and TV-L1 optical flow. The evaluation procedure includes quantitative assessment of the dedicated artificial deformations, target registration error calculation, 3D contour propagation and medical experts visual judgment. The results demonstrate that the currently, practically applied image registration (rigid registration and B-Splines FFD) are not able to correctly reconstruct discontinuous deformation fields. We show that the symmetric Demons provide the most accurate soft tissues alignment in terms of the ability to reconstruct the deformation field, target registration error and relative tumor volume change, while B-Splines FFD and TV-L1 optical flow are not an appropriate choice for the breast tumor bed localization problem

  17. A multi-object statistical atlas adaptive for deformable registration errors in anomalous medical image segmentation

    NASA Astrophysics Data System (ADS)

    Botter Martins, Samuel; Vallin Spina, Thiago; Yasuda, Clarissa; Falcão, Alexandre X.

    2017-02-01

    Statistical Atlases have played an important role towards automated medical image segmentation. However, a challenge has been to make the atlas more adaptable to possible errors in deformable registration of anomalous images, given that the body structures of interest for segmentation might present significant differences in shape and texture. Recently, deformable registration errors have been accounted by a method that locally translates the statistical atlas over the test image, after registration, and evaluates candidate objects from a delineation algorithm in order to choose the best one as final segmentation. In this paper, we improve its delineation algorithm and extend the model to be a multi-object statistical atlas, built from control images and adaptable to anomalous images, by incorporating a texture classifier. In order to provide a first proof of concept, we instantiate the new method for segmenting, object-by-object and all objects simultaneously, the left and right brain hemispheres, and the cerebellum, without the brainstem, and evaluate it on MRT1-images of epilepsy patients before and after brain surgery, which removed portions of the temporal lobe. The results show efficiency gain with statistically significant higher accuracy, using the mean Average Symmetric Surface Distance, with respect to the original approach.

  18. An error analysis perspective for patient alignment systems.

    PubMed

    Figl, Michael; Kaar, Marcus; Hoffman, Rainer; Kratochwil, Alfred; Hummel, Johann

    2013-09-01

    This paper analyses the effects of error sources which can be found in patient alignment systems. As an example, an ultrasound (US) repositioning system and its transformation chain are assessed. The findings of this concept can also be applied to any navigation system. In a first step, all error sources were identified and where applicable, corresponding target registration errors were computed. By applying error propagation calculations on these commonly used registration/calibration and tracking errors, we were able to analyse the components of the overall error. Furthermore, we defined a special situation where the whole registration chain reduces to the error caused by the tracking system. Additionally, we used a phantom to evaluate the errors arising from the image-to-image registration procedure, depending on the image metric used. We have also discussed how this analysis can be applied to other positioning systems such as Cone Beam CT-based systems or Brainlab's ExacTrac. The estimates found by our error propagation analysis are in good agreement with the numbers found in the phantom study but significantly smaller than results from patient evaluations. We probably underestimated human influences such as the US scan head positioning by the operator and tissue deformation. Rotational errors of the tracking system can multiply these errors, depending on the relative position of tracker and probe. We were able to analyse the components of the overall error of a typical patient positioning system. We consider this to be a contribution to the optimization of the positioning accuracy for computer guidance systems.

  19. Improvement of registration accuracy in accelerated partial breast irradiation using the point-based rigid-body registration algorithm for patients with implanted fiducial markers

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Inoue, Minoru; Yoshimura, Michio, E-mail: myossy@kuhp.kyoto-u.ac.jp; Sato, Sayaka

    2015-04-15

    Purpose: To investigate image-registration errors when using fiducial markers with a manual method and the point-based rigid-body registration (PRBR) algorithm in accelerated partial breast irradiation (APBI) patients, with accompanying fiducial deviations. Methods: Twenty-two consecutive patients were enrolled in a prospective trial examining 10-fraction APBI. Titanium clips were implanted intraoperatively around the seroma in all patients. For image-registration, the positions of the clips in daily kV x-ray images were matched to those in the planning digitally reconstructed radiographs. Fiducial and gravity registration errors (FREs and GREs, respectively), representing resulting misalignments of the edge and center of the target, respectively, were comparedmore » between the manual and algorithm-based methods. Results: In total, 218 fractions were evaluated. Although the mean FRE/GRE values for the manual and algorithm-based methods were within 3 mm (2.3/1.7 and 1.3/0.4 mm, respectively), the percentages of fractions where FRE/GRE exceeded 3 mm using the manual and algorithm-based methods were 18.8%/7.3% and 0%/0%, respectively. Manual registration resulted in 18.6% of patients with fractions of FRE/GRE exceeding 5 mm. The patients with larger clip deviation had significantly more fractions showing large FRE/GRE using manual registration. Conclusions: For image-registration using fiducial markers in APBI, the manual registration results in more fractions with considerable registration error due to loss of fiducial objectivity resulting from their deviation. The authors recommend the PRBR algorithm as a safe and effective strategy for accurate, image-guided registration and PTV margin reduction.« less

  20. A new markerless patient-to-image registration method using a portable 3D scanner.

    PubMed

    Fan, Yifeng; Jiang, Dongsheng; Wang, Manning; Song, Zhijian

    2014-10-01

    Patient-to-image registration is critical to providing surgeons with reliable guidance information in the application of image-guided neurosurgery systems. The conventional point-matching registration method, which is based on skin markers, requires expensive and time-consuming logistic support. Surface-matching registration with facial surface scans is an alternative method, but the registration accuracy is unstable and the error in the more posterior parts of the head is usually large because the scan range is limited. This study proposes a new surface-matching method using a portable 3D scanner to acquire a point cloud of the entire head to perform the patient-to-image registration. A new method for transforming the scan points from the device space into the patient space without calibration and tracking was developed. Five positioning targets were attached on a reference star, and their coordinates in the patient space were measured prior. During registration, the authors moved the scanner around the head to scan its entire surface as well as the positioning targets, and the scanner generated a unique point cloud in the device space. The coordinates of the positioning targets in the device space were automatically detected by the scanner, and a spatial transformation from the device space to the patient space could be calculated by registering them to their coordinates in the patient space that had been measured prior. A three-step registration algorithm was then used to register the patient space to the image space. The authors evaluated their method on a rigid head phantom and an elastic head phantom to verify its practicality and to calculate the target registration error (TRE) in different regions of the head phantoms. The authors also conducted an experiment with a real patient's data to test the feasibility of their method in the clinical environment. In the phantom experiments, the mean fiducial registration error between the device space and the patient

  1. 3D point cloud analysis of structured light registration in computer-assisted navigation in spinal surgeries

    NASA Astrophysics Data System (ADS)

    Gupta, Shaurya; Guha, Daipayan; Jakubovic, Raphael; Yang, Victor X. D.

    2017-02-01

    Computer-assisted navigation is used by surgeons in spine procedures to guide pedicle screws to improve placement accuracy and in some cases, to better visualize patient's underlying anatomy. Intraoperative registration is performed to establish a correlation between patient's anatomy and the pre/intra-operative image. Current algorithms rely on seeding points obtained directly from the exposed spinal surface to achieve clinically acceptable registration accuracy. Registration of these three dimensional surface point-clouds are prone to various systematic errors. The goal of this study was to evaluate the robustness of surgical navigation systems by looking at the relationship between the optical density of an acquired 3D point-cloud and the corresponding surgical navigation error. A retrospective review of a total of 48 registrations performed using an experimental structured light navigation system developed within our lab was conducted. For each registration, the number of points in the acquired point cloud was evaluated relative to whether the registration was acceptable, the corresponding system reported error and target registration error. It was demonstrated that the number of points in the point cloud neither correlates with the acceptance/rejection of a registration or the system reported error. However, a negative correlation was observed between the number of the points in the point-cloud and the corresponding sagittal angular error. Thus, system reported total registration points and accuracy are insufficient to gauge the accuracy of a navigation system and the operating surgeon must verify and validate registration based on anatomical landmarks prior to commencing surgery.

  2. Error analysis on squareness of multi-sensor integrated CMM for the multistep registration method

    NASA Astrophysics Data System (ADS)

    Zhao, Yan; Wang, Yiwen; Ye, Xiuling; Wang, Zhong; Fu, Luhua

    2018-01-01

    The multistep registration(MSR) method in [1] is to register two different classes of sensors deployed on z-arm of CMM(coordinate measuring machine): a video camera and a tactile probe sensor. In general, it is difficult to obtain a very precise registration result with a single common standard, instead, this method is achieved by measuring two different standards with a constant distance between them two which are fixed on a steel plate. Although many factors have been considered such as the measuring ability of sensors, the uncertainty of the machine and the number of data pairs, there is no exact analysis on the squareness between the x-axis and the y-axis on the xy plane. For this sake, error analysis on the squareness of multi-sensor integrated CMM for the multistep registration method will be made to examine the validation of the MSR method. Synthetic experiments on the squareness on the xy plane for the simplified MSR with an inclination rotation are simulated, which will lead to a regular result. Experiments have been carried out with the multi-standard device designed also in [1], meanwhile, inspections with the help of a laser interferometer on the xy plane have been carried out. The final results are conformed to the simulations, and the squareness errors of the MSR method are also similar to the results of interferometer. In other word, the MSR can also adopted/utilized to verify the squareness of a CMM.

  3. Direct endoscopic video registration for sinus surgery

    NASA Astrophysics Data System (ADS)

    Mirota, Daniel; Taylor, Russell H.; Ishii, Masaru; Hager, Gregory D.

    2009-02-01

    Advances in computer vision have made possible robust 3D reconstruction of monocular endoscopic video. These reconstructions accurately represent the visible anatomy and, once registered to pre-operative CT data, enable a navigation system to track directly through video eliminating the need for an external tracking system. Video registration provides the means for a direct interface between an endoscope and a navigation system and allows a shorter chain of rigid-body transformations to be used to solve the patient/navigation-system registration. To solve this registration step we propose a new 3D-3D registration algorithm based on Trimmed Iterative Closest Point (TrICP)1 and the z-buffer algorithm.2 The algorithm takes as input a 3D point cloud of relative scale with the origin at the camera center, an isosurface from the CT, and an initial guess of the scale and location. Our algorithm utilizes only the visible polygons of the isosurface from the current camera location during each iteration to minimize the search area of the target region and robustly reject outliers of the reconstruction. We present example registrations in the sinus passage applicable to both sinus surgery and transnasal surgery. To evaluate our algorithm's performance we compare it to registration via Optotrak and present closest distance point to surface error. We show our algorithm has a mean closest distance error of .2268mm.

  4. Automatic image registration performance for two different CBCT systems; variation with imaging dose

    NASA Astrophysics Data System (ADS)

    Barber, J.; Sykes, J. R.; Holloway, L.; Thwaites, D. I.

    2014-03-01

    The performance of an automatic image registration algorithm was compared on image sets collected with two commercial CBCT systems, and the relationship with imaging dose was explored. CBCT images of a CIRS Virtually Human Male Pelvis phantom (VHMP) were collected on Varian TrueBeam/OBI and Elekta Synergy/XVI linear accelerators, across a range of mAs settings. Each CBCT image was registered 100 times, with random initial offsets introduced. Image registration was performed using the grey value correlation ratio algorithm in the Elekta XVI software, to a mask of the prostate volume with 5 mm expansion. Residual registration errors were calculated after correcting for the initial introduced phantom set-up error. Registration performance with the OBI images was similar to that of XVI. There was a clear dependence on imaging dose for the XVI images with residual errors increasing below 4mGy. It was not possible to acquire images with doses lower than ~5mGy with the OBI system and no evidence of reduced performance was observed at this dose. Registration failures (maximum target registration error > 3.6 mm on the surface of a 30mm sphere) occurred in 5% to 9% of registrations except for the lowest dose XVI scan (31%). The uncertainty in automatic image registration with both OBI and XVI images was found to be adequate for clinical use within a normal range of acquisition settings.

  5. Registration of organs with sliding interfaces and changing topologies

    NASA Astrophysics Data System (ADS)

    Berendsen, Floris F.; Kotte, Alexis N. T. J.; Viergever, Max A.; Pluim, Josien P. W.

    2014-03-01

    Smoothness and continuity assumptions on the deformation field in deformable image registration do not hold for applications where the imaged objects have sliding interfaces. Recent extensions to deformable image registration that accommodate for sliding motion of organs are limited to sliding motion along approximately planar surfaces or cannot model sliding that changes the topological configuration in case of multiple organs. We propose a new extension to free-form image registration that is not limited in this way. Our method uses a transformation model that consists of uniform B-spline transformations for each organ region separately, which is based on segmentation of one image. Since this model can create overlapping regions or gaps between regions, we introduce a penalty term that minimizes this undesired effect. The penalty term acts on the surfaces of the organ regions and is optimized simultaneously with the image similarity. To evaluate our method registrations were performed on publicly available inhale-exhale CT scans for which performances of other methods are known. Target registration errors are computed on dense landmark sets that are available with these datasets. On these data our method outperforms the other methods in terms of target registration error and, where applicable, also in terms of overlap and gap volumes. The approximation of the other methods of sliding motion along planar surfaces is reasonably well suited for the motion present in the lung data. The ability of our method to handle sliding along curved boundaries and for changing region topology configurations was demonstrated on synthetic images.

  6. Registration and fusion quantification of augmented reality based nasal endoscopic surgery.

    PubMed

    Chu, Yakui; Yang, Jian; Ma, Shaodong; Ai, Danni; Li, Wenjie; Song, Hong; Li, Liang; Chen, Duanduan; Chen, Lei; Wang, Yongtian

    2017-12-01

    This paper quantifies the registration and fusion display errors of augmented reality-based nasal endoscopic surgery (ARNES). We comparatively investigated the spatial calibration process for front-end endoscopy and redefined the accuracy level of a calibrated endoscope by using a calibration tool with improved structural reliability. We also studied how registration accuracy was combined with the number and distribution of the deployed fiducial points (FPs) for positioning and the measured registration time. A physically integrated ARNES prototype was customarily configured for performance evaluation in skull base tumor resection surgery with an innovative approach of dynamic endoscopic vision expansion. As advised by surgical experts in otolaryngology, we proposed a hierarchical rendering scheme to properly adapt the fused images with the required visual sensation. By constraining the rendered sight in a known depth and radius, the visual focus of the surgeon can be induced only on the anticipated critical anatomies and vessel structures to avoid misguidance. Furthermore, error analysis was conducted to examine the feasibility of hybrid optical tracking based on point cloud, which was proposed in our previous work as an in-surgery registration solution. Measured results indicated that the error of target registration for ARNES can be reduced to 0.77 ± 0.07 mm. For initial registration, our results suggest that a trade-off for a new minimal time of registration can be reached when the distribution of five FPs is considered. For in-surgery registration, our findings reveal that the intrinsic registration error is a major cause of performance loss. Rigid model and cadaver experiments confirmed that the scenic integration and display fluency of ARNES are smooth, as demonstrated by three clinical trials that surpassed practicality. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Surface driven biomechanical breast image registration

    NASA Astrophysics Data System (ADS)

    Eiben, Björn; Vavourakis, Vasileios; Hipwell, John H.; Kabus, Sven; Lorenz, Cristian; Buelow, Thomas; Williams, Norman R.; Keshtgar, M.; Hawkes, David J.

    2016-03-01

    Biomechanical modelling enables large deformation simulations of breast tissues under different loading conditions to be performed. Such simulations can be utilised to transform prone Magnetic Resonance (MR) images into a different patient position, such as upright or supine. We present a novel integration of biomechanical modelling with a surface registration algorithm which optimises the unknown material parameters of a biomechanical model and performs a subsequent regularised surface alignment. This allows deformations induced by effects other than gravity, such as those due to contact of the breast and MR coil, to be reversed. Correction displacements are applied to the biomechanical model enabling transformation of the original pre-surgical images to the corresponding target position. The algorithm is evaluated for the prone-to-supine case using prone MR images and the skin outline of supine Computed Tomography (CT) scans for three patients. A mean target registration error (TRE) of 10:9 mm for internal structures is achieved. For the prone-to-upright scenario, an optical 3D surface scan of one patient is used as a registration target and the nipple distances after alignment between the transformed MRI and the surface are 10:1 mm and 6:3 mm respectively.

  8. An automatic markerless registration method for neurosurgical robotics based on an optical camera.

    PubMed

    Meng, Fanle; Zhai, Fangwen; Zeng, Bowei; Ding, Hui; Wang, Guangzhi

    2018-02-01

    Current markerless registration methods for neurosurgical robotics use the facial surface to match the robot space with the image space, and acquisition of the facial surface usually requires manual interaction and constrains the patient to a supine position. To overcome these drawbacks, we propose a registration method that is automatic and does not constrain patient position. An optical camera attached to the robot end effector captures images around the patient's head from multiple views. Then, high coverage of the head surface is reconstructed from the images through multi-view stereo vision. Since the acquired head surface point cloud contains color information, a specific mark that is manually drawn on the patient's head prior to the capture procedure can be extracted to automatically accomplish coarse registration rather than using facial anatomic landmarks. Then, fine registration is achieved by registering the high coverage of the head surface without relying solely on the facial region, thus eliminating patient position constraints. The head surface was acquired by the camera with a good repeatability accuracy. The average target registration error of 8 different patient positions measured with targets inside a head phantom was [Formula: see text], while the mean surface registration error was [Formula: see text]. The method proposed in this paper achieves automatic markerless registration in multiple patient positions and guarantees registration accuracy inside the head. This method provides a new approach for establishing the spatial relationship between the image space and the robot space.

  9. Real-time registration of 3D to 2D ultrasound images for image-guided prostate biopsy.

    PubMed

    Gillies, Derek J; Gardi, Lori; De Silva, Tharindu; Zhao, Shuang-Ren; Fenster, Aaron

    2017-09-01

    During image-guided prostate biopsy, needles are targeted at tissues that are suspicious of cancer to obtain specimen for histological examination. Unfortunately, patient motion causes targeting errors when using an MR-transrectal ultrasound (TRUS) fusion approach to augment the conventional biopsy procedure. This study aims to develop an automatic motion correction algorithm approaching the frame rate of an ultrasound system to be used in fusion-based prostate biopsy systems. Two modes of operation have been investigated for the clinical implementation of the algorithm: motion compensation using a single user initiated correction performed prior to biopsy, and real-time continuous motion compensation performed automatically as a background process. Retrospective 2D and 3D TRUS patient images acquired prior to biopsy gun firing were registered using an intensity-based algorithm utilizing normalized cross-correlation and Powell's method for optimization. 2D and 3D images were downsampled and cropped to estimate the optimal amount of image information that would perform registrations quickly and accurately. The optimal search order during optimization was also analyzed to avoid local optima in the search space. Error in the algorithm was computed using target registration errors (TREs) from manually identified homologous fiducials in a clinical patient dataset. The algorithm was evaluated for real-time performance using the two different modes of clinical implementations by way of user initiated and continuous motion compensation methods on a tissue mimicking prostate phantom. After implementation in a TRUS-guided system with an image downsampling factor of 4, the proposed approach resulted in a mean ± std TRE and computation time of 1.6 ± 0.6 mm and 57 ± 20 ms respectively. The user initiated mode performed registrations with in-plane, out-of-plane, and roll motions computation times of 108 ± 38 ms, 60 ± 23 ms, and 89 ± 27 ms, respectively, and corresponding

  10. Robust Nonrigid Multimodal Image Registration using Local Frequency Maps*

    PubMed Central

    Jian, Bing; Vemuri, Baba C.; Marroquin, José L.

    2008-01-01

    Automatic multi-modal image registration is central to numerous tasks in medical imaging today and has a vast range of applications e.g., image guidance, atlas construction, etc. In this paper, we present a novel multi-modal 3D non-rigid registration algorithm where in 3D images to be registered are represented by their corresponding local frequency maps efficiently computed using the Riesz transform as opposed to the popularly used Gabor filters. The non-rigid registration between these local frequency maps is formulated in a statistically robust framework involving the minimization of the integral squared error a.k.a. L2E (L2 error). This error is expressed as the squared difference between the true density of the residual (which is the squared difference between the non-rigidly transformed reference and the target local frequency representations) and a Gaussian or mixture of Gaussians density approximation of the same. The non-rigid transformation is expressed in a B-spline basis to achieve the desired smoothness in the transformation as well as computational efficiency. The key contributions of this work are (i) the use of Riesz transform to achieve better efficiency in computing the local frequency representation in comparison to Gabor filter-based approaches, (ii) new mathematical model for local-frequency based non-rigid registration, (iii) analytic computation of the gradient of the robust non-rigid registration cost function to achieve efficient and accurate registration. The proposed non-rigid L2E-based registration is a significant extension of research reported in literature to date. We present experimental results for registering several real data sets with synthetic and real non-rigid misalignments. PMID:17354721

  11. Sulcal set optimization for cortical surface registration.

    PubMed

    Joshi, Anand A; Pantazis, Dimitrios; Li, Quanzheng; Damasio, Hanna; Shattuck, David W; Toga, Arthur W; Leahy, Richard M

    2010-04-15

    Flat mapping based cortical surface registration constrained by manually traced sulcal curves has been widely used for inter subject comparisons of neuroanatomical data. Even for an experienced neuroanatomist, manual sulcal tracing can be quite time consuming, with the cost increasing with the number of sulcal curves used for registration. We present a method for estimation of an optimal subset of size N(C) from N possible candidate sulcal curves that minimizes a mean squared error metric over all combinations of N(C) curves. The resulting procedure allows us to estimate a subset with a reduced number of curves to be traced as part of the registration procedure leading to optimal use of manual labeling effort for registration. To minimize the error metric we analyze the correlation structure of the errors in the sulcal curves by modeling them as a multivariate Gaussian distribution. For a given subset of sulci used as constraints in surface registration, the proposed model estimates registration error based on the correlation structure of the sulcal errors. The optimal subset of constraint curves consists of the N(C) sulci that jointly minimize the estimated error variance for the subset of unconstrained curves conditioned on the N(C) constraint curves. The optimal subsets of sulci are presented and the estimated and actual registration errors for these subsets are computed. Copyright 2009 Elsevier Inc. All rights reserved.

  12. A bronchoscopic navigation system using bronchoscope center calibration for accurate registration of electromagnetic tracker and CT volume without markers.

    PubMed

    Luo, Xiongbiao

    2014-06-01

    Various bronchoscopic navigation systems are developed for diagnosis, staging, and treatment of lung and bronchus cancers. To construct electromagnetically navigated bronchoscopy systems, registration of preoperative images and an electromagnetic tracker must be performed. This paper proposes a new marker-free registration method, which uses the centerlines of the bronchial tree and the center of a bronchoscope tip where an electromagnetic sensor is attached, to align preoperative images and electromagnetic tracker systems. The chest computed tomography (CT) volume (preoperative images) was segmented to extract the bronchial centerlines. An electromagnetic sensor was fixed at the bronchoscope tip surface. A model was designed and printed using a 3D printer to calibrate the relationship between the fixed sensor and the bronchoscope tip center. For each sensor measurement that includes sensor position and orientation information, its corresponding bronchoscope tip center position was calculated. By minimizing the distance between each bronchoscope tip center position and the bronchial centerlines, the spatial alignment of the electromagnetic tracker system and the CT volume was determined. After obtaining the spatial alignment, an electromagnetic navigation bronchoscopy system was established to real-timely track or locate a bronchoscope inside the bronchial tree during bronchoscopic examinations. The electromagnetic navigation bronchoscopy system was validated on a dynamic bronchial phantom that can simulate respiratory motion with a breath rate range of 0-10 min(-1). The fiducial and target registration errors of this navigation system were evaluated. The average fiducial registration error was reduced from 8.7 to 6.6 mm. The average target registration error, which indicates all tracked or navigated bronchoscope position accuracy, was much reduced from 6.8 to 4.5 mm compared to previous registration methods. An electromagnetically navigated bronchoscopy system was

  13. Volumetric Image Guidance Using Carina vs Spine as Registration Landmarks for Conventionally Fractionated Lung Radiotherapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lavoie, Caroline; Higgins, Jane; Bissonnette, Jean-Pierre

    2012-12-01

    Purpose: To compare the relative accuracy of 2 image guided radiation therapy methods using carina vs spine as landmarks and then to identify which landmark is superior relative to tumor coverage. Methods and Materials: For 98 lung patients, 2596 daily image-guidance cone-beam computed tomography scans were analyzed. Tattoos were used for initial patient alignment; then, spine and carina registrations were performed independently. A separate analysis assessed the adequacy of gross tumor volume, internal target volume, and planning target volume coverage on cone-beam computed tomography using the initial, middle, and final fractions of radiation therapy. Coverage was recorded for primary tumormore » (T), nodes (N), and combined target (T+N). Three scenarios were compared: tattoos alignment, spine registration, and carina registration. Results: Spine and carina registrations identified setup errors {>=}5 mm in 35% and 46% of fractions, respectively. The mean vector difference between spine and carina matching had a magnitude of 3.3 mm. Spine and carina improved combined target coverage, compared with tattoos, in 50% and 34% (spine) to 54% and 46% (carina) of the first and final fractions, respectively. Carina matching showed greater combined target coverage in 17% and 23% of fractions for the first and final fractions, respectively; with spine matching, this was only observed in 4% (first) and 6% (final) of fractions. Carina matching provided superior nodes coverage at the end of radiation compared with spine matching (P=.0006), without compromising primary tumor coverage. Conclusion: Frequent patient setup errors occur in locally advanced lung cancer patients. Spine and carina registrations improved combined target coverage throughout the treatment course, but carina matching provided superior combined target coverage.« less

  14. A Demons algorithm for image registration with locally adaptive regularization.

    PubMed

    Cahill, Nathan D; Noble, J Alison; Hawkes, David J

    2009-01-01

    Thirion's Demons is a popular algorithm for nonrigid image registration because of its linear computational complexity and ease of implementation. It approximately solves the diffusion registration problem by successively estimating force vectors that drive the deformation toward alignment and smoothing the force vectors by Gaussian convolution. In this article, we show how the Demons algorithm can be generalized to allow image-driven locally adaptive regularization in a manner that preserves both the linear complexity and ease of implementation of the original Demons algorithm. We show that the proposed algorithm exhibits lower target registration error and requires less computational effort than the original Demons algorithm on the registration of serial chest CT scans of patients with lung nodules.

  15. Improving registration accuracy.

    PubMed

    Murphy, J Patrick; Shorrosh, Paul

    2008-04-01

    A registration quality assurance initiative--whether manual or automated--can result in benefits such as: Cleaner claims, Reduced cost to collect, Enhanced revenue, Decreased registration, error rates, Improved staff morale, Fewer customer complaints

  16. Registration of PET and CT images based on multiresolution gradient of mutual information demons algorithm for positioning esophageal cancer patients.

    PubMed

    Jin, Shuo; Li, Dengwang; Wang, Hongjun; Yin, Yong

    2013-01-07

    Accurate registration of 18F-FDG PET (positron emission tomography) and CT (computed tomography) images has important clinical significance in radiation oncology. PET and CT images are acquired from (18)F-FDG PET/CT scanner, but the two acquisition processes are separate and take a long time. As a result, there are position errors in global and deformable errors in local caused by respiratory movement or organ peristalsis. The purpose of this work was to implement and validate a deformable CT to PET image registration method in esophageal cancer to eventually facilitate accurate positioning the tumor target on CT, and improve the accuracy of radiation therapy. Global registration was firstly utilized to preprocess position errors between PET and CT images, achieving the purpose of aligning these two images on the whole. Demons algorithm, based on optical flow field, has the features of fast process speed and high accuracy, and the gradient of mutual information-based demons (GMI demons) algorithm adds an additional external force based on the gradient of mutual information (GMI) between two images, which is suitable for multimodality images registration. In this paper, GMI demons algorithm was used to achieve local deformable registration of PET and CT images, which can effectively reduce errors between internal organs. In addition, to speed up the registration process, maintain its robustness, and avoid the local extremum, multiresolution image pyramid structure was used before deformable registration. By quantitatively and qualitatively analyzing cases with esophageal cancer, the registration scheme proposed in this paper can improve registration accuracy and speed, which is helpful for precisely positioning tumor target and developing the radiation treatment planning in clinical radiation therapy application.

  17. Applying the algorithm "assessing quality using image registration circuits" (AQUIRC) to multi-atlas segmentation

    NASA Astrophysics Data System (ADS)

    Datteri, Ryan; Asman, Andrew J.; Landman, Bennett A.; Dawant, Benoit M.

    2014-03-01

    Multi-atlas registration-based segmentation is a popular technique in the medical imaging community, used to transform anatomical and functional information from a set of atlases onto a new patient that lacks this information. The accuracy of the projected information on the target image is dependent on the quality of the registrations between the atlas images and the target image. Recently, we have developed a technique called AQUIRC that aims at estimating the error of a non-rigid registration at the local level and was shown to correlate to error in a simulated case. Herein, we extend upon this work by applying AQUIRC to atlas selection at the local level across multiple structures in cases in which non-rigid registration is difficult. AQUIRC is applied to 6 structures, the brainstem, optic chiasm, left and right optic nerves, and the left and right eyes. We compare the results of AQUIRC to that of popular techniques, including Majority Vote, STAPLE, Non-Local STAPLE, and Locally-Weighted Vote. We show that AQUIRC can be used as a method to combine multiple segmentations and increase the accuracy of the projected information on a target image, and is comparable to cutting edge methods in the multi-atlas segmentation field.

  18. A spline-based non-linear diffeomorphism for multimodal prostate registration.

    PubMed

    Mitra, Jhimli; Kato, Zoltan; Martí, Robert; Oliver, Arnau; Lladó, Xavier; Sidibé, Désiré; Ghose, Soumya; Vilanova, Joan C; Comet, Josep; Meriaudeau, Fabrice

    2012-08-01

    This paper presents a novel method for non-rigid registration of transrectal ultrasound and magnetic resonance prostate images based on a non-linear regularized framework of point correspondences obtained from a statistical measure of shape-contexts. The segmented prostate shapes are represented by shape-contexts and the Bhattacharyya distance between the shape representations is used to find the point correspondences between the 2D fixed and moving images. The registration method involves parametric estimation of the non-linear diffeomorphism between the multimodal images and has its basis in solving a set of non-linear equations of thin-plate splines. The solution is obtained as the least-squares solution of an over-determined system of non-linear equations constructed by integrating a set of non-linear functions over the fixed and moving images. However, this may not result in clinically acceptable transformations of the anatomical targets. Therefore, the regularized bending energy of the thin-plate splines along with the localization error of established correspondences should be included in the system of equations. The registration accuracies of the proposed method are evaluated in 20 pairs of prostate mid-gland ultrasound and magnetic resonance images. The results obtained in terms of Dice similarity coefficient show an average of 0.980±0.004, average 95% Hausdorff distance of 1.63±0.48 mm and mean target registration and target localization errors of 1.60±1.17 mm and 0.15±0.12 mm respectively. Copyright © 2012 Elsevier B.V. All rights reserved.

  19. Background suppression of infrared small target image based on inter-frame registration

    NASA Astrophysics Data System (ADS)

    Ye, Xiubo; Xue, Bindang

    2018-04-01

    We propose a multi-frame background suppression method for remote infrared small target detection. Inter-frame information is necessary when the heavy background clutters make it difficult to distinguish real targets and false alarms. A registration procedure based on points matching in image patches is used to compensate the local deformation of background. Then the target can be separated by background subtraction. Experiments show our method serves as an effective preliminary of target detection.

  20. SU-E-J-29: Automatic Image Registration Performance of Three IGRT Systems for Prostate Radiotherapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Barber, J; University of Sydney, Sydney, NSW; Sykes, J

    Purpose: To compare the performance of an automatic image registration algorithm on image sets collected on three commercial image guidance systems, and explore its relationship with imaging parameters such as dose and sharpness. Methods: Images of a CIRS Virtually Human Male Pelvis phantom (VHMP) were collected on the CBCT systems of Varian TrueBeam/OBI and Elekta Synergy/XVI linear accelerators, across a range of mAs settings; and MVCT on a Tomotherapy Hi-ART accelerator with a range of pitch. Using the 6D correlation ratio algorithm of XVI, each image was registered to a mask of the prostate volume with a 5 mm expansion.more » Registrations were repeated 100 times, with random initial offsets introduced to simulate daily matching. Residual registration errors were calculated by correcting for the initial phantom set-up error. Automatic registration was also repeated after reconstructing images with different sharpness filters. Results: All three systems showed good registration performance, with residual translations <0.5mm (1σ) for typical clinical dose and reconstruction settings. Residual rotational error had larger range, with 0.8°, 1.2° and 1.9° for 1σ in XVI, OBI and Tomotherapy respectively. The registration accuracy of XVI images showed a strong dependence on imaging dose, particularly below 4mGy. No evidence of reduced performance was observed at the lowest dose settings for OBI and Tomotherapy, but these were above 4mGy. Registration failures (maximum target registration error > 3.6 mm on the surface of a 30mm sphere) occurred in 5% to 10% of registrations. Changing the sharpness of image reconstruction had no significant effect on registration performance. Conclusions: Using the present automatic image registration algorithm, all IGRT systems tested provided satisfactory registrations for clinical use, within a normal range of acquisition settings.« less

  1. Image Registration: A Necessary Evil

    NASA Technical Reports Server (NTRS)

    Bell, James; McLachlan, Blair; Hermstad, Dexter; Trosin, Jeff; George, Michael W. (Technical Monitor)

    1995-01-01

    Registration of test and reference images is a key component of nearly all PSP data reduction techniques. This is done to ensure that a test image pixel viewing a particular point on the model is ratioed by the reference image pixel which views the same point. Typically registration is needed to account for model motion due to differing airloads when the wind-off and wind-on images are taken. Registration is also necessary when two cameras are used for simultaneous acquisition of data from a dual-frequency paint. This presentation will discuss the advantages and disadvantages of several different image registration techniques. In order to do so, it is necessary to propose both an accuracy requirement for image registration and a means for measuring the accuracy of a particular technique. High contrast regions in the unregistered images are most sensitive to registration errors, and it is proposed that these regions be used to establish the error limits for registration. Once this is done, the actual registration error can be determined by locating corresponding points on the test and reference images, and determining how well a particular registration technique matches them. An example of this procedure is shown for three transforms used to register images of a semispan model. Thirty control points were located on the model. A subset of the points were used to determine the coefficients of each registration transform, and the error with which each transform aligned the remaining points was determined. The results indicate the general superiority of a third-order polynomial over other candidate transforms, as well as showing how registration accuracy varies with number of control points. Finally, it is proposed that image registration may eventually be done away with completely. As more accurate image resection techniques and more detailed model surface grids become available, it will be possible to map raw image data onto the model surface accurately. Intensity

  2. Registration of PET and CT images based on multiresolution gradient of mutual information demons algorithm for positioning esophageal cancer patients

    PubMed Central

    Jin, Shuo; Li, Dengwang; Yin, Yong

    2013-01-01

    Accurate registration of  18F−FDG PET (positron emission tomography) and CT (computed tomography) images has important clinical significance in radiation oncology. PET and CT images are acquired from  18F−FDG PET/CT scanner, but the two acquisition processes are separate and take a long time. As a result, there are position errors in global and deformable errors in local caused by respiratory movement or organ peristalsis. The purpose of this work was to implement and validate a deformable CT to PET image registration method in esophageal cancer to eventually facilitate accurate positioning the tumor target on CT, and improve the accuracy of radiation therapy. Global registration was firstly utilized to preprocess position errors between PET and CT images, achieving the purpose of aligning these two images on the whole. Demons algorithm, based on optical flow field, has the features of fast process speed and high accuracy, and the gradient of mutual information‐based demons (GMI demons) algorithm adds an additional external force based on the gradient of mutual information (GMI) between two images, which is suitable for multimodality images registration. In this paper, GMI demons algorithm was used to achieve local deformable registration of PET and CT images, which can effectively reduce errors between internal organs. In addition, to speed up the registration process, maintain its robustness, and avoid the local extremum, multiresolution image pyramid structure was used before deformable registration. By quantitatively and qualitatively analyzing cases with esophageal cancer, the registration scheme proposed in this paper can improve registration accuracy and speed, which is helpful for precisely positioning tumor target and developing the radiation treatment planning in clinical radiation therapy application. PACS numbers: 87.57.nj, 87.57.Q‐, 87.57.uk PMID:23318381

  3. Robust video super-resolution with registration efficiency adaptation

    NASA Astrophysics Data System (ADS)

    Zhang, Xinfeng; Xiong, Ruiqin; Ma, Siwei; Zhang, Li; Gao, Wen

    2010-07-01

    Super-Resolution (SR) is a technique to construct a high-resolution (HR) frame by fusing a group of low-resolution (LR) frames describing the same scene. The effectiveness of the conventional super-resolution techniques, when applied on video sequences, strongly relies on the efficiency of motion alignment achieved by image registration. Unfortunately, such efficiency is limited by the motion complexity in the video and the capability of adopted motion model. In image regions with severe registration errors, annoying artifacts usually appear in the produced super-resolution video. This paper proposes a robust video super-resolution technique that adapts itself to the spatially-varying registration efficiency. The reliability of each reference pixel is measured by the corresponding registration error and incorporated into the optimization objective function of SR reconstruction. This makes the SR reconstruction highly immune to the registration errors, as outliers with higher registration errors are assigned lower weights in the objective function. In particular, we carefully design a mechanism to assign weights according to registration errors. The proposed superresolution scheme has been tested with various video sequences and experimental results clearly demonstrate the effectiveness of the proposed method.

  4. DIRBoost-an algorithm for boosting deformable image registration: application to lung CT intra-subject registration.

    PubMed

    Muenzing, Sascha E A; van Ginneken, Bram; Viergever, Max A; Pluim, Josien P W

    2014-04-01

    We introduce a boosting algorithm to improve on existing methods for deformable image registration (DIR). The proposed DIRBoost algorithm is inspired by the theory on hypothesis boosting, well known in the field of machine learning. DIRBoost utilizes a method for automatic registration error detection to obtain estimates of local registration quality. All areas detected as erroneously registered are subjected to boosting, i.e. undergo iterative registrations by employing boosting masks on both the fixed and moving image. We validated the DIRBoost algorithm on three different DIR methods (ANTS gSyn, NiftyReg, and DROP) on three independent reference datasets of pulmonary image scan pairs. DIRBoost reduced registration errors significantly and consistently on all reference datasets for each DIR algorithm, yielding an improvement of the registration accuracy by 5-34% depending on the dataset and the registration algorithm employed. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. WE-AB-BRA-04: Evaluation of the Tumor Registration Error in Biopsy Procedures Performed Under Real Time PET/CT Guidance

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Fanchon, L; INSERM U1101, Brest; Apte, A

    2015-06-15

    Purpose: PET/CT guidance is used for biopsies of metabolically active lesions, which are not well seen on CT alone or to target the metabolically active tissue in tumor ablations. It has also been shown that PET/CT guided biopsies provide an opportunity to verify the location of the lesion border at the place of needle insertion. However the error in needle placement with respect to the metabolically active region may be affected by motion between the PET/CT scan performed at the start of the procedure and the CT scan performed with the needle in place and this error has not beenmore » previously quantified. Methods: Specimens from 31 PET/CT guided biopsies were investigated and correlated to the intraoperative PET scan under an IRB approved HIPAA compliant protocol. For 4 of the cases in which larger motion was suspected a second PET scan was obtained with the needle in place. The CT and the PET images obtained before and after the needle insertion were used to calculate the displacement of the voxels along the needle path. CTpost was registered to CTpre using a free form deformable registration and then fused with PETpre. The shifts between the PET image contours (42% of SUVmax) for PETpre and PETpost were obtained at the needle position. Results: For these extreme cases the displacement of the CT voxels along the needle path ranged from 2.9 to 8 mm with a mean of 5 mm. The shift of the PET image segmentation contours (42% of SUVmax) at the needle position ranged from 2.3 to 7 mm between the two scans. Conclusion: Evaluation of the mis-registration between the CT with the needle in place and the pre-biopsy PET can be obtained using deformable registration of the respective CT scans and can be used to indicate the need of a second PET in real-time. This work is supported in part by a grant from Biospace Lab, S.A.« less

  6. A bronchoscopic navigation system using bronchoscope center calibration for accurate registration of electromagnetic tracker and CT volume without markers

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Luo, Xiongbiao, E-mail: xiongbiao.luo@gmail.com

    2014-06-15

    Purpose: Various bronchoscopic navigation systems are developed for diagnosis, staging, and treatment of lung and bronchus cancers. To construct electromagnetically navigated bronchoscopy systems, registration of preoperative images and an electromagnetic tracker must be performed. This paper proposes a new marker-free registration method, which uses the centerlines of the bronchial tree and the center of a bronchoscope tip where an electromagnetic sensor is attached, to align preoperative images and electromagnetic tracker systems. Methods: The chest computed tomography (CT) volume (preoperative images) was segmented to extract the bronchial centerlines. An electromagnetic sensor was fixed at the bronchoscope tip surface. A model wasmore » designed and printed using a 3D printer to calibrate the relationship between the fixed sensor and the bronchoscope tip center. For each sensor measurement that includes sensor position and orientation information, its corresponding bronchoscope tip center position was calculated. By minimizing the distance between each bronchoscope tip center position and the bronchial centerlines, the spatial alignment of the electromagnetic tracker system and the CT volume was determined. After obtaining the spatial alignment, an electromagnetic navigation bronchoscopy system was established to real-timely track or locate a bronchoscope inside the bronchial tree during bronchoscopic examinations. Results: The electromagnetic navigation bronchoscopy system was validated on a dynamic bronchial phantom that can simulate respiratory motion with a breath rate range of 0–10 min{sup −1}. The fiducial and target registration errors of this navigation system were evaluated. The average fiducial registration error was reduced from 8.7 to 6.6 mm. The average target registration error, which indicates all tracked or navigated bronchoscope position accuracy, was much reduced from 6.8 to 4.5 mm compared to previous registration methods. Conclusions

  7. Complex background suppression using global-local registration strategy for the detection of small-moving target on moving platform

    NASA Astrophysics Data System (ADS)

    Zou, Tianhao; Zuo, Zhengrong

    2018-02-01

    Target detection is a very important and basic problem of computer vision and image processing. The most often case we meet in real world is a detection task for a moving-small target on moving platform. The commonly used methods, such as Registration-based suppression, can hardly achieve a desired result. To crack this hard nut, we introduce a Global-local registration based suppression method. Differ from the traditional ones, the proposed Global-local Registration Strategy consider both the global consistency and the local diversity of the background, obtain a better performance than normal background suppression methods. In this paper, we first discussed the features about the small-moving target detection on unstable platform. Then we introduced a new strategy and conducted an experiment to confirm its noisy stability. In the end, we confirmed the background suppression method based on global-local registration strategy has a better perform in moving target detection on moving platform.

  8. Open-source image registration for MRI-TRUS fusion-guided prostate interventions.

    PubMed

    Fedorov, Andriy; Khallaghi, Siavash; Sánchez, C Antonio; Lasso, Andras; Fels, Sidney; Tuncali, Kemal; Sugar, Emily Neubauer; Kapur, Tina; Zhang, Chenxi; Wells, William; Nguyen, Paul L; Abolmaesumi, Purang; Tempany, Clare

    2015-06-01

    We propose two software tools for non-rigid registration of MRI and transrectal ultrasound (TRUS) images of the prostate. Our ultimate goal is to develop an open-source solution to support MRI-TRUS fusion image guidance of prostate interventions, such as targeted biopsy for prostate cancer detection and focal therapy. It is widely hypothesized that image registration is an essential component in such systems. The two non-rigid registration methods are: (1) a deformable registration of the prostate segmentation distance maps with B-spline regularization and (2) a finite element-based deformable registration of the segmentation surfaces in the presence of partial data. We evaluate the methods retrospectively using clinical patient image data collected during standard clinical procedures. Computation time and Target Registration Error (TRE) calculated at the expert-identified anatomical landmarks were used as quantitative measures for the evaluation. The presented image registration tools were capable of completing deformable registration computation within 5 min. Average TRE was approximately 3 mm for both methods, which is comparable with the slice thickness in our MRI data. Both tools are available under nonrestrictive open-source license. We release open-source tools that may be used for registration during MRI-TRUS-guided prostate interventions. Our tools implement novel registration approaches and produce acceptable registration results. We believe these tools will lower the barriers in development and deployment of interventional research solutions and facilitate comparison with similar tools.

  9. Nonrigid registration of carotid ultrasound and MR images using a "twisting and bending" model

    NASA Astrophysics Data System (ADS)

    Nanayakkara, Nuwan D.; Chiu, Bernard; Samani, Abbas; Spence, J. David; Parraga, Grace; Samarabandu, Jagath; Fenster, Aaron

    2008-03-01

    Atherosclerosis at the carotid bifurcation resulting in cerebral emboli is a major cause of ischemic stroke. Most strokes associated with carotid atherosclerosis can be prevented by lifestyle/dietary changes and pharmacological treatments if identified early by monitoring carotid plaque changes. Plaque composition information from magnetic resonance (MR) carotid images and dynamic characteristics information from 3D ultrasound (US) are necessary for developing and validating US imaging tools to identify vulnerable carotid plaques. Combining these images requires nonrigid registration to correct the non-linear miss-alignments caused by relative twisting and bending in the neck due to different head positions during the two image acquisitions sessions. The high degree of freedom and large number of parameters associated with existing nonrigid image registration methods causes several problems including unnatural plaque morphology alteration, computational complexity, and low reliability. Our approach was to model the normal movement of the neck using a "twisting and bending model" with only six parameters for nonrigid registration. We evaluated our registration technique using intra-subject in-vivo 3D US and 3D MR carotid images acquired on the same day. We calculated the Mean Registration Error (MRE) between the segmented vessel surfaces in the target image and the registered image using a distance-based error metric after applying our "twisting bending model" based nonrigid registration algorithm. We achieved an average registration error of 1.33+/-0.41mm using our nonrigid registration technique. Visual inspection of segmented vessel surfaces also showed a substantial improvement of alignment with our non-rigid registration technique.

  10. Deformable image registration for tissues with large displacements

    PubMed Central

    Huang, Xishi; Ren, Jing; Green, Mark

    2017-01-01

    Abstract. Image registration for internal organs and soft tissues is considered extremely challenging due to organ shifts and tissue deformation caused by patients’ movements such as respiration and repositioning. In our previous work, we proposed a fast registration method for deformable tissues with small rotations. We extend our method to deformable registration of soft tissues with large displacements. We analyzed the deformation field of the liver by decomposing the deformation into shift, rotation, and pure deformation components and concluded that in many clinical cases, the liver deformation contains large rotations and small deformations. This analysis justified the use of linear elastic theory in our image registration method. We also proposed a region-based neuro-fuzzy transformation model to seamlessly stitch together local affine and local rigid models in different regions. We have performed the experiments on a liver MRI image set and showed the effectiveness of the proposed registration method. We have also compared the performance of the proposed method with the previous method on tissues with large rotations and showed that the proposed method outperformed the previous method when dealing with the combination of pure deformation and large rotations. Validation results show that we can achieve a target registration error of 1.87±0.87  mm and an average centerline distance error of 1.28±0.78  mm. The proposed technique has the potential to significantly improve registration capabilities and the quality of intraoperative image guidance. To the best of our knowledge, this is the first time that the complex displacement of the liver is explicitly separated into local pure deformation and rigid motion. PMID:28149924

  11. Overlay improvement by exposure map based mask registration optimization

    NASA Astrophysics Data System (ADS)

    Shi, Irene; Guo, Eric; Chen, Ming; Lu, Max; Li, Gordon; Li, Rivan; Tian, Eric

    2015-03-01

    Along with the increased miniaturization of semiconductor electronic devices, the design rules of advanced semiconductor devices shrink dramatically. [1] One of the main challenges of lithography step is the layer-to-layer overlay control. Furthermore, DPT (Double Patterning Technology) has been adapted for the advanced technology node like 28nm and 14nm, corresponding overlay budget becomes even tighter. [2][3] After the in-die mask registration (pattern placement) measurement is introduced, with the model analysis of a KLA SOV (sources of variation) tool, it's observed that registration difference between masks is a significant error source of wafer layer-to-layer overlay at 28nm process. [4][5] Mask registration optimization would highly improve wafer overlay performance accordingly. It was reported that a laser based registration control (RegC) process could be applied after the pattern generation or after pellicle mounting and allowed fine tuning of the mask registration. [6] In this paper we propose a novel method of mask registration correction, which can be applied before mask writing based on mask exposure map, considering the factors of mask chip layout, writing sequence, and pattern density distribution. Our experiment data show if pattern density on the mask keeps at a low level, in-die mask registration residue error in 3sigma could be always under 5nm whatever blank type and related writer POSCOR (position correction) file was applied; it proves random error induced by material or equipment would occupy relatively fixed error budget as an error source of mask registration. On the real production, comparing the mask registration difference through critical production layers, it could be revealed that registration residue error of line space layers with higher pattern density is always much larger than the one of contact hole layers with lower pattern density. Additionally, the mask registration difference between layers with similar pattern density

  12. Registration of 2D to 3D joint images using phase-based mutual information

    NASA Astrophysics Data System (ADS)

    Dalvi, Rupin; Abugharbieh, Rafeef; Pickering, Mark; Scarvell, Jennie; Smith, Paul

    2007-03-01

    Registration of two dimensional to three dimensional orthopaedic medical image data has important applications particularly in the area of image guided surgery and sports medicine. Fluoroscopy to computer tomography (CT) registration is an important case, wherein digitally reconstructed radiographs derived from the CT data are registered to the fluoroscopy data. Traditional registration metrics such as intensity-based mutual information (MI) typically work well but often suffer from gross misregistration errors when the image to be registered contains a partial view of the anatomy visible in the target image. Phase-based MI provides a robust alternative similarity measure which, in addition to possessing the general robustness and noise immunity that MI provides, also employs local phase information in the registration process which makes it less susceptible to the aforementioned errors. In this paper, we propose using the complex wavelet transform for computing image phase information and incorporating that into a phase-based MI measure for image registration. Tests on a CT volume and 6 fluoroscopy images of the knee are presented. The femur and the tibia in the CT volume were individually registered to the fluoroscopy images using intensity-based MI, gradient-based MI and phase-based MI. Errors in the coordinates of fiducials present in the bone structures were used to assess the accuracy of the different registration schemes. Quantitative results demonstrate that the performance of intensity-based MI was the worst. Gradient-based MI performed slightly better, while phase-based MI results were the best consistently producing the lowest errors.

  13. Inverse consistent non-rigid image registration based on robust point set matching

    PubMed Central

    2014-01-01

    Background Robust point matching (RPM) has been extensively used in non-rigid registration of images to robustly register two sets of image points. However, except for the location at control points, RPM cannot estimate the consistent correspondence between two images because RPM is a unidirectional image matching approach. Therefore, it is an important issue to make an improvement in image registration based on RPM. Methods In our work, a consistent image registration approach based on the point sets matching is proposed to incorporate the property of inverse consistency and improve registration accuracy. Instead of only estimating the forward transformation between the source point sets and the target point sets in state-of-the-art RPM algorithms, the forward and backward transformations between two point sets are estimated concurrently in our algorithm. The inverse consistency constraints are introduced to the cost function of RPM and the fuzzy correspondences between two point sets are estimated based on both the forward and backward transformations simultaneously. A modified consistent landmark thin-plate spline registration is discussed in detail to find the forward and backward transformations during the optimization of RPM. The similarity of image content is also incorporated into point matching in order to improve image matching. Results Synthetic data sets, medical images are employed to demonstrate and validate the performance of our approach. The inverse consistent errors of our algorithm are smaller than RPM. Especially, the topology of transformations is preserved well for our algorithm for the large deformation between point sets. Moreover, the distance errors of our algorithm are similar to that of RPM, and they maintain a downward trend as whole, which demonstrates the convergence of our algorithm. The registration errors for image registrations are evaluated also. Again, our algorithm achieves the lower registration errors in same iteration number

  14. Symposium Registration | The Metastatic Niche: Models, Mechanisms and Targeting Targets into Therapeutics

    Cancer.gov

    Symposium Registration Register for the meeting and abstract submission. Registration for the meeting is required and registration is free. ONLINE REGISTRATION IS CLOSED. Please contact Julia E. Lam (Julia.Lam@nih.gov) if you want to register to attend this event. Abstracts should be submitted at the time of registration and a limited number will be selected for oral presentation and the remainder for poster presentation.   Abstract Submission Deadline is February 21st 2017.

  15. Validation of elastic registration algorithms based on adaptive irregular grids for medical applications

    NASA Astrophysics Data System (ADS)

    Franz, Astrid; Carlsen, Ingwer C.; Renisch, Steffen; Wischmann, Hans-Aloys

    2006-03-01

    Elastic registration of medical images is an active field of current research. Registration algorithms have to be validated in order to show that they fulfill the requirements of a particular clinical application. Furthermore, validation strategies compare the performance of different registration algorithms and can hence judge which algorithm is best suited for a target application. In the literature, validation strategies for rigid registration algorithms have been analyzed. For a known ground truth they assess the displacement error at a few landmarks, which is not sufficient for elastic transformations described by a huge number of parameters. Hence we consider the displacement error averaged over all pixels in the whole image or in a region-of-interest of clinical relevance. Using artificially, but realistically deformed images of the application domain, we use this quality measure to analyze an elastic registration based on transformations defined on adaptive irregular grids for the following clinical applications: Magnetic Resonance (MR) images of freely moving joints for orthopedic investigations, thoracic Computed Tomography (CT) images for the detection of pulmonary embolisms, and transmission images as used for the attenuation correction and registration of independently acquired Positron Emission Tomography (PET) and CT images. The definition of a region-of-interest allows to restrict the analysis of the registration accuracy to clinically relevant image areas. The behaviour of the displacement error as a function of the number of transformation control points and their placement can be used for identifying the best strategy for the initial placement of the control points.

  16. SU-E-J-88: The Study of Setup Error Measured by CBCT in Postoperative Radiotherapy for Cervical Carcinoma

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Runxiao, L; Aikun, W; Xiaomei, F

    2015-06-15

    Purpose: To compare two registration methods in the CBCT guided radiotherapy for cervical carcinoma, analyze the setup errors and registration methods, determine the margin required for clinical target volume(CTV) extending to planning target volume(PTV). Methods: Twenty patients with cervical carcinoma were enrolled. All patients were underwent CT simulation in the supine position. Transfering the CT images to the treatment planning system and defining the CTV, PTV and the organs at risk (OAR), then transmit them to the XVI workshop. CBCT scans were performed before radiotherapy and registered to planning CT images according to bone and gray value registration methods. Comparedmore » two methods and obtain left-right(X), superior-inferior(Y), anterior-posterior (Z) setup errors, the margin required for CTV to PTV were calculated. Results: Setup errors were unavoidable in postoperative cervical carcinoma irradiation. The setup errors measured by method of bone (systemic ± random) on X(1eft.right),Y(superior.inferior),Z(anterior.posterior) directions were(0.24±3.62),(0.77±5.05) and (0.13±3.89)mm, respectively, the setup errors measured by method of grey (systemic ± random) on X(1eft-right), Y(superior-inferior), Z(anterior-posterior) directions were(0.31±3.93), (0.85±5.16) and (0.21±4.12)mm, respectively.The spatial distributions of setup error was maximum in Y direction. The margins were 4 mm in X axis, 6 mm in Y axis, 4 mm in Z axis respectively.These two registration methods were similar and highly recommended. Conclusion: Both bone and grey registration methods could offer an accurate setup error. The influence of setup errors of a PTV margin would be suggested by 4mm, 4mm and 6mm on X, Y and Z directions for postoperative radiotherapy for cervical carcinoma.« less

  17. 4D-CT Lung registration using anatomy-based multi-level multi-resolution optical flow analysis and thin-plate splines.

    PubMed

    Min, Yugang; Neylon, John; Shah, Amish; Meeks, Sanford; Lee, Percy; Kupelian, Patrick; Santhanam, Anand P

    2014-09-01

    The accuracy of 4D-CT registration is limited by inconsistent Hounsfield unit (HU) values in the 4D-CT data from one respiratory phase to another and lower image contrast for lung substructures. This paper presents an optical flow and thin-plate spline (TPS)-based 4D-CT registration method to account for these limitations. The use of unified HU values on multiple anatomy levels (e.g., the lung contour, blood vessels, and parenchyma) accounts for registration errors by inconsistent landmark HU value. While 3D multi-resolution optical flow analysis registers each anatomical level, TPS is employed for propagating the results from one anatomical level to another ultimately leading to the 4D-CT registration. 4D-CT registration was validated using target registration error (TRE), inverse consistency error (ICE) metrics, and a statistical image comparison using Gamma criteria of 1 % intensity difference in 2 mm(3) window range. Validation results showed that the proposed method was able to register CT lung datasets with TRE and ICE values <3 mm. In addition, the average number of voxel that failed the Gamma criteria was <3 %, which supports the clinical applicability of the propose registration mechanism. The proposed 4D-CT registration computes the volumetric lung deformations within clinically viable accuracy.

  18. Surface-based prostate registration with biomechanical regularization

    NASA Astrophysics Data System (ADS)

    van de Ven, Wendy J. M.; Hu, Yipeng; Barentsz, Jelle O.; Karssemeijer, Nico; Barratt, Dean; Huisman, Henkjan J.

    2013-03-01

    Adding MR-derived information to standard transrectal ultrasound (TRUS) images for guiding prostate biopsy is of substantial clinical interest. A tumor visible on MR images can be projected on ultrasound by using MRUS registration. A common approach is to use surface-based registration. We hypothesize that biomechanical modeling will better control deformation inside the prostate than a regular surface-based registration method. We developed a novel method by extending a surface-based registration with finite element (FE) simulation to better predict internal deformation of the prostate. For each of six patients, a tetrahedral mesh was constructed from the manual prostate segmentation. Next, the internal prostate deformation was simulated using the derived radial surface displacement as boundary condition. The deformation field within the gland was calculated using the predicted FE node displacements and thin-plate spline interpolation. We tested our method on MR guided MR biopsy imaging data, as landmarks can easily be identified on MR images. For evaluation of the registration accuracy we used 45 anatomical landmarks located in all regions of the prostate. Our results show that the median target registration error of a surface-based registration with biomechanical regularization is 1.88 mm, which is significantly different from 2.61 mm without biomechanical regularization. We can conclude that biomechanical FE modeling has the potential to improve the accuracy of multimodal prostate registration when comparing it to regular surface-based registration.

  19. The hidden KPI registration accuracy.

    PubMed

    Shorrosh, Paul

    2011-09-01

    Determining the registration accuracy rate is fundamental to improving revenue cycle key performance indicators. A registration quality assurance (QA) process allows errors to be corrected before bills are sent and helps registrars learn from their mistakes. Tools are available to help patient access staff who perform registration QA manually.

  20. Real-time automatic registration in optical surgical navigation

    NASA Astrophysics Data System (ADS)

    Lin, Qinyong; Yang, Rongqian; Cai, Ken; Si, Xuan; Chen, Xiuwen; Wu, Xiaoming

    2016-05-01

    An image-guided surgical navigation system requires the improvement of the patient-to-image registration time to enhance the convenience of the registration procedure. A critical step in achieving this aim is performing a fully automatic patient-to-image registration. This study reports on a design of custom fiducial markers and the performance of a real-time automatic patient-to-image registration method using these markers on the basis of an optical tracking system for rigid anatomy. The custom fiducial markers are designed to be automatically localized in both patient and image spaces. An automatic localization method is performed by registering a point cloud sampled from the three dimensional (3D) pedestal model surface of a fiducial marker to each pedestal of fiducial markers searched in image space. A head phantom is constructed to estimate the performance of the real-time automatic registration method under four fiducial configurations. The head phantom experimental results demonstrate that the real-time automatic registration method is more convenient, rapid, and accurate than the manual method. The time required for each registration is approximately 0.1 s. The automatic localization method precisely localizes the fiducial markers in image space. The averaged target registration error for the four configurations is approximately 0.7 mm. The automatic registration performance is independent of the positions relative to the tracking system and the movement of the patient during the operation.

  1. Automated brainstem co-registration (ABC) for MRI.

    PubMed

    Napadow, Vitaly; Dhond, Rupali; Kennedy, David; Hui, Kathleen K S; Makris, Nikos

    2006-09-01

    Group data analysis in brainstem neuroimaging is predicated on accurate co-registration of anatomy. As the brainstem is comprised of many functionally heterogeneous nuclei densely situated adjacent to one another, relatively small errors in co-registration can manifest in increased variance or decreased sensitivity (or significance) in detecting activations. We have devised a 2-stage automated, reference mask guided registration technique (Automated Brainstem Co-registration, or ABC) for improved brainstem co-registration. Our approach utilized a brainstem mask dataset to weight an automated co-registration cost function. Our method was validated through measurement of RMS error at 12 manually defined landmarks. These landmarks were also used as guides for a secondary manual co-registration option, intended for outlier individuals that may not adequately co-register with our automated method. Our methodology was tested on 10 healthy human subjects and compared to traditional co-registration techniques (Talairach transform and automated affine transform to the MNI-152 template). We found that ABC had a significantly lower mean RMS error (1.22 +/- 0.39 mm) than Talairach transform (2.88 +/- 1.22 mm, mu +/- sigma) and the global affine (3.26 +/- 0.81 mm) method. Improved accuracy was also found for our manual-landmark-guided option (1.51 +/- 0.43 mm). Visualizing individual brainstem borders demonstrated more consistent and uniform overlap for ABC compared to traditional global co-registration techniques. Improved robustness (lower susceptibility to outliers) was demonstrated with ABC through lower inter-subject RMS error variance compared with traditional co-registration methods. The use of easily available and validated tools (AFNI and FSL) for this method should ease adoption by other investigators interested in brainstem data group analysis.

  2. Automated dental implantation using image-guided robotics: registration results.

    PubMed

    Sun, Xiaoyan; McKenzie, Frederic D; Bawab, Sebastian; Li, Jiang; Yoon, Yongki; Huang, Jen-K

    2011-09-01

    One of the most important factors affecting the outcome of dental implantation is the accurate insertion of the implant into the patient's jaw bone, which requires a high degree of anatomical accuracy. With the accuracy and stability of robots, image-guided robotics is expected to provide more reliable and successful outcomes for dental implantation. Here, we proposed the use of a robot for drilling the implant site in preparation for the insertion of the implant. An image-guided robotic system for automated dental implantation is described in this paper. Patient-specific 3D models are reconstructed from preoperative Cone-beam CT images, and implantation planning is performed with these virtual models. A two-step registration procedure is applied to transform the preoperative plan of the implant insertion into intra-operative operations of the robot with the help of a Coordinate Measurement Machine (CMM). Experiments are carried out with a phantom that is generated from the patient-specific 3D model. Fiducial Registration Error (FRE) and Target Registration Error (TRE) values are calculated to evaluate the accuracy of the registration procedure. FRE values are less than 0.30 mm. Final TRE values after the two-step registration are 1.42 ± 0.70 mm (N = 5). The registration results of an automated dental implantation system using image-guided robotics are reported in this paper. Phantom experiments show that the practice of robot in the dental implantation is feasible and the system accuracy is comparable to other similar systems for dental implantation.

  3. 3D non-rigid surface-based MR-TRUS registration for image-guided prostate biopsy

    NASA Astrophysics Data System (ADS)

    Sun, Yue; Qiu, Wu; Romagnoli, Cesare; Fenster, Aaron

    2014-03-01

    Two dimensional (2D) transrectal ultrasound (TRUS) guided prostate biopsy is the standard approach for definitive diagnosis of prostate cancer (PCa). However, due to the lack of image contrast of prostate tumors needed to clearly visualize early-stage PCa, prostate biopsy often results in false negatives, requiring repeat biopsies. Magnetic Resonance Imaging (MRI) has been considered to be a promising imaging modality for noninvasive identification of PCa, since it can provide a high sensitivity and specificity for the detection of early stage PCa. Our main objective is to develop and validate a registration method of 3D MR-TRUS images, allowing generation of volumetric 3D maps of targets identified in 3D MR images to be biopsied using 3D TRUS images. Our registration method first makes use of an initial rigid registration of 3D MR images to 3D TRUS images using 6 manually placed approximately corresponding landmarks in each image. Following the manual initialization, two prostate surfaces are segmented from 3D MR and TRUS images and then non-rigidly registered using a thin-plate spline (TPS) algorithm. The registration accuracy was evaluated using 4 patient images by measuring target registration error (TRE) of manually identified corresponding intrinsic fiducials (calcifications and/or cysts) in the prostates. Experimental results show that the proposed method yielded an overall mean TRE of 2.05 mm, which is favorably comparable to a clinical requirement for an error of less than 2.5 mm.

  4. Multiple window spatial registration error of a gamma camera: 133Ba point source as a replacement of the NEMA procedure.

    PubMed

    Bergmann, Helmar; Minear, Gregory; Raith, Maria; Schaffarich, Peter M

    2008-12-09

    The accuracy of multiple window spatial resolution characterises the performance of a gamma camera for dual isotope imaging. In the present study we investigate an alternative method to the standard NEMA procedure for measuring this performance parameter. A long-lived 133Ba point source with gamma energies close to 67Ga and a single bore lead collimator were used to measure the multiple window spatial registration error. Calculation of the positions of the point source in the images used the NEMA algorithm. The results were validated against the values obtained by the standard NEMA procedure which uses a liquid 67Ga source with collimation. Of the source-collimator configurations under investigation an optimum collimator geometry, consisting of a 5 mm thick lead disk with a diameter of 46 mm and a 5 mm central bore, was selected. The multiple window spatial registration errors obtained by the 133Ba method showed excellent reproducibility (standard deviation < 0.07 mm). The values were compared with the results from the NEMA procedure obtained at the same locations and showed small differences with a correlation coefficient of 0.51 (p < 0.05). In addition, the 133Ba point source method proved to be much easier to use. A Bland-Altman analysis showed that the 133Ba and the 67Ga Method can be used interchangeably. The 133Ba point source method measures the multiple window spatial registration error with essentially the same accuracy as the NEMA-recommended procedure, but is easier and safer to use and has the potential to replace the current standard procedure.

  5. Registration of human skull computed tomography data to an ultrasound treatment space using a sparse high frequency ultrasound hemispherical array

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    O’Reilly, Meaghan A., E-mail: moreilly@sri.utoront

    Purpose: Transcranial focused ultrasound (FUS) shows great promise for a range of therapeutic applications in the brain. Current clinical investigations rely on the use of magnetic resonance imaging (MRI) to monitor treatments and for the registration of preoperative computed tomography (CT)-data to the MR images at the time of treatment to correct the sound aberrations caused by the skull. For some applications, MRI is not an appropriate choice for therapy monitoring and its cost may limit the accessibility of these treatments. An alternative approach, using high frequency ultrasound measurements to localize the skull surface and register CT data to themore » ultrasound treatment space, for the purposes of skull-related phase aberration correction and treatment targeting, has been developed. Methods: A prototype high frequency, hemispherical sparse array was fabricated. Pulse-echo measurements of the surface of five ex vivo human skulls were made, and the CT datasets of each skull were obtained. The acoustic data were used to rigidly register the CT-derived skull surface to the treatment space. The ultrasound-based registrations of the CT datasets were compared to the gold-standard landmark-based registrations. Results: The results show on an average sub-millimeter (0.9 ± 0.2 mm) displacement and subdegree (0.8° ± 0.4°) rotation registration errors. Numerical simulations predict that registration errors on this scale will result in a mean targeting error of 1.0 ± 0.2 mm and reduction in focal pressure of 1.0% ± 0.6% when targeting a midbrain structure (e.g., hippocampus) using a commercially available low-frequency brain prototype device (InSightec, 230 kHz brain system). Conclusions: If combined with ultrasound-based treatment monitoring techniques, this registration method could allow for the development of a low-cost transcranial FUS treatment platform to make this technology more widely available.« less

  6. Registration of human skull computed tomography data to an ultrasound treatment space using a sparse high frequency ultrasound hemispherical array.

    PubMed

    O'Reilly, Meaghan A; Jones, Ryan M; Birman, Gabriel; Hynynen, Kullervo

    2016-09-01

    Transcranial focused ultrasound (FUS) shows great promise for a range of therapeutic applications in the brain. Current clinical investigations rely on the use of magnetic resonance imaging (MRI) to monitor treatments and for the registration of preoperative computed tomography (CT)-data to the MR images at the time of treatment to correct the sound aberrations caused by the skull. For some applications, MRI is not an appropriate choice for therapy monitoring and its cost may limit the accessibility of these treatments. An alternative approach, using high frequency ultrasound measurements to localize the skull surface and register CT data to the ultrasound treatment space, for the purposes of skull-related phase aberration correction and treatment targeting, has been developed. A prototype high frequency, hemispherical sparse array was fabricated. Pulse-echo measurements of the surface of five ex vivo human skulls were made, and the CT datasets of each skull were obtained. The acoustic data were used to rigidly register the CT-derived skull surface to the treatment space. The ultrasound-based registrations of the CT datasets were compared to the gold-standard landmark-based registrations. The results show on an average sub-millimeter (0.9 ± 0.2 mm) displacement and subdegree (0.8° ± 0.4°) rotation registration errors. Numerical simulations predict that registration errors on this scale will result in a mean targeting error of 1.0 ± 0.2 mm and reduction in focal pressure of 1.0% ± 0.6% when targeting a midbrain structure (e.g., hippocampus) using a commercially available low-frequency brain prototype device (InSightec, 230 kHz brain system). If combined with ultrasound-based treatment monitoring techniques, this registration method could allow for the development of a low-cost transcranial FUS treatment platform to make this technology more widely available.

  7. Registration of human skull computed tomography data to an ultrasound treatment space using a sparse high frequency ultrasound hemispherical array

    PubMed Central

    O’Reilly, Meaghan A.; Jones, Ryan M.; Birman, Gabriel; Hynynen, Kullervo

    2016-01-01

    Purpose: Transcranial focused ultrasound (FUS) shows great promise for a range of therapeutic applications in the brain. Current clinical investigations rely on the use of magnetic resonance imaging (MRI) to monitor treatments and for the registration of preoperative computed tomography (CT)-data to the MR images at the time of treatment to correct the sound aberrations caused by the skull. For some applications, MRI is not an appropriate choice for therapy monitoring and its cost may limit the accessibility of these treatments. An alternative approach, using high frequency ultrasound measurements to localize the skull surface and register CT data to the ultrasound treatment space, for the purposes of skull-related phase aberration correction and treatment targeting, has been developed. Methods: A prototype high frequency, hemispherical sparse array was fabricated. Pulse-echo measurements of the surface of five ex vivo human skulls were made, and the CT datasets of each skull were obtained. The acoustic data were used to rigidly register the CT-derived skull surface to the treatment space. The ultrasound-based registrations of the CT datasets were compared to the gold-standard landmark-based registrations. Results: The results show on an average sub-millimeter (0.9 ± 0.2 mm) displacement and subdegree (0.8° ± 0.4°) rotation registration errors. Numerical simulations predict that registration errors on this scale will result in a mean targeting error of 1.0 ± 0.2 mm and reduction in focal pressure of 1.0% ± 0.6% when targeting a midbrain structure (e.g., hippocampus) using a commercially available low-frequency brain prototype device (InSightec, 230 kHz brain system). Conclusions: If combined with ultrasound-based treatment monitoring techniques, this registration method could allow for the development of a low-cost transcranial FUS treatment platform to make this technology more widely available. PMID:27587036

  8. Deformable planning CT to cone-beam CT image registration in head-and-neck cancer

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hou Jidong; Guerrero, Mariana; Chen, Wenjuan

    2011-04-15

    Purpose: The purpose of this work was to implement and validate a deformable CT to cone-beam computed tomography (CBCT) image registration method in head-and-neck cancer to eventually facilitate automatic target delineation on CBCT. Methods: Twelve head-and-neck cancer patients underwent a planning CT and weekly CBCT during the 5-7 week treatment period. The 12 planning CT images (moving images) of these patients were registered to their weekly CBCT images (fixed images) via the symmetric force Demons algorithm and using a multiresolution scheme. Histogram matching was used to compensate for the intensity difference between the two types of images. Using nine knownmore » anatomic points as registration targets, the accuracy of the registration was evaluated using the target registration error (TRE). In addition, region-of-interest (ROI) contours drawn on the planning CT were morphed to the CBCT images and the volume overlap index (VOI) between registered contours and manually delineated contours was evaluated. Results: The mean TRE value of the nine target points was less than 3.0 mm, the slice thickness of the planning CT. Of the 369 target points evaluated for registration accuracy, the average TRE value was 2.6{+-}0.6 mm. The mean TRE for bony tissue targets was 2.4{+-}0.2 mm, while the mean TRE for soft tissue targets was 2.8{+-}0.2 mm. The average VOI between the registered and manually delineated ROI contours was 76.2{+-}4.6%, which is consistent with that reported in previous studies. Conclusions: The authors have implemented and validated a deformable image registration method to register planning CT images to weekly CBCT images in head-and-neck cancer cases. The accuracy of the TRE values suggests that they can be used as a promising tool for automatic target delineation on CBCT.« less

  9. The ANACONDA algorithm for deformable image registration in radiotherapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Weistrand, Ola; Svensson, Stina, E-mail: stina.svensson@raysearchlabs.com

    2015-01-15

    Purpose: The purpose of this work was to describe a versatile algorithm for deformable image registration with applications in radiotherapy and to validate it on thoracic 4DCT data as well as CT/cone beam CT (CBCT) data. Methods: ANAtomically CONstrained Deformation Algorithm (ANACONDA) combines image information (i.e., intensities) with anatomical information as provided by contoured image sets. The registration problem is formulated as a nonlinear optimization problem and solved with an in-house developed solver, tailored to this problem. The objective function, which is minimized during optimization, is a linear combination of four nonlinear terms: 1. image similarity term; 2. grid regularizationmore » term, which aims at keeping the deformed image grid smooth and invertible; 3. a shape based regularization term which works to keep the deformation anatomically reasonable when regions of interest are present in the reference image; and 4. a penalty term which is added to the optimization problem when controlling structures are used, aimed at deforming the selected structure in the reference image to the corresponding structure in the target image. Results: To validate ANACONDA, the authors have used 16 publically available thoracic 4DCT data sets for which target registration errors from several algorithms have been reported in the literature. On average for the 16 data sets, the target registration error is 1.17 ± 0.87 mm, Dice similarity coefficient is 0.98 for the two lungs, and image similarity, measured by the correlation coefficient, is 0.95. The authors have also validated ANACONDA using two pelvic cases and one head and neck case with planning CT and daily acquired CBCT. Each image has been contoured by a physician (radiation oncologist) or experienced radiation therapist. The results are an improvement with respect to rigid registration. However, for the head and neck case, the sample set is too small to show statistical significance. Conclusions

  10. WE-AB-BRA-09: Registration of Preoperative MRI to Intraoperative Radiographs for Automatic Vertebral Target Localization

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    De Silva, T; Uneri, A; Ketcha, M

    Purpose: Accurate localization of target vertebrae is essential to safe, effective spine surgery, but wrong-level surgery occurs with surprisingly high frequency. Recent research yielded the “LevelCheck” method for 3D-2D registration of preoperative CT to intraoperative radiographs, providing decision support for level localization. We report a new method (MR-LevelCheck) to perform 3D-2D registration based on preoperative MRI, presenting a solution for the increasingly common scenario in which MRI (not CT) is used for preoperative planning. Methods: Direct extension of LevelCheck is confounded by large mismatch in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simplemore » vertebrae segmentation. Using seed points at centroids, vertebrae are segmented using continuous max-flow method and dilated by 1.8 mm to include surrounding cortical bone (inconspicuous in T2w-MRI). MRI projections are computed (analogous to DRR) using segmentation and registered to intraoperative radiographs. The method was tested in a retrospective IRB-approved study involving 11 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. Registration accuracy was evaluated in terms of projection-distance-error (PDE) between the true and estimated location of vertebrae in each radiograph. Results: The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch, and large capture range. Segmentation achieved Dice coefficient = 89.2 ± 2.3 and mean-absolute-distance (MAD) = 1.5 ± 0.3 mm. Registration demonstrated robust performance under realistic patient variations, with PDE = 4.0 ± 1.9 mm (median ± iqr) and converged with run-time = 23.3 ± 1.7 s. Conclusion: The MR-LevelCheck algorithm provides an important extension to a previously validated decision support tool in spine surgery by extending its

  11. Multiview marker-free registration of forest terrestrial laser scanner data with embedded confidence metrics

    DOE PAGES

    Kelbe, David; Oak Ridge National Lab.; van Aardt, Jan; ...

