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Sample records for 3d image registration

  1. Practical pseudo-3D registration for large tomographic images

    NASA Astrophysics Data System (ADS)

    Liu, Xuan; Laperre, Kjell; Sasov, Alexander

    2014-09-01

    Image registration is a powerful tool in various tomographic applications. Our main focus is on microCT applications in which samples/animals can be scanned multiple times under different conditions or at different time points. For this purpose, a registration tool capable of handling fairly large volumes has been developed, using a novel pseudo-3D method to achieve fast and interactive registration with simultaneous 3D visualization. To reduce computation complexity in 3D registration, we decompose it into several 2D registrations, which are applied to the orthogonal views (transaxial, sagittal and coronal) sequentially and iteratively. After registration in each view, the next view is retrieved with the new transformation matrix for registration. This reduces the computation complexity significantly. For rigid transform, we only need to search for 3 parameters (2 shifts, 1 rotation) in each of the 3 orthogonal views instead of 6 (3 shifts, 3 rotations) for full 3D volume. In addition, the amount of voxels involved is also significantly reduced. For the proposed pseudo-3D method, image-based registration is employed, with Sum of Square Difference (SSD) as the similarity measure. The searching engine is Powell's conjugate direction method. In this paper, only rigid transform is used. However, it can be extended to affine transform by adding scaling and possibly shearing to the transform model. We have noticed that more information can be used in the 2D registration if Maximum Intensity Projections (MIP) or Parallel Projections (PP) is used instead of the orthogonal views. Also, other similarity measures, such as covariance or mutual information, can be easily incorporated. The initial evaluation on microCT data shows very promising results. Two application examples are shown: dental samples before and after treatment and structural changes in materials before and after compression. Evaluation on registration accuracy between pseudo-3D method and true 3D method has

  2. Fast 3D fluid registration of brain magnetic resonance images

    NASA Astrophysics Data System (ADS)

    Leporé, Natasha; Chou, Yi-Yu; Lopez, Oscar L.; Aizenstein, Howard J.; Becker, James T.; Toga, Arthur W.; Thompson, Paul M.

    2008-03-01

    Fluid registration is widely used in medical imaging to track anatomical changes, to correct image distortions, and to integrate multi-modality data. Fluid mappings guarantee that the template image deforms smoothly into the target, without tearing or folding, even when large deformations are required for accurate matching. Here we implemented an intensity-based fluid registration algorithm, accelerated by using a filter designed by Bro-Nielsen and Gramkow. We validated the algorithm on 2D and 3D geometric phantoms using the mean square difference between the final registered image and target as a measure of the accuracy of the registration. In tests on phantom images with different levels of overlap, varying amounts of Gaussian noise, and different intensity gradients, the fluid method outperformed a more commonly used elastic registration method, both in terms of accuracy and in avoiding topological errors during deformation. We also studied the effect of varying the viscosity coefficients in the viscous fluid equation, to optimize registration accuracy. Finally, we applied the fluid registration algorithm to a dataset of 2D binary corpus callosum images and 3D volumetric brain MRIs from 14 healthy individuals to assess its accuracy and robustness.

  3. 2D/3D Image Registration using Regression Learning

    PubMed Central

    Chou, Chen-Rui; Frederick, Brandon; Mageras, Gig; Chang, Sha; Pizer, Stephen

    2013-01-01

    In computer vision and image analysis, image registration between 2D projections and a 3D image that achieves high accuracy and near real-time computation is challenging. In this paper, we propose a novel method that can rapidly detect an object’s 3D rigid motion or deformation from a 2D projection image or a small set thereof. The method is called CLARET (Correction via Limited-Angle Residues in External Beam Therapy) and consists of two stages: registration preceded by shape space and regression learning. In the registration stage, linear operators are used to iteratively estimate the motion/deformation parameters based on the current intensity residue between the target projec-tion(s) and the digitally reconstructed radiograph(s) (DRRs) of the estimated 3D image. The method determines the linear operators via a two-step learning process. First, it builds a low-order parametric model of the image region’s motion/deformation shape space from its prior 3D images. Second, using learning-time samples produced from the 3D images, it formulates the relationships between the model parameters and the co-varying 2D projection intensity residues by multi-scale linear regressions. The calculated multi-scale regression matrices yield the coarse-to-fine linear operators used in estimating the model parameters from the 2D projection intensity residues in the registration. The method’s application to Image-guided Radiation Therapy (IGRT) requires only a few seconds and yields good results in localizing a tumor under rigid motion in the head and neck and under respiratory deformation in the lung, using one treatment-time imaging 2D projection or a small set thereof. PMID:24058278