    2016-10-18

    Terrestrial laser scanning has demonstrated increasing potential for rapid comprehensive measurement of forest structure, especially when multiple scans are spatially registered in order to reduce the limitations of occlusion. Although marker-based registration techniques (based on retro-reflective spherical targets) are commonly used in practice, a blind marker-free approach is preferable, insofar as it supports rapid operational data acquisition. To support these efforts, we extend the pairwise registration approach of our earlier work, and develop a graph-theoretical framework to perform blind marker-free global registration of multiple point cloud data sets. Pairwise pose estimates are weighted based on their estimated error, in ordermore » to overcome pose conflict while exploiting redundant information and improving precision. The proposed approach was tested for eight diverse New England forest sites, with 25 scans collected at each site. Quantitative assessment was provided via a novel embedded confidence metric, with a mean estimated root-mean-square error of 7.2 cm and 89% of scans connected to the reference node. Lastly, this paper assesses the validity of the embedded multiview registration confidence metric and evaluates the performance of the proposed registration algorithm.« less

  12. Model-to-image based 2D-3D registration of angiographic data

    NASA Astrophysics Data System (ADS)

    Mollus, Sabine; Lübke, Jördis; Walczuch, Andreas J.; Schumann, Heidrun; Weese, Jürgen

    2008-03-01

    We propose a novel registration method, which combines well-known vessel detection techniques with aspects of model adaptation. The proposed method is tailored to the requirements of 2D-3D-registration of interventional angiographic X-ray data such as acquired during abdominal procedures. As prerequisite, a vessel centerline is extracted out of a rotational angiography (3DRA) data set to build an individual model of the vascular tree. Following the two steps of local vessel detection and model transformation the centerline model is matched to one dynamic subtraction angiography (DSA) target image. Thereby, the in-plane position and the 3D orientation of the centerline is related to the vessel candidates found in the target image minimizing the residual error in least squares manner. In contrast to feature-based methods, no segmentation of the vessel tree in the 2D target image is required. First experiments with synthetic angiographies and clinical data sets indicate that matching with the proposed model-to-image based registration approach is accurate and robust and is characterized by a large capture range.

  13. Panorama imaging for image-to-physical registration of narrow drill holes inside spongy bones

    NASA Astrophysics Data System (ADS)

    Bergmeier, Jan; Fast, Jacob Friedemann; Ortmaier, Tobias; Kahrs, Lüder Alexander

    2017-03-01

    Image-to-physical registration based on volumetric data like computed tomography on the one side and intraoperative endoscopic images on the other side is an important method for various surgical applications. In this contribution, we present methods to generate panoramic views from endoscopic recordings for image-to-physical registration of narrow drill holes inside spongy bone. One core application is the registration of drill poses inside the mastoid during minimally invasive cochlear implantations. Besides the development of image processing software for registration, investigations are performed on a miniaturized optical system, achieving 360° radial imaging with one shot by extending a conventional, small, rigid, rod lens endoscope. A reflective cone geometry is used to deflect radially incoming light rays into the endoscope optics. Therefore, a cone mirror is mounted in front of a conventional 0° endoscope. Furthermore, panoramic images of inner drill hole surfaces in artificial bone material are created. Prior to drilling, cone beam computed tomography data is acquired from this artificial bone and simulated endoscopic views are generated from this data. A qualitative and quantitative image comparison of resulting views in terms of image-to-image registration is performed. First results show that downsizing of panoramic optics to a diameter of 3mm is possible. Conventional rigid rod lens endoscopes can be extended to produce suitable panoramic one-shot image data. Using unrolling and stitching methods, images of the inner drill hole surface similar to computed tomography image data of the same surface were created. Registration is performed on ten perturbations of the search space and results in target registration errors of (0:487 +/- 0:438)mm at the entry point and (0:957 +/- 0:948)mm at the exit as well as an angular error of (1:763 +/- 1:536)°. The results show suitability of this image data for image-to-image registration. Analysis of the error

  14. Comparison of carina-based versus bony anatomy-based registration for setup verification in esophageal cancer radiotherapy.

    PubMed

    Machiels, Mélanie; Jin, Peng; van Gurp, Christianne H; van Hooft, Jeanin E; Alderliesten, Tanja; Hulshof, Maarten C C M

    2018-03-21

    To investigate the feasibility and geometric accuracy of carina-based registration for CBCT-guided setup verification in esophageal cancer IGRT, compared with current practice bony anatomy-based registration. Included were 24 esophageal cancer patients with 65 implanted fiducial markers, visible on planning CTs and follow-up CBCTs. All available CBCT scans (n = 236) were rigidly registered to the planning CT with respect to the bony anatomy and the carina. Target coverage was visually inspected and marker position variation was quantified relative to both registration approaches; the variation of systematic (Σ) and random errors (σ) was estimated. Automatic carina-based registration was feasible in 94.9% of the CBCT scans, with an adequate target coverage in 91.1% compared to 100% after bony anatomy-based registration. Overall, Σ (σ) in the LR/CC/AP direction was 2.9(2.4)/4.1(2.4)/2.2(1.8) mm using the bony anatomy registration compared to 3.3(3.0)/3.6(2.6)/3.9(3.1) mm for the carina. Mid-thoracic placed markers showed a non-significant but smaller Σ in CC and AP direction when using the carina-based registration. Compared with a bony anatomy-based registration, carina-based registration for esophageal cancer IGRT results in inadequate target coverage in 8.9% of cases. Furthermore, large Σ and σ, requiring larger anisotropic margins, were seen after carina-based registration. Only for tumors entirely confined to the mid-thoracic region the carina-based registration might be slightly favorable.

  15. A Bayesian nonrigid registration method to enhance intraoperative target definition in image-guided prostate procedures through uncertainty characterization

    PubMed Central

    Pursley, Jennifer; Risholm, Petter; Fedorov, Andriy; Tuncali, Kemal; Fennessy, Fiona M.; Wells, William M.; Tempany, Clare M.; Cormack, Robert A.

    2012-01-01

    variation in the shape and volume of the segmented prostate in diagnostic and intraprocedural images. The probabilistic method allowed us to convey registration results in terms of posterior distributions, with the dispersion providing a patient-specific estimate of the registration uncertainty. The median of the predictive distance distribution between the deformed prostate boundary and the segmented boundary was ⩽3 mm (95th percentiles within ±4 mm) for all ten patients. The accuracy and precision of the internal deformation was evaluated by comparing the posterior predictive distance distribution for the CZ-PZ interface for each patient, with the median distance ranging from −0.6 to 2.4 mm. Posterior predictive distances between naturally occurring landmarks showed registration errors of ⩽5 mm in any direction. The uncertainty was not a global measure, but instead was local and varied throughout the registration region. Registration uncertainties were largest in the apical region of the prostate. Conclusions: Using a Bayesian nonrigid registration method, the authors determined the posterior distribution on deformations between diagnostic and intraprocedural MR images and quantified the uncertainty in the registration results. The feasibility of this approach was tested and results were positive. The probabilistic framework allows us to evaluate both patient-specific and location-specific estimates of the uncertainty in the registration result. Although the framework was tested on MR-guided procedures, the preliminary results suggest that it may be applied to TRUS-guided procedures as well, where the addition of diagnostic MR information may have a larger impact on target definition and clinical guidance. PMID:23127078

  16. Monitoring tumor motion by real time 2D/3D registration during radiotherapy.

    PubMed

    Gendrin, Christelle; Furtado, Hugo; Weber, Christoph; Bloch, Christoph; Figl, Michael; Pawiro, Supriyanto Ardjo; Bergmann, Helmar; Stock, Markus; Fichtinger, Gabor; Georg, Dietmar; Birkfellner, Wolfgang

    2012-02-01

    In this paper, we investigate the possibility to use X-ray based real time 2D/3D registration for non-invasive tumor motion monitoring during radiotherapy. The 2D/3D registration scheme is implemented using general purpose computation on graphics hardware (GPGPU) programming techniques and several algorithmic refinements in the registration process. Validation is conducted off-line using a phantom and five clinical patient data sets. The registration is performed on a region of interest (ROI) centered around the planned target volume (PTV). The phantom motion is measured with an rms error of 2.56 mm. For the patient data sets, a sinusoidal movement that clearly correlates to the breathing cycle is shown. Videos show a good match between X-ray and digitally reconstructed radiographs (DRR) displacement. Mean registration time is 0.5 s. We have demonstrated that real-time organ motion monitoring using image based markerless registration is feasible. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  17. Assessing the intrinsic precision of 3D/3D rigid image registration results for patient setup in the absence of a ground truth.

    PubMed

    Wu, Jian; Murphy, Martin J

    2010-06-01

    To assess the precision and robustness of patient setup corrections computed from 3D/3D rigid registration methods using image intensity, when no ground truth validation is possible. Fifteen pairs of male pelvic CTs were rigidly registered using four different in-house registration methods. Registration results were compared for different resolutions and image content by varying the image down-sampling ratio and by thresholding out soft tissue to isolate bony landmarks. Intrinsic registration precision was investigated by comparing the different methods and by reversing the source and the target roles of the two images being registered. The translational reversibility errors for successful registrations ranged from 0.0 to 1.69 mm. Rotations were less than 1 degrees. Mutual information failed in most registrations that used only bony landmarks. The magnitude of the reversibility error was strongly correlated with the success/ failure of each algorithm to find the global minimum. Rigid image registrations have an intrinsic uncertainty and robustness that depends on the imaging modality, the registration algorithm, the image resolution, and the image content. In the absence of an absolute ground truth, the variation in the shifts calculated by several different methods provides a useful estimate of that uncertainty. The difference observed by reversing the source and target images can be used as an indication of robust convergence.

  18. SU-E-J-13: Six Degree of Freedom Image Fusion Accuracy for Cranial Target Localization On the Varian Edge Stereotactic Radiosurgery System: Comparison Between 2D/3D and KV CBCT Image Registration

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Xu, H; Song, K; Chetty, I

    Purpose: To determine the 6 degree of freedom systematic deviations between 2D/3D and CBCT image registration with various imaging setups and fusion algorithms on the Varian Edge Linac. Methods: An anthropomorphic head phantom with radio opaque targets embedded was scanned with CT slice thicknesses of 0.8, 1, 2, and 3mm. The 6 DOF systematic errors were assessed by comparing 2D/3D (kV/MV with CT) with 3D/3D (CBCT with CT) image registrations with different offset positions, similarity measures, image filters, and CBCT slice thicknesses (1 and 2 mm). The 2D/3D registration accuracy of 51 fractions for 26 cranial SRS patients was alsomore » evaluated by analyzing 2D/3D pre-treatment verification taken after 3D/3D image registrations. Results: The systematic deviations of 2D/3D image registration using kV- kV, MV-kV and MV-MV image pairs were within ±0.3mm and ±0.3° for translations and rotations with 95% confidence interval (CI) for a reference CT with 0.8 mm slice thickness. No significant difference (P>0.05) on target localization was observed between 0.8mm, 1mm, and 2mm CT slice thicknesses with CBCT slice thicknesses of 1mm and 2mm. With 3mm CT slice thickness, both 2D/3D and 3D/3D registrations performed less accurately in longitudinal direction than thinner CT slice thickness (0.60±0.12mm and 0.63±0.07mm off, respectively). Using content filter and using similarity measure of pattern intensity instead of mutual information, improved the 2D/3D registration accuracy significantly (P=0.02 and P=0.01, respectively). For the patient study, means and standard deviations of residual errors were 0.09±0.32mm, −0.22±0.51mm and −0.07±0.32mm in VRT, LNG and LAT directions, respectively, and 0.12°±0.46°, −0.12°±0.39° and 0.06°±0.28° in RTN, PITCH, and ROLL directions, respectively. 95% CI of translational and rotational deviations were comparable to those in phantom study. Conclusion: 2D/3D image registration provided on the Varian Edge radiosurgery

  19. Effect of endorectal balloon positioning errors on target deformation and dosimetric quality during prostate SBRT

    NASA Astrophysics Data System (ADS)

    Jones, Bernard L.; Gan, Gregory; Kavanagh, Brian; Miften, Moyed

    2013-11-01

    An inflatable endorectal balloon (ERB) is often used during stereotactic body radiation therapy (SBRT) for treatment of prostate cancer in order to reduce both intrafraction motion of the target and risk of rectal toxicity. However, the ERB can exert significant force on the prostate, and this work assessed the impact of ERB position errors on deformation of the prostate and treatment dose metrics. Seventy-one cone-beam computed tomography (CBCT) image datasets of nine patients with clinical stage T1cN0M0 prostate cancer were studied. An ERB (Flexi-Cuff, EZ-EM, Westbury, NY) inflated with 60 cm3 of air was used during simulation and treatment, and daily kilovoltage (kV) CBCT imaging was performed to localize the prostate. The shape of the ERB in each CBCT was analyzed to determine errors in position, size, and shape. A deformable registration algorithm was used to track the dose received by (and deformation of) the prostate, and dosimetric values such as D95, PTV coverage, and Dice coefficient for the prostate were calculated. The average balloon position error was 0.5 cm in the inferior direction, with errors ranging from 2 cm inferiorly to 1 cm superiorly. The prostate was deformed primarily in the AP direction, and tilted primarily in the anterior-posterior/superior-inferior plane. A significant correlation was seen between errors in depth of ERB insertion (DOI) and mean voxel-wise deformation, prostate tilt, Dice coefficient, and planning-to-treatment prostate inter-surface distance (p < 0.001). Dosimetrically, DOI is negatively correlated with prostate D95 and PTV coverage (p < 0.001). For the model of ERB studied, error in ERB position can cause deformations in the prostate that negatively affect treatment, and this additional aspect of setup error should be considered when ERBs are used for prostate SBRT. Before treatment, the ERB position should be verified, and the ERB should be adjusted if the error is observed to exceed tolerable values.

  20. Efficient feature-based 2D/3D registration of transesophageal echocardiography to x-ray fluoroscopy for cardiac interventions

    NASA Astrophysics Data System (ADS)

    Hatt, Charles R.; Speidel, Michael A.; Raval, Amish N.

    2014-03-01

    We present a novel 2D/ 3D registration algorithm for fusion between transesophageal echocardiography (TEE) and X-ray fluoroscopy (XRF). The TEE probe is modeled as a subset of 3D gradient and intensity point features, which facilitates efficient 3D-to-2D perspective projection. A novel cost-function, based on a combination of intensity and edge features, evaluates the registration cost value without the need for time-consuming generation of digitally reconstructed radiographs (DRRs). Validation experiments were performed with simulations and phantom data. For simulations, in silica XRF images of a TEE probe were generated in a number of different pose configurations using a previously acquired CT image. Random misregistrations were applied and our method was used to recover the TEE probe pose and compare the result to the ground truth. Phantom experiments were performed by attaching fiducial markers externally to a TEE probe, imaging the probe with an interventional cardiac angiographic x-ray system, and comparing the pose estimated from the external markers to that estimated from the TEE probe using our algorithm. Simulations found a 3D target registration error of 1.08(1.92) mm for biplane (monoplane) geometries, while the phantom experiment found a 2D target registration error of 0.69mm. For phantom experiments, we demonstrated a monoplane tracking frame-rate of 1.38 fps. The proposed feature-based registration method is computationally efficient, resulting in near real-time, accurate image based registration between TEE and XRF.

  1. Debiasing affective forecasting errors with targeted, but not representative, experience narratives.

    PubMed

    Shaffer, Victoria A; Focella, Elizabeth S; Scherer, Laura D; Zikmund-Fisher, Brian J

    2016-10-01

    To determine whether representative experience narratives (describing a range of possible experiences) or targeted experience narratives (targeting the direction of forecasting bias) can reduce affective forecasting errors, or errors in predictions of experiences. In Study 1, participants (N=366) were surveyed about their experiences with 10 common medical events. Those who had never experienced the event provided ratings of predicted discomfort and those who had experienced the event provided ratings of actual discomfort. Participants making predictions were randomly assigned to either the representative experience narrative condition or the control condition in which they made predictions without reading narratives. In Study 2, participants (N=196) were again surveyed about their experiences with these 10 medical events, but participants making predictions were randomly assigned to either the targeted experience narrative condition or the control condition. Affective forecasting errors were observed in both studies. These forecasting errors were reduced with the use of targeted experience narratives (Study 2) but not representative experience narratives (Study 1). Targeted, but not representative, narratives improved the accuracy of predicted discomfort. Public collections of patient experiences should favor stories that target affective forecasting biases over stories representing the range of possible experiences. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  2. An image warping technique for rodent brain MRI-histology registration based on thin-plate splines with landmark optimization

    NASA Astrophysics Data System (ADS)

    Liu, Yutong; Uberti, Mariano; Dou, Huanyu; Mosley, R. Lee; Gendelman, Howard E.; Boska, Michael D.

    2009-02-01

    Coregistration of in vivo magnetic resonance imaging (MRI) with histology provides validation of disease biomarker and pathobiology studies. Although thin-plate splines are widely used in such image registration, point landmark selection is error prone and often time-consuming. We present a technique to optimize landmark selection for thin-plate splines and demonstrate its usefulness in warping rodent brain MRI to histological sections. In this technique, contours are drawn on the corresponding MRI slices and images of histological sections. The landmarks are extracted from the contours by equal spacing then optimized by minimizing a cost function consisting of the landmark displacement and contour curvature. The technique was validated using simulation data and brain MRI-histology coregistration in a murine model of HIV-1 encephalitis. Registration error was quantified by calculating target registration error (TRE). The TRE of approximately 8 pixels for 20-80 landmarks without optimization was stable at different landmark numbers. The optimized results were more accurate at low landmark numbers (TRE of approximately 2 pixels for 50 landmarks), while the accuracy decreased (TRE approximately 8 pixels for larger numbers of landmarks (70- 80). The results demonstrated that registration accuracy decreases with the increasing landmark numbers offering more confidence in MRI-histology registration using thin-plate splines.

  3. Phase measurement error in summation of electron holography series.

    PubMed

    McLeod, Robert A; Bergen, Michael; Malac, Marek

    2014-06-01

    Off-axis electron holography is a method for the transmission electron microscope (TEM) that measures the electric and magnetic properties of a specimen. The electrostatic and magnetic potentials modulate the electron wavefront phase. The error in measurement of the phase therefore determines the smallest observable changes in electric and magnetic properties. Here we explore the summation of a hologram series to reduce the phase error and thereby improve the sensitivity of electron holography. Summation of hologram series requires independent registration and correction of image drift and phase wavefront drift, the consequences of which are discussed. Optimization of the electro-optical configuration of the TEM for the double biprism configuration is examined. An analytical model of image and phase drift, composed of a combination of linear drift and Brownian random-walk, is derived and experimentally verified. The accuracy of image registration via cross-correlation and phase registration is characterized by simulated hologram series. The model of series summation errors allows the optimization of phase error as a function of exposure time and fringe carrier frequency for a target spatial resolution. An experimental example of hologram series summation is provided on WS2 fullerenes. A metric is provided to measure the object phase error from experimental results and compared to analytical predictions. The ultimate experimental object root-mean-square phase error is 0.006 rad (2π/1050) at a spatial resolution less than 0.615 nm and a total exposure time of 900 s. The ultimate phase error in vacuum adjacent to the specimen is 0.0037 rad (2π/1700). The analytical prediction of phase error differs with the experimental metrics by +7% inside the object and -5% in the vacuum, indicating that the model can provide reliable quantitative predictions. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

  4. Accuracy assessment of fluoroscopy-transesophageal echocardiography registration

    NASA Astrophysics Data System (ADS)

    Lang, Pencilla; Seslija, Petar; Bainbridge, Daniel; Guiraudon, Gerard M.; Jones, Doug L.; Chu, Michael W.; Holdsworth, David W.; Peters, Terry M.

    2011-03-01

    This study assesses the accuracy of a new transesophageal (TEE) ultrasound (US) fluoroscopy registration technique designed to guide percutaneous aortic valve replacement. In this minimally invasive procedure, a valve is inserted into the aortic annulus via a catheter. Navigation and positioning of the valve is guided primarily by intra-operative fluoroscopy. Poor anatomical visualization of the aortic root region can result in incorrect positioning, leading to heart valve embolization, obstruction of the coronary ostia and acute kidney injury. The use of TEE US images to augment intra-operative fluoroscopy provides significant improvements to image-guidance. Registration is achieved using an image-based TEE probe tracking technique and US calibration. TEE probe tracking is accomplished using a single-perspective pose estimation algorithm. Pose estimation from a single image allows registration to be achieved using only images collected in standard OR workflow. Accuracy of this registration technique is assessed using three models: a point target phantom, a cadaveric porcine heart with implanted fiducials, and in-vivo porcine images. Results demonstrate that registration can be achieved with an RMS error of less than 1.5mm, which is within the clinical accuracy requirements of 5mm. US-fluoroscopy registration based on single-perspective pose estimation demonstrates promise as a method for providing guidance to percutaneous aortic valve replacement procedures. Future work will focus on real-time implementation and a visualization system that can be used in the operating room.

  5. Cortical Surface Registration for Image-Guided Neurosurgery Using Laser-Range Scanning

    PubMed Central

    Sinha, Tuhin K.; Cash, David M.; Galloway, Robert L.; Weil, Robert J.

    2013-01-01

    In this paper, a method of acquiring intraoperative data using a laser range scanner (LRS) is presented within the context of model-updated image-guided surgery. Registering textured point clouds generated by the LRS to tomographic data is explored using established point-based and surface techniques as well as a novel method that incorporates geometry and intensity information via mutual information (SurfaceMI). Phantom registration studies were performed to examine accuracy and robustness for each framework. In addition, an in vivo registration is performed to demonstrate feasibility of the data acquisition system in the operating room. Results indicate that SurfaceMI performed better in many cases than point-based (PBR) and iterative closest point (ICP) methods for registration of textured point clouds. Mean target registration error (TRE) for simulated deep tissue targets in a phantom were 1.0 ± 0.2, 2.0 ± 0.3, and 1.2 ± 0.3 mm for PBR, ICP, and SurfaceMI, respectively. With regard to in vivo registration, the mean TRE of vessel contour points for each framework was 1.9 ± 1.0, 0 9 ± 0.6, and 1.3 ± 0.5 for PBR, ICP, and SurfaceMI, respectively. The methods discussed in this paper in conjunction with the quantitative data provide impetus for using LRS technology within the model-updated image-guided surgery framework. PMID:12906252

  6. Automated patient identification and localization error detection using 2-dimensional to 3-dimensional registration of kilovoltage x-ray setup images.

    PubMed

    Lamb, James M; Agazaryan, Nzhde; Low, Daniel A

    2013-10-01

    To determine whether kilovoltage x-ray projection radiation therapy setup images could be used to perform patient identification and detect gross errors in patient setup using a computer algorithm. Three patient cohorts treated using a commercially available image guided radiation therapy (IGRT) system that uses 2-dimensional to 3-dimensional (2D-3D) image registration were retrospectively analyzed: a group of 100 cranial radiation therapy patients, a group of 100 prostate cancer patients, and a group of 83 patients treated for spinal lesions. The setup images were acquired using fixed in-room kilovoltage imaging systems. In the prostate and cranial patient groups, localizations using image registration were performed between computed tomography (CT) simulation images from radiation therapy planning and setup x-ray images corresponding both to the same patient and to different patients. For the spinal patients, localizations were performed to the correct vertebral body, and to an adjacent vertebral body, using planning CTs and setup x-ray images from the same patient. An image similarity measure used by the IGRT system image registration algorithm was extracted from the IGRT system log files and evaluated as a discriminant for error detection. A threshold value of the similarity measure could be chosen to separate correct and incorrect patient matches and correct and incorrect vertebral body localizations with excellent accuracy for these patient cohorts. A 10-fold cross-validation using linear discriminant analysis yielded misclassification probabilities of 0.000, 0.0045, and 0.014 for the cranial, prostate, and spinal cases, respectively. An automated measure of the image similarity between x-ray setup images and corresponding planning CT images could be used to perform automated patient identification and detection of localization errors in radiation therapy treatments. Copyright © 2013 Elsevier Inc. All rights reserved.

  7. An augmented parametric response map with consideration of image registration error: towards guidance of locally adaptive radiotherapy

    NASA Astrophysics Data System (ADS)

    Lausch, Anthony; Chen, Jeff; Ward, Aaron D.; Gaede, Stewart; Lee, Ting-Yim; Wong, Eugene

    2014-11-01

    Parametric response map (PRM) analysis is a voxel-wise technique for predicting overall treatment outcome, which shows promise as a tool for guiding personalized locally adaptive radiotherapy (RT). However, image registration error (IRE) introduces uncertainty into this analysis which may limit its use for guiding RT. Here we extend the PRM method to include an IRE-related PRM analysis confidence interval and also incorporate multiple graded classification thresholds to facilitate visualization. A Gaussian IRE model was used to compute an expected value and confidence interval for PRM analysis. The augmented PRM (A-PRM) was evaluated using CT-perfusion functional image data from patients treated with RT for glioma and hepatocellular carcinoma. Known rigid IREs were simulated by applying one thousand different rigid transformations to each image set. PRM and A-PRM analyses of the transformed images were then compared to analyses of the original images (ground truth) in order to investigate the two methods in the presence of controlled IRE. The A-PRM was shown to help visualize and quantify IRE-related analysis uncertainty. The use of multiple graded classification thresholds also provided additional contextual information which could be useful for visually identifying adaptive RT targets (e.g. sub-volume boosts). The A-PRM should facilitate reliable PRM guided adaptive RT by allowing the user to identify if a patient’s unique IRE-related PRM analysis uncertainty has the potential to influence target delineation.

  8. A Bayesian nonrigid registration method to enhance intraoperative target definition in image-guided prostate procedures through uncertainty characterization

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Pursley, Jennifer; Risholm, Petter; Fedorov, Andriy

    2012-11-15

    observed variation in the shape and volume of the segmented prostate in diagnostic and intraprocedural images. The probabilistic method allowed us to convey registration results in terms of posterior distributions, with the dispersion providing a patient-specific estimate of the registration uncertainty. The median of the predictive distance distribution between the deformed prostate boundary and the segmented boundary was Less-Than-Or-Slanted-Equal-To 3 mm (95th percentiles within {+-}4 mm) for all ten patients. The accuracy and precision of the internal deformation was evaluated by comparing the posterior predictive distance distribution for the CZ-PZ interface for each patient, with the median distance ranging from -0.6 to 2.4 mm. Posterior predictive distances between naturally occurring landmarks showed registration errors of Less-Than-Or-Slanted-Equal-To 5 mm in any direction. The uncertainty was not a global measure, but instead was local and varied throughout the registration region. Registration uncertainties were largest in the apical region of the prostate. Conclusions: Using a Bayesian nonrigid registration method, the authors determined the posterior distribution on deformations between diagnostic and intraprocedural MR images and quantified the uncertainty in the registration results. The feasibility of this approach was tested and results were positive. The probabilistic framework allows us to evaluate both patient-specific and location-specific estimates of the uncertainty in the registration result. Although the framework was tested on MR-guided procedures, the preliminary results suggest that it may be applied to TRUS-guided procedures as well, where the addition of diagnostic MR information may have a larger impact on target definition and clinical guidance.« less

  9. A study on the theoretical and practical accuracy of conoscopic holography-based surface measurements: toward image registration in minimally invasive surgery†

    PubMed Central

    Burgner, J.; Simpson, A. L.; Fitzpatrick, J. M.; Lathrop, R. A.; Herrell, S. D.; Miga, M. I.; Webster, R. J.

    2013-01-01

    Background Registered medical images can assist with surgical navigation and enable image-guided therapy delivery. In soft tissues, surface-based registration is often used and can be facilitated by laser surface scanning. Tracked conoscopic holography (which provides distance measurements) has been recently proposed as a minimally invasive way to obtain surface scans. Moving this technique from concept to clinical use requires a rigorous accuracy evaluation, which is the purpose of our paper. Methods We adapt recent non-homogeneous and anisotropic point-based registration results to provide a theoretical framework for predicting the accuracy of tracked distance measurement systems. Experiments are conducted a complex objects of defined geometry, an anthropomorphic kidney phantom and a human cadaver kidney. Results Experiments agree with model predictions, producing point RMS errors consistently < 1 mm, surface-based registration with mean closest point error < 1 mm in the phantom and a RMS target registration error of 0.8 mm in the human cadaver kidney. Conclusions Tracked conoscopic holography is clinically viable; it enables minimally invasive surface scan accuracy comparable to current clinical methods that require open surgery. PMID:22761086

  10. Analysis of deformable image registration accuracy using computational modeling

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhong Hualiang; Kim, Jinkoo; Chetty, Indrin J.

    2010-03-15

    Computer aided modeling of anatomic deformation, allowing various techniques and protocols in radiation therapy to be systematically verified and studied, has become increasingly attractive. In this study the potential issues in deformable image registration (DIR) were analyzed based on two numerical phantoms: One, a synthesized, low intensity gradient prostate image, and the other a lung patient's CT image data set. Each phantom was modeled with region-specific material parameters with its deformation solved using a finite element method. The resultant displacements were used to construct a benchmark to quantify the displacement errors of the Demons and B-Spline-based registrations. The results showmore » that the accuracy of these registration algorithms depends on the chosen parameters, the selection of which is closely associated with the intensity gradients of the underlying images. For the Demons algorithm, both single resolution (SR) and multiresolution (MR) registrations required approximately 300 iterations to reach an accuracy of 1.4 mm mean error in the lung patient's CT image (and 0.7 mm mean error averaged in the lung only). For the low gradient prostate phantom, these algorithms (both SR and MR) required at least 1600 iterations to reduce their mean errors to 2 mm. For the B-Spline algorithms, best performance (mean errors of 1.9 mm for SR and 1.6 mm for MR, respectively) on the low gradient prostate was achieved using five grid nodes in each direction. Adding more grid nodes resulted in larger errors. For the lung patient's CT data set, the B-Spline registrations required ten grid nodes in each direction for highest accuracy (1.4 mm for SR and 1.5 mm for MR). The numbers of iterations or grid nodes required for optimal registrations depended on the intensity gradients of the underlying images. In summary, the performance of the Demons and B-Spline registrations have been quantitatively evaluated using numerical phantoms. The results show that

  11. Multimodal Image Registration through Simultaneous Segmentation.

    PubMed

    Aganj, Iman; Fischl, Bruce

    2017-11-01

    Multimodal image registration facilitates the combination of complementary information from images acquired with different modalities. Most existing methods require computation of the joint histogram of the images, while some perform joint segmentation and registration in alternate iterations. In this work, we introduce a new non-information-theoretical method for pairwise multimodal image registration, in which the error of segmentation - using both images - is considered as the registration cost function. We empirically evaluate our method via rigid registration of multi-contrast brain magnetic resonance images, and demonstrate an often higher registration accuracy in the results produced by the proposed technique, compared to those by several existing methods.

  12. Direct three-dimensional ultrasound-to-video registration using photoacoustic markers

    NASA Astrophysics Data System (ADS)

    Cheng, Alexis; Kang, Jin U.; Taylor, Russell H.; Boctor, Emad M.

    2013-06-01

    Modern surgical procedures often have a fusion of video and other imaging modalities to provide the surgeon with information support. This requires interventional guidance equipment and surgical navigation systems to register different tools and devices together, such as stereoscopic endoscopes and ultrasound (US) transducers. In this work, the focus is specifically on the registration between these two devices. Electromagnetic and optical trackers are typically used to acquire this registration, but they have various drawbacks typically leading to target registration errors (TRE) of approximately 3 mm. We introduce photoacoustic markers for direct three-dimensional (3-D) US-to-video registration. The feasibility of this method was demonstrated on synthetic and ex vivo porcine liver, kidney, and fat phantoms with an air-coupled laser and a motorized 3-D US probe. The resulting TRE for each experiment ranged from 380 to 850 μm with standard deviations ranging from 150 to 450 μm. We also discuss a roadmap to bring this system into the surgical setting and possible challenges along the way.

  13. Enhanced Optical Head Tracking for Cranial Radiation Therapy: Supporting Surface Registration by Cutaneous Structures

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wissel, Tobias, E-mail: wissel@rob.uni-luebeck.de; Graduate School for Computing in Medicine and Life Science, University of Lübeck, Lübeck; Stüber, Patrick

    2016-06-01

    Purpose: To support surface registration in cranial radiation therapy by structural information. The risk for spatial ambiguities is minimized by using tissue thickness variations predicted from backscattered near-infrared (NIR) light from the forehead. Methods and Materials: In a pilot study we recorded NIR surface scans by laser triangulation from 30 volunteers of different skin type. A ground truth for the soft-tissue thickness was segmented from MR scans. After initially matching the NIR scans to the MR reference, Gaussian processes were trained to predict tissue thicknesses from NIR backscatter. Moreover, motion starting from this initial registration was simulated by 5000 randommore » transformations of the NIR scan away from the MR reference. Re-registration to the MR scan was compared with and without tissue thickness support. Results: By adding prior knowledge to the backscatter features, such as incident angle and neighborhood information in the scanning grid, we showed that tissue thickness can be predicted with mean errors of <0.2 mm, irrespective of the skin type. With this additional information, the average registration error improved from 3.4 mm to 0.48 mm by a factor of 7. Misalignments of more than 1 mm were almost thoroughly (98.9%) pushed below 1 mm. Conclusions: For almost all cases tissue-enhanced matching achieved better results than purely spatial registration. Ambiguities can be minimized if the cutaneous structures do not agree. This valuable support for surface registration increases tracking robustness and avoids misalignment of tumor targets far from the registration site.« less

  14. A gaussian mixture + demons deformable registration method for cone-beam CT-guided robotic transoral base-of-tongue surgery

    NASA Astrophysics Data System (ADS)

    Reaungamornrat, S.; Liu, W. P.; Schafer, S.; Otake, Y.; Nithiananthan, S.; Uneri, A.; Richmon, J.; Sorger, J.; Siewerdsen, J. H.; Taylor, R. H.

    2013-03-01

    Purpose: An increasingly popular minimally invasive approach to resection of oropharyngeal / base-of-tongue cancer is made possible by a transoral technique conducted with the assistance of a surgical robot. However, the highly deformed surgical setup (neck flexed, mouth open, and tongue retracted) compared to the typical patient orientation in preoperative images poses a challenge to guidance and localization of the tumor target and adjacent critical anatomy. Intraoperative cone-beam CT (CBCT) can account for such deformation, but due to the low contrast of soft-tissue in CBCT images, direct localization of the target and critical tissues in CBCT images can be difficult. Such structures may be more readily delineated in preoperative CT or MR images, so a method to deformably register such information to intraoperative CBCT could offer significant value. This paper details the initial implementation of a deformable registration framework to align preoperative images with the deformed intraoperative scene and gives preliminary evaluation of the geometric accuracy of registration in CBCT-guided TORS. Method: The deformable registration aligns preoperative CT or MR to intraoperative CBCT by integrating two established approaches. The volume of interest is first segmented (specifically, the region of the tongue from the tip to the hyoid), and a Gaussian mixture (GM) mode1 of surface point clouds is used for rigid initialization (GMRigid) as well as an initial deformation (GMNonRigid). Next, refinement of the registration is performed using the Demons algorithm applied to distance transformations of the GM-registered and CBCT volumes. The registration accuracy of the framework was quantified in preliminary studies using a cadaver emulating preoperative and intraoperative setups. Geometric accuracy of registration was quantified in terms of target registration error (TRE) and surface distance error. Result: With each

  15. Cost-effective surgical registration using consumer depth cameras

    NASA Astrophysics Data System (ADS)

    Potter, Michael; Yaniv, Ziv

    2016-03-01

    The high costs associated with technological innovation have been previously identified as both a major contributor to the rise of health care expenses, and as a limitation for widespread adoption of new technologies. In this work we evaluate the use of two consumer grade depth cameras, the Microsoft Kinect v1 and 3DSystems Sense, as a means for acquiring point clouds for registration. These devices have the potential to replace professional grade laser range scanning devices in medical interventions that do not require sub-millimetric registration accuracy, and may do so at a significantly reduced cost. To facilitate the use of these devices we have developed a near real-time (1-4 sec/frame) rigid registration framework combining several alignment heuristics with the Iterative Closest Point (ICP) algorithm. Using nearest neighbor registration error as our evaluation criterion we found the optimal scanning distances for the Sense and Kinect to be 50-60cm and 70-80cm respectively. When imaging a skull phantom at these distances, RMS error values of 1.35mm and 1.14mm were obtained. The registration framework was then evaluated using cranial MR scans of two subjects. For the first subject, the RMS error using the Sense was 1.28 +/- 0.01 mm. Using the Kinect this error was 1.24 +/- 0.03 mm. For the second subject, whose MR scan was significantly corrupted by metal implants, the errors increased to 1.44 +/- 0.03 mm and 1.74 +/- 0.06 mm but the system nonetheless performed within acceptable bounds.

  16. Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model.

    PubMed

    Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher; Gail, Alexander

    2015-04-01

    Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement ("jump") consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. Copyright © 2015 the American Physiological Society.

  17. Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model

    PubMed Central

    Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher

    2015-01-01

    Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement (“jump”) consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. PMID:25609106

  18. Combination of intensity-based image registration with 3D simulation in radiation therapy.

    PubMed

    Li, Pan; Malsch, Urban; Bendl, Rolf

    2008-09-07

    Modern techniques of radiotherapy like intensity modulated radiation therapy (IMRT) make it possible to deliver high dose to tumors of different irregular shapes at the same time sparing surrounding healthy tissue. However, internal tumor motion makes precise calculation of the delivered dose distribution challenging. This makes analysis of tumor motion necessary. One way to describe target motion is using image registration. Many registration methods have already been developed previously. However, most of them belong either to geometric approaches or to intensity approaches. Methods which take account of anatomical information and results of intensity matching can greatly improve the results of image registration. Based on this idea, a combined method of image registration followed by 3D modeling and simulation was introduced in this project. Experiments were carried out for five patients 4DCT lung datasets. In the 3D simulation, models obtained from images of end-exhalation were deformed to the state of end-inhalation. Diaphragm motions were around -25 mm in the cranial-caudal (CC) direction. To verify the quality of our new method, displacements of landmarks were calculated and compared with measurements in the CT images. Improvement of accuracy after simulations has been shown compared to the results obtained only by intensity-based image registration. The average improvement was 0.97 mm. The average Euclidean error of the combined method was around 3.77 mm. Unrealistic motions such as curl-shaped deformations in the results of image registration were corrected. The combined method required less than 30 min. Our method provides information about the deformation of the target volume, which we need for dose optimization and target definition in our planning system.

  19. The registration of non-cooperative moving targets laser point cloud in different view point

    NASA Astrophysics Data System (ADS)

    Wang, Shuai; Sun, Huayan; Guo, Huichao

    2018-01-01

    Non-cooperative moving target multi-view cloud registration is the key technology of 3D reconstruction of laser threedimension imaging. The main problem is that the density changes greatly and noise exists under different acquisition conditions of point cloud. In this paper, firstly, the feature descriptor is used to find the most similar point cloud, and then based on the registration algorithm of region segmentation, the geometric structure of the point is extracted by the geometric similarity between point and point, The point cloud is divided into regions based on spectral clustering, feature descriptors are created for each region, searching to find the most similar regions in the most similar point of view cloud, and then aligning the pair of point clouds by aligning their minimum bounding boxes. Repeat the above steps again until registration of all point clouds is completed. Experiments show that this method is insensitive to the density of point clouds and performs well on the noise of laser three-dimension imaging.

  20. Biomechanical deformable image registration of longitudinal lung CT images using vessel information

    NASA Astrophysics Data System (ADS)

    Cazoulat, Guillaume; Owen, Dawn; Matuszak, Martha M.; Balter, James M.; Brock, Kristy K.

    2016-07-01

    Spatial correlation of lung tissue across longitudinal images, as the patient responds to treatment, is a critical step in adaptive radiotherapy. The goal of this work is to expand a biomechanical model-based deformable registration algorithm (Morfeus) to achieve accurate registration in the presence of significant anatomical changes. Six lung cancer patients previously treated with conventionally fractionated radiotherapy were retrospectively evaluated. Exhale CT scans were obtained at treatment planning and following three weeks of treatment. For each patient, the planning CT was registered to the follow-up CT using Morfeus, a biomechanical model-based deformable registration algorithm. To model the complex response of the lung, an extension to Morfeus has been developed: an initial deformation was estimated with Morfeus consisting of boundary conditions on the chest wall and incorporating a sliding interface with the lungs. It was hypothesized that the addition of boundary conditions based on vessel tree matching would provide a robust reduction of the residual registration error. To achieve this, the vessel trees were segmented on the two images by thresholding a vesselness image based on the Hessian matrix’s eigenvalues. For each point on the reference vessel tree centerline, the displacement vector was estimated by applying a variant of the Demons registration algorithm between the planning CT and the deformed follow-up CT. An expert independently identified corresponding landmarks well distributed in the lung to compute target registration errors (TRE). The TRE was: 5.8+/- 2.9 , 3.4+/- 2.3 and 1.6+/- 1.3 mm after rigid registration, Morfeus and Morfeus with boundary conditions on the vessel tree, respectively. In conclusion, the addition of boundary conditions on the vessels significantly improved the accuracy in modeling the response of the lung and tumor over the course of radiotherapy. Minimizing and modeling these geometrical uncertainties will enable

  1. A material sensitivity study on the accuracy of deformable organ registration using linear biomechanical models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chi, Y.; Liang, J.; Yan, D.

    2006-02-15

    Model-based deformable organ registration techniques using the finite element method (FEM) have recently been investigated intensively and applied to image-guided adaptive radiotherapy (IGART). These techniques assume that human organs are linearly elastic material, and their mechanical properties are predetermined. Unfortunately, the accurate measurement of the tissue material properties is challenging and the properties usually vary between patients. A common issue is therefore the achievable accuracy of the calculation due to the limited access to tissue elastic material constants. In this study, we performed a systematic investigation on this subject based on tissue biomechanics and computer simulations to establish the relationshipsmore » between achievable registration accuracy and tissue mechanical and organ geometrical properties. Primarily we focused on image registration for three organs: rectal wall, bladder wall, and prostate. The tissue anisotropy due to orientation preference in tissue fiber alignment is captured by using an orthotropic or a transversely isotropic elastic model. First we developed biomechanical models for the rectal wall, bladder wall, and prostate using simplified geometries and investigated the effect of varying material parameters on the resulting organ deformation. Then computer models based on patient image data were constructed, and image registrations were performed. The sensitivity of registration errors was studied by perturbating the tissue material properties from their mean values while fixing the boundary conditions. The simulation results demonstrated that registration error for a subvolume increases as its distance from the boundary increases. Also, a variable associated with material stability was found to be a dominant factor in registration accuracy in the context of material uncertainty. For hollow thin organs such as rectal walls and bladder walls, the registration errors are limited. Given 30% in material

  2. Accurate CT-MR image registration for deep brain stimulation: a multi-observer evaluation study

    NASA Astrophysics Data System (ADS)

    Rühaak, Jan; Derksen, Alexander; Heldmann, Stefan; Hallmann, Marc; Meine, Hans

    2015-03-01

    Since the first clinical interventions in the late 1980s, Deep Brain Stimulation (DBS) of the subthalamic nucleus has evolved into a very effective treatment option for patients with severe Parkinson's disease. DBS entails the implantation of an electrode that performs high frequency stimulations to a target area deep inside the brain. A very accurate placement of the electrode is a prerequisite for positive therapy outcome. The assessment of the intervention result is of central importance in DBS treatment and involves the registration of pre- and postinterventional scans. In this paper, we present an image processing pipeline for highly accurate registration of postoperative CT to preoperative MR. Our method consists of two steps: a fully automatic pre-alignment using a detection of the skull tip in the CT based on fuzzy connectedness, and an intensity-based rigid registration. The registration uses the Normalized Gradient Fields distance measure in a multilevel Gauss-Newton optimization framework and focuses on a region around the subthalamic nucleus in the MR. The accuracy of our method was extensively evaluated on 20 DBS datasets from clinical routine and compared with manual expert registrations. For each dataset, three independent registrations were available, thus allowing to relate algorithmic with expert performance. Our method achieved an average registration error of 0.95mm in the target region around the subthalamic nucleus as compared to an inter-observer variability of 1.12 mm. Together with the short registration time of about five seconds on average, our method forms a very attractive package that can be considered ready for clinical use.

  3. NOTE: Optimization of megavoltage CT scan registration settings for thoracic cases on helical tomotherapy

    NASA Astrophysics Data System (ADS)

    Woodford, Curtis; Yartsev, Slav; Van Dyk, Jake

    2007-08-01

    This study aims to investigate the settings that provide optimum registration accuracy when registering megavoltage CT (MVCT) studies acquired on tomotherapy with planning kilovoltage CT (kVCT) studies of patients with lung cancer. For each experiment, the systematic difference between the actual and planned positions of the thorax phantom was determined by setting the phantom up at the planning isocenter, generating and registering an MVCT study. The phantom was translated by 5 or 10 mm, MVCT scanned, and registration was performed again. A root-mean-square equation that calculated the residual error of the registration based on the known shift and systematic difference was used to assess the accuracy of the registration process. The phantom study results for 18 combinations of different MVCT/kVCT registration options are presented and compared to clinical registration data from 17 lung cancer patients. MVCT studies acquired with coarse (6 mm), normal (4 mm) and fine (2 mm) slice spacings could all be registered with similar residual errors. No specific combination of resolution and fusion selection technique resulted in a lower residual error. A scan length of 6 cm with any slice spacing registered with the full image fusion selection technique and fine resolution will result in a low residual error most of the time. On average, large corrections made manually by clinicians to the automatic registration values are infrequent. Small manual corrections within the residual error averages of the registration process occur, but their impact on the average patient position is small. Registrations using the full image fusion selection technique and fine resolution of 6 cm MVCT scans with coarse slices have a low residual error, and this strategy can be clinically used for lung cancer patients treated on tomotherapy. Automatic registration values are accurate on average, and a quick verification on a sagittal MVCT slice should be enough to detect registration outliers.

  4. Nonrigid liver registration for image-guided surgery using partial surface data: a novel iterative approach

    NASA Astrophysics Data System (ADS)

    Rucker, D. Caleb; Wu, Yifei; Ondrake, Janet E.; Pheiffer, Thomas S.; Simpson, Amber L.; Miga, Michael I.

    2013-03-01

    In the context of open abdominal image-guided liver surgery, the efficacy of an image-guidance system relies on its ability to (1) accurately depict tool locations with respect to the anatomy, and (2) maintain the work flow of the surgical team. Laser-range scanned (LRS) partial surface measurements can be taken intraoperatively with relatively little impact on the surgical work flow, as opposed to other intraoperative imaging modalities. Previous research has demonstrated that this kind of partial surface data may be (1) used to drive a rigid registration of the preoperative CT image volume to intraoperative patient space, and (2) extrapolated and combined with a tissue-mechanics-based organ model to drive a non-rigid registration, thus compensating for organ deformations. In this paper we present a novel approach for intraoperative nonrigid liver registration which iteratively reconstructs a displacement field on the posterior side of the organ in order to minimize the error between the deformed model and the intraopreative surface data. Experimental results with a phantom liver undergoing large deformations demonstrate that this method achieves target registration errors (TRE) with a mean of 4.0 mm in the prediction of a set of 58 locations inside the phantom, which represents a 50% improvement over rigid registration alone, and a 44% improvement over the prior non-iterative single-solve method of extrapolating boundary conditions via a surface Laplacian.

  5. Investigation of Parallax Issues for Multi-Lens Multispectral Camera Band Co-Registration

    NASA Astrophysics Data System (ADS)

    Jhan, J. P.; Rau, J. Y.; Haala, N.; Cramer, M.

    2017-08-01

    The multi-lens multispectral cameras (MSCs), such as Micasense Rededge and Parrot Sequoia, can record multispectral information by each separated lenses. With their lightweight and small size, which making they are more suitable for mounting on an Unmanned Aerial System (UAS) to collect high spatial images for vegetation investigation. However, due to the multi-sensor geometry of multi-lens structure induces significant band misregistration effects in original image, performing band co-registration is necessary in order to obtain accurate spectral information. A robust and adaptive band-to-band image transform (RABBIT) is proposed to perform band co-registration of multi-lens MSCs. First is to obtain the camera rig information from camera system calibration, and utilizes the calibrated results for performing image transformation and lens distortion correction. Since the calibration uncertainty leads to different amount of systematic errors, the last step is to optimize the results in order to acquire a better co-registration accuracy. Due to the potential issues of parallax that will cause significant band misregistration effects when images are closer to the targets, four datasets thus acquired from Rededge and Sequoia were applied to evaluate the performance of RABBIT, including aerial and close-range imagery. From the results of aerial images, it shows that RABBIT can achieve sub-pixel accuracy level that is suitable for the band co-registration purpose of any multi-lens MSC. In addition, the results of close-range images also has same performance, if we focus on the band co-registration on specific target for 3D modelling, or when the target has equal distance to the camera.

  6. Registration performance on EUV masks using high-resolution registration metrology

    NASA Astrophysics Data System (ADS)

    Steinert, Steffen; Solowan, Hans-Michael; Park, Jinback; Han, Hakseung; Beyer, Dirk; Scherübl, Thomas

    2016-10-01

    Next-generation lithography based on EUV continues to move forward to high-volume manufacturing. Given the technical challenges and the throughput concerns a hybrid approach with 193 nm immersion lithography is expected, at least in the initial state. Due to the increasing complexity at smaller nodes a multitude of different masks, both DUV (193 nm) and EUV (13.5 nm) reticles, will then be required in the lithography process-flow. The individual registration of each mask and the resulting overlay error are of crucial importance in order to ensure proper functionality of the chips. While registration and overlay metrology on DUV masks has been the standard for decades, this has yet to be demonstrated on EUV masks. Past generations of mask registration tools were not necessarily limited in their tool stability, but in their resolution capabilities. The scope of this work is an image placement investigation of high-end EUV masks together with a registration and resolution performance qualification. For this we employ a new generation registration metrology system embedded in a production environment for full-spec EUV masks. This paper presents excellent registration performance not only on standard overlay markers but also on more sophisticated e-beam calibration patterns.

  7. Model-based registration for assessment of spinal deformities in idiopathic scoliosis

    NASA Astrophysics Data System (ADS)

    Forsberg, Daniel; Lundström, Claes; Andersson, Mats; Knutsson, Hans

    2014-01-01

    Detailed analysis of spinal deformity is important within orthopaedic healthcare, in particular for assessment of idiopathic scoliosis. This paper addresses this challenge by proposing an image analysis method, capable of providing a full three-dimensional spine characterization. The proposed method is based on the registration of a highly detailed spine model to image data from computed tomography. The registration process provides an accurate segmentation of each individual vertebra and the ability to derive various measures describing the spinal deformity. The derived measures are estimated from landmarks attached to the spine model and transferred to the patient data according to the registration result. Evaluation of the method provides an average point-to-surface error of 0.9 mm ± 0.9 (comparing segmentations), and an average target registration error of 2.3 mm ± 1.7 (comparing landmarks). Comparing automatic and manual measurements of axial vertebral rotation provides a mean absolute difference of 2.5° ± 1.8, which is on a par with other computerized methods for assessing axial vertebral rotation. A significant advantage of our method, compared to other computerized methods for rotational measurements, is that it does not rely on vertebral symmetry for computing the rotational measures. The proposed method is fully automatic and computationally efficient, only requiring three to four minutes to process an entire image volume covering vertebrae L5 to T1. Given the use of landmarks, the method can be readily adapted to estimate other measures describing a spinal deformity by changing the set of employed landmarks. In addition, the method has the potential to be utilized for accurate segmentations of the vertebrae in routine computed tomography examinations, given the relatively low point-to-surface error.

  8. Intensity-based 2D 3D registration for lead localization in robot guided deep brain stimulation

    NASA Astrophysics Data System (ADS)

    Hunsche, Stefan; Sauner, Dieter; El Majdoub, Faycal; Neudorfer, Clemens; Poggenborg, Jörg; Goßmann, Axel; Maarouf, Mohammad

    2017-03-01

    Intraoperative assessment of lead localization has become a standard procedure during deep brain stimulation surgery in many centers, allowing immediate verification of targeting accuracy and, if necessary, adjustment of the trajectory. The most suitable imaging modality to determine lead positioning, however, remains controversially discussed. Current approaches entail the implementation of computed tomography and magnetic resonance imaging. In the present study, we adopted the technique of intensity-based 2D 3D registration that is commonly employed in stereotactic radiotherapy and spinal surgery. For this purpose, intraoperatively acquired 2D x-ray images were fused with preoperative 3D computed tomography (CT) data to verify lead placement during stereotactic robot assisted surgery. Accuracy of lead localization determined from 2D 3D registration was compared to conventional 3D 3D registration in a subsequent patient study. The mean Euclidian distance of lead coordinates estimated from intensity-based 2D 3D registration versus flat-panel detector CT 3D 3D registration was 0.7 mm  ±  0.2 mm. Maximum values of these distances amounted to 1.2 mm. To further investigate 2D 3D registration a simulation study was conducted, challenging two observers to visually assess artificially generated 2D 3D registration errors. 95% of deviation simulations, which were visually assessed as sufficient, had a registration error below 0.7 mm. In conclusion, 2D 3D intensity-based registration revealed high accuracy and reliability during robot guided stereotactic neurosurgery and holds great potential as a low dose, cost effective means for intraoperative lead localization.

  9. Image-guided ex-vivo targeting accuracy using a laparoscopic tissue localization system

    NASA Astrophysics Data System (ADS)

    Bieszczad, Jerry; Friets, Eric; Knaus, Darin; Rauth, Thomas; Herline, Alan; Miga, Michael; Galloway, Robert; Kynor, David

    2007-03-01

    In image-guided surgery, discrete fiducials are used to determine a spatial registration between the location of surgical tools in the operating theater and the location of targeted subsurface lesions and critical anatomic features depicted in preoperative tomographic image data. However, the lack of readily localized anatomic landmarks has greatly hindered the use of image-guided surgery in minimally invasive abdominal procedures. To address these needs, we have previously described a laser-based system for localization of internal surface anatomy using conventional laparoscopes. During a procedure, this system generates a digitized, three-dimensional representation of visible anatomic surfaces in the abdominal cavity. This paper presents the results of an experiment utilizing an ex-vivo bovine liver to assess subsurface targeting accuracy achieved using our system. During the experiment, several radiopaque targets were inserted into the liver parenchyma. The location of each target was recorded using an optically-tracked insertion probe. The liver surface was digitized using our system, and registered with the liver surface extracted from post-procedure CT images. This surface-based registration was then used to transform the position of the inserted targets into the CT image volume. The target registration error (TRE) achieved using our surface-based registration (given a suitable registration algorithm initialization) was 2.4 mm +/- 1.0 mm. A comparable TRE (2.6 mm +/- 1.7 mm) was obtained using a registration based on traditional fiducial markers placed on the surface of the same liver. These results indicate the potential of fiducial-free, surface-to-surface registration for image-guided lesion targeting in minimally invasive abdominal surgery.

  10. MIND Demons: Symmetric Diffeomorphic Deformable Registration of MR and CT for Image-Guided Spine Surgery.

    PubMed

    Reaungamornrat, Sureerat; De Silva, Tharindu; Uneri, Ali; Vogt, Sebastian; Kleinszig, Gerhard; Khanna, Akhil J; Wolinsky, Jean-Paul; Prince, Jerry L; Siewerdsen, Jeffrey H

    2016-11-01

    Intraoperative localization of target anatomy and critical structures defined in preoperative MR/CT images can be achieved through the use of multimodality deformable registration. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality-independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. The method, called MIND Demons, finds a deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the integrated velocity fields, a modality-insensitive similarity function suitable to multimodality images, and smoothness on the diffeomorphisms themselves. Direct optimization without relying on the exponential map and stationary velocity field approximation used in conventional diffeomorphic Demons is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, normalized MI (NMI) Demons, and MIND with a diffusion-based registration method (MIND-elastic). The method yielded sub-voxel invertibility (0.008 mm) and nonzero-positive Jacobian determinants. It also showed improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.7 mm compared to 11.3, 3.1, 5.6, and 2.4 mm for MI FFD, LMI FFD, NMI Demons, and MIND-elastic methods, respectively. Validation in clinical studies demonstrated realistic deformations with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine.

  11. MIND Demons: Symmetric Diffeomorphic Deformable Registration of MR and CT for Image-Guided Spine Surgery

    PubMed Central

    Reaungamornrat, Sureerat; De Silva, Tharindu; Uneri, Ali; Vogt, Sebastian; Kleinszig, Gerhard; Khanna, Akhil J; Wolinsky, Jean-Paul; Prince, Jerry L.

    2016-01-01

    Intraoperative localization of target anatomy and critical structures defined in preoperative MR/CT images can be achieved through the use of multimodality deformable registration. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality-independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. The method, called MIND Demons, finds a deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the integrated velocity fields, a modality-insensitive similarity function suitable to multimodality images, and smoothness on the diffeomorphisms themselves. Direct optimization without relying on the exponential map and stationary velocity field approximation used in conventional diffeomorphic Demons is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, normalized MI (NMI) Demons, and MIND with a diffusion-based registration method (MIND-elastic). The method yielded sub-voxel invertibility (0.008 mm) and nonzero-positive Jacobian determinants. It also showed improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.7 mm compared to 11.3, 3.1, 5.6, and 2.4 mm for MI FFD, LMI FFD, NMI Demons, and MIND-elastic methods, respectively. Validation in clinical studies demonstrated realistic deformations with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. PMID:27295656

  12. 40 CFR 68.160 - Registration.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... purposes of correcting minor clerical errors, updating administrative information, providing missing data... substances handled in covered processes. (b) The registration shall include the following data: (1...

  13. 40 CFR 68.160 - Registration.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... purposes of correcting minor clerical errors, updating administrative information, providing missing data... substances handled in covered processes. (b) The registration shall include the following data: (1...

  14. 40 CFR 68.160 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... purposes of correcting minor clerical errors, updating administrative information, providing missing data... substances handled in covered processes. (b) The registration shall include the following data: (1...

  15. a Global Registration Algorithm of the Single-Closed Ring Multi-Stations Point Cloud

    NASA Astrophysics Data System (ADS)

    Yang, R.; Pan, L.; Xiang, Z.; Zeng, H.

    2018-04-01

    Aimed at the global registration problem of the single-closed ring multi-stations point cloud, a formula in order to calculate the error of rotation matrix was constructed according to the definition of error. The global registration algorithm of multi-station point cloud was derived to minimize the error of rotation matrix. And fast-computing formulas of transformation matrix with whose implementation steps and simulation experiment scheme was given. Compared three different processing schemes of multi-station point cloud, the experimental results showed that the effectiveness of the new global registration method was verified, and it could effectively complete the global registration of point cloud.

  16. 2D-3D rigid registration to compensate for prostate motion during 3D TRUS-guided biopsy.

    PubMed

    De Silva, Tharindu; Fenster, Aaron; Cool, Derek W; Gardi, Lori; Romagnoli, Cesare; Samarabandu, Jagath; Ward, Aaron D

    2013-02-01

    Three-dimensional (3D) transrectal ultrasound (TRUS)-guided systems have been developed to improve targeting accuracy during prostate biopsy. However, prostate motion during the procedure is a potential source of error that can cause target misalignments. The authors present an image-based registration technique to compensate for prostate motion by registering the live two-dimensional (2D) TRUS images acquired during the biopsy procedure to a preacquired 3D TRUS image. The registration must be performed both accurately and quickly in order to be useful during the clinical procedure. The authors implemented an intensity-based 2D-3D rigid registration algorithm optimizing the normalized cross-correlation (NCC) metric using Powell's method. The 2D TRUS images acquired during the procedure prior to biopsy gun firing were registered to the baseline 3D TRUS image acquired at the beginning of the procedure. The accuracy was measured by calculating the target registration error (TRE) using manually identified fiducials within the prostate; these fiducials were used for validation only and were not provided as inputs to the registration algorithm. They also evaluated the accuracy when the registrations were performed continuously throughout the biopsy by acquiring and registering live 2D TRUS images every second. This measured the improvement in accuracy resulting from performing the registration, continuously compensating for motion during the procedure. To further validate the method using a more challenging data set, registrations were performed using 3D TRUS images acquired by intentionally exerting different levels of ultrasound probe pressures in order to measure the performance of our algorithm when the prostate tissue was intentionally deformed. In this data set, biopsy scenarios were simulated by extracting 2D frames from the 3D TRUS images and registering them to the baseline 3D image. A graphics processing unit (GPU)-based implementation was used to improve the

  17. Determination of optimal ultrasound planes for the initialisation of image registration during endoscopic ultrasound-guided procedures.

    PubMed

    Bonmati, Ester; Hu, Yipeng; Gibson, Eli; Uribarri, Laura; Keane, Geri; Gurusami, Kurinchi; Davidson, Brian; Pereira, Stephen P; Clarkson, Matthew J; Barratt, Dean C

    2018-06-01

    Navigation of endoscopic ultrasound (EUS)-guided procedures of the upper gastrointestinal (GI) system can be technically challenging due to the small fields-of-view of ultrasound and optical devices, as well as the anatomical variability and limited number of orienting landmarks during navigation. Co-registration of an EUS device and a pre-procedure 3D image can enhance the ability to navigate. However, the fidelity of this contextual information depends on the accuracy of registration. The purpose of this study was to develop and test the feasibility of a simulation-based planning method for pre-selecting patient-specific EUS-visible anatomical landmark locations to maximise the accuracy and robustness of a feature-based multimodality registration method. A registration approach was adopted in which landmarks are registered to anatomical structures segmented from the pre-procedure volume. The predicted target registration errors (TREs) of EUS-CT registration were estimated using simulated visible anatomical landmarks and a Monte Carlo simulation of landmark localisation error. The optimal planes were selected based on the 90th percentile of TREs, which provide a robust and more accurate EUS-CT registration initialisation. The method was evaluated by comparing the accuracy and robustness of registrations initialised using optimised planes versus non-optimised planes using manually segmented CT images and simulated ([Formula: see text]) or retrospective clinical ([Formula: see text]) EUS landmarks. The results show a lower 90th percentile TRE when registration is initialised using the optimised planes compared with a non-optimised initialisation approach (p value [Formula: see text]). The proposed simulation-based method to find optimised EUS planes and landmarks for EUS-guided procedures may have the potential to improve registration accuracy. Further work will investigate applying the technique in a clinical setting.

  18. Skull registration for prone patient position using tracked ultrasound

    NASA Astrophysics Data System (ADS)

    Underwood, Grace; Ungi, Tamas; Baum, Zachary; Lasso, Andras; Kronreif, Gernot; Fichtinger, Gabor

    2017-03-01

    PURPOSE: Tracked navigation has become prevalent in neurosurgery. Problems with registration of a patient and a preoperative image arise when the patient is in a prone position. Surfaces accessible to optical tracking on the back of the head are unreliable for registration. We investigated the accuracy of surface-based registration using points accessible through tracked ultrasound. Using ultrasound allows access to bone surfaces that are not available through optical tracking. Tracked ultrasound could eliminate the need to work (i) under the table for registration and (ii) adjust the tracker between surgery and registration. In addition, tracked ultrasound could provide a non-invasive method in comparison to an alternative method of registration involving screw implantation. METHODS: A phantom study was performed to test the feasibility of tracked ultrasound for registration. An initial registration was performed to partially align the pre-operative computer tomography data and skull phantom. The initial registration was performed by an anatomical landmark registration. Surface points accessible by tracked ultrasound were collected and used to perform an Iterative Closest Point Algorithm. RESULTS: When the surface registration was compared to a ground truth landmark registration, the average TRE was found to be 1.6+/-0.1mm and the average distance of points off the skull surface was 0.6+/-0.1mm. CONCLUSION: The use of tracked ultrasound is feasible for registration of patients in prone position and eliminates the need to perform registration under the table. The translational component of error found was minimal. Therefore, the amount of TRE in registration is due to a rotational component of error.

  19. A Robust Linear Feature-Based Procedure for Automated Registration of Point Clouds

    PubMed Central

    Poreba, Martyna; Goulette, François

    2015-01-01

    With the variety of measurement techniques available on the market today, fusing multi-source complementary information into one dataset is a matter of great interest. Target-based, point-based and feature-based methods are some of the approaches used to place data in a common reference frame by estimating its corresponding transformation parameters. This paper proposes a new linear feature-based method to perform accurate registration of point clouds, either in 2D or 3D. A two-step fast algorithm called Robust Line Matching and Registration (RLMR), which combines coarse and fine registration, was developed. The initial estimate is found from a triplet of conjugate line pairs, selected by a RANSAC algorithm. Then, this transformation is refined using an iterative optimization algorithm. Conjugates of linear features are identified with respect to a similarity metric representing a line-to-line distance. The efficiency and robustness to noise of the proposed method are evaluated and discussed. The algorithm is valid and ensures valuable results when pre-aligned point clouds with the same scale are used. The studies show that the matching accuracy is at least 99.5%. The transformation parameters are also estimated correctly. The error in rotation is better than 2.8% full scale, while the translation error is less than 12.7%. PMID:25594589

  20. Registration of liver images to minimally invasive intraoperative surface and subsurface data

    NASA Astrophysics Data System (ADS)

    Wu, Yifei; Rucker, D. C.; Conley, Rebekah H.; Pheiffer, Thomas S.; Simpson, Amber L.; Geevarghese, Sunil K.; Miga, Michael I.

    2014-03-01

    Laparoscopic liver resection is increasingly being performed with results comparable to open cases while incurring less trauma and reducing recovery time. The tradeoff is increased difficulty due to limited visibility and restricted freedom of movement. Image-guided surgical navigation systems have the potential to help localize anatomical features to improve procedural safety and achieve better surgical resection outcome. Previous research has demonstrated that intraoperative surface data can be used to drive a finite element tissue mechanics organ model such that high resolution preoperative scans are registered and visualized in the context of the current surgical pose. In this paper we present an investigation of using sparse data as imposed by laparoscopic limitations to drive a registration model. Non-contact laparoscopicallyacquired surface swabbing and mock-ultrasound subsurface data were used within the context of a nonrigid registration methodology to align mock deformed intraoperative surface data to the corresponding preoperative liver model as derived from pre-operative image segmentations. The mock testing setup to validate the potential of this approach used a tissue-mimicking liver phantom with a realistic abdomen-port patient configuration. Experimental results demonstrates a range of target registration errors (TRE) on the order of 5mm were achieving using only surface swab data, while use of only subsurface data yielded errors on the order of 6mm. Registrations using a combination of both datasets achieved TRE on the order of 2.5mm and represent a sizeable improvement over either dataset alone.

  1. Geometric error characterization and error budgets. [thematic mapper

    NASA Technical Reports Server (NTRS)

    Beyer, E.

    1982-01-01

    Procedures used in characterizing geometric error sources for a spaceborne imaging system are described using the LANDSAT D thematic mapper ground segment processing as the prototype. Software was tested through simulation and is undergoing tests with the operational hardware as part of the prelaunch system evaluation. Geometric accuracy specifications, geometric correction, and control point processing are discussed. Cross track and along track errors are tabulated for the thematic mapper, the spacecraft, and ground processing to show the temporal registration error budget in pixel (42.5 microrad) 90%.

  2. Evaluating the utility of 3D TRUS image information in guiding intra-procedure registration for motion compensation

    NASA Astrophysics Data System (ADS)

    De Silva, Tharindu; Cool, Derek W.; Romagnoli, Cesare; Fenster, Aaron; Ward, Aaron D.

    2014-03-01

    In targeted 3D transrectal ultrasound (TRUS)-guided biopsy, patient and prostate movement during the procedure can cause target misalignments that hinder accurate sampling of pre-planned suspicious tissue locations. Multiple solutions have been proposed for motion compensation via registration of intra-procedural TRUS images to a baseline 3D TRUS image acquired at the beginning of the biopsy procedure. While 2D TRUS images are widely used for intra-procedural guidance, some solutions utilize richer intra-procedural images such as bi- or multi-planar TRUS or 3D TRUS, acquired by specialized probes. In this work, we measured the impact of such richer intra-procedural imaging on motion compensation accuracy, to evaluate the tradeoff between cost and complexity of intra-procedural imaging versus improved motion compensation. We acquired baseline and intra-procedural 3D TRUS images from 29 patients at standard sextant-template biopsy locations. We used the planes extracted from the 3D intra-procedural scans to simulate 2D and 3D information available in different clinically relevant scenarios for registration. The registration accuracy was evaluated by calculating the target registration error (TRE) using manually identified homologous fiducial markers (micro-calcifications). Our results indicate that TRE improves gradually when the number of intra-procedural imaging planes used in registration is increased. Full 3D TRUS information helps the registration algorithm to robustly converge to more accurate solutions. These results can also inform the design of a fail-safe workflow during motion compensation in a system using a tracked 2D TRUS probe, by prescribing rotational acquisitions that can be performed quickly and easily by the physician immediately prior to needle targeting.

  3. MIND Demons for MR-to-CT Deformable Image Registration In Image-Guided Spine Surgery

    PubMed Central

    Reaungamornrat, S.; De Silva, T.; Uneri, A.; Wolinsky, J.-P.; Khanna, A. J.; Kleinszig, G.; Vogt, S.; Prince, J. L.; Siewerdsen, J. H.

    2016-01-01

    Purpose Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. Method The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. Result The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. Conclusions A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The

  4. MIND Demons for MR-to-CT Deformable Image Registration In Image-Guided Spine Surgery.

    PubMed

    Reaungamornrat, S; De Silva, T; Uneri, A; Wolinsky, J-P; Khanna, A J; Kleinszig, G; Vogt, S; Prince, J L; Siewerdsen, J H

    2016-02-27

    Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The method yields registration

  5. Interactive 3-D registration of ultrasound and magnetic resonance images based on a magnetic position sensor.

    PubMed

    Pagoulatos, N; Edwards, W S; Haynor, D R; Kim, Y

    1999-12-01

    The use of stereotactic systems has been one of the main approaches for image-based guidance of the surgical tool within the brain. The main limitation of stereotactic systems is that they are based on preoperative images that might become outdated and invalid during the course of surgery. Ultrasound (US) is considered the most practical and cost-effective intraoperative imaging modality, but US images inherently have a low signal-to-noise ratio. Integrating intraoperative US with stereotactic systems has recently been attempted. In this paper, we present a new system for interactively registering two-dimensional US and three-dimensional magnetic resonance (MR) images. This registration is based on tracking the US probe with a dc magnetic position sensor. We have performed an extensive analysis of the errors of our system by using a custom-built phantom. The registration error between the MR and the position sensor space was found to have a mean value of 1.78 mm and a standard deviation of 0.18 mm. The registration error between US and MR space was dependent on the distance of the target point from the US probe face. For a 3.5-MHz phased one-dimensional array transducer and a depth of 6 cm, the mean value of the registration error was 2.00 mm and the standard deviation was 0.75 mm. The registered MR images were reconstructed using either zeroth-order or first-order interpolation. The ease of use and the interactive nature of our system (approximately 6.5 frames/s for 344 x 310 images and first-order interpolation on a Pentium II 450 MHz) demonstrates its potential to be used in the operating room.

  6. TU-CD-BRA-01: A Novel 3D Registration Method for Multiparametric Radiological Images

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Akhbardeh, A; Parekth, VS; Jacobs, MA

    2015-06-15

    Purpose: Multiparametric and multimodality radiological imaging methods, such as, magnetic resonance imaging(MRI), computed tomography(CT), and positron emission tomography(PET), provide multiple types of tissue contrast and anatomical information for clinical diagnosis. However, these radiological modalities are acquired using very different technical parameters, e.g.,field of view(FOV), matrix size, and scan planes, which, can lead to challenges in registering the different data sets. Therefore, we developed a hybrid registration method based on 3D wavelet transformation and 3D interpolations that performs 3D resampling and rotation of the target radiological images without loss of information Methods: T1-weighted, T2-weighted, diffusion-weighted-imaging(DWI), dynamic-contrast-enhanced(DCE) MRI and PET/CT were usedmore » in the registration algorithm from breast and prostate data at 3T MRI and multimodality(PET/CT) cases. The hybrid registration scheme consists of several steps to reslice and match each modality using a combination of 3D wavelets, interpolations, and affine registration steps. First, orthogonal reslicing is performed to equalize FOV, matrix sizes and the number of slices using wavelet transformation. Second, angular resampling of the target data is performed to match the reference data. Finally, using optimized angles from resampling, 3D registration is performed using similarity transformation(scaling and translation) between the reference and resliced target volume is performed. After registration, the mean-square-error(MSE) and Dice Similarity(DS) between the reference and registered target volumes were calculated. Results: The 3D registration method registered synthetic and clinical data with significant improvement(p<0.05) of overlap between anatomical structures. After transforming and deforming the synthetic data, the MSE and Dice similarity were 0.12 and 0.99. The average improvement of the MSE in breast was 62%(0.27 to 0.10) and

  7. Results of a Multi-Institutional Benchmark Test for Cranial CT/MR Image Registration

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ulin, Kenneth; Urie, Marcia M., E-mail: murie@qarc.or; Cherlow, Joel M.

    2010-08-01

    Purpose: Variability in computed tomography/magnetic resonance imaging (CT/MR) cranial image registration was assessed using a benchmark case developed by the Quality Assurance Review Center to credential institutions for participation in Children's Oncology Group Protocol ACNS0221 for treatment of pediatric low-grade glioma. Methods and Materials: Two DICOM image sets, an MR and a CT of the same patient, were provided to each institution. A small target in the posterior occipital lobe was readily visible on two slices of the MR scan and not visible on the CT scan. Each institution registered the two scans using whatever software system and method itmore » ordinarily uses for such a case. The target volume was then contoured on the two MR slices, and the coordinates of the center of the corresponding target in the CT coordinate system were reported. The average of all submissions was used to determine the true center of the target. Results: Results are reported from 51 submissions representing 45 institutions and 11 software systems. The average error in the position of the center of the target was 1.8 mm (1 standard deviation = 2.2 mm). The least variation in position was in the lateral direction. Manual registration gave significantly better results than did automatic registration (p = 0.02). Conclusion: When MR and CT scans of the head are registered with currently available software, there is inherent uncertainty of approximately 2 mm (1 standard deviation), which should be considered when defining planning target volumes and PRVs for organs at risk on registered image sets.« less

  8. Preliminary GOES-R ABI navigation and registration assessment results

    NASA Astrophysics Data System (ADS)

    Tan, B.; Dellomo, J.; Wolfe, R. E.; Reth, A. D.

    2017-12-01

    The US Geostationary Operational Environmental Satellite - R Series (GOES-R) was launched on November 19, 2016, and was designated GOESR-16 upon reaching geostationary orbit ten days later. The Advanced Baseline Imager (ABI) is the primary instrument on the GOES-R series for imaging Earth's surface and atmosphere to aid in weather prediction and climate monitoring. We developed algorithms and software for independent verification of the ABI Image Navigation and Registration (INR). Since late January 2017, four INR metrics have been continuously generated to monitor the ABI INR performance: navigation (NAV) error, channel-to-channel registration (CCR) error, frame-to-frame registration (FFR) error, and within-frame registration (WIFR) error. In this paper, we will describe the fundamental algorithm used for the image registration and briefly discuss the processing flow of INR Performance Assessment Tool Set (IPATS) developed for ABI INR. The assessment of the accuracy shows that IPATS measurements error is about 1/20 of the size of a pixel. Then the GOES-16 NAV assessments results, the primary metric, from January to August 2017, will be presented. The INR has improved over time as post-launch tests were performed and corrections were applied. The mean NAV error of the visible and near infrared (VNIR) channels dropped from 20 μrad in January to around 5 μrad (+/-4 μrad, 1 σ) in June, while the mean NAV error of long wave infrared (LWIR) channels dropped from around 70 μrad in January to around 5 μrad (+/-15 μrad, 1 σ) in June. A full global ABI image is composed with 22 east-west direction swaths. The swath-wise NAV error analysis shows that there was some variation in the mean swath-wise NAV errors. The variations are about as much as 20% of the scene NAV mean errors. As expected, the swaths over the tropical area have far fewer valid assessments (matchups) than those in mid-latitude region due to cloud coverage. It was also found that there was a rotation

  9. Predicting target vessel location on robot-assisted coronary artery bypass graft using CT to ultrasound registration

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Cho, Daniel S.; Linte, Cristian; Chen, Elvis C. S.

    Purpose: Although robot-assisted coronary artery bypass grafting (RA-CABG) has gained more acceptance worldwide, its success still depends on the surgeon's experience and expertise, and the conversion rate to full sternotomy is in the order of 15%-25%. One of the reasons for conversion is poor pre-operative planning, which is based solely on pre-operative computed tomography (CT) images. In this paper, the authors propose a technique to estimate the global peri-operative displacement of the heart and to predict the intra-operative target vessel location, validated via both an in vitro and a clinical study. Methods: As the peri-operative heart migration during RA-CABG hasmore » never been reported in the literatures, a simple in vitro validation study was conducted using a heart phantom. To mimic the clinical workflow, a pre-operative CT as well as peri-operative ultrasound images at three different stages in the procedure (Stage{sub 0}--following intubation; Stage{sub 1}--following lung deflation; and Stage{sub 2}--following thoracic insufflation) were acquired during the experiment. Following image acquisition, a rigid-body registration using iterative closest point algorithm with the robust estimator was employed to map the pre-operative stage to each of the peri-operative ones, to estimate the heart migration and predict the peri-operative target vessel location. Moreover, a clinical validation of this technique was conducted using offline patient data, where a Monte Carlo simulation was used to overcome the limitations arising due to the invisibility of the target vessel in the peri-operative ultrasound images. Results: For the in vitro study, the computed target registration error (TRE) at Stage{sub 0}, Stage{sub 1}, and Stage{sub 2} was 2.1, 3.3, and 2.6 mm, respectively. According to the offline clinical validation study, the maximum TRE at the left anterior descending (LAD) coronary artery was 4.1 mm at Stage{sub 0}, 5.1 mm at Stage{sub 1}, and 3.4 mm at

  10. A simultaneously calibration approach for installation and attitude errors of an INS/GPS/LDS target tracker.

    PubMed

    Cheng, Jianhua; Chen, Daidai; Sun, Xiangyu; Wang, Tongda

    2015-02-04

    To obtain the absolute position of a target is one of the basic topics for non-cooperated target tracking problems. In this paper, we present a simultaneously calibration method for an Inertial navigation system (INS)/Global position system (GPS)/Laser distance scanner (LDS) integrated system based target positioning approach. The INS/GPS integrated system provides the attitude and position of observer, and LDS offers the distance between the observer and the target. The two most significant errors are taken into jointly consideration and analyzed: (1) the attitude measure error of INS/GPS; (2) the installation error between INS/GPS and LDS subsystems. Consequently, a INS/GPS/LDS based target positioning approach considering these two errors is proposed. In order to improve the performance of this approach, a novel calibration method is designed to simultaneously estimate and compensate these two main errors. Finally, simulations are conducted to access the performance of the proposed target positioning approach and the designed simultaneously calibration method.

  11. Elastic registration of prostate MR images based on state estimation of dynamical systems

    NASA Astrophysics Data System (ADS)

    Marami, Bahram; Ghoul, Suha; Sirouspour, Shahin; Capson, David W.; Davidson, Sean R. H.; Trachtenberg, John; Fenster, Aaron

    2014-03-01

    Magnetic resonance imaging (MRI) is being increasingly used for image-guided biopsy and focal therapy of prostate cancer. A combined rigid and deformable registration technique is proposed to register pre-treatment diagnostic 3T magnetic resonance (MR) images, with the identified target tumor(s), to the intra-treatment 1.5T MR images. The pre-treatment 3T images are acquired with patients in strictly supine position using an endorectal coil, while 1.5T images are obtained intra-operatively just before insertion of the ablation needle with patients in the lithotomy position. An intensity-based registration routine rigidly aligns two images in which the transformation parameters is initialized using three pairs of manually selected approximate corresponding points. The rigid registration is followed by a deformable registration algorithm employing a generic dynamic linear elastic deformation model discretized by the finite element method (FEM). The model is used in a classical state estimation framework to estimate the deformation of the prostate based on a similarity metric between pre- and intra-treatment images. Registration results using 10 sets of prostate MR images showed that the proposed method can significantly improve registration accuracy in terms of target registration error (TRE) for all prostate substructures. The root mean square (RMS) TRE of 46 manually identified fiducial points was found to be 2.40+/-1.20 mm, 2.51+/-1.20 mm, and 2.28+/-1.22mm for the whole gland (WG), central gland (CG), and peripheral zone (PZ), respectively after deformable registration. These values are improved from 3.15+/-1.60 mm, 3.09+/-1.50 mm, and 3.20+/-1.73mm in the WG, CG and PZ, respectively resulted from rigid registration. Registration results are also evaluated based on the Dice similarity coefficient (DSC), mean absolute surface distances (MAD) and maximum absolute surface distances (MAXD) of the WG and CG in the prostate images.

  12. Investigation of 3D histograms of oriented gradients for image-based registration of CT with interventional CBCT

    NASA Astrophysics Data System (ADS)

    Trimborn, Barbara; Wolf, Ivo; Abu-Sammour, Denis; Henzler, Thomas; Schad, Lothar R.; Zöllner, Frank G.

    2017-03-01

    Image registration of preprocedural contrast-enhanced CTs to intraprocedual cone-beam computed tomography (CBCT) can provide additional information for interventional liver oncology procedures such as transcatheter arterial chemoembolisation (TACE). In this paper, a novel similarity metric for gradient-based image registration is proposed. The metric relies on the patch-based computation of histograms of oriented gradients (HOG) building the basis for a feature descriptor. The metric was implemented in a framework for rigid 3D-3D-registration of pre-interventional CT with intra-interventional CBCT data obtained during the workflow of a TACE. To evaluate the performance of the new metric, the capture range was estimated based on the calculation of the mean target registration error and compared to the results obtained with a normalized cross correlation metric. The results show that 3D HOG feature descriptors are suitable as image-similarity metric and that the novel metric can compete with established methods in terms of registration accuracy

  13. Beating-heart registration for organ-mounted robots.

    PubMed

    Wood, Nathan A; Schwartzman, David; Passineau, Michael J; Moraca, Robert J; Zenati, Marco A; Riviere, Cameron N

    2018-03-06

    Organ-mounted robots address the problem of beating-heart surgery by adhering to the heart, passively providing a platform that approaches zero relative motion. Because of the quasi-periodic deformation of the heart due to heartbeat and respiration, registration must address not only spatial registration but also temporal registration. Motion data were collected in the porcine model in vivo (N = 6). Fourier series models of heart motion were developed. By comparing registrations generated using an iterative closest-point approach at different phases of respiration, the phase corresponding to minimum registration distance is identified. The spatiotemporal registration technique presented here reduces registration error by an average of 4.2 mm over the 6 trials, in comparison with a more simplistic static registration that merely averages out the physiological motion. An empirical metric for spatiotemporal registration of organ-mounted robots is defined and demonstrated using data from animal models in vivo. Copyright © 2018 John Wiley & Sons, Ltd.

  14. Speeding up Coarse Point Cloud Registration by Threshold-Independent Baysac Match Selection

    NASA Astrophysics Data System (ADS)

    Kang, Z.; Lindenbergh, R.; Pu, S.

    2016-06-01

    This paper presents an algorithm for the automatic registration of terrestrial point clouds by match selection using an efficiently conditional sampling method -- threshold-independent BaySAC (BAYes SAmpling Consensus) and employs the error metric of average point-to-surface residual to reduce the random measurement error and then approach the real registration error. BaySAC and other basic sampling algorithms usually need to artificially determine a threshold by which inlier points are identified, which leads to a threshold-dependent verification process. Therefore, we applied the LMedS method to construct the cost function that is used to determine the optimum model to reduce the influence of human factors and improve the robustness of the model estimate. Point-to-point and point-to-surface error metrics are most commonly used. However, point-to-point error in general consists of at least two components, random measurement error and systematic error as a result of a remaining error in the found rigid body transformation. Thus we employ the measure of the average point-to-surface residual to evaluate the registration accuracy. The proposed approaches, together with a traditional RANSAC approach, are tested on four data sets acquired by three different scanners in terms of their computational efficiency and quality of the final registration. The registration results show the st.dev of the average point-to-surface residuals is reduced from 1.4 cm (plain RANSAC) to 0.5 cm (threshold-independent BaySAC). The results also show that, compared to the performance of RANSAC, our BaySAC strategies lead to less iterations and cheaper computational cost when the hypothesis set is contaminated with more outliers.

  15. Evaluation of targeting errors in ultrasound-assisted radiotherapy

    PubMed Central

    Wang, Michael; Rohling, Robert; Duzenli, Cheryl; Clark, Brenda; Archip, Neculai

    2014-01-01

    A method for validating the start-to-end accuracy of a 3D ultrasound-based patient positioning system for radiotherapy is described. A radiosensitive polymer gel is used to record the actual dose delivered to a rigid phantom after being positioned using 3D ultrasound guidance. Comparison of the delivered dose with the treatment plan allows accuracy of the entire radiotherapy treatment process, from simulation to 3D ultrasound guidance, and finally delivery of radiation, to be evaluated. The 3D ultrasound patient positioning system has a number of features for achieving high accuracy and reducing operator dependence. These include using tracked 3D ultrasound scans of the target anatomy acquired using a dedicated 3D ultrasound probe during both the simulation and treatment sessions, automatic 3D ultrasound-to-ultrasound registration, and use of infra-red LED (IRED) markers of the optical position sensing system for registering simulation CT to ultrasound data. The mean target localization accuracy of this system was 2.5mm for four target locations inside the phantom, compared to 1.6mm obtained using the conventional patient positioning method of laser alignment. Since the phantom is rigid, this represents the best possible set-up accuracy of the system. Thus, these results suggest that 3D ultrasound-based target localization is practically feasible and potentially capable of increasing the accuracy of patient positioning for radiotherapy in sites where day-to-day organ shifts are greater than 1mm in magnitude. PMID:18723271

  16. Validation of non-rigid point-set registration methods using a porcine bladder pelvic phantom

    NASA Astrophysics Data System (ADS)

    Zakariaee, Roja; Hamarneh, Ghassan; Brown, Colin J.; Spadinger, Ingrid

    2016-01-01

    The problem of accurate dose accumulation in fractionated radiotherapy treatment for highly deformable organs, such as bladder, has garnered increasing interest over the past few years. However, more research is required in order to find a robust and efficient solution and to increase the accuracy over the current methods. The purpose of this study was to evaluate the feasibility and accuracy of utilizing non-rigid (affine or deformable) point-set registration in accumulating dose in bladder of different sizes and shapes. A pelvic phantom was built to house an ex vivo porcine bladder with fiducial landmarks adhered onto its surface. Four different volume fillings of the bladder were used (90, 180, 360 and 480 cc). The performance of MATLAB implementations of five different methods were compared, in aligning the bladder contour point-sets. The approaches evaluated were coherent point drift (CPD), gaussian mixture model, shape context, thin-plate spline robust point matching (TPS-RPM) and finite iterative closest point (ICP-finite). The evaluation metrics included registration runtime, target registration error (TRE), root-mean-square error (RMS) and Hausdorff distance (HD). The reference (source) dataset was alternated through all four points-sets, in order to study the effect of reference volume on the registration outcomes. While all deformable algorithms provided reasonable registration results, CPD provided the best TRE values (6.4 mm), and TPS-RPM yielded the best mean RMS and HD values (1.4 and 6.8 mm, respectively). ICP-finite was the fastest technique and TPS-RPM, the slowest.

  17. Three-dimensional nonrigid landmark-based magnetic resonance to transrectal ultrasound registration for image-guided prostate biopsy.

    PubMed

    Sun, Yue; Qiu, Wu; Yuan, Jing; Romagnoli, Cesare; Fenster, Aaron

    2015-04-01

    Registration of three-dimensional (3-D) magnetic resonance (MR) to 3-D transrectal ultrasound (TRUS) prostate images is an important step in the planning and guidance of 3-D TRUS guided prostate biopsy. In order to accurately and efficiently perform the registration, a nonrigid landmark-based registration method is required to account for the different deformations of the prostate when using these two modalities. We describe a nonrigid landmark-based method for registration of 3-D TRUS to MR prostate images. The landmark-based registration method first makes use of an initial rigid registration of 3-D MR to 3-D TRUS images using six manually placed approximately corresponding landmarks in each image. Following manual initialization, the two prostate surfaces are segmented from 3-D MR and TRUS images and then nonrigidly registered using the following steps: (1) rotationally reslicing corresponding segmented prostate surfaces from both 3-D MR and TRUS images around a specified axis, (2) an approach to find point correspondences on the surfaces of the segmented surfaces, and (3) deformation of the surface of the prostate in the MR image to match the surface of the prostate in the 3-D TRUS image and the interior using a thin-plate spline algorithm. The registration accuracy was evaluated using 17 patient prostate MR and 3-D TRUS images by measuring the target registration error (TRE). Experimental results showed that the proposed method yielded an overall mean TRE of [Formula: see text] for the rigid registration and [Formula: see text] for the nonrigid registration, which is favorably comparable to a clinical requirement for an error of less than 2.5 mm. A landmark-based nonrigid 3-D MR-TRUS registration approach is proposed, which takes into account the correspondences on the prostate surface, inside the prostate, as well as the centroid of the prostate. Experimental results indicate that the proposed method yields clinically sufficient accuracy.

  18. Computed tomography lung iodine contrast mapping by image registration and subtraction

    NASA Astrophysics Data System (ADS)

    Goatman, Keith; Plakas, Costas; Schuijf, Joanne; Beveridge, Erin; Prokop, Mathias

    2014-03-01

    Pulmonary embolism (PE) is a relatively common and potentially life threatening disease, affecting around 600,000 people annually in the United States alone. Prompt treatment using anticoagulants is effective and saves lives, but unnecessary treatment risks life threatening haemorrhage. The specificity of any diagnostic test for PE is therefore as important as its sensitivity. Computed tomography (CT) angiography is routinely used to diagnose PE. However, there are concerns it may over-report the condition. Additional information about the severity of an occlusion can be obtained from an iodine contrast map that represents tissue perfusion. Such maps tend to be derived from dual-energy CT acquisitions. However, they may also be calculated by subtracting pre- and post-contrast CT scans. Indeed, there are technical advantages to such a subtraction approach, including better contrast-to-noise ratio for the same radiation dose, and bone suppression. However, subtraction relies on accurate image registration. This paper presents a framework for the automatic alignment of pre- and post-contrast lung volumes prior to subtraction. The registration accuracy is evaluated for seven subjects for whom pre- and post-contrast helical CT scans were acquired using a Toshiba Aquilion ONE scanner. One hundred corresponding points were annotated on the pre- and post-contrast scans, distributed throughout the lung volume. Surface-to-surface error distances were also calculated from lung segmentations. Prior to registration the mean Euclidean landmark alignment error was 2.57mm (range 1.43-4.34 mm), and following registration the mean error was 0.54mm (range 0.44-0.64 mm). The mean surface error distance was 1.89mm before registration and 0.47mm after registration. There was a commensurate reduction in visual artefacts following registration. In conclusion, a framework for pre- and post-contrast lung registration has been developed that is sufficiently accurate for lung subtraction

  19. 3D prostate MR-TRUS non-rigid registration using dual optimization with volume-preserving constraint

    NASA Astrophysics Data System (ADS)

    Qiu, Wu; Yuan, Jing; Fenster, Aaron

    2016-03-01

    We introduce an efficient and novel convex optimization-based approach to the challenging non-rigid registration of 3D prostate magnetic resonance (MR) and transrectal ultrasound (TRUS) images, which incorporates a new volume preserving constraint to essentially improve the accuracy of targeting suspicious regions during the 3D TRUS guided prostate biopsy. Especially, we propose a fast sequential convex optimization scheme to efficiently minimize the employed highly nonlinear image fidelity function using the robust multi-channel modality independent neighborhood descriptor (MIND) across the two modalities of MR and TRUS. The registration accuracy was evaluated using 10 patient images by calculating the target registration error (TRE) using manually identified corresponding intrinsic fiducials in the whole prostate gland. We also compared the MR and TRUS manually segmented prostate surfaces in the registered images in terms of the Dice similarity coefficient (DSC), mean absolute surface distance (MAD), and maximum absolute surface distance (MAXD). Experimental results showed that the proposed method with the introduced volume-preserving prior significantly improves the registration accuracy comparing to the method without the volume-preserving constraint, by yielding an overall mean TRE of 2:0+/-0:7 mm, and an average DSC of 86:5+/-3:5%, MAD of 1:4+/-0:6 mm and MAXD of 6:5+/-3:5 mm.

  20. Simultaneous 3D–2D image registration and C-arm calibration: Application to endovascular image-guided interventions

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mitrović, Uroš; Pernuš, Franjo; Likar, Boštjan

    Purpose: Three-dimensional to two-dimensional (3D–2D) image registration is a key to fusion and simultaneous visualization of valuable information contained in 3D pre-interventional and 2D intra-interventional images with the final goal of image guidance of a procedure. In this paper, the authors focus on 3D–2D image registration within the context of intracranial endovascular image-guided interventions (EIGIs), where the 3D and 2D images are generally acquired with the same C-arm system. The accuracy and robustness of any 3D–2D registration method, to be used in a clinical setting, is influenced by (1) the method itself, (2) uncertainty of initial pose of the 3Dmore » image from which registration starts, (3) uncertainty of C-arm’s geometry and pose, and (4) the number of 2D intra-interventional images used for registration, which is generally one and at most two. The study of these influences requires rigorous and objective validation of any 3D–2D registration method against a highly accurate reference or “gold standard” registration, performed on clinical image datasets acquired in the context of the intervention. Methods: The registration process is split into two sequential, i.e., initial and final, registration stages. The initial stage is either machine-based or template matching. The latter aims to reduce possibly large in-plane translation errors by matching a projection of the 3D vessel model and 2D image. In the final registration stage, four state-of-the-art intrinsic image-based 3D–2D registration methods, which involve simultaneous refinement of rigid-body and C-arm parameters, are evaluated. For objective validation, the authors acquired an image database of 15 patients undergoing cerebral EIGI, for which accurate gold standard registrations were established by fiducial marker coregistration. Results: Based on target registration error, the obtained success rates of 3D to a single 2D image registration after initial machine

  1. Accuracy of surface registration compared to conventional volumetric registration in patient positioning for head-and-neck radiotherapy: A simulation study using patient data

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kim, Youngjun; Li, Ruijiang; Na, Yong Hum

    2014-12-15

    Purpose: 3D optical surface imaging has been applied to patient positioning in radiation therapy (RT). The optical patient positioning system is advantageous over conventional method using cone-beam computed tomography (CBCT) in that it is radiation free, frameless, and is capable of real-time monitoring. While the conventional radiographic method uses volumetric registration, the optical system uses surface matching for patient alignment. The relative accuracy of these two methods has not yet been sufficiently investigated. This study aims to investigate the theoretical accuracy of the surface registration based on a simulation study using patient data. Methods: This study compares the relative accuracymore » of surface and volumetric registration in head-and-neck RT. The authors examined 26 patient data sets, each consisting of planning CT data acquired before treatment and patient setup CBCT data acquired at the time of treatment. As input data of surface registration, patient’s skin surfaces were created by contouring patient skin from planning CT and treatment CBCT. Surface registration was performed using the iterative closest points algorithm by point–plane closest, which minimizes the normal distance between source points and target surfaces. Six degrees of freedom (three translations and three rotations) were used in both surface and volumetric registrations and the results were compared. The accuracy of each method was estimated by digital phantom tests. Results: Based on the results of 26 patients, the authors found that the average and maximum root-mean-square translation deviation between the surface and volumetric registrations were 2.7 and 5.2 mm, respectively. The residual error of the surface registration was calculated to have an average of 0.9 mm and a maximum of 1.7 mm. Conclusions: Surface registration may lead to results different from those of the conventional volumetric registration. Only limited accuracy can be achieved for patient

  2. Supervoxels for graph cuts-based deformable image registration using guided image filtering

    NASA Astrophysics Data System (ADS)

    Szmul, Adam; Papież, Bartłomiej W.; Hallack, Andre; Grau, Vicente; Schnabel, Julia A.

    2017-11-01

    We propose combining a supervoxel-based image representation with the concept of graph cuts as an efficient optimization technique for three-dimensional (3-D) deformable image registration. Due to the pixels/voxels-wise graph construction, the use of graph cuts in this context has been mainly limited to two-dimensional (2-D) applications. However, our work overcomes some of the previous limitations by posing the problem on a graph created by adjacent supervoxels, where the number of nodes in the graph is reduced from the number of voxels to the number of supervoxels. We demonstrate how a supervoxel image representation combined with graph cuts-based optimization can be applied to 3-D data. We further show that the application of a relaxed graph representation of the image, followed by guided image filtering over the estimated deformation field, allows us to model "sliding motion." Applying this method to lung image registration results in highly accurate image registration and anatomically plausible estimations of the deformations. Evaluation of our method on a publicly available computed tomography lung image dataset leads to the observation that our approach compares very favorably with state of the art methods in continuous and discrete image registration, achieving target registration error of 1.16 mm on average per landmark.

  3. Supervoxels for Graph Cuts-Based Deformable Image Registration Using Guided Image Filtering.

    PubMed

    Szmul, Adam; Papież, Bartłomiej W; Hallack, Andre; Grau, Vicente; Schnabel, Julia A

    2017-10-04

    In this work we propose to combine a supervoxel-based image representation with the concept of graph cuts as an efficient optimization technique for 3D deformable image registration. Due to the pixels/voxels-wise graph construction, the use of graph cuts in this context has been mainly limited to 2D applications. However, our work overcomes some of the previous limitations by posing the problem on a graph created by adjacent supervoxels, where the number of nodes in the graph is reduced from the number of voxels to the number of supervoxels. We demonstrate how a supervoxel image representation, combined with graph cuts-based optimization can be applied to 3D data. We further show that the application of a relaxed graph representation of the image, followed by guided image filtering over the estimated deformation field, allows us to model 'sliding motion'. Applying this method to lung image registration, results in highly accurate image registration and anatomically plausible estimations of the deformations. Evaluation of our method on a publicly available Computed Tomography lung image dataset (www.dir-lab.com) leads to the observation that our new approach compares very favorably with state-of-the-art in continuous and discrete image registration methods achieving Target Registration Error of 1.16mm on average per landmark.

  4. Distance-preserving rigidity penalty on deformable image registration of multiple skeletal components in the neck

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kim, Jihun, E-mail: jihun@umich.edu; Saitou, Kazuhiro; Matuszak, Martha M.

    Purpose: This study aims at developing and testing a novel rigidity penalty suitable for the deformable registration of tightly located skeletal components in the head and neck from planning computed tomography (CT) and daily cone-beam CT (CBCT) scans of patients undergoing radiotherapy. Methods: The proposed rigidity penalty is designed to preserve intervoxel distances within each bony structure. This penalty was tested in the intensity-based B-spline deformable registration of five cervical vertebral bodies (C1–C5). The displacement vector fields (DVFs) from the registrations were compared to the DVFs generated by using rigid body motions of the cervical vertebrae, measured by the surfacemore » registration of vertebrae delineated on CT and CBCT images. Twenty five pairs of planning CT (reference) and treatment CBCTs (target) from five patients were aligned without and with the penalty. An existing penalty based on the orthonormality of the deformation gradient tensor was also tested and the effects of the penalties compared. Results: The mean magnitude of the maximum registration error with the proposed distance-preserving penalty was (0.86, 1.12, 1.33) mm compared to (2.11, 2.49, 2.46) without penalty and (1.53, 1.64, 1.64) with the existing orthonormality-based penalty. The improvement in the accuracy of the deformable image registration was also verified by comparing the Procrustes distance between the DVFs. With the proposed penalty, the average distance was 0.11 (σ 0.03 mm) which is smaller than 0.53 (0.1 mm) without penalty and 0.28 (0.04 mm) with the orthonormality-based penalty. Conclusions: The accuracy of aligning multiple bony elements was improved by using the proposed distance-preserving rigidity penalty. The voxel-based statistical analysis of the registration error shows that the proposed penalty improved the integrity of the DVFs within the vertebral bodies.« less

  5. Distance-preserving rigidity penalty on deformable image registration of multiple skeletal components in the neck

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kim, Jihun, E-mail: jihun@umich.edu; Saitou, Kazuhiro; Matuszak, Martha M.

    2013-12-15

    Purpose: This study aims at developing and testing a novel rigidity penalty suitable for the deformable registration of tightly located skeletal components in the head and neck from planning computed tomography (CT) and daily cone-beam CT (CBCT) scans of patients undergoing radiotherapy. Methods: The proposed rigidity penalty is designed to preserve intervoxel distances within each bony structure. This penalty was tested in the intensity-based B-spline deformable registration of five cervical vertebral bodies (C1–C5). The displacement vector fields (DVFs) from the registrations were compared to the DVFs generated by using rigid body motions of the cervical vertebrae, measured by the surfacemore » registration of vertebrae delineated on CT and CBCT images. Twenty five pairs of planning CT (reference) and treatment CBCTs (target) from five patients were aligned without and with the penalty. An existing penalty based on the orthonormality of the deformation gradient tensor was also tested and the effects of the penalties compared. Results: The mean magnitude of the maximum registration error with the proposed distance-preserving penalty was (0.86, 1.12, 1.33) mm compared to (2.11, 2.49, 2.46) without penalty and (1.53, 1.64, 1.64) with the existing orthonormality-based penalty. The improvement in the accuracy of the deformable image registration was also verified by comparing the Procrustes distance between the DVFs. With the proposed penalty, the average distance was 0.11 (σ 0.03 mm) which is smaller than 0.53 (0.1 mm) without penalty and 0.28 (0.04 mm) with the orthonormality-based penalty. Conclusions: The accuracy of aligning multiple bony elements was improved by using the proposed distance-preserving rigidity penalty. The voxel-based statistical analysis of the registration error shows that the proposed penalty improved the integrity of the DVFs within the vertebral bodies.« less

  6. Group-wise feature-based registration of CT and ultrasound images of spine

    NASA Astrophysics Data System (ADS)

    Rasoulian, Abtin; Mousavi, Parvin; Hedjazi Moghari, Mehdi; Foroughi, Pezhman; Abolmaesumi, Purang

    2010-02-01

    Registration of pre-operative CT and freehand intra-operative ultrasound of lumbar spine could aid surgeons in the spinal needle injection which is a common procedure for pain management. Patients are always in a supine position during the CT scan, and in the prone or sitting position during the intervention. This leads to a difference in the spinal curvature between the two imaging modalities, which means a single rigid registration cannot be used for all of the lumbar vertebrae. In this work, a method for group-wise registration of pre-operative CT and intra-operative freehand 2-D ultrasound images of the lumbar spine is presented. The approach utilizes a pointbased registration technique based on the unscented Kalman filter, taking as input segmented vertebrae surfaces in both CT and ultrasound data. Ultrasound images are automatically segmented using a dynamic programming approach, while the CT images are semi-automatically segmented using thresholding. Since the curvature of the spine is different between the pre-operative and the intra-operative data, the registration approach is designed to simultaneously align individual groups of points segmented from each vertebra in the two imaging modalities. A biomechanical model is used to constrain the vertebrae transformation parameters during the registration and to ensure convergence. The mean target registration error achieved for individual vertebrae on five spine phantoms generated from CT data of patients, is 2.47 mm with standard deviation of 1.14 mm.

  7. Low Target Prevalence Is a Stubborn Source of Errors in Visual Search Tasks

    ERIC Educational Resources Information Center

    Wolfe, Jeremy M.; Horowitz, Todd S.; Van Wert, Michael J.; Kenner, Naomi M.; Place, Skyler S.; Kibbi, Nour

    2007-01-01

    In visual search tasks, observers look for targets in displays containing distractors. Likelihood that targets will be missed varies with target prevalence, the frequency with which targets are presented across trials. Miss error rates are much higher at low target prevalence (1%-2%) than at high prevalence (50%). Unfortunately, low prevalence is…

  8. Automated geographic registration and radiometric correction for UAV-based mosaics

    NASA Astrophysics Data System (ADS)

    Thomasson, J. Alex; Shi, Yeyin; Sima, Chao; Yang, Chenghai; Cope, Dale A.

    2017-05-01

    Texas A and M University has been operating a large-scale, UAV-based, agricultural remote-sensing research project since 2015. To use UAV-based images in agricultural production, many high-resolution images must be mosaicked together to create an image of an agricultural field. Two key difficulties to science-based utilization of such mosaics are geographic registration and radiometric calibration. In our current research project, image files are taken to the computer laboratory after the flight, and semi-manual pre-processing is implemented on the raw image data, including ortho-mosaicking and radiometric calibration. Ground control points (GCPs) are critical for high-quality geographic registration of images during mosaicking. Applications requiring accurate reflectance data also require radiometric-calibration references so that reflectance values of image objects can be calculated. We have developed a method for automated geographic registration and radiometric correction with targets that are installed semi-permanently at distributed locations around fields. The targets are a combination of black (≍5% reflectance), dark gray (≍20% reflectance), and light gray (≍40% reflectance) sections that provide for a transformation of pixel-value to reflectance in the dynamic range of crop fields. The exact spectral reflectance of each target is known, having been measured with a spectrophotometer. At the time of installation, each target is measured for position with a real-time kinematic GPS receiver to give its precise latitude and longitude. Automated location of the reference targets in the images is required for precise, automated, geographic registration; and automated calculation of the digital-number to reflectance transformation is required for automated radiometric calibration. To validate the system for radiometric calibration, a calibrated UAV-based image mosaic of a field was compared to a calibrated single image from a manned aircraft. Reflectance

  9. A prospective comparison between auto-registration and manual registration of real-time ultrasound with MR images for percutaneous ablation or biopsy of hepatic lesions.

    PubMed

    Cha, Dong Ik; Lee, Min Woo; Song, Kyoung Doo; Oh, Young-Taek; Jeong, Ja-Yeon; Chang, Jung-Woo; Ryu, Jiwon; Lee, Kyong Joon; Kim, Jaeil; Bang, Won-Chul; Shin, Dong Kuk; Choi, Sung Jin; Koh, Dalkwon; Seo, Bong Koo; Kim, Kyunga

    2017-06-01

    To compare the accuracy and required time for image fusion of real-time ultrasound (US) with pre-procedural magnetic resonance (MR) images between positioning auto-registration and manual registration for percutaneous radiofrequency ablation or biopsy of hepatic lesions. This prospective study was approved by the institutional review board, and all patients gave written informed consent. Twenty-two patients (male/female, n = 18/n = 4; age, 61.0 ± 7.7 years) who were referred for planning US to assess the feasibility of radiofrequency ablation (n = 21) or biopsy (n = 1) for focal hepatic lesions were included. One experienced radiologist performed the two types of image fusion methods in each patient. The performance of auto-registration and manual registration was evaluated. The accuracy of the two methods, based on measuring registration error, and the time required for image fusion for both methods were recorded using in-house software and respectively compared using the Wilcoxon signed rank test. Image fusion was successful in all patients. The registration error was not significantly different between the two methods (auto-registration: median, 3.75 mm; range, 1.0-15.8 mm vs. manual registration: median, 2.95 mm; range, 1.2-12.5 mm, p = 0.242). The time required for image fusion was significantly shorter with auto-registration than with manual registration (median, 28.5 s; range, 18-47 s, vs. median, 36.5 s; range, 14-105 s, p = 0.026). Positioning auto-registration showed promising results compared with manual registration, with similar accuracy and even shorter registration time.

  10. Ultrasound to video registration using a bi-plane transrectal probe with photoacoustic markers

    NASA Astrophysics Data System (ADS)

    Cheng, Alexis; Kang, Hyun Jae; Zhang, Haichong K.; Taylor, Russell H.; Boctor, Emad M.

    2016-03-01

    Modern surgical scenarios typically provide surgeons with additional information through fusion of video and other imaging modalities. To provide this information, the tools and devices used in surgery must be registered together with interventional guidance equipment and surgical navigation systems. In this work, we focus explicitly on registering ultrasound with a stereo camera system using photoacoustic markers. Previous work has shown that photoacoustic markers can be used in this registration task to achieve target registration errors lower than the current available systems. Photoacoustic markers are defined as a set of non-collinear laser spots projected onto some surface. They can be simultaneously visualized by a stereo camera system and an ultrasound transducer because of the photoacoustic effect. In more recent work, the three-dimensional ultrasound volume was replaced by images from a single ultrasound image pose from a convex array transducer. The feasibility of this approach was demonstrated, but the accuracy was lacking due to the physical limitations of the convex array transducer. In this work, we propose the use of a bi-plane transrectal ultrasound transducer. The main advantage of using this type of transducer is that the ultrasound elements are no longer restricted to a single plane. While this development would be limited to prostate applications, liver and kidney applications are also feasible if a suitable transducer is built. This work is demonstrated in two experiments, one without photoacoustic sources and one with. The resulting target registration error for these experiments were 1.07mm±0.35mm and 1.27mm+/-0.47mm respectively, both of which are better than current available navigation systems.

  11. Deformable registration of CT and cone-beam CT with local intensity matching.

    PubMed

    Park, Seyoun; Plishker, William; Quon, Harry; Wong, John; Shekhar, Raj; Lee, Junghoon

    2017-02-07

    Cone-beam CT (CBCT) is a widely used intra-operative imaging modality in image-guided radiotherapy and surgery. A short scan followed by a filtered-backprojection is typically used for CBCT reconstruction. While data on the mid-plane (plane of source-detector rotation) is complete, off-mid-planes undergo different information deficiency and the computed reconstructions are approximate. This causes different reconstruction artifacts at off-mid-planes depending on slice locations, and therefore impedes accurate registration between CT and CBCT. In this paper, we propose a method to accurately register CT and CBCT by iteratively matching local CT and CBCT intensities. We correct CBCT intensities by matching local intensity histograms slice by slice in conjunction with intensity-based deformable registration. The correction-registration steps are repeated in an alternating way until the result image converges. We integrate the intensity matching into three different deformable registration methods, B-spline, demons, and optical flow that are widely used for CT-CBCT registration. All three registration methods were implemented on a graphics processing unit for efficient parallel computation. We tested the proposed methods on twenty five head and neck cancer cases and compared the performance with state-of-the-art registration methods. Normalized cross correlation (NCC), structural similarity index (SSIM), and target registration error (TRE) were computed to evaluate the registration performance. Our method produced overall NCC of 0.96, SSIM of 0.94, and TRE of 2.26 → 2.27 mm, outperforming existing methods by 9%, 12%, and 27%, respectively. Experimental results also show that our method performs consistently and is more accurate than existing algorithms, and also computationally efficient.

  12. Deformable registration of CT and cone-beam CT with local intensity matching

    NASA Astrophysics Data System (ADS)

    Park, Seyoun; Plishker, William; Quon, Harry; Wong, John; Shekhar, Raj; Lee, Junghoon

    2017-02-01

    Cone-beam CT (CBCT) is a widely used intra-operative imaging modality in image-guided radiotherapy and surgery. A short scan followed by a filtered-backprojection is typically used for CBCT reconstruction. While data on the mid-plane (plane of source-detector rotation) is complete, off-mid-planes undergo different information deficiency and the computed reconstructions are approximate. This causes different reconstruction artifacts at off-mid-planes depending on slice locations, and therefore impedes accurate registration between CT and CBCT. In this paper, we propose a method to accurately register CT and CBCT by iteratively matching local CT and CBCT intensities. We correct CBCT intensities by matching local intensity histograms slice by slice in conjunction with intensity-based deformable registration. The correction-registration steps are repeated in an alternating way until the result image converges. We integrate the intensity matching into three different deformable registration methods, B-spline, demons, and optical flow that are widely used for CT-CBCT registration. All three registration methods were implemented on a graphics processing unit for efficient parallel computation. We tested the proposed methods on twenty five head and neck cancer cases and compared the performance with state-of-the-art registration methods. Normalized cross correlation (NCC), structural similarity index (SSIM), and target registration error (TRE) were computed to evaluate the registration performance. Our method produced overall NCC of 0.96, SSIM of 0.94, and TRE of 2.26 → 2.27 mm, outperforming existing methods by 9%, 12%, and 27%, respectively. Experimental results also show that our method performs consistently and is more accurate than existing algorithms, and also computationally efficient.

  13. MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery

    NASA Astrophysics Data System (ADS)

    Reaungamornrat, S.; De Silva, T.; Uneri, A.; Wolinsky, J.-P.; Khanna, A. J.; Kleinszig, G.; Vogt, S.; Prince, J. L.; Siewerdsen, J. H.

    2016-03-01

    Purpose: Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. Method: The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. Result: The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. Conclusions: A modality-independent deformable registration method has been developed to estimate a

  14. Deformable Image Registration for Cone-Beam CT Guided Transoral Robotic Base of Tongue Surgery

    PubMed Central

    Reaungamornrat, S.; Liu, W. P.; Wang, A. S.; Otake, Y.; Nithiananthan, S.; Uneri, A.; Schafer, S.; Tryggestad, E.; Richmon, J.; Sorger, J. M.; Siewerdsen, J. H.; Taylor, R. H.

    2013-01-01

    Transoral robotic surgery (TORS) offers a minimally invasive approach to resection of base of tongue tumors. However, precise localization of the surgical target and adjacent critical structures can be challenged by the highly deformed intraoperative setup. We propose a deformable registration method using intraoperative cone-beam CT (CBCT) to accurately align preoperative CT or MR images with the intraoperative scene. The registration method combines a Gaussian mixture (GM) model followed by a variation of the Demons algorithm. First, following segmentation of the volume of interest (i.e., volume of the tongue extending to the hyoid), a GM model is applied to surface point clouds for rigid initialization (GM rigid) followed by nonrigid deformation (GM nonrigid). Second, the registration is refined using the Demons algorithm applied to distance map transforms of the (GM-registered) preoperative image and intraoperative CBCT. Performance was evaluated in repeat cadaver studies (25 image pairs) in terms of target registration error (TRE), entropy correlation coefficient (ECC), and normalized pointwise mutual information (NPMI). Retraction of the tongue in the TORS operative setup induced gross deformation >30 mm. The mean TRE following the GM rigid, GM nonrigid, and Demons steps was 4.6, 2.1, and 1.7 mm, respectively. The respective ECC was 0.57, 0.70, and 0.73 and NPMI was 0.46, 0.57, and 0.60. Registration accuracy was best across the superior aspect of the tongue and in proximity to the hyoid (by virtue of GM registration of surface points on these structures). The Demons step refined registration primarily in deeper portions of the tongue further from the surface and hyoid bone. Since the method does not use image intensities directly, it is suitable to multi-modality registration of preoperative CT or MR with intraoperative CBCT. Extending the 3D image registration to the fusion of image and planning data in stereo-endoscopic video is anticipated to support

  15. Deformable image registration for cone-beam CT guided transoral robotic base-of-tongue surgery

    NASA Astrophysics Data System (ADS)

    Reaungamornrat, S.; Liu, W. P.; Wang, A. S.; Otake, Y.; Nithiananthan, S.; Uneri, A.; Schafer, S.; Tryggestad, E.; Richmon, J.; Sorger, J. M.; Siewerdsen, J. H.; Taylor, R. H.

    2013-07-01

    Transoral robotic surgery (TORS) offers a minimally invasive approach to resection of base-of-tongue tumors. However, precise localization of the surgical target and adjacent critical structures can be challenged by the highly deformed intraoperative setup. We propose a deformable registration method using intraoperative cone-beam computed tomography (CBCT) to accurately align preoperative CT or MR images with the intraoperative scene. The registration method combines a Gaussian mixture (GM) model followed by a variation of the Demons algorithm. First, following segmentation of the volume of interest (i.e. volume of the tongue extending to the hyoid), a GM model is applied to surface point clouds for rigid initialization (GM rigid) followed by nonrigid deformation (GM nonrigid). Second, the registration is refined using the Demons algorithm applied to distance map transforms of the (GM-registered) preoperative image and intraoperative CBCT. Performance was evaluated in repeat cadaver studies (25 image pairs) in terms of target registration error (TRE), entropy correlation coefficient (ECC) and normalized pointwise mutual information (NPMI). Retraction of the tongue in the TORS operative setup induced gross deformation >30 mm. The mean TRE following the GM rigid, GM nonrigid and Demons steps was 4.6, 2.1 and 1.7 mm, respectively. The respective ECC was 0.57, 0.70 and 0.73, and NPMI was 0.46, 0.57 and 0.60. Registration accuracy was best across the superior aspect of the tongue and in proximity to the hyoid (by virtue of GM registration of surface points on these structures). The Demons step refined registration primarily in deeper portions of the tongue further from the surface and hyoid bone. Since the method does not use image intensities directly, it is suitable to multi-modality registration of preoperative CT or MR with intraoperative CBCT. Extending the 3D image registration to the fusion of image and planning data in stereo-endoscopic video is anticipated to

  16. Registration of in vivo MR to histology of rodent brains using blockface imaging

    NASA Astrophysics Data System (ADS)

    Uberti, Mariano; Liu, Yutong; Dou, Huanyu; Mosley, R. Lee; Gendelman, Howard E.; Boska, Michael

    2009-02-01

    Registration of MRI to histopathological sections can enhance bioimaging validation for use in pathobiologic, diagnostic, and therapeutic evaluations. However, commonly used registration methods fall short of this goal due to tissue shrinkage and tearing after brain extraction and preparation. In attempts to overcome these limitations we developed a software toolbox using 3D blockface imaging as the common space of reference. This toolbox includes a semi-automatic brain extraction technique using constraint level sets (CLS), 3D reconstruction methods for the blockface and MR volume, and a 2D warping technique using thin-plate splines with landmark optimization. Using this toolbox, the rodent brain volume is first extracted from the whole head MRI using CLS. The blockface volume is reconstructed followed by 3D brain MRI registration to the blockface volume to correct the global deformations due to brain extraction and fixation. Finally, registered MRI and histological slices are warped to corresponding blockface images to correct slice specific deformations. The CLS brain extraction technique was validated by comparing manual results showing 94% overlap. The image warping technique was validated by calculating target registration error (TRE). Results showed a registration accuracy of a TRE < 1 pixel. Lastly, the registration method and the software tools developed were used to validate cell migration in murine human immunodeficiency virus type one encephalitis.

  17. Low target prevalence is a stubborn source of errors in visual search tasks

    PubMed Central

    Wolfe, Jeremy M.; Horowitz, Todd S.; Van Wert, Michael J.; Kenner, Naomi M.; Place, Skyler S.; Kibbi, Nour

    2009-01-01

    In visual search tasks, observers look for targets in displays containing distractors. Likelihood that targets will be missed varies with target prevalence, the frequency with which targets are presented across trials. Miss error rates are much higher at low target prevalence (1–2%) than at high prevalence (50%). Unfortunately, low prevalence is characteristic of important search tasks like airport security and medical screening where miss errors are dangerous. A series of experiments show this prevalence effect is very robust. In signal detection terms, the prevalence effect can be explained as a criterion shift and not a change in sensitivity. Several efforts to induce observers to adopt a better criterion fail. However, a regime of brief retraining periods with high prevalence and full feedback allows observers to hold a good criterion during periods of low prevalence with no feedback. PMID:17999575

  18. Voxel-based statistical analysis of uncertainties associated with deformable image registration

    NASA Astrophysics Data System (ADS)

    Li, Shunshan; Glide-Hurst, Carri; Lu, Mei; Kim, Jinkoo; Wen, Ning; Adams, Jeffrey N.; Gordon, James; Chetty, Indrin J.; Zhong, Hualiang

    2013-09-01

    Deformable image registration (DIR) algorithms have inherent uncertainties in their displacement vector fields (DVFs).The purpose of this study is to develop an optimal metric to estimate DIR uncertainties. Six computational phantoms have been developed from the CT images of lung cancer patients using a finite element method (FEM). The FEM generated DVFs were used as a standard for registrations performed on each of these phantoms. A mechanics-based metric, unbalanced energy (UE), was developed to evaluate these registration DVFs. The potential correlation between UE and DIR errors was explored using multivariate analysis, and the results were validated by landmark approach and compared with two other error metrics: DVF inverse consistency (IC) and image intensity difference (ID). Landmark-based validation was performed using the POPI-model. The results show that the Pearson correlation coefficient between UE and DIR error is rUE-error = 0.50. This is higher than rIC-error = 0.29 for IC and DIR error and rID-error = 0.37 for ID and DIR error. The Pearson correlation coefficient between UE and the product of the DIR displacements and errors is rUE-error × DVF = 0.62 for the six patients and rUE-error × DVF = 0.73 for the POPI-model data. It has been demonstrated that UE has a strong correlation with DIR errors, and the UE metric outperforms the IC and ID metrics in estimating DIR uncertainties. The quantified UE metric can be a useful tool for adaptive treatment strategies, including probability-based adaptive treatment planning.

  19. A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

    PubMed Central

    Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin

    2012-01-01

    Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766

  20. SU-E-J-94: Positioning Errors Resulting From Using Bony Anatomy Alignment for Treating SBRT Lung Tumor

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Frame, C; Ding, G

    Purpose: To quantify patient setups errors based on bony anatomy registration rather than 3D tumor alignment for SBRT lung treatments. Method: A retrospective study was performed for patients treated with lung SBRT and imaged with kV cone beam computed tomography (kV-CBCT) image-guidance. Daily CBCT images were registered to treatment planning CTs based on bony anatomy alignment and then inter-fraction tumor movement was evaluated by comparing shift in the tumor center in the medial-lateral, anterior-posterior, and superior-inferior directions. The PTV V100% was evaluated for each patient based on the average daily tumor displacement to assess the impact of the positioning errormore » on the target coverage when the registrations were based on bony anatomy. Of the 35 patients studied, 15 were free-breathing treatments, 10 used abdominal compression with a stereotactic body frame, and the remaining 10 were performed with BodyFIX vacuum bags. Results: For free-breathing treatments, the range of tumor displacement error is between 1–6 mm in the medial-lateral, 1–13 mm in the anterior-posterior, and 1–7 mm in the superior-inferior directions. These positioning errors lead to 6–22% underdose coverage for PTV - V100% . Patients treated with abdominal compression immobilization showed positional errors of 0–4mm mediallaterally, 0–3mm anterior-posteriorly, and 0–2 mm inferior-superiorly with PTV - V100% underdose ranging between 6–17%. For patients immobilized with the vacuum bags, the positional errors were found to be 0–1 mm medial-laterally, 0–1mm anterior-posteriorly, and 0–2 mm inferior-superiorly with PTV - V100% under dose ranging between 5–6% only. Conclusion: It is necessary to align the tumor target by using 3D image guidance to ensure adequate tumor coverage before performing SBRT lung treatments. The BodyFIX vacuum bag immobilization method has the least positioning errors among the three methods studied when bony anatomy is used for

  1. Erotic target location errors: an underappreciated paraphilic dimension.

    PubMed

    Lawrence, Anne A

    2009-01-01

    Based on studies of heterosexual male fetishists, transvestites, and transsexuals, Blanchard (1991) proposed the existence of a hitherto unrecognized paraphilic dimension, erotic target location errors (ETLEs), involving the erroneous location of erotic targets in the environment. ETLEs can involve preferential attention to a peripheral or inessential part of an erotic target, manifesting as fetishism, or mislocation of an erotic target in one's own body, manifesting as the desire to impersonate or become a facsimile of the erotic target (e.g., transvestism or transsexualism). Despite its potential clinical and heuristic value, the concept that ETLEs define a paraphilic dimension is underappreciated. This review summarizes the studies leading to the concept of ETLEs and describes how ETLEs are believed to manifest in men whose preferred erotic targets are women, children, men, amputees, plush animals, and real animals. This review also describes ETLEs in women; discusses possible etiologies of ETLEs; considers the implications of the ETLE concept for psychoanalytic theories of transvestism and male-to-female transsexualism, as well as for the forthcoming revision of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; suggests reasons why the concept of ETLEs has been underappreciated; and describes what might result if the concept were more widely appreciated.

  2. [Accurate 3D free-form registration between fan-beam CT and cone-beam CT].

    PubMed

    Liang, Yueqiang; Xu, Hongbing; Li, Baosheng; Li, Hongsheng; Yang, Fujun

    2012-06-01

    Because the X-ray scatters, the CT numbers in cone-beam CT cannot exactly correspond to the electron densities. This, therefore, results in registration error when the intensity-based registration algorithm is used to register planning fan-beam CT and cone-beam CT. In order to reduce the registration error, we have developed an accurate gradient-based registration algorithm. The gradient-based deformable registration problem is described as a minimization of energy functional. Through the calculus of variations and Gauss-Seidel finite difference method, we derived the iterative formula of the deformable registration. The algorithm was implemented by GPU through OpenCL framework, with which the registration time was greatly reduced. Our experimental results showed that the proposed gradient-based registration algorithm could register more accurately the clinical cone-beam CT and fan-beam CT images compared with the intensity-based algorithm. The GPU-accelerated algorithm meets the real-time requirement in the online adaptive radiotherapy.

  3. Supervoxels for Graph Cuts-Based Deformable Image Registration Using Guided Image Filtering

    PubMed Central

    Szmul, Adam; Papież, Bartłomiej W.; Hallack, Andre; Grau, Vicente; Schnabel, Julia A.

    2017-01-01

    In this work we propose to combine a supervoxel-based image representation with the concept of graph cuts as an efficient optimization technique for 3D deformable image registration. Due to the pixels/voxels-wise graph construction, the use of graph cuts in this context has been mainly limited to 2D applications. However, our work overcomes some of the previous limitations by posing the problem on a graph created by adjacent supervoxels, where the number of nodes in the graph is reduced from the number of voxels to the number of supervoxels. We demonstrate how a supervoxel image representation, combined with graph cuts-based optimization can be applied to 3D data. We further show that the application of a relaxed graph representation of the image, followed by guided image filtering over the estimated deformation field, allows us to model ‘sliding motion’. Applying this method to lung image registration, results in highly accurate image registration and anatomically plausible estimations of the deformations. Evaluation of our method on a publicly available Computed Tomography lung image dataset (www.dir-lab.com) leads to the observation that our new approach compares very favorably with state-of-the-art in continuous and discrete image registration methods achieving Target Registration Error of 1.16mm on average per landmark. PMID:29225433

  4. TU-H-CAMPUS-JeP1-05: Dose Deformation Error Associated with Deformable Image Registration Pathways

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Surucu, M; Woerner, A; Roeske, J

    Purpose: To evaluate errors associated with using different deformable image registration (DIR) pathways to deform dose from planning CT (pCT) to cone-beam CT (CBCT). Methods: Deforming dose is controversial because of the lack of quality assurance tools. We previously proposed a novel metric to evaluate dose deformation error (DDE) by warping dose information using two methods, via dose and contour deformation. First, isodose lines of the pCT were converted into structures and then deformed to the CBCT using an image based deformation map (dose/structure/deform). Alternatively, the dose matrix from the pCT was deformed to CBCT using the same deformation map,more » and then the same isodose lines of the deformed dose were converted into structures (dose/deform/structure). The doses corresponding to each structure were queried from the deformed dose and full-width-half-maximums were used to evaluate the dose dispersion. The difference between the FWHM of each isodose level structure is defined as the DDE. Three head-and-neck cancer patients were identified. For each patient, two DIRs were performed between the pCT and CBCT, either deforming pCT-to-CBCT or CBCT-to-pCT. We evaluated the errors associated by using either of these pathways to deform dose. A commercially available, Demons based DIR was used for this study, and 10 isodose levels (20% to 105%) were used to evaluate the errors in various dose levels. Results: The prescription dose for all patients was 70 Gy. The mean DDE for CT-to-CBCT deformation was 1.0 Gy (range: 0.3–2.0 Gy) and this was increased to 4.3 Gy (range: 1.5–6.4 Gy) for CBCT-to-CT deformation. The mean increase in DDE between the two deformations was 3.3 Gy (range: 1.0–5.4 Gy). Conclusion: The proposed DDF was used to quantitatively estimate dose deformation errors caused by different pathways to perform DIR. Deforming dose using CBCT-to-CT deformation produced greater error than CT-to-CBCT deformation.« less

  5. International Test Comparisons: Reviewing Translation Error in Different Source Language-Target Language Combinations

    ERIC Educational Resources Information Center

    Zhao, Xueyu; Solano-Flores, Guillermo; Qian, Ming

    2018-01-01

    This article addresses test translation review in international test comparisons. We investigated the applicability of the theory of test translation error--a theory of the multidimensionality and inevitability of test translation error--across source language-target language combinations in the translation of PISA (Programme of International…

  6. The feasibility of manual parameter tuning for deformable breast MR image registration from a multi-objective optimization perspective.

    PubMed

    Pirpinia, Kleopatra; Bosman, Peter A N; Loo, Claudette E; Winter-Warnars, Gonneke; Janssen, Natasja N Y; Scholten, Astrid N; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

    2017-06-23

    Deformable image registration is typically formulated as an optimization problem involving a linearly weighted combination of terms that correspond to objectives of interest (e.g. similarity, deformation magnitude). The weights, along with multiple other parameters, need to be manually tuned for each application, a task currently addressed mainly via trial-and-error approaches. Such approaches can only be successful if there is a sensible interplay between parameters, objectives, and desired registration outcome. This, however, is not well established. To study this interplay, we use multi-objective optimization, where multiple solutions exist that represent the optimal trade-offs between the objectives, forming a so-called Pareto front. Here, we focus on weight tuning. To study the space a user has to navigate during manual weight tuning, we randomly sample multiple linear combinations. To understand how these combinations relate to desirability of registration outcome, we associate with each outcome a mean target registration error (TRE) based on expert-defined anatomical landmarks. Further, we employ a multi-objective evolutionary algorithm that optimizes the weight combinations, yielding a Pareto front of solutions, which can be directly navigated by the user. To study how the complexity of manual weight tuning changes depending on the registration problem, we consider an easy problem, prone-to-prone breast MR image registration, and a hard problem, prone-to-supine breast MR image registration. Lastly, we investigate how guidance information as an additional objective influences the prone-to-supine registration outcome. Results show that the interplay between weights, objectives, and registration outcome makes manual weight tuning feasible for the prone-to-prone problem, but very challenging for the harder prone-to-supine problem. Here, patient-specific, multi-objective weight optimization is needed, obtaining a mean TRE of 13.6 mm without guidance

  7. The feasibility of manual parameter tuning for deformable breast MR image registration from a multi-objective optimization perspective

    NASA Astrophysics Data System (ADS)

    Pirpinia, Kleopatra; Bosman, Peter A. N.; E Loo, Claudette; Winter-Warnars, Gonneke; Y Janssen, Natasja N.; Scholten, Astrid N.; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

    2017-07-01

    Deformable image registration is typically formulated as an optimization problem involving a linearly weighted combination of terms that correspond to objectives of interest (e.g. similarity, deformation magnitude). The weights, along with multiple other parameters, need to be manually tuned for each application, a task currently addressed mainly via trial-and-error approaches. Such approaches can only be successful if there is a sensible interplay between parameters, objectives, and desired registration outcome. This, however, is not well established. To study this interplay, we use multi-objective optimization, where multiple solutions exist that represent the optimal trade-offs between the objectives, forming a so-called Pareto front. Here, we focus on weight tuning. To study the space a user has to navigate during manual weight tuning, we randomly sample multiple linear combinations. To understand how these combinations relate to desirability of registration outcome, we associate with each outcome a mean target registration error (TRE) based on expert-defined anatomical landmarks. Further, we employ a multi-objective evolutionary algorithm that optimizes the weight combinations, yielding a Pareto front of solutions, which can be directly navigated by the user. To study how the complexity of manual weight tuning changes depending on the registration problem, we consider an easy problem, prone-to-prone breast MR image registration, and a hard problem, prone-to-supine breast MR image registration. Lastly, we investigate how guidance information as an additional objective influences the prone-to-supine registration outcome. Results show that the interplay between weights, objectives, and registration outcome makes manual weight tuning feasible for the prone-to-prone problem, but very challenging for the harder prone-to-supine problem. Here, patient-specific, multi-objective weight optimization is needed, obtaining a mean TRE of 13.6 mm without guidance

  8. Estimation of slipping organ motion by registration with direction-dependent regularization.

    PubMed

    Schmidt-Richberg, Alexander; Werner, René; Handels, Heinz; Ehrhardt, Jan

    2012-01-01

    Accurate estimation of respiratory motion is essential for many applications in medical 4D imaging, for example for radiotherapy of thoracic and abdominal tumors. It is usually done by non-linear registration of image scans at different states of the breathing cycle but without further modeling of specific physiological motion properties. In this context, the accurate computation of respiration-driven lung motion is especially challenging because this organ is sliding along the surrounding tissue during the breathing cycle, leading to discontinuities in the motion field. Without considering this property in the registration model, common intensity-based algorithms cause incorrect estimation along the object boundaries. In this paper, we present a model for incorporating slipping motion in image registration. Extending the common diffusion registration by distinguishing between normal- and tangential-directed motion, we are able to estimate slipping motion at the organ boundaries while preventing gaps and ensuring smooth motion fields inside and outside. We further present an algorithm for a fully automatic detection of discontinuities in the motion field, which does not rely on a prior segmentation of the organ. We evaluate the approach for the estimation of lung motion based on 23 inspiration/expiration pairs of thoracic CT images. The results show a visually more plausible motion estimation. Moreover, the target registration error is quantified using manually defined landmarks and a significant improvement over the standard diffusion regularization is shown. Copyright © 2011 Elsevier B.V. All rights reserved.

  9. Robust registration of sparsely sectioned histology to ex-vivo MRI of temporal lobe resections

    NASA Astrophysics Data System (ADS)

    Goubran, Maged; Khan, Ali R.; Crukley, Cathie; Buchanan, Susan; Santyr, Brendan; deRibaupierre, Sandrine; Peters, Terry M.

    2012-02-01

    Surgical resection of epileptic foci is a typical treatment for drug-resistant epilepsy, however, accurate preoperative localization is challenging and often requires invasive sub-dural or intra-cranial electrode placement. The presence of cellular abnormalities in the resected tissue can be used to validate the effectiveness of multispectralMagnetic Resonance Imaging (MRI) in pre-operative foci localization and surgical planning. If successful, these techniques can lead to improved surgical outcomes and less invasive procedures. Towards this goal, a novel pipeline is presented here for post-operative imaging of temporal lobe specimens involving MRI and digital histology, and present and evaluate methods for bringing these images into spatial correspondence. The sparsely-sectioned histology images of resected tissue represents a challenge for 3D reconstruction which we address with a combined 3D and 2D rigid registration algorithm that alternates between slice-based and volume-based registration with the ex-vivo MRI. We also evaluate four methods for non-rigid within-plane registration using both images and fiducials, with the top performing method resulting in a target registration error of 0.87 mm. This work allows for the spatially-local comparison of histology with post-operative MRI and paves the way for eventual registration with pre-operative MRI images.

  10. Registration of an on-axis see-through head-mounted display and camera system

    NASA Astrophysics Data System (ADS)

    Luo, Gang; Rensing, Noa M.; Weststrate, Evan; Peli, Eli

    2005-02-01

    An optical see-through head-mounted display (HMD) system integrating a miniature camera that is aligned with the user's pupil is developed and tested. Such an HMD system has a potential value in many augmented reality applications, in which registration of the virtual display to the real scene is one of the critical aspects. The camera alignment to the user's pupil results in a simple yet accurate calibration and a low registration error across a wide range of depth. In reality, a small camera-eye misalignment may still occur in such a system due to the inevitable variations of HMD wearing position with respect to the eye. The effects of such errors are measured. Calculation further shows that the registration error as a function of viewing distance behaves nearly the same for different virtual image distances, except for a shift. The impact of prismatic effect of the display lens on registration is also discussed.

  11. Sci—Fri AM: Mountain — 06: Optimizing planning target volume in lung radiotherapy using deformable registration

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hoang, P; Wierzbicki, M; Juravinski Cancer Centre, Medical Physics Department, Hamilton, Ontario

    A four dimensional computed tomography (4DCT) image is acquired for all radically treated, lung cancer patients to define the internal target volume (ITV), which encompasses tumour motion due to breathing and subclinical disease. Patient set-up error and anatomical motion that is not due to breathing is addressed through an additional 1 cm margin around the ITV to obtain the planning target volume (PTV). The objective of this retrospective study is to find the minimum PTV margin that provides an acceptable probability of delivering the prescribed dose to the ITV. Acquisition of a kV cone beam computed tomography (CBCT) image atmore » each fraction was used to shift the treatment couch to accurately align the spinal cord and carina. Our method utilized deformable image registration to automatically position the planning ITV on each CBCT. We evaluated the percentage of the ITV surface that fell within various PTVs for 79 fractions across 18 patients. Treatment success was defined as a situation where at least 99% of the ITV is covered by the PTV. Overall, this is to be achieved in at least 90% of the treatment fractions. The current approach with a 1cm PTV margin was successful ∼96% of the time. This analysis revealed that the current margin can be reduced to 0.8cm isotropic or 0.6×0.6×1 cm{sup 3} non-isotropic, which were successful 92 and 91 percent of the time respectively. Moreover, we have shown that these margins maintain accuracy, despite intrafractional variation, and maximize CBCT image guidance capabilities.« less

  12. Monoplane 3D-2D registration of cerebral angiograms based on multi-objective stratified optimization

    NASA Astrophysics Data System (ADS)

    Aksoy, T.; Špiclin, Ž.; Pernuš, F.; Unal, G.

    2017-12-01

    Registration of 3D pre-interventional to 2D intra-interventional medical images has an increasingly important role in surgical planning, navigation and treatment, because it enables the physician to co-locate depth information given by pre-interventional 3D images with the live information in intra-interventional 2D images such as x-ray. Most tasks during image-guided interventions are carried out under a monoplane x-ray, which is a highly ill-posed problem for state-of-the-art 3D to 2D registration methods. To address the problem of rigid 3D-2D monoplane registration we propose a novel multi-objective stratified parameter optimization, wherein a small set of high-magnitude intensity gradients are matched between the 3D and 2D images. The stratified parameter optimization matches rotation templates to depth templates, first sampled from projected 3D gradients and second from the 2D image gradients, so as to recover 3D rigid-body rotations and out-of-plane translation. The objective for matching was the gradient magnitude correlation coefficient, which is invariant to in-plane translation. The in-plane translations are then found by locating the maximum of the gradient phase correlation between the best matching pair of rotation and depth templates. On twenty pairs of 3D and 2D images of ten patients undergoing cerebral endovascular image-guided intervention the 3D to monoplane 2D registration experiments were setup with a rather high range of initial mean target registration error from 0 to 100 mm. The proposed method effectively reduced the registration error to below 2 mm, which was further refined by a fast iterative method and resulted in a high final registration accuracy (0.40 mm) and high success rate (> 96%). Taking into account a fast execution time below 10 s, the observed performance of the proposed method shows a high potential for application into clinical image-guidance systems.

  13. Incorporation of a laser range scanner into image-guided liver surgery: surface acquisition, registration, and tracking.

    PubMed

    Cash, David M; Sinha, Tuhin K; Chapman, William C; Terawaki, Hiromi; Dawant, Benoit M; Galloway, Robert L; Miga, Michael I

    2003-07-01

    As image guided surgical procedures become increasingly diverse, there will be more scenarios where point-based fiducials cannot be accurately localized for registration and rigid body assumptions no longer hold. As a result, procedures will rely more frequently on anatomical surfaces for the basis of image alignment and will require intraoperative geometric data to measure and compensate for tissue deformation in the organ. In this paper we outline methods for which a laser range scanner may be used to accomplish these tasks intraoperatively. A laser range scanner based on the optical principle of triangulation acquires a dense set of three-dimensional point data in a very rapid, noncontact fashion. Phantom studies were performed to test the ability to link range scan data with traditional modes of image-guided surgery data through localization, registration, and tracking in physical space. The experiments demonstrate that the scanner is capable of localizing point-based fiducials to within 0.2 mm and capable of achieving point and surface based registrations with target registration error of less than 2.0 mm. Tracking points in physical space with the range scanning system yields an error of 1.4 +/- 0.8 mm. Surface deformation studies were performed with the range scanner in order to determine if this device was capable of acquiring enough information for compensation algorithms. In the surface deformation studies, the range scanner was able to detect changes in surface shape due to deformation comparable to those detected by tomographic image studies. Use of the range scanner has been approved for clinical trials, and an initial intraoperative range scan experiment is presented. In all of these studies, the primary source of error in range scan data is deterministically related to the position and orientation of the surface within the scanner's field of view. However, this systematic error can be corrected, allowing the range scanner to provide a rapid, robust

  14. Evaluation of nonrigid registration models for interfraction dose accumulation in radiotherapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Janssens, Guillaume; Orban de Xivry, Jonathan; Fekkes, Stein

    2009-09-15

    Purpose: Interfraction dose accumulation is necessary to evaluate the dose distribution of an entire course of treatment by adding up multiple dose distributions of different treatment fractions. This accumulation of dose distributions is not straightforward as changes in the patient anatomy may occur during treatment. For this purpose, the accuracy of nonrigid registration methods is assessed for dose accumulation based on the calculated deformations fields. Methods: A phantom study using a deformable cubic silicon phantom with implanted markers and a cylindrical silicon phantom with MOSFET detectors has been performed. The phantoms were deformed and images were acquired using a cone-beammore » CT imager. Dose calculations were performed on these CT scans using the treatment planning system. Nonrigid CT-based registration was performed using two different methods, the Morphons and Demons. The resulting deformation field was applied on the dose distribution. For both phantoms, accuracy of the registered dose distribution was assessed. For the cylindrical phantom, also measured dose values in the deformed conditions were compared with the dose values of the registered dose distributions. Finally, interfraction dose accumulation for two treatment fractions of a patient with primary rectal cancer has been performed and evaluated using isodose lines and the dose volume histograms of the target volume and normal tissue. Results: A significant decrease in the difference in marker or MOSFET position was observed after nonrigid registration methods (p<0.001) for both phantoms and with both methods, as well as a significant decrease in the dose estimation error (p<0.01 for the cubic phantom and p<0.001 for the cylindrical) with both methods. Considering the whole data set at once, the difference between estimated and measured doses was also significantly decreased using registration (p<0.001 for both methods). The patient case showed a slightly underdosed planning target

  15. Effect of limbal marking prior to laser ablation on the magnitude of cyclotorsional error.

    PubMed

    Chen, Xiangjun; Stojanovic, Aleksandar; Stojanovic, Filip; Eidet, Jon Roger; Raeder, Sten; Øritsland, Haakon; Utheim, Tor Paaske

    2012-05-01

    To evaluate the residual registration error after limbal-marking-based manual adjustment in cyclotorsional tracker-controlled laser refractive surgery. Two hundred eyes undergoing custom surface ablation with the iVIS Suite (iVIS Technologies) were divided into limbal marked (marked) and non-limbal marked (unmarked) groups. Iris registration information was acquired preoperatively from all eyes. Preoperatively, the horizontal axis was recorded in the marked group for use in manual cyclotorsional alignment prior to surgical iris registration. During iris registration, the preoperative iris information was compared to the eye-tracker captured image. The magnitudes of the registration error angle and cyclotorsional movement during the subsequent laser ablation were recorded and analyzed. Mean magnitude of registration error angle (absolute value) was 1.82°±1.31° (range: 0.00° to 5.50°) and 2.90°±2.40° (range: 0.00° to 13.50°) for the marked and unmarked groups, respectively (P<.001). Mean magnitude of cyclotorsional movement during the laser ablation (absolute value) was 1.15°±1.34° (range: 0.00° to 7.00°) and 0.68°±0.97° (range: 0.00° to 6.00°) for the marked and unmarked groups, respectively (P=.005). Forty-six percent and 60% of eyes had registration error >2°, whereas 22% and 20% of eyes had cyclotorsional movement during ablation >2° in the marked and unmarked groups, respectively. Limbal-marking-based manual alignment prior to laser ablation significantly reduced cyclotorsional registration error. However, residual registration misalignment and cyclotorsional movements remained during ablation. Copyright 2012, SLACK Incorporated.

  16. Calculation of the confidence intervals for transformation parameters in the registration of medical images

    PubMed Central

    Bansal, Ravi; Staib, Lawrence H.; Laine, Andrew F.; Xu, Dongrong; Liu, Jun; Posecion, Lainie F.; Peterson, Bradley S.

    2010-01-01

    Images from different individuals typically cannot be registered precisely because anatomical features within the images differ across the people imaged and because the current methods for image registration have inherent technological limitations that interfere with perfect registration. Quantifying the inevitable error in image registration is therefore of crucial importance in assessing the effects that image misregistration may have on subsequent analyses in an imaging study. We have developed a mathematical framework for quantifying errors in registration by computing the confidence intervals of the estimated parameters (3 translations, 3 rotations, and 1 global scale) for the similarity transformation. The presence of noise in images and the variability in anatomy across individuals ensures that estimated registration parameters are always random variables. We assume a functional relation among intensities across voxels in the images, and we use the theory of nonlinear, least-squares estimation to show that the parameters are multivariate Gaussian distributed. We then use the covariance matrix of this distribution to compute the confidence intervals of the transformation parameters. These confidence intervals provide a quantitative assessment of the registration error across the images. Because transformation parameters are nonlinearly related to the coordinates of landmark points in the brain, we subsequently show that the coordinates of those landmark points are also multivariate Gaussian distributed. Using these distributions, we then compute the confidence intervals of the coordinates for landmark points in the image. Each of these confidence intervals in turn provides a quantitative assessment of the registration error at a particular landmark point. Because our method is computationally intensive, however, its current implementation is limited to assessing the error of the parameters in the similarity transformation across images. We assessed the

  17. Identifying types and causes of errors in mortality data in a clinical registry using multiple information systems.

    PubMed

    Koetsier, Antonie; Peek, Niels; de Keizer, Nicolette

    2012-01-01

    Errors may occur in the registration of in-hospital mortality, making it less reliable as a quality indicator. We assessed the types of errors made in in-hospital mortality registration in the clinical quality registry National Intensive Care Evaluation (NICE) by comparing its mortality data to data from a national insurance claims database. Subsequently, we performed site visits at eleven Intensive Care Units (ICUs) to investigate the number, types and causes of errors made in in-hospital mortality registration. A total of 255 errors were found in the NICE registry. Two different types of software malfunction accounted for almost 80% of the errors. The remaining 20% were five types of manual transcription errors and human failures to record outcome data. Clinical registries should be aware of the possible existence of errors in recorded outcome data and understand their causes. In order to prevent errors, we recommend to thoroughly verify the software that is used in the registration process.

  18. Bilateral filter regularized accelerated Demons for improved discontinuity preserving registration.

    PubMed

    Demirović, D; Šerifović-Trbalić, A; Prljača, N; Cattin, Ph C

    2015-03-01

    The classical accelerated Demons algorithm uses Gaussian smoothing to penalize oscillatory motion in the displacement fields during registration. This well known method uses the L2 norm for regularization. Whereas the L2 norm is known for producing well behaving smooth deformation fields it cannot properly deal with discontinuities often seen in the deformation field as the regularizer cannot differentiate between discontinuities and smooth part of motion field. In this paper we propose replacement the Gaussian filter of the accelerated Demons with a bilateral filter. In contrast the bilateral filter not only uses information from displacement field but also from the image intensities. In this way we can smooth the motion field depending on image content as opposed to the classical Gaussian filtering. By proper adjustment of two tunable parameters one can obtain more realistic deformations in a case of discontinuity. The proposed approach was tested on 2D and 3D datasets and showed significant improvements in the Target Registration Error (TRE) for the well known POPI dataset. Despite the increased computational complexity, the improved registration result is justified in particular abdominal data sets where discontinuities often appear due to sliding organ motion. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Performance Evaluation of MIND Demons Deformable Registration of MR and CT Images in Spinal Interventions

    PubMed Central

    Reaungamornrat, S.; De Silva, T.; Uneri, A.; Goerres, J.; Jacobson, M.; Ketcha, M.; Vogt, S.; Kleinszig, G.; Khanna, A. J.; Wolinsky, J.-P.; Prince, J. L.; Siewerdsen, J. H.