  4. 3D/3D registration of coronary CTA and biplane XA reconstructions for improved image guidance

    SciTech Connect

    Dibildox, Gerardo Baka, Nora; Walsum, Theo van; Punt, Mark; Aben, Jean-Paul; Schultz, Carl; Niessen, Wiro

    2014-09-15

    Purpose: The authors aim to improve image guidance during percutaneous coronary interventions of chronic total occlusions (CTO) by providing information obtained from computed tomography angiography (CTA) to the cardiac interventionist. To this end, the authors investigate a method to register a 3D CTA model to biplane reconstructions. Methods: The authors developed a method for registering preoperative coronary CTA with intraoperative biplane x-ray angiography (XA) images via 3D models of the coronary arteries. The models are extracted from the CTA and biplane XA images, and are temporally aligned based on CTA reconstruction phase and XA ECG signals. Rigid spatial alignment is achieved with a robust probabilistic point set registration approach using Gaussian mixture models (GMMs). This approach is extended by including orientation in the Gaussian mixtures and by weighting bifurcation points. The method is evaluated on retrospectively acquired coronary CTA datasets of 23 CTO patients for which biplane XA images are available. Results: The Gaussian mixture model approach achieved a median registration accuracy of 1.7 mm. The extended GMM approach including orientation was not significantly different (P > 0.1) but did improve robustness with regards to the initialization of the 3D models. Conclusions: The authors demonstrated that the GMM approach can effectively be applied to register CTA to biplane XA images for the purpose of improving image guidance in percutaneous coronary interventions.

  5. Registration of multi-view apical 3D echocardiography images

    NASA Astrophysics Data System (ADS)

    Mulder, H. W.; van Stralen, M.; van der Zwaan, H. B.; Leung, K. Y. E.; Bosch, J. G.; Pluim, J. P. W.

    2011-03-01

    Real-time three-dimensional echocardiography (RT3DE) is a non-invasive method to visualize the heart. Disadvantageously, it suffers from non-uniform image quality and a limited field of view. Image quality can be improved by fusion of multiple echocardiography images. Successful registration of the images is essential for prosperous fusion. Therefore, this study examines the performance of different methods for intrasubject registration of multi-view apical RT3DE images. A total of 14 data sets was annotated by two observers who indicated the position of the apex and four points on the mitral valve ring. These annotations were used to evaluate registration. Multi-view end-diastolic (ED) as well as end-systolic (ES) images were rigidly registered in a multi-resolution strategy. The performance of single-frame and multi-frame registration was examined. Multi-frame registration optimizes the metric for several time frames simultaneously. Furthermore, the suitability of mutual information (MI) as similarity measure was compared to normalized cross-correlation (NCC). For initialization of the registration, a transformation that describes the probe movement was obtained by manually registering five representative data sets. It was found that multi-frame registration can improve registration results with respect to single-frame registration. Additionally, NCC outperformed MI as similarity measure. If NCC was optimized in a multi-frame registration strategy including ED and ES time frames, the performance of the automatic method was comparable to that of manual registration. In conclusion, automatic registration of RT3DE images performs as good as manual registration. As registration precedes image fusion, this method can contribute to improved quality of echocardiography images.

  6. Combined registration of 3D tibia and femur implant models in 3D magnetic resonance images

    NASA Astrophysics Data System (ADS)

    Englmeier, Karl-Hans; Siebert, Markus; von Eisenhart-Rothe, Ruediger; Graichen, Heiko