    2016-01-01

    Accurate intraoperative localization of target anatomy and adjacent nervous and vascular tissue is essential to safe, effective surgery, and multimodality deformable registration can be used to identify such anatomy by fusing preoperative CT or MR images with intraoperative images. A deformable image registration method has been developed to estimate viscoelastic diffeomorphisms between preoperative MR and intraoperative CT using modality-independent neighborhood descriptors (MIND) and a Huber metric for robust registration. The method, called MIND Demons, optimizes a constrained symmetric energy functional incorporating priors on smoothness, geodesics, and invertibility by alternating between Gauss-Newton optimization and Tikhonov regularization in a multiresolution scheme. Registration performance was evaluated for the MIND Demons method with a symmetric energy formulation in comparison to an asymmetric form, and sensitivity to anisotropic MR voxel-size was analyzed in phantom experiments emulating image-guided spine-surgery in comparison to a free-form deformation (FFD) method using local mutual information (LMI). Performance was validated in a clinical study involving 15 patients undergoing intervention of the cervical, thoracic, and lumbar spine. The target registration error (TRE) for the symmetric MIND Demons formulation [1.3 ± 0.8 mm (median ± interquartile)] outperformed the asymmetric form [3.6 ± 4.4 mm]. The method demonstrated fairly minor sensitivity to anisotropic MR voxel size, with median TRE ranging 1.3 – 2.9 mm for MR slice thickness ranging 0.9 – 9.9 mm, compared to TRE = 3.2 – 4.1 mm for LMI FFD over the same range. Evaluation in clinical data demonstrated sub-voxel TRE (< 2 mm) in all fifteen cases with realistic deformations that preserved topology with sub-voxel invertibility (0.001 mm) and positive-determinant spatial Jacobians. The approach therefore appears robust against realistic anisotropic resolution characteristics in MR and

  20. Sinusoidal Siemens star spatial frequency response measurement errors due to misidentified target centers

    DOE PAGES

    Birch, Gabriel Carisle; Griffin, John Clark

    2015-07-23

    Numerous methods are available to measure the spatial frequency response (SFR) of an optical system. A recent change to the ISO 12233 photography resolution standard includes a sinusoidal Siemens star test target. We take the sinusoidal Siemens star proposed by the ISO 12233 standard, measure system SFR, and perform an analysis of errors induced by incorrectly identifying the center of a test target. We show a closed-form solution for the radial profile intensity measurement given an incorrectly determined center and describe how this error reduces the measured SFR of the system. As a result, using the closed-form solution, we proposemore » a two-step process by which test target centers are corrected and the measured SFR is restored to the nominal, correctly centered values.« less

  1. Adaptive marker-free registration using a multiple point strategy for real-time and robust endoscope electromagnetic navigation.

    PubMed

    Luo, Xiongbiao; Wan, Ying; He, Xiangjian; Mori, Kensaku

    2015-02-01

    Registration of pre-clinical images to physical space is indispensable for computer-assisted endoscopic interventions in operating rooms. Electromagnetically navigated endoscopic interventions are increasingly performed at current diagnoses and treatments. Such interventions use an electromagnetic tracker with a miniature sensor that is usually attached at an endoscope distal tip to real time track endoscope movements in a pre-clinical image space. Spatial alignment between the electromagnetic tracker (or sensor) and pre-clinical images must be performed to navigate the endoscope to target regions. This paper proposes an adaptive marker-free registration method that uses a multiple point selection strategy. This method seeks to address an assumption that the endoscope is operated along the centerline of an intraluminal organ which is easily violated during interventions. We introduce an adaptive strategy that generates multiple points in terms of sensor measurements and endoscope tip center calibration. From these generated points, we adaptively choose the optimal point, which is the closest to its assigned the centerline of the hollow organ, to perform registration. The experimental results demonstrate that our proposed adaptive strategy significantly reduced the target registration error from 5.32 to 2.59 mm in static phantoms validation, as well as from at least 7.58 mm to 4.71 mm in dynamic phantom validation compared to current available methods. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  2. Non-rigid registration for fusion of carotid vascular ultrasound and MRI volumetric datasets

    NASA Astrophysics Data System (ADS)

    Chan, R. C.; Sokka, S.; Hinton, D.; Houser, S.; Manzke, R.; Hanekamp, A.; Reddy, V. Y.; Kaazempur-Mofrad, M. R.; Rasche, V.

    2006-03-01

    In carotid plaque imaging, MRI provides exquisite soft-tissue characterization, but lacks the temporal resolution for tissue strain imaging that real-time 3D ultrasound (3DUS) can provide. On the other hand, real-time 3DUS currently lacks the spatial resolution of carotid MRI. Non-rigid alignment of ultrasound and MRI data is essential for integrating complementary morphology and biomechanical information for carotid vascular assessment. We assessed non-rigid registration for fusion of 3DUS and MRI carotid data based on deformable models which are warped to maximize voxel similarity. We performed validation in vitro using isolated carotid artery imaging. These samples were subjected to soft-tissue deformations during 3DUS and were imaged in a static configuration with standard MR carotid pulse sequences. Registration of the source ultrasound sequences to the target MR volume was performed and the mean absolute distance between fiducials within the ultrasound and MR datasets was measured to determine inter-modality alignment quality. Our results indicate that registration errors on the order of 1mm are possible in vitro despite the low-resolution of current generation 3DUS transducers. Registration performance should be further improved with the use of higher frequency 3DUS prototypes and efforts are underway to test those probes for in vivo 3DUS carotid imaging.

  3. Dual-projection 3D-2D registration for surgical guidance: preclinical evaluation of performance and minimum angular separation

    NASA Astrophysics Data System (ADS)

    Uneri, A.; Otake, Y.; Wang, A. S.; Kleinszig, G.; Vogt, S.; Gallia, G. L.; Rigamonti, D.; Wolinsky, J.-P.; Gokaslan, Ziya L.; Khanna, A. J.; Siewerdsen, J. H.

    2014-03-01

    An algorithm for 3D-2D registration of CT and x-ray projections has been developed using dual projection views to provide 3D localization with accuracy exceeding that of conventional tracking systems. The registration framework employs a normalized gradient information (NGI) similarity metric and covariance matrix adaptation evolution strategy (CMAES) to solve for the patient pose in 6 degrees of freedom. Registration performance was evaluated in anthropomorphic head and chest phantoms, as well as a human torso cadaver, using C-arm projection views acquired at angular separations (Δ𝜃) ranging 0-178°. Registration accuracy was assessed in terms target registration error (TRE) and compared to that of an electromagnetic tracker. Studies evaluated the influence of C-arm magnification, x-ray dose, and preoperative CT slice thickness on registration accuracy and the minimum angular separation required to achieve TRE ~2 mm. The results indicate that Δ𝜃 as small as 10-20° is adequate to achieve TRE <2 mm with 95% confidence, comparable or superior to that of commercial trackers. The method allows direct registration of preoperative CT and planning data to intraoperative fluoroscopy, providing 3D localization free from conventional limitations associated with external fiducial markers, stereotactic frames, trackers, and manual registration. The studies support potential application to percutaneous spine procedures and intracranial neurosurgery.

  4. Correlation and registration of ERTS multispectral imagery. [by a digital processing technique

    NASA Technical Reports Server (NTRS)

    Bonrud, L. O.; Henrikson, P. J.

    1974-01-01

    Examples of automatic digital processing demonstrate the feasibility of registering one ERTS multispectral scanner (MSS) image with another obtained on a subsequent orbit, and automatic matching, correlation, and registration of MSS imagery with aerial photography (multisensor correlation) is demonstrated. Excellent correlation was obtained with patch sizes exceeding 16 pixels square. Qualities which lead to effective control point selection are distinctive features, good contrast, and constant feature characteristics. Results of the study indicate that more than 300 degrees of freedom are required to register two standard ERTS-1 MSS frames covering 100 by 100 nautical miles to an accuracy of 0.6 pixel mean radial displacement error. An automatic strip processing technique demonstrates 600 to 1200 degrees of freedom over a quater frame of ERTS imagery. Registration accuracies in the range of 0.3 pixel to 0.5 pixel mean radial error were confirmed by independent error analysis. Accuracies in the range of 0.5 pixel to 1.4 pixel mean radial error were demonstrated by semi-automatic registration over small geographic areas.

  5. SU-E-J-248: Comparative Study of Two Image Registration for Image-Guided Radiation Therapy in Esophageal Cancer

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Shang, K; Wang, J; Liu, D

    2014-06-01

    Purpose: Image-guided radiation therapy (IGRT) is one of the major treatment of esophageal cancer. Gray value registration and bone registration are two kinds of image registration, the purpose of this work is to compare which one is more suitable for esophageal cancer patients. Methods: Twenty three esophageal patients were treated by Elekta Synergy, CBCT images were acquired and automatically registered to planning kilovoltage CT scans according to gray value or bone registration. The setup errors were measured in the X, Y and Z axis, respectively. Two kinds of setup errors were analysed by matching T test statistical method. Results: Fourmore » hundred and five groups of CBCT images were available and the systematic and random setup errors (cm) in X, Y, Z directions were 0.35, 0.63, 0.29 and 0.31, 0.53, 0.21 with gray value registration, while 0.37, 0.64, 0.26 and 0.32, 0.55, 0.20 with bone registration, respectively. Compared with bone registration and gray value registration, the setup errors in X and Z axis have significant differences. In Y axis, both measurement comparison results of T value is 0.256 (P value > 0.05); In X axis, the T value is 5.287(P value < 0.05); In Z axis, the T value is −5.138 (P value < 0.05). Conclusion: Gray value registration is recommended in image-guided radiotherapy for esophageal cancer and the other thoracic tumors. Manual registration could be applied when it is necessary. Bone registration is more suitable for the head tumor and pelvic tumor department where composed of redundant interconnected and immobile bone tissue.« less

  6. Band co-registration modeling of LAPAN-A3/IPB multispectral imager based on satellite attitude

    NASA Astrophysics Data System (ADS)

    Hakim, P. R.; Syafrudin, A. H.; Utama, S.; Jayani, A. P. S.

    2018-05-01

    One of significant geometric distortion on images of LAPAN-A3/IPB multispectral imager is co-registration error between each color channel detector. Band co-registration distortion usually can be corrected by using several approaches, which are manual method, image matching algorithm, or sensor modeling and calibration approach. This paper develops another approach to minimize band co-registration distortion on LAPAN-A3/IPB multispectral image by using supervised modeling of image matching with respect to satellite attitude. Modeling results show that band co-registration error in across-track axis is strongly influenced by yaw angle, while error in along-track axis is fairly influenced by both pitch and roll angle. Accuracy of the models obtained is pretty good, which lies between 1-3 pixels error for each axis of each pair of band co-registration. This mean that the model can be used to correct the distorted images without the need of slower image matching algorithm, nor the laborious effort needed in manual approach and sensor calibration. Since the calculation can be executed in order of seconds, this approach can be used in real time quick-look image processing in ground station or even in satellite on-board image processing.

  7. Fast time-of-flight camera based surface registration for radiotherapy patient positioning.

    PubMed

    Placht, Simon; Stancanello, Joseph; Schaller, Christian; Balda, Michael; Angelopoulou, Elli

    2012-01-01

    This work introduces a rigid registration framework for patient positioning in radiotherapy, based on real-time surface acquisition by a time-of-flight (ToF) camera. Dynamic properties of the system are also investigated for future gating/tracking strategies. A novel preregistration algorithm, based on translation and rotation-invariant features representing surface structures, was developed. Using these features, corresponding three-dimensional points were computed in order to determine initial registration parameters. These parameters became a robust input to an accelerated version of the iterative closest point (ICP) algorithm for the fine-tuning of the registration result. Distance calibration and Kalman filtering were used to compensate for ToF-camera dependent noise. Additionally, the advantage of using the feature based preregistration over an "ICP only" strategy was evaluated, as well as the robustness of the rigid-transformation-based method to deformation. The proposed surface registration method was validated using phantom data. A mean target registration error (TRE) for translations and rotations of 1.62 ± 1.08 mm and 0.07° ± 0.05°, respectively, was achieved. There was a temporal delay of about 65 ms in the registration output, which can be seen as negligible considering the dynamics of biological systems. Feature based preregistration allowed for accurate and robust registrations even at very large initial displacements. Deformations affected the accuracy of the results, necessitating particular care in cases of deformed surfaces. The proposed solution is able to solve surface registration problems with an accuracy suitable for radiotherapy cases where external surfaces offer primary or complementary information to patient positioning. The system shows promising dynamic properties for its use in gating/tracking applications. The overall system is competitive with commonly-used surface registration technologies. Its main benefit is the

  8. Registration of Laser Scanning Point Clouds: A Review

    PubMed Central

    Cheng, Liang; Chen, Song; Xu, Hao; Wu, Yang; Li, Manchun

    2018-01-01

    The integration of multi-platform, multi-angle, and multi-temporal LiDAR data has become important for geospatial data applications. This paper presents a comprehensive review of LiDAR data registration in the fields of photogrammetry and remote sensing. At present, a coarse-to-fine registration strategy is commonly used for LiDAR point clouds registration. The coarse registration method is first used to achieve a good initial position, based on which registration is then refined utilizing the fine registration method. According to the coarse-to-fine framework, this paper reviews current registration methods and their methodologies, and identifies important differences between them. The lack of standard data and unified evaluation systems is identified as a factor limiting objective comparison of different methods. The paper also describes the most commonly-used point cloud registration error analysis methods. Finally, avenues for future work on LiDAR data registration in terms of applications, data, and technology are discussed. In particular, there is a need to address registration of multi-angle and multi-scale data from various newly available types of LiDAR hardware, which will play an important role in diverse applications such as forest resource surveys, urban energy use, cultural heritage protection, and unmanned vehicles. PMID:29883397

  9. Registration of Laser Scanning Point Clouds: A Review.

    PubMed

    Cheng, Liang; Chen, Song; Liu, Xiaoqiang; Xu, Hao; Wu, Yang; Li, Manchun; Chen, Yanming

    2018-05-21

    The integration of multi-platform, multi-angle, and multi-temporal LiDAR data has become important for geospatial data applications. This paper presents a comprehensive review of LiDAR data registration in the fields of photogrammetry and remote sensing. At present, a coarse-to-fine registration strategy is commonly used for LiDAR point clouds registration. The coarse registration method is first used to achieve a good initial position, based on which registration is then refined utilizing the fine registration method. According to the coarse-to-fine framework, this paper reviews current registration methods and their methodologies, and identifies important differences between them. The lack of standard data and unified evaluation systems is identified as a factor limiting objective comparison of different methods. The paper also describes the most commonly-used point cloud registration error analysis methods. Finally, avenues for future work on LiDAR data registration in terms of applications, data, and technology are discussed. In particular, there is a need to address registration of multi-angle and multi-scale data from various newly available types of LiDAR hardware, which will play an important role in diverse applications such as forest resource surveys, urban energy use, cultural heritage protection, and unmanned vehicles.

  10. Non-rigid point set registration of curves: registration of the superficial vessel centerlines of the brain

    NASA Astrophysics Data System (ADS)

    Marreiros, Filipe M. M.; Wang, Chunliang; Rossitti, Sandro; Smedby, Örjan

    2016-03-01

    In this study we present a non-rigid point set registration for 3D curves (composed by 3D set of points). The method was evaluated in the task of registration of 3D superficial vessels of the brain where it was used to match vessel centerline points. It consists of a combination of the Coherent Point Drift (CPD) and the Thin-Plate Spline (TPS) semilandmarks. The CPD is used to perform the initial matching of centerline 3D points, while the semilandmark method iteratively relaxes/slides the points. For the evaluation, a Magnetic Resonance Angiography (MRA) dataset was used. Deformations were applied to the extracted vessels centerlines to simulate brain bulging and sinking, using a TPS deformation where a few control points were manipulated to obtain the desired transformation (T1). Once the correspondences are known, the corresponding points are used to define a new TPS deformation(T2). The errors are measured in the deformed space, by transforming the original points using T1 and T2 and measuring the distance between them. To simulate cases where the deformed vessel data is incomplete, parts of the reference vessels were cut and then deformed. Furthermore, anisotropic normally distributed noise was added. The results show that the error estimates (root mean square error and mean error) are below 1 mm, even in the presence of noise and incomplete data.

  11. Mammogram registration: a phantom-based evaluation of compressed breast thickness variation effects.

    PubMed

    Richard, Frédéric J P; Bakić, Predrag R; Maidment, Andrew D A

    2006-02-01

    The temporal comparison of mammograms is complex; a wide variety of factors can cause changes in image appearance. Mammogram registration is proposed as a method to reduce the effects of these changes and potentially to emphasize genuine alterations in breast tissue. Evaluation of such registration techniques is difficult since ground truth regarding breast deformations is not available in clinical mammograms. In this paper, we propose a systematic approach to evaluate sensitivity of registration methods to various types of changes in mammograms using synthetic breast images with known deformations. As a first step, images of the same simulated breasts with various amounts of simulated physical compression have been used to evaluate a previously described nonrigid mammogram registration technique. Registration performance is measured by calculating the average displacement error over a set of evaluation points identified in mammogram pairs. Applying appropriate thickness compensation and using a preferred order of the registered images, we obtained an average displacement error of 1.6 mm for mammograms with compression differences of 1-3 cm. The proposed methodology is applicable to analysis of other sources of mammogram differences and can be extended to the registration of multimodality breast data.

  12. 37 CFR 201.7 - Cancellation of completed registrations.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... or omissions which would generally have been rectified before registration, the Copyright Office will attempt to rectify the error through correspondence with the remitter. Except in those cases enumerated in...

  13. A global CT to US registration of the lumbar spine

    NASA Astrophysics Data System (ADS)

    Nagpal, Simrin; Hacihaliloglu, Ilker; Ungi, Tamas; Rasoulian, Abtin; Osborn, Jill; Lessoway, Victoria A.; Rohling, Robert N.; Borschneck, Daniel P.; Abolmaesumi, Purang; Mousavi, Parvin

    2014-03-01

    During percutaneous lumbar spine needle interventions, alignment of the preoperative computed tomography (CT) with intraoperative ultrasound (US) can augment anatomical visualization for the clinician. We propose an approach to rigidly align CT and US data of the lumbar spine. The approach involves an intensity-based volume registration step, followed by a surface segmentation and a point-based registration of the entire lumbar spine volume. A clinical feasibility study resulted in mean registration error of approximately 3 mm between CT and US data.

  14. Prostate multimodality image registration based on B-splines and quadrature local energy.

    PubMed

    Mitra, Jhimli; Martí, Robert; Oliver, Arnau; Lladó, Xavier; Ghose, Soumya; Vilanova, Joan C; Meriaudeau, Fabrice

    2012-05-01

    Needle biopsy of the prostate is guided by Transrectal Ultrasound (TRUS) imaging. The TRUS images do not provide proper spatial localization of malignant tissues due to the poor sensitivity of TRUS to visualize early malignancy. Magnetic Resonance Imaging (MRI) has been shown to be sensitive for the detection of early stage malignancy, and therefore, a novel 2D deformable registration method that overlays pre-biopsy MRI onto TRUS images has been proposed. The registration method involves B-spline deformations with Normalized Mutual Information (NMI) as the similarity measure computed from the texture images obtained from the amplitude responses of the directional quadrature filter pairs. Registration accuracy of the proposed method is evaluated by computing the Dice Similarity coefficient (DSC) and 95% Hausdorff Distance (HD) values for 20 patients prostate mid-gland slices and Target Registration Error (TRE) for 18 patients only where homologous structures are visible in both the TRUS and transformed MR images. The proposed method and B-splines using NMI computed from intensities provide average TRE values of 2.64 ± 1.37 and 4.43 ± 2.77 mm respectively. Our method shows statistically significant improvement in TRE when compared with B-spline using NMI computed from intensities with Student's t test p = 0.02. The proposed method shows 1.18 times improvement over thin-plate splines registration with average TRE of 3.11 ± 2.18 mm. The mean DSC and the mean 95% HD values obtained with the proposed method of B-spline with NMI computed from texture are 0.943 ± 0.039 and 4.75 ± 2.40 mm respectively. The texture energy computed from the quadrature filter pairs provides better registration accuracy for multimodal images than raw intensities. Low TRE values of the proposed registration method add to the feasibility of it being used during TRUS-guided biopsy.

  15. Altitude Registration of Limb-Scattered Radiation

    NASA Technical Reports Server (NTRS)

    Moy, Leslie; Bhartia, Pawan K.; Jaross, Glen; Loughman, Robert; Kramarova, Natalya; Chen, Zhong; Taha, Ghassan; Chen, Grace; Xu, Philippe

    2017-01-01

    One of the largest constraints to the retrieval of accurate ozone profiles from UV backscatter limb sounding sensors is altitude registration. Two methods, the Rayleigh scattering attitude sensing (RSAS) and absolute radiance residual method (ARRM), are able to determine altitude registration to the accuracy necessary for long-term ozone monitoring. The methods compare model calculations of radiances to measured radiances and are independent of onboard tracking devices. RSAS determines absolute altitude errors, but, because the method is susceptible to aerosol interference, it is limited to latitudes and time periods with minimal aerosol contamination. ARRM, a new technique introduced in this paper, can be applied across all seasons and altitudes. However, it is only appropriate for relative altitude error estimates. The application of RSAS to Limb Profiler (LP) measurements from the Ozone Mapping and Profiler Suite (OMPS) on board the Suomi NPP (SNPP) satellite indicates tangent height (TH) errors greater than 1 km with an absolute accuracy of +/-200 m. Results using ARRM indicate a approx. 300 to 400m intra-orbital TH change varying seasonally +/-100 m, likely due to either errors in the spacecraft pointing or in the geopotential height (GPH) data that we use in our analysis. ARRM shows a change of approx. 200m over 5 years with a relative accuracy (a long-term accuracy) of 100m outside the polar regions.

  16. Accuracy of radiotherapy dose calculations based on cone-beam CT: comparison of deformable registration and image correction based methods

    NASA Astrophysics Data System (ADS)

    Marchant, T. E.; Joshi, K. D.; Moore, C. J.

    2018-03-01

    Radiotherapy dose calculations based on cone-beam CT (CBCT) images can be inaccurate due to unreliable Hounsfield units (HU) in the CBCT. Deformable image registration of planning CT images to CBCT, and direct correction of CBCT image values are two methods proposed to allow heterogeneity corrected dose calculations based on CBCT. In this paper we compare the accuracy and robustness of these two approaches. CBCT images for 44 patients were used including pelvis, lung and head & neck sites. CBCT HU were corrected using a ‘shading correction’ algorithm and via deformable registration of planning CT to CBCT using either Elastix or Niftyreg. Radiotherapy dose distributions were re-calculated with heterogeneity correction based on the corrected CBCT and several relevant dose metrics for target and OAR volumes were calculated. Accuracy of CBCT based dose metrics was determined using an ‘override ratio’ method where the ratio of the dose metric to that calculated on a bulk-density assigned version of the same image is assumed to be constant for each patient, allowing comparison to the patient’s planning CT as a gold standard. Similar performance is achieved by shading corrected CBCT and both deformable registration algorithms, with mean and standard deviation of dose metric error less than 1% for all sites studied. For lung images, use of deformed CT leads to slightly larger standard deviation of dose metric error than shading corrected CBCT with more dose metric errors greater than 2% observed (7% versus 1%).

  17. Simultaneous Nonrigid Registration, Segmentation, and Tumor Detection in MRI Guided Cervical Cancer Radiation Therapy

    PubMed Central

    Lu, Chao; Chelikani, Sudhakar; Jaffray, David A.; Milosevic, Michael F.; Staib, Lawrence H.; Duncan, James S.

    2013-01-01

    External beam radiation therapy (EBRT) for the treatment of cancer enables accurate placement of radiation dose on the cancerous region. However, the deformation of soft tissue during the course of treatment, such as in cervical cancer, presents significant challenges for the delineation of the target volume and other structures of interest. Furthermore, the presence and regression of pathologies such as tumors may violate registration constraints and cause registration errors. In this paper, automatic segmentation, nonrigid registration and tumor detection in cervical magnetic resonance (MR) data are addressed simultaneously using a unified Bayesian framework. The proposed novel method can generate a tumor probability map while progressively identifying the boundary of an organ of interest based on the achieved nonrigid transformation. The method is able to handle the challenges of significant tumor regression and its effect on surrounding tissues. The new method was compared to various currently existing algorithms on a set of 36 MR data from six patients, each patient has six T2-weighted MR cervical images. The results show that the proposed approach achieves an accuracy comparable to manual segmentation and it significantly outperforms the existing registration algorithms. In addition, the tumor detection result generated by the proposed method has a high agreement with manual delineation by a qualified clinician. PMID:22328178

  18. Depth-resolved registration of transesophageal echo to x-ray fluoroscopy using an inverse geometry fluoroscopy system

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hatt, Charles R.; Tomkowiak, Michael T.; Dunkerley, David A. P.

    2015-12-15

    Purpose: Image registration between standard x-ray fluoroscopy and transesophageal echocardiography (TEE) has recently been proposed. Scanning-beam digital x-ray (SBDX) is an inverse geometry fluoroscopy system designed for cardiac procedures. This study presents a method for 3D registration of SBDX and TEE images based on the tomosynthesis and 3D tracking capabilities of SBDX. Methods: The registration algorithm utilizes the stack of tomosynthetic planes produced by the SBDX system to estimate the physical 3D coordinates of salient key-points on the TEE probe. The key-points are used to arrive at an initial estimate of the probe pose, which is then refined using amore » 2D/3D registration method adapted for inverse geometry fluoroscopy. A phantom study was conducted to evaluate probe pose estimation accuracy relative to the ground truth, as defined by a set of coregistered fiducial markers. This experiment was conducted with varying probe poses and levels of signal difference-to-noise ratio (SDNR). Additional phantom and in vivo studies were performed to evaluate the correspondence of catheter tip positions in TEE and x-ray images following registration of the two modalities. Results: Target registration error (TRE) was used to characterize both pose estimation and registration accuracy. In the study of pose estimation accuracy, successful pose estimates (3D TRE < 5.0 mm) were obtained in 97% of cases when the SDNR was 5.9 or higher in seven out of eight poses. Under these conditions, 3D TRE was 2.32 ± 1.88 mm, and 2D (projection) TRE was 1.61 ± 1.36 mm. Probe localization error along the source-detector axis was 0.87 ± 1.31 mm. For the in vivo experiments, mean 3D TRE ranged from 2.6 to 4.6 mm and mean 2D TRE ranged from 1.1 to 1.6 mm. Anatomy extracted from the echo images appeared well aligned when projected onto the SBDX images. Conclusions: Full 6 DOF image registration between SBDX and TEE is feasible and accurate to within 5 mm. Future studies will

  19. Stopping Criteria for Log-Domain Diffeomorphic Demons Registration: An Experimental Survey for Radiotherapy Application.

    PubMed

    Peroni, M; Golland, P; Sharp, G C; Baroni, G

    2016-02-01

    A crucial issue in deformable image registration is achieving a robust registration algorithm at a reasonable computational cost. Given the iterative nature of the optimization procedure an algorithm must automatically detect convergence, and stop the iterative process when most appropriate. This paper ranks the performances of three stopping criteria and six stopping value computation strategies for a Log-Domain Demons Deformable registration method simulating both a coarse and a fine registration. The analyzed stopping criteria are: (a) velocity field update magnitude, (b) mean squared error, and (c) harmonic energy. Each stoping condition is formulated so that the user defines a threshold ∊, which quantifies the residual error that is acceptable for the particular problem and calculation strategy. In this work, we did not aim at assigning a value to e, but to give insights in how to evaluate and to set the threshold on a given exit strategy in a very popular registration scheme. Experiments on phantom and patient data demonstrate that comparing the optimization metric minimum over the most recent three iterations with the minimum over the fourth to sixth most recent iterations can be an appropriate algorithm stopping strategy. The harmonic energy was found to provide best trade-off between robustness and speed of convergence for the analyzed registration method at coarse registration, but was outperformed by mean squared error when all the original pixel information is used. This suggests the need of developing mathematically sound new convergence criteria in which both image and vector field information could be used to detect the actual convergence, which could be especially useful when considering multi-resolution registrations. Further work should be also dedicated to study same strategies performances in other deformable registration methods and body districts. © The Author(s) 2014.

  20. On the dosimetric effect and reduction of inverse consistency and transitivity errors in deformable image registration for dose accumulation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bender, Edward T.; Hardcastle, Nicholas; Tome, Wolfgang A.

    2012-01-15

    Purpose: Deformable image registration (DIR) is necessary for accurate dose accumulation between multiple radiotherapy image sets. DIR algorithms can suffer from inverse and transitivity inconsistencies. When using deformation vector fields (DVFs) that exhibit inverse-inconsistency and are nontransitive, dose accumulation on a given image set via different image pathways will lead to different accumulated doses. The purpose of this study was to investigate the dosimetric effect of and propose a postprocessing solution to reduce inverse consistency and transitivity errors. Methods: Four MVCT images and four phases of a lung 4DCT, each with an associated calculated dose, were selected for analysis. DVFsmore » between all four images in each data set were created using the Fast Symmetric Demons algorithm. Dose was accumulated on the fourth image in each set using DIR via two different image pathways. The two accumulated doses on the fourth image were compared. The inverse consistency and transitivity errors in the DVFs were then reduced. The dose accumulation was repeated using the processed DVFs, the results of which were compared with the accumulated dose from the original DVFs. To evaluate the influence of the postprocessing technique on DVF accuracy, the original and processed DVF accuracy was evaluated on the lung 4DCT data on which anatomical landmarks had been identified by an expert. Results: Dose accumulation to the same image via different image pathways resulted in two different accumulated dose results. After the inverse consistency errors were reduced, the difference between the accumulated doses diminished. The difference was further reduced after reducing the transitivity errors. The postprocessing technique had minimal effect on the accuracy of the DVF for the lung 4DCT images. Conclusions: This study shows that inverse consistency and transitivity errors in DIR have a significant dosimetric effect in dose accumulation; Depending on the image pathway

  1. [Medical image elastic registration smoothed by unconstrained optimized thin-plate spline].

    PubMed

    Zhang, Yu; Li, Shuxiang; Chen, Wufan; Liu, Zhexing

    2003-12-01

    Elastic registration of medical image is an important subject in medical image processing. Previous work has concentrated on selecting the corresponding landmarks manually and then using thin-plate spline interpolating to gain the elastic transformation. However, the landmarks extraction is always prone to error, which will influence the registration results. Localizing the landmarks manually is also difficult and time-consuming. We the optimization theory to improve the thin-plate spline interpolation, and based on it, used an automatic method to extract the landmarks. Combining these two steps, we have proposed an automatic, exact and robust registration method and have gained satisfactory registration results.

  2. Automated robust registration of grossly misregistered whole-slide images with varying stains

    NASA Astrophysics Data System (ADS)

    Litjens, G.; Safferling, K.; Grabe, N.

    2016-03-01

    Cancer diagnosis and pharmaceutical research increasingly depend on the accurate quantification of cancer biomarkers. Identification of biomarkers is usually performed through immunohistochemical staining of cancer sections on glass slides. However, combination of multiple biomarkers from a wide variety of immunohistochemically stained slides is a tedious process in traditional histopathology due to the switching of glass slides and re-identification of regions of interest by pathologists. Digital pathology now allows us to apply image registration algorithms to digitized whole-slides to align the differing immunohistochemical stains automatically. However, registration algorithms need to be robust to changes in color due to differing stains and severe changes in tissue content between slides. In this work we developed a robust registration methodology to allow for fast coarse alignment of multiple immunohistochemical stains to the base hematyoxylin and eosin stained image. We applied HSD color model conversion to obtain a less stain color dependent representation of the whole-slide images. Subsequently, optical density thresholding and connected component analysis were used to identify the relevant regions for registration. Template matching using normalized mutual information was applied to provide initial translation and rotation parameters, after which a cost function-driven affine registration was performed. The algorithm was validated using 40 slides from 10 prostate cancer patients, with landmark registration error as a metric. Median landmark registration error was around 180 microns, which indicates performance is adequate for practical application. None of the registrations failed, indicating the robustness of the algorithm.

  3. Estimation of the uncertainty of elastic image registration with the demons algorithm.

    PubMed

    Hub, M; Karger, C P

    2013-05-07

    The accuracy of elastic image registration is limited. We propose an approach to detect voxels where registration based on the demons algorithm is likely to perform inaccurately, compared to other locations of the same image. The approach is based on the assumption that the local reproducibility of the registration can be regarded as a measure of uncertainty of the image registration. The reproducibility is determined as the standard deviation of the displacement vector components obtained from multiple registrations. These registrations differ in predefined initial deformations. The proposed approach was tested with artificially deformed lung images, where the ground truth on the deformation is known. In voxels where the result of the registration was less reproducible, the registration turned out to have larger average registration errors as compared to locations of the same image, where the registration was more reproducible. The proposed method can show a clinician in which area of the image the elastic registration with the demons algorithm cannot be expected to be accurate.

  4. Motion tracking in the liver: Validation of a method based on 4D ultrasound using a nonrigid registration technique

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Vijayan, Sinara, E-mail: sinara.vijayan@ntnu.no; Klein, Stefan; Hofstad, Erlend Fagertun

    Purpose: Treatments like radiotherapy and focused ultrasound in the abdomen require accurate motion tracking, in order to optimize dosage delivery to the target and minimize damage to critical structures and healthy tissues around the target. 4D ultrasound is a promising modality for motion tracking during such treatments. In this study, the authors evaluate the accuracy of motion tracking in the liver based on deformable registration of 4D ultrasound images. Methods: The offline analysis was performed using a nonrigid registration algorithm that was specifically designed for motion estimation from dynamic imaging data. The method registers the entire 4D image data sequencemore » in a groupwise optimization fashion, thus avoiding a bias toward a specifically chosen reference time point. Three healthy volunteers were scanned over several breathing cycles (12 s) from three different positions and angles on the abdomen; a total of nine 4D scans for the three volunteers. Well-defined anatomic landmarks were manually annotated in all 96 time frames for assessment of the automatic algorithm. The error of the automatic motion estimation method was compared with interobserver variability. The authors also performed experiments to investigate the influence of parameters defining the deformation field flexibility and evaluated how well the method performed with a lower temporal resolution in order to establish the minimum frame rate required for accurate motion estimation. Results: The registration method estimated liver motion with an error of 1 mm (75% percentile over all datasets), which was lower than the interobserver variability of 1.4 mm. The results were only slightly dependent on the degrees of freedom of the deformation model. The registration error increased to 2.8 mm with an eight times lower temporal resolution. Conclusions: The authors conclude that the methodology was able to accurately track the motion of the liver in the 4D ultrasound data. The authors

  5. Deformable registration for image-guided spine surgery: preserving rigid body vertebral morphology in free-form transformations

    NASA Astrophysics Data System (ADS)

    Reaungamornrat, S.; Wang, A. S.; Uneri, A.; Otake, Y.; Zhao, Z.; Khanna, A. J.; Siewerdsen, J. H.

    2014-03-01

    Purpose: Deformable registration of preoperative and intraoperative images facilitates accurate localization of target and critical anatomy in image-guided spine surgery. However, conventional deformable registration fails to preserve the morphology of rigid bone anatomy and can impart distortions that confound high-precision intervention. We propose a constrained registration method that preserves rigid morphology while allowing deformation of surrounding soft tissues. Method: The registration method aligns preoperative 3D CT to intraoperative cone-beam CT (CBCT) using free-form deformation (FFD) with penalties on rigid body motion imposed according to a simple intensity threshold. The penalties enforced 3 properties of a rigid transformation - namely, constraints on affinity (AC), orthogonality (OC), and properness (PC). The method also incorporated an injectivity constraint (IC) to preserve topology. Physical experiments (involving phantoms, an ovine spine, and a human cadaver) as well as digital simulations were performed to evaluate the sensitivity to registration parameters, preservation of rigid body morphology, and overall registration accuracy of constrained FFD in comparison to conventional unconstrained FFD (denoted uFFD) and Demons registration. Result: FFD with orthogonality and injectivity constraints (denoted FFD+OC+IC) demonstrated improved performance compared to uFFD and Demons. Affinity and properness constraints offered little or no additional improvement. The FFD+OC+IC method preserved rigid body morphology at near-ideal values of zero dilatation (D = 0.05, compared to 0.39 and 0.56 for uFFD and Demons, respectively) and shear (S = 0.08, compared to 0.36 and 0.44 for uFFD and Demons, respectively). Target registration error (TRE) was similarly improved for FFD+OC+IC (0.7 mm), compared to 1.4 and 1.8 mm for uFFD and Demons. Results were validated in human cadaver studies using CT and CBCT images, with FFD+OC+IC providing excellent preservation

  6. 3D/2D model-to-image registration by imitation learning for cardiac procedures.

    PubMed

    Toth, Daniel; Miao, Shun; Kurzendorfer, Tanja; Rinaldi, Christopher A; Liao, Rui; Mansi, Tommaso; Rhode, Kawal; Mountney, Peter

    2018-05-12

    In cardiac interventions, such as cardiac resynchronization therapy (CRT), image guidance can be enhanced by involving preoperative models. Multimodality 3D/2D registration for image guidance, however, remains a significant research challenge for fundamentally different image data, i.e., MR to X-ray. Registration methods must account for differences in intensity, contrast levels, resolution, dimensionality, field of view. Furthermore, same anatomical structures may not be visible in both modalities. Current approaches have focused on developing modality-specific solutions for individual clinical use cases, by introducing constraints, or identifying cross-modality information manually. Machine learning approaches have the potential to create more general registration platforms. However, training image to image methods would require large multimodal datasets and ground truth for each target application. This paper proposes a model-to-image registration approach instead, because it is common in image-guided interventions to create anatomical models for diagnosis, planning or guidance prior to procedures. An imitation learning-based method, trained on 702 datasets, is used to register preoperative models to intraoperative X-ray images. Accuracy is demonstrated on cardiac models and artificial X-rays generated from CTs. The registration error was [Formula: see text] on 1000 test cases, superior to that of manual ([Formula: see text]) and gradient-based ([Formula: see text]) registration. High robustness is shown in 19 clinical CRT cases. Besides the proposed methods feasibility in a clinical environment, evaluation has shown good accuracy and high robustness indicating that it could be applied in image-guided interventions.

  7. Three-dimensional registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation.

    PubMed

    Prabhu, David; Mehanna, Emile; Gargesha, Madhusudhana; Brandt, Eric; Wen, Di; van Ditzhuijzen, Nienke S; Chamie, Daniel; Yamamoto, Hirosada; Fujino, Yusuke; Alian, Ali; Patel, Jaymin; Costa, Marco; Bezerra, Hiram G; Wilson, David L

    2016-04-01

    Evidence suggests high-resolution, high-contrast, [Formula: see text] intravascular optical coherence tomography (IVOCT) can distinguish plaque types, but further validation is needed, especially for automated plaque characterization. We developed experimental and three-dimensional (3-D) registration methods to provide validation of IVOCT pullback volumes using microscopic, color, and fluorescent cryo-image volumes with optional registered cryo-histology. A specialized registration method matched IVOCT pullback images acquired in the catheter reference frame to a true 3-D cryo-image volume. Briefly, an 11-parameter registration model including a polynomial virtual catheter was initialized within the cryo-image volume, and perpendicular images were extracted, mimicking IVOCT image acquisition. Virtual catheter parameters were optimized to maximize cryo and IVOCT lumen overlap. Multiple assessments suggested that the registration error was better than the [Formula: see text] spacing between IVOCT image frames. Tests on a digital synthetic phantom gave a registration error of only [Formula: see text] (signed distance). Visual assessment of randomly presented nearby frames suggested registration accuracy within 1 IVOCT frame interval ([Formula: see text]). This would eliminate potential misinterpretations confronted by the typical histological approaches to validation, with estimated 1-mm errors. The method can be used to create annotated datasets and automated plaque classification methods and can be extended to other intravascular imaging modalities.

  8. Registration of pencil beam proton radiography data with X-ray CT.

    PubMed

    Deffet, Sylvain; Macq, Benoît; Righetto, Roberto; Vander Stappen, François; Farace, Paolo

    2017-10-01

    Proton radiography seems to be a promising tool for assessing the quality of the stopping power computation in proton therapy. However, range error maps obtained on the basis of proton radiographs are very sensitive to small misalignment between the planning CT and the proton radiography acquisitions. In order to be able to mitigate misalignment in postprocessing, the authors implemented a fast method for registration between pencil proton radiography data obtained with a multilayer ionization chamber (MLIC) and an X-ray CT acquired on a head phantom. The registration was performed by optimizing a cost function which performs a comparison between the acquired data and simulated integral depth-dose curves. Two methodologies were considered, one based on dual orthogonal projections and the other one on a single projection. For each methodology, the robustness of the registration algorithm with respect to three confounding factors (measurement noise, CT calibration errors, and spot spacing) was investigated by testing the accuracy of the method through simulations based on a CT scan of a head phantom. The present registration method showed robust convergence towards the optimal solution. For the level of measurement noise and the uncertainty in the stopping power computation expected in proton radiography using a MLIC, the accuracy appeared to be better than 0.3° for angles and 0.3 mm for translations by use of the appropriate cost function. The spot spacing analysis showed that a spacing larger than the 5 mm used by other authors for the investigation of a MLIC for proton radiography led to results with absolute accuracy better than 0.3° for angles and 1 mm for translations when orthogonal proton radiographs were fed into the algorithm. In the case of a single projection, 6 mm was the largest spot spacing presenting an acceptable registration accuracy. For registration of proton radiography data with X-ray CT, the use of a direct ray-tracing algorithm to compute

  9. Deformable image registration with content mismatch: a demons variant to account for added material and surgical devices in the target image

    NASA Astrophysics Data System (ADS)

    Nithiananthan, S.; Uneri, A.; Schafer, S.; Mirota, D.; Otake, Y.; Stayman, J. W.; Zbijewski, W.; Khanna, A. J.; Reh, D. D.; Gallia, G. L.; Siewerdsen, J. H.

    2013-03-01

    Fast, accurate, deformable image registration is an important aspect of image-guided interventions. Among the factors that can confound registration is the presence of additional material in the intraoperative image - e.g., contrast bolus or a surgical implant - that was not present in the prior image. Existing deformable registration methods generally fail to account for tissue excised between image acquisitions and typically simply "move" voxels within the images with no ability to account for tissue that is removed or introduced between scans. We present a variant of the Demons algorithm to accommodate such content mismatch. The approach combines segmentation of mismatched content with deformable registration featuring an extra pseudo-spatial dimension representing a reservoir from which material can be drawn into the registered image. Previous work tested the registration method in the presence of tissue excision ("missing tissue"). The current paper tests the method in the presence of additional material in the target image and presents a general method by which either missing or additional material can be accommodated. The method was tested in phantom studies, simulations, and cadaver models in the context of intraoperative cone-beam CT with three examples of content mismatch: a variable-diameter bolus (contrast injection); surgical device (rod), and additional material (bone cement). Registration accuracy was assessed in terms of difference images and normalized cross correlation (NCC). We identify the difficulties that traditional registration algorithms encounter when faced with content mismatch and evaluate the ability of the proposed method to overcome these challenges.

  10. Registration of Laser Scanning Point Clouds and Aerial Images Using either Artificial or Natural Tie Features

    NASA Astrophysics Data System (ADS)

    Rönnholm, P.; Haggrén, H.

    2012-07-01

    Integration of laser scanning data and photographs is an excellent combination regarding both redundancy and complementary. Applications of integration vary from sensor and data calibration to advanced classification and scene understanding. In this research, only airborne laser scanning and aerial images are considered. Currently, the initial registration is solved using direct orientation sensors GPS and inertial measurements. However, the accuracy is not usually sufficient for reliable integration of data sets, and thus the initial registration needs to be improved. A registration of data from different sources requires searching and measuring of accurate tie features. Usually, points, lines or planes are preferred as tie features. Therefore, the majority of resent methods rely highly on artificial objects, such as buildings, targets or road paintings. However, in many areas no such objects are available. For example in forestry areas, it would be advantageous to be able to improve registration between laser data and images without making additional ground measurements. Therefore, there is a need to solve registration using only natural features, such as vegetation and ground surfaces. Using vegetation as tie features is challenging, because the shape and even location of vegetation can change because of wind, for example. The aim of this article was to compare registration accuracies derived by using either artificial or natural tie features. The test area included urban objects as well as trees and other vegetation. In this area, two registrations were performed, firstly, using mainly built objects and, secondly, using only vegetation and ground surface. The registrations were solved applying the interactive orientation method. As a result, using artificial tie features leaded to a successful registration in all directions of the coordinate system axes. In the case of using natural tie features, however, the detection of correct heights was difficult causing

  11. Semiautomatic registration of 3D transabdominal ultrasound images for patient repositioning during postprostatectomy radiotherapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Presles, Benoît, E-mail: benoit.presles@creatis.insa-lyon.fr; Rit, Simon; Sarrut, David

    2014-12-15

    Purpose: The aim of the present work is to propose and evaluate registration algorithms of three-dimensional (3D) transabdominal (TA) ultrasound (US) images to setup postprostatectomy patients during radiation therapy. Methods: Three registration methods have been developed and evaluated to register a reference 3D-TA-US image acquired during the planning CT session and a 3D-TA-US image acquired before each treatment session. The first method (method A) uses only gray value information, whereas the second one (method B) uses only gradient information. The third one (method C) combines both sets of information. All methods restrict the comparison to a region of interest computedmore » from the dilated reference positioning volume drawn on the reference image and use mutual information as a similarity measure. The considered geometric transformations are translations and have been optimized by using the adaptive stochastic gradient descent algorithm. Validation has been carried out using manual registration by three operators of the same set of image pairs as the algorithms. Sixty-two treatment US images of seven patients irradiated after a prostatectomy have been registered to their corresponding reference US image. The reference registration has been defined as the average of the manual registration values. Registration error has been calculated by subtracting the reference registration from the algorithm result. For each session, the method has been considered a failure if the registration error was above both the interoperator variability of the session and a global threshold of 3.0 mm. Results: All proposed registration algorithms have no systematic bias. Method B leads to the best results with mean errors of −0.6, 0.7, and −0.2 mm in left–right (LR), superior–inferior (SI), and anterior–posterior (AP) directions, respectively. With this method, the standard deviations of the mean error are of 1.7, 2.4, and 2.6 mm in LR, SI, and AP directions

  12. Estimation of motion fields by non-linear registration for local lung motion analysis in 4D CT image data.

    PubMed

    Werner, René; Ehrhardt, Jan; Schmidt-Richberg, Alexander; Heiss, Anabell; Handels, Heinz

    2010-11-01

    Motivated by radiotherapy of lung cancer non- linear registration is applied to estimate 3D motion fields for local lung motion analysis in thoracic 4D CT images. Reliability of analysis results depends on the registration accuracy. Therefore, our study consists of two parts: optimization and evaluation of a non-linear registration scheme for motion field estimation, followed by a registration-based analysis of lung motion patterns. The study is based on 4D CT data of 17 patients. Different distance measures and force terms for thoracic CT registration are implemented and compared: sum of squared differences versus a force term related to Thirion's demons registration; masked versus unmasked force computation. The most accurate approach is applied to local lung motion analysis. Masked Thirion forces outperform the other force terms. The mean target registration error is 1.3 ± 0.2 mm, which is in the order of voxel size. Based on resulting motion fields and inter-patient normalization of inner lung coordinates and breathing depths a non-linear dependency between inner lung position and corresponding strength of motion is identified. The dependency is observed for all patients without or with only small tumors. Quantitative evaluation of the estimated motion fields indicates high spatial registration accuracy. It allows for reliable registration-based local lung motion analysis. The large amount of information encoded in the motion fields makes it possible to draw detailed conclusions, e.g., to identify the dependency of inner lung localization and motion. Our examinations illustrate the potential of registration-based motion analysis.

  13. Fast and robust multimodal image registration using a local derivative pattern.

    PubMed

    Jiang, Dongsheng; Shi, Yonghong; Chen, Xinrong; Wang, Manning; Song, Zhijian

    2017-02-01

    Deformable multimodal image registration, which can benefit radiotherapy and image guided surgery by providing complementary information, remains a challenging task in the medical image analysis field due to the difficulty of defining a proper similarity measure. This article presents a novel, robust and fast binary descriptor, the discriminative local derivative pattern (dLDP), which is able to encode images of different modalities into similar image representations. dLDP calculates a binary string for each voxel according to the pattern of intensity derivatives in its neighborhood. The descriptor similarity is evaluated using the Hamming distance, which can be efficiently computed, instead of conventional L1 or L2 norms. For the first time, we validated the effectiveness and feasibility of the local derivative pattern for multimodal deformable image registration with several multi-modal registration applications. dLDP was compared with three state-of-the-art methods in artificial image and clinical settings. In the experiments of deformable registration between different magnetic resonance imaging (MRI) modalities from BrainWeb, between computed tomography and MRI images from patient data, and between MRI and ultrasound images from BITE database, we show our method outperforms localized mutual information and entropy images in terms of both accuracy and time efficiency. We have further validated dLDP for the deformable registration of preoperative MRI and three-dimensional intraoperative ultrasound images. Our results indicate that dLDP reduces the average mean target registration error from 4.12 mm to 2.30 mm. This accuracy is statistically equivalent to the accuracy of the state-of-the-art methods in the study; however, in terms of computational complexity, our method significantly outperforms other methods and is even comparable to the sum of the absolute difference. The results reveal that dLDP can achieve superior performance regarding both accuracy and

  14. Investigation of TM Band-to-band Registration Using the JSC Registration Processor

    NASA Technical Reports Server (NTRS)

    Yao, S. S.; Amis, M. L.

    1984-01-01

    The JSC registration processor performs scene-to-scene (or band-to-band) correlation based on edge images. The edge images are derived from a percentage of the edge pixels calculated from the raw scene data, excluding clouds and other extraneous data in the scene. Correlations are performed on patches (blocks) of the edge images, and the correlation peak location in each patch is estimated iteratively to fractional pixel location accuracy. Peak offset locations from all patches over the scene are then considered together, and a variety of tests are made to weed out outliers and other inconsistencies before a distortion model is assumed. Thus, the correlation peak offset locations in each patch indicate quantitatively how well the two TM bands register to each other over that patch of scene data. The average of these offsets indicate the overall accuracies of the band-to-band registration. The registration processor was also used to register one acquisition to another acquisition of multitemporal TM data acquired over the same ground track. Band 4 images from both acquisitions were correlated and an rms error of a fraction of a pixel was routinely obtained.

  15. A hybrid patient-specific biomechanical model based image registration method for the motion estimation of lungs.

    PubMed

    Han, Lianghao; Dong, Hua; McClelland, Jamie R; Han, Liangxiu; Hawkes, David J; Barratt, Dean C

    2017-07-01

    This paper presents a new hybrid biomechanical model-based non-rigid image registration method for lung motion estimation. In the proposed method, a patient-specific biomechanical modelling process captures major physically realistic deformations with explicit physical modelling of sliding motion, whilst a subsequent non-rigid image registration process compensates for small residuals. The proposed algorithm was evaluated with 10 4D CT datasets of lung cancer patients. The target registration error (TRE), defined as the Euclidean distance of landmark pairs, was significantly lower with the proposed method (TRE = 1.37 mm) than with biomechanical modelling (TRE = 3.81 mm) and intensity-based image registration without specific considerations for sliding motion (TRE = 4.57 mm). The proposed method achieved a comparable accuracy as several recently developed intensity-based registration algorithms with sliding handling on the same datasets. A detailed comparison on the distributions of TREs with three non-rigid intensity-based algorithms showed that the proposed method performed especially well on estimating the displacement field of lung surface regions (mean TRE = 1.33 mm, maximum TRE = 5.3 mm). The effects of biomechanical model parameters (such as Poisson's ratio, friction and tissue heterogeneity) on displacement estimation were investigated. The potential of the algorithm in optimising biomechanical models of lungs through analysing the pattern of displacement compensation from the image registration process has also been demonstrated. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Intra-operative Localization of Brachytherapy Implants Using Intensity-based Registration

    PubMed Central

    KarimAghaloo, Z.; Abolmaesumi, P.; Ahmidi, N.; Chen, T.K.; Gobbi, D. G.; Fichtinger, G.

    2010-01-01

    In prostate brachytherapy, a transrectal ultrasound (TRUS) will show the prostate boundary but not all the implanted seeds, while fluoroscopy will show all the seeds clearly but not the boundary. We propose an intensity-based registration between TRUS images and the implant reconstructed from uoroscopy as a means of achieving accurate intra-operative dosimetry. The TRUS images are first filtered and compounded, and then registered to the uoroscopy model via mutual information. A training phantom was implanted with 48 seeds and imaged. Various ultrasound filtering techniques were analyzed, and the best results were achieved with the Bayesian combination of adaptive thresholding, phase congruency, and compensation for the non-uniform ultrasound beam profile in the elevation and lateral directions. The average registration error between corresponding seeds relative to the ground truth was 0.78 mm. The effect of false positives and false negatives in ultrasound were investigated by masking true seeds in the uoroscopy volume or adding false seeds. The registration error remained below 1.01 mm when the false positive rate was 31%, and 0.96 mm when the false negative rate was 31%. This fully automated method delivers excellent registration accuracy and robustness in phantom studies, and promises to demonstrate clinically adequate performance on human data as well. Keywords: Prostate brachytherapy, Ultrasound, Fluoroscopy, Registration. PMID:21152376

  17. Deformable image registration with local rigidity constraints for cone-beam CT-guided spine surgery

    NASA Astrophysics Data System (ADS)

    Reaungamornrat, S.; Wang, A. S.; Uneri, A.; Otake, Y.; Khanna, A. J.; Siewerdsen, J. H.

    2014-07-01

    , respectively). Target registration error (TRE) was similarly improved for FFD+OC+IC (0.7 mm), compared to 1.4 and 1.8 mm for uFFD and Demons. Results were validated in human cadaver studies using CT and CBCT images, with FFD+OC+IC providing excellent preservation of rigid morphology and equivalent or improved TRE. The approach therefore overcomes distortions intrinsic to uFFD and could better facilitate high-precision IGSS.

  18. Altitude registration of limb-scattered radiation

    NASA Astrophysics Data System (ADS)

    Moy, Leslie; Bhartia, Pawan K.; Jaross, Glen; Loughman, Robert; Kramarova, Natalya; Chen, Zhong; Taha, Ghassan; Chen, Grace; Xu, Philippe

    2017-01-01

    One of the largest constraints to the retrieval of accurate ozone profiles from UV backscatter limb sounding sensors is altitude registration. Two methods, the Rayleigh scattering attitude sensing (RSAS) and absolute radiance residual method (ARRM), are able to determine altitude registration to the accuracy necessary for long-term ozone monitoring. The methods compare model calculations of radiances to measured radiances and are independent of onboard tracking devices. RSAS determines absolute altitude errors, but, because the method is susceptible to aerosol interference, it is limited to latitudes and time periods with minimal aerosol contamination. ARRM, a new technique introduced in this paper, can be applied across all seasons and altitudes. However, it is only appropriate for relative altitude error estimates. The application of RSAS to Limb Profiler (LP) measurements from the Ozone Mapping and Profiler Suite (OMPS) on board the Suomi NPP (SNPP) satellite indicates tangent height (TH) errors greater than 1 km with an absolute accuracy of ±200 m. Results using ARRM indicate a ˜ 300 to 400 m intra-orbital TH change varying seasonally ±100 m, likely due to either errors in the spacecraft pointing or in the geopotential height (GPH) data that we use in our analysis. ARRM shows a change of ˜ 200 m over ˜ 5 years with a relative accuracy (a long-term accuracy) of ±100 m outside the polar regions.

  19. In-die mask registration measurement on 28nm-node and beyond

    NASA Astrophysics Data System (ADS)

    Chen, Shen Hung; Cheng, Yung Feng; Chen, Ming Jui

    2013-09-01

    As semiconductor go to smaller node, the critical dimension (CD) of process become more and more small. For lithography, RET (Resolution Enhancement Technology) applications can be used for wafer printing of smaller CD/pitch on 28nm node and beyond. SMO (Source Mask Optimization), DPT (Double Patterning Technology) and SADP (Self-Align Double Patterning) can provide lower k1 value for lithography. In another way, image placement error and overlay control also become more and more important for smaller chip size (advanced node). Mask registration (image placement error) and mask overlay are important factors to affect wafer overlay control/performance especially for DPT or SADP. In traditional method, the designed registration marks (cross type, square type) with larger CD were put into scribe-line of mask frame for registration and overlay measurement. However, these patterns are far way from real patterns. It does not show the registration of real pattern directly and is not a convincing method. In this study, the in-die (in-chip) registration measurement is introduced. We extract the dummy patterns that are close to main pattern from post-OPC (Optical Proximity Correction) gds by our desired rule and choose the patterns that distribute over whole mask uniformly. The convergence test shows 100 points measurement has a reliable result.

  20. Marker-free registration for the accurate integration of CT images and the subject's anatomy during navigation surgery of the maxillary sinus

    PubMed Central

    Kang, S-H; Kim, M-K; Kim, J-H; Park, H-K; Park, W

    2012-01-01

    Objective This study compared three marker-free registration methods that are applicable to a navigation system that can be used for maxillary sinus surgery, and evaluated the associated errors, with the aim of determining which registration method is the most applicable for operations that require accurate navigation. Methods The CT digital imaging and communications in medicine (DICOM) data of ten maxillary models in DICOM files were converted into stereolithography file format. All of the ten maxillofacial models were scanned three dimensionally using a light-based three-dimensional scanner. The methods applied for registration of the maxillofacial models utilized the tooth cusp, bony landmarks and maxillary sinus anterior wall area. The errors during registration were compared between the groups. Results There were differences between the three registration methods in the zygoma, sinus posterior wall, molar alveolar, premolar alveolar, lateral nasal aperture and the infraorbital areas. The error was smallest using the overlay method for the anterior wall of the maxillary sinus, and the difference was statistically significant. Conclusion The navigation error can be minimized by conducting registration using the anterior wall of the maxillary sinus during image-guided surgery of the maxillary sinus. PMID:22499127

  1. Object-constrained meshless deformable algorithm for high speed 3D nonrigid registration between CT and CBCT

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chen Ting; Kim, Sung; Goyal, Sharad

    2010-01-15

    displacement map was generated. Segmented volumes in the CT images deformed using the displacement field were compared against the manual segmentations in the CBCT images to quantitatively measure the convergence of the shape and the volume. Other image features were also used to evaluate the overall performance of the registration. Results: The algorithm was able to complete the segmentation and registration process within 1 min, and the superimposed clinical objects achieved a volumetric similarity measure of over 90% between the reference and the registered data. Validation results also showed that the proposed registration could accurately trace the deformation inside the target volume with average errors of less than 1 mm. The method had a solid performance in registering the simulated images with up to 20 Hounsfield unit white noise added. Also, the side by side comparison with the original demons algorithm demonstrated its improved registration performance over the local pixel-based registration approaches. Conclusions: Given the strength and efficiency of the algorithm, the proposed method has significant clinical potential to accelerate and to improve the CBCT delineation and targets tracking in online IGRT applications.« less

  2. Automatic three-dimensional registration of intravascular optical coherence tomography images

    NASA Astrophysics Data System (ADS)

    Ughi, Giovanni J.; Adriaenssens, Tom; Larsson, Matilda; Dubois, Christophe; Sinnaeve, Peter R.; Coosemans, Mark; Desmet, Walter; D'hooge, Jan

    2012-02-01

    Intravascular optical coherence tomography (IV-OCT) is a catheter-based high-resolution imaging technique able to visualize the inner wall of the coronary arteries and implanted devices in vivo with an axial resolution below 20 μm. IV-OCT is being used in several clinical trials aiming to quantify the vessel response to stent implantation over time. However, stent analysis is currently performed manually and corresponding images taken at different time points are matched through a very labor-intensive and subjective procedure. We present an automated method for the spatial registration of IV-OCT datasets. Stent struts are segmented through consecutive images and three-dimensional models of the stents are created for both datasets to be registered. The two models are initially roughly registered through an automatic initialization procedure and an iterative closest point algorithm is subsequently applied for a more precise registration. To correct for nonuniform rotational distortions (NURDs) and other potential acquisition artifacts, the registration is consecutively refined on a local level. The algorithm was first validated by using an in vitro experimental setup based on a polyvinyl-alcohol gel tubular phantom. Subsequently, an in vivo validation was obtained by exploiting stable vessel landmarks. The mean registration error in vitro was quantified to be 0.14 mm in the longitudinal axis and 7.3-deg mean rotation error. In vivo validation resulted in 0.23 mm in the longitudinal axis and 10.1-deg rotation error. These results indicate that the proposed methodology can be used for automatic registration of in vivo IV-OCT datasets. Such a tool will be indispensable for larger studies on vessel healing pathophysiology and reaction to stent implantation. As such, it will be valuable in testing the performance of new generations of intracoronary devices and new therapeutic drugs.

  3. Analysis of target wavefront error for secondary mirror of a spaceborne telescope

    NASA Astrophysics Data System (ADS)

    Chang, Shenq-Tsong; Lin, Wei-Cheng; Kuo, Ching-Hsiang; Chan, Chia-Yen; Lin, Yu-Chuan; Huang, Ting-Ming

    2014-09-01

    During the fabrication of an aspherical mirror, the inspection of the residual wavefront error is critical. In the program of a spaceborne telescope development, primary mirror is made of ZERODUR with clear aperture of 450 mm. The mass is 10 kg after lightweighting. Deformation of mirror due to gravity is expected; hence uniform supporting measured by load cells has been applied to reduce the gravity effect. Inspection has been taken to determine the residual wavefront error at the configuration of mirror face upwards. Correction polishing has been performed according to the measurement. However, after comparing with the data measured by bench test while the primary mirror is at a configuration of mirror face horizontal, deviations have been found for the two measurements. Optical system that is not able to meet the requirement is predicted according to the measured wavefront error by bench test. A target wavefront error of secondary mirror is therefore analyzed to correct that of primary mirror. Optical performance accordingly is presented.

  4. Performance evaluation of MIND demons deformable registration of MR and CT images in spinal interventions.

    PubMed

    Reaungamornrat, S; De Silva, T; Uneri, A; Goerres, J; Jacobson, M; Ketcha, M; Vogt, S; Kleinszig, G; Khanna, A J; Wolinsky, J-P; Prince, J L; Siewerdsen, J H

    2016-12-07

    Accurate intraoperative localization of target anatomy and adjacent nervous and vascular tissue is essential to safe, effective surgery, and multimodality deformable registration can be used to identify such anatomy by fusing preoperative CT or MR images with intraoperative images. A deformable image registration method has been developed to estimate viscoelastic diffeomorphisms between preoperative MR and intraoperative CT using modality-independent neighborhood descriptors (MIND) and a Huber metric for robust registration. The method, called MIND Demons, optimizes a constrained symmetric energy functional incorporating priors on smoothness, geodesics, and invertibility by alternating between Gauss-Newton optimization and Tikhonov regularization in a multiresolution scheme. Registration performance was evaluated for the MIND Demons method with a symmetric energy formulation in comparison to an asymmetric form, and sensitivity to anisotropic MR voxel-size was analyzed in phantom experiments emulating image-guided spine-surgery in comparison to a free-form deformation (FFD) method using local mutual information (LMI). Performance was validated in a clinical study involving 15 patients undergoing intervention of the cervical, thoracic, and lumbar spine. The target registration error (TRE) for the symmetric MIND Demons formulation (1.3  ±  0.8 mm (median  ±  interquartile)) outperformed the asymmetric form (3.6  ±  4.4 mm). The method demonstrated fairly minor sensitivity to anisotropic MR voxel size, with median TRE ranging 1.3-2.9 mm for MR slice thickness ranging 0.9-9.9 mm, compared to TRE  =  3.2-4.1 mm for LMI FFD over the same range. Evaluation in clinical data demonstrated sub-voxel TRE (<2 mm) in all fifteen cases with realistic deformations that preserved topology with sub-voxel invertibility (0.001 mm) and positive-determinant spatial Jacobians. The approach therefore appears robust against realistic

  5. Performance evaluation of MIND demons deformable registration of MR and CT images in spinal interventions

    NASA Astrophysics Data System (ADS)

    Reaungamornrat, S.; De Silva, T.; Uneri, A.; Goerres, J.; Jacobson, M.; Ketcha, M.; Vogt, S.; Kleinszig, G.; Khanna, A. J.; Wolinsky, J.-P.; Prince, J. L.; Siewerdsen, J. H.

    2016-12-01

    Accurate intraoperative localization of target anatomy and adjacent nervous and vascular tissue is essential to safe, effective surgery, and multimodality deformable registration can be used to identify such anatomy by fusing preoperative CT or MR images with intraoperative images. A deformable image registration method has been developed to estimate viscoelastic diffeomorphisms between preoperative MR and intraoperative CT using modality-independent neighborhood descriptors (MIND) and a Huber metric for robust registration. The method, called MIND Demons, optimizes a constrained symmetric energy functional incorporating priors on smoothness, geodesics, and invertibility by alternating between Gauss-Newton optimization and Tikhonov regularization in a multiresolution scheme. Registration performance was evaluated for the MIND Demons method with a symmetric energy formulation in comparison to an asymmetric form, and sensitivity to anisotropic MR voxel-size was analyzed in phantom experiments emulating image-guided spine-surgery in comparison to a free-form deformation (FFD) method using local mutual information (LMI). Performance was validated in a clinical study involving 15 patients undergoing intervention of the cervical, thoracic, and lumbar spine. The target registration error (TRE) for the symmetric MIND Demons formulation (1.3  ±  0.8 mm (median  ±  interquartile)) outperformed the asymmetric form (3.6  ±  4.4 mm). The method demonstrated fairly minor sensitivity to anisotropic MR voxel size, with median TRE ranging 1.3-2.9 mm for MR slice thickness ranging 0.9-9.9 mm, compared to TRE  =  3.2-4.1 mm for LMI FFD over the same range. Evaluation in clinical data demonstrated sub-voxel TRE (<2 mm) in all fifteen cases with realistic deformations that preserved topology with sub-voxel invertibility (0.001 mm) and positive-determinant spatial Jacobians. The approach therefore appears robust against realistic

  6. Persistent aerial video registration and fast multi-view mosaicing.

    PubMed

    Molina, Edgardo; Zhu, Zhigang

    2014-05-01

    Capturing aerial imagery at high resolutions often leads to very low frame rate video streams, well under full motion video standards, due to bandwidth, storage, and cost constraints. Low frame rates make registration difficult when an aircraft is moving at high speeds or when global positioning system (GPS) contains large errors or it fails. We present a method that takes advantage of persistent cyclic video data collections to perform an online registration with drift correction. We split the persistent aerial imagery collection into individual cycles of the scene, identify and correct the registration errors on the first cycle in a batch operation, and then use the corrected base cycle as a reference pass to register and correct subsequent passes online. A set of multi-view panoramic mosaics is then constructed for each aerial pass for representation, presentation and exploitation of the 3D dynamic scene. These sets of mosaics are all in alignment to the reference cycle allowing their direct use in change detection, tracking, and 3D reconstruction/visualization algorithms. Stereo viewing with adaptive baselines and varying view angles is realized by choosing a pair of mosaics from a set of multi-view mosaics. Further, the mosaics for the second pass and later can be generated and visualized online as their is no further batch error correction.

  7. Registration of multiple video images to preoperative CT for image-guided surgery

    NASA Astrophysics Data System (ADS)

    Clarkson, Matthew J.; Rueckert, Daniel; Hill, Derek L.; Hawkes, David J.

    1999-05-01

    In this paper we propose a method which uses multiple video images to establish the pose of a CT volume with respect to video camera coordinates for use in image guided surgery. The majority of neurosurgical procedures require the neurosurgeon to relate the pre-operative MR/CT data to the intra-operative scene. Registration of 2D video images to the pre-operative 3D image enables a perspective projection of the pre-operative data to be overlaid onto the video image. Our registration method is based on image intensity and uses a simple iterative optimization scheme to maximize the mutual information between a video image and a rendering from the pre-operative data. Video images are obtained from a stereo operating microscope, with a field of view of approximately 110 X 80 mm. We have extended an existing information theoretical framework for 2D-3D registration, so that multiple video images can be registered simultaneously to the pre-operative data. Experiments were performed on video and CT images of a skull phantom. We took three video images, and our algorithm registered these individually to the 3D image. The mean projection error varied between 4.33 and 9.81 millimeters (mm), and the mean 3D error varied between 4.47 and 11.92 mm. Using our novel techniques we then registered five video views simultaneously to the 3D model. This produced an accurate and robust registration with a mean projection error of 0.68 mm and a mean 3D error of 1.05 mm.

  8. SU-C-207B-06: Comparison of Registration Methods for Modeling Pathologic Response of Esophageal Cancer to Chemoradiation Therapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Riyahi, S; Choi, W; Bhooshan, N

    2016-06-15

    Purpose: To compare linear and deformable registration methods for evaluation of tumor response to Chemoradiation therapy (CRT) in patients with esophageal cancer. Methods: Linear and multi-resolution BSpline deformable registration were performed on Pre-Post-CRT CT/PET images of 20 patients with esophageal cancer. For both registration methods, we registered CT using Mean Square Error (MSE) metric, however to register PET we used transformation obtained using Mutual Information (MI) from the same CT due to being multi-modality. Similarity of Warped-CT/PET was quantitatively evaluated using Normalized Mutual Information and plausibility of DF was assessed using inverse consistency Error. To evaluate tumor response four groupsmore » of tumor features were examined: (1) Conventional PET/CT e.g. SUV, diameter (2) Clinical parameters e.g. TNM stage, histology (3)spatial-temporal PET features that describe intensity, texture and geometry of tumor (4)all features combined. Dominant features were identified using 10-fold cross-validation and Support Vector Machine (SVM) was deployed for tumor response prediction while the accuracy was evaluated by ROC Area Under Curve (AUC). Results: Average and standard deviation of Normalized mutual information for deformable registration using MSE was 0.2±0.054 and for linear registration was 0.1±0.026, showing higher NMI for deformable registration. Likewise for MI metric, deformable registration had 0.13±0.035 comparing to linear counterpart with 0.12±0.037. Inverse consistency error for deformable registration for MSE metric was 4.65±2.49 and for linear was 1.32±2.3 showing smaller value for linear registration. The same conclusion was obtained for MI in terms of inverse consistency error. AUC for both linear and deformable registration was 1 showing no absolute difference in terms of response evaluation. Conclusion: Deformable registration showed better NMI comparing to linear registration, however inverse consistency of

  9. Effect of Antenna Pointing Errors on SAR Imaging Considering the Change of the Point Target Location

    NASA Astrophysics Data System (ADS)

    Zhang, Xin; Liu, Shijie; Yu, Haifeng; Tong, Xiaohua; Huang, Guoman

    2018-04-01

    Towards spaceborne spotlight SAR, the antenna is regulated by the SAR system with specific regularity, so the shaking of the internal mechanism is inevitable. Moreover, external environment also has an effect on the stability of SAR platform. Both of them will cause the jitter of the SAR platform attitude. The platform attitude instability will introduce antenna pointing error on both the azimuth and range directions, and influence the acquisition of SAR original data and ultimate imaging quality. In this paper, the relations between the antenna pointing errors and the three-axis attitude errors are deduced, then the relations between spaceborne spotlight SAR imaging of the point target and antenna pointing errors are analysed based on the paired echo theory, meanwhile, the change of the azimuth antenna gain is considered as the spotlight SAR platform moves ahead. The simulation experiments manifest the effects on spotlight SAR imaging caused by antenna pointing errors are related to the target location, that is, the pointing errors of the antenna beam will severely influence the area far away from the scene centre of azimuth direction in the illuminated scene.

  10. A statistical model for analyzing the rotational error of single isocenter for multiple targets technique.

    PubMed

    Chang, Jenghwa

    2017-06-01

    To develop a statistical model that incorporates the treatment uncertainty from the rotational error of the single isocenter for multiple targets technique, and calculates the extra PTV (planning target volume) margin required to compensate for this error. The random vector for modeling the setup (S) error in the three-dimensional (3D) patient coordinate system was assumed to follow a 3D normal distribution with a zero mean, and standard deviations of σ x , σ y , σ z . It was further assumed that the rotation of clinical target volume (CTV) about the isocenter happens randomly and follows a three-dimensional (3D) independent normal distribution with a zero mean and a uniform standard deviation of σ δ . This rotation leads to a rotational random error (R), which also has a 3D independent normal distribution with a zero mean and a uniform standard deviation of σ R equal to the product of σδπ180 and dI⇔T, the distance between the isocenter and CTV. Both (S and R) random vectors were summed, normalized, and transformed to the spherical coordinates to derive the Chi distribution with three degrees of freedom for the radial coordinate of S+R. PTV margin was determined using the critical value of this distribution for a 0.05 significance level so that 95% of the time the treatment target would be covered by the prescription dose. The additional PTV margin required to compensate for the rotational error was calculated as a function of σ R and dI⇔T. The effect of the rotational error is more pronounced for treatments that require high accuracy/precision like stereotactic radiosurgery (SRS) or stereotactic body radiotherapy (SBRT). With a uniform 2-mm PTV margin (or σ x = σ y = σ z = 0.715 mm), a σ R = 0.328 mm will decrease the CTV coverage probability from 95.0% to 90.9%, or an additional 0.2-mm PTV margin is needed to prevent this loss of coverage. If we choose 0.2 mm as the threshold, any σ R > 0.328 mm will lead to an extra PTV margin that cannot be

  11. Geodesic active fields--a geometric framework for image registration.

    PubMed

    Zosso, Dominique; Bresson, Xavier; Thiran, Jean-Philippe

    2011-05-01

    In this paper we present a novel geometric framework called geodesic active fields for general image registration. In image registration, one looks for the underlying deformation field that best maps one image onto another. This is a classic ill-posed inverse problem, which is usually solved by adding a regularization term. Here, we propose a multiplicative coupling between the registration term and the regularization term, which turns out to be equivalent to embed the deformation field in a weighted minimal surface problem. Then, the deformation field is driven by a minimization flow toward a harmonic map corresponding to the solution of the registration problem. This proposed approach for registration shares close similarities with the well-known geodesic active contours model in image segmentation, where the segmentation term (the edge detector function) is coupled with the regularization term (the length functional) via multiplication as well. As a matter of fact, our proposed geometric model is actually the exact mathematical generalization to vector fields of the weighted length problem for curves and surfaces introduced by Caselles-Kimmel-Sapiro. The energy of the deformation field is measured with the Polyakov energy weighted by a suitable image distance, borrowed from standard registration models. We investigate three different weighting functions, the squared error and the approximated absolute error for monomodal images, and the local joint entropy for multimodal images. As compared to specialized state-of-the-art methods tailored for specific applications, our geometric framework involves important contributions. Firstly, our general formulation for registration works on any parametrizable, smooth and differentiable surface, including nonflat and multiscale images. In the latter case, multiscale images are registered at all scales simultaneously, and the relations between space and scale are intrinsically being accounted for. Second, this method is, to

  12. Target Uncertainty Mediates Sensorimotor Error Correction.

    PubMed

    Acerbi, Luigi; Vijayakumar, Sethu; Wolpert, Daniel M

    2017-01-01

    Human movements are prone to errors that arise from inaccuracies in both our perceptual processing and execution of motor commands. We can reduce such errors by both improving our estimates of the state of the world and through online error correction of the ongoing action. Two prominent frameworks that explain how humans solve these problems are Bayesian estimation and stochastic optimal feedback control. Here we examine the interaction between estimation and control by asking if uncertainty in estimates affects how subjects correct for errors that may arise during the movement. Unbeknownst to participants, we randomly shifted the visual feedback of their finger position as they reached to indicate the center of mass of an object. Even though participants were given ample time to compensate for this perturbation, they only fully corrected for the induced error on trials with low uncertainty about center of mass, with correction only partial in trials involving more uncertainty. The analysis of subjects' scores revealed that participants corrected for errors just enough to avoid significant decrease in their overall scores, in agreement with the minimal intervention principle of optimal feedback control. We explain this behavior with a term in the loss function that accounts for the additional effort of adjusting one's response. By suggesting that subjects' decision uncertainty, as reflected in their posterior distribution, is a major factor in determining how their sensorimotor system responds to error, our findings support theoretical models in which the decision making and control processes are fully integrated.