    2008-03-01

    The most frequent reasons for revision of total knee arthroplasty are loosening and abnormal axial alignment leading to an unphysiological kinematic of the knee implant. To get an idea about the postoperative kinematic of the implant, it is essential to determine the position and orientation of the tibial and femoral prosthesis. Therefore we developed a registration method for fitting 3D CAD-models of knee joint prostheses into an 3D MR image. This rigid registration is the basis for a quantitative analysis of the kinematics of knee implants. Firstly the surface data of the prostheses models are converted into a voxel representation; a recursive algorithm determines all boundary voxels of the original triangular surface data. Secondly an initial preconfiguration of the implants by the user is still necessary for the following step: The user has to perform a rough preconfiguration of both remaining prostheses models, so that the fine matching process gets a reasonable starting point. After that an automated gradient-based fine matching process determines the best absolute position and orientation: This iterative process changes all 6 parameters (3 rotational- and 3 translational parameters) of a model by a minimal amount until a maximum value of the matching function is reached. To examine the spread of the final solutions of the registration, the interobserver variability was measured in a group of testers. This variability, calculated by the relative standard deviation, improved from about 50% (pure manual registration) to 0.5% (rough manual preconfiguration and subsequent fine registration with the automatic fine matching process).

  7. Registration and 3D visualization of large microscopy images

    NASA Astrophysics Data System (ADS)

    Mosaliganti, Kishore; Pan, Tony; Sharp, Richard; Ridgway, Randall; Iyengar, Srivathsan; Gulacy, Alexandra; Wenzel, Pamela; de Bruin, Alain; Machiraju, Raghu; Huang, Kun; Leone, Gustavo; Saltz, Joel

    2006-03-01

    Inactivation of the retinoblastoma gene in mouse embryos causes tissue infiltrations into critical sections of the placenta, which has been shown to affect fetal survivability. Our collaborators in cancer genetics are extremely interested in examining the three dimensional nature of these infiltrations given a stack of two dimensional light microscopy images. Three sets of wildtype and mutant placentas was sectioned serially and digitized using a commercial light microscopy scanner. Each individual placenta dataset consisted of approximately 1000 images totaling 700 GB in size, which were registered into a volumetric dataset using National Library of Medicine's (NIH/NLM) Insight Segmentation and Registration Toolkit (ITK). This paper describes our method for image registration to aid in volume visualization of tissue level intermixing for both wildtype and Rb - specimens. The registration process faces many challenges arising from the large image sizes, damages during sectioning, staining gradients both within and across sections, and background noise. These issues limit the direct application of standard registration techniques due to frequent convergence to local solutions. In this work, we develop a mixture of automated and semi-automated enhancements with ground-truth validation for the mutual information-based registration algorithm. Our final volume renderings clearly show tissue intermixing differences between both wildtype and Rb - specimens which are not obvious prior to registration.

  8. 3D registration through pseudo x-ray image generation.

    PubMed

    Viant, W J; Barnel, F

    2001-01-01

    Registration of a pre operative plan with the intra operative position of the patient is still a largely unsolved problem. Current techniques generally require fiducials, either artificial or anatomic, to achieve the registration solution. Invariably these fiducials require implantation and/or direct digitisation. The technique described in this paper requires no digitisation or implantation of fiducials, but instead relies on the shape and form of the anatomy through a fully automated image comparison process. A pseudo image, generated from a virtual image intensifier's view of a CT dataset, is intra operatively compared with a real x-ray image. The principle is to align the virtual with the real image intensifier. The technique is an extension to the work undertaken by Domergue [1] and based on original ideas by Weese [4]. PMID:11317805

  9. Registration of 3-D images using weighted geometrical features

    SciTech Connect

    Maurer, C.R. Jr.; Aboutanos, G.B.; Dawant, B.M.; Maciunas, R.J.; Fitzpatrick, J.M.

    1996-12-01

    In this paper, the authors present a weighted geometrical features (WGF) registration algorithm. Its efficacy is demonstrated by combining points and a surface. The technique is an extension of Besl and McKay`s iterative closest point (ICP) algorithm. The authors use the WGF algorithm to register X-ray computed tomography (CT) and T2-weighted magnetic resonance (MR) volume head images acquired from eleven patients that underwent craniotomies in a neurosurgical clinical trial. Each patient had five external markers attached to transcutaneous posts screwed into the outer table of the skull. The authors define registration error as the distance between positions of corresponding markers that are not used for registration. The CT and MR images are registered using fiducial points (marker positions) only, a surface only, and various weighted combinations of points and a surface. The CT surface is derived from contours corresponding to the inner surface of the skull. The MR surface is derived from contours corresponding to the cerebrospinal fluid (CSF)-dura interface. Registration using points and a surface is found to be significantly more accurate than registration using only points or a surface.