  13. Demons deformable registration for CBCT-guided procedures in the head and neck: convergence and accuracy.

    PubMed

    Nithiananthan, S; Brock, K K; Daly, M J; Chan, H; Irish, J C; Siewerdsen, J H

    2009-10-01

    The accuracy and convergence behavior of a variant of the Demons deformable registration algorithm were investigated for use in cone-beam CT (CBCT)-guided procedures of the head and neck. Online use of deformable registration for guidance of therapeutic procedures such as image-guided surgery or radiation therapy places trade-offs on accuracy and computational expense. This work describes a convergence criterion for Demons registration developed to balance these demands; the accuracy of a multiscale Demons implementation using this convergence criterion is quantified in CBCT images of the head and neck. Using an open-source "symmetric" Demons registration algorithm, a convergence criterion based on the change in the deformation field between iterations was developed to advance among multiple levels of a multiscale image pyramid in a manner that optimized accuracy and computation time. The convergence criterion was optimized in cadaver studies involving CBCT images acquired using a surgical C-arm prototype modified for 3D intraoperative imaging. CBCT-to-CBCT registration was performed and accuracy was quantified in terms of the normalized cross-correlation (NCC) and target registration error (TRE). The accuracy and robustness of the algorithm were then tested in clinical CBCT images of ten patients undergoing radiation therapy of the head and neck. The cadaver model allowed optimization of the convergence factor and initial measurements of registration accuracy: Demons registration exhibited TRE=(0.8+/-0.3) mm and NCC =0.99 in the cadaveric head compared to TRE=(2.6+/-1.0) mm and NCC=0.93 with rigid registration. Similarly for the patient data, Demons registration gave mean TRE=(1.6+/-0.9) mm compared to rigid registration TRE=(3.6+/-1.9) mm, suggesting registration accuracy at or near the voxel size of the patient images (1 x 1 x 2 mm3). The multiscale implementation based on optimal convergence criteria completed registration in 52 s for the cadaveric head and in

  14. Deformable registration of x-ray to MRI for post-implant dosimetry in prostate brachytherapy

    NASA Astrophysics Data System (ADS)

    Park, Seyoun; Song, Danny Y.; Lee, Junghoon

    2016-03-01

    Post-implant dosimetric assessment in prostate brachytherapy is typically performed using CT as the standard imaging modality. However, poor soft tissue contrast in CT causes significant variability in target contouring, resulting in incorrect dose calculations for organs of interest. CT-MR fusion-based approach has been advocated taking advantage of the complementary capabilities of CT (seed identification) and MRI (soft tissue visibility), and has proved to provide more accurate dosimetry calculations. However, seed segmentation in CT requires manual review, and the accuracy is limited by the reconstructed voxel resolution. In addition, CT deposits considerable amount of radiation to the patient. In this paper, we propose an X-ray and MRI based post-implant dosimetry approach. Implanted seeds are localized using three X-ray images by solving a combinatorial optimization problem, and the identified seeds are registered to MR images by an intensity-based points-to-volume registration. We pre-process the MR images using geometric and Gaussian filtering. To accommodate potential soft tissue deformation, our registration is performed in two steps, an initial affine transformation and local deformable registration. An evolutionary optimizer in conjunction with a points-to-volume similarity metric is used for the affine registration. Local prostate deformation and seed migration are then adjusted by the deformable registration step with external and internal force constraints. We tested our algorithm on six patient data sets, achieving registration error of (1.2+/-0.8) mm in < 30 sec. Our proposed approach has the potential to be a fast and cost-effective solution for post-implant dosimetry with equivalent accuracy as the CT-MR fusion-based approach.

  15. Targeting errors in the ICU: use of a national database.

    PubMed

    Kleinpell, Ruth; Thompson, David; Kelso, Lynn; Pronovost, Peter J

    2006-12-01

    The authors believe that as we move from viewing adverse event reporting system as punitive, and as the safety culture improves, reporting will likely increase. Voluntary incident reporting systems can be used to improve patient safety in the ICU by identifying broken or inadequate systems that lead to adverse events [26]. Voluntary external reporting systems such as the ICUSRS can be used to target errors and produce evidence-based best practice measures to improve patient safety in the ICU.

  16. Target Uncertainty Mediates Sensorimotor Error Correction

    PubMed Central

    Vijayakumar, Sethu; Wolpert, Daniel M.

    2017-01-01

    Human movements are prone to errors that arise from inaccuracies in both our perceptual processing and execution of motor commands. We can reduce such errors by both improving our estimates of the state of the world and through online error correction of the ongoing action. Two prominent frameworks that explain how humans solve these problems are Bayesian estimation and stochastic optimal feedback control. Here we examine the interaction between estimation and control by asking if uncertainty in estimates affects how subjects correct for errors that may arise during the movement. Unbeknownst to participants, we randomly shifted the visual feedback of their finger position as they reached to indicate the center of mass of an object. Even though participants were given ample time to compensate for this perturbation, they only fully corrected for the induced error on trials with low uncertainty about center of mass, with correction only partial in trials involving more uncertainty. The analysis of subjects’ scores revealed that participants corrected for errors just enough to avoid significant decrease in their overall scores, in agreement with the minimal intervention principle of optimal feedback control. We explain this behavior with a term in the loss function that accounts for the additional effort of adjusting one’s response. By suggesting that subjects’ decision uncertainty, as reflected in their posterior distribution, is a major factor in determining how their sensorimotor system responds to error, our findings support theoretical models in which the decision making and control processes are fully integrated. PMID:28129323

  17. Semi-automatic registration of 3D orthodontics models from photographs

    NASA Astrophysics Data System (ADS)

    Destrez, Raphaël.; Treuillet, Sylvie; Lucas, Yves; Albouy-Kissi, Benjamin

    2013-03-01

    In orthodontics, a common practice used to diagnose and plan the treatment is the dental cast. After digitization by a CT-scan or a laser scanner, the obtained 3D surface models can feed orthodontics numerical tools for computer-aided diagnosis and treatment planning. One of the pre-processing critical steps is the 3D registration of dental arches to obtain the occlusion of these numerical models. For this task, we propose a vision based method to automatically compute the registration based on photos of patient mouth. From a set of matched singular points between two photos and the dental 3D models, the rigid transformation to apply to the mandible to be in contact with the maxillary may be computed by minimizing the reprojection errors. During a precedent study, we established the feasibility of this visual registration approach with a manual selection of singular points. This paper addresses the issue of automatic point detection. Based on a priori knowledge, histogram thresholding and edge detection are used to extract specific points in 2D images. Concurrently, curvatures information detects 3D corresponding points. To improve the quality of the final registration, we also introduce a combined optimization of the projection matrix with the 2D/3D point positions. These new developments are evaluated on real data by considering the reprojection errors and the deviation angles after registration in respect to the manual reference occlusion realized by a specialist.

  18. Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI

    NASA Astrophysics Data System (ADS)

    Hwuang, Eileen; Rusu, Mirabela; Karthigeyan, Sudha; Agner, Shannon C.; Sparks, Rachel; Shih, Natalie; Tomaszewski, John E.; Rosen, Mark; Feldman, Michael; Madabhushi, Anant

    2014-03-01

    to allow the algorithm to more effectively register multimodal images. SERg is also tested within the free-form deformation framework driven by mutual information. Nine pairs of synthetic T1-weighted to T2-weighted brain MRI were registered under the following conditions: five levels of noise (0%, 1%, 3%, 5%, and 7%) and two levels of bias field (20% and 40%) each with and without noise. We demonstrate that across all of these conditions, SERg yields a mean squared error that is 81.51% lower than that of Demons driven by MRI intensity alone. We also spatially align twenty-six ex vivo histology sections and in vivo prostate MRI in order to map the spatial extent of prostate cancer onto corresponding radiologic imaging. SERg performs better than intensity registration by decreasing the root mean squared distance of annotated landmarks in the prostate gland via both Demons algorithm and mutual information-driven free-form deformation. In both synthetic and clinical experiments, the observed improvement in alignment of the template and target images suggest the utility of parametric eigenvector representations and hence SERg for multimodal image registration.

  19. Local setup errors in image-guided radiotherapy for head and neck cancer patients immobilized with a custom-made device.

    PubMed

    Giske, Kristina; Stoiber, Eva M; Schwarz, Michael; Stoll, Armin; Muenter, Marc W; Timke, Carmen; Roeder, Falk; Debus, Juergen; Huber, Peter E; Thieke, Christian; Bendl, Rolf

    2011-06-01

    To evaluate the local positioning uncertainties during fractionated radiotherapy of head-and-neck cancer patients immobilized using a custom-made fixation device and discuss the effect of possible patient correction strategies for these uncertainties. A total of 45 head-and-neck patients underwent regular control computed tomography scanning using an in-room computed tomography scanner. The local and global positioning variations of all patients were evaluated by applying a rigid registration algorithm. One bounding box around the complete target volume and nine local registration boxes containing relevant anatomic structures were introduced. The resulting uncertainties for a stereotactic setup and the deformations referenced to one anatomic local registration box were determined. Local deformations of the patients immobilized using our custom-made device were compared with previously published results. Several patient positioning correction strategies were simulated, and the residual local uncertainties were calculated. The patient anatomy in the stereotactic setup showed local systematic positioning deviations of 1-4 mm. The deformations referenced to a particular anatomic local registration box were similar to the reported deformations assessed from patients immobilized with commercially available Aquaplast masks. A global correction, including the rotational error compensation, decreased the remaining local translational errors. Depending on the chosen patient positioning strategy, the remaining local uncertainties varied considerably. Local deformations in head-and-neck patients occur even if an elaborate, custom-made patient fixation method is used. A rotational error correction decreased the required margins considerably. None of the considered correction strategies achieved perfect alignment. Therefore, weighting of anatomic subregions to obtain the optimal correction vector should be investigated in the future. Copyright © 2011 Elsevier Inc. All rights

  20. On Statistical Analysis of Neuroimages with Imperfect Registration

    PubMed Central

    Kim, Won Hwa; Ravi, Sathya N.; Johnson, Sterling C.; Okonkwo, Ozioma C.; Singh, Vikas

    2016-01-01

    A variety of studies in neuroscience/neuroimaging seek to perform statistical inference on the acquired brain image scans for diagnosis as well as understanding the pathological manifestation of diseases. To do so, an important first step is to register (or co-register) all of the image data into a common coordinate system. This permits meaningful comparison of the intensities at each voxel across groups (e.g., diseased versus healthy) to evaluate the effects of the disease and/or use machine learning algorithms in a subsequent step. But errors in the underlying registration make this problematic, they either decrease the statistical power or make the follow-up inference tasks less effective/accurate. In this paper, we derive a novel algorithm which offers immunity to local errors in the underlying deformation field obtained from registration procedures. By deriving a deformation invariant representation of the image, the downstream analysis can be made more robust as if one had access to a (hypothetical) far superior registration procedure. Our algorithm is based on recent work on scattering transform. Using this as a starting point, we show how results from harmonic analysis (especially, non-Euclidean wavelets) yields strategies for designing deformation and additive noise invariant representations of large 3-D brain image volumes. We present a set of results on synthetic and real brain images where we achieve robust statistical analysis even in the presence of substantial deformation errors; here, standard analysis procedures significantly under-perform and fail to identify the true signal. PMID:27042168

  1. Multimodal registration of three-dimensional maxillodental cone beam CT and photogrammetry data over time.

    PubMed

    Bolandzadeh, N; Bischof, W; Flores-Mir, C; Boulanger, P

    2013-01-01

    In recent years, one of the foci of orthodontics has been on systems for the evaluation of treatment results and the tracking of tissue variations over time. This can be accomplished through analysing three-dimensional orthodontic images obtained before and after the treatments. Since complementary information is achieved by integrating multiple imaging modalities, cone beam CT (CBCT) and stereophotogrammetry technologies are used in this study to develop a method for tracking bone, teeth and facial soft-tissue variations over time. We propose a two-phase procedure of multimodal (Phase 1) and multitemporal (Phase 2) registration which aligns images taken from the same patient by different imaging modalities and at different times. Extrinsic (for Phase 1) and intrinsic (for Phase 2) landmark-based registration methods are employed as an initiation for a robust iterative closest points algorithm. Since the mandible moves independently of the upper skull, the registration procedure is applied separately on the mandible and the upper skull. The results show that the signed error distributions of both mandible and skull registrations follow a mixture of two Gaussian distributions, corresponding to alignment errors (due to our method) and temporal change over time. We suggest that the large values among the total registration errors correspond to the temporal change resulting from (1) the effect of treatment (i.e. the orthodontic changes of teeth positions); (2) the biological changes such as teeth growth over time, especially for teenagers; and (3) the segmentation procedure and CBCT precision change over time.

  2. A Multistage Approach for Image Registration.

    PubMed

    Bowen, Francis; Hu, Jianghai; Du, Eliza Yingzi

    2016-09-01

    Successful image registration is an important step for object recognition, target detection, remote sensing, multimodal content fusion, scene blending, and disaster assessment and management. The geometric and photometric variations between images adversely affect the ability for an algorithm to estimate the transformation parameters that relate the two images. Local deformations, lighting conditions, object obstructions, and perspective differences all contribute to the challenges faced by traditional registration techniques. In this paper, a novel multistage registration approach is proposed that is resilient to view point differences, image content variations, and lighting conditions. Robust registration is realized through the utilization of a novel region descriptor which couples with the spatial and texture characteristics of invariant feature points. The proposed region descriptor is exploited in a multistage approach. A multistage process allows the utilization of the graph-based descriptor in many scenarios thus allowing the algorithm to be applied to a broader set of images. Each successive stage of the registration technique is evaluated through an effective similarity metric which determines subsequent action. The registration of aerial and street view images from pre- and post-disaster provide strong evidence that the proposed method estimates more accurate global transformation parameters than traditional feature-based methods. Experimental results show the robustness and accuracy of the proposed multistage image registration methodology.

  3. Robust 3D-2D image registration: application to spine interventions and vertebral labeling in the presence of anatomical deformation

    NASA Astrophysics Data System (ADS)

    Otake, Yoshito; Wang, Adam S.; Webster Stayman, J.; Uneri, Ali; Kleinszig, Gerhard; Vogt, Sebastian; Khanna, A. Jay; Gokaslan, Ziya L.; Siewerdsen, Jeffrey H.

    2013-12-01

    We present a framework for robustly estimating registration between a 3D volume image and a 2D projection image and evaluate its precision and robustness in spine interventions for vertebral localization in the presence of anatomical deformation. The framework employs a normalized gradient information similarity metric and multi-start covariance matrix adaptation evolution strategy optimization with local-restarts, which provided improved robustness against deformation and content mismatch. The parallelized implementation allowed orders-of-magnitude acceleration in computation time and improved the robustness of registration via multi-start global optimization. Experiments involved a cadaver specimen and two CT datasets (supine and prone) and 36 C-arm fluoroscopy images acquired with the specimen in four positions (supine, prone, supine with lordosis, prone with kyphosis), three regions (thoracic, abdominal, and lumbar), and three levels of geometric magnification (1.7, 2.0, 2.4). Registration accuracy was evaluated in terms of projection distance error (PDE) between the estimated and true target points in the projection image, including 14 400 random trials (200 trials on the 72 registration scenarios) with initialization error up to ±200 mm and ±10°. The resulting median PDE was better than 0.1 mm in all cases, depending somewhat on the resolution of input CT and fluoroscopy images. The cadaver experiments illustrated the tradeoff between robustness and computation time, yielding a success rate of 99.993% in vertebral labeling (with ‘success’ defined as PDE <5 mm) using 1,718 664 ± 96 582 function evaluations computed in 54.0 ± 3.5 s on a mid-range GPU (nVidia, GeForce GTX690). Parameters yielding a faster search (e.g., fewer multi-starts) reduced robustness under conditions of large deformation and poor initialization (99.535% success for the same data registered in 13.1 s), but given good initialization (e.g., ±5 mm, assuming a robust initial

  4. Development of a patient positioning error compensation tool for Korea Heavy-Ion Medical Accelerator Treatment Center

    NASA Astrophysics Data System (ADS)

    Kim, Min-Joo; Suh, Tae-Suk; Cho, Woong; Jung, Won-Gyun

    2015-07-01

    In this study, a potential validation tool for compensating for the patient positioning error was developed by using 2D/3D and 3D/3D image registration. For 2D/3D registration, digitallyreconstructed radiography (DRR) and three-dimensional computed tomography (3D-CT) images were applied. The ray-casting algorithm is the most straightforward method for generating DRR, so we adopted the traditional ray-casting method, which finds the intersections of a ray with all objects, voxels of the 3D-CT volume in the scene. The similarity between the extracted DRR and the orthogonal image was measured by using a normalized mutual information method. Two orthogonal images were acquired from a Cyber-knife system from the anterior-posterior (AP) and right lateral (RL) views. The 3D-CT and the two orthogonal images of an anthropomorphic phantom and of the head and neck of a cancer patient were used in this study. For 3D/3D registration, planning CT and in-room CT images were applied. After registration, the translation and the rotation factors were calculated to position a couch to be movable in six dimensions. Registration accuracies and average errors of 2.12 mm ± 0.50 mm for transformations and 1.23 ° ± 0.40 ° for rotations were acquired by using 2D/3D registration with the anthropomorphic Alderson-Rando phantom. In addition, registration accuracies and average errors of 0.90 mm ± 0.30 mm for transformations and 1.00 ° ± 0.2 ° for rotations were acquired by using CT image sets. We demonstrated that this validation tool could compensate for patient positioning errors. In addition, this research could be a fundamental step in compensating for patient positioning errors at the Korea Heavy-ion Medical Accelerator Treatment Center.

  5. Using patient-specific phantoms to evaluate deformable image registration algorithms for adaptive radiation therapy

    PubMed Central

    Stanley, Nick; Glide-Hurst, Carri; Kim, Jinkoo; Adams, Jeffrey; Li, Shunshan; Wen, Ning; Chetty, Indrin J.; Zhong, Hualiang

    2014-01-01

    The quality of adaptive treatment planning depends on the accuracy of its underlying deformable image registration (DIR). The purpose of this study is to evaluate the performance of two DIR algorithms, B-spline–based deformable multipass (DMP) and deformable demons (Demons), implemented in a commercial software package. Evaluations were conducted using both computational and physical deformable phantoms. Based on a finite element method (FEM), a total of 11 computational models were developed from a set of CT images acquired from four lung and one prostate cancer patients. FEM generated displacement vector fields (DVF) were used to construct the lung and prostate image phantoms. Based on a fast-Fourier transform technique, image noise power spectrum was incorporated into the prostate image phantoms to create simulated CBCT images. The FEM-DVF served as a gold standard for verification of the two registration algorithms performed on these phantoms. The registration algorithms were also evaluated at the homologous points quantified in the CT images of a physical lung phantom. The results indicated that the mean errors of the DMP algorithm were in the range of 1.0 ~ 3.1 mm for the computational phantoms and 1.9 mm for the physical lung phantom. For the computational prostate phantoms, the corresponding mean error was 1.0–1.9 mm in the prostate, 1.9–2.4 mm in the rectum, and 1.8–2.1 mm over the entire patient body. Sinusoidal errors induced by B-spline interpolations were observed in all the displacement profiles of the DMP registrations. Regions of large displacements were observed to have more registration errors. Patient-specific FEM models have been developed to evaluate the DIR algorithms implemented in the commercial software package. It has been found that the accuracy of these algorithms is patient-dependent and related to various factors including tissue deformation magnitudes and image intensity gradients across the regions of interest. This may

  6. Three-Dimensional Registration for Handheld Profiling Systems Based on Multiple Shot Structured Light

    PubMed Central

    Ayaz, Shirazi Muhammad; Kim, Min Young

    2018-01-01

    In this article, a multi-view registration approach for the 3D handheld profiling system based on the multiple shot structured light technique is proposed. The multi-view registration approach is categorized into coarse registration and point cloud refinement using the iterative closest point (ICP) algorithm. Coarse registration of multiple point clouds was performed using relative orientation and translation parameters estimated via homography-based visual navigation. The proposed system was evaluated using an artificial human skull and a paper box object. For the quantitative evaluation of the accuracy of a single 3D scan, a paper box was reconstructed, and the mean errors in its height and breadth were found to be 9.4 μm and 23 μm, respectively. A comprehensive quantitative evaluation and comparison of proposed algorithm was performed with other variants of ICP. The root mean square error for the ICP algorithm to register a pair of point clouds of the skull object was also found to be less than 1 mm. PMID:29642552

  7. Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis

    PubMed Central

    Wang, Shijun; Yao, Jianhua; Liu, Jiamin; Petrick, Nicholas; Van Uitert, Robert L.; Periaswamy, Senthil; Summers, Ronald M.

    2009-01-01

    Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice—Once supine and once prone—to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined by the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27±52.97 to 14.98 mm±11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline. PMID:20095272

  8. Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wang Shijun; Yao Jianhua; Liu Jiamin

    Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice--Once supine and once prone--to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined bymore » the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27{+-}52.97 to 14.98 mm{+-}11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline.« less

  9. Intraoperative Image-based Multiview 2D/3D Registration for Image-Guided Orthopaedic Surgery: Incorporation of Fiducial-Based C-Arm Tracking and GPU-Acceleration

    PubMed Central

    Armand, Mehran; Armiger, Robert S.; Kutzer, Michael D.; Basafa, Ehsan; Kazanzides, Peter; Taylor, Russell H.

    2012-01-01

    Intraoperative patient registration may significantly affect the outcome of image-guided surgery (IGS). Image-based registration approaches have several advantages over the currently dominant point-based direct contact methods and are used in some industry solutions in image-guided radiation therapy with fixed X-ray gantries. However, technical challenges including geometric calibration and computational cost have precluded their use with mobile C-arms for IGS. We propose a 2D/3D registration framework for intraoperative patient registration using a conventional mobile X-ray imager combining fiducial-based C-arm tracking and graphics processing unit (GPU)-acceleration. The two-stage framework 1) acquires X-ray images and estimates relative pose between the images using a custom-made in-image fiducial, and 2) estimates the patient pose using intensity-based 2D/3D registration. Experimental validations using a publicly available gold standard dataset, a plastic bone phantom and cadaveric specimens have been conducted. The mean target registration error (mTRE) was 0.34 ± 0.04 mm (success rate: 100%, registration time: 14.2 s) for the phantom with two images 90° apart, and 0.99 ± 0.41 mm (81%, 16.3 s) for the cadaveric specimen with images 58.5° apart. The experimental results showed the feasibility of the proposed registration framework as a practical alternative for IGS routines. PMID:22113773

  10. Evaluation of an Automatic Registration-Based Algorithm for Direct Measurement of Volume Change in Tumors

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sarkar, Saradwata; Johnson, Timothy D.; Ma, Bing

    2012-07-01

    Purpose: Assuming that early tumor volume change is a biomarker for response to therapy, accurate quantification of early volume changes could aid in adapting an individual patient's therapy and lead to shorter clinical trials. We investigated an image registration-based approach for tumor volume change quantification that may more reliably detect smaller changes that occur in shorter intervals than can be detected by existing algorithms. Methods and Materials: Variance and bias of the registration-based approach were evaluated using retrospective, in vivo, very-short-interval diffusion magnetic resonance imaging scans where true zero tumor volume change is unequivocally known and synthetic data, respectively. Themore » interval scans were nonlinearly registered using two similarity measures: mutual information (MI) and normalized cross-correlation (NCC). Results: The 95% confidence interval of the percentage volume change error was (-8.93% to 10.49%) for MI-based and (-7.69%, 8.83%) for NCC-based registrations. Linear mixed-effects models demonstrated that error in measuring volume change increased with increase in tumor volume and decreased with the increase in the tumor's normalized mutual information, even when NCC was the similarity measure being optimized during registration. The 95% confidence interval of the relative volume change error for the synthetic examinations with known changes over {+-}80% of reference tumor volume was (-3.02% to 3.86%). Statistically significant bias was not demonstrated. Conclusion: A low-noise, low-bias tumor volume change measurement algorithm using nonlinear registration is described. Errors in change measurement were a function of tumor volume and the normalized mutual information content of the tumor.« less

  11. Techniques in Altitude Registration for Limb Scatter Instruments

    NASA Astrophysics Data System (ADS)

    Moy, L.; Jaross, G.; Bhartia, P. K.; Kramarova, N. A.

    2017-12-01

    One of the largest constraints to the retrieval of accurate ozone profiles from limb sounding sensors is altitude registration. As described in Moy et al. (2017) two methods applicable to UV limb scattering, the Rayleigh Scattering Attitude Sensing (RSAS) and Absolute Radiance Residual Method (ARRM), have been used to determine altitude registration to the accuracy necessary for long-term ozone monitoring. The methods compare model calculations of radiances to measured radiances and are independent of onboard tracking devices. RSAS determines absolute altitude errors but, because the method is susceptible to aerosol interference, it is limited to latitudes and time periods with minimal aerosol contamination. ARRM, a new technique using wavelengths near 300 nm, can be applied across all seasons and altitudes, but its sensitivity to accurate instrument calibration means it may be inappropriate for anything but monitoring change. These characteristics make the two techniques complementary. Both methods have been applied to Limb Profiler instrument measurements from the Ozone Mapping and Profiler Suite (OMPS) onboard the Suomi NPP (SNPP) satellite. The results from RSAS and ARRM differ by as much as 500 m over orbital and seasonal time scales, but long-term pointing trends derived from the two indicate changes within 100 m over the 5 year data record. In this paper we further discuss what these methods are revealing about the stability of LP's altitude registration. An independent evaluation of pointing errors using VIIRS, another sensor onboard the Suomi NPP satellite, indicates changes of as much as 80 m over the course of the mission. The correlations between VIIRS and the ARRM time series suggest a high degree of precision in this limb technique. We have therefore relied upon ARRM to evaluate error sources in more widespread altitude registration techniques such as RSAS and lunar observations. These techniques can be more readily applied to other limb scatter

  12. Pairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game

    NASA Astrophysics Data System (ADS)

    Zai, Dawei; Li, Jonathan; Guo, Yulan; Cheng, Ming; Huang, Pengdi; Cao, Xiaofei; Wang, Cheng

    2017-12-01

    It is challenging to automatically register TLS point clouds with noise, outliers and varying overlap. In this paper, we propose a new method for pairwise registration of TLS point clouds. We first generate covariance matrix descriptors with an adaptive neighborhood size from point clouds to find candidate correspondences, we then construct a non-cooperative game to isolate mutual compatible correspondences, which are considered as true positives. The method was tested on three models acquired by two different TLS systems. Experimental results demonstrate that our proposed adaptive covariance (ACOV) descriptor is invariant to rigid transformation and robust to noise and varying resolutions. The average registration errors achieved on three models are 0.46 cm, 0.32 cm and 1.73 cm, respectively. The computational times cost on these models are about 288 s, 184 s and 903 s, respectively. Besides, our registration framework using ACOV descriptors and a game theoretic method is superior to the state-of-the-art methods in terms of both registration error and computational time. The experiment on a large outdoor scene further demonstrates the feasibility and effectiveness of our proposed pairwise registration framework.

  13. Edge-based correlation image registration for multispectral imaging

    DOEpatents

    Nandy, Prabal [Albuquerque, NM

    2009-11-17

    Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

  14. Visuomotor adaptation needs a validation of prediction error by feedback error

    PubMed Central

    Gaveau, Valérie; Prablanc, Claude; Laurent, Damien; Rossetti, Yves; Priot, Anne-Emmanuelle

    2014-01-01

    The processes underlying short-term plasticity induced by visuomotor adaptation to a shifted visual field are still debated. Two main sources of error can induce motor adaptation: reaching feedback errors, which correspond to visually perceived discrepancies between hand and target positions, and errors between predicted and actual visual reafferences of the moving hand. These two sources of error are closely intertwined and difficult to disentangle, as both the target and the reaching limb are simultaneously visible. Accordingly, the goal of the present study was to clarify the relative contributions of these two types of errors during a pointing task under prism-displaced vision. In “terminal feedback error” condition, viewing of their hand by subjects was allowed only at movement end, simultaneously with viewing of the target. In “movement prediction error” condition, viewing of the hand was limited to movement duration, in the absence of any visual target, and error signals arose solely from comparisons between predicted and actual reafferences of the hand. In order to prevent intentional corrections of errors, a subthreshold, progressive stepwise increase in prism deviation was used, so that subjects remained unaware of the visual deviation applied in both conditions. An adaptive aftereffect was observed in the “terminal feedback error” condition only. As far as subjects remained unaware of the optical deviation and self-assigned pointing errors, prediction error alone was insufficient to induce adaptation. These results indicate a critical role of hand-to-target feedback error signals in visuomotor adaptation; consistent with recent neurophysiological findings, they suggest that a combination of feedback and prediction error signals is necessary for eliciting aftereffects. They also suggest that feedback error updates the prediction of reafferences when a visual perturbation is introduced gradually and cognitive factors are eliminated or strongly

  15. Patient identification errors: the detective in the laboratory.

    PubMed

    Salinas, Maria; López-Garrigós, Maite; Lillo, Rosa; Gutiérrez, Mercedes; Lugo, Javier; Leiva-Salinas, Carlos

    2013-11-01

    The eradication of errors regarding patients' identification is one of the main goals for safety improvement. As clinical laboratory intervenes in 70% of clinical decisions, laboratory safety is crucial in patient safety. We studied the number of Laboratory Information System (LIS) demographic data errors registered in our laboratory during one year. The laboratory attends a variety of inpatients and outpatients. The demographic data of outpatients is registered in the LIS, when they present to the laboratory front desk. The requests from the primary care centers (PCC) are made electronically by the general practitioner. A manual step is always done at the PCC to conciliate the patient identification number in the electronic request with the one in the LIS. Manual registration is done through hospital information system demographic data capture when patient's medical record number is registered in LIS. Laboratory report is always sent out electronically to the patient's electronic medical record. Daily, every demographic data in LIS is manually compared to the request form to detect potential errors. Fewer errors were committed when electronic order was used. There was great error variability between PCC when using the electronic order. LIS demographic data manual registration errors depended on patient origin and test requesting method. Even when using the electronic approach, errors were detected. There was a great variability between PCC even when using this electronic modality; this suggests that the number of errors is still dependent on the personnel in charge of the technology. © 2013.

  16. Demons deformable registration for CBCT-guided procedures in the head and neck: Convergence and accuracy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Nithiananthan, S.; Brock, K. K.; Daly, M. J.

    2009-10-15

    Purpose: The accuracy and convergence behavior of a variant of the Demons deformable registration algorithm were investigated for use in cone-beam CT (CBCT)-guided procedures of the head and neck. Online use of deformable registration for guidance of therapeutic procedures such as image-guided surgery or radiation therapy places trade-offs on accuracy and computational expense. This work describes a convergence criterion for Demons registration developed to balance these demands; the accuracy of a multiscale Demons implementation using this convergence criterion is quantified in CBCT images of the head and neck. Methods: Using an open-source ''symmetric'' Demons registration algorithm, a convergence criterion basedmore » on the change in the deformation field between iterations was developed to advance among multiple levels of a multiscale image pyramid in a manner that optimized accuracy and computation time. The convergence criterion was optimized in cadaver studies involving CBCT images acquired using a surgical C-arm prototype modified for 3D intraoperative imaging. CBCT-to-CBCT registration was performed and accuracy was quantified in terms of the normalized cross-correlation (NCC) and target registration error (TRE). The accuracy and robustness of the algorithm were then tested in clinical CBCT images of ten patients undergoing radiation therapy of the head and neck. Results: The cadaver model allowed optimization of the convergence factor and initial measurements of registration accuracy: Demons registration exhibited TRE=(0.8{+-}0.3) mm and NCC=0.99 in the cadaveric head compared to TRE=(2.6{+-}1.0) mm and NCC=0.93 with rigid registration. Similarly for the patient data, Demons registration gave mean TRE=(1.6{+-}0.9) mm compared to rigid registration TRE=(3.6{+-}1.9) mm, suggesting registration accuracy at or near the voxel size of the patient images (1x1x2 mm{sup 3}). The multiscale implementation based on optimal convergence criteria completed

  17. Demons deformable registration for CBCT-guided procedures in the head and neck: Convergence and accuracy

    PubMed Central

    Nithiananthan, S.; Brock, K. K.; Daly, M. J.; Chan, H.; Irish, J. C.; Siewerdsen, J. H.

    2009-01-01

    Purpose: The accuracy and convergence behavior of a variant of the Demons deformable registration algorithm were investigated for use in cone-beam CT (CBCT)-guided procedures of the head and neck. Online use of deformable registration for guidance of therapeutic procedures such as image-guided surgery or radiation therapy places trade-offs on accuracy and computational expense. This work describes a convergence criterion for Demons registration developed to balance these demands; the accuracy of a multiscale Demons implementation using this convergence criterion is quantified in CBCT images of the head and neck. Methods: Using an open-source “symmetric” Demons registration algorithm, a convergence criterion based on the change in the deformation field between iterations was developed to advance among multiple levels of a multiscale image pyramid in a manner that optimized accuracy and computation time. The convergence criterion was optimized in cadaver studies involving CBCT images acquired using a surgical C-arm prototype modified for 3D intraoperative imaging. CBCT-to-CBCT registration was performed and accuracy was quantified in terms of the normalized cross-correlation (NCC) and target registration error (TRE). The accuracy and robustness of the algorithm were then tested in clinical CBCT images of ten patients undergoing radiation therapy of the head and neck. Results: The cadaver model allowed optimization of the convergence factor and initial measurements of registration accuracy: Demons registration exhibited TRE=(0.8±0.3) mm and NCC=0.99 in the cadaveric head compared to TRE=(2.6±1.0) mm and NCC=0.93 with rigid registration. Similarly for the patient data, Demons registration gave mean TRE=(1.6±0.9) mm compared to rigid registration TRE=(3.6±1.9) mm, suggesting registration accuracy at or near the voxel size of the patient images (1×1×2 mm3). The multiscale implementation based on optimal convergence criteria completed registration in 52 s for

  18. Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach

    PubMed Central

    Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali; Mirota, Daniel J.; Stayman, J. Webster; Zbijewski, Wojciech; Brock, Kristy K.; Daly, Michael J.; Chan, Harley; Irish, Jonathan C.; Siewerdsen, Jeffrey H.

    2011-01-01

    Purpose: A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values (“intensity”). Methods: A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specific intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and∕or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. Results: The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5±2.8) mm compared to (3.5±3.0) mm

  19. Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach.

    PubMed

    Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali; Mirota, Daniel J; Stayman, J Webster; Zbijewski, Wojciech; Brock, Kristy K; Daly, Michael J; Chan, Harley; Irish, Jonathan C; Siewerdsen, Jeffrey H

    2011-04-01

    A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values ("intensity"). A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specific intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and/or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5 +/- 2.8) mm compared to (3.5 +/- 3.0) mm with rigid registration. A

  20. Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali

    2011-04-15

    Purpose: A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values (''intensity''). Methods: A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specificmore » intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and/or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. Results: The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5{+-}2.8) mm compared to (3

  1. Clustered Mutation Signatures Reveal that Error-Prone DNA Repair Targets Mutations to Active Genes.

    PubMed

    Supek, Fran; Lehner, Ben

    2017-07-27

    Many processes can cause the same nucleotide change in a genome, making the identification of the mechanisms causing mutations a difficult challenge. Here, we show that clustered mutations provide a more precise fingerprint of mutagenic processes. Of nine clustered mutation signatures identified from >1,000 tumor genomes, three relate to variable APOBEC activity and three are associated with tobacco smoking. An additional signature matches the spectrum of translesion DNA polymerase eta (POLH). In lymphoid cells, these mutations target promoters, consistent with AID-initiated somatic hypermutation. In solid tumors, however, they are associated with UV exposure and alcohol consumption and target the H3K36me3 chromatin of active genes in a mismatch repair (MMR)-dependent manner. These regions normally have a low mutation rate because error-free MMR also targets H3K36me3 chromatin. Carcinogens and error-prone repair therefore redistribute mutations to the more important regions of the genome, contributing a substantial mutation load in many tumors, including driver mutations. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Proceedings of the NASA Workshop on Registration and Rectification

    NASA Technical Reports Server (NTRS)

    Bryant, N. A. (Editor)

    1982-01-01

    Issues associated with the registration and rectification of remotely sensed data. Near and long range applications research tasks and some medium range technology augmentation research areas are recommended. Image sharpness, feature extraction, inter-image mapping, error analysis, and verification methods are addressed.

  3. WE-AB-BRA-09: Sensitivity of Plan Re-Optimization to Errors in Deformable Image Registration in Online Adaptive Image-Guided Radiation Therapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    McClain, B; Olsen, J; Green, O

    2015-06-15

    Purpose: Online adaptive therapy (ART) relies on auto-contouring using deformable image registration (DIR). DIR’s inherent uncertainties require user intervention and manual edits while the patient is on the table. We investigated the dosimetric impact of DIR errors on the quality of re-optimized plans, and used the findings to establish regions for focusing manual edits to where DIR errors can Result in clinically relevant dose differences. Methods: Our clinical implementation of online adaptive MR-IGRT involves using DIR to transfer contours from CT to daily MR, followed by a physicians’ edits. The plan is then re-optimized to meet the organs at riskmore » (OARs) constraints. Re-optimized abdomen and pelvis plans generated based on physician edited OARs were selected as the baseline for evaluation. Plans were then re-optimized on auto-deformed contours with manual edits limited to pre-defined uniform rings (0 to 5cm) around the PTV. A 0cm ring indicates that the auto-deformed OARs were used without editing. The magnitude of the variations caused by the non-deterministic optimizer was quantified by repeat re-optimizations on the same geometry to determine the mean and standard deviation (STD). For each re-optimized plan, various volumetric parameters for the PTV, the OARs were extracted along with DVH and isodose evaluation. A plan was deemed acceptable if the variation from the baseline plan was within one STD. Results: Initial results show that for abdomen and pancreas cases, a minimum of 5cm margin around the PTV is required for contour corrections, while for pelvic and liver cases a 2–3 cm margin is sufficient. Conclusion: Focusing manual contour edits to regions of dosimetric relevance can reduce contouring time in the online ART process while maintaining a clinically comparable plan. Future work will further refine the contouring region by evaluating the path along the beams, dose gradients near the target and OAR dose metrics.« less

  4. Image navigation and registration performance assessment tool set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

    NASA Astrophysics Data System (ADS)

    De Luccia, Frank J.; Houchin, Scott; Porter, Brian C.; Graybill, Justin; Haas, Evan; Johnson, Patrick D.; Isaacson, Peter J.; Reth, Alan D.

    2016-05-01

    The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99. 73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

  5. Image Navigation and Registration Performance Assessment Tool Set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

    NASA Technical Reports Server (NTRS)

    De Luccia, Frank J.; Houchin, Scott; Porter, Brian C.; Graybill, Justin; Haas, Evan; Johnson, Patrick D.; Isaacson, Peter J.; Reth, Alan D.

    2016-01-01

    The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24-hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24-hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

  6. Scene-based nonuniformity correction algorithm based on interframe registration.

    PubMed

    Zuo, Chao; Chen, Qian; Gu, Guohua; Sui, Xiubao

    2011-06-01

    In this paper, we present a simple and effective scene-based nonuniformity correction (NUC) method for infrared focal plane arrays based on interframe registration. This method estimates the global translation between two adjacent frames and minimizes the mean square error between the two properly registered images to make any two detectors with the same scene produce the same output value. In this way, the accumulation of the registration error can be avoided and the NUC can be achieved. The advantages of the proposed algorithm lie in its low computational complexity and storage requirements and ability to capture temporal drifts in the nonuniformity parameters. The performance of the proposed technique is thoroughly studied with infrared image sequences with simulated nonuniformity and infrared imagery with real nonuniformity. It shows a significantly fast and reliable fixed-pattern noise reduction and obtains an effective frame-by-frame adaptive estimation of each detector's gain and offset.

  7. Validation of Imaging With Pathology in Laryngeal Cancer: Accuracy of the Registration Methodology

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Caldas-Magalhaes, Joana, E-mail: J.CaldasMagalhaes@umcutrecht.nl; Kasperts, Nicolien; Kooij, Nina

    2012-02-01

    Purpose: To investigate the feasibility and accuracy of an automated method to validate gross tumor volume (GTV) delineations with pathology in laryngeal and hypopharyngeal cancer. Methods and Materials: High-resolution computed tomography (CT{sub HR}), magnetic resonance imaging (MRI), and positron emission tomography (PET) scans were obtained from 10 patients before total laryngectomy. The GTV was delineated separately in each imaging modality. The laryngectomy specimen was sliced transversely in 3-mm-thick slices, and whole-mount hematoxylin-eosin stained (H and E) sections were obtained. A pathologist delineated tumor tissue in the H and E sections (GTV{sub PATH}). An automatic three-dimensional (3D) reconstruction of the specimenmore » was performed, and the CT{sub HR}, MRI, and PET were semiautomatically and rigidly registered to the 3D specimen. The accuracy of the pathology-imaging registration and the specimen deformation and shrinkage were assessed. The tumor delineation inaccuracies were compared with the registration errors. Results: Good agreement was observed between anatomical landmarks in the 3D specimen and in the in vivo images. Limited deformations and shrinkage (3% {+-} 1%) were found inside the cartilage skeleton. The root mean squared error of the registration between the 3D specimen and the CT, MRI, and PET was on average 1.5, 3.0, and 3.3 mm, respectively, in the cartilage skeleton. The GTV{sub PATH} volume was 7.2 mL, on average. The GTVs based on CT, MRI, and PET generated a mean volume of 14.9, 18.3, and 9.8 mL and covered the GTV{sub PATH} by 85%, 88%, and 77%, respectively. The tumor delineation inaccuracies exceeded the registration error in all the imaging modalities. Conclusions: Validation of GTV delineations with pathology is feasible with an average overall accuracy below 3.5 mm inside the laryngeal skeleton. The tumor delineation inaccuracies were larger than the registration error. Therefore, an accurate histological

  8. Technical Note: Error metrics for estimating the accuracy of needle/instrument placement during transperineal magnetic resonance/ultrasound-guided prostate interventions.

    PubMed

    Bonmati, Ester; Hu, Yipeng; Villarini, Barbara; Rodell, Rachael; Martin, Paul; Han, Lianghao; Donaldson, Ian; Ahmed, Hashim U; Moore, Caroline M; Emberton, Mark; Barratt, Dean C

    2018-04-01

    Image-guided systems that fuse magnetic resonance imaging (MRI) with three-dimensional (3D) ultrasound (US) images for performing targeted prostate needle biopsy and minimally invasive treatments for prostate cancer are of increasing clinical interest. To date, a wide range of different accuracy estimation procedures and error metrics have been reported, which makes comparing the performance of different systems difficult. A set of nine measures are presented to assess the accuracy of MRI-US image registration, needle positioning, needle guidance, and overall system error, with the aim of providing a methodology for estimating the accuracy of instrument placement using a MR/US-guided transperineal approach. Using the SmartTarget fusion system, an MRI-US image alignment error was determined to be 2.0 ± 1.0 mm (mean ± SD), and an overall system instrument targeting error of 3.0 ± 1.2 mm. Three needle deployments for each target phantom lesion was found to result in a 100% lesion hit rate and a median predicted cancer core length of 5.2 mm. The application of a comprehensive, unbiased validation assessment for MR/US guided systems can provide useful information on system performance for quality assurance and system comparison. Furthermore, such an analysis can be helpful in identifying relationships between these errors, providing insight into the technical behavior of these systems. © 2018 American Association of Physicists in Medicine.

  9. Image registration with auto-mapped control volumes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Schreibmann, Eduard; Xing Lei

    2006-04-15

    Many image registration algorithms rely on the use of homologous control points on the two input image sets to be registered. In reality, the interactive identification of the control points on both images is tedious, difficult, and often a source of error. We propose a two-step algorithm to automatically identify homologous regions that are used as a priori information during the image registration procedure. First, a number of small control volumes having distinct anatomical features are identified on the model image in a somewhat arbitrary fashion. Instead of attempting to find their correspondences in the reference image through user interaction,more » in the proposed method, each of the control regions is mapped to the corresponding part of the reference image by using an automated image registration algorithm. A normalized cross-correlation (NCC) function or mutual information was used as the auto-mapping metric and a limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS) was employed to optimize the function to find the optimal mapping. For rigid registration, the transformation parameters of the system are obtained by averaging that derived from the individual control volumes. In our deformable calculation, the mapped control volumes are treated as the nodes or control points with known positions on the two images. If the number of control volumes is not enough to cover the whole image to be registered, additional nodes are placed on the model image and then located on the reference image in a manner similar to the conventional BSpline deformable calculation. For deformable registration, the established correspondence by the auto-mapped control volumes provides valuable guidance for the registration calculation and greatly reduces the dimensionality of the problem. The performance of the two-step registrations was applied to three rigid registration cases (two PET-CT registrations and a brain MRI-CT registration) and one deformable

  10. A review of setup error in supine breast radiotherapy using cone-beam computed tomography

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Batumalai, Vikneswary, E-mail: Vikneswary.batumalai@sswahs.nsw.gov.au; Liverpool and Macarthur Cancer Therapy Centres, New South Wales; Ingham Institute of Applied Medical Research, Sydney, New South Wales

    2016-10-01

    Setup error in breast radiotherapy (RT) measured with 3-dimensional cone-beam computed tomography (CBCT) is becoming more common. The purpose of this study is to review the literature relating to the magnitude of setup error in breast RT measured with CBCT. The different methods of image registration between CBCT and planning computed tomography (CT) scan were also explored. A literature search, not limited by date, was conducted using Medline and Google Scholar with the following key words: breast cancer, RT, setup error, and CBCT. This review includes studies that reported on systematic and random errors, and the methods used when registeringmore » CBCT scans with planning CT scan. A total of 11 relevant studies were identified for inclusion in this review. The average magnitude of error is generally less than 5 mm across a number of studies reviewed. The common registration methods used when registering CBCT scans with planning CT scan are based on bony anatomy, soft tissue, and surgical clips. No clear relationships between the setup errors detected and methods of registration were observed from this review. Further studies are needed to assess the benefit of CBCT over electronic portal image, as CBCT remains unproven to be of wide benefit in breast RT.« less

  11. Determination of drill paths for percutaneous cochlear access accounting for target positioning error

    NASA Astrophysics Data System (ADS)

    Noble, Jack H.; Warren, Frank M.; Labadie, Robert F.; Dawant, Benoit; Fitzpatrick, J. Michael

    2007-03-01

    In cochlear implant surgery an electrode array is permanently implanted to stimulate the auditory nerve and allow deaf people to hear. Current surgical techniques require wide excavation of the mastoid region of the temporal bone and one to three hours time to avoid damage to vital structures. Recently a far less invasive approach has been proposed-percutaneous cochlear access, in which a single hole is drilled from skull surface to the cochlea. The drill path is determined by attaching a fiducial system to the patient's skull and then choosing, on a pre-operative CT, an entry point and a target point. The drill is advanced to the target, the electrodes placed through the hole, and a stimulator implanted at the surface of the skull. The major challenge is the determination of a safe and effective drill path, which with high probability avoids specific vital structures-the facial nerve, the ossicles, and the external ear canal-and arrives at the basal turn of the cochlea. These four features lie within a few millimeters of each other, the drill is one millimeter in diameter, and errors in the determination of the target position are on the order of 0.5mm root-mean square. Thus, path selection is both difficult and critical to the success of the surgery. This paper presents a method for finding optimally safe and effective paths while accounting for target positioning error.

  12. Automatic image fusion of real-time ultrasound with computed tomography images: a prospective comparison between two auto-registration methods.

    PubMed

    Cha, Dong Ik; Lee, Min Woo; Kim, Ah Yeong; Kang, Tae Wook; Oh, Young-Taek; Jeong, Ja-Yeon; Chang, Jung-Woo; Ryu, Jiwon; Lee, Kyong Joon; Kim, Jaeil; Bang, Won-Chul; Shin, Dong Kuk; Choi, Sung Jin; Koh, Dalkwon; Seo, Bong Koo; Kim, Kyunga

    2017-11-01

    Background A major drawback of conventional manual image fusion is that the process may be complex, especially for less-experienced operators. Recently, two automatic image fusion techniques called Positioning and Sweeping auto-registration have been developed. Purpose To compare the accuracy and required time for image fusion of real-time ultrasonography (US) and computed tomography (CT) images between Positioning and Sweeping auto-registration. Material and Methods Eighteen consecutive patients referred for planning US for radiofrequency ablation or biopsy for focal hepatic lesions were enrolled. Image fusion using both auto-registration methods was performed for each patient. Registration error, time required for image fusion, and number of point locks used were compared using the Wilcoxon signed rank test. Results Image fusion was successful in all patients. Positioning auto-registration was significantly faster than Sweeping auto-registration for both initial (median, 11 s [range, 3-16 s] vs. 32 s [range, 21-38 s]; P < 0.001] and complete (median, 34.0 s [range, 26-66 s] vs. 47.5 s [range, 32-90]; P = 0.001] image fusion. Registration error of Positioning auto-registration was significantly higher for initial image fusion (median, 38.8 mm [range, 16.0-84.6 mm] vs. 18.2 mm [6.7-73.4 mm]; P = 0.029), but not for complete image fusion (median, 4.75 mm [range, 1.7-9.9 mm] vs. 5.8 mm [range, 2.0-13.0 mm]; P = 0.338]. Number of point locks required to refine the initially fused images was significantly higher with Positioning auto-registration (median, 2 [range, 2-3] vs. 1 [range, 1-2]; P = 0.012]. Conclusion Positioning auto-registration offers faster image fusion between real-time US and pre-procedural CT images than Sweeping auto-registration. The final registration error is similar between the two methods.

  13. Control over structure-specific flexibility improves anatomical accuracy for point-based deformable registration in bladder cancer radiotherapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wognum, S.; Chai, X.; Hulshof, M. C. C. M.

    2013-02-15

    Purpose: Future developments in image guided adaptive radiotherapy (IGART) for bladder cancer require accurate deformable image registration techniques for the precise assessment of tumor and bladder motion and deformation that occur as a result of large bladder volume changes during the course of radiotherapy treatment. The aim was to employ an extended version of a point-based deformable registration algorithm that allows control over tissue-specific flexibility in combination with the authors' unique patient dataset, in order to overcome two major challenges of bladder cancer registration, i.e., the difficulty in accounting for the difference in flexibility between the bladder wall and tumormore » and the lack of visible anatomical landmarks for validation. Methods: The registration algorithm used in the current study is an extension of the symmetric-thin plate splines-robust point matching (S-TPS-RPM) algorithm, a symmetric feature-based registration method. The S-TPS-RPM algorithm has been previously extended to allow control over the degree of flexibility of different structures via a weight parameter. The extended weighted S-TPS-RPM algorithm was tested and validated on CT data (planning- and four to five repeat-CTs) of five urinary bladder cancer patients who received lipiodol injections before radiotherapy. The performance of the weighted S-TPS-RPM method, applied to bladder and tumor structures simultaneously, was compared with a previous version of the S-TPS-RPM algorithm applied to bladder wall structure alone and with a simultaneous nonweighted S-TPS-RPM registration of the bladder and tumor structures. Performance was assessed in terms of anatomical and geometric accuracy. The anatomical accuracy was calculated as the residual distance error (RDE) of the lipiodol markers and the geometric accuracy was determined by the surface distance, surface coverage, and inverse consistency errors. Optimal parameter values for the flexibility and bladder weight

  14. Control over structure-specific flexibility improves anatomical accuracy for point-based deformable registration in bladder cancer radiotherapy.

    PubMed

    Wognum, S; Bondar, L; Zolnay, A G; Chai, X; Hulshof, M C C M; Hoogeman, M S; Bel, A

    2013-02-01

    Future developments in image guided adaptive radiotherapy (IGART) for bladder cancer require accurate deformable image registration techniques for the precise assessment of tumor and bladder motion and deformation that occur as a result of large bladder volume changes during the course of radiotherapy treatment. The aim was to employ an extended version of a point-based deformable registration algorithm that allows control over tissue-specific flexibility in combination with the authors' unique patient dataset, in order to overcome two major challenges of bladder cancer registration, i.e., the difficulty in accounting for the difference in flexibility between the bladder wall and tumor and the lack of visible anatomical landmarks for validation. The registration algorithm used in the current study is an extension of the symmetric-thin plate splines-robust point matching (S-TPS-RPM) algorithm, a symmetric feature-based registration method. The S-TPS-RPM algorithm has been previously extended to allow control over the degree of flexibility of different structures via a weight parameter. The extended weighted S-TPS-RPM algorithm was tested and validated on CT data (planning- and four to five repeat-CTs) of five urinary bladder cancer patients who received lipiodol injections before radiotherapy. The performance of the weighted S-TPS-RPM method, applied to bladder and tumor structures simultaneously, was compared with a previous version of the S-TPS-RPM algorithm applied to bladder wall structure alone and with a simultaneous nonweighted S-TPS-RPM registration of the bladder and tumor structures. Performance was assessed in terms of anatomical and geometric accuracy. The anatomical accuracy was calculated as the residual distance error (RDE) of the lipiodol markers and the geometric accuracy was determined by the surface distance, surface coverage, and inverse consistency errors. Optimal parameter values for the flexibility and bladder weight parameters were determined

  15. Magnetic resonance imaging-targeted, 3D transrectal ultrasound-guided fusion biopsy for prostate cancer: Quantifying the impact of needle delivery error on diagnosis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Martin, Peter R., E-mail: pmarti46@uwo.ca; Cool, Derek W.; Romagnoli, Cesare

    2014-07-15

    Purpose: Magnetic resonance imaging (MRI)-targeted, 3D transrectal ultrasound (TRUS)-guided “fusion” prostate biopsy intends to reduce the ∼23% false negative rate of clinical two-dimensional TRUS-guided sextant biopsy. Although it has been reported to double the positive yield, MRI-targeted biopsies continue to yield false negatives. Therefore, the authors propose to investigate how biopsy system needle delivery error affects the probability of sampling each tumor, by accounting for uncertainties due to guidance system error, image registration error, and irregular tumor shapes. Methods: T2-weighted, dynamic contrast-enhanced T1-weighted, and diffusion-weighted prostate MRI and 3D TRUS images were obtained from 49 patients. A radiologist and radiologymore » resident contoured 81 suspicious regions, yielding 3D tumor surfaces that were registered to the 3D TRUS images using an iterative closest point prostate surface-based method to yield 3D binary images of the suspicious regions in the TRUS context. The probabilityP of obtaining a sample of tumor tissue in one biopsy core was calculated by integrating a 3D Gaussian distribution over each suspicious region domain. Next, the authors performed an exhaustive search to determine the maximum root mean squared error (RMSE, in mm) of a biopsy system that gives P ≥ 95% for each tumor sample, and then repeated this procedure for equal-volume spheres corresponding to each tumor sample. Finally, the authors investigated the effect of probe-axis-direction error on measured tumor burden by studying the relationship between the error and estimated percentage of core involvement. Results: Given a 3.5 mm RMSE for contemporary fusion biopsy systems,P ≥ 95% for 21 out of 81 tumors. The authors determined that for a biopsy system with 3.5 mm RMSE, one cannot expect to sample tumors of approximately 1 cm{sup 3} or smaller with 95% probability with only one biopsy core. The predicted maximum RMSE giving P ≥ 95% for

  16. Real-time CT-video registration for continuous endoscopic guidance

    NASA Astrophysics Data System (ADS)

    Merritt, Scott A.; Rai, Lav; Higgins, William E.

    2006-03-01

    Previous research has shown that CT-image-based guidance could be useful for the bronchoscopic assessment of lung cancer. This research drew upon the registration of bronchoscopic video images to CT-based endoluminal renderings of the airway tree. The proposed methods either were restricted to discrete single-frame registration, which took several seconds to complete, or required non-real-time buffering and processing of video sequences. We have devised a fast 2D/3D image registration method that performs single-frame CT-Video registration in under 1/15th of a second. This allows the method to be used for real-time registration at full video frame rates without significantly altering the physician's behavior. The method achieves its speed through a gradient-based optimization method that allows most of the computation to be performed off-line. During live registration, the optimization iteratively steps toward the locally optimal viewpoint at which a CT-based endoluminal view is most similar to a current bronchoscopic video frame. After an initial registration to begin the process (generally done in the trachea for bronchoscopy), subsequent registrations are performed in real-time on each incoming video frame. As each new bronchoscopic video frame becomes available, the current optimization is initialized using the previous frame's optimization result, allowing continuous guidance to proceed without manual re-initialization. Tests were performed using both synthetic and pre-recorded bronchoscopic video. The results show that the method is robust to initialization errors, that registration accuracy is high, and that continuous registration can proceed on real-time video at >15 frames per sec. with minimal user-intervention.

  17. 3D craniofacial registration using thin-plate spline transform and cylindrical surface projection

    PubMed Central

    Chen, Yucong; Deng, Qingqiong; Duan, Fuqing

    2017-01-01

    Craniofacial registration is used to establish the point-to-point correspondence in a unified coordinate system among human craniofacial models. It is the foundation of craniofacial reconstruction and other craniofacial statistical analysis research. In this paper, a non-rigid 3D craniofacial registration method using thin-plate spline transform and cylindrical surface projection is proposed. First, the gradient descent optimization is utilized to improve a cylindrical surface fitting (CSF) for the reference craniofacial model. Second, the thin-plate spline transform (TPST) is applied to deform a target craniofacial model to the reference model. Finally, the cylindrical surface projection (CSP) is used to derive the point correspondence between the reference and deformed target models. To accelerate the procedure, the iterative closest point ICP algorithm is used to obtain a rough correspondence, which can provide a possible intersection area of the CSP. Finally, the inverse TPST is used to map the obtained corresponding points from the deformed target craniofacial model to the original model, and it can be realized directly by the correspondence between the original target model and the deformed target model. Three types of registration, namely, reflexive, involutive and transitive registration, are carried out to verify the effectiveness of the proposed craniofacial registration algorithm. Comparison with the methods in the literature shows that the proposed method is more accurate. PMID:28982117

  18. 3D craniofacial registration using thin-plate spline transform and cylindrical surface projection.

    PubMed

    Chen, Yucong; Zhao, Junli; Deng, Qingqiong; Duan, Fuqing

    2017-01-01

    Craniofacial registration is used to establish the point-to-point correspondence in a unified coordinate system among human craniofacial models. It is the foundation of craniofacial reconstruction and other craniofacial statistical analysis research. In this paper, a non-rigid 3D craniofacial registration method using thin-plate spline transform and cylindrical surface projection is proposed. First, the gradient descent optimization is utilized to improve a cylindrical surface fitting (CSF) for the reference craniofacial model. Second, the thin-plate spline transform (TPST) is applied to deform a target craniofacial model to the reference model. Finally, the cylindrical surface projection (CSP) is used to derive the point correspondence between the reference and deformed target models. To accelerate the procedure, the iterative closest point ICP algorithm is used to obtain a rough correspondence, which can provide a possible intersection area of the CSP. Finally, the inverse TPST is used to map the obtained corresponding points from the deformed target craniofacial model to the original model, and it can be realized directly by the correspondence between the original target model and the deformed target model. Three types of registration, namely, reflexive, involutive and transitive registration, are carried out to verify the effectiveness of the proposed craniofacial registration algorithm. Comparison with the methods in the literature shows that the proposed method is more accurate.

  19. Automatic Masking for Robust 3D-2D Image Registration in Image-Guided Spine Surgery.

    PubMed

    Ketcha, M D; De Silva, T; Uneri, A; Kleinszig, G; Vogt, S; Wolinsky, J-P; Siewerdsen, J H

    During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.

  20. Automatic masking for robust 3D-2D image registration in image-guided spine surgery

    NASA Astrophysics Data System (ADS)

    Ketcha, M. D.; De Silva, T.; Uneri, A.; Kleinszig, G.; Vogt, S.; Wolinsky, J.-P.; Siewerdsen, J. H.

    2016-03-01

    During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.

  1. Voxel-based modeling and quantification of the proximal femur using inter-subject registration of quantitative CT images.

    PubMed

    Li, Wenjun; Kezele, Irina; Collins, D Louis; Zijdenbos, Alex; Keyak, Joyce; Kornak, John; Koyama, Alain; Saeed, Isra; Leblanc, Adrian; Harris, Tamara; Lu, Ying; Lang, Thomas

    2007-11-01

    We have developed a general framework which employs quantitative computed tomography (QCT) imaging and inter-subject image registration to model the three-dimensional structure of the hip, with the goal of quantifying changes in the spatial distribution of bone as it is affected by aging, drug treatment or mechanical unloading. We have adapted rigid and non-rigid inter-subject registration techniques to transform groups of hip QCT scans into a common reference space and to construct composite proximal femoral models. We have applied this technique to a longitudinal study of 16 astronauts who on average, incurred high losses of hip bone density during spaceflights of 4-6 months on the International Space Station (ISS). We compared the pre-flight and post-flight composite hip models, and observed the gradients of the bone loss distribution. We performed paired t-tests, on a voxel by voxel basis, corrected for multiple comparisons using false discovery rate (FDR), and observed regions inside the proximal femur that showed the most significant bone loss. To validate our registration algorithm, we selected the 16 pre-flight scans and manually marked 4 landmarks for each scan. After registration, the average distance between the mapped landmarks and the corresponding landmarks in the target scan was 2.56 mm. The average error due to manual landmark identification was 1.70 mm.

  2. Sensitivity of geographic information system outputs to errors in remotely sensed data

    NASA Technical Reports Server (NTRS)

    Ramapriyan, H. K.; Boyd, R. K.; Gunther, F. J.; Lu, Y. C.

    1981-01-01

    The sensitivity of the outputs of a geographic information system (GIS) to errors in inputs derived from remotely sensed data (RSD) is investigated using a suitability model with per-cell decisions and a gridded geographic data base whose cells are larger than the RSD pixels. The process of preparing RSD as input to a GIS is analyzed, and the errors associated with classification and registration are examined. In the case of the model considered, it is found that the errors caused during classification and registration are partially compensated by the aggregation of pixels. The compensation is quantified by means of an analytical model, a Monte Carlo simulation, and experiments with Landsat data. The results show that error reductions of the order of 50% occur because of aggregation when 25 pixels of RSD are used per cell in the geographic data base.

  3. Spacecraft camera image registration

    NASA Technical Reports Server (NTRS)

    Kamel, Ahmed A. (Inventor); Graul, Donald W. (Inventor); Chan, Fred N. T. (Inventor); Gamble, Donald W. (Inventor)

    1987-01-01

    A system for achieving spacecraft camera (1, 2) image registration comprises a portion external to the spacecraft and an image motion compensation system (IMCS) portion onboard the spacecraft. Within the IMCS, a computer (38) calculates an image registration compensation signal (60) which is sent to the scan control loops (84, 88, 94, 98) of the onboard cameras (1, 2). At the location external to the spacecraft, the long-term orbital and attitude perturbations on the spacecraft are modeled. Coefficients (K, A) from this model are periodically sent to the onboard computer (38) by means of a command unit (39). The coefficients (K, A) take into account observations of stars and landmarks made by the spacecraft cameras (1, 2) themselves. The computer (38) takes as inputs the updated coefficients (K, A) plus synchronization information indicating the mirror position (AZ, EL) of each of the spacecraft cameras (1, 2), operating mode, and starting and stopping status of the scan lines generated by these cameras (1, 2), and generates in response thereto the image registration compensation signal (60). The sources of periodic thermal errors on the spacecraft are discussed. The system is checked by calculating measurement residuals, the difference between the landmark and star locations predicted at the external location and the landmark and star locations as measured by the spacecraft cameras (1, 2).

  4. Registration-based interpolation applied to cardiac MRI

    NASA Astrophysics Data System (ADS)

    Ólafsdóttir, Hildur; Pedersen, Henrik; Hansen, Michael S.; Lyksborg, Mark; Hansen, Mads Fogtmann; Darkner, Sune; Larsen, Rasmus

    2010-03-01

    Various approaches have been proposed for segmentation of cardiac MRI. An accurate segmentation of the myocardium and ventricles is essential to determine parameters of interest for the function of the heart, such as the ejection fraction. One problem with MRI is the poor resolution in one dimension. A 3D registration algorithm will typically use a trilinear interpolation of intensities to determine the intensity of a deformed template image. Due to the poor resolution across slices, such linear approximation is highly inaccurate since the assumption of smooth underlying intensities is violated. Registration-based interpolation is based on 2D registrations between adjacent slices and is independent of segmentations. Hence, rather than assuming smoothness in intensity, the assumption is that the anatomy is consistent across slices. The basis for the proposed approach is the set of 2D registrations between each pair of slices, both ways. The intensity of a new slice is then weighted by (i) the deformation functions and (ii) the intensities in the warped images. Unlike the approach by Penney et al. 2004, this approach takes into account deformation both ways, which gives more robustness where correspondence between slices is poor. We demonstrate the approach on a toy example and on a set of cardiac CINE MRI. Qualitative inspection reveals that the proposed approach provides a more convincing transition between slices than images obtained by linear interpolation. A quantitative validation reveals significantly lower reconstruction errors than both linear and registration-based interpolation based on one-way registrations.

  5. Positioning accuracy in a registration-free CT-based navigation system

    NASA Astrophysics Data System (ADS)

    Brandenberger, D.; Birkfellner, W.; Baumann, B.; Messmer, P.; Huegli, R. W.; Regazzoni, P.; Jacob, A. L.

    2007-12-01

    In order to maintain overall navigation accuracy established by a calibration procedure in our CT-based registration-free navigation system, the CT scanner has to repeatedly generate identical volume images of a target at the same coordinates. We tested the positioning accuracy of the prototype of an advanced workplace for image-guided surgery (AWIGS) which features an operating table capable of direct patient transfer into a CT scanner. Volume images (N = 154) of a specialized phantom were analysed for translational shifting after various table translations. Variables included added weight and phantom position on the table. The navigation system's calibration accuracy was determined (bias 2.1 mm, precision ± 0.7 mm, N = 12). In repeated use, a bias of 3.0 mm and a precision of ± 0.9 mm (N = 10) were maintainable. Instances of translational image shifting were related to the table-to-CT scanner docking mechanism. A distance scaling error when altering the table's height was detected. Initial prototype problems visible in our study causing systematic errors were resolved by repeated system calibrations between interventions. We conclude that the accuracy achieved is sufficient for a wide range of clinical applications in surgery and interventional radiology.

  6. Using patient‐specific phantoms to evaluate deformable image registration algorithms for adaptive radiation therapy

    PubMed Central

    Stanley, Nick; Glide‐Hurst, Carri; Kim, Jinkoo; Adams, Jeffrey; Li, Shunshan; Wen, Ning; Chetty, Indrin J

    2013-01-01

    The quality of adaptive treatment planning depends on the accuracy of its underlying deformable image registration (DIR). The purpose of this study is to evaluate the performance of two DIR algorithms, B‐spline‐based deformable multipass (DMP) and deformable demons (Demons), implemented in a commercial software package. Evaluations were conducted using both computational and physical deformable phantoms. Based on a finite element method (FEM), a total of 11 computational models were developed from a set of CT images acquired from four lung and one prostate cancer patients. FEM generated displacement vector fields (DVF) were used to construct the lung and prostate image phantoms. Based on a fast‐Fourier transform technique, image noise power spectrum was incorporated into the prostate image phantoms to create simulated CBCT images. The FEM‐DVF served as a gold standard for verification of the two registration algorithms performed on these phantoms. The registration algorithms were also evaluated at the homologous points quantified in the CT images of a physical lung phantom. The results indicated that the mean errors of the DMP algorithm were in the range of 1.0~3.1mm for the computational phantoms and 1.9 mm for the physical lung phantom. For the computational prostate phantoms, the corresponding mean error was 1.0–1.9 mm in the prostate, 1.9–2.4 mm in the rectum, and 1.8–2.1 mm over the entire patient body. Sinusoidal errors induced by B‐spline interpolations were observed in all the displacement profiles of the DMP registrations. Regions of large displacements were observed to have more registration errors. Patient‐specific FEM models have been developed to evaluate the DIR algorithms implemented in the commercial software package. It has been found that the accuracy of these algorithms is patient‐dependent and related to various factors including tissue deformation magnitudes and image intensity gradients across the regions of interest. This

  7. TU-F-BRF-03: Effect of Radiation Therapy Planning Scan Registration On the Dose in Lung Cancer Patient CT Scans

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Cunliffe, A; Contee, C; White, B

    Purpose: To characterize the effect of deformable registration of serial computed tomography (CT) scans on the radiation dose calculated from a treatment planning scan. Methods: Eighteen patients who received curative doses (≥60Gy, 2Gy/fraction) of photon radiation therapy for lung cancer treatment were retrospectively identified. For each patient, a diagnostic-quality pre-therapy (4–75 days) CT scan and a treatment planning scan with an associated dose map calculated in Pinnacle were collected. To establish baseline correspondence between scan pairs, a researcher manually identified anatomically corresponding landmark point pairs between the two scans. Pre-therapy scans were co-registered with planning scans (and associated dose maps)more » using the Plastimatch demons and Fraunhofer MEVIS deformable registration algorithms. Landmark points in each pretherapy scan were automatically mapped to the planning scan using the displacement vector field output from both registration algorithms. The absolute difference in planned dose (|ΔD|) between manually and automatically mapped landmark points was calculated. Using regression modeling, |ΔD| was modeled as a function of the distance between manually and automatically matched points (registration error, E), the dose standard deviation (SD-dose) in the eight-pixel neighborhood, and the registration algorithm used. Results: 52–92 landmark point pairs (median: 82) were identified in each patient's scans. Average |ΔD| across patients was 3.66Gy (range: 1.2–7.2Gy). |ΔD| was significantly reduced by 0.53Gy using Plastimatch demons compared with Fraunhofer MEVIS. |ΔD| increased significantly as a function of E (0.39Gy/mm) and SD-dose (2.23Gy/Gy). Conclusion: An average error of <4Gy in radiation dose was introduced when points were mapped between CT scan pairs using deformable registration. Dose differences following registration were significantly increased when the Fraunhofer MEVIS registration algorithm was

  8. Non-rigid registration of 3D ultrasound for neurosurgery using automatic feature detection and matching.

    PubMed

    Machado, Inês; Toews, Matthew; Luo, Jie; Unadkat, Prashin; Essayed, Walid; George, Elizabeth; Teodoro, Pedro; Carvalho, Herculano; Martins, Jorge; Golland, Polina; Pieper, Steve; Frisken, Sarah; Golby, Alexandra; Wells, William

    2018-06-04

    The brain undergoes significant structural change over the course of neurosurgery, including highly nonlinear deformation and resection. It can be informative to recover the spatial mapping between structures identified in preoperative surgical planning and the intraoperative state of the brain. We present a novel feature-based method for achieving robust, fully automatic deformable registration of intraoperative neurosurgical ultrasound images. A sparse set of local image feature correspondences is first estimated between ultrasound image pairs, after which rigid, affine and thin-plate spline models are used to estimate dense mappings throughout the image. Correspondences are derived from 3D features, distinctive generic image patterns that are automatically extracted from 3D ultrasound images and characterized in terms of their geometry (i.e., location, scale, and orientation) and a descriptor of local image appearance. Feature correspondences between ultrasound images are achieved based on a nearest-neighbor descriptor matching and probabilistic voting model similar to the Hough transform. Experiments demonstrate our method on intraoperative ultrasound images acquired before and after opening of the dura mater, during resection and after resection in nine clinical cases. A total of 1620 automatically extracted 3D feature correspondences were manually validated by eleven experts and used to guide the registration. Then, using manually labeled corresponding landmarks in the pre- and post-resection ultrasound images, we show that our feature-based registration reduces the mean target registration error from an initial value of 3.3 to 1.5 mm. This result demonstrates that the 3D features promise to offer a robust and accurate solution for 3D ultrasound registration and to correct for brain shift in image-guided neurosurgery.

  9. Quantitative Analysis Tools and Digital Phantoms for Deformable Image Registration Quality Assurance.

    PubMed

    Kim, Haksoo; Park, Samuel B; Monroe, James I; Traughber, Bryan J; Zheng, Yiran; Lo, Simon S; Yao, Min; Mansur, David; Ellis, Rodney; Machtay, Mitchell; Sohn, Jason W

    2015-08-01

    This article proposes quantitative analysis tools and digital phantoms to quantify intrinsic errors of deformable image registration (DIR) systems and establish quality assurance (QA) procedures for clinical use of DIR systems utilizing local and global error analysis methods with clinically realistic digital image phantoms. Landmark-based image registration verifications are suitable only for images with significant feature points. To address this shortfall, we adapted a deformation vector field (DVF) comparison approach with new analysis techniques to quantify the results. Digital image phantoms are derived from data sets of actual patient images (a reference image set, R, a test image set, T). Image sets from the same patient taken at different times are registered with deformable methods producing a reference DVFref. Applying DVFref to the original reference image deforms T into a new image R'. The data set, R', T, and DVFref, is from a realistic truth set and therefore can be used to analyze any DIR system and expose intrinsic errors by comparing DVFref and DVFtest. For quantitative error analysis, calculating and delineating differences between DVFs, 2 methods were used, (1) a local error analysis tool that displays deformation error magnitudes with color mapping on each image slice and (2) a global error analysis tool that calculates a deformation error histogram, which describes a cumulative probability function of errors for each anatomical structure. Three digital image phantoms were generated from three patients with a head and neck, a lung and a liver cancer. The DIR QA was evaluated using the case with head and neck. © The Author(s) 2014.