  10. 3D-2D registration of cerebral angiograms: a method and evaluation on clinical images.

    PubMed

    Mitrovic, Uroš; Špiclin, Žiga; Likar, Boštjan; Pernuš, Franjo

    2013-08-01

    Endovascular image-guided interventions (EIGI) involve navigation of a catheter through the vasculature followed by application of treatment at the site of anomaly using live 2D projection images for guidance. 3D images acquired prior to EIGI are used to quantify the vascular anomaly and plan the intervention. If fused with the information of live 2D images they can also facilitate navigation and treatment. For this purpose 3D-2D image registration is required. Although several 3D-2D registration methods for EIGI achieve registration accuracy below 1 mm, their clinical application is still limited by insufficient robustness or reliability. In this paper, we propose a 3D-2D registration method based on matching a 3D vasculature model to intensity gradients of live 2D images. To objectively validate 3D-2D registration methods, we acquired a clinical image database of 10 patients undergoing cerebral EIGI and established "gold standard" registrations by aligning fiducial markers in 3D and 2D images. The proposed method had mean registration accuracy below 0.65 mm, which was comparable to tested state-of-the-art methods, and execution time below 1 s. With the highest rate of successful registrations and the highest capture range the proposed method was the most robust and thus a good candidate for application in EIGI. PMID:23649179

  11. 3D registration through pseudo x-ray image generation.

    PubMed

    Domergue, G; Viant, W J

    2000-01-01

    One of the less effective processes within current Computer Assisted Surgery systems, utilizing pre-operative planning, is the registration of the plan with the intra-operative position of the patient. The technique described in this paper requires no digitisation of anatomical features or fiducial markers but instead relies on image matching between pseudo and real x-ray images generated by a virtual and a real image intensifier respectively. The technique is an extension to the work undertaken by Weese [1]. PMID:10977585

  12. 3D prostate segmentation of ultrasound images combining longitudinal image registration and machine learning

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Fei, Baowei

    2012-02-01

    We developed a three-dimensional (3D) segmentation method for transrectal ultrasound (TRUS) images, which is based on longitudinal image registration and machine learning. Using longitudinal images of each individual patient, we register previously acquired images to the new images of the same subject. Three orthogonal Gabor filter banks were used to extract texture features from each registered image. Patient-specific Gabor features from the registered images are used to train kernel support vector machines (KSVMs) and then to segment the newly acquired prostate image. The segmentation method was tested in TRUS data from five patients. The average surface distance between our and manual segmentation is 1.18 +/- 0.31 mm, indicating that our automatic segmentation method based on longitudinal image registration is feasible for segmenting the prostate in TRUS images.

  13. Image-based RSA: Roentgen stereophotogrammetric analysis based on 2D-3D image registration.

    PubMed

    de Bruin, P W; Kaptein, B L; Stoel, B C; Reiber, J H C; Rozing, P M; Valstar, E R

    2008-01-01

    Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3D image registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3D image registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: |mu |< 0.083 mm for translations and |mu| < 0.023 degrees for rotations. The precision sigma in x-, y-, and z-direction was 0.090, 0.077, and 0.220 mm for translations and 0.155 degrees , 0.243 degrees , and 0.074 degrees for rotations. Our results show that the accuracy and precision of in vitro IBRSA, performed under ideal laboratory conditions, are lower than in vitro standard RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications. PMID:17706656

  14. Automatic Masking for Robust 3D-2D Image Registration in Image-Guided Spine Surgery

    PubMed Central

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

    2016-01-01

    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.

  15. Assessing 3D tunnel position in ACL reconstruction using a novel single image 3D-2D registration

    NASA Astrophysics Data System (ADS)

    Kang, X.; Yau, W. P.; Otake, Y.; Cheung, P. Y. S.; Hu, Y.; Taylor, R. H.

    2012-02-01

    The routinely used procedure for evaluating tunnel positions following anterior cruciate ligament (ACL) reconstructions based on standard X-ray images is known to pose difficulties in terms of obtaining accurate measures, especially in providing three-dimensional tunnel positions. This is largely due to the variability in individual knee joint pose relative to X-ray plates. Accurate results were reported using postoperative CT. However, its extensive usage in clinical routine is hampered by its major requirement of having CT scans of individual patients, which is not available for most ACL reconstructions. These difficulties are addressed through the proposed method, which aligns a knee model to X-ray images using our novel single-image 3D-2D registration method and then estimates the 3D tunnel position. In the proposed method, the alignment is achieved by using a novel contour-based 3D-2D registration method wherein image contours are treated as a set of oriented points. However, instead of using some form of orientation weighting function and multiplying it with a distance function, we formulate the 3D-2D registration as a probability density estimation using a mixture of von Mises-Fisher-Gaussian (vMFG) distributions and solve it through an expectation maximization (EM) algorithm. Compared with the ground-truth established from postoperative CT, our registration method in an experiment using a plastic phantom showed accurate results with errors of (-0.43°+/-1.19°, 0.45°+/-2.17°, 0.23°+/-1.05°) and (0.03+/-0.55, -0.03+/-0.54, -2.73+/-1.64) mm. As for the entry point of the ACL tunnel, one of the key measurements, it was obtained with high accuracy of 0.53+/-0.30 mm distance errors.

  16. Fully automatic and robust 3D registration of serial-section microscopic images.

    PubMed

    Wang, Ching-Wei; Budiman Gosno, Eric; Li, Yen-Sheng

    2015-01-01

    Robust and fully automatic 3D registration of serial-section microscopic images is critical for detailed anatomical reconstruction of large biological specimens, such as reconstructions of dense neuronal tissues or 3D histology reconstruction to gain new structural insights. However, robust and fully automatic 3D image registration for biological data is difficult due to complex deformations, unbalanced staining and variations on data appearance. This study presents a fully automatic and robust 3D registration technique for microscopic image reconstruction, and we demonstrate our method on two ssTEM datasets of drosophila brain neural tissues, serial confocal laser scanning microscopic images of a drosophila brain, serial histopathological images of renal cortical tissues and a synthetic test case. The results show that the presented fully automatic method is promising to reassemble continuous volumes and minimize artificial deformations for all data and outperforms four state-of-the-art 3D registration techniques to consistently produce solid 3D reconstructed anatomies with less discontinuities and deformations. PMID:26449756

  17. Fully automatic and robust 3D registration of serial-section microscopic images

    PubMed Central

    Wang, Ching-Wei; Budiman Gosno, Eric; Li, Yen-Sheng

    2015-01-01

    Robust and fully automatic 3D registration of serial-section microscopic images is critical for detailed anatomical reconstruction of large biological specimens, such as reconstructions of dense neuronal tissues or 3D histology reconstruction to gain new structural insights. However, robust and fully automatic 3D image registration for biological data is difficult due to complex deformations, unbalanced staining and variations on data appearance. This study presents a fully automatic and robust 3D registration technique for microscopic image reconstruction, and we demonstrate our method on two ssTEM datasets of drosophila brain neural tissues, serial confocal laser scanning microscopic images of a drosophila brain, serial histopathological images of renal cortical tissues and a synthetic test case. The results show that the presented fully automatic method is promising to reassemble continuous volumes and minimize artificial deformations for all data and outperforms four state-of-the-art 3D registration techniques to consistently produce solid 3D reconstructed anatomies with less discontinuities and deformations. PMID:26449756

  18. Nonrigid registration and classification of the kidneys in 3D dynamic contrast enhanced (DCE) MR images

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Ghafourian, Pegah; Sharma, Puneet; Salman, Khalil; Martin, Diego; Fei, Baowei

    2012-02-01

    We have applied image analysis methods in the assessment of human kidney perfusion based on 3D dynamic contrast-enhanced (DCE) MRI data. This approach consists of 3D non-rigid image registration of the kidneys and fuzzy C-mean classification of kidney tissues. The proposed registration method reduced motion artifacts in the dynamic images and improved the analysis of kidney compartments (cortex, medulla, and cavities). The dynamic intensity curves show the successive transition of the contrast agent through kidney compartments. The proposed method for motion correction and kidney compartment classification may be used to improve the validity and usefulness of further model-based pharmacokinetic analysis of kidney function.