  10. SU-E-J-115: Correlation of Displacement Vector Fields Calculated by Deformable Image Registration Algorithms with Motion Parameters of CT Images with Well-Defined Targets and Controlled-Motion

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jaskowiak, J; Ahmad, S; Ali, I

    Purpose: To investigate correlation of displacement vector fields (DVF) calculated by deformable image registration algorithms with motion parameters in helical axial and cone-beam CT images with motion artifacts. Methods: A mobile thorax phantom with well-known targets with different sizes that were made from water-equivalent material and inserted in foam to simulate lung lesions. The thorax phantom was imaged with helical, axial and cone-beam CT. The phantom was moved with a cyclic motion with different motion amplitudes and frequencies along the superior-inferior direction. Different deformable image registration algorithms including demons, fast demons, Horn-Shunck and iterative-optical-flow from the DIRART software were usedmore » to deform CT images for the phantom with different motion patterns. The CT images of the mobile phantom were deformed to CT images of the stationary phantom. Results: The values of displacement vectors calculated by deformable image registration algorithm correlated strongly with motion amplitude where large displacement vectors were calculated for CT images with large motion amplitudes. For example, the maximal displacement vectors were nearly equal to the motion amplitudes (5mm, 10mm or 20mm) at interfaces between the mobile targets lung tissue, while the minimal displacement vectors were nearly equal to negative the motion amplitudes. The maximal and minimal displacement vectors matched with edges of the blurred targets along the Z-axis (motion-direction), while DVF’s were small in the other directions. This indicates that the blurred edges by phantom motion were shifted largely to match with the actual target edge. These shifts were nearly equal to the motion amplitude. Conclusions: The DVF from deformable-image registration algorithms correlated well with motion amplitude of well-defined mobile targets. This can be used to extract motion parameters such as amplitude. However, as motion amplitudes increased, image artifacts

  11. TU-F-BRF-02: MR-US Prostate Registration Using Patient-Specific Tissue Elasticity Property Prior for MR-Targeted, TRUS-Guided HDR Brachytherapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Yang, X; Rossi, P; Ogunleye, T

    2014-06-15

    Purpose: High-dose-rate (HDR) brachytherapy has become a popular treatment modality for prostate cancer. Conventional transrectal ultrasound (TRUS)-guided prostate HDR brachytherapy could benefit significantly from MR-targeted, TRUS-guided procedure where the tumor locations, acquired from the multiparametric MRI, are incorporated into the treatment planning. In order to enable this integration, we have developed a MR-TRUS registration with a patient-specific biomechanical elasticity prior. Methods: The proposed method used a biomechanical elasticity prior to guide the prostate volumetric B-spline deformation in the MRI and TRUS registration. The patient-specific biomechanical elasticity prior was generated using ultrasound elastography, where two 3D TRUS prostate images were acquiredmore » under different probe-induced pressures during the HDR procedure, which takes 2-4 minutes. These two 3D TRUS images were used to calculate the local displacement (elasticity map) of two prostate volumes. The B-spline transformation was calculated by minimizing the Euclidean distance between the normalized attribute vectors of the prostate surface landmarks on the MR and TRUS. This technique was evaluated through two studies: a prostate-phantom study and a pilot study with 5 patients undergoing prostate HDR treatment. The accuracy of our approach was assessed through the locations of several landmarks in the post-registration and TRUS images; our registration results were compared with the surface-based method. Results: For the phantom study, the mean landmark displacement of the proposed method was 1.29±0.11 mm. For the 5 patients, the mean landmark displacement of the surface-based method was 3.25±0.51 mm; our method, 1.71±0.25 mm. Therefore, our proposed method of prostate registration outperformed the surfaced-based registration significantly. Conclusion: We have developed a novel MR-TRUS prostate registration approach based on patient-specific biomechanical elasticity

  12. Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

    NASA Astrophysics Data System (ADS)

    Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

    2018-01-01

    To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

  13. Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

    NASA Technical Reports Server (NTRS)

    DeLuccia, Frank J.; Houchin, Scott; Porter, Brian C.; Graybill, Justin; Haas, Evan; Johnson, Patrick D.; Isaacson, Peter J.; Reth, Alan D.

    2016-01-01

    The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

  14. Joint image registration and fusion method with a gradient strength regularization

    NASA Astrophysics Data System (ADS)

    Lidong, Huang; Wei, Zhao; Jun, Wang

    2015-05-01

    Image registration is an essential process for image fusion, and fusion performance can be used to evaluate registration accuracy. We propose a maximum likelihood (ML) approach to joint image registration and fusion instead of treating them as two independent processes in the conventional way. To improve the visual quality of a fused image, a gradient strength (GS) regularization is introduced in the cost function of ML. The GS of the fused image is controllable by setting the target GS value in the regularization term. This is useful because a larger target GS brings a clearer fused image and a smaller target GS makes the fused image smoother and thus restrains noise. Hence, the subjective quality of the fused image can be improved whether the source images are polluted by noise or not. We can obtain the fused image and registration parameters successively by minimizing the cost function using an iterative optimization method. Experimental results show that our method is effective with transformation, rotation, and scale parameters in the range of [-2.0, 2.0] pixel, [-1.1 deg, 1.1 deg], and [0.95, 1.05], respectively, and variances of noise smaller than 300. It also demonstrated that our method yields a more visual pleasing fused image and higher registration accuracy compared with a state-of-the-art algorithm.

  15. TH-CD-206-09: Learning-Based MRI-CT Prostate Registration Using Spare Patch-Deformation Dictionary

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Yang, X; Jani, A; Rossi, P

    Purpose: To enable MRI-guided prostate radiotherapy, MRI-CT deformable registration is required to map the MRI-defined tumor and key organ contours onto the CT images. Due to the intrinsic differences in grey-level intensity characteristics between MRI and CT images, the integration of MRI into CT-based radiotherapy is very challenging. We are developing a learning-based registration approach to address this technical challenge. Methods: We propose to estimate the deformation between MRI and CT images in a patch-wise fashion by using the sparse representation technique. Specifically, we assume that two image patches should follow the same deformation if their patch-wise appearance patterns aremore » similar. We first extract a set of key points in the new CT image. Then, for each key point, we adaptively construct a coupled dictionary from the training MRI-CT images, where each coupled element includes both appearance and deformation of the same image patch. After calculating the sparse coefficients in representing the patch appearance of each key point based on the constructed dictionary, we can predict the deformation for this point by applying the same sparse coefficients to the respective deformations in the dictionary. Results: This registration technique was validated with 10 prostate-cancer patients’ data and its performance was compared with the commonly used free-form-deformation-based registration. Several landmarks in both images were identified to evaluate the accuracy of our approach. Overall, the averaged target registration error of the intensity-based registration and the proposed method was 3.8±0.4 mm and 1.9±0.3 mm, respectively. Conclusion: We have developed a novel prostate MR-CT registration approach based on patch-deformation dictionary, demonstrated its clinical feasibility, and validated its accuracy. This technique will either reduce or compensate for the effect of patient-specific treatment variation measured during the course of

  16. Exploiting Measurement Uncertainty Estimation in Evaluation of GOES-R ABI Image Navigation Accuracy Using Image Registration Techniques

    NASA Technical Reports Server (NTRS)

    Haas, Evan; DeLuccia, Frank

    2016-01-01

    In evaluating GOES-R Advanced Baseline Imager (ABI) image navigation quality, upsampled sub-images of ABI images are translated against downsampled Landsat 8 images of localized, high contrast earth scenes to determine the translations in the East-West and North-South directions that provide maximum correlation. The native Landsat resolution is much finer than that of ABI, and Landsat navigation accuracy is much better than ABI required navigation accuracy and expected performance. Therefore, Landsat images are considered to provide ground truth for comparison with ABI images, and the translations of ABI sub-images that produce maximum correlation with Landsat localized images are interpreted as ABI navigation errors. The measured local navigation errors from registration of numerous sub-images with the Landsat images are averaged to provide a statistically reliable measurement of the overall navigation error of the ABI image. The dispersion of the local navigation errors is also of great interest, since ABI navigation requirements are specified as bounds on the 99.73rd percentile of the magnitudes of per pixel navigation errors. However, the measurement uncertainty inherent in the use of image registration techniques tends to broaden the dispersion in measured local navigation errors, masking the true navigation performance of the ABI system. We have devised a novel and simple method for estimating the magnitude of the measurement uncertainty in registration error for any pair of images of the same earth scene. We use these measurement uncertainty estimates to filter out the higher quality measurements of local navigation error for inclusion in statistics. In so doing, we substantially reduce the dispersion in measured local navigation errors, thereby better approximating the true navigation performance of the ABI system.

  17. A Locally Adaptive Regularization Based on Anisotropic Diffusion for Deformable Image Registration of Sliding Organs

    PubMed Central

    Pace, Danielle F.; Aylward, Stephen R.; Niethammer, Marc

    2014-01-01

    We propose a deformable image registration algorithm that uses anisotropic smoothing for regularization to find correspondences between images of sliding organs. In particular, we apply the method for respiratory motion estimation in longitudinal thoracic and abdominal computed tomography scans. The algorithm uses locally adaptive diffusion tensors to determine the direction and magnitude with which to smooth the components of the displacement field that are normal and tangential to an expected sliding boundary. Validation was performed using synthetic, phantom, and 14 clinical datasets, including the publicly available DIR-Lab dataset. We show that motion discontinuities caused by sliding can be effectively recovered, unlike conventional regularizations that enforce globally smooth motion. In the clinical datasets, target registration error showed improved accuracy for lung landmarks compared to the diffusive regularization. We also present a generalization of our algorithm to other sliding geometries, including sliding tubes (e.g., needles sliding through tissue, or contrast agent flowing through a vessel). Potential clinical applications of this method include longitudinal change detection and radiotherapy for lung or abdominal tumours, especially those near the chest or abdominal wall. PMID:23899632

  18. A locally adaptive regularization based on anisotropic diffusion for deformable image registration of sliding organs.

    PubMed

    Pace, Danielle F; Aylward, Stephen R; Niethammer, Marc

    2013-11-01

    We propose a deformable image registration algorithm that uses anisotropic smoothing for regularization to find correspondences between images of sliding organs. In particular, we apply the method for respiratory motion estimation in longitudinal thoracic and abdominal computed tomography scans. The algorithm uses locally adaptive diffusion tensors to determine the direction and magnitude with which to smooth the components of the displacement field that are normal and tangential to an expected sliding boundary. Validation was performed using synthetic, phantom, and 14 clinical datasets, including the publicly available DIR-Lab dataset. We show that motion discontinuities caused by sliding can be effectively recovered, unlike conventional regularizations that enforce globally smooth motion. In the clinical datasets, target registration error showed improved accuracy for lung landmarks compared to the diffusive regularization. We also present a generalization of our algorithm to other sliding geometries, including sliding tubes (e.g., needles sliding through tissue, or contrast agent flowing through a vessel). Potential clinical applications of this method include longitudinal change detection and radiotherapy for lung or abdominal tumours, especially those near the chest or abdominal wall.

  19. Exclusion of patients with concomitant chronic conditions in ongoing randomised controlled trials targeting 10 common chronic conditions and registered at ClinicalTrials.gov: a systematic review of registration details.

    PubMed

    Buffel du Vaure, Céline; Dechartres, Agnès; Battin, Constance; Ravaud, Philippe; Boutron, Isabelle

    2016-09-27

    To systematically assess registration details of ongoing randomised controlled trials (RCTs) targeting 10 common chronic conditions and registered at ClinicalTrials.gov and to determine the prevalence of (1) trial records excluding patients with concomitant chronic condition(s) and (2) those specifically targeting patients with concomitant chronic conditions. Systematic review of trial registration records. ClinicalTrials.gov register. All ongoing RCTs registered from 1 January 2014 to 31 January 2015 that assessed an intervention targeting adults with coronary heart disease (CHD), hypertension, heart failure, stroke/transient ischaemic attack, atrial fibrillation, type 2 diabetes, chronic obstructive pulmonary disease, painful condition, depression and dementia with a target sample size ≥100. From the trial registration records, 2 researchers independently recorded the trial characteristics and the number of exclusion criteria and determined whether patients with concomitant chronic conditions were excluded or specifically targeted. Among 319 ongoing RCTs, despite the high prevalence of the concomitant chronic conditions, patients with these conditions were excluded in 251 trials (79%). For example, although 91% of patients with CHD had a concomitant chronic condition, 69% of trials targeting such patients excluded patients with concomitant chronic condition(s). When considering the co-occurrence of 2 chronic conditions, 31% of patients with chronic pain also had depression, but 58% of the trials targeting patients with chronic pain excluded patients with depression. Only 37 trials (12%) assessed interventions specifically targeting patients with concomitant chronic conditions; 31 (84%) excluded patients with concomitant chronic condition(s). Despite widespread multimorbidity, more than three-quarters of ongoing trials assessing interventions for patients with chronic conditions excluded patients with concomitant chronic conditions. Published by the BMJ

  20. Phantom study and accuracy evaluation of an image-to-world registration approach used with electro-magnetic tracking system for neurosurgery

    NASA Astrophysics Data System (ADS)

    Li, Senhu; Sarment, David

    2015-12-01

    Minimally invasive neurosurgery needs intraoperative imaging updates and high efficient image guide system to facilitate the procedure. An automatic image guided system utilized with a compact and mobile intraoperative CT imager was introduced in this work. A tracking frame that can be easily attached onto the commercially available skull clamp was designed. With known geometry of fiducial and tracking sensor arranged on this rigid frame that was fabricated through high precision 3D printing, not only was an accurate, fully automatic registration method developed in a simple and less-costly approach, but also it helped in estimating the errors from fiducial localization in image space through image processing, and in patient space through the calibration of tracking frame. Our phantom study shows the fiducial registration error as 0.348+/-0.028mm, comparing the manual registration error as 1.976+/-0.778mm. The system in this study provided a robust and accurate image-to-patient registration without interruption of routine surgical workflow and any user interactions involved through the neurosurgery.

  1. 3D surface-based registration of ultrasound and histology in prostate cancer imaging.

    PubMed

    Schalk, Stefan G; Postema, Arnoud; Saidov, Tamerlan A; Demi, Libertario; Smeenge, Martijn; de la Rosette, Jean J M C H; Wijkstra, Hessel; Mischi, Massimo

    2016-01-01

    Several transrectal ultrasound (TRUS)-based techniques aiming at accurate localization of prostate cancer are emerging to improve diagnostics or to assist with focal therapy. However, precise validation prior to introduction into clinical practice is required. Histopathology after radical prostatectomy provides an excellent ground truth, but needs accurate registration with imaging. In this work, a 3D, surface-based, elastic registration method was developed to fuse TRUS images with histopathologic results. To maximize the applicability in clinical practice, no auxiliary sensors or dedicated hardware were used for the registration. The mean registration errors, measured in vitro and in vivo, were 1.5±0.2 and 2.1±0.5mm, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Realistic simulated MRI and SPECT databases. Application to SPECT/MRI registration evaluation.

    PubMed

    Aubert-Broche, Berengere; Grova, Christophe; Reilhac, Anthonin; Evans, Alan C; Collins, D Louis

    2006-01-01

    This paper describes the construction of simulated SPECT and MRI databases that account for realistic anatomical and functional variability. The data is used as a gold-standard to evaluate four SPECT/MRI similarity-based registration methods. Simulation realism was accounted for using accurate physical models of data generation and acquisition. MRI and SPECT simulations were generated from three subjects to take into account inter-subject anatomical variability. Functional SPECT data were computed from six functional models of brain perfusion. Previous models of normal perfusion and ictal perfusion observed in Mesial Temporal Lobe Epilepsy (MTLE) were considered to generate functional variability. We studied the impact noise and intensity non-uniformity in MRI simulations and SPECT scatter correction may have on registration accuracy. We quantified the amount of registration error caused by anatomical and functional variability. Registration involving ictal data was less accurate than registration involving normal data. MR intensity nonuniformity was the main factor decreasing registration accuracy. The proposed simulated database is promising to evaluate many functional neuroimaging methods, involving MRI and SPECT data.

  3. Markerless laser registration in image-guided oral and maxillofacial surgery.

    PubMed

    Marmulla, Rüdiger; Lüth, Tim; Mühling, Joachim; Hassfeld, Stefan

    2004-07-01

    The use of registration markers in computer-assisted surgery is combined with high logistic costs and efforts. Markerless patient registration using laser scan surface registration techniques is a new challenging method. The present study was performed to evaluate the clinical accuracy in finding defined target points within the surgical site after markerless patient registration in image-guided oral and maxillofacial surgery. Twenty consecutive patients with different cranial diseases were scheduled for computer-assisted surgery. Data set alignment between the surgical site and the computed tomography (CT) data set was performed by markerless laser scan surface registration of the patient's face. Intraoral rigidly attached registration markers were used as target points, which had to be detected by an infrared pointer. The Surgical Segment Navigator SSN++ has been used for all procedures. SSN++ is an investigative product based on the SSN system that had previously been developed by the presenting authors with the support of Carl Zeiss (Oberkochen, Germany). SSN++ is connected to a Polaris infrared camera (Northern Digital, Waterloo, Ontario, Canada) and to a Minolta VI 900 3D digitizer (Tokyo, Japan) for high-resolution laser scanning. Minimal differences in shape between the laser scan surface and the surface generated from the CT data set could be detected. Nevertheless, high-resolution laser scan of the skin surface allows for a precise patient registration (mean deviation 1.1 mm, maximum deviation 1.8 mm). Radiation load, logistic costs, and efforts arising from the planning of computer-assisted surgery of the head can be reduced because native (markerless) CT data sets can be used for laser scan-based surface registration.

  4. Three-dimensional analysis of the surface registration accuracy of electromagnetic navigation systems in live endoscopic sinus surgery.

    PubMed

    Chang, C M; Fang, K M; Huang, T W; Wang, C T; Cheng, P W

    2013-12-01

    Studies on the performance of surface registration with electromagnetic tracking systems are lacking in both live surgery and the laboratory setting. This study presents the efficiency in time of the system preparation as well as the navigational accuracy of surface registration using electromagnetic tracking systems. Forty patients with bilateral chronic paranasal pansinusitis underwent endoscopic sinus surgery after undergoing sinus computed tomography scans. The surgeries were performed under electromagnetic navigation guidance after the surface registration had been carried out on all of the patients. The intraoperative measurements indicate the time taken for equipment set-up, surface registration and surgical procedure, as well as the degree of navigation error along 3 axes. The time taken for equipment set-up, surface registration and the surgical procedure was 179 +- 23 seconds, 39 +- 4.8 seconds and 114 +- 36 minutes, respectively. A comparison of the navigation error along the 3 axes showed that the deviation in the medial-lateral direction was significantly less than that in the anterior-posterior and cranial-caudal directions. The procedures of equipment set-up and surface registration in electromagnetic navigation tracking are efficient, convenient and easy to manipulate. The system accuracy is within the acceptable ranges, especially on the medial-lateral axis.

  5. Evaluation of image registration in PET/CT of the liver and recommendations for optimized imaging.

    PubMed

    Vogel, Wouter V; van Dalen, Jorn A; Wiering, Bas; Huisman, Henkjan; Corstens, Frans H M; Ruers, Theo J M; Oyen, Wim J G

    2007-06-01

    Multimodality PET/CT of the liver can be performed with an integrated (hybrid) PET/CT scanner or with software fusion of dedicated PET and CT. Accurate anatomic correlation and good image quality of both modalities are important prerequisites, regardless of the applied method. Registration accuracy is influenced by breathing motion differences on PET and CT, which may also have impact on (attenuation correction-related) artifacts, especially in the upper abdomen. The impact of these issues was evaluated for both hybrid PET/CT and software fusion, focused on imaging of the liver. Thirty patients underwent hybrid PET/CT, 20 with CT during expiration breath-hold (EB) and 10 with CT during free breathing (FB). Ten additional patients underwent software fusion of dedicated PET and dedicated expiration breath-hold CT (SF). The image registration accuracy was evaluated at the location of liver borders on CT and uncorrected PET images and at the location of liver lesions. Attenuation-correction artifacts were evaluated by comparison of liver borders on uncorrected and attenuation-corrected PET images. CT images were evaluated for the presence of breathing artifacts. In EB, 40% of patients had an absolute registration error of the diaphragm in the craniocaudal direction of >1 cm (range, -16 to 44 mm), and 45% of lesions were mispositioned >1 cm. In 50% of cases, attenuation-correction artifacts caused a deformation of the liver dome on PET of >1 cm. Poor compliance to breath-hold instructions caused CT artifacts in 55% of cases. In FB, 30% had registration errors of >1 cm (range, -4 to 16 mm) and PET artifacts were less extensive, but all CT images had breathing artifacts. As SF allows independent alignment of PET and CT, no registration errors or artifacts of >1 cm of the diaphragm occurred. Hybrid PET/CT of the liver may have significant registration errors and artifacts related to breathing motion. The extent of these issues depends on the selected breathing protocol and

  6. Automated retina identification based on multiscale elastic registration.

    PubMed

    Figueiredo, Isabel N; Moura, Susana; Neves, Júlio S; Pinto, Luís; Kumar, Sunil; Oliveira, Carlos M; Ramos, João D

    2016-12-01

    In this work we propose a novel method for identifying individuals based on retinal fundus image matching. The method is based on the image registration of retina blood vessels, since it is known that the retina vasculature of an individual is a signature, i.e., a distinctive pattern of the individual. The proposed image registration consists of a multiscale affine registration followed by a multiscale elastic registration. The major advantage of this particular two-step image registration procedure is that it is able to account for both rigid and non-rigid deformations either inherent to the retina tissues or as a result of the imaging process itself. Afterwards a decision identification measure, relying on a suitable normalized function, is defined to decide whether or not the pair of images belongs to the same individual. The method is tested on a data set of 21721 real pairs generated from a total of 946 retinal fundus images of 339 different individuals, consisting of patients followed in the context of different retinal diseases and also healthy patients. The evaluation of its performance reveals that it achieves a very low false rejection rate (FRR) at zero FAR (the false acceptance rate), equal to 0.084, as well as a low equal error rate (EER), equal to 0.053. Moreover, the tests performed by using only the multiscale affine registration, and discarding the multiscale elastic registration, clearly show the advantage of the proposed approach. The outcome of this study also indicates that the proposed method is reliable and competitive with other existing retinal identification methods, and forecasts its future appropriateness and applicability in real-life applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. A comparative study between evaluation methods for quality control procedures for determining the accuracy of PET/CT registration

    NASA Astrophysics Data System (ADS)

    Cha, Min Kyoung; Ko, Hyun Soo; Jung, Woo Young; Ryu, Jae Kwang; Choe, Bo-Young

    2015-08-01

    The Accuracy of registration between positron emission tomography (PET) and computed tomography (CT) images is one of the important factors for reliable diagnosis in PET/CT examinations. Although quality control (QC) for checking alignment of PET and CT images should be performed periodically, the procedures have not been fully established. The aim of this study is to determine optimal quality control (QC) procedures that can be performed at the user level to ensure the accuracy of PET/CT registration. Two phantoms were used to carry out this study: the American college of Radiology (ACR)-approved PET phantom and National Electrical Manufacturers Association (NEMA) International Electrotechnical Commission (IEC) body phantom, containing fillable spheres. All PET/CT images were acquired on a Biograph TruePoint 40 PET/CT scanner using routine protocols. To measure registration error, the spatial coordinates of the estimated centers of the target slice (spheres) was calculated independently for the PET and the CT images in two ways. We compared the images from the ACR-approved PET phantom to that from the NEMA IEC body phantom. Also, we measured the total time required from phantom preparation to image analysis. The first analysis method showed a total difference of 0.636 ± 0.11 mm for the largest hot sphere and 0.198 ± 0.09 mm for the largest cold sphere in the case of the ACR-approved PET phantom. In the NEMA IEC body phantom, the total difference was 3.720 ± 0.97 mm for the largest hot sphere and 4.800 ± 0.85 mm for the largest cold sphere. The second analysis method showed that the differences in the x location at the line profile of the lesion on PET and CT were (1.33, 1.33) mm for a bone lesion, (-1.26, -1.33) mm for an air lesion and (-1.67, -1.60) mm for a hot sphere lesion for the ACR-approved PET phantom. For the NEMA IEC body phantom, the differences in the x location at the line profile of the lesion on PET and CT were (-1.33, 4.00) mm for the air

  8. Target/error overlap in jargonaphasia: The case for a one-source model, lexical and non-lexical summation, and the special status of correct responses.

    PubMed

    Olson, Andrew; Halloran, Elizabeth; Romani, Cristina

    2015-12-01

    We present three jargonaphasic patients who made phonological errors in naming, repetition and reading. We analyse target/response overlap using statistical models to answer three questions: 1) Is there a single phonological source for errors or two sources, one for target-related errors and a separate source for abstruse errors? 2) Can correct responses be predicted by the same distribution used to predict errors or do they show a completion boost (CB)? 3) Is non-lexical and lexical information summed during reading and repetition? The answers were clear. 1) Abstruse errors did not require a separate distribution created by failure to access word forms. Abstruse and target-related errors were the endpoints of a single overlap distribution. 2) Correct responses required a special factor, e.g., a CB or lexical/phonological feedback, to preserve their integrity. 3) Reading and repetition required separate lexical and non-lexical contributions that were combined at output. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Feature-based US to CT registration of the aortic root

    NASA Astrophysics Data System (ADS)

    Lang, Pencilla; Chen, Elvis C. S.; Guiraudon, Gerard M.; Jones, Doug L.; Bainbridge, Daniel; Chu, Michael W.; Drangova, Maria; Hata, Noby; Jain, Ameet; Peters, Terry M.

    2011-03-01

    A feature-based registration was developed to align biplane and tracked ultrasound images of the aortic root with a preoperative CT volume. In transcatheter aortic valve replacement, a prosthetic valve is inserted into the aortic annulus via a catheter. Poor anatomical visualization of the aortic root region can result in incorrect positioning, leading to significant morbidity and mortality. Registration of pre-operative CT to transesophageal ultrasound and fluoroscopy images is a major step towards providing augmented image guidance for this procedure. The proposed registration approach uses an iterative closest point algorithm to register a surface mesh generated from CT to 3D US points reconstructed from a single biplane US acquisition, or multiple tracked US images. The use of a single simultaneous acquisition biplane image eliminates reconstruction error introduced by cardiac gating and TEE probe tracking, creating potential for real-time intra-operative registration. A simple initialization procedure is used to minimize changes to operating room workflow. The algorithm is tested on images acquired from excised porcine hearts. Results demonstrate a clinically acceptable accuracy of 2.6mm and 5mm for tracked US to CT and biplane US to CT registration respectively.

  10. [Application of elastic registration based on Demons algorithm in cone beam CT].

    PubMed

    Pang, Haowen; Sun, Xiaoyang

    2014-02-01

    We applied Demons and accelerated Demons elastic registration algorithm in radiotherapy cone beam CT (CBCT) images, We provided software support for real-time understanding of organ changes during radiotherapy. We wrote a 3D CBCT image elastic registration program using Matlab software, and we tested and verified the images of two patients with cervical cancer 3D CBCT images for elastic registration, based on the classic Demons algorithm, minimum mean square error (MSE) decreased 59.7%, correlation coefficient (CC) increased 11.0%. While for the accelerated Demons algorithm, MSE decreased 40.1%, CC increased 7.2%. The experimental verification with two methods of Demons algorithm obtained the desired results, but the small difference appeared to be lack of precision, and the total registration time was a little long. All these problems need to be further improved for accuracy and reducing of time.

  11. SU-E-J-97: Evaluation of Multi-Modality (CT/MR/PET) Image Registration Accuracy in Radiotherapy Planning.

    PubMed

    Sethi, A; Rusu, I; Surucu, M; Halama, J

    2012-06-01

    Evaluate accuracy of multi-modality image registration in radiotherapy planning process. A water-filled anthropomorphic head phantom containing eight 'donut-shaped' fiducial markers (3 internal + 5 external) was selected for this study. Seven image sets (3CTs, 3MRs and PET) of phantom were acquired and fused in a commercial treatment planning system. First, a narrow slice (0.75mm) baseline CT scan was acquired (CT1). Subsequently, the phantom was re-scanned with a coarse slice width = 1.5mm (CT2) and after subjecting phantom to rotation/displacement (CT3). Next, the phantom was scanned in a 1.5 Tesla MR scanner and three MR image sets (axial T1, axial T2, coronal T1) were acquired at 2mm slice width. Finally, the phantom and center of fiducials were doped with 18F and a PET scan was performed with 2mm cubic voxels. All image scans (CT/MR/PET) were fused to the baseline (CT1) data using automated mutual-information based fusion algorithm. Difference between centroids of fiducial markers in various image modalities was used to assess image registration accuracy. CT/CT image registration was superior to CT/MR and CT/PET: average CT/CT fusion error was found to be 0.64 ± 0.14 mm. Corresponding values for CT/MR and CT/PET fusion were 1.33 ± 0.71mm and 1.11 ± 0.37mm. Internal markers near the center of phantom fused better than external markers placed on the phantom surface. This was particularly true for the CT/MR and CT/PET. The inferior quality of external marker fusion indicates possible distortion effects toward the edges of MR image. Peripheral targets in the PET scan may be subject to parallax error caused by depth of interaction of photons in detectors. Current widespread use of multimodality imaging in radiotherapy planning calls for periodic quality assurance of image registration process. Such studies may help improve safety and accuracy in treatment planning. © 2012 American Association of Physicists in Medicine.

  12. Preliminary Studies for a CBCT Imaging Protocol for Offline Organ Motion Analysis: Registration Software Validation and CTDI Measurements

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Falco, Maria Daniela, E-mail: mdanielafalco@hotmail.co; Fontanarosa, Davide; Miceli, Roberto

    2011-04-01

    Cone-beam X-ray volumetric imaging in the treatment room, allows online correction of set-up errors and offline assessment of residual set-up errors and organ motion. In this study the registration algorithm of the X-ray volume imaging software (XVI, Elekta, Crawley, United Kingdom), which manages a commercial cone-beam computed tomography (CBCT)-based positioning system, has been tested using a homemade and an anthropomorphic phantom to: (1) assess its performance in detecting known translational and rotational set-up errors and (2) transfer the transformation matrix of its registrations into a commercial treatment planning system (TPS) for offline organ motion analysis. Furthermore, CBCT dose index hasmore » been measured for a particular site (prostate: 120 kV, 1028.8 mAs, approximately 640 frames) using a standard Perspex cylindrical body phantom (diameter 32 cm, length 15 cm) and a 10-cm-long pencil ionization chamber. We have found that known displacements were correctly calculated by the registration software to within 1.3 mm and 0.4{sup o}. For the anthropomorphic phantom, only translational displacements have been considered. Both studies have shown errors within the intrinsic uncertainty of our system for translational displacements (estimated as 0.87 mm) and rotational displacements (estimated as 0.22{sup o}). The resulting table translations proposed by the system to correct the displacements were also checked with portal images and found to place the isocenter of the plan on the linac isocenter within an error of 1 mm, which is the dimension of the spherical lead marker inserted at the center of the homemade phantom. The registration matrix translated into the TPS image fusion module correctly reproduced the alignment between planning CT scans and CBCT scans. Finally, measurements on the CBCT dose index indicate that CBCT acquisition delivers less dose than conventional CT scans and electronic portal imaging device portals. The registration software

  13. Evaluation of low-dose limits in 3D-2D rigid registration for surgical guidance

    NASA Astrophysics Data System (ADS)

    Uneri, A.; Wang, A. S.; Otake, Y.; Kleinszig, G.; Vogt, S.; Khanna, A. J.; Gallia, G. L.; Gokaslan, Z. L.; Siewerdsen, J. H.

    2014-09-01

    An algorithm for intensity-based 3D-2D registration of CT and C-arm fluoroscopy is evaluated for use in surgical guidance, specifically considering the low-dose limits of the fluoroscopic x-ray projections. The registration method is based on a framework using the covariance matrix adaptation evolution strategy (CMA-ES) to identify the 3D patient pose that maximizes the gradient information similarity metric. Registration performance was evaluated in an anthropomorphic head phantom emulating intracranial neurosurgery, using target registration error (TRE) to characterize accuracy and robustness in terms of 95% confidence upper bound in comparison to that of an infrared surgical tracking system. Three clinical scenarios were considered: (1) single-view image + guidance, wherein a single x-ray projection is used for visualization and 3D-2D guidance; (2) dual-view image + guidance, wherein one projection is acquired for visualization, combined with a second (lower-dose) projection acquired at a different C-arm angle for 3D-2D guidance; and (3) dual-view guidance, wherein both projections are acquired at low dose for the purpose of 3D-2D guidance alone (not visualization). In each case, registration accuracy was evaluated as a function of the entrance surface dose associated with the projection view(s). Results indicate that images acquired at a dose as low as 4 μGy (approximately one-tenth the dose of a typical fluoroscopic frame) were sufficient to provide TRE comparable or superior to that of conventional surgical tracking, allowing 3D-2D guidance at a level of dose that is at most 10% greater than conventional fluoroscopy (scenario #2) and potentially reducing the dose to approximately 20% of the level in a conventional fluoroscopically guided procedure (scenario #3).

  14. TU-AB-202-03: Prediction of PET Transfer Uncertainty by DIR Error Estimating Software, AUTODIRECT

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kim, H; Chen, J; Phillips, J

    2016-06-15

    Purpose: Deformable image registration (DIR) is a powerful tool, but DIR errors can adversely affect its clinical applications. To estimate voxel-specific DIR uncertainty, a software tool, called AUTODIRECT (automated DIR evaluation of confidence tool), has been developed and validated. This work tests the ability of this software to predict uncertainty for the transfer of standard uptake values (SUV) from positron-emission tomography (PET) with DIR. Methods: Virtual phantoms are used for this study. Each phantom has a planning computed tomography (CT) image and a diagnostic PET-CT image set. A deformation was digitally applied to the diagnostic CT to create the planningmore » CT image and establish a known deformation between the images. One lung and three rectum patient datasets were employed to create the virtual phantoms. Both of these sites have difficult deformation scenarios associated with them, which can affect DIR accuracy (lung tissue sliding and changes in rectal filling). The virtual phantoms were created to simulate these scenarios by introducing discontinuities in the deformation field at the lung rectum border. The DIR algorithm from Plastimatch software was applied to these phantoms. The SUV mapping errors from the DIR were then compared to that predicted by AUTODIRECT. Results: The SUV error distributions closely followed the AUTODIRECT predicted error distribution for the 4 test cases. The minimum and maximum PET SUVs were produced from AUTODIRECT at 95% confidence interval before applying gradient-based SUV segmentation for each of these volumes. Notably, 93.5% of the target volume warped by the true deformation was included within the AUTODIRECT-predicted maximum SUV volume after the segmentation, while 78.9% of the target volume was within the target volume warped by Plastimatch. Conclusion: The AUTODIRECT framework is able to predict PET transfer uncertainty caused by DIR, which enables an understanding of the associated target volume

  15. A fast and fully automatic registration approach based on point features for multi-source remote-sensing images

    NASA Astrophysics Data System (ADS)

    Yu, Le; Zhang, Dengrong; Holden, Eun-Jung

    2008-07-01

    Automatic registration of multi-source remote-sensing images is a difficult task as it must deal with the varying illuminations and resolutions of the images, different perspectives and the local deformations within the images. This paper proposes a fully automatic and fast non-rigid image registration technique that addresses those issues. The proposed technique performs a pre-registration process that coarsely aligns the input image to the reference image by automatically detecting their matching points by using the scale invariant feature transform (SIFT) method and an affine transformation model. Once the coarse registration is completed, it performs a fine-scale registration process based on a piecewise linear transformation technique using feature points that are detected by the Harris corner detector. The registration process firstly finds in succession, tie point pairs between the input and the reference image by detecting Harris corners and applying a cross-matching strategy based on a wavelet pyramid for a fast search speed. Tie point pairs with large errors are pruned by an error-checking step. The input image is then rectified by using triangulated irregular networks (TINs) to deal with irregular local deformations caused by the fluctuation of the terrain. For each triangular facet of the TIN, affine transformations are estimated and applied for rectification. Experiments with Quickbird, SPOT5, SPOT4, TM remote-sensing images of the Hangzhou area in China demonstrate the efficiency and the accuracy of the proposed technique for multi-source remote-sensing image registration.

  16. Selecting registration schemes in case of interstitial lung disease follow-up in CT

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Vlachopoulos, Georgios; Korfiatis, Panayiotis; Skiadopoulos, Spyros

    Purpose: Primary goal of this study is to select optimal registration schemes in the framework of interstitial lung disease (ILD) follow-up analysis in CT. Methods: A set of 128 multiresolution schemes composed of multiresolution nonrigid and combinations of rigid and nonrigid registration schemes are evaluated, utilizing ten artificially warped ILD follow-up volumes, originating from ten clinical volumetric CT scans of ILD affected patients, to select candidate optimal schemes. Specifically, all combinations of four transformation models (three rigid: rigid, similarity, affine and one nonrigid: third order B-spline), four cost functions (sum-of-square distances, normalized correlation coefficient, mutual information, and normalized mutual information),more » four gradient descent optimizers (standard, regular step, adaptive stochastic, and finite difference), and two types of pyramids (recursive and Gaussian-smoothing) were considered. The selection process involves two stages. The first stage involves identification of schemes with deformation field singularities, according to the determinant of the Jacobian matrix. In the second stage, evaluation methodology is based on distance between corresponding landmark points in both normal lung parenchyma (NLP) and ILD affected regions. Statistical analysis was performed in order to select near optimal registration schemes per evaluation metric. Performance of the candidate registration schemes was verified on a case sample of ten clinical follow-up CT scans to obtain the selected registration schemes. Results: By considering near optimal schemes common to all ranking lists, 16 out of 128 registration schemes were initially selected. These schemes obtained submillimeter registration accuracies in terms of average distance errors 0.18 ± 0.01 mm for NLP and 0.20 ± 0.01 mm for ILD, in case of artificially generated follow-up data. Registration accuracy in terms of average distance error in clinical follow-up data was in

  17. Manual limbal markings versus iris-registration software for correction of myopic astigmatism by laser in situ keratomileusis.

    PubMed

    Shen, Elizabeth P; Chen, Wei-Li; Hu, Fung-Rong

    2010-03-01

    To compare the efficacy and safety of manual limbal markings and wavefront-guided treatment with iris-registration software in laser in situ keratomileusis (LASIK) for myopic astigmatism. National Taiwan University Hospital, Taipei, Taiwan. Eyes with myopic astigmatism had LASIK with a Technolas 217z laser. Eyes in the limbal-marking group had conventional LASIK (PlanoScan or Zyoptix tissue-saving algorithm) with manual cyclotorsional-error adjustments according to 2 limbal marks. Eyes in the iris-registration group had wavefront-guided ablation (Zyoptix) in which cyclotorsional errors were automatically detected and adjusted. Refraction, corneal topography, and visual acuity data were compared between groups. Vector analysis was by the Alpins method. The mean preoperative spherical equivalent (SE) was -6.64 diopters (D) +/- 1.99 (SD) in the limbal-marking group and -6.72 +/- 1.86 D in the iris-registration group (P = .92). At 6 months, the mean SE was -0.42 +/- 0.63 D and -0.47 +/- 0.62 D, respectively (P = .08). There was no statistically significant difference between groups in the astigmatism correction, success, or flattening index values using 6-month postoperative refractive data. The angle of error was within +/-10 degrees in 73% of eyes in the limbal-marking group and 75% of eyes in the iris-registration group. Manual limbal markings and iris-registration software were equally effective and safe in LASIK for myopic astigmatism, showing that checking cyclotorsion by manual limbal markings is a safe alternative when automated systems are not available. Copyright 2010 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

  18. INVITED REVIEW--IMAGE REGISTRATION IN VETERINARY RADIATION ONCOLOGY: INDICATIONS, IMPLICATIONS, AND FUTURE ADVANCES.

    PubMed

    Feng, Yang; Lawrence, Jessica; Cheng, Kun; Montgomery, Dean; Forrest, Lisa; Mclaren, Duncan B; McLaughlin, Stephen; Argyle, David J; Nailon, William H

    2016-01-01

    The field of veterinary radiation therapy (RT) has gained substantial momentum in recent decades with significant advances in conformal treatment planning, image-guided radiation therapy (IGRT), and intensity-modulated (IMRT) techniques. At the root of these advancements lie improvements in tumor imaging, image alignment (registration), target volume delineation, and identification of critical structures. Image registration has been widely used to combine information from multimodality images such as computerized tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) to improve the accuracy of radiation delivery and reliably identify tumor-bearing areas. Many different techniques have been applied in image registration. This review provides an overview of medical image registration in RT and its applications in veterinary oncology. A summary of the most commonly used approaches in human and veterinary medicine is presented along with their current use in IGRT and adaptive radiation therapy (ART). It is important to realize that registration does not guarantee that target volumes, such as the gross tumor volume (GTV), are correctly identified on the image being registered, as limitations unique to registration algorithms exist. Research involving novel registration frameworks for automatic segmentation of tumor volumes is ongoing and comparative oncology programs offer a unique opportunity to test the efficacy of proposed algorithms. © 2016 American College of Veterinary Radiology.

  19. An ITK framework for deterministic global optimization for medical image registration

    NASA Astrophysics Data System (ADS)

    Dru, Florence; Wachowiak, Mark P.; Peters, Terry M.

    2006-03-01

    Similarity metric optimization is an essential step in intensity-based rigid and nonrigid medical image registration. For clinical applications, such as image guidance of minimally invasive procedures, registration accuracy and efficiency are prime considerations. In addition, clinical utility is enhanced when registration is integrated into image analysis and visualization frameworks, such as the popular Insight Toolkit (ITK). ITK is an open source software environment increasingly used to aid the development, testing, and integration of new imaging algorithms. In this paper, we present a new ITK-based implementation of the DIRECT (Dividing Rectangles) deterministic global optimization algorithm for medical image registration. Previously, it has been shown that DIRECT improves the capture range and accuracy for rigid registration. Our ITK class also contains enhancements over the original DIRECT algorithm by improving stopping criteria, adaptively adjusting a locality parameter, and by incorporating Powell's method for local refinement. 3D-3D registration experiments with ground-truth brain volumes and clinical cardiac volumes show that combining DIRECT with Powell's method improves registration accuracy over Powell's method used alone, is less sensitive to initial misorientation errors, and, with the new stopping criteria, facilitates adequate exploration of the search space without expending expensive iterations on non-improving function evaluations. Finally, in this framework, a new parallel implementation for computing mutual information is presented, resulting in near-linear speedup with two processors.

  20. A 4D biomechanical lung phantom for joint segmentation/registration evaluation

    NASA Astrophysics Data System (ADS)

    Markel, Daniel; Levesque, Ives; Larkin, Joe; Léger, Pierre; El Naqa, Issam

    2016-10-01

    At present, there exists few openly available methods for evaluation of simultaneous segmentation and registration algorithms. These methods allow for a combination of both techniques to track the tumor in complex settings such as adaptive radiotherapy. We have produced a quality assurance platform for evaluating this specific subset of algorithms using a preserved porcine lung in such that it is multi-modality compatible: positron emission tomography (PET), computer tomography (CT) and magnetic resonance imaging (MRI). A computer controlled respirator was constructed to pneumatically manipulate the lungs in order to replicate human breathing traces. A registration ground truth was provided using an in-house bifurcation tracking pipeline. Segmentation ground truth was provided by synthetic multi-compartment lesions to simulate biologically active tumor, background tissue and a necrotic core. The bifurcation tracking pipeline results were compared to digital deformations and used to evaluate three registration algorithms, Diffeomorphic demons, fast-symmetric forces demons and MiMVista’s deformable registration tool. Three segmentation algorithms the Chan Vese level sets method, a Hybrid technique and the multi-valued level sets algorithm. The respirator was able to replicate three seperate breathing traces with a mean accuracy of 2-2.2%. Bifurcation tracking error was found to be sub-voxel when using human CT data for displacements up to 6.5 cm and approximately 1.5 voxel widths for displacements up to 3.5 cm for the porcine lungs. For the fast-symmetric, diffeomorphic and MiMvista registration algorithms, mean geometric errors were found to be 0.430+/- 0.001 , 0.416+/- 0.001 and 0.605+/- 0.002 voxels widths respectively using the vector field differences and 0.4+/- 0.2 , 0.4+/- 0.2 and 0.6+/- 0.2 voxel widths using the bifurcation tracking pipeline. The proposed phantom was found sufficient for accurate evaluation of registration and segmentation algorithms

  1. The impact of registration accuracy on imaging validation study design: A novel statistical power calculation.

    PubMed

    Gibson, Eli; Fenster, Aaron; Ward, Aaron D

    2013-10-01

    Novel imaging modalities are pushing the boundaries of what is possible in medical imaging, but their signal properties are not always well understood. The evaluation of these novel imaging modalities is critical to achieving their research and clinical potential. Image registration of novel modalities to accepted reference standard modalities is an important part of characterizing the modalities and elucidating the effect of underlying focal disease on the imaging signal. The strengths of the conclusions drawn from these analyses are limited by statistical power. Based on the observation that in this context, statistical power depends in part on uncertainty arising from registration error, we derive a power calculation formula relating registration error, number of subjects, and the minimum detectable difference between normal and pathologic regions on imaging, for an imaging validation study design that accommodates signal correlations within image regions. Monte Carlo simulations were used to evaluate the derived models and test the strength of their assumptions, showing that the model yielded predictions of the power, the number of subjects, and the minimum detectable difference of simulated experiments accurate to within a maximum error of 1% when the assumptions of the derivation were met, and characterizing sensitivities of the model to violations of the assumptions. The use of these formulae is illustrated through a calculation of the number of subjects required for a case study, modeled closely after a prostate cancer imaging validation study currently taking place at our institution. The power calculation formulae address three central questions in the design of imaging validation studies: (1) What is the maximum acceptable registration error? (2) How many subjects are needed? (3) What is the minimum detectable difference between normal and pathologic image regions? Copyright © 2013 Elsevier B.V. All rights reserved.

  2. Third molar development: evaluation of nine tooth development registration techniques for age estimations.

    PubMed

    Thevissen, Patrick W; Fieuws, Steffen; Willems, Guy

    2013-03-01

    Multiple third molar development registration techniques exist. Therefore the aim of this study was to detect which third molar development registration technique was most promising to use as a tool for subadult age estimation. On a collection of 1199 panoramic radiographs the development of all present third molars was registered following nine different registration techniques [Gleiser, Hunt (GH); Haavikko (HV); Demirjian (DM); Raungpaka (RA); Gustafson, Koch (GK); Harris, Nortje (HN); Kullman (KU); Moorrees (MO); Cameriere (CA)]. Regression models with age as response and the third molar registration as predictor were developed for each registration technique separately. The MO technique disclosed highest R(2) (F 51%, M 45%) and lowest root mean squared error (F 3.42 years; M 3.67 years) values, but differences with other techniques were small in magnitude. The amount of stages utilized in the explored staging techniques slightly influenced the age predictions. © 2013 American Academy of Forensic Sciences.

  3. Optimized SIFTFlow for registration of whole-mount histology to reference optical images

    PubMed Central

    Shojaii, Rushin; Martel, Anne L.

    2016-01-01

    Abstract. The registration of two-dimensional histology images to reference images from other modalities is an important preprocessing step in the reconstruction of three-dimensional histology volumes. This is a challenging problem because of the differences in the appearances of histology images and other modalities, and the presence of large nonrigid deformations which occur during slide preparation. This paper shows the feasibility of using densely sampled scale-invariant feature transform (SIFT) features and a SIFTFlow deformable registration algorithm for coregistering whole-mount histology images with blockface optical images. We present a method for jointly optimizing the regularization parameters used by the SIFTFlow objective function and use it to determine the most appropriate values for the registration of breast lumpectomy specimens. We demonstrate that tuning the regularization parameters results in significant improvements in accuracy and we also show that SIFTFlow outperforms a previously described edge-based registration method. The accuracy of the histology images to blockface images registration using the optimized SIFTFlow method was assessed using an independent test set of images from five different lumpectomy specimens and the mean registration error was 0.32±0.22  mm. PMID:27774494

  4. Registration-based segmentation with articulated model from multipostural magnetic resonance images for hand bone motion animation.

    PubMed

    Chen, Hsin-Chen; Jou, I-Ming; Wang, Chien-Kuo; Su, Fong-Chin; Sun, Yung-Nien

    2010-06-01

    The quantitative measurements of hand bones, including volume, surface, orientation, and position are essential in investigating hand kinematics. Moreover, within the measurement stage, bone segmentation is the most important step due to its certain influences on measuring accuracy. Since hand bones are small and tubular in shape, magnetic resonance (MR) imaging is prone to artifacts such as nonuniform intensity and fuzzy boundaries. Thus, greater detail is required for improving segmentation accuracy. The authors then propose using a novel registration-based method on an articulated hand model to segment hand bones from multipostural MR images. The proposed method consists of the model construction and registration-based segmentation stages. Given a reference postural image, the first stage requires construction of a drivable reference model characterized by hand bone shapes, intensity patterns, and articulated joint mechanism. By applying the reference model to the second stage, the authors initially design a model-based registration pursuant to intensity distribution similarity, MR bone intensity properties, and constraints of model geometry to align the reference model to target bone regions of the given postural image. The authors then refine the resulting surface to improve the superimposition between the registered reference model and target bone boundaries. For each subject, given a reference postural image, the proposed method can automatically segment all hand bones from all other postural images. Compared to the ground truth from two experts, the resulting surface image had an average margin of error within 1 mm (mm) only. In addition, the proposed method showed good agreement on the overlap of bone segmentations by dice similarity coefficient and also demonstrated better segmentation results than conventional methods. The proposed registration-based segmentation method can successfully overcome drawbacks caused by inherent artifacts in MR images and

  5. Effect of deformable registration on the dose calculated in radiation therapy planning CT scans of lung cancer patients

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Cunliffe, Alexandra R.; Armato, Samuel G.; White, Bradley

    2015-01-15

    : An average error of <4 Gy in radiation dose was introduced when points were mapped between CT scan pairs using deformable registration, with the majority of points yielding dose-mapping error <2 Gy (approximately 3% of the total prescribed dose). Registration accuracy was highest using the Fraunhofer MEVIS EMPIRE10 algorithm, resulting in the smallest errors in mapped dose. Dose differences following registration increased significantly with increasing spatial registration errors, dose, and dose gradient (i.e., SD{sub dose}). This model provides a measurement of the uncertainty in the radiation dose when points are mapped between serial CT scans through deformable registration.« less

  6. 2D-3D registration for cranial radiation therapy using a 3D kV CBCT and a single limited field-of-view 2D kV radiograph.

    PubMed

    Munbodh, Reshma; Knisely, Jonathan Ps; Jaffray, David A; Moseley, Douglas J

    2018-05-01

    We present and evaluate a fully automated 2D-3D intensity-based registration framework using a single limited field-of-view (FOV) 2D kV radiograph and a 3D kV CBCT for 3D estimation of patient setup errors during brain radiotherapy. We evaluated two similarity measures, the Pearson correlation coefficient on image intensity values (ICC) and maximum likelihood measure with Gaussian noise (MLG), derived from the statistics of transmission images. Pose determination experiments were conducted on 2D kV radiographs in the anterior-posterior (AP) and left lateral (LL) views and 3D kV CBCTs of an anthropomorphic head phantom. In order to minimize radiation exposure and exclude nonrigid structures from the registration, limited FOV 2D kV radiographs were employed. A spatial frequency band useful for the 2D-3D registration was identified from the bone-to-no-bone spectral ratio (BNBSR) of digitally reconstructed radiographs (DRRs) computed from the 3D kV planning CT of the phantom. The images being registered were filtered accordingly prior to computation of the similarity measures. We evaluated the registration accuracy achievable with a single 2D kV radiograph and with the registration results from the AP and LL views combined. We also compared the performance of the 2D-3D registration solutions proposed to that of a commercial 3D-3D registration algorithm, which used the entire skull for the registration. The ground truth was determined from markers affixed to the phantom and visible in the CBCT images. The accuracy of the 2D-3D registration solutions, as quantified by the root mean squared value of the target registration error (TRE) calculated over a radius of 3 cm for all poses tested, was ICC AP : 0.56 mm, MLG AP : 0.74 mm, ICC LL : 0.57 mm, MLG LL : 0.54 mm, ICC (AP and LL combined): 0.19 mm, and MLG (AP and LL combined): 0.21 mm. The accuracy of the 3D-3D registration algorithm was 0.27 mm. There was no significant difference in mean TRE for the 2D-3D registration

  7. Active edge maps for medical image registration

    NASA Astrophysics Data System (ADS)

    Kerwin, William; Yuan, Chun

    2001-07-01

    Applying edge detection prior to performing image registration yields several advantages over raw intensity- based registration. Advantages include the ability to register multicontrast or multimodality images, immunity to intensity variations, and the potential for computationally efficient algorithms. In this work, a common framework for edge-based image registration is formulated as an adaptation of snakes used in boundary detection. Called active edge maps, the new formulation finds a one-to-one transformation T(x) that maps points in a source image to corresponding locations in a target image using an energy minimization approach. The energy consists of an image component that is small when edge features are well matched in the two images, and an internal term that restricts T(x) to allowable configurations. The active edge map formulation is illustrated here with a specific example developed for affine registration of carotid artery magnetic resonance images. In this example, edges are identified using a magnitude of gradient operator, image energy is determined using a Gaussian weighted distance function, and the internal energy includes separate, adjustable components that control volume preservation and rigidity.

  8. Quantitative modeling of the accuracy in registering preoperative patient-specific anatomic models into left atrial cardiac ablation procedures

    PubMed Central

    Rettmann, Maryam E.; Holmes, David R.; Kwartowitz, David M.; Gunawan, Mia; Johnson, Susan B.; Camp, Jon J.; Cameron, Bruce M.; Dalegrave, Charles; Kolasa, Mark W.; Packer, Douglas L.; Robb, Richard A.

    2014-01-01

    Purpose: In cardiac ablation therapy, accurate anatomic guidance is necessary to create effective tissue lesions for elimination of left atrial fibrillation. While fluoroscopy, ultrasound, and electroanatomic maps are important guidance tools, they lack information regarding detailed patient anatomy which can be obtained from high resolution imaging techniques. For this reason, there has been significant effort in incorporating detailed, patient-specific models generated from preoperative imaging datasets into the procedure. Both clinical and animal studies have investigated registration and targeting accuracy when using preoperative models; however, the effect of various error sources on registration accuracy has not been quantitatively evaluated. Methods: Data from phantom, canine, and patient studies are used to model and evaluate registration accuracy. In the phantom studies, data are collected using a magnetically tracked catheter on a static phantom model. Monte Carlo simulation studies were run to evaluate both baseline errors as well as the effect of different sources of error that would be present in a dynamic in vivo setting. Error is simulated by varying the variance parameters on the landmark fiducial, physical target, and surface point locations in the phantom simulation studies. In vivo validation studies were undertaken in six canines in which metal clips were placed in the left atrium to serve as ground truth points. A small clinical evaluation was completed in three patients. Landmark-based and combined landmark and surface-based registration algorithms were evaluated in all studies. In the phantom and canine studies, both target registration error and point-to-surface error are used to assess accuracy. In the patient studies, no ground truth is available and registration accuracy is quantified using point-to-surface error only. Results: The phantom simulation studies demonstrated that combined landmark and surface-based registration improved

  9. WE-AB-BRA-12: Virtual Endoscope Tracking for Endoscopy-CT Image Registration

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ingram, W; Rao, A; Wendt, R

    Purpose: The use of endoscopy in radiotherapy will remain limited until we can register endoscopic video to CT using standard clinical equipment. In this phantom study we tested a registration method using virtual endoscopy to measure CT-space positions from endoscopic video. Methods: Our phantom is a contorted clay cylinder with 2-mm-diameter markers in the luminal surface. These markers are visible on both CT and endoscopic video. Virtual endoscope images were rendered from a polygonal mesh created by segmenting the phantom’s luminal surface on CT. We tested registration accuracy by tracking the endoscope’s 6-degree-of-freedom coordinates frame-to-frame in a video recorded asmore » it moved through the phantom, and using these coordinates to measure CT-space positions of markers visible in the final frame. To track the endoscope we used the Nelder-Mead method to search for coordinates that render the virtual frame most similar to the next recorded frame. We measured the endoscope’s initial-frame coordinates using a set of visible markers, and for image similarity we used a combination of mutual information and gradient alignment. CT-space marker positions were measured by projecting their final-frame pixel addresses through the virtual endoscope to intersect with the mesh. Registration error was quantified as the distance between this intersection and the marker’s manually-selected CT-space position. Results: Tracking succeeded for 6 of 8 videos, for which the mean registration error was 4.8±3.5mm (24 measurements total). The mean error in the axial direction (3.1±3.3mm) was larger than in the sagittal or coronal directions (2.0±2.3mm, 1.7±1.6mm). In the other 2 videos, the virtual endoscope got stuck in a false minimum. Conclusion: Our method can successfully track the position and orientation of an endoscope, and it provides accurate spatial mapping from endoscopic video to CT. This method will serve as a foundation for an endoscopy

  10. a Weighted Closed-Form Solution for Rgb-D Data Registration

    NASA Astrophysics Data System (ADS)

    Vestena, K. M.; Dos Santos, D. R.; Oilveira, E. M., Jr.; Pavan, N. L.; Khoshelham, K.

    2016-06-01

    Existing 3D indoor mapping of RGB-D data are prominently point-based and feature-based methods. In most cases iterative closest point (ICP) and its variants are generally used for pairwise registration process. Considering that the ICP algorithm requires an relatively accurate initial transformation and high overlap a weighted closed-form solution for RGB-D data registration is proposed. In this solution, we weighted and normalized the 3D points based on the theoretical random errors and the dual-number quaternions are used to represent the 3D rigid body motion. Basically, dual-number quaternions provide a closed-form solution by minimizing a cost function. The most important advantage of the closed-form solution is that it provides the optimal transformation in one-step, it does not need to calculate good initial estimates and expressively decreases the demand for computer resources in contrast to the iterative method. Basically, first our method exploits RGB information. We employed a scale invariant feature transformation (SIFT) for extracting, detecting, and matching features. It is able to detect and describe local features that are invariant to scaling and rotation. To detect and filter outliers, we used random sample consensus (RANSAC) algorithm, jointly with an statistical dispersion called interquartile range (IQR). After, a new RGB-D loop-closure solution is implemented based on the volumetric information between pair of point clouds and the dispersion of the random errors. The loop-closure consists to recognize when the sensor revisits some region. Finally, a globally consistent map is created to minimize the registration errors via a graph-based optimization. The effectiveness of the proposed method is demonstrated with a Kinect dataset. The experimental results show that the proposed method can properly map the indoor environment with an absolute accuracy around 1.5% of the travel of a trajectory.

  11. Image registration assessment in radiotherapy image guidance based on control chart monitoring.

    PubMed

    Xia, Wenyao; Breen, Stephen L

    2018-04-01

    Image guidance with cone beam computed tomography in radiotherapy can guarantee the precision and accuracy of patient positioning prior to treatment delivery. During the image guidance process, operators need to take great effort to evaluate the image guidance quality before correcting a patient's position. This work proposes an image registration assessment method based on control chart monitoring to reduce the effort taken by the operator. According to the control chart plotted by daily registration scores of each patient, the proposed method can quickly detect both alignment errors and image quality inconsistency. Therefore, the proposed method can provide a clear guideline for the operators to identify unacceptable image quality and unacceptable image registration with minimal effort. Experimental results demonstrate that by using control charts from a clinical database of 10 patients undergoing prostate radiotherapy, the proposed method can quickly identify out-of-control signals and find special cause of out-of-control registration events.

  12. Multi-institutional Validation Study of Commercially Available Deformable Image Registration Software for Thoracic Images.

    PubMed

    Kadoya, Noriyuki; Nakajima, Yujiro; Saito, Masahide; Miyabe, Yuki; Kurooka, Masahiko; Kito, Satoshi; Fujita, Yukio; Sasaki, Motoharu; Arai, Kazuhiro; Tani, Kensuke; Yagi, Masashi; Wakita, Akihisa; Tohyama, Naoki; Jingu, Keiichi

    2016-10-01

    To assess the accuracy of the commercially available deformable image registration (DIR) software for thoracic images at multiple institutions. Thoracic 4-dimensional (4D) CT images of 10 patients with esophageal or lung cancer were used. Datasets for these patients were provided by DIR-lab (dir-lab.com) and included a coordinate list of anatomic landmarks (300 bronchial bifurcations) that had been manually identified. Deformable image registration was performed between the peak-inhale and -exhale images. Deformable image registration error was determined by calculating the difference at each landmark point between the displacement calculated by DIR software and that calculated by the landmark. Eleven institutions participated in this study: 4 used RayStation (RaySearch Laboratories, Stockholm, Sweden), 5 used MIM Software (Cleveland, OH), and 3 used Velocity (Varian Medical Systems, Palo Alto, CA). The ranges of the average absolute registration errors over all cases were as follows: 0.48 to 1.51 mm (right-left), 0.53 to 2.86 mm (anterior-posterior), 0.85 to 4.46 mm (superior-inferior), and 1.26 to 6.20 mm (3-dimensional). For each DIR software package, the average 3-dimensional registration error (range) was as follows: RayStation, 3.28 mm (1.26-3.91 mm); MIM Software, 3.29 mm (2.17-3.61 mm); and Velocity, 5.01 mm (4.02-6.20 mm). These results demonstrate that there was moderate variation among institutions, although the DIR software was the same. We evaluated the commercially available DIR software using thoracic 4D-CT images from multiple centers. Our results demonstrated that DIR accuracy differed among institutions because it was dependent on both the DIR software and procedure. Our results could be helpful for establishing prospective clinical trials and for the widespread use of DIR software. In addition, for clinical care, we should try to find the optimal DIR procedure using thoracic 4D-CT data. Copyright © 2016 Elsevier Inc. All rights

  13. Multi-institutional Validation Study of Commercially Available Deformable Image Registration Software for Thoracic Images

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kadoya, Noriyuki, E-mail: kadoya.n@rad.med.tohoku.ac.jp; Nakajima, Yujiro; Saito, Masahide

    Purpose: To assess the accuracy of the commercially available deformable image registration (DIR) software for thoracic images at multiple institutions. Methods and Materials: Thoracic 4-dimensional (4D) CT images of 10 patients with esophageal or lung cancer were used. Datasets for these patients were provided by DIR-lab ( (dir-lab.com)) and included a coordinate list of anatomic landmarks (300 bronchial bifurcations) that had been manually identified. Deformable image registration was performed between the peak-inhale and -exhale images. Deformable image registration error was determined by calculating the difference at each landmark point between the displacement calculated by DIR software and that calculated bymore » the landmark. Results: Eleven institutions participated in this study: 4 used RayStation (RaySearch Laboratories, Stockholm, Sweden), 5 used MIM Software (Cleveland, OH), and 3 used Velocity (Varian Medical Systems, Palo Alto, CA). The ranges of the average absolute registration errors over all cases were as follows: 0.48 to 1.51 mm (right-left), 0.53 to 2.86 mm (anterior-posterior), 0.85 to 4.46 mm (superior-inferior), and 1.26 to 6.20 mm (3-dimensional). For each DIR software package, the average 3-dimensional registration error (range) was as follows: RayStation, 3.28 mm (1.26-3.91 mm); MIM Software, 3.29 mm (2.17-3.61 mm); and Velocity, 5.01 mm (4.02-6.20 mm). These results demonstrate that there was moderate variation among institutions, although the DIR software was the same. Conclusions: We evaluated the commercially available DIR software using thoracic 4D-CT images from multiple centers. Our results demonstrated that DIR accuracy differed among institutions because it was dependent on both the DIR software and procedure. Our results could be helpful for establishing prospective clinical trials and for the widespread use of DIR software. In addition, for clinical care, we should try to find the optimal DIR procedure using

  14. Automatic segmentation and co-registration of gated CT angiography datasets: measuring abdominal aortic pulsatility

    NASA Astrophysics Data System (ADS)

    Wentz, Robert; Manduca, Armando; Fletcher, J. G.; Siddiki, Hassan; Shields, Raymond C.; Vrtiska, Terri; Spencer, Garrett; Primak, Andrew N.; Zhang, Jie; Nielson, Theresa; McCollough, Cynthia; Yu, Lifeng

    2007-03-01

    Purpose: To develop robust, novel segmentation and co-registration software to analyze temporally overlapping CT angiography datasets, with an aim to permit automated measurement of regional aortic pulsatility in patients with abdominal aortic aneurysms. Methods: We perform retrospective gated CT angiography in patients with abdominal aortic aneurysms. Multiple, temporally overlapping, time-resolved CT angiography datasets are reconstructed over the cardiac cycle, with aortic segmentation performed using a priori anatomic assumptions for the aorta and heart. Visual quality assessment is performed following automatic segmentation with manual editing. Following subsequent centerline generation, centerlines are cross-registered across phases, with internal validation of co-registration performed by examining registration at the regions of greatest diameter change (i.e. when the second derivative is maximal). Results: We have performed gated CT angiography in 60 patients. Automatic seed placement is successful in 79% of datasets, requiring either no editing (70%) or minimal editing (less than 1 minute; 12%). Causes of error include segmentation into adjacent, high-attenuating, nonvascular tissues; small segmentation errors associated with calcified plaque; and segmentation of non-renal, small paralumbar arteries. Internal validation of cross-registration demonstrates appropriate registration in our patient population. In general, we observed that aortic pulsatility can vary along the course of the abdominal aorta. Pulsation can also vary within an aneurysm as well as between aneurysms, but the clinical significance of these findings remain unknown. Conclusions: Visualization of large vessel pulsatility is possible using ECG-gated CT angiography, partial scan reconstruction, automatic segmentation, centerline generation, and coregistration of temporally resolved datasets.

  15. Complete Systematic Error Model of SSR for Sensor Registration in ATC Surveillance Networks

    PubMed Central

    Besada, Juan A.

    2017-01-01

    In this paper, a complete and rigorous mathematical model for secondary surveillance radar systematic errors (biases) is developed. The model takes into account the physical effects systematically affecting the measurement processes. The azimuth biases are calculated from the physical error of the antenna calibration and the errors of the angle determination dispositive. Distance bias is calculated from the delay of the signal produced by the refractivity index of the atmosphere, and from clock errors, while the altitude bias is calculated taking into account the atmosphere conditions (pressure and temperature). It will be shown, using simulated and real data, that adapting a classical bias estimation process to use the complete parametrized model results in improved accuracy in the bias estimation. PMID:28934157

  16. Efficient Multi-Atlas Registration using an Intermediate Template Image

    PubMed Central

    Dewey, Blake E.; Carass, Aaron; Blitz, Ari M.; Prince, Jerry L.

    2017-01-01

    Multi-atlas label fusion is an accurate but time-consuming method of labeling the human brain. Using an intermediate image as a registration target can allow researchers to reduce time constraints by storing the deformations required of the atlas images. In this paper, we investigate the effect of registration through an intermediate template image on multi-atlas label fusion and propose a novel registration technique to counteract the negative effects of through-template registration. We show that overall computation time can be decreased dramatically with minimal impact on final label accuracy and time can be exchanged for improved results in a predictable manner. We see almost complete recovery of Dice similarity over a simple through-template registration using the corrected method and still maintain a 3–4 times speed increase. Further, we evaluate the effectiveness of this method on brains of patients with normal-pressure hydrocephalus, where abnormal brain shape presents labeling difficulties, specifically the ventricular labels. Our correction method creates substantially better ventricular labeling than traditional methods and maintains the speed increase seen in healthy subjects. PMID:28943702

  17. Efficient multi-atlas registration using an intermediate template image

    NASA Astrophysics Data System (ADS)

    Dewey, Blake E.; Carass, Aaron; Blitz, Ari M.; Prince, Jerry L.

    2017-03-01

    Multi-atlas label fusion is an accurate but time-consuming method of labeling the human brain. Using an intermediate image as a registration target can allow researchers to reduce time constraints by storing the deformations required of the atlas images. In this paper, we investigate the effect of registration through an intermediate template image on multi-atlas label fusion and propose a novel registration technique to counteract the negative effects of through-template registration. We show that overall computation time can be decreased dramatically with minimal impact on final label accuracy and time can be exchanged for improved results in a predictable manner. We see almost complete recovery of Dice similarity over a simple through-template registration using the corrected method and still maintain a 3-4 times speed increase. Further, we evaluate the effectiveness of this method on brains of patients with normal-pressure hydrocephalus, where abnormal brain shape presents labeling difficulties, specifically the ventricular labels. Our correction method creates substantially better ventricular labeling than traditional methods and maintains the speed increase seen in healthy subjects.

  18. Non-rigid registration between 3D ultrasound and CT images of the liver based on intensity and gradient information

    NASA Astrophysics Data System (ADS)

    Lee, Duhgoon; Nam, Woo Hyun; Lee, Jae Young; Ra, Jong Beom

    2011-01-01

    In order to utilize both ultrasound (US) and computed tomography (CT) images of the liver concurrently for medical applications such as diagnosis and image-guided intervention, non-rigid registration between these two types of images is an essential step, as local deformation between US and CT images exists due to the different respiratory phases involved and due to the probe pressure that occurs in US imaging. This paper introduces a voxel-based non-rigid registration algorithm between the 3D B-mode US and CT images of the liver. In the proposed algorithm, to improve the registration accuracy, we utilize the surface information of the liver and gallbladder in addition to the information of the vessels inside the liver. For an effective correlation between US and CT images, we treat those anatomical regions separately according to their characteristics in US and CT images. Based on a novel objective function using a 3D joint histogram of the intensity and gradient information, vessel-based non-rigid registration is followed by surface-based non-rigid registration in sequence, which improves the registration accuracy. The proposed algorithm is tested for ten clinical datasets and quantitative evaluations are conducted. Experimental results show that the registration error between anatomical features of US and CT images is less than 2 mm on average, even with local deformation due to different respiratory phases and probe pressure. In addition, the lesion registration error is less than 3 mm on average with a maximum of 4.5 mm that is considered acceptable for clinical applications.

  19. Convex Hull Aided Registration Method (CHARM).

    PubMed

    Fan, Jingfan; Yang, Jian; Zhao, Yitian; Ai, Danni; Liu, Yonghuai; Wang, Ge; Wang, Yongtian

    2017-09-01

    Non-rigid registration finds many applications such as photogrammetry, motion tracking, model retrieval, and object recognition. In this paper we propose a novel convex hull aided registration method (CHARM) to match two point sets subject to a non-rigid transformation. First, two convex hulls are extracted from the source and target respectively. Then, all points of the point sets are projected onto the reference plane through each triangular facet of the hulls. From these projections, invariant features are extracted and matched optimally. The matched feature point pairs are mapped back onto the triangular facets of the convex hulls to remove outliers that are outside any relevant triangular facet. The rigid transformation from the source to the target is robustly estimated by the random sample consensus (RANSAC) scheme through minimizing the distance between the matched feature point pairs. Finally, these feature points are utilized as the control points to achieve non-rigid deformation in the form of thin-plate spline of the entire source point set towards the target one. The experimental results based on both synthetic and real data show that the proposed algorithm outperforms several state-of-the-art ones with respect to sampling, rotational angle, and data noise. In addition, the proposed CHARM algorithm also shows higher computational efficiency compared to these methods.

  20. Extra-dimensional Demons: a method for incorporating missing tissue in deformable image registration.

    PubMed

    Nithiananthan, Sajendra; Schafer, Sebastian; Mirota, Daniel J; Stayman, J Webster; Zbijewski, Wojciech; Reh, Douglas D; Gallia, Gary L; Siewerdsen, Jeffrey H

    2012-09-01

    conventional Demons approach imparted unrealistic distortions in areas around tissue excision, whereas XDD provided accurate "ejection" of voxels within the excision site and maintained the registration accuracy throughout the rest of the image. Registration accuracy in areas far from the excision site (e.g., > ∼5 mm) was identical for the two approaches. Quantitation of the effect was consistent in analysis of NMI, normalized cross-correlation (NCC), target registration error (TRE), and accuracy of voxels ejected from the volume (true-positive and false-positive analysis). The registration accuracy for conventional Demons was found to degrade steeply as a function of excision size, whereas XDD was robust in this regard. Cadaver studies involving realistic excision of the clivus, vidian canal, and ethmoid sinuses demonstrated similar results, with unrealistic distortion of anatomy imparted by conventional Demons and accurate ejection and deformation for XDD. Adaptation of the Demons deformable registration process to include segmentation (i.e., identification of excised tissue) and an extra dimension in the deformation field provided a means to accurately accommodate missing tissue between image acquisitions. The extra-dimensional approach yielded accurate "ejection" of voxels local to the excision site while preserving the registration accuracy (typically subvoxel) of the conventional Demons approach throughout the rest of the image. The ability to accommodate missing tissue volumes is important to application of CBCT for surgical guidance (e.g., skull base drillout) and may have application in other areas of CBCT guidance.

  1. Statistical modeling of 4D respiratory lung motion using diffeomorphic image registration.

    PubMed

    Ehrhardt, Jan; Werner, René; Schmidt-Richberg, Alexander; Handels, Heinz

    2011-02-01

    Modeling of respiratory motion has become increasingly important in various applications of medical imaging (e.g., radiation therapy of lung cancer). Current modeling approaches are usually confined to intra-patient registration of 3D image data representing the individual patient's anatomy at different breathing phases. We propose an approach to generate a mean motion model of the lung based on thoracic 4D computed tomography (CT) data of different patients to extend the motion modeling capabilities. Our modeling process consists of three steps: an intra-subject registration to generate subject-specific motion models, the generation of an average shape and intensity atlas of the lung as anatomical reference frame, and the registration of the subject-specific motion models to the atlas in order to build a statistical 4D mean motion model (4D-MMM). Furthermore, we present methods to adapt the 4D mean motion model to a patient-specific lung geometry. In all steps, a symmetric diffeomorphic nonlinear intensity-based registration method was employed. The Log-Euclidean framework was used to compute statistics on the diffeomorphic transformations. The presented methods are then used to build a mean motion model of respiratory lung motion using thoracic 4D CT data sets of 17 patients. We evaluate the model by applying it for estimating respiratory motion of ten lung cancer patients. The prediction is evaluated with respect to landmark and tumor motion, and the quantitative analysis results in a mean target registration error (TRE) of 3.3 ±1.6 mm if lung dynamics are not impaired by large lung tumors or other lung disorders (e.g., emphysema). With regard to lung tumor motion, we show that prediction accuracy is independent of tumor size and tumor motion amplitude in the considered data set. However, tumors adhering to non-lung structures degrade local lung dynamics significantly and the model-based prediction accuracy is lower in these cases. The statistical respiratory

  2. Toward magnetic resonance-guided electroanatomical voltage mapping for catheter ablation of scar-related ventricular tachycardia: a comparison of registration methods.

    PubMed

    Tao, Qian; Milles, Julien; VAN Huls VAN Taxis, Carine; Lamb, Hildo J; Reiber, Johan H C; Zeppenfeld, Katja; VAN DER Geest, Rob J

    2012-01-01

    Integration of preprocedural delayed enhanced magnetic resonance imaging (DE-MRI) with electroanatomical voltage mapping (EAVM) may provide additional high-resolution substrate information for catheter ablation of scar-related ventricular tachycardias (VT). Accurate and fast image integration of DE-MRI with EAVM is desirable for MR-guided ablation. Twenty-six VT patients with large transmural scar underwent catheter ablation and preprocedural DE-MRI. With different registration models and EAVM input, 3 image integration methods were evaluated and compared to the commercial registration module CartoMerge. The performance was evaluated both in terms of distance measure that describes surface matching, and correlation measure that describes actual scar correspondence. Compared to CartoMerge, the method that uses the translation-and-rotation model and high-density EAVM input resulted in a registration error of 4.32±0.69 mm as compared to 4.84 ± 1.07 (P <0.05); the method that uses the translation model and high-density EAVM input resulted in a registration error of 4.60 ± 0.65 mm (P = NS); and the method that uses the translation model and a single anatomical landmark input resulted in a registration error of 6.58 ± 1.63 mm (P < 0.05). No significant difference in scar correlation was observed between all 3 methods and CartoMerge (P = NS). During VT ablation procedures, accurate integration of EAVM and DE-MRI can be achieved using a translation registration model and a single anatomical landmark. This model allows for image integration in minimal mapping time and is likely to reduce fluoroscopy time and increase procedure efficacy. © 2011 Wiley Periodicals, Inc.