  19. 3D nonrigid medical image registration using a new information theoretic measure

    NASA Astrophysics Data System (ADS)

    Li, Bicao; Yang, Guanyu; Coatrieux, Jean Louis; Li, Baosheng; Shu, Huazhong

    2015-11-01

    This work presents a novel method for the nonrigid registration of medical images based on the Arimoto entropy, a generalization of the Shannon entropy. The proposed method employed the Jensen-Arimoto divergence measure as a similarity metric to measure the statistical dependence between medical images. Free-form deformations were adopted as the transformation model and the Parzen window estimation was applied to compute the probability distributions. A penalty term is incorporated into the objective function to smooth the nonrigid transformation. The goal of registration is to optimize an objective function consisting of a dissimilarity term and a penalty term, which would be minimal when two deformed images are perfectly aligned using the limited memory BFGS optimization method, and thus to get the optimal geometric transformation. To validate the performance of the proposed method, experiments on both simulated 3D brain MR images and real 3D thoracic CT data sets were designed and performed on the open source elastix package. For the simulated experiments, the registration errors of 3D brain MR images with various magnitudes of known deformations and different levels of noise were measured. For the real data tests, four data sets of 4D thoracic CT from four patients were selected to assess the registration performance of the method, including ten 3D CT images for each 4D CT data covering an entire respiration cycle. These results were compared with the normalized cross correlation and the mutual information methods and show a slight but true improvement in registration accuracy.

  20. Automatic 3D ultrasound calibration for image guided therapy using intramodality image registration

    NASA Astrophysics Data System (ADS)

    Schlosser, Jeffrey; Kirmizibayrak, Can; Shamdasani, Vijay; Metz, Steve; Hristov, Dimitre

    2013-11-01

    Many real time ultrasound (US) guided therapies can benefit from management of motion-induced anatomical changes with respect to a previously acquired computerized anatomy model. Spatial calibration is a prerequisite to transforming US image information to the reference frame of the anatomy model. We present a new method for calibrating 3D US volumes using intramodality image registration, derived from the ‘hand-eye’ calibration technique. The method is fully automated by implementing data rejection based on sensor displacements, automatic registration over overlapping image regions, and a self-consistency error metric evaluated continuously during calibration. We also present a novel method for validating US calibrations based on measurement of physical phantom displacements within US images. Both calibration and validation can be performed on arbitrary phantoms. Results indicate that normalized mutual information and localized cross correlation produce the most accurate 3D US registrations for calibration. Volumetric image alignment is more accurate and reproducible than point selection for validating the calibrations, yielding <1.5 mm root mean square error, a significant improvement relative to previously reported hand-eye US calibration results. Comparison of two different phantoms for calibration and for validation revealed significant differences for validation (p = 0.003) but not for calibration (p = 0.795).

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

    SciTech Connect

    Presles, Benoît Rit, Simon; Sarrut, David; Fargier-Voiron, Marie; Liebgott, Hervé; Biston, Marie-Claude; Munoz, Alexandre; Pommier, Pascal; Lynch, Rod

    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 computed 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, respectively

  2. Progressive attenuation fields: Fast 2D-3D image registration without precomputation

    SciTech Connect

    Rohlfing, Torsten; Russakoff, Daniel B.; Denzler, Joachim; Mori, Kensaku; Maurer, Calvin R. Jr.

    2005-09-15

    Computation of digitally reconstructed radiograph (DRR) images is the rate-limiting step in most current intensity-based algorithms for the registration of three-dimensional (3D) images to two-dimensional (2D) projection images. This paper introduces and evaluates the progressive attenuation field (PAF), which is a new method to speed up DRR computation. A PAF is closely related to an attenuation field (AF). A major difference is that a PAF is constructed on the fly as the registration proceeds; it does not require any precomputation time, nor does it make any prior assumptions of the patient pose or limit the permissible range of patient motion. A PAF effectively acts as a cache memory for projection values once they are computed, rather than as a lookup table for precomputed projections like standard AFs. We use a cylindrical attenuation field parametrization, which is better suited for many medical applications of 2D-3D registration than the usual two-plane parametrization. The computed attenuation values are stored in a hash table for time-efficient storage and access. Using clinical gold-standard spine image data sets from five patients, we demonstrate consistent speedups of intensity-based 2D-3D image registration using PAF DRRs by a factor of 10 over conventional ray casting DRRs with no decrease of registration accuracy or robustness.

  3. A new gold-standard dataset for 2D/3D image registration evaluation

    NASA Astrophysics Data System (ADS)

    Pawiro, Supriyanto; Markelj, Primoz; Gendrin, Christelle; Figl, Michael; Stock, Markus; Bloch, Christoph; Weber, Christoph; Unger, Ewald; Nöbauer, Iris; Kainberger, Franz; Bergmeister, Helga; Georg, Dietmar; Bergmann, Helmar; Birkfellner, Wolfgang

    2010-02-01

    In this paper, we propose a new gold standard data set for the validation of 2D/3D image registration algorithms for image guided radiotherapy. A gold standard data set was calculated using a pig head with attached fiducial markers. We used several imaging modalities common in diagnostic imaging or radiotherapy which include 64-slice computed tomography (CT), magnetic resonance imaging (MRI) using T1, T2 and proton density (PD) sequences, and cone beam CT (CBCT) imaging data. Radiographic data were acquired using kilovoltage (kV) and megavoltage (MV) imaging techniques. The image information reflects both anatomy and reliable fiducial marker information, and improves over existing data sets by the level of anatomical detail and image data quality. The markers of three dimensional (3D) and two dimensional (2D) images were segmented using Analyze 9.0 (AnalyzeDirect, Inc) and an in-house software. The projection distance errors (PDE) and the expected target registration errors (TRE) over all the image data sets were found to be less than 1.7 mm and 1.3 mm, respectively. The gold standard data set, obtained with state-of-the-art imaging technology, has the potential to improve the validation of 2D/3D registration algorithms for image guided therapy.

  4. Optimizing nonrigid registration performance between volumetric true 3D ultrasound images in image-guided neurosurgery

    NASA Astrophysics Data System (ADS)

    Ji, Songbai; Fan, Xiaoyao; Roberts, David W.; Hartov, Alex; Paulsen, Keith D.

    2011-03-01

    Compensating for brain shift as surgery progresses is important to ensure sufficient accuracy in patient-to-image registration in the operating room (OR) for reliable neuronavigation. Ultrasound has emerged as an important and practical imaging technique for brain shift compensation either by itself or through computational modeling that estimates whole-brain deformation. Using volumetric true 3D ultrasound (3DUS), it is possible to nonrigidly (e.g., based on B-splines) register two temporally different 3DUS images directly to generate feature displacement maps for data assimilation in the biomechanical model. Because of a large amount of data and number of degrees-of-freedom (DOFs) involved, however, a significant computational cost may be required that can adversely influence the clinical feasibility of the technique for efficiently generating model-updated MR (uMR) in the OR. This paper parametrically investigates three B-splines registration parameters and their influence on the computational cost and registration accuracy: number of grid nodes along each direction, floating image volume down-sampling rate, and number of iterations. A simulated rigid body displacement field was employed as a ground-truth against which the accuracy of displacements generated from the B-splines nonrigid registration was compared. A set of optimal parameters was then determined empirically that result in a registration computational cost of less than 1 min and a sub-millimetric accuracy in displacement measurement. These resulting parameters were further applied to a clinical surgery case to demonstrate their practical use. Our results indicate that the optimal set of parameters result in sufficient accuracy and computational efficiency in model computation, which is important for future application of the overall biomechanical modeling to generate uMR for image-guidance in the OR.