  3. Effect of iris registration on outcomes of FEMTOLASIK for myopia and myopic astigmatism.

    PubMed

    Ghoreishi, Mohammad; Beni, Zahra Naderi; Beni, Afsaneh Naderi; Kianersi, Farzan

    2017-09-05

    To compare the visual and refractive outcomes after FEMTOLASIK with and without iris registration. In this randomized, prospective, comparative, contralateral eye study, 118 eyes of 59 patients with myopia and myopic astigmatism underwent LASIK using the Femto LDV femtosecond laser (160 µm) and the MEL80 with or without iris registration. For each patient, iris registration FEMTOLASIK was performed on one eye and non-iris registration FEMTOLASIK was performed on the other eye, assigned at random. Patients were evaluated before and 12 months. Uncorrected visual acuity, best-corrected visual acuity, manifest refraction, contrast sensitivity, and higher-order aberrations (HOAs) were evaluated. At 12 months, the mean UDVA was 0.002 ± 0.07 logMAR (20/19) in iris registration eyes and 0.00 ± 0.06 logMAR (20/24) in non-iris registration eyes (P = 0.9). 61% of iris registration eyes and 71.2% of non-iris registration eyes achieved a UDVA of 20/20 or better (P = 0.31); 98.3% of eyes with the iris registration FEMTOLASIK and 94.9% with the non-iris registration FEMTOLASIK were within ±0.50 D from emmetropia (P = 0.71). No statistically significant difference was found in postoperative contrast sensitivity between groups at 3, 6, 12, or 18 cycles/degree (P > 0.05). There was significant increase in total HOA root mean square in two groups. The mean error magnitude of surgically induced astigmatism 12 months postoperatively was -0.33 in iris registration eyes and -0.24 in the non-iris registration eyes (P = 0.36). FEMTOLASIK with and without iris registration provides similar results in myopic and myopic astigmatism patients.

  4. SU-E-J-90: 2D/3D Registration Using KV-MV Image Pairs for Higher Accuracy Image Guided Radiotherapy.

    PubMed

    Furtado, H; Figl, M; Stock, M; Georg, D; Birkfellner, W

    2012-06-01

    In this work, we investigate the impact of using paired portal mega-voltage (MV) and kilo-voltage (kV) images, on 2D/3D registration accuracy with the purpose of improving tumor motion tracking during radiotherapy. Tumor motion tracking is important as motion remains one of the biggest sources of uncertainty in dose application. 2D/3D registration is successfully used in online tumor motion tracking, nevertheless, one limitation of this technique is the inability to resolve movement along the imaging beam axis using only one projection image. Our evaluation consisted in comparing the accuracy of registration using different 2D image combinations: only one 2D image (1-kV), one kV and one MV image (1kV-1MV) and two kV images (2-kV). For each of the image combinations we evaluated the registration results using 250 starting points as initial displacements from the gold standard. We measured the final mean target registration error (mTRE) and the success rate for each registration. Each of the combinations was evaluated using four different merit functions. When using the MI merit function (a popular choice for this application) the RMS mTRE drops from 6.4 mm when using only one image to 2.1 mm when using image pairs. The success rate increases from 62% to 99.6%. A similar trend was observed for all four merit functions. Typically, the results are slightly better with 2-kV images than with 1kV-1MV. We evaluated the impact of using different image combinations on accuracy of 2D/3D registration for tumor motion monitoring. Our results show that using a kV-MV image pair, leads to improved results as motion can be accurately resolved in six degrees of freedom. Given the possibility to acquire these two images simultaneously, this is not only very workflow efficient but is also shown to be a good approach to improve registration accuracy. © 2012 American Association of Physicists in Medicine.

  5. A minimalist approach to bias estimation for passive sensor measurements with targets of opportunity

    NASA Astrophysics Data System (ADS)

    Belfadel, Djedjiga; Osborne, Richard W.; Bar-Shalom, Yaakov

    2013-09-01

    In order to carry out data fusion, registration error correction is crucial in multisensor systems. This requires estimation of the sensor measurement biases. It is important to correct for these bias errors so that the multiple sensor measurements and/or tracks can be referenced as accurately as possible to a common tracking coordinate system. This paper provides a solution for bias estimation for the minimum number of passive sensors (two), when only targets of opportunity are available. The sensor measurements are assumed time-coincident (synchronous) and perfectly associated. Since these sensors provide only line of sight (LOS) measurements, the formation of a single composite Cartesian measurement obtained from fusing the LOS measurements from different sensors is needed to avoid the need for nonlinear filtering. We evaluate the Cramer-Rao Lower Bound (CRLB) on the covariance of the bias estimate, i.e., the quantification of the available information about the biases. Statistical tests on the results of simulations show that this method is statistically efficient, even for small sample sizes (as few as two sensors and six points on the trajectory of a single target of opportunity). We also show that the RMS position error is significantly improved with bias estimation compared with the target position estimation using the original biased measurements.

  6. Automatic Localization of Vertebral Levels in X-Ray Fluoroscopy Using 3D-2D Registration: A Tool to Reduce Wrong-Site Surgery

    PubMed Central

    Otake, Y.; Schafer, S.; Stayman, J. W.; Zbijewski, W.; Kleinszig, G.; Graumann, R.; Khanna, A. J.; Siewerdsen, J. H.

    2012-01-01

    Surgical targeting of the incorrect vertebral level (“wrong-level” surgery) is among the more common wrong-site surgical errors, attributed primarily to a lack of uniquely identifiable radiographic landmarks in the mid-thoracic spine. Conventional localization method involves manual counting of vertebral bodies under fluoroscopy, is prone to human error, and carries additional time and dose. We propose an image registration and visualization system (referred to as LevelCheck), for decision support in spine surgery by automatically labeling vertebral levels in fluoroscopy using a GPU-accelerated, intensity-based 3D-2D (viz., CT-to-fluoroscopy) registration. A gradient information (GI) similarity metric and CMA-ES optimizer were chosen due to their robustness and inherent suitability for parallelization. Simulation studies involved 10 patient CT datasets from which 50,000 simulated fluoroscopic images were generated from C-arm poses selected to approximate C-arm operator and positioning variability. Physical experiments used an anthropomorphic chest phantom imaged under real fluoroscopy. The registration accuracy was evaluated as the mean projection distance (mPD) between the estimated and true center of vertebral levels. Trials were defined as successful if the estimated position was within the projection of the vertebral body (viz., mPD < 5mm). Simulation studies showed a success rate of 99.998% (1 failure in 50,000 trials) and computation time of 4.7 sec on a midrange GPU. Analysis of failure modes identified cases of false local optima in the search space arising from longitudinal periodicity in vertebral structures. Physical experiments demonstrated robustness of the algorithm against quantum noise and x-ray scatter. The ability to automatically localize target anatomy in fluoroscopy in near-real-time could be valuable in reducing the occurrence of wrong-site surgery while helping to reduce radiation exposure. The method is applicable beyond the specific

  7. Deformable registration of the inflated and deflated lung in cone-beam CT-guided thoracic surgery: Initial investigation of a combined model- and image-driven approach

    PubMed Central

    Uneri, Ali; Nithiananthan, Sajendra; Schafer, Sebastian; Otake, Yoshito; Stayman, J. Webster; Kleinszig, Gerhard; Sussman, Marc S.; Prince, Jerry L.; Siewerdsen, Jeffrey H.

    2013-01-01

    Purpose: Surgical resection is the preferred modality for curative treatment of early stage lung cancer, but localization of small tumors (<10 mm diameter) during surgery presents a major challenge that is likely to increase as more early-stage disease is detected incidentally and in low-dose CT screening. To overcome the difficulty of manual localization (fingers inserted through intercostal ports) and the cost, logistics, and morbidity of preoperative tagging (coil or dye placement under CT-fluoroscopy), the authors propose the use of intraoperative cone-beam CT (CBCT) and deformable image registration to guide targeting of small tumors in video-assisted thoracic surgery (VATS). A novel algorithm is reported for registration of the lung from its inflated state (prior to pleural breach) to the deflated state (during resection) to localize surgical targets and adjacent critical anatomy. Methods: The registration approach geometrically resolves images of the inflated and deflated lung using a coarse model-driven stage followed by a finer image-driven stage. The model-driven stage uses image features derived from the lung surfaces and airways: triangular surface meshes are morphed to capture bulk motion; concurrently, the airways generate graph structures from which corresponding nodes are identified. Interpolation of the sparse motion fields computed from the bounding surface and interior airways provides a 3D motion field that coarsely registers the lung and initializes the subsequent image-driven stage. The image-driven stage employs an intensity-corrected, symmetric form of the Demons method. The algorithm was validated over 12 datasets, obtained from porcine specimen experiments emulating CBCT-guided VATS. Geometric accuracy was quantified in terms of target registration error (TRE) in anatomical targets throughout the lung, and normalized cross-correlation. Variations of the algorithm were investigated to study the behavior of the model- and image-driven stages

  8. Deformable registration of the inflated and deflated lung in cone-beam CT-guided thoracic surgery: initial investigation of a combined model- and image-driven approach.

    PubMed

    Uneri, Ali; Nithiananthan, Sajendra; Schafer, Sebastian; Otake, Yoshito; Stayman, J Webster; Kleinszig, Gerhard; Sussman, Marc S; Prince, Jerry L; Siewerdsen, Jeffrey H

    2013-01-01

    Surgical resection is the preferred modality for curative treatment of early stage lung cancer, but localization of small tumors (<10 mm diameter) during surgery presents a major challenge that is likely to increase as more early-stage disease is detected incidentally and in low-dose CT screening. To overcome the difficulty of manual localization (fingers inserted through intercostal ports) and the cost, logistics, and morbidity of preoperative tagging (coil or dye placement under CT-fluoroscopy), the authors propose the use of intraoperative cone-beam CT (CBCT) and deformable image registration to guide targeting of small tumors in video-assisted thoracic surgery (VATS). A novel algorithm is reported for registration of the lung from its inflated state (prior to pleural breach) to the deflated state (during resection) to localize surgical targets and adjacent critical anatomy. The registration approach geometrically resolves images of the inflated and deflated lung using a coarse model-driven stage followed by a finer image-driven stage. The model-driven stage uses image features derived from the lung surfaces and airways: triangular surface meshes are morphed to capture bulk motion; concurrently, the airways generate graph structures from which corresponding nodes are identified. Interpolation of the sparse motion fields computed from the bounding surface and interior airways provides a 3D motion field that coarsely registers the lung and initializes the subsequent image-driven stage. The image-driven stage employs an intensity-corrected, symmetric form of the Demons method. The algorithm was validated over 12 datasets, obtained from porcine specimen experiments emulating CBCT-guided VATS. Geometric accuracy was quantified in terms of target registration error (TRE) in anatomical targets throughout the lung, and normalized cross-correlation. Variations of the algorithm were investigated to study the behavior of the model- and image-driven stages by modifying

  9. An automated, quantitative, and case-specific evaluation of deformable image registration in computed tomography images

    NASA Astrophysics Data System (ADS)

    Kierkels, R. G. J.; den Otter, L. A.; Korevaar, E. W.; Langendijk, J. A.; van der Schaaf, A.; Knopf, A. C.; Sijtsema, N. M.

    2018-02-01

    A prerequisite for adaptive dose-tracking in radiotherapy is the assessment of the deformable image registration (DIR) quality. In this work, various metrics that quantify DIR uncertainties are investigated using realistic deformation fields of 26 head and neck and 12 lung cancer patients. Metrics related to the physiologically feasibility (the Jacobian determinant, harmonic energy (HE), and octahedral shear strain (OSS)) and numerically robustness of the deformation (the inverse consistency error (ICE), transitivity error (TE), and distance discordance metric (DDM)) were investigated. The deformable registrations were performed using a B-spline transformation model. The DIR error metrics were log-transformed and correlated (Pearson) against the log-transformed ground-truth error on a voxel level. Correlations of r  ⩾  0.5 were found for the DDM and HE. Given a DIR tolerance threshold of 2.0 mm and a negative predictive value of 0.90, the DDM and HE thresholds were 0.49 mm and 0.014, respectively. In conclusion, the log-transformed DDM and HE can be used to identify voxels at risk for large DIR errors with a large negative predictive value. The HE and/or DDM can therefore be used to perform automated quality assurance of each CT-based DIR for head and neck and lung cancer patients.

  10. Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin

    Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

  11. Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

    DOE PAGES

    Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin; ...

    2016-04-04

    Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

  12. Using direct mail to promote organ donor registration: Two campaigns and a meta-analysis.

    PubMed

    Feeley, Thomas H; Quick, Brian L; Lee, Seyoung

    2016-12-01

    Two direct mail campaigns were undertaken in Rochester and Buffalo, New York, with the goal of enrolling adults aged 50-64 years into the state organ and tissue donation electronic registry. Meta-analytic methods were used to summarize the body of research on the effects of direct mail marketing to promote organ donation registration. In the first study, 40 000 mailers were sent to targeted adults in Rochester, New York, and varied by brochure-only, letter-only, and letter plus brochure mailing conditions. A follow-up mailer using letter-only was sent to 20 000 individuals in Buffalo, New York area. In a second study, campaign results were combined with previously published direct mail campaigns in a random-effects meta-analysis. The overall registration rates were 1.6% and 4.6% for the Rochester and Buffalo campaigns, and the letter-only condition outperformed the brochure-only and letter plus brochure conditions in the Rochester area campaigns. Meta-analysis indicated a 3.3% registration rates across 15 campaigns and 329 137 targeted individuals. Registration rates were higher when targeting 18-year-olds and when direct mail letters were authored by officials affiliated with state departments. Use of direct mail to promote organ donor registration is an inexpensive method to increase enrollments in state registries. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  13. The influence of CT based attenuation correction on PET/CT registration: an evaluation study

    NASA Astrophysics Data System (ADS)

    Yaniv, Ziv; Wong, Kenneth H.; Banovac, Filip; Levy, Elliot; Cleary, Kevin

    2007-03-01

    We are currently developing a PET/CT based navigation system for guidance of biopsies and radiofrequency ablation (RFA) of early stage hepatic tumors. For these procedures, combined PET/CT data can potentially improve current interventions. The diagnostic efficacy of biopsies can potentially be improved by accurately targeting the region within the tumor that exhibits the highest metabolic activity. For RFA procedures the system can potentially enable treatment of early stage tumors, targeting tumors before structural abnormalities are clearly visible on CT. In both cases target definition is based on the metabolic data (PET), and navigation is based on the spatial data (CT), making the system highly dependent upon accurate spatial alignment between these data sets. In our institute all clinical data sets include three image volumes: one CT, and two PET volumes, with and without CT-based attenuation correction. This paper studies the effect of the CT-based attenuation correction on the registration process. From comparing the pairs of registrations from five data sets we observe that the point motion magnitude difference between registrations is on the same scale as the point motion magnitude in each one of the registrations, and that visual inspection cannot identify this discrepancy. We conclude that using non-rigid registration to align the PET and CT data sets is too variable, and most likely does not provide sufficient accuracy for interventional procedures.

  14. Comparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI using different models of contrast enhancement.

    PubMed

    Buonaccorsi, Giovanni A; Roberts, Caleb; Cheung, Sue; Watson, Yvonne; O'Connor, James P B; Davies, Karen; Jackson, Alan; Jayson, Gordon C; Parker, Geoff J M

    2006-09-01

    The quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data is subject to model fitting errors caused by motion during the time-series data acquisition. However, the time-varying features that occur as a result of contrast enhancement can confound motion correction techniques based on conventional registration similarity measures. We have therefore developed a heuristic, locally controlled tracer kinetic model-driven registration procedure, in which the model accounts for contrast enhancement, and applied it to the registration of abdominal DCE-MRI data at high temporal resolution. Using severely motion-corrupted data sets that had been excluded from analysis in a clinical trial of an antiangiogenic agent, we compared the results obtained when using different models to drive the tracer kinetic model-driven registration with those obtained when using a conventional registration against the time series mean image volume. Using tracer kinetic model-driven registration, it was possible to improve model fitting by reducing the sum of squared errors but the improvement was only realized when using a model that adequately described the features of the time series data. The registration against the time series mean significantly distorted the time series data, as did tracer kinetic model-driven registration using a simpler model of contrast enhancement. When an appropriate model is used, tracer kinetic model-driven registration influences motion-corrupted model fit parameter estimates and provides significant improvements in localization in three-dimensional parameter maps. This has positive implications for the use of quantitative DCE-MRI for example in clinical trials of antiangiogenic or antivascular agents.

  15. Automatic parameter selection for feature-based multi-sensor image registration

    NASA Astrophysics Data System (ADS)

    DelMarco, Stephen; Tom, Victor; Webb, Helen; Chao, Alan

    2006-05-01

    Accurate image registration is critical for applications such as precision targeting, geo-location, change-detection, surveillance, and remote sensing. However, the increasing volume of image data is exceeding the current capacity of human analysts to perform manual registration. This image data glut necessitates the development of automated approaches to image registration, including algorithm parameter value selection. Proper parameter value selection is crucial to the success of registration techniques. The appropriate algorithm parameters can be highly scene and sensor dependent. Therefore, robust algorithm parameter value selection approaches are a critical component of an end-to-end image registration algorithm. In previous work, we developed a general framework for multisensor image registration which includes feature-based registration approaches. In this work we examine the problem of automated parameter selection. We apply the automated parameter selection approach of Yitzhaky and Peli to select parameters for feature-based registration of multisensor image data. The approach consists of generating multiple feature-detected images by sweeping over parameter combinations and using these images to generate estimated ground truth. The feature-detected images are compared to the estimated ground truth images to generate ROC points associated with each parameter combination. We develop a strategy for selecting the optimal parameter set by choosing the parameter combination corresponding to the optimal ROC point. We present numerical results showing the effectiveness of the approach using registration of collected SAR data to reference EO data.

  16. Hyperbolic Harmonic Mapping for Surface Registration

    PubMed Central

    Shi, Rui; Zeng, Wei; Su, Zhengyu; Jiang, Jian; Damasio, Hanna; Lu, Zhonglin; Wang, Yalin; Yau, Shing-Tung; Gu, Xianfeng

    2016-01-01

    Automatic computation of surface correspondence via harmonic map is an active research field in computer vision, computer graphics and computational geometry. It may help document and understand physical and biological phenomena and also has broad applications in biometrics, medical imaging and motion capture inducstries. Although numerous studies have been devoted to harmonic map research, limited progress has been made to compute a diffeomorphic harmonic map on general topology surfaces with landmark constraints. This work conquers this problem by changing the Riemannian metric on the target surface to a hyperbolic metric so that the harmonic mapping is guaranteed to be a diffeomorphism under landmark constraints. The computational algorithms are based on Ricci flow and nonlinear heat diffusion methods. The approach is general and robust. We employ our algorithm to study the constrained surface registration problem which applies to both computer vision and medical imaging applications. Experimental results demonstrate that, by changing the Riemannian metric, the registrations are always diffeomorphic and achieve relatively high performance when evaluated with some popular surface registration evaluation standards. PMID:27187948

  17. Quantitative modeling of the accuracy in registering preoperative patient-specific anatomic models into left atrial cardiac ablation procedures

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rettmann, Maryam E., E-mail: rettmann.maryam@mayo.edu; Holmes, David R.; Camp, Jon J.

    2014-02-15

    Purpose: In cardiac ablation therapy, accurate anatomic guidance is necessary to create effective tissue lesions for elimination of left atrial fibrillation. While fluoroscopy, ultrasound, and electroanatomic maps are important guidance tools, they lack information regarding detailed patient anatomy which can be obtained from high resolution imaging techniques. For this reason, there has been significant effort in incorporating detailed, patient-specific models generated from preoperative imaging datasets into the procedure. Both clinical and animal studies have investigated registration and targeting accuracy when using preoperative models; however, the effect of various error sources on registration accuracy has not been quantitatively evaluated. Methods: Datamore » from phantom, canine, and patient studies are used to model and evaluate registration accuracy. In the phantom studies, data are collected using a magnetically tracked catheter on a static phantom model. Monte Carlo simulation studies were run to evaluate both baseline errors as well as the effect of different sources of error that would be present in a dynamicin vivo setting. Error is simulated by varying the variance parameters on the landmark fiducial, physical target, and surface point locations in the phantom simulation studies. In vivo validation studies were undertaken in six canines in which metal clips were placed in the left atrium to serve as ground truth points. A small clinical evaluation was completed in three patients. Landmark-based and combined landmark and surface-based registration algorithms were evaluated in all studies. In the phantom and canine studies, both target registration error and point-to-surface error are used to assess accuracy. In the patient studies, no ground truth is available and registration accuracy is quantified using point-to-surface error only. Results: The phantom simulation studies demonstrated that combined landmark and surface-based registration

  18. Error-related brain activity and error awareness in an error classification paradigm.

    PubMed

    Di Gregorio, Francesco; Steinhauser, Marco; Maier, Martin E

    2016-10-01

    Error-related brain activity has been linked to error detection enabling adaptive behavioral adjustments. However, it is still unclear which role error awareness plays in this process. Here, we show that the error-related negativity (Ne/ERN), an event-related potential reflecting early error monitoring, is dissociable from the degree of error awareness. Participants responded to a target while ignoring two different incongruent distractors. After responding, they indicated whether they had committed an error, and if so, whether they had responded to one or to the other distractor. This error classification paradigm allowed distinguishing partially aware errors, (i.e., errors that were noticed but misclassified) and fully aware errors (i.e., errors that were correctly classified). The Ne/ERN was larger for partially aware errors than for fully aware errors. Whereas this speaks against the idea that the Ne/ERN foreshadows the degree of error awareness, it confirms the prediction of a computational model, which relates the Ne/ERN to post-response conflict. This model predicts that stronger distractor processing - a prerequisite of error classification in our paradigm - leads to lower post-response conflict and thus a smaller Ne/ERN. This implies that the relationship between Ne/ERN and error awareness depends on how error awareness is related to response conflict in a specific task. Our results further indicate that the Ne/ERN but not the degree of error awareness determines adaptive performance adjustments. Taken together, we conclude that the Ne/ERN is dissociable from error awareness and foreshadows adaptive performance adjustments. Our results suggest that the relationship between the Ne/ERN and error awareness is correlative and mediated by response conflict. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Registration algorithm of point clouds based on multiscale normal features

    NASA Astrophysics Data System (ADS)

    Lu, Jun; Peng, Zhongtao; Su, Hang; Xia, GuiHua

    2015-01-01

    The point cloud registration technology for obtaining a three-dimensional digital model is widely applied in many areas. To improve the accuracy and speed of point cloud registration, a registration method based on multiscale normal vectors is proposed. The proposed registration method mainly includes three parts: the selection of key points, the calculation of feature descriptors, and the determining and optimization of correspondences. First, key points are selected from the point cloud based on the changes of magnitude of multiscale curvatures obtained by using principal components analysis. Then the feature descriptor of each key point is proposed, which consists of 21 elements based on multiscale normal vectors and curvatures. The correspondences in a pair of two point clouds are determined according to the descriptor's similarity of key points in the source point cloud and target point cloud. Correspondences are optimized by using a random sampling consistency algorithm and clustering technology. Finally, singular value decomposition is applied to optimized correspondences so that the rigid transformation matrix between two point clouds is obtained. Experimental results show that the proposed point cloud registration algorithm has a faster calculation speed, higher registration accuracy, and better antinoise performance.

  20. Prospective registration trends, reasons for retrospective registration and mechanisms to increase prospective registration compliance: descriptive analysis and survey.

    PubMed

    Hunter, Kylie Elizabeth; Seidler, Anna Lene; Askie, Lisa M

    2018-03-01

    To analyse prospective versus retrospective trial registration trends on the Australian New Zealand Clinical Trials Registry (ANZCTR) and to evaluate the reasons for non-compliance with prospective registration. Part 1: Descriptive analysis of trial registration trends from 2006 to 2015. Part 2: Online registrant survey. Part 1: All interventional trials registered on ANZCTR from 2006 to 2015. Part 2: Random sample of those who had retrospectively registered a trial on ANZCTR between 2010 and 2015. Part 1: Proportion of prospective versus retrospective clinical trial registrations (ie, registration before versus after enrolment of the first participant) on the ANZCTR overall and by various key metrics, such as sponsor, funder, recruitment country and sample size. Part 2: Reasons for non-compliance with prospective registration and perceived usefulness of various proposed mechanisms to improve prospective registration compliance. Part 1: Analysis of the complete dataset of 9450 trials revealed that compliance with prospective registration increased from 48% (216 out of 446 trials) in 2006 to 63% (723/1148) in 2012 and has since plateaued at around 64%. Patterns of compliance were relatively consistent across sponsor and funder types (industry vs non-industry), type of intervention (drug vs non-drug) and size of trial (n<100, 100-500, >500). However, primary sponsors from Australia/New Zealand were almost twice as likely to register prospectively (62%; 4613/7452) compared with sponsors from other countries with a WHO Network Registry (35%; 377/1084) or sponsors from countries without a WHO Registry (29%; 230/781). Part 2: The majority (56%; 84/149) of survey respondents cited lack of awareness as a reason for not registering their study prospectively. Seventy-four per cent (111/149) stated that linking registration to ethics approval would facilitate prospective registration. Despite some progress, compliance with prospective registration remains suboptimal. Linking

  1. Prospective registration trends, reasons for retrospective registration and mechanisms to increase prospective registration compliance: descriptive analysis and survey

    PubMed Central

    Seidler, Anna Lene; Askie, Lisa M

    2018-01-01

    Objectives To analyse prospective versus retrospective trial registration trends on the Australian New Zealand Clinical Trials Registry (ANZCTR) and to evaluate the reasons for non-compliance with prospective registration. Design Part 1: Descriptive analysis of trial registration trends from 2006 to 2015. Part 2: Online registrant survey. Participants Part 1: All interventional trials registered on ANZCTR from 2006 to 2015. Part 2: Random sample of those who had retrospectively registered a trial on ANZCTR between 2010 and 2015. Main outcome measures Part 1: Proportion of prospective versus retrospective clinical trial registrations (ie, registration before versus after enrolment of the first participant) on the ANZCTR overall and by various key metrics, such as sponsor, funder, recruitment country and sample size. Part 2: Reasons for non-compliance with prospective registration and perceived usefulness of various proposed mechanisms to improve prospective registration compliance. Results Part 1: Analysis of the complete dataset of 9450 trials revealed that compliance with prospective registration increased from 48% (216 out of 446 trials) in 2006 to 63% (723/1148) in 2012 and has since plateaued at around 64%. Patterns of compliance were relatively consistent across sponsor and funder types (industry vs non-industry), type of intervention (drug vs non-drug) and size of trial (n<100, 100–500, >500). However, primary sponsors from Australia/New Zealand were almost twice as likely to register prospectively (62%; 4613/7452) compared with sponsors from other countries with a WHO Network Registry (35%; 377/1084) or sponsors from countries without a WHO Registry (29%; 230/781). Part 2: The majority (56%; 84/149) of survey respondents cited lack of awareness as a reason for not registering their study prospectively. Seventy-four per cent (111/149) stated that linking registration to ethics approval would facilitate prospective registration. Conclusions Despite some

  2. 21 CFR 1301.35 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 223) to an applicant if... Federal Register. (c) The Certificate of Registration (DEA Form 223) shall contain the name, address, and...

  3. 21 CFR 1301.35 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 223) to an applicant if... Federal Register. (c) The Certificate of Registration (DEA Form 223) shall contain the name, address, and...

  4. MRI signal intensity based B-spline nonrigid registration for pre- and intraoperative imaging during prostate brachytherapy.

    PubMed

    Oguro, Sota; Tokuda, Junichi; Elhawary, Haytham; Haker, Steven; Kikinis, Ron; Tempany, Clare M C; Hata, Nobuhiko

    2009-11-01

    To apply an intensity-based nonrigid registration algorithm to MRI-guided prostate brachytherapy clinical data and to assess its accuracy. A nonrigid registration of preoperative MRI to intraoperative MRI images was carried out in 16 cases using a Basis-Spline algorithm in a retrospective manner. The registration was assessed qualitatively by experts' visual inspection and quantitatively by measuring the Dice similarity coefficient (DSC) for total gland (TG), central gland (CG), and peripheral zone (PZ), the mutual information (MI) metric, and the fiducial registration error (FRE) between corresponding anatomical landmarks for both the nonrigid and a rigid registration method. All 16 cases were successfully registered in less than 5 min. After the nonrigid registration, DSC values for TG, CG, PZ were 0.91, 0.89, 0.79, respectively, the MI metric was -0.19 +/- 0.07 and FRE presented a value of 2.3 +/- 1.8 mm. All the metrics were significantly better than in the case of rigid registration, as determined by one-sided t-tests. The intensity-based nonrigid registration method using clinical data was demonstrated to be feasible and showed statistically improved metrics when compare to only rigid registration. The method is a valuable tool to integrate pre- and intraoperative images for brachytherapy.

  5. 21 CFR 1309.42 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ...; denial of registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 511) to..., shall hold a hearing on the application pursuant to § 1309.51. (b) The Certificate of Registration (DEA...

  6. 21 CFR 1309.42 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ...; denial of registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 511) to..., shall hold a hearing on the application pursuant to § 1309.51. (b) The Certificate of Registration (DEA...

  7. Registration of angiographic image on real-time fluoroscopic image for image-guided percutaneous coronary intervention.

    PubMed

    Kim, Dongkue; Park, Sangsoo; Jeong, Myung Ho; Ryu, Jeha

    2018-02-01

    In percutaneous coronary intervention (PCI), cardiologists must study two different X-ray image sources: a fluoroscopic image and an angiogram. Manipulating a guidewire while alternately monitoring the two separate images on separate screens requires a deep understanding of the anatomy of coronary vessels and substantial training. We propose 2D/2D spatiotemporal image registration of the two images in a single image in order to provide cardiologists with enhanced visual guidance in PCI. The proposed 2D/2D spatiotemporal registration method uses a cross-correlation of two ECG series in each image to temporally synchronize two separate images and register an angiographic image onto the fluoroscopic image. A guidewire centerline is then extracted from the fluoroscopic image in real time, and the alignment of the centerline with vessel outlines of the chosen angiographic image is optimized using the iterative closest point algorithm for spatial registration. A proof-of-concept evaluation with a phantom coronary vessel model with engineering students showed an error reduction rate greater than 74% on wrong insertion to nontarget branches compared to the non-registration method and more than 47% reduction in the task completion time in performing guidewire manipulation for very difficult tasks. Evaluation with a small number of experienced doctors shows a potentially significant reduction in both task completion time and error rate for difficult tasks. The total registration time with real procedure X-ray (angiographic and fluoroscopic) images takes [Formula: see text] 60 ms, which is within the fluoroscopic image acquisition rate of 15 Hz. By providing cardiologists with better visual guidance in PCI, the proposed spatiotemporal image registration method is shown to be useful in advancing the guidewire to the coronary vessel branches, especially those difficult to insert into.

  8. Development and evaluation of an articulated registration algorithm for human skeleton registration

    NASA Astrophysics Data System (ADS)

    Yip, Stephen; Perk, Timothy; Jeraj, Robert

    2014-03-01

    Accurate registration over multiple scans is necessary to assess treatment response of bone diseases (e.g. metastatic bone lesions). This study aimed to develop and evaluate an articulated registration algorithm for the whole-body skeleton registration in human patients. In articulated registration, whole-body skeletons are registered by auto-segmenting into individual bones using atlas-based segmentation, and then rigidly aligning them. Sixteen patients (weight = 80-117 kg, height = 168-191 cm) with advanced prostate cancer underwent the pre- and mid-treatment PET/CT scans over a course of cancer therapy. Skeletons were extracted from the CT images by thresholding (HU>150). Skeletons were registered using the articulated, rigid, and deformable registration algorithms to account for position and postural variability between scans. The inter-observers agreement in the atlas creation, the agreement between the manually and atlas-based segmented bones, and the registration performances of all three registration algorithms were all assessed using the Dice similarity index—DSIobserved, DSIatlas, and DSIregister. Hausdorff distance (dHausdorff) of the registered skeletons was also used for registration evaluation. Nearly negligible inter-observers variability was found in the bone atlases creation as the DSIobserver was 96 ± 2%. Atlas-based and manual segmented bones were in excellent agreement with DSIatlas of 90 ± 3%. Articulated (DSIregsiter = 75 ± 2%, dHausdorff = 0.37 ± 0.08 cm) and deformable registration algorithms (DSIregister = 77 ± 3%, dHausdorff = 0.34 ± 0.08 cm) considerably outperformed the rigid registration algorithm (DSIregsiter = 59 ± 9%, dHausdorff = 0.69 ± 0.20 cm) in the skeleton registration as the rigid registration algorithm failed to capture the skeleton flexibility in the joints. Despite superior skeleton registration performance, deformable registration algorithm failed to preserve the local rigidity of bones as over 60% of the

  9. SU-E-J-91: Biomechanical Deformable Image Registration of Longitudinal Lung CT Images

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Cazoulat, G; Owen, D; Matuszak, M

    2015-06-15

    Purpose: Spatial correlation of lung tissue across longitudinal images, as the patient responds to treatment, is a critical step in adaptive radiotherapy. The goal of this work is to expand a biomechanical model-based deformable registration algorithm (Morfeus) to achieve accurate registration in the presence of significant anatomical changes. Methods: Four lung cancer patients previously treated with conventionally fractionated radiotherapy that exhibited notable tumor shrinkage during treatment were retrospectively evaluated. Exhale breathhold CT scans were obtained at treatment planning (PCT) and following three weeks (W3CT) of treatment. For each patient, the PCT was registered to the W3CT using Morfeus, a biomechanicalmore » model-based deformable registration algorithm, consisting of boundary conditions on the lungs and incorporating a sliding interface between the lung and chest wall. To model the complex response of the lung, an extension to Morfeus has been developed: (i) The vessel tree was segmented by thresholding a vesselness image based on the Hessian matrix’s eigenvalues and the centerline was extracted; (ii) A 3D shape context method was used to find correspondences between the trees of the two images; (ii) Correspondences were used as additional boundary conditions (Morfeus+vBC). An expert independently identified corresponding landmarks well distributed in the lung to compute Target Registration Errors (TRE). Results: The TRE within 15mm of the tumor boundaries (on average 11 landmarks) is: 6.1±1.8, 4.6±1.1 and 3.8±2.3 mm after rigid registration, Morfeus and Morfeus+vBC, respectively. The TRE in the rest of the lung (on average 13 landmarks) is: 6.4±3.9, 4.7±2.2 and 3.6±1.9 mm, which is on the order of the 2mm isotropic dose grid vector (3.5mm). Conclusion: The addition of boundary conditions on the vessels improved the accuracy in modeling the response of the lung and tumor over the course of radiotherapy. Minimizing and modeling these

  10. Radiographic and anatomic basis for prostate contouring errors and methods to improve prostate contouring accuracy.

    PubMed

    McLaughlin, Patrick W; Evans, Cheryl; Feng, Mary; Narayana, Vrinda

    2010-02-01

    Use of highly conformal radiation for prostate cancer can lead to both overtreatment of surrounding normal tissues and undertreatment of the prostate itself. In this retrospective study we analyzed the radiographic and anatomic basis of common errors in computed tomography (CT) contouring and suggest methods to correct them. Three hundred patients with prostate cancer underwent CT and magnetic resonance imaging (MRI). The prostate was delineated independently on the data sets. CT and MRI contours were compared by use of deformable registration. Errors in target delineation were analyzed and methods to avoid such errors detailed. Contouring errors were identified at the prostatic apex, mid gland, and base on CT. At the apex, the genitourinary diaphragm, rectum, and anterior fascia contribute to overestimation. At the mid prostate, the anterior and lateral fasciae contribute to overestimation. At the base, the bladder and anterior fascia contribute to anterior overestimation. Transition zone hypertrophy and bladder neck variability contribute to errors of overestimation and underestimation at the superior base, whereas variable prostate-to-seminal vesicle relationships with prostate hypertrophy contribute to contouring errors at the posterior base. Most CT contouring errors can be detected by (1) inspection of a lateral view of prostate contours to detect projection from the expected globular form and (2) recognition of anatomic structures (genitourinary diaphragm) on the CT scans that are clearly visible on MRI. This study shows that many CT prostate contouring errors can be improved without direct incorporation of MRI data. Copyright 2010 Elsevier Inc. All rights reserved.

  11. Effective 2D-3D medical image registration using Support Vector Machine.

    PubMed

    Qi, Wenyuan; Gu, Lixu; Zhao, Qiang

    2008-01-01

    Registration of pre-operative 3D volume dataset and intra-operative 2D images gradually becomes an important technique to assist radiologists in diagnosing complicated diseases easily and quickly. In this paper, we proposed a novel 2D/3D registration framework based on Support Vector Machine (SVM) to compensate the disadvantages of generating large number of DRR images in the stage of intra-operation. Estimated similarity metric distribution could be built up from the relationship between parameters of transform and prior sparse target metric values by means of SVR method. Based on which, global optimal parameters of transform are finally searched out by an optimizer in order to guide 3D volume dataset to match intra-operative 2D image. Experiments reveal that our proposed registration method improved performance compared to conventional registration method and also provided a precise registration result efficiently.

  12. Comparison of manual and automatic MR-CT registration for radiotherapy of prostate cancer.

    PubMed

    Korsager, Anne Sofie; Carl, Jesper; Riis Østergaard, Lasse

    2016-05-08

    In image-guided radiotherapy (IGRT) of prostate cancer, delineation of the clini-cal target volume (CTV) often relies on magnetic resonance (MR) because of its good soft-tissue visualization. Registration of MR and computed tomography (CT) is required in order to add this accurate delineation to the dose planning CT. An automatic approach for local MR-CT registration of the prostate has previously been developed using a voxel property-based registration as an alternative to a manual landmark-based registration. The aim of this study is to compare the two registration approaches and to investigate the clinical potential for replacing the manual registration with the automatic registration. Registrations and analysis were performed for 30 prostate cancer patients treated with IGRT using a Ni-Ti prostate stent as a fiducial marker. The comparison included computing translational and rotational differences between the approaches, visual inspection, and computing the overlap of the CTV. The computed mean translational difference was 1.65, 1.60, and 1.80mm and the computed mean rotational difference was 1.51°, 3.93°, and 2.09° in the superior/inferior, anterior/posterior, and medial/lateral direction, respectively. The sensitivity of overlap was 87%. The results demonstrate that the automatic registration approach performs registrations comparable to the manual registration.

  13. Relative range error evaluation of terrestrial laser scanners using a plate, a sphere, and a novel dual-sphere-plate target.

    PubMed

    Muralikrishnan, Bala; Rachakonda, Prem; Lee, Vincent; Shilling, Meghan; Sawyer, Daniel; Cheok, Geraldine; Cournoyer, Luc

    2017-12-01

    Terrestrial laser scanners (TLS) are a class of 3D imaging systems that produce a 3D point cloud by measuring the range and two angles to a point. The fundamental measurement of a TLS is range. Relative range error is one component of the overall range error of TLS and its estimation is therefore an important aspect in establishing metrological traceability of measurements performed using these systems. Target geometry is an important aspect to consider when realizing the relative range tests. The recently published ASTM E2938-15 mandates the use of a plate target for the relative range tests. While a plate target may reasonably be expected to produce distortion free data even at far distances, the target itself needs careful alignment at each of the relative range test positions. In this paper, we discuss relative range experiments performed using a plate target and then address the advantages and limitations of using a sphere target. We then present a novel dual-sphere-plate target that draws from the advantages of the sphere and the plate without the associated limitations. The spheres in the dual-sphere-plate target are used simply as fiducials to identify a point on the surface of the plate that is common to both the scanner and the reference instrument, thus overcoming the need to carefully align the target.

  14. Automatic Registration of Terrestrial Laser Scanner Point Clouds Using Natural Planar Surfaces

    NASA Astrophysics Data System (ADS)

    Theiler, P. W.; Schindler, K.

    2012-07-01

    Terrestrial laser scanners have become a standard piece of surveying equipment, used in diverse fields like geomatics, manufacturing and medicine. However, the processing of today's large point clouds is time-consuming, cumbersome and not automated enough. A basic step of post-processing is the registration of scans from different viewpoints. At present this is still done using artificial targets or tie points, mostly by manual clicking. The aim of this registration step is a coarse alignment, which can then be improved with the existing algorithm for fine registration. The focus of this paper is to provide such a coarse registration in a fully automatic fashion, and without placing any target objects in the scene. The basic idea is to use virtual tie points generated by intersecting planar surfaces in the scene. Such planes are detected in the data with RANSAC and optimally fitted using least squares estimation. Due to the huge amount of recorded points, planes can be determined very accurately, resulting in well-defined tie points. Given two sets of potential tie points recovered in two different scans, registration is performed by searching for the assignment which preserves the geometric configuration of the largest possible subset of all tie points. Since exhaustive search over all possible assignments is intractable even for moderate numbers of points, the search is guided by matching individual pairs of tie points with the help of a novel descriptor based on the properties of a point's parent planes. Experiments show that the proposed method is able to successfully coarse register TLS point clouds without the need for artificial targets.

  15. Extra-dimensional Demons: A method for incorporating missing tissue in deformable image registration

    PubMed Central

    Nithiananthan, Sajendra; Schafer, Sebastian; Mirota, Daniel J.; Stayman, J. Webster; Zbijewski, Wojciech; Reh, Douglas D.; Gallia, Gary L.; Siewerdsen, Jeffrey H.

    2012-01-01

    revealed major differences: the conventional Demons approach imparted unrealistic distortions in areas around tissue excision, whereas XDD provided accurate “ejection” of voxels within the excision site and maintained the registration accuracy throughout the rest of the image. Registration accuracy in areas far from the excision site (e.g., > ∼5 mm) was identical for the two approaches. Quantitation of the effect was consistent in analysis of NMI, normalized cross-correlation (NCC), target registration error (TRE), and accuracy of voxels ejected from the volume (true-positive and false-positive analysis). The registration accuracy for conventional Demons was found to degrade steeply as a function of excision size, whereas XDD was robust in this regard. Cadaver studies involving realistic excision of the clivus, vidian canal, and ethmoid sinuses demonstrated similar results, with unrealistic distortion of anatomy imparted by conventional Demons and accurate ejection and deformation for XDD. Conclusions: Adaptation of the Demons deformable registration process to include segmentation (i.e., identification of excised tissue) and an extra dimension in the deformation field provided a means to accurately accommodate missing tissue between image acquisitions. The extra-dimensional approach yielded accurate “ejection” of voxels local to the excision site while preserving the registration accuracy (typically subvoxel) of the conventional Demons approach throughout the rest of the image. The ability to accommodate missing tissue volumes is important to application of CBCT for surgical guidance (e.g., skull base drillout) and may have application in other areas of CBCT guidance. PMID:22957637

  16. Fast elastic registration of soft tissues under large deformations.

    PubMed

    Peterlík, Igor; Courtecuisse, Hadrien; Rohling, Robert; Abolmaesumi, Purang; Nguan, Christopher; Cotin, Stéphane; Salcudean, Septimiu

    2018-04-01

    A fast and accurate fusion of intra-operative images with a pre-operative data is a key component of computer-aided interventions which aim at improving the outcomes of the intervention while reducing the patient's discomfort. In this paper, we focus on the problematic of the intra-operative navigation during abdominal surgery, which requires an accurate registration of tissues undergoing large deformations. Such a scenario occurs in the case of partial hepatectomy: to facilitate the access to the pathology, e.g. a tumor located in the posterior part of the right lobe, the surgery is performed on a patient in lateral position. Due to the change in patient's position, the resection plan based on the pre-operative CT scan acquired in the supine position must be updated to account for the deformations. We suppose that an imaging modality, such as the cone-beam CT, provides the information about the intra-operative shape of an organ, however, due to the reduced radiation dose and contrast, the actual locations of the internal structures necessary to update the planning are not available. To this end, we propose a method allowing for fast registration of the pre-operative data represented by a detailed 3D model of the liver and its internal structure and the actual configuration given by the organ surface extracted from the intra-operative image. The algorithm behind the method combines the iterative closest point technique with a biomechanical model based on a co-rotational formulation of linear elasticity which accounts for large deformations of the tissue. The performance, robustness and accuracy of the method is quantitatively assessed on a control semi-synthetic dataset with known ground truth and a real dataset composed of nine pairs of abdominal CT scans acquired in supine and flank positions. It is shown that the proposed surface-matching method is capable of reducing the target registration error evaluated of the internal structures of the organ from more than

  17. Accurate tracking of tumor volume change during radiotherapy by CT-CBCT registration with intensity correction

    NASA Astrophysics Data System (ADS)

    Park, Seyoun; Robinson, Adam; Quon, Harry; Kiess, Ana P.; Shen, Colette; Wong, John; Plishker, William; Shekhar, Raj; Lee, Junghoon

    2016-03-01

    In this paper, we propose a CT-CBCT registration method to accurately predict the tumor volume change based on daily cone-beam CTs (CBCTs) during radiotherapy. CBCT is commonly used to reduce patient setup error during radiotherapy, but its poor image quality impedes accurate monitoring of anatomical changes. Although physician's contours drawn on the planning CT can be automatically propagated to daily CBCTs by deformable image registration (DIR), artifacts in CBCT often cause undesirable errors. To improve the accuracy of the registration-based segmentation, we developed a DIR method that iteratively corrects CBCT intensities by local histogram matching. Three popular DIR algorithms (B-spline, demons, and optical flow) with the intensity correction were implemented on a graphics processing unit for efficient computation. We evaluated their performances on six head and neck (HN) cancer cases. For each case, four trained scientists manually contoured the nodal gross tumor volume (GTV) on the planning CT and every other fraction CBCTs to which the propagated GTV contours by DIR were compared. The performance was also compared with commercial image registration software based on conventional mutual information (MI), VelocityAI (Varian Medical Systems Inc.). The volume differences (mean±std in cc) between the average of the manual segmentations and automatic segmentations are 3.70+/-2.30 (B-spline), 1.25+/-1.78 (demons), 0.93+/-1.14 (optical flow), and 4.39+/-3.86 (VelocityAI). The proposed method significantly reduced the estimation error by 9% (B-spline), 38% (demons), and 51% (optical flow) over the results using VelocityAI. Although demonstrated only on HN nodal GTVs, the results imply that the proposed method can produce improved segmentation of other critical structures over conventional methods.

  18. Poster - Thurs Eve-12: A needle-positioning robot co-registered with volumetric x-ray micro-computed tomography images for minimally-invasive small-animal interventions.

    PubMed

    Waspe, A C; Holdsworth, D W; Lacefield, J C; Fenster, A

    2008-07-01

    Preclinical research protocols often require the delivery of biological substances to specific targets in small animal disease models. To target biologically relevant locations in mice accurately, the needle positioning error needs to be < 200 μm. If targeting is inaccurate, experimental results can be inconclusive or misleading. We have developed a robotic manipulator that is capable of positioning a needle with a mean error < 100 μm. An apparatus and method were developed for integrating the needle-positioning robot with volumetric micro-computed tomography image guidance for interventions in small animals. Accurate image-to-robot registration is critical for integration as it enables targets identified in the image to be mapped to physical coordinates inside the animal. Registration is accomplished by injecting barium sulphate into needle tracks as the robot withdraws the needle from target points in a tissue-mimicking phantom. Registration accuracy is therefore affected by the positioning error of the robot and is assessed by measuring the point-to-line fiducial and target registration errors (FRE, TRE). Centroid points along cross-sectional slices of the track are determined using region growing segmentation followed by application of a center-of-mass algorithm. The centerline points are registered to needle trajectories in robot coordinates by applying an iterative closest point algorithm between points and lines. Implementing this procedure with four fiducial needle tracks produced a point-to-line FRE and TRE of 246 ± 58 μm and 194 ± 18 μm, respectively. The proposed registration technique produced a TRE < 200 μm, in the presence of robot positioning error, meeting design specification. © 2008 American Association of Physicists in Medicine.

  19. A framework for automatic creation of gold-standard rigid 3D-2D registration datasets.

    PubMed

    Madan, Hennadii; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga

    2017-02-01

    Advanced image-guided medical procedures incorporate 2D intra-interventional information into pre-interventional 3D image and plan of the procedure through 3D/2D image registration (32R). To enter clinical use, and even for publication purposes, novel and existing 32R methods have to be rigorously validated. The performance of a 32R method can be estimated by comparing it to an accurate reference or gold standard method (usually based on fiducial markers) on the same set of images (gold standard dataset). Objective validation and comparison of methods are possible only if evaluation methodology is standardized, and the gold standard  dataset is made publicly available. Currently, very few such datasets exist and only one contains images of multiple patients acquired during a procedure. To encourage the creation of gold standard 32R datasets, we propose an automatic framework. The framework is based on rigid registration of fiducial markers. The main novelty is spatial grouping of fiducial markers on the carrier device, which enables automatic marker localization and identification across the 3D and 2D images. The proposed framework was demonstrated on clinical angiograms of 20 patients. Rigid 32R computed by the framework was more accurate than that obtained manually, with the respective target registration error below 0.027 mm compared to 0.040 mm. The framework is applicable for gold standard setup on any rigid anatomy, provided that the acquired images contain spatially grouped fiducial markers. The gold standard datasets and software will be made publicly available.

  20. Deformable 3D-2D registration for guiding K-wire placement in pelvic trauma surgery

    NASA Astrophysics Data System (ADS)

    Goerres, J.; Jacobson, M.; Uneri, A.; de Silva, T.; Ketcha, M.; Reaungamornrat, S.; Vogt, S.; Kleinszig, G.; Wolinsky, J.-P.; Osgood, G.; Siewerdsen, J. H.

    2017-03-01

    Pelvic Kirschner wire (K-wire) insertion is a challenging surgical task requiring interpretation of complex 3D anatomical shape from 2D projections (fluoroscopy) and delivery of device trajectories within fairly narrow bone corridors in proximity to adjacent nerves and vessels. Over long trajectories ( 10-25 cm), K-wires tend to curve (deform), making conventional rigid navigation inaccurate at the tip location. A system is presented that provides accurate 3D localization and guidance of rigid or deformable surgical devices ("components" - e.g., K-wires) based on 3D-2D registration. The patient is registered to a preoperative CT image by virtually projecting digitally reconstructed radiographs (DRRs) and matching to two or more intraoperative x-ray projections. The K-wire is localized using an analogous procedure matching DRRs of a deformably parametrized model for the device component (deformable known-component registration, or dKC-Reg). A cadaver study was performed in which a K-wire trajectory was delivered in the pelvis. The system demonstrated target registration error (TRE) of 2.1 ± 0.3 mm in location of the K-wire tip (median ± interquartile range, IQR) and 0.8 ± 1.4º in orientation at the tip (median ± IQR), providing functionality analogous to surgical tracking / navigation using imaging systems already in the surgical arsenal without reliance on a surgical tracker. The method offers quantitative 3D guidance using images (e.g., inlet / outlet views) already acquired in the standard of care, potentially extending the advantages of navigation to broader utilization in trauma surgery to improve surgical precision and safety.

  1. Assessment of Thematic Mapper Band-to-band Registration by the Block Correlation Method

    NASA Technical Reports Server (NTRS)

    Card, D. H.; Wrigley, R. C.; Mertz, F. C.; Hall, J. R.

    1984-01-01

    The design of the Thematic Mapper (TM) multispectral radiometer makes it susceptible to band-to-band misregistration. To estimate band-to-band misregistration a block correlation method is employed. This method is chosen over other possible techniques (band differencing and flickering) because quantitative results are produced. The method correlates rectangular blocks of pixels from one band against blocks centered on identical pixels from a second band. The block pairs are shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient for each shift position is computed. The displacement corresponding to the maximum correlation is taken as the best estimate of registration error for each block pair. Subpixel shifts are estimated by a bi-quadratic interpolation of the correlation values surrounding the maximum correlation. To obtain statistical summaries for each band combination post processing of the block correlation results performed. The method results in estimates of registration error that are consistent with expectations.

  2. Closing the loop of the medication use process using electronic medication administration registration.

    PubMed

    Lenderink, Bertil W; Egberts, Toine C G

    2004-08-01

    Recent reports and studies of errors in the medication process have raised the awareness of the threat to public health. An essential step in this multi-stage process is the actual administration of a medicine to the patient. The closed loop system is thought to be a way of preventing medication errors. Current information technology can facilitate this process. This article describes the way barcode technology is being used to facilitate medication administration registration on several wards in our hospital and nursing home.

  3. Optimization of real-time rigid registration motion compensation for prostate biopsies using 2D/3D ultrasound

    NASA Astrophysics Data System (ADS)

    Gillies, Derek J.; Gardi, Lori; Zhao, Ren; Fenster, Aaron

    2017-03-01

    During image-guided prostate biopsy, needles are targeted at suspicious tissues to obtain specimens that are later examined histologically for cancer. Patient motion causes inaccuracies when using MR-transrectal ultrasound (TRUS) image fusion approaches used to augment the conventional biopsy procedure. Motion compensation using a single, user initiated correction can be performed to temporarily compensate for prostate motion, but a real-time continuous registration offers an improvement to clinical workflow by reducing user interaction and procedure time. An automatic motion compensation method, approaching the frame rate of a TRUS-guided system, has been developed for use during fusion-based prostate biopsy to improve image guidance. 2D and 3D TRUS images of a prostate phantom were registered using an intensity based algorithm utilizing normalized cross-correlation and Powell's method for optimization with user initiated and continuous registration techniques. The user initiated correction performed with observed computation times of 78 ± 35 ms, 74 ± 28 ms, and 113 ± 49 ms for in-plane, out-of-plane, and roll motions, respectively, corresponding to errors of 0.5 ± 0.5 mm, 1.5 ± 1.4 mm, and 1.5 ± 1.6°. The continuous correction performed significantly faster (p < 0.05) than the user initiated method, with observed computation times of 31 ± 4 ms, 32 ± 4 ms, and 31 ± 6 ms for in-plane, out-of-plane, and roll motions, respectively, corresponding to errors of 0.2 ± 0.2 mm, 0.6 ± 0.5 mm, and 0.8 ± 0.4°.

  4. SU-F-J-88: Comparison of Two Deformable Image Registration Algorithms for CT-To-CT Contour Propagation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Gopal, A; Xu, H; Chen, S

    Purpose: To compare the contour propagation accuracy of two deformable image registration (DIR) algorithms in the Raystation treatment planning system – the “Hybrid” algorithm based on image intensities and anatomical information; and the “Biomechanical” algorithm based on linear anatomical elasticity and finite element modeling. Methods: Both DIR algorithms were used for CT-to-CT deformation for 20 lung radiation therapy patients that underwent treatment plan revisions. Deformation accuracy was evaluated using landmark tracking to measure the target registration error (TRE) and inverse consistency error (ICE). The deformed contours were also evaluated against physician drawn contours using Dice similarity coefficients (DSC). Contour propagationmore » was qualitatively assessed using a visual quality score assigned by physicians, and a refinement quality score (0 0.9 for lungs, > 0.85 for heart, > 0.8 for liver) and similar qualitative assessments (VQS < 0.35, RQS > 0.75 for lungs). When anatomical structures were used to control the deformation, the DSC improved more significantly for the biomechanical DIR compared to the hybrid DIR, while the VQS and RQS improved only for the controlling structures. However, while the inclusion of controlling structures improved the TRE for the hybrid DIR, it increased the TRE for the biomechanical DIR. Conclusion: The hybrid DIR was found to perform slightly better than the biomechanical DIR based on lower TRE while the DSC, VQS, and RQS studies yielded comparable results for both. The use of controlling structures showed considerable improvement in the hybrid DIR results and is recommended for clinical use in contour propagation.« less

  5. Registration and Marking Requirements for UAS. Unmanned Aircraft System (UAS) Registration

    NASA Technical Reports Server (NTRS)

    2005-01-01

    The registration of an aircraft is a prerequisite for issuance of a U.S. certificate of airworthiness by the FAA. The procedures and requirements for aircraft registration, and the subsequent issuance of registration numbers, are contained in FAR Part 47. However, the process/method(s) for applying the requirements of Parts 45 & 47 to Unmanned Aircraft Systems (UAS) has not been defined. This task resolved the application of 14 CFR Parts 45 and 47 to UAS. Key Findings: UAS are aircraft systems and as such the recommended approach to registration is to follow the same process for registration as manned aircraft. This will require manufacturers to comply with the requirements for 14 CFR 47, Aircraft Registration and 14 CFR 45, Identification and Registration Marking. In addition, only the UA should be identified with the N number registration markings. There should also be a documentation link showing the applicability of the control station and communication link to the UA. The documentation link can be in the form of a Type Certificate Data Sheet (TCDS) entry or a UAS logbook entry. The recommended process for the registration of UAS is similar to the manned aircraft process and is outlined in a 6-step process in the paper.

  6. An accuracy assessment of different rigid body image registration methods and robotic couch positional corrections using a novel phantom

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Arumugam, Sankar; Xing Aitang; Jameson, Michael G.

    2013-03-15

    Purpose: Image guided radiotherapy (IGRT) using cone beam computed tomography (CBCT) images greatly reduces interfractional patient positional uncertainties. An understanding of uncertainties in the IGRT process itself is essential to ensure appropriate use of this technology. The purpose of this study was to develop a phantom capable of assessing the accuracy of IGRT hardware and software including a 6 degrees of freedom patient positioning system and to investigate the accuracy of the Elekta XVI system in combination with the HexaPOD robotic treatment couch top. Methods: The constructed phantom enabled verification of the three automatic rigid body registrations (gray value, bone,more » seed) available in the Elekta XVI software and includes an adjustable mount that introduces known rotational offsets to the phantom from its reference position. Repeated positioning of the phantom was undertaken to assess phantom rotational accuracy. Using this phantom the accuracy of the XVI registration algorithms was assessed considering CBCT hardware factors and image resolution together with the residual error in the overall image guidance process when positional corrections were performed through the HexaPOD couch system. Results: The phantom positioning was found to be within 0.04 ({sigma}= 0.12) Degree-Sign , 0.02 ({sigma}= 0.13) Degree-Sign , and -0.03 ({sigma}= 0.06) Degree-Sign in X, Y, and Z directions, respectively, enabling assessment of IGRT with a 6 degrees of freedom patient positioning system. The gray value registration algorithm showed the least error in calculated offsets with maximum mean difference of -0.2({sigma}= 0.4) mm in translational and -0.1({sigma}= 0.1) Degree-Sign in rotational directions for all image resolutions. Bone and seed registration were found to be sensitive to CBCT image resolution. Seed registration was found to be most sensitive demonstrating a maximum mean error of -0.3({sigma}= 0.9) mm and -1.4({sigma}= 1.7) Degree-Sign in

  7. FMRI 3D registration based on Fourier space subsets using neural networks.

    PubMed

    Freire, Luis C; Gouveia, Ana R; Godinho, Fernando M

    2010-01-01

    In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

  8. 3D/2D image registration using weighted histogram of gradient directions

    NASA Astrophysics Data System (ADS)

    Ghafurian, Soheil; Hacihaliloglu, Ilker; Metaxas, Dimitris N.; Tan, Virak; Li, Kang

    2015-03-01

    Three dimensional (3D) to two dimensional (2D) image registration is crucial in many medical applications such as image-guided evaluation of musculoskeletal disorders. One of the key problems is to estimate the 3D CT- reconstructed bone model positions (translation and rotation) which maximize the similarity between the digitally reconstructed radiographs (DRRs) and the 2D fluoroscopic images using a registration method. This problem is computational-intensive due to a large search space and the complicated DRR generation process. Also, finding a similarity measure which converges to the global optimum instead of local optima adds to the challenge. To circumvent these issues, most existing registration methods need a manual initialization, which requires user interaction and is prone to human error. In this paper, we introduce a novel feature-based registration method using the weighted histogram of gradient directions of images. This method simplifies the computation by searching the parameter space (rotation and translation) sequentially rather than simultaneously. In our numeric simulation experiments, the proposed registration algorithm was able to achieve sub-millimeter and sub-degree accuracies. Moreover, our method is robust to the initial guess. It can tolerate up to +/-90°rotation offset from the global optimal solution, which minimizes the need for human interaction to initialize the algorithm.

  9. Using manual prostate contours to enhance deformable registration of endorectal MRI.

    PubMed

    Cheung, M R; Krishnan, K

    2012-10-01

    Endorectal MRI provides detailed images of the prostate anatomy and is useful for radiation treatment planning. Here we describe a Demons field-initialized B-spline deformable registration of prostate MRI. T2-weighted endorectal MRIs of five patients were used. The prostate and the tumor of each patient were manually contoured. The planning MRIs and their segmentations were simulated by warping the corresponding endorectal MRIs using thin plate spline (TPS). Deformable registration was initialized using the deformation field generated using Demons algorithm to map the deformed prostate MRI to the non-deformed one. The solution was refined with B-Spline registration. Volume overlap similarity was used to assess the accuracy of registration and to suggest a minimum margin to account for the registration errors. Initialization using Demons algorithm took about 15 min on a computer with 2.8 GHz Intel, 1.3 GB RAM. Refinement B-spline registration (200 iterations) took less than 5 min. Using the synthetic images as the ground truth, at zero margin, the average (S.D.) 98 (±0.4)% for prostate coverage was 97 (±1)% for tumor. The average (±S.D.) treatment margin required to cover the entire prostate was 1.5 (±0.2)mm. The average (± S.D.) treatment margin required to cover the tumor was 0.7 (±0.1)mm. We also demonstrated the challenges in registering an in vivo deformed MRI to an in vivo non-deformed MRI. We here present a deformable registration scheme that can overcome large deformation. This platform is expected to be useful for prostate cancer radiation treatment planning. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  10. Evaluating the effects of modeling errors for isolated finite three-dimensional targets

    NASA Astrophysics Data System (ADS)

    Henn, Mark-Alexander; Barnes, Bryan M.; Zhou, Hui

    2017-10-01

    Optical three-dimensional (3-D) nanostructure metrology utilizes a model-based metrology approach to determine critical dimensions (CDs) that are well below the inspection wavelength. Our project at the National Institute of Standards and Technology is evaluating how to attain key CD and shape parameters from engineered in-die capable metrology targets. More specifically, the quantities of interest are determined by varying the input parameters for a physical model until the simulations agree with the actual measurements within acceptable error bounds. As in most applications, establishing a reasonable balance between model accuracy and time efficiency is a complicated task. A well-established simplification is to model the intrinsically finite 3-D nanostructures as either periodic or infinite in one direction, reducing the computationally expensive 3-D simulations to usually less complex two-dimensional (2-D) problems. Systematic errors caused by this simplified model can directly influence the fitting of the model to the measurement data and are expected to become more apparent with decreasing lengths of the structures. We identify these effects using selected simulation results and present experimental setups, e.g., illumination numerical apertures and focal ranges, that can increase the validity of the 2-D approach.

  11. TU-AB-202-06: Quantitative Evaluation of Deformable Image Registration in MRI-Guided Adaptive Radiation Therapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mooney, K; Zhao, T; Green, O

    Purpose: To assess the performance of the deformable image registration algorithm used for MRI-guided adaptive radiation therapy using image feature analysis. Methods: MR images were collected from five patients treated on the MRIdian (ViewRay, Inc., Oakwood Village, OH), a three head Cobalt-60 therapy machine with an 0.35 T MR system. The images were acquired immediately prior to treatment with a uniform 1.5 mm resolution. Treatment sites were as follows: head/neck, lung, breast, stomach, and bladder. Deformable image registration was performed using the ViewRay software between the first fraction MRI and the final fraction MRI, and the DICE similarity coefficient (DSC)more » for the skin contours was reported. The SIFT and Harris feature detection and matching algorithms identified point features in each image separately, then found matching features in the other image. The target registration error (TRE) was defined as the vector distance between matched features on the two image sets. Each deformation was evaluated based on comparison of average TRE and DSC. Results: Image feature analysis produced between 2000–9500 points for evaluation on the patient images. The average (± standard deviation) TRE for all patients was 3.3 mm (±3.1 mm), and the passing rate of TRE<3 mm was 60% on the images. The head/neck patient had the best average TRE (1.9 mm±2.3 mm) and the best passing rate (80%). The lung patient had the worst average TRE (4.8 mm±3.3 mm) and the worst passing rate (37.2%). DSC was not significantly correlated with either TRE (p=0.63) or passing rate (p=0.55). Conclusions: Feature matching provides a quantitative assessment of deformable image registration, with a large number of data points for analysis. The TRE of matched features can be used to evaluate the registration of many objects throughout the volume, whereas DSC mainly provides a measure of gross overlap. We have a research agreement with ViewRay Inc.« less

  12. Adaptive Diffeomorphic Multiresolution Demons and Their Application to Same Modality Medical Image Registration with Large Deformation

    PubMed Central

    Wang, Chang; Ren, Qiongqiong; Qin, Xin

    2018-01-01

    Diffeomorphic demons can guarantee smooth and reversible deformation and avoid unreasonable deformation. However, the number of iterations needs to be set manually, and this greatly influences the registration result. In order to solve this problem, we proposed adaptive diffeomorphic multiresolution demons in this paper. We used an optimized framework with nonrigid registration and diffeomorphism strategy, designed a similarity energy function based on grey value, and stopped iterations adaptively. This method was tested by synthetic image and same modality medical image. Large deformation was simulated by rotational distortion and extrusion transform, medical image registration with large deformation was performed, and quantitative analyses were conducted using the registration evaluation indexes, and the influence of different driving forces and parameters on the registration result was analyzed. The registration results of same modality medical images were compared with those obtained using active demons, additive demons, and diffeomorphic demons. Quantitative analyses showed that the proposed method's normalized cross-correlation coefficient and structural similarity were the highest and mean square error was the lowest. Medical image registration with large deformation could be performed successfully; evaluation indexes remained stable with an increase in deformation strength. The proposed method is effective and robust, and it can be applied to nonrigid registration of same modality medical images with large deformation.

  13. Adaptive Diffeomorphic Multiresolution Demons and Their Application to Same Modality Medical Image Registration with Large Deformation.

    PubMed

    Wang, Chang; Ren, Qiongqiong; Qin, Xin; Yu, Yi

    2018-01-01

    Diffeomorphic demons can guarantee smooth and reversible deformation and avoid unreasonable deformation. However, the number of iterations needs to be set manually, and this greatly influences the registration result. In order to solve this problem, we proposed adaptive diffeomorphic multiresolution demons in this paper. We used an optimized framework with nonrigid registration and diffeomorphism strategy, designed a similarity energy function based on grey value, and stopped iterations adaptively. This method was tested by synthetic image and same modality medical image. Large deformation was simulated by rotational distortion and extrusion transform, medical image registration with large deformation was performed, and quantitative analyses were conducted using the registration evaluation indexes, and the influence of different driving forces and parameters on the registration result was analyzed. The registration results of same modality medical images were compared with those obtained using active demons, additive demons, and diffeomorphic demons. Quantitative analyses showed that the proposed method's normalized cross-correlation coefficient and structural similarity were the highest and mean square error was the lowest. Medical image registration with large deformation could be performed successfully; evaluation indexes remained stable with an increase in deformation strength. The proposed method is effective and robust, and it can be applied to nonrigid registration of same modality medical images with large deformation.

  14. Evaluation of non-rigid registration parameters for atlas-based segmentation of CT images of human cochlea

    NASA Astrophysics Data System (ADS)

    Elfarnawany, Mai; Alam, S. Riyahi; Agrawal, Sumit K.; Ladak, Hanif M.

    2017-02-01

    Cochlear implant surgery is a hearing restoration procedure for patients with profound hearing loss. In this surgery, an electrode is inserted into the cochlea to stimulate the auditory nerve and restore the patient's hearing. Clinical computed tomography (CT) images are used for planning and evaluation of electrode placement, but their low resolution limits the visualization of internal cochlear structures. Therefore, high resolution micro-CT images are used to develop atlas-based segmentation methods to extract these nonvisible anatomical features in clinical CT images. Accurate registration of the high and low resolution CT images is a prerequisite for reliable atlas-based segmentation. In this study, we evaluate and compare different non-rigid B-spline registration parameters using micro-CT and clinical CT images of five cadaveric human cochleae. The varying registration parameters are cost function (normalized correlation (NC), mutual information and mean square error), interpolation method (linear, windowed-sinc and B-spline) and sampling percentage (1%, 10% and 100%). We compare the registration results visually and quantitatively using the Dice similarity coefficient (DSC), Hausdorff distance (HD) and absolute percentage error in cochlear volume. Using MI or MSE cost functions and linear or windowed-sinc interpolation resulted in visually undesirable deformation of internal cochlear structures. Quantitatively, the transforms using 100% sampling percentage yielded the highest DSC and smallest HD (0.828+/-0.021 and 0.25+/-0.09mm respectively). Therefore, B-spline registration with cost function: NC, interpolation: B-spline and sampling percentage: moments 100% can be the foundation of developing an optimized atlas-based segmentation algorithm of intracochlear structures in clinical CT images.

  15. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 21 Food and Drugs 7 2013-04-01 2013-04-01 false Notification of registrant; cosmetic product... OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.6 Notification of registrant; cosmetic product establishment registration number. The...

  16. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 21 Food and Drugs 7 2012-04-01 2012-04-01 false Notification of registrant; cosmetic product... OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.6 Notification of registrant; cosmetic product establishment registration number. The...

  17. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 21 Food and Drugs 7 2010-04-01 2010-04-01 false Notification of registrant; cosmetic product... OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.6 Notification of registrant; cosmetic product establishment registration number. The...

  18. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 7 2011-04-01 2010-04-01 true Notification of registrant; cosmetic product... OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.6 Notification of registrant; cosmetic product establishment registration number. The...

  19. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 21 Food and Drugs 7 2014-04-01 2014-04-01 false Notification of registrant; cosmetic product... OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.6 Notification of registrant; cosmetic product establishment registration number. The...

  20. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic product...

  1. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic product...

  2. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic product...

  3. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic product...

  4. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic product...

  5. Comparison of Online 6 Degree-of-Freedom Image Registration of Varian TrueBeam Cone-Beam CT and BrainLab ExacTrac X-Ray for Intracranial Radiosurgery.

    PubMed

    Li, Jun; Shi, Wenyin; Andrews, David; Werner-Wasik, Maria; Lu, Bo; Yu, Yan; Dicker, Adam; Liu, Haisong

    2017-06-01

    The study was aimed to compare online 6 degree-of-freedom image registrations of TrueBeam cone-beam computed tomography and BrainLab ExacTrac X-ray imaging systems for intracranial radiosurgery. Phantom and patient studies were performed on a Varian TrueBeam STx linear accelerator (version 2.5), which is integrated with a BrainLab ExacTrac imaging system (version 6.1.1). The phantom study was based on a Rando head phantom and was designed to evaluate isocenter location dependence of the image registrations. Ten isocenters at various locations representing clinical treatment sites were selected in the phantom. Cone-beam computed tomography and ExacTrac X-ray images were taken when the phantom was located at each isocenter. The patient study included 34 patients. Cone-beam computed tomography and ExacTrac X-ray images were taken at each patient's treatment position. The 6 degree-of-freedom image registrations were performed on cone-beam computed tomography and ExacTrac, and residual errors calculated from cone-beam computed tomography and ExacTrac were compared. In the phantom study, the average residual error differences (absolute values) between cone-beam computed tomography and ExacTrac image registrations were 0.17 ± 0.11 mm, 0.36 ± 0.20 mm, and 0.25 ± 0.11 mm in the vertical, longitudinal, and lateral directions, respectively. The average residual error differences in the rotation, roll, and pitch were 0.34° ± 0.08°, 0.13° ± 0.09°, and 0.12° ± 0.10°, respectively. In the patient study, the average residual error differences in the vertical, longitudinal, and lateral directions were 0.20 ± 0.16 mm, 0.30 ± 0.18 mm, 0.21 ± 0.18 mm, respectively. The average residual error differences in the rotation, roll, and pitch were 0.40°± 0.16°, 0.17° ± 0.13°, and 0.20° ± 0.14°, respectively. Overall, the average residual error differences were <0.4 mm in the translational directions and <0.5° in the rotational directions. ExacTrac X-ray image

  6. MRI Signal Intensity Based B-Spline Nonrigid Registration for Pre- and Intraoperative Imaging During Prostate Brachytherapy

    PubMed Central

    Oguro, Sota; Tokuda, Junichi; Elhawary, Haytham; Haker, Steven; Kikinis, Ron; Tempany, Clare M.C.; Hata, Nobuhiko

    2009-01-01

    Purpose To apply an intensity-based nonrigid registration algorithm to MRI-guided prostate brachytherapy clinical data and to assess its accuracy. Materials and Methods A nonrigid registration of preoperative MRI to intraoperative MRI images was carried out in 16 cases using a Basis-Spline algorithm in a retrospective manner. The registration was assessed qualitatively by experts’ visual inspection and quantitatively by measuring the Dice similarity coefficient (DSC) for total gland (TG), central gland (CG), and peripheral zone (PZ), the mutual information (MI) metric, and the fiducial registration error (FRE) between corresponding anatomical landmarks for both the nonrigid and a rigid registration method. Results All 16 cases were successfully registered in less than 5 min. After the nonrigid registration, DSC values for TG, CG, PZ were 0.91, 0.89, 0.79, respectively, the MI metric was −0.19 ± 0.07 and FRE presented a value of 2.3 ± 1.8 mm. All the metrics were significantly better than in the case of rigid registration, as determined by one-sided t-tests. Conclusion The intensity-based nonrigid registration method using clinical data was demonstrated to be feasible and showed statistically improved metrics when compare to only rigid registration. The method is a valuable tool to integrate pre- and intraoperative images for brachytherapy. PMID:19856437

  7. Comparison of manual and automatic MR‐CT registration for radiotherapy of prostate cancer

    PubMed Central

    Carl, Jesper; Østergaard, Lasse Riis

    2016-01-01

    In image‐guided radiotherapy (IGRT) of prostate cancer, delineation of the clinical target volume (CTV) often relies on magnetic resonance (MR) because of its good soft‐tissue visualization. Registration of MR and computed tomography (CT) is required in order to add this accurate delineation to the dose planning CT. An automatic approach for local MR‐CT registration of the prostate has previously been developed using a voxel property‐based registration as an alternative to a manual landmark‐based registration. The aim of this study is to compare the two registration approaches and to investigate the clinical potential for replacing the manual registration with the automatic registration. Registrations and analysis were performed for 30 prostate cancer patients treated with IGRT using a Ni‐Ti prostate stent as a fiducial marker. The comparison included computing translational and rotational differences between the approaches, visual inspection, and computing the overlap of the CTV. The computed mean translational difference was 1.65, 1.60, and 1.80 mm and the computed mean rotational difference was 1.51°, 3.93°, and 2.09° in the superior/inferior, anterior/posterior, and medial/lateral direction, respectively. The sensitivity of overlap was 87%. The results demonstrate that the automatic registration approach performs registrations comparable to the manual registration. PACS number(s): 87.57.nj, 87.61.‐c, 87.57.Q‐, 87.56.J‐ PMID:27167285

  8. Morphological Feature Extraction for Automatic Registration of Multispectral Images

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2007-01-01

    The task of image registration can be divided into two major components, i.e., the extraction of control points or features from images, and the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual extraction of control features can be subjective and extremely time consuming, and often results in few usable points. On the other hand, automated feature extraction allows using invariant target features such as edges, corners, and line intersections as relevant landmarks for registration purposes. In this paper, we present an extension of a recently developed morphological approach for automatic extraction of landmark chips and corresponding windows in a fully unsupervised manner for the registration of multispectral images. Once a set of chip-window pairs is obtained, a (hierarchical) robust feature matching procedure, based on a multiresolution overcomplete wavelet decomposition scheme, is used for registration purposes. The proposed method is validated on a pair of remotely sensed scenes acquired by the Advanced Land Imager (ALI) multispectral instrument and the Hyperion hyperspectral instrument aboard NASA's Earth Observing-1 satellite.

  9. Evaluation of body-wise and organ-wise registrations for abdominal organs

    NASA Astrophysics Data System (ADS)

    Xu, Zhoubing; Panjwani, Sahil A.; Lee, Christopher P.; Burke, Ryan P.; Baucom, Rebeccah B.; Poulose, Benjamin K.; Abramson, Richard G.; Landman, Bennett A.

    2016-03-01

    Identifying cross-sectional and longitudinal correspondence in the abdomen on computed tomography (CT) scans is necessary for quantitatively tracking change and understanding population characteristics, yet abdominal image registration is a challenging problem. The key difficulty in solving this problem is huge variations in organ dimensions and shapes across subjects. The current standard registration method uses the global or body-wise registration technique, which is based on the global topology for alignment. This method (although producing decent results) has substantial influence of outliers, thus leaving room for significant improvement. Here, we study a new image registration approach using local (organ-wise registration) by first creating organ-specific bounding boxes and then using these regions of interest (ROIs) for aligning references to target. Based on Dice Similarity Coefficient (DSC), Mean Surface Distance (MSD) and Hausdorff Distance (HD), the organ-wise approach is demonstrated to have significantly better results by minimizing the distorting effects of organ variations. This paper compares exclusively the two registration methods by providing novel quantitative and qualitative comparison data and is a subset of the more comprehensive problem of improving the multi-atlas segmentation by using organ normalization.

  10. 75 FR 41968 - Re-Registration and Renewal of Aircraft Registration

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-20

    ... the use of the second or ``Pink Copy'' of the application for registration for a reasonable period of... under ``Pink Copy'' temporary authority at any time if an application for registration is made. Due to... reference to the ``pink copy'' of the Aircraft Registration Application. V. Miscellaneous Comments A. Re...

  11. Automatic bone detection and soft tissue aware ultrasound-CT registration for computer-aided orthopedic surgery.

    PubMed

    Wein, Wolfgang; Karamalis, Athanasios; Baumgartner, Adrian; Navab, Nassir

    2015-06-01

    The transfer of preoperative CT data into the tracking system coordinates within an operating room is of high interest for computer-aided orthopedic surgery. In this work, we introduce a solution for intra-operative ultrasound-CT registration of bones. We have developed methods for fully automatic real-time bone detection in ultrasound images and global automatic registration to CT. The bone detection algorithm uses a novel bone-specific feature descriptor and was thoroughly evaluated on both in-vivo and ex-vivo data. A global optimization strategy aligns the bone surface, followed by a soft tissue aware intensity-based registration to provide higher local registration accuracy. We evaluated the system on femur, tibia and fibula anatomy in a cadaver study with human legs, where magnetically tracked bone markers were implanted to yield ground truth information. An overall median system error of 3.7 mm was achieved on 11 datasets. Global and fully automatic registration of bones aquired with ultrasound to CT is feasible, with bone detection and tracking operating in real time for immediate feedback to the surgeon.

  12. A 3D global-to-local deformable mesh model based registration and anatomy-constrained segmentation method for image guided prostate radiotherapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhou Jinghao; Kim, Sung; Jabbour, Salma

    2010-03-15

    2.45 to 6.54 mm for ASM. The volume overlap ratio ranged from 79% to 91% for ACRASM and from 44% to 80% for ASM. These data demonstrated that the segmentation results of ACRASM were in better agreement with the corresponding benchmarks than those of ASM. The developed registration algorithm was quantitatively evaluated by comparing the registered target volumes from the pCT to the benchmarks on the CBCT. The mean distance and the root mean square error ranged from 0.38 to 2.2 mm and from 0.45 to 2.36 mm, respectively, between the CBCT images and the registered pCT. The mean overlap ratio of the prostate volumes ranged from 85.2% to 95% after registration. The average time of the ACRASM-based segmentation was under 1 min. The average time of the global transformation was from 2 to 4 min on two 3D volumes and the average time of the local transformation was from 20 to 34 s on two deformable superquadrics mesh models. Conclusions: A novel and fast segmentation and deformable registration method was developed to capture the transformation between the planning and treatment images for external beam radiotherapy of prostate cancers. This method increases the computational efficiency and may provide foundation to achieve real time adaptive radiotherapy.« less

  13. Misclassification Errors in Unsupervised Classification Methods. Comparison Based on the Simulation of Targeted Proteomics Data

    PubMed Central

    Andreev, Victor P; Gillespie, Brenda W; Helfand, Brian T; Merion, Robert M

    2016-01-01

    Unsupervised classification methods are gaining acceptance in omics studies of complex common diseases, which are often vaguely defined and are likely the collections of disease subtypes. Unsupervised classification based on the molecular signatures identified in omics studies have the potential to reflect molecular mechanisms of the subtypes of the disease and to lead to more targeted and successful interventions for the identified subtypes. Multiple classification algorithms exist but none is ideal for all types of data. Importantly, there are no established methods to estimate sample size in unsupervised classification (unlike power analysis in hypothesis testing). Therefore, we developed a simulation approach allowing comparison of misclassification errors and estimating the required sample size for a given effect size, number, and correlation matrix of the differentially abundant proteins in targeted proteomics studies. All the experiments were performed in silico. The simulated data imitated the expected one from the study of the plasma of patients with lower urinary tract dysfunction with the aptamer proteomics assay Somascan (SomaLogic Inc, Boulder, CO), which targeted 1129 proteins, including 330 involved in inflammation, 180 in stress response, 80 in aging, etc. Three popular clustering methods (hierarchical, k-means, and k-medoids) were compared. K-means clustering performed much better for the simulated data than the other two methods and enabled classification with misclassification error below 5% in the simulated cohort of 100 patients based on the molecular signatures of 40 differentially abundant proteins (effect size 1.5) from among the 1129-protein panel. PMID:27524871

  14. Undergraduate Cross Registration.

    ERIC Educational Resources Information Center

    Grupe, Fritz H.

    This report discusses various aspects of undergraduate cross-registration procedures, including the dimensions, values, roles and functions, basic assumptions, and facilitating and encouragment of cross-registration. Dimensions of cross-registration encompass financial exchange, eligibility, program limitations, type of grade and credit; extent of…

  15. Registration of retinal sequences from new video-ophthalmoscopic camera.

    PubMed

    Kolar, Radim; Tornow, Ralf P; Odstrcilik, Jan; Liberdova, Ivana

    2016-05-20

    Analysis of fast temporal changes on retinas has become an important part of diagnostic video-ophthalmology. It enables investigation of the hemodynamic processes in retinal tissue, e.g. blood-vessel diameter changes as a result of blood-pressure variation, spontaneous venous pulsation influenced by intracranial-intraocular pressure difference, blood-volume changes as a result of changes in light reflection from retinal tissue, and blood flow using laser speckle contrast imaging. For such applications, image registration of the recorded sequence must be performed. Here we use a new non-mydriatic video-ophthalmoscope for simple and fast acquisition of low SNR retinal sequences. We introduce a novel, two-step approach for fast image registration. The phase correlation in the first stage removes large eye movements. Lucas-Kanade tracking in the second stage removes small eye movements. We propose robust adaptive selection of the tracking points, which is the most important part of tracking-based approaches. We also describe a method for quantitative evaluation of the registration results, based on vascular tree intensity profiles. The achieved registration error evaluated on 23 sequences (5840 frames) is 0.78 ± 0.67 pixels inside the optic disc and 1.39 ± 0.63 pixels outside the optic disc. We compared the results with the commonly used approaches based on Lucas-Kanade tracking and scale-invariant feature transform, which achieved worse results. The proposed method can efficiently correct particular frames of retinal sequences for shift and rotation. The registration results for each frame (shift in X and Y direction and eye rotation) can also be used for eye-movement evaluation during single-spot fixation tasks.

  16. Registration of parametric dynamic F-18-FDG PET/CT breast images with parametric dynamic Gd-DTPA breast images

    NASA Astrophysics Data System (ADS)

    Magri, Alphonso; Krol, Andrzej; Lipson, Edward; Mandel, James; McGraw, Wendy; Lee, Wei; Tillapaugh-Fay, Gwen; Feiglin, David

    2009-02-01

    This study was undertaken to register 3D parametric breast images derived from Gd-DTPA MR and F-18-FDG PET/CT dynamic image series. Nonlinear curve fitting (Levenburg-Marquardt algorithm) based on realistic two-compartment models was performed voxel-by-voxel separately for MR (Brix) and PET (Patlak). PET dynamic series consists of 50 frames of 1-minute duration. Each consecutive PET image was nonrigidly registered to the first frame using a finite element method and fiducial skin markers. The 12 post-contrast MR images were nonrigidly registered to the precontrast frame using a free-form deformation (FFD) method. Parametric MR images were registered to parametric PET images via CT using FFD because the first PET time frame was acquired immediately after the CT image on a PET/CT scanner and is considered registered to the CT image. We conclude that nonrigid registration of PET and MR parametric images using CT data acquired during PET/CT scan and the FFD method resulted in their improved spatial coregistration. The success of this procedure was limited due to relatively large target registration error, TRE = 15.1+/-7.7 mm, as compared to spatial resolution of PET (6-7 mm), and swirling image artifacts created in MR parametric images by the FFD. Further refinement of nonrigid registration of PET and MR parametric images is necessary to enhance visualization and integration of complex diagnostic information provided by both modalities that will lead to improved diagnostic performance.

  17. Deformable 3D-2D registration for CT and its application to low dose tomographic fluoroscopy

    NASA Astrophysics Data System (ADS)

    Flach, Barbara; Brehm, Marcus; Sawall, Stefan; Kachelrieß, Marc

    2014-12-01

    Many applications in medical imaging include image registration for matching of images from the same or different modalities. In the case of full data sampling, the respective reconstructed images are usually of such a good image quality that standard deformable volume-to-volume (3D-3D) registration approaches can be applied. But research in temporal-correlated image reconstruction and dose reductions increases the number of cases where rawdata are available from only few projection angles. Here, deteriorated image quality leads to non-acceptable deformable volume-to-volume registration results. Therefore a registration approach is required that is robust against a decreasing number of projections defining the target position. We propose a deformable volume-to-rawdata (3D-2D) registration method that aims at finding a displacement vector field maximizing the alignment of a CT volume and the acquired rawdata based on the sum of squared differences in rawdata domain. The registration is constrained by a regularization term in accordance with a fluid-based diffusion. Both cost function components, the rawdata fidelity and the regularization term, are optimized in an alternating manner. The matching criterion is optimized by a conjugate gradient descent for nonlinear functions, while the regularization is realized by convolution of the vector fields with Gaussian kernels. We validate the proposed method and compare it to the demons algorithm, a well-known 3D-3D registration method. The comparison is done for a range of 4-60 target projections using datasets from low dose tomographic fluoroscopy as an application example. The results show a high correlation to the ground truth target position without introducing artifacts even in the case of very few projections. In particular the matching in the rawdata domain is improved compared to the 3D-3D registration for the investigated range. The proposed volume-to-rawdata registration increases the robustness regarding sparse

  18. Coarse Point Cloud Registration by Egi Matching of Voxel Clusters

    NASA Astrophysics Data System (ADS)

    Wang, Jinhu; Lindenbergh, Roderik; Shen, Yueqian; Menenti, Massimo

    2016-06-01

    Laser scanning samples the surface geometry of objects efficiently and records versatile information as point clouds. However, often more scans are required to fully cover a scene. Therefore, a registration step is required that transforms the different scans into a common coordinate system. The registration of point clouds is usually conducted in two steps, i.e. coarse registration followed by fine registration. In this study an automatic marker-free coarse registration method for pair-wise scans is presented. First the two input point clouds are re-sampled as voxels and dimensionality features of the voxels are determined by principal component analysis (PCA). Then voxel cells with the same dimensionality are clustered. Next, the Extended Gaussian Image (EGI) descriptor of those voxel clusters are constructed using significant eigenvectors of each voxel in the cluster. Correspondences between clusters in source and target data are obtained according to the similarity between their EGI descriptors. The random sampling consensus (RANSAC) algorithm is employed to remove outlying correspondences until a coarse alignment is obtained. If necessary, a fine registration is performed in a final step. This new method is illustrated on scan data sampling two indoor scenarios. The results of the tests are evaluated by computing the point to point distance between the two input point clouds. The presented two tests resulted in mean distances of 7.6 mm and 9.5 mm respectively, which are adequate for fine registration.

  19. TU-AB-202-07: A Novel Method for Registration of Mid-Treatment PET/CT Images Under Conditions of Tumor Regression for Patients with Locally Advanced Lung Cancers

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sharifi, Hoda; Department of Physics, Oakland University, Rochester, MI; Zhang, Hong

    Purpose: In PET-guided adaptive radiotherapy (RT), changes in the metabolic activity at individual voxels cannot be derived until the duringtreatment CT images are appropriately registered to pre-treatment CT images. However, deformable image registration (DIR) usually does not preserve tumor volume. This may induce errors when comparing to the target. The aim of this study was to develop a DIR-integrated mechanical modeling technique to track radiation-induced metabolic changes on PET images. Methods: Three patients with non-small cell lung cancer (NSCLC) were treated with adaptive radiotherapy under RTOG 1106. Two PET/CT image sets were acquired 2 weeks before RT and 18 fractionsmore » after the start of treatment. DIR was performed to register the during-RT CT to the pre-RT CT using a B-spline algorithm and the resultant displacements in the region of tumor were remodeled using a hybrid finite element method (FEM). Gross tumor volume (GTV) was delineated on the during-RT PET/CT image sets and deformed using the 3D deformation vector fields generated by the CT-based registrations. Metabolic tumor volume (MTV) was calculated using the pre- and during–RT image set. The quality of the PET mapping was evaluated based on the constancy of the mapped MTV and landmark comparison. Results: The B-spline-based registrations changed MTVs by 7.3%, 4.6% and −5.9% for the 3 patients and the correspondent changes for the hybrid FEM method −2.9%, 1% and 6.3%, respectively. Landmark comparisons were used to evaluate the Rigid, B-Spline, and hybrid FEM registrations with the mean errors of 10.1 ± 1.6 mm, 4.4 ± 0.4 mm, and 3.6 ± 0.4 mm for three patients. The hybrid FEM method outperforms the B-Spline-only registration for patients with tumor regression Conclusion: The hybrid FEM modeling technique improves the B-Spline registrations in tumor regions. This technique may help compare metabolic activities between two PET/CT images with regressing tumors. The author

  20. A novel registration-based methodology for prediction of trabecular bone fabric from clinical QCT: A comprehensive analysis

    PubMed Central

    Reyes, Mauricio; Zysset, Philippe

    2017-01-01

    Osteoporosis leads to hip fractures in aging populations and is diagnosed by modern medical imaging techniques such as quantitative computed tomography (QCT). Hip fracture sites involve trabecular bone, whose strength is determined by volume fraction and orientation, known as fabric. However, bone fabric cannot be reliably assessed in clinical QCT images of proximal femur. Accordingly, we propose a novel registration-based estimation of bone fabric designed to preserve tensor properties of bone fabric and to map bone fabric by a global and local decomposition of the gradient of a non-rigid image registration transformation. Furthermore, no comprehensive analysis on the critical components of this methodology has been previously conducted. Hence, the aim of this work was to identify the best registration-based strategy to assign bone fabric to the QCT image of a patient’s proximal femur. The normalized correlation coefficient and curvature-based regularization were used for image-based registration and the Frobenius norm of the stretch tensor of the local gradient was selected to quantify the distance among the proximal femora in the population. Based on this distance, closest, farthest and mean femora with a distinction of sex were chosen as alternative atlases to evaluate their influence on bone fabric prediction. Second, we analyzed different tensor mapping schemes for bone fabric prediction: identity, rotation-only, rotation and stretch tensor. Third, we investigated the use of a population average fabric atlas. A leave one out (LOO) evaluation study was performed with a dual QCT and HR-pQCT database of 36 pairs of human femora. The quality of the fabric prediction was assessed with three metrics, the tensor norm (TN) error, the degree of anisotropy (DA) error and the angular deviation of the principal tensor direction (PTD). The closest femur atlas (CTP) with a full rotation (CR) for fabric mapping delivered the best results with a TN error of 7.3 ± 0.9%, a

  1. Registration of Space Objects

    NASA Astrophysics Data System (ADS)

    Schmidt-Tedd, Bernhard

    2017-07-01

    Space objects are subject to registration in order to allocate "jurisdiction and control" over those objects in the sovereign-free environment of outer space. This approach is similar to the registration of ships in view of the high sea and for aircrafts with respect to the international airspace. Registration is one of the basic principles of space law, starting with UN General Assembly Resolution 1721 B (XVI) of December 20, 1961, followed by Resolution 1962 (XVIII) of December 13, 1963, then formulated in Article VIII of the Outer Space Treaty of 1967 and as specified in the Registration Convention of 1975. Registration of space objects can be seen today as a principle of customary international law, relevant for each spacefaring state. Registration is divided into a national and an international level. The State Party establishes a national registry for its space objects, and those registrations have to be communicated via diplomatic channel to the UN Register of space objects. This UN Register is handled by the UN Office for Outer Space Affairs (UNOOSA) and is an open source of information for space objects worldwide. Registration is linked to the so-called launching state of the relevant space object. There might be more than one launching state for the specific launch event, but only one state actor can register a specific space object. The state of registry gains "jurisdiction and control" over the space object and therefore no double registration is permissible. Based on the established UN Space Law, registration practice was subject to some adaptions due to technical developments and legal challenges. After the privatization of the major international satellite organizations, a number of non-registrations had to be faced. The state actors reacted with the UN Registration Practice Resolution of 2007 as elaborated in the Legal Subcommittee of UNCOPUOS, the Committee for the Peaceful Use of Outer Space. In this context an UNOOSA Registration Information

  2. Co-Registration Between Multisource Remote-Sensing Images

    NASA Astrophysics Data System (ADS)

    Wu, J.; Chang, C.; Tsai, H.-Y.; Liu, M.-C.

    2012-07-01

    Image registration is essential for geospatial information systems analysis, which usually involves integrating multitemporal and multispectral datasets from remote optical and radar sensors. An algorithm that deals with feature extraction, keypoint matching, outlier detection and image warping is experimented in this study. The methods currently available in the literature rely on techniques, such as the scale-invariant feature transform, between-edge cost minimization, normalized cross correlation, leasts-quares image matching, random sample consensus, iterated data snooping and thin-plate splines. Their basics are highlighted and encoded into a computer program. The test images are excerpts from digital files created by the multispectral SPOT-5 and Formosat-2 sensors, and by the panchromatic IKONOS and QuickBird sensors. Suburban areas, housing rooftops, the countryside and hilly plantations are studied. The co-registered images are displayed with block subimages in a criss-cross pattern. Besides the imagery, the registration accuracy is expressed by the root mean square error. Toward the end, this paper also includes a few opinions on issues that are believed to hinder a correct correspondence between diverse images.

  3. Analytical and experimental design and analysis of an optimal processor for image registration

    NASA Technical Reports Server (NTRS)

    Mcgillem, C. D. (Principal Investigator); Svedlow, M.; Anuta, P. E.

    1976-01-01

    The author has identified the following significant results. A quantitative measure of the registration processor accuracy in terms of the variance of the registration error was derived. With the appropriate assumptions, the variance was shown to be inversely proportional to the square of the effective bandwidth times the signal to noise ratio. The final expressions were presented to emphasize both the form and simplicity of their representation. In the situation where relative spatial distortions exist between images to be registered, expressions were derived for estimating the loss in output signal to noise ratio due to these spatial distortions. These results are in terms of a reduction factor.

  4. Assessment of Thematic Mapper band-to-band registration by the block correlation method

    NASA Technical Reports Server (NTRS)

    Card, D. H.; Wrigley, R. C.; Mertz, F. C.; Hall, J. R.

    1983-01-01

    Rectangular blocks of pixels from one band image were statistically correlated against blocks centered on identical pixels from a second band image. The block pairs were shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient to the maximum correlation was taken as the best estimate of registration error for each block pair. For the band combinations of the Arkansas scene studied, the misregistration of TM spectral bands within the noncooled focal plane lie well within the 0.2 pixel target specification. Misregistration between the middle IR bands is well within this specification also. The thermal IR band has an apparent misregistration with TM band 7 of approximately 3 pixels in each direction. The TM band 3 has a misregistration of approximately 0.2 pixel in the across-scan direction and 0.5 pixel in the along-scan direction, with both TM bands 5 and 7.

  5. Assessment of Thematic Mapper Band-to-band Registration by the Block Correlation Method

    NASA Technical Reports Server (NTRS)

    Card, D. H.; Wrigley, R. C.; Mertz, F. C.; Hall, J. R.

    1985-01-01

    Rectangular blocks of pixels from one band image were statistically correlated against blocks centered on identical pixels from a second band image. The block pairs were shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient to the maximum correlation was taken as the best estimate of registration error for each block pair. For the band combinations of the Arkansas scene studied, the misregistration of TM spectral bands within the noncooled focal plane lie well within the 0.2 pixel target specification. Misregistration between the middle IR bands is well within this specification also. The thermal IR band has an apparent misregistration with TM band 7 of approximately 3 pixels in each direction. The TM band 3 has a misregistration of approximately 0.2 pixel in the across-scan direction and 0.5 pixel in the along-scan direction, with both TM bands 5 and 7.

  6. Respiratory motion correction in dynamic MRI using robust data decomposition registration - application to DCE-MRI.

    PubMed

    Hamy, Valentin; Dikaios, Nikolaos; Punwani, Shonit; Melbourne, Andrew; Latifoltojar, Arash; Makanyanga, Jesica; Chouhan, Manil; Helbren, Emma; Menys, Alex; Taylor, Stuart; Atkinson, David

    2014-02-01

    Motion correction in Dynamic Contrast Enhanced (DCE-) MRI is challenging because rapid intensity changes can compromise common (intensity based) registration algorithms. In this study we introduce a novel registration technique based on robust principal component analysis (RPCA) to decompose a given time-series into a low rank and a sparse component. This allows robust separation of motion components that can be registered, from intensity variations that are left unchanged. This Robust Data Decomposition Registration (RDDR) is demonstrated on both simulated and a wide range of clinical data. Robustness to different types of motion and breathing choices during acquisition is demonstrated for a variety of imaged organs including liver, small bowel and prostate. The analysis of clinically relevant regions of interest showed both a decrease of error (15-62% reduction following registration) in tissue time-intensity curves and improved areas under the curve (AUC60) at early enhancement. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

  7. Seeing Your Error Alters My Pointing: Observing Systematic Pointing Errors Induces Sensori-Motor After-Effects

    PubMed Central

    Ronchi, Roberta; Revol, Patrice; Katayama, Masahiro; Rossetti, Yves; Farnè, Alessandro

    2011-01-01

    During the procedure of prism adaptation, subjects execute pointing movements to visual targets under a lateral optical displacement: As consequence of the discrepancy between visual and proprioceptive inputs, their visuo-motor activity is characterized by pointing errors. The perception of such final errors triggers error-correction processes that eventually result into sensori-motor compensation, opposite to the prismatic displacement (i.e., after-effects). Here we tested whether the mere observation of erroneous pointing movements, similar to those executed during prism adaptation, is sufficient to produce adaptation-like after-effects. Neurotypical participants observed, from a first-person perspective, the examiner's arm making incorrect pointing movements that systematically overshot visual targets location to the right, thus simulating a rightward optical deviation. Three classical after-effect measures (proprioceptive, visual and visual-proprioceptive shift) were recorded before and after first-person's perspective observation of pointing errors. Results showed that mere visual exposure to an arm that systematically points on the right-side of a target (i.e., without error correction) produces a leftward after-effect, which mostly affects the observer's proprioceptive estimation of her body midline. In addition, being exposed to such a constant visual error induced in the observer the illusion “to feel” the seen movement. These findings indicate that it is possible to elicit sensori-motor after-effects by mere observation of movement errors. PMID:21731649

  8. Atlas-based identification of targets for functional radiosurgery

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Stancanello, Joseph; Romanelli, Pantaleo; Modugno, Nicola

    2006-06-15

    -mask distance to the clinical outcome of the treatments in ten cases of bilateral DBS implants. Electrode placement may have an effect within a radius of stimulation equal to 2 mm, therefore the registration process is considered successful if error is less than 2 mm. The registrations of the MNI atlas onto the patient space succeeded in all cases. The comparison of the distance to the clinical outcome revealed good agreement: where the distance was high (at least in one implant), the clinical outcome was poor; where there was a close correlation between the structures, clinical outcome revealed an improvement of the pathological condition. In conclusion, the proposed method seems to provide a useful tool for the identification of the target nuclei for functional radiosurgery. Also, the method is applicable to other types of functional treatment.« less

  9. Fast interactive registration tool for reproducible multi-spectral imaging for wound healing and treatment evaluation

    NASA Astrophysics Data System (ADS)

    Noordmans, Herke J.; de Roode, Rowland; Verdaasdonk, Rudolf

    2007-02-01

    Multi-spectral images of human tissue taken in-vivo often contain image alignment problems as patients have difficulty in retaining their posture during the acquisition time of 20 seconds. Previously, it has been attempted to correct motion errors with image registration software developed for MR or CT data but these algorithms have been proven to be too slow and erroneous for practical use with multi-spectral images. A new software package has been developed which allows the user to play a decisive role in the registration process as the user can monitor the progress of the registration continuously and force it in the right direction when it starts to fail. The software efficiently exploits videocard hardware to gain speed and to provide a perfect subvoxel correspondence between registration field and display. An 8 bit graphic card was used to efficiently register and resample 12 bit images using the hardware interpolation modes present on the graphic card. To show the feasibility of this new registration process, the software was applied in clinical practice evaluating the dosimetry for psoriasis and KTP laser treatment. The microscopic differences between images of normal skin and skin exposed to UV light proved that an affine registration step including zooming and slanting is critical for a subsequent elastic match to have success. The combination of user interactive registration software with optimal addressing the potentials of PC video card hardware greatly improves the speed of multi spectral image registration.

  10. 16 CFR 1130.8 - Requirements for Web site registration or alternative e-mail registration.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 16 Commercial Practices 2 2012-01-01 2012-01-01 false Requirements for Web site registration or... PRODUCTS § 1130.8 Requirements for Web site registration or alternative e-mail registration. (a) Link to registration page. The manufacturer's Web site, or other Web site established for the purpose of registration...

  11. 16 CFR 1130.8 - Requirements for Web site registration or alternative e-mail registration.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 16 Commercial Practices 2 2011-01-01 2011-01-01 false Requirements for Web site registration or... PRODUCTS § 1130.8 Requirements for Web site registration or alternative e-mail registration. (a) Link to registration page. The manufacturer's Web site, or other Web site established for the purpose of registration...

  12. 16 CFR 1130.7 - Requirements for Web site registration or alternative e-mail registration.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 16 Commercial Practices 2 2014-01-01 2014-01-01 false Requirements for Web site registration or... PRODUCTS § 1130.7 Requirements for Web site registration or alternative e-mail registration. (a) Link to registration page. The manufacturer's Web site, or other Web site established for the purpose of registration...

  13. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft registration must place a U.S. registration number (registration mark) on the Aircraft Registration Application, AC... Dealer's Aircraft Registration Certificate, AC Form 8050-6, who applies for a temporary registration...

  14. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft registration must place a U.S. registration number (registration mark) on the Aircraft Registration Application, AC... Dealer's Aircraft Registration Certificate, AC Form 8050-6, who applies for a temporary registration...

  15. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft registration must place a U.S. registration number (registration mark) on the Aircraft Registration Application, AC... Dealer's Aircraft Registration Certificate, AC Form 8050-6, who applies for a temporary registration...

  16. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft registration must place a U.S. registration number (registration mark) on the Aircraft Registration Application, AC... Dealer's Aircraft Registration Certificate, AC Form 8050-6, who applies for a temporary registration...

  17. A GPU-based symmetric non-rigid image registration method in human lung.

    PubMed

    Haghighi, Babak; D Ellingwood, Nathan; Yin, Youbing; Hoffman, Eric A; Lin, Ching-Long

    2018-03-01

    Quantitative computed tomography (QCT) of the lungs plays an increasing role in identifying sub-phenotypes of pathologies previously lumped into broad categories such as chronic obstructive pulmonary disease and asthma. Methods for image matching and linking multiple lung volumes have proven useful in linking structure to function and in the identification of regional longitudinal changes. Here, we seek to improve the accuracy of image matching via the use of a symmetric multi-level non-rigid registration employing an inverse consistent (IC) transformation whereby images are registered both in the forward and reverse directions. To develop the symmetric method, two similarity measures, the sum of squared intensity difference (SSD) and the sum of squared tissue volume difference (SSTVD), were used. The method is based on a novel generic mathematical framework to include forward and backward transformations, simultaneously, eliminating the need to compute the inverse transformation. Two implementations were used to assess the proposed method: a two-dimensional (2-D) implementation using synthetic examples with SSD, and a multi-core CPU and graphics processing unit (GPU) implementation with SSTVD for three-dimensional (3-D) human lung datasets (six normal adults studied at total lung capacity (TLC) and functional residual capacity (FRC)). Success was evaluated in terms of the IC transformation consistency serving to link TLC to FRC. 2-D registration on synthetic images, using both symmetric and non-symmetric SSD methods, and comparison of displacement fields showed that the symmetric method gave a symmetrical grid shape and reduced IC errors, with the mean values of IC errors decreased by 37%. Results for both symmetric and non-symmetric transformations of human datasets showed that the symmetric method gave better results for IC errors in all cases, with mean values of IC errors for the symmetric method lower than the non-symmetric methods using both SSD and SSTVD

  18. Automatic Marker-free Longitudinal Infrared Image Registration by Shape Context Based Matching and Competitive Winner-guided Optimal Corresponding

    PubMed Central

    Lee, Chia-Yen; Wang, Hao-Jen; Lai, Jhih-Hao; Chang, Yeun-Chung; Huang, Chiun-Sheng

    2017-01-01

    Long-term comparisons of infrared image can facilitate the assessment of breast cancer tissue growth and early tumor detection, in which longitudinal infrared image registration is a necessary step. However, it is hard to keep markers attached on a body surface for weeks, and rather difficult to detect anatomic fiducial markers and match them in the infrared image during registration process. The proposed study, automatic longitudinal infrared registration algorithm, develops an automatic vascular intersection detection method and establishes feature descriptors by shape context to achieve robust matching, as well as to obtain control points for the deformation model. In addition, competitive winner-guided mechanism is developed for optimal corresponding. The proposed algorithm is evaluated in two ways. Results show that the algorithm can quickly lead to accurate image registration and that the effectiveness is superior to manual registration with a mean error being 0.91 pixels. These findings demonstrate that the proposed registration algorithm is reasonably accurate and provide a novel method of extracting a greater amount of useful data from infrared images. PMID:28145474

  19. The distance discordance metric - A novel approach to quantifying spatial uncertainties in intra- and inter-patient deformable image registration

    PubMed Central

    Saleh, Ziad H.; Apte, Aditya P.; Sharp, Gregory C.; Shusharina, Nadezhda P.; Wang, Ya; Veeraraghavan, Harini; Thor, Maria; Muren, Ludvig P.; Rao, Shyam S.; Lee, Nancy Y.; Deasy, Joseph O.

    2014-01-01

    Previous methods to estimate the inherent accuracy of deformable image registration (DIR) have typically been performed relative to a known ground truth, such as tracking of anatomic landmarks or known deformations in a physical or virtual phantom. In this study, we propose a new approach to estimate the spatial geometric uncertainty of DIR using statistical sampling techniques that can be applied to the resulting deformation vector fields (DVFs) for a given registration. The proposed DIR performance metric, the distance discordance metric (DDM), is based on the variability in the distance between corresponding voxels from different images, which are co-registered to the same voxel at location (X) in an arbitrarily chosen “reference” image. The DDM value, at location (X) in the reference image, represents the mean dispersion between voxels, when these images are registered to other images in the image set. The method requires at least four registered images to estimate the uncertainty of the DIRs, both for inter-and intra-patient DIR. To validate the proposed method, we generated an image set by deforming a software phantom with known DVFs. The registration error was computed at each voxel in the “reference” phantom and then compared to DDM, inverse consistency error (ICE), and transitivity error (TE) over the entire phantom. The DDM showed a higher Pearson correlation (Rp) with the actual error (Rp ranged from 0.6 to 0.9) in comparison with ICE and TE (Rp ranged from 0.2 to 0.8). In the resulting spatial DDM map, regions with distinct intensity gradients had a lower discordance and therefore, less variability relative to regions with uniform intensity. Subsequently, we applied DDM for intra-patient DIR in an image set of 10 longitudinal computed tomography (CT) scans of one prostate cancer patient and for inter-patient DIR in an image set of 10 planning CT scans of different head and neck cancer patients. For both intra- and inter-patient DIR, the spatial

  20. GOES I/M image navigation and registration

    NASA Technical Reports Server (NTRS)

    Fiorello, J. L., Jr.; Oh, I. H.; Kelly, K. A.; Ranne, L.

    1989-01-01

    Image Navigation and Registration (INR) is the system that will be used on future Geostationary Operational Environmental Satellite (GOES) missions to locate and register radiometric imagery data. It consists of a semiclosed loop system with a ground-based segment that generates coefficients to perform image motion compensation (IMC). The IMC coefficients are uplinked to the satellite-based segment, where they are used to adjust the displacement of the imagery data due to movement of the imaging instrument line-of-sight. The flight dynamics aspects of the INR system is discussed in terms of the attitude and orbit determination, attitude pointing, and attitude and orbit control needed to perform INR. The modeling used in the determination of orbit and attitude is discussed, along with the method of on-orbit control used in the INR system, and various factors that affect stability. Also discussed are potential error sources inherent in the INR system and the operational methods of compensating for these errors.

  1. 75 FR 52859 - Re-Registration and Renewal of Aircraft Registration; OMB Approval of Information Collection

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-08-30

    ... Aircraft Registration; OMB Approval of Information Collection AGENCY: Federal Aviation Administration, DOT... final rule, ``Re-Registration and Renewal of Aircraft Registration,'' which was published on July 20..., the FAA published the final rule, ``Re-Registration and Renewal of Aircraft Registration'' (75 FR...

  2. 75 FR 58292 - Re-Registration and Renewal of Aircraft Registration; OMB Approval of Information Collection...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-24

    ...-0188; Amdt. No. 47-29A] RIN 2120-AI89 Re-Registration and Renewal of Aircraft Registration; OMB... contained in the ``Re-Registration and Renewal of Aircraft Registration'' final rule. The final rule was... Renewal of Aircraft Registration'' (75 FR 41968). The final rule contained information collection...

  3. SU-E-J-114: A Practical Hybrid Method for Improving the Quality of CT-CBCT Deformable Image Registration for Head and Neck Radiotherapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Liu, C; Kumarasiri, A; Chetvertkov, M

    2015-06-15

    Purpose: Accurate deformable image registration (DIR) between CT and CBCT in H&N is challenging. In this study, we propose a practical hybrid method that uses not only the pixel intensities but also organ physical properties, structure volume of interest (VOI), and interactive local registrations. Methods: Five oropharyngeal cancer patients were selected retrospectively. For each patient, the planning CT was registered to the last fraction CBCT, where the anatomy difference was largest. A three step registration strategy was tested; Step1) DIR using pixel intensity only, Step2) DIR with additional use of structure VOI and rigidity penalty, and Step3) interactive local correction.more » For Step1, a public-domain open-source DIR algorithm was used (cubic B-spline, mutual information, steepest gradient optimization, and 4-level multi-resolution). For Step2, rigidity penalty was applied on bony anatomies and brain, and a structure VOI was used to handle the body truncation such as the shoulder cut-off on CBCT. Finally, in Step3, the registrations were reviewed on our in-house developed software and the erroneous areas were corrected via a local registration using level-set motion algorithm. Results: After Step1, there were considerable amount of registration errors in soft tissues and unrealistic stretching in the posterior to the neck and near the shoulder due to body truncation. The brain was also found deformed to a measurable extent near the superior border of CBCT. Such errors could be effectively removed by using a structure VOI and rigidity penalty. The rest of the local soft tissue error could be corrected using the interactive software tool. The estimated interactive correction time was approximately 5 minutes. Conclusion: The DIR using only the image pixel intensity was vulnerable to noise and body truncation. A corrective action was inevitable to achieve good quality of registrations. We found the proposed three-step hybrid method efficient and practical

  4. Targeted Next Generation Sequencing in Patients with Inborn Errors of Metabolism

    PubMed Central

    Yubero, Dèlia; Brandi, Núria; Ormazabal, Aida; Garcia-Cazorla, Àngels; Pérez-Dueñas, Belén; Campistol, Jaime; Ribes, Antonia; Palau, Francesc

    2016-01-01

    Background Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabolism (IEM). The final aim of the study was to compare the findings for the diagnostic yield of NGS in patients who presented with consistent clinical and biochemical suspicion of IEM with those obtained for patients who did not have specific biomarkers. Methods The subjects studied (n = 146) were classified into two categories: Group 1 (n = 81), which consisted of patients with clinical and biochemical suspicion of IEM, and Group 2 (n = 65), which consisted of IEM cases with clinical suspicion and unspecific biomarkers. A total of 171 genes were analyzed using a custom targeted panel of genes followed by Sanger validation. Results Genetic diagnosis was achieved in 50% of patients (73/146). In addition, the diagnostic yield obtained for Group 1 was 78% (63/81), and this rate decreased to 15.4% (10/65) in Group 2 (X2 = 76.171; p < 0.0001). Conclusions A rapid and effective genetic diagnosis was achieved in our cohort, particularly the group that had both clinical and biochemical indications for the diagnosis. PMID:27243974

  5. An accelerated image matching technique for UAV orthoimage registration

    NASA Astrophysics Data System (ADS)

    Tsai, Chung-Hsien; Lin, Yu-Ching

    2017-06-01

    Using an Unmanned Aerial Vehicle (UAV) drone with an attached non-metric camera has become a popular low-cost approach for collecting geospatial data. A well-georeferenced orthoimage is a fundamental product for geomatics professionals. To achieve high positioning accuracy of orthoimages, precise sensor position and orientation data, or a number of ground control points (GCPs), are often required. Alternatively, image registration is a solution for improving the accuracy of a UAV orthoimage, as long as a historical reference image is available. This study proposes a registration scheme, including an Accelerated Binary Robust Invariant Scalable Keypoints (ABRISK) algorithm and spatial analysis of corresponding control points for image registration. To determine a match between two input images, feature descriptors from one image are compared with those from another image. A "Sorting Ring" is used to filter out uncorrected feature pairs as early as possible in the stage of matching feature points, to speed up the matching process. The results demonstrate that the proposed ABRISK approach outperforms the vector-based Scale Invariant Feature Transform (SIFT) approach where radiometric variations exist. ABRISK is 19.2 times and 312 times faster than SIFT for image sizes of 1000 × 1000 pixels and 4000 × 4000 pixels, respectively. ABRISK is 4.7 times faster than Binary Robust Invariant Scalable Keypoints (BRISK). Furthermore, the positional accuracy of the UAV orthoimage after applying the proposed image registration scheme is improved by an average of root mean square error (RMSE) of 2.58 m for six test orthoimages whose spatial resolutions vary from 6.7 cm to 10.7 cm.

  6. Fast interactive elastic registration of 12-bit multi-spectral images with subvoxel accuracy using display hardware

    NASA Astrophysics Data System (ADS)

    Noordmans, Herke Jan; de Roode, Rowland; Verdaasdonk, Rudolf

    2007-03-01

    Multi-spectral images of human tissue taken in-vivo often contain image alignment problems as patients have difficulty in retaining their posture during the acquisition time of 20 seconds. Previously, it has been attempted to correct motion errors with image registration software developed for MR or CT data but these algorithms have been proven to be too slow and erroneous for practical use with multi-spectral images. A new software package has been developed which allows the user to play a decisive role in the registration process as the user can monitor the progress of the registration continuously and force it in the right direction when it starts to fail. The software efficiently exploits videocard hardware to gain speed and to provide a perfect subvoxel correspondence between registration field and display. An 8 bit graphic card was used to efficiently register and resample 12 bit images using the hardware interpolation modes present on the graphic card. To show the feasibility of this new registration process, the software was applied in clinical practice evaluating the dosimetry for psoriasis and KTP laser treatment. The microscopic differences between images of normal skin and skin exposed to UV light proved that an affine registration step including zooming and slanting is critical for a subsequent elastic match to have success. The combination of user interactive registration software with optimal addressing the potentials of PC video card hardware greatly improves the speed of multi spectral image registration.

  7. 28 CFR 12.3 - Prior registration with the Foreign Agents Registration Unit.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 28 Judicial Administration 1 2013-07-01 2013-07-01 false Prior registration with the Foreign Agents Registration Unit. 12.3 Section 12.3 Judicial Administration DEPARTMENT OF JUSTICE REGISTRATION OF CERTAIN PERSONS HAVING KNOWLEDGE OF FOREIGN ESPIONAGE, COUNTERESPIONAGE, OR SABOTAGE MATTERS UNDER THE ACT...

  8. 28 CFR 12.3 - Prior registration with the Foreign Agents Registration Unit.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 28 Judicial Administration 1 2014-07-01 2014-07-01 false Prior registration with the Foreign Agents Registration Unit. 12.3 Section 12.3 Judicial Administration DEPARTMENT OF JUSTICE REGISTRATION OF CERTAIN PERSONS HAVING KNOWLEDGE OF FOREIGN ESPIONAGE, COUNTERESPIONAGE, OR SABOTAGE MATTERS UNDER THE ACT...

  9. 28 CFR 12.3 - Prior registration with the Foreign Agents Registration Unit.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Prior registration with the Foreign Agents Registration Unit. 12.3 Section 12.3 Judicial Administration DEPARTMENT OF JUSTICE REGISTRATION OF CERTAIN PERSONS HAVING KNOWLEDGE OF FOREIGN ESPIONAGE, COUNTERESPIONAGE, OR SABOTAGE MATTERS UNDER THE ACT...

  10. 28 CFR 12.3 - Prior registration with the Foreign Agents Registration Unit.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 28 Judicial Administration 1 2011-07-01 2011-07-01 false Prior registration with the Foreign Agents Registration Unit. 12.3 Section 12.3 Judicial Administration DEPARTMENT OF JUSTICE REGISTRATION OF CERTAIN PERSONS HAVING KNOWLEDGE OF FOREIGN ESPIONAGE, COUNTERESPIONAGE, OR SABOTAGE MATTERS UNDER THE ACT...

  11. 28 CFR 12.3 - Prior registration with the Foreign Agents Registration Unit.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 28 Judicial Administration 1 2012-07-01 2012-07-01 false Prior registration with the Foreign Agents Registration Unit. 12.3 Section 12.3 Judicial Administration DEPARTMENT OF JUSTICE REGISTRATION OF CERTAIN PERSONS HAVING KNOWLEDGE OF FOREIGN ESPIONAGE, COUNTERESPIONAGE, OR SABOTAGE MATTERS UNDER THE ACT...

  12. Registration using natural features for augmented reality systems.

    PubMed

    Yuan, M L; Ong, S K; Nee, A Y C

    2006-01-01

    Registration is one of the most difficult problems in augmented reality (AR) systems. In this paper, a simple registration method using natural features based on the projective reconstruction technique is proposed. This method consists of two steps: embedding and rendering. Embedding involves specifying four points to build the world coordinate system on which a virtual object will be superimposed. In rendering, the Kanade-Lucas-Tomasi (KLT) feature tracker is used to track the natural feature correspondences in the live video. The natural features that have been tracked are used to estimate the corresponding projective matrix in the image sequence. Next, the projective reconstruction technique is used to transfer the four specified points to compute the registration matrix for augmentation. This paper also proposes a robust method for estimating the projective matrix, where the natural features that have been tracked are normalized (translation and scaling) and used as the input data. The estimated projective matrix will be used as an initial estimate for a nonlinear optimization method that minimizes the actual residual errors based on the Levenberg-Marquardt (LM) minimization method, thus making the results more robust and stable. The proposed registration method has three major advantages: 1) It is simple, as no predefined fiducials or markers are used for registration for either indoor and outdoor AR applications. 2) It is robust, because it remains effective as long as at least six natural features are tracked during the entire augmentation, and the existence of the corresponding projective matrices in the live video is guaranteed. Meanwhile, the robust method to estimate the projective matrix can obtain stable results even when there are some outliers during the tracking process. 3) Virtual objects can still be superimposed on the specified areas, even if some parts of the areas are occluded during the entire process. Some indoor and outdoor experiments have

  13. Robust non-rigid registration algorithm based on local affine registration

    NASA Astrophysics Data System (ADS)

    Wu, Liyang; Xiong, Lei; Du, Shaoyi; Bi, Duyan; Fang, Ting; Liu, Kun; Wu, Dongpeng

    2018-04-01

    Aiming at the problem that the traditional point set non-rigid registration algorithm has low precision and slow convergence speed for complex local deformation data, this paper proposes a robust non-rigid registration algorithm based on local affine registration. The algorithm uses a hierarchical iterative method to complete the point set non-rigid registration from coarse to fine. In each iteration, the sub data point sets and sub model point sets are divided and the shape control points of each sub point set are updated. Then we use the control point guided affine ICP algorithm to solve the local affine transformation between the corresponding sub point sets. Next, the local affine transformation obtained by the previous step is used to update the sub data point sets and their shape control point sets. When the algorithm reaches the maximum iteration layer K, the loop ends and outputs the updated sub data point sets. Experimental results demonstrate that the accuracy and convergence of our algorithm are greatly improved compared with the traditional point set non-rigid registration algorithms.

  14. Modeling patterns of anatomical deformations in prostate patients undergoing radiation therapy with an endorectal balloon

    NASA Astrophysics Data System (ADS)

    Brion, Eliott; Richter, Christian; Macq, Benoit; Stützer, Kristin; Exner, Florian; Troost, Esther; Hölscher, Tobias; Bondar, Luiza

    2017-03-01

    External beam radiation therapy (EBRT) treats cancer by delivering daily fractions of radiation to a target volume. For prostate cancer, the target undergoes day-to-day variations in position, volume, and shape. For stereotactic photon and for proton EBRT, endorectal balloons (ERBs) can be used to limit variations. To date, patterns of non-rigid variations for patients with ERB have not been modeled. We extracted and modeled the patient-specific patterns of variations, using regularly acquired CT-images, non-rigid point cloud registration, and principal component analysis (PCA). For each patient, a non-rigid point-set registration method, called Coherent Point Drift, (CPD) was used to automatically generate landmark correspondences between all target shapes. To ensure accurate registrations, we tested and validated CPD by identifying parameter values leading to the smallest registration errors (surface matching error 0.13+/-0.09 mm). PCA demonstrated that 88+/-3.2% of the target motion could be explained using only 4 principal modes. The most dominant component of target motion is a squeezing and stretching in the anterior-posterior and superior-inferior directions. A PCA model of daily landmark displacements, generated using 6 to 10 CT-scans, could explain well the target motion for the CT-scans not included in the model (modeling error decreased from 1.83+/-0.8 mm for 6 CT-scans to 1.6+/-0.7 mm for 10 CT-scans). PCA modeling error was smaller than the naive approximation by the mean shape (approximation error 2.66+/-0.59 mm). Future work will investigate the use of the PCA-model to improve the accuracy of EBRT techniques that are highly susceptible to anatomical variations such as, proton therapy

  15. Accurate and ergonomic method of registration for image-guided neurosurgery

    NASA Astrophysics Data System (ADS)

    Henderson, Jaimie M.; Bucholz, Richard D.

    1994-05-01

    There has been considerable interest in the development of frameless stereotaxy based upon scalp mounted fiducials. In practice we have experienced difficulty in relating markers to the image data sets in our series of 25 frameless cases, as well as inaccuracy due to scalp movement and the size of the markers. We have developed an alternative system for accurately and conveniently achieving surgical registration for image-guided neurosurgery based on alignment and matching of patient forehead contours. The system consists of a laser contour digitizer which is used in the operating room to acquire forehead contours, editing software for extracting contours from patient image data sets, and a contour-match algorithm for aligning the two contours and performing data set registration. The contour digitizer is tracked by a camera array which relates its position with respect to light emitting diodes placed on the head clamp. Once registered, surgical instrument can be tracked throughout the procedure. Contours can be extracted from either CT or MRI image datasets. The system has proven to be robust in the laboratory setting. Overall error of registration is 1 - 2 millimeters in routine use. Image to patient registration can therefore be achieved quite easily and accurately, without the need for fixation of external markers to the skull, or manually finding markers on the scalp and image datasets. The system is unobtrusive and imposes little additional effort on the neurosurgeon, broadening the appeal of image-guided surgery.

  16. A Robust False Matching Points Detection Method for Remote Sensing Image Registration

    NASA Astrophysics Data System (ADS)

    Shan, X. J.; Tang, P.

    2015-04-01

    Given the influences of illumination, imaging angle, and geometric distortion, among others, false matching points still occur in all image registration algorithms. Therefore, false matching points detection is an important step in remote sensing image registration. Random Sample Consensus (RANSAC) is typically used to detect false matching points. However, RANSAC method cannot detect all false matching points in some remote sensing images. Therefore, a robust false matching points detection method based on Knearest- neighbour (K-NN) graph (KGD) is proposed in this method to obtain robust and high accuracy result. The KGD method starts with the construction of the K-NN graph in one image. K-NN graph can be first generated for each matching points and its K nearest matching points. Local transformation model for each matching point is then obtained by using its K nearest matching points. The error of each matching point is computed by using its transformation model. Last, L matching points with largest error are identified false matching points and removed. This process is iterative until all errors are smaller than the given threshold. In addition, KGD method can be used in combination with other methods, such as RANSAC. Several remote sensing images with different resolutions and terrains are used in the experiment. We evaluate the performance of KGD method, RANSAC + KGD method, RANSAC, and Graph Transformation Matching (GTM). The experimental results demonstrate the superior performance of the KGD and RANSAC + KGD methods.

  17. Targeted endomyocardial injections of therapeutic cells using x-ray fused with MRI guidance

    NASA Astrophysics Data System (ADS)

    Gutiérrez, Luis F.; de Silva, Ranil; McVeigh, Elliot R.; Ozturk, Cengizhan; Lederman, Robert J.

    2006-03-01

    The utility of X-ray fused with MRI (XFM) using external fiducial markers to perform targeted endomyocardial injections in infarcted hearts of swine was tested. Endomyocardial injections of feridex-labeled mesenchymal stromal cells (Fe-MSC) were performed in the previously infarcted hearts of 12 Yucatan miniswine (33-67 kg). Animals had pre-injection cardiac MRI, XFM-guided endomyocardial injection of Fe-MSC suspension spiked with tissue dye, and post-injection MRI. 24 hours later, after euthanasia, the hearts were excised, sliced and stained with TTC. During the injection procedure, operators were provided with 3D surfaces of endocardium, epicardium, myocardial wall thickness and infarct registered with live XF images to facilitate device navigation and choice of injection location. 130 injections were performed in hearts where diastolic wall thickness ranged from 2.6 to 17.7 mm. Visual inspection of the pattern of dye staining on TTC stained heart slices correlated (r=0.98) with XFM-derived injection locations mapped onto delayed hyperenhancement MRI and the susceptibility artifacts seen on the post-injection T2*-weighted gradient echo MRI. The in vivo target registration error was 3.17+/-2.61 mm (n=64) and 75% of injections were within 4 mm of the predicted location. 3D to 2D registration of XF and MR images using external fiducial markers enables accurate targeted endomyocardial injection in a swine model of myocardial infarction. The present data suggest that the safety and efficacy of this approach for performing targeted endomyocardial delivery should be evaluated further clinically.

  18. 16 CFR 1130.8 - Requirements for Web site registration or alternative e-mail registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 16 Commercial Practices 2 2010-01-01 2010-01-01 false Requirements for Web site registration or... PRODUCTS (Eff. June 28, 2010) § 1130.8 Requirements for Web site registration or alternative e-mail registration. (a) Link to registration page. The manufacturer's Web site, or other Web site established for the...

  19. High School Voter Registration.

    ERIC Educational Resources Information Center

    Institute for Political/Legal Education, Sewell, NJ.

    Methods for conducting peer voter registration of high school students cover establishing a permanent voter registration committee and identifying and registering eligible students. The permanent voter registration committee, made up of student body representatives, class representatives, and selected teachers, guarantees comprehensive…

  20. Motion compensation for MRI-compatible patient-mounted needle guide device: estimation of targeting accuracy in MRI-guided kidney cryoablations

    NASA Astrophysics Data System (ADS)

    Tokuda, Junichi; Chauvin, Laurent; Ninni, Brian; Kato, Takahisa; King, Franklin; Tuncali, Kemal; Hata, Nobuhiko

    2018-04-01

    Patient-mounted needle guide devices for percutaneous ablation are vulnerable to patient motion. The objective of this study is to develop and evaluate a software system for an MRI-compatible patient-mounted needle guide device that can adaptively compensate for displacement of the device due to patient motion using a novel image-based automatic device-to-image registration technique. We have developed a software system for an MRI-compatible patient-mounted needle guide device for percutaneous ablation. It features fully-automated image-based device-to-image registration to track the device position, and a device controller to adjust the needle trajectory to compensate for the displacement of the device. We performed: (a) a phantom study using a clinical MR scanner to evaluate registration performance; (b) simulations using intraoperative time-series MR data acquired in 20 clinical cases of MRI-guided renal cryoablations to assess its impact on motion compensation; and (c) a pilot clinical study in three patients to test its feasibility during the clinical procedure. FRE, TRE, and success rate of device-to-image registration were mm, mm, and 98.3% for the phantom images. The simulation study showed that the motion compensation reduced the targeting error for needle placement from 8.2 mm to 5.4 mm (p  <  0.0005) in patients under general anesthesia (GA), and from 14.4 mm to 10.0 mm () in patients under monitored anesthesia care (MAC). The pilot study showed that the software registered the device successfully in a clinical setting. Our simulation study demonstrated that the software system could significantly improve targeting accuracy in patients treated under both MAC and GA. Intraprocedural image-based device-to-image registration was feasible.

  1. Landmark-based elastic registration using approximating thin-plate splines.

    PubMed

    Rohr, K; Stiehl, H S; Sprengel, R; Buzug, T M; Weese, J; Kuhn, M H

    2001-06-01

    We consider elastic image registration based on a set of corresponding anatomical point landmarks and approximating thin-plate splines. This approach is an extension of the original interpolating thin-plate spline approach and allows to take into account landmark localization errors. The extension is important for clinical applications since landmark extraction is always prone to error. Our approach is based on a minimizing functional and can cope with isotropic as well as anisotropic landmark errors. In particular, in the latter case it is possible to include different types of landmarks, e.g., unique point landmarks as well as arbitrary edge points. Also, the scheme is general with respect to the image dimension and the order of smoothness of the underlying functional. Optimal affine transformations as well as interpolating thin-plate splines are special cases of this scheme. To localize landmarks we use a semi-automatic approach which is based on three-dimensional (3-D) differential operators. Experimental results are presented for two-dimensional as well as 3-D tomographic images of the human brain.

  2. Design and Error Analysis of a Vehicular AR System with Auto-Harmonization.

    PubMed

    Foxlin, Eric; Calloway, Thomas; Zhang, Hongsheng

    2015-12-01

    This paper describes the design, development and testing of an AR system that was developed for aerospace and ground vehicles to meet stringent accuracy and robustness requirements. The system uses an optical see-through HMD, and thus requires extremely low latency, high tracking accuracy and precision alignment and calibration of all subsystems in order to avoid mis-registration and "swim". The paper focuses on the optical/inertial hybrid tracking system and describes novel solutions to the challenges with the optics, algorithms, synchronization, and alignment with the vehicle and HMD systems. Tracker accuracy is presented with simulation results to predict the registration accuracy. A car test is used to create a through-the-eyepiece video demonstrating well-registered augmentations of the road and nearby structures while driving. Finally, a detailed covariance analysis of AR registration error is derived.

  3. Dense image registration through MRFs and efficient linear programming.

    PubMed

    Glocker, Ben; Komodakis, Nikos; Tziritas, Georgios; Navab, Nassir; Paragios, Nikos

    2008-12-01

    In this paper, we introduce a novel and efficient approach to dense image registration, which does not require a derivative of the employed cost function. In such a context, the registration problem is formulated using a discrete Markov random field objective function. First, towards dimensionality reduction on the variables we assume that the dense deformation field can be expressed using a small number of control points (registration grid) and an interpolation strategy. Then, the registration cost is expressed using a discrete sum over image costs (using an arbitrary similarity measure) projected on the control points, and a smoothness term that penalizes local deviations on the deformation field according to a neighborhood system on the grid. Towards a discrete approach, the search space is quantized resulting in a fully discrete model. In order to account for large deformations and produce results on a high resolution level, a multi-scale incremental approach is considered where the optimal solution is iteratively updated. This is done through successive morphings of the source towards the target image. Efficient linear programming using the primal dual principles is considered to recover the lowest potential of the cost function. Very promising results using synthetic data with known deformations and real data demonstrate the potentials of our approach.

  4. A reference dataset for deformable image registration spatial accuracy evaluation using the COPDgene study archive

    NASA Astrophysics Data System (ADS)

    Castillo, Richard; Castillo, Edward; Fuentes, David; Ahmad, Moiz; Wood, Abbie M.; Ludwig, Michelle S.; Guerrero, Thomas

    2013-05-01

    Landmark point-pairs provide a strategy to assess deformable image registration (DIR) accuracy in terms of the spatial registration of the underlying anatomy depicted in medical images. In this study, we propose to augment a publicly available database (www.dir-lab.com) of medical images with large sets of manually identified anatomic feature pairs between breath-hold computed tomography (BH-CT) images for DIR spatial accuracy evaluation. Ten BH-CT image pairs were randomly selected from the COPDgene study cases. Each patient had received CT imaging of the entire thorax in the supine position at one-fourth dose normal expiration and maximum effort full dose inspiration. Using dedicated in-house software, an imaging expert manually identified large sets of anatomic feature pairs between images. Estimates of inter- and intra-observer spatial variation in feature localization were determined by repeat measurements of multiple observers over subsets of randomly selected features. 7298 anatomic landmark features were manually paired between the 10 sets of images. Quantity of feature pairs per case ranged from 447 to 1172. Average 3D Euclidean landmark displacements varied substantially among cases, ranging from 12.29 (SD: 6.39) to 30.90 (SD: 14.05) mm. Repeat registration of uniformly sampled subsets of 150 landmarks for each case yielded estimates of observer localization error, which ranged in average from 0.58 (SD: 0.87) to 1.06 (SD: 2.38) mm for each case. The additions to the online web database (www.dir-lab.com) described in this work will broaden the applicability of the reference data, providing a freely available common dataset for targeted critical evaluation of DIR spatial accuracy performance in multiple clinical settings. Estimates of observer variance in feature localization suggest consistent spatial accuracy for all observers across both four-dimensional CT and COPDgene patient cohorts.

  5. 14 CFR 47.43 - Invalid registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... REGISTRATION Certificates of Aircraft Registration § 47.43 Invalid registration. (a) The registration of an...) compliance with 49 U.S.C. 44101-44104. (b) If the registration of an aircraft is invalid under paragraph (a) of this section, the holder of the invalid Certificate of Aircraft Registration shall return it as...

  6. 21 CFR 1301.52 - Termination of registration; transfer of registration; distribution upon discontinuance of business.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... discontinues business or professional practice. Any registrant who ceases legal existence or discontinues... registration; distribution upon discontinuance of business. 1301.52 Section 1301.52 Food and Drugs DRUG... of registration; transfer of registration; distribution upon discontinuance of business. (a) Except...

  7. 14 CFR 47.43 - Invalid registration.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... REGISTRATION Certificates of Aircraft Registration § 47.43 Invalid registration. (a) The registration of an...) compliance with 49 U.S.C. 44101-44104. (b) If the registration of an aircraft is invalid under paragraph (a) of this section, the holder of the invalid Certificate of Aircraft Registration, AC Form 8050-3, must...

  8. 14 CFR 47.43 - Invalid registration.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... REGISTRATION Certificates of Aircraft Registration § 47.43 Invalid registration. (a) The registration of an...) compliance with 49 U.S.C. 44101-44104. (b) If the registration of an aircraft is invalid under paragraph (a) of this section, the holder of the invalid Certificate of Aircraft Registration, AC Form 8050-3, must...

  9. Automatic registration of panoramic image sequence and mobile laser scanning data using semantic features

    NASA Astrophysics Data System (ADS)

    Li, Jianping; Yang, Bisheng; Chen, Chi; Huang, Ronggang; Dong, Zhen; Xiao, Wen

    2018-02-01

    Inaccurate exterior orientation parameters (EoPs) between sensors obtained by pre-calibration leads to failure of registration between panoramic image sequence and mobile laser scanning data. To address this challenge, this paper proposes an automatic registration method based on semantic features extracted from panoramic images and point clouds. Firstly, accurate rotation parameters between the panoramic camera and the laser scanner are estimated using GPS and IMU aided structure from motion (SfM). The initial EoPs of panoramic images are obtained at the same time. Secondly, vehicles in panoramic images are extracted by the Faster-RCNN as candidate primitives to be matched with potential corresponding primitives in point clouds according to the initial EoPs. Finally, translation between the panoramic camera and the laser scanner is refined by maximizing the overlapping area of corresponding primitive pairs based on the Particle Swarm Optimization (PSO), resulting in a finer registration between panoramic image sequences and point clouds. Two challenging urban scenes were experimented to assess the proposed method, and the final registration errors of these two scenes were both less than three pixels, which demonstrates a high level of automation, robustness and accuracy.

  10. Estimation of error in maximal intensity projection-based internal target volume of lung tumors: a simulation and comparison study using dynamic magnetic resonance imaging.

    PubMed

    Cai, Jing; Read, Paul W; Baisden, Joseph M; Larner, James M; Benedict, Stanley H; Sheng, Ke

    2007-11-01

    To evaluate the error in four-dimensional computed tomography (4D-CT) maximal intensity projection (MIP)-based lung tumor internal target volume determination using a simulation method based on dynamic magnetic resonance imaging (dMRI). Eight healthy volunteers and six lung tumor patients underwent a 5-min MRI scan in the sagittal plane to acquire dynamic images of lung motion. A MATLAB program was written to generate re-sorted dMRI using 4D-CT acquisition methods (RedCAM) by segmenting and rebinning the MRI scans. The maximal intensity projection images were generated from RedCAM and dMRI, and the errors in the MIP-based internal target area (ITA) from RedCAM (epsilon), compared with those from dMRI, were determined and correlated with the subjects' respiratory variability (nu). Maximal intensity projection-based ITAs from RedCAM were comparatively smaller than those from dMRI in both phantom studies (epsilon = -21.64% +/- 8.23%) and lung tumor patient studies (epsilon = -20.31% +/- 11.36%). The errors in MIP-based ITA from RedCAM correlated linearly (epsilon = -5.13nu - 6.71, r(2) = 0.76) with the subjects' respiratory variability. Because of the low temporal resolution and retrospective re-sorting, 4D-CT might not accurately depict the excursion of a moving tumor. Using a 4D-CT MIP image to define the internal target volume might therefore cause underdosing and an increased risk of subsequent treatment failure. Patient-specific respiratory variability might also be a useful predictor of the 4D-CT-induced error in MIP-based internal target volume determination.

  11. Fluid Registration of Diffusion Tensor Images Using Information Theory

    PubMed Central

    Chiang, Ming-Chang; Leow, Alex D.; Klunder, Andrea D.; Dutton, Rebecca A.; Barysheva, Marina; Rose, Stephen E.; McMahon, Katie L.; de Zubicaray, Greig I.; Toga, Arthur W.; Thompson, Paul M.

    2008-01-01

    We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data. PMID:18390342

  12. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... registration card or other method of registration prescribed by the Director of Selective Service by a person... method of registration prescribed by the Director, he shall advise in writing the Selective Service System, P.O. Box 94638, Palatine, IL 60094-4638. (c) The methods of registration prescribed by the...

  13. Fundamental limits of image registration performance: Effects of image noise and resolution in CT-guided interventions.

    PubMed

    Ketcha, M D; de Silva, T; Han, R; Uneri, A; Goerres, J; Jacobson, M; Vogt, S; Kleinszig, G; Siewerdsen, J H

    2017-02-11

    In image-guided procedures, image acquisition is often performed primarily for the task of geometrically registering information from another image dataset, rather than detection / visualization of a particular feature. While the ability to detect a particular feature in an image has been studied extensively with respect to image quality characteristics (noise, resolution) and is an ongoing, active area of research, comparatively little has been accomplished to relate such image quality characteristics to registration performance. To establish such a framework, we derived Cramer-Rao lower bounds (CRLB) for registration accuracy, revealing the underlying dependencies on image variance and gradient strength. The CRLB was analyzed as a function of image quality factors (in particular, dose) for various similarity metrics and compared to registration accuracy using CT images of an anthropomorphic head phantom at various simulated dose levels. Performance was evaluated in terms of root mean square error (RMSE) of the registration parameters. Analysis of the CRLB shows two primary dependencies: 1) noise variance (related to dose); and 2) sum of squared image gradients (related to spatial resolution and image content). Comparison of the measured RMSE to the CRLB showed that the best registration method, RMSE achieved the CRLB to within an efficiency factor of 0.21, and optimal estimators followed the predicted inverse proportionality between registration performance and radiation dose. Analysis of the CRLB for image registration is an important step toward understanding and evaluating an intraoperative imaging system with respect to a registration task. While the CRLB is optimistic in absolute performance, it reveals a basis for relating the performance of registration estimators as a function of noise content and may be used to guide acquisition parameter selection (e.g., dose) for purposes of intraoperative registration.

  14. Intraoperative evaluation of device placement in spine surgery using known-component 3D-2D image registration

    NASA Astrophysics Data System (ADS)

    Uneri, A.; De Silva, T.; Goerres, J.; Jacobson, M. W.; Ketcha, M. D.; Reaungamornrat, S.; Kleinszig, G.; Vogt, S.; Khanna, A. J.; Osgood, G. M.; Wolinsky, J.-P.; Siewerdsen, J. H.

    2017-04-01

    Intraoperative x-ray radiography/fluoroscopy is commonly used to assess the placement of surgical devices in the operating room (e.g. spine pedicle screws), but qualitative interpretation can fail to reliably detect suboptimal delivery and/or breach of adjacent critical structures. We present a 3D-2D image registration method wherein intraoperative radiographs are leveraged in combination with prior knowledge of the patient and surgical components for quantitative assessment of device placement and more rigorous quality assurance (QA) of the surgical product. The algorithm is based on known-component registration (KC-Reg) in which patient-specific preoperative CT and parametric component models are used. The registration performs optimization of gradient similarity, removes the need for offline geometric calibration of the C-arm, and simultaneously solves for multiple component bodies, thereby allowing QA in a single step (e.g. spinal construct with 4-20 screws). Performance was tested in a spine phantom, and first clinical results are reported for QA of transpedicle screws delivered in a patient undergoing thoracolumbar spine surgery. Simultaneous registration of ten pedicle screws (five contralateral pairs) demonstrated mean target registration error (TRE) of 1.1  ±  0.1 mm at the screw tip and 0.7  ±  0.4° in angulation when a prior geometric calibration was used. The calibration-free formulation, with the aid of component collision constraints, achieved TRE of 1.4  ±  0.6 mm. In all cases, a statistically significant improvement (p  <  0.05) was observed for the simultaneous solutions in comparison to previously reported sequential solution of individual components. Initial application in clinical data in spine surgery demonstrated TRE of 2.7  ±  2.6 mm and 1.5  ±  0.8°. The KC-Reg algorithm offers an independent check and quantitative QA of the surgical product using radiographic/fluoroscopic views

  15. Petition for Rulemaking to Evaluate Synergestic Effects of Pesticides during Registration and Registration Review

    EPA Pesticide Factsheets

    This petition from the Center for Biological Diversity asks that the Agency require all applicants and registrants to provide data on the potential synergistic effects of pesticides during the registration and registration review processes.

  16. A quantitative comparison of the performance of three deformable registration algorithms in radiotherapy

    PubMed Central

    Fabri, Daniella; Zambrano, Valentina; Bhatia, Amon; Furtado, Hugo; Bergmann, Helmar; Stock, Markus; Bloch, Christoph; Lütgendorf-Caucig, Carola; Pawiro, Supriyanto; Georg, Dietmar; Birkfellner, Wolfgang; Figl, Michael

    2013-01-01

    We present an evaluation of various non-rigid registration algorithms for the purpose of compensating interfractional motion of the target volume and organs at risk areas when acquiring CBCT image data prior to irradiation. Three different deformable registration (DR) methods were used: the Demons algorithm implemented in the iPlan Software (BrainLAB AG, Feldkirchen, Germany) and two custom-developed piecewise methods using either a Normalized Correlation or a Mutual Information metric (featureletNC and featureletMI). These methods were tested on data acquired using a novel purpose-built phantom for deformable registration and clinical CT/CBCT data of prostate and lung cancer patients. The Dice similarity coefficient (DSC) between manually drawn contours and the contours generated by a derived deformation field of the structures in question was compared to the result obtained with rigid registration (RR). For the phantom, the piecewise methods were slightly superior, the featureletNC for the intramodality and the featureletMI for the intermodality registrations. For the prostate cases in less than 50% of the images studied the DSC was improved over RR. Deformable registration methods improved the outcome over a rigid registration for lung cases and in the phantom study, but not in a significant way for the prostate study. A significantly superior deformation method could not be identified. PMID:23969092

  17. Feature-based pairwise retinal image registration by radial distortion correction

    NASA Astrophysics Data System (ADS)

    Lee, Sangyeol; Abràmoff, Michael D.; Reinhardt, Joseph M.

    2007-03-01

    Fundus camera imaging is widely used to document disorders such as diabetic retinopathy and macular degeneration. Multiple retinal images can be combined together through a procedure known as mosaicing to form an image with a larger field of view. Mosaicing typically requires multiple pairwise registrations of partially overlapped images. We describe a new method for pairwise retinal image registration. The proposed method is unique in that the radial distortion due to image acquisition is corrected prior to the geometric transformation. Vessel lines are detected using the Hessian operator and are used as input features to the registration. Since the overlapping region is typically small in a retinal image pair, only a few correspondences are available, thus limiting the applicable model to an afine transform at best. To recover the distortion due to curved-surface of retina and lens optics, a combined approach of an afine model with a radial distortion correction is proposed. The parameters of the image acquisition and radial distortion models are estimated during an optimization step that uses Powell's method driven by the vessel line distance. Experimental results using 20 pairs of green channel images acquired from three subjects with a fundus camera confirmed that the afine model with distortion correction could register retinal image pairs to within 1.88+/-0.35 pixels accuracy (mean +/- standard deviation) assessed by vessel line error, which is 17% better than the afine-only approach. Because the proposed method needs only two correspondences, it can be applied to obtain good registration accuracy even in the case of small overlap between retinal image pairs.

  18. SU-E-J-119: What Effect Have the Volume Defined in the Alignment Clipbox for Cervical Cancer Using Automatic Registration Methods for Cone- Beam CT Verification?

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wang, W; Yang, H; Wang, Y

    2014-06-01

    Purpose: To investigate the impact of different clipbox volumes with automated registration techniques using commercially available software with on board volumetric imaging(OBI) for treatment verification in cervical cancer patients. Methods: Fifty cervical cancer patients received daily CBCT scans(on-board imaging v1.5 system, Varian Medical Systems) during the first treatment week and weekly thereafter were included this analysis. A total of 450 CBCT scans were registered to the planning CTscan using pelvic clipbox(clipbox-Pelvic) and around PTV clip box(clipbox- PTV). The translations(anterior-posterior, left-right, superior-inferior) and the rotations(yaw, pitch and roll) errors for each matches were recorded. The setup errors and the systematic andmore » random errors for both of the clip-boxes were calculated. Paired Samples t test was used to analysis the differences between clipbox-Pelvic and clipbox-PTV. Results: . The SD of systematic error(σ) was 1.0mm, 2.0mm,3.2mm and 1.9mm,2.3mm, 3.0mm in the AP, LR and SI directions for clipbox-Pelvic and clipbox-PTV, respectively. The average random error(Σ)was 1.7mm, 2.0mm,4.2mm and 1.7mm,3.4mm, 4.4mm in the AP, LR and SI directions for clipbox-Pelvic and clipbox-PTV, respectively. But, only the SI direction was acquired significantly differences between two image registration volumes(p=0.002,p=0.01 for mean and SD). For rotations, the yaw mean/SD and the pitch SD were acquired significantly differences between clipbox-Pelvic and clipbox-PTV. Conclusion: The defined volume for Image registration is important for cervical cancer when 3D/3D match was used. The alignment clipbox can effect the setup errors obtained. Further analysis is need to determine the optimal defined volume to use the image registration in cervical cancer. Conflict of interest: none.« less

  19. Multiscale registration algorithm for alignment of meshes

    NASA Astrophysics Data System (ADS)

    Vadde, Srikanth; Kamarthi, Sagar V.; Gupta, Surendra M.

    2004-03-01

    Taking a multi-resolution approach, this research work proposes an effective algorithm for aligning a pair of scans obtained by scanning an object's surface from two adjacent views. This algorithm first encases each scan in the pair with an array of cubes of equal and fixed size. For each scan in the pair a surrogate scan is created by the centroids of the cubes that encase the scan. The Gaussian curvatures of points across the surrogate scan pair are compared to find the surrogate corresponding points. If the difference between the Gaussian curvatures of any two points on the surrogate scan pair is less than a predetermined threshold, then those two points are accepted as a pair of surrogate corresponding points. The rotation and translation values between the surrogate scan pair are determined by using a set of surrogate corresponding points. Using the same rotation and translation values the original scan pairs are aligned. The resulting registration (or alignment) error is computed to check the accuracy of the scan alignment. When the registration error becomes acceptably small, the algorithm is terminated. Otherwise the above process is continued with cubes of smaller and smaller sizes until the algorithm is terminated. However at each finer resolution the search space for finding the surrogate corresponding points is restricted to the regions in the neighborhood of the surrogate points that were at found at the preceding coarser level. The surrogate corresponding points, as the resolution becomes finer and finer, converge to the true corresponding points on the original scans. This approach offers three main benefits: it improves the chances of finding the true corresponding points on the scans, minimize the adverse effects of noise in the scans, and reduce the computational load for finding the corresponding points.

  20. Off-Campus Registration Procedures.

    ERIC Educational Resources Information Center

    Maas, Michael L.

    Registration is one of the more critical functions that a college staff encounters each semester. To have a smooth, efficient, college-wide registration, it is essential that all segments of the college be aware of registration procedures as well as data control operations. This packet was designed to acquaint interested parties with the…