  5. Voxel-based 2-D/3-D registration of fluoroscopy images and CT scans for image-guided surgery.

    PubMed

    Weese, J; Penney, G P; Desmedt, P; Buzug, T M; Hill, D L; Hawkes, D J

    1997-12-01

    Registration of intraoperative fluoroscopy images with preoperative three-dimensional (3-D) CT images can be used for several purposes in image-guided surgery. On the one hand, it can be used to display the position of surgical instruments, which are being tracked by a localizer, in the preoperative CT scan. On the other hand, the registration result can be used to project preoperative planning information or important anatomical structures visible in the CT image onto the fluoroscopy image. For this registration task, a novel voxel-based method in combination with a new similarity measure (pattern intensity) has been developed. The basic concept of the method is explained at the example of two-dimensional (2-D)/3-D registration of a vertebra in an X-ray fluoroscopy image with a 3-D CT image. The registration method is described, and the results for a spine phantom are presented and discussed. Registration has been carried out repeatedly with different starting estimates to study the capture range. Information about registration accuracy has been obtained by comparing the registration results with a highly accurate "ground-truth" registration, which has been derived from fiducial markers attached to the phantom prior to imaging. In addition, registration results for different vertebrae have been compared. The results show that the rotation parameters and the shifts parallel to the projection plane can accurately be determined from a single projection. Because of the projection geometry, the accuracy of the height above the projection plane is significantly lower. PMID:11020832

  6. Radial subsampling for fast cost function computation in intensity-based 3D image registration

    NASA Astrophysics Data System (ADS)

    Boettger, Thomas; Wolf, Ivo; Meinzer, Hans-Peter; Celi, Juan Carlos

    2007-03-01

    Image registration is always a trade-off between accuracy and speed. Looking towards clinical scenarios the time for bringing two or more images into registration should be around a few seconds only. We present a new scheme for subsampling 3D-image data to allow for efficient computation of cost functions in intensity-based image registration. Starting from an arbitrary center point voxels are sampled along scan lines which do radially extend from the center point. We analyzed the characteristics of different cost functions computed on the sub-sampled data and compared them to known cost functions with respect to local optima. Results show the cost functions are smooth and give high peaks at the expected optima. Furthermore we investigated capture range of cost functions computed under the new subsampling scheme. Capture range was remarkably better for the new scheme compared to metrics using all voxels or different subsampling schemes and high registration accuracy was achieved as well. The most important result is the improvement in terms of speed making this scheme very interesting for clinical scenarios. We conclude using the new subsampling scheme intensity-based 3D image registration can be performed much faster than using other approaches while maintaining high accuracy. A variety of different extensions of the new approach is conceivable, e.g. non-regular distribution of the scan lines or not to let the scan lines start from a center point only, but from the surface of an organ model for example.

  7. A practical salient region feature based 3D multi-modality registration method for medical images

    NASA Astrophysics Data System (ADS)

    Hahn, Dieter A.; Wolz, Gabriele; Sun, Yiyong; Hornegger, Joachim; Sauer, Frank; Kuwert, Torsten; Xu, Chenyang

    2006-03-01

    We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3D image pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.

  8. A faster method for 3D/2D medical image registration--a simulation study.

    PubMed

    Birkfellner, Wolfgang; Wirth, Joachim; Burgstaller, Wolfgang; Baumann, Bernard; Staedele, Harald; Hammer, Beat; Gellrich, Niels Claudius; Jacob, Augustinus Ludwig; Regazzoni, Pietro; Messmer, Peter

    2003-08-21

    3D/2D patient-to-computed-tomography (CT) registration is a method to determine a transformation that maps two coordinate systems by comparing a projection image rendered from CT to a real projection image. Iterative variation of the CT's position between rendering steps finally leads to exact registration. Applications include exact patient positioning in radiation therapy, calibration of surgical robots, and pose estimation in computer-aided surgery. One of the problems associated with 3D/2D registration is the fact that finding a registration includes solving a minimization problem in six degrees of freedom (dof) in motion. This results in considerable time requirements since for each iteration step at least one volume rendering has to be computed. We show that by choosing an appropriate world coordinate system and by applying a 2D/2D registration method in each iteration step, the number of iterations can be grossly reduced from n6 to n5. Here, n is the number of discrete variations around a given coordinate. Depending on the configuration of the optimization algorithm, this reduces the total number of iterations necessary to at least 1/3 of it's original value. The method was implemented and extensively tested on simulated x-ray images of a tibia, a pelvis and a skull base. When using one projective image and a discrete full parameter space search for solving the optimization problem, average accuracy was found to be 1.0 +/- 0.6(degrees) and 4.1 +/- 1.9 (mm) for a registration in six parameters, and 1.0 +/- 0.7(degrees) and 4.2 +/- 1.6 (mm) when using the 5 + 1 dof method described in this paper. Time requirements were reduced by a factor 3.1. We conclude that this hardware-independent optimization of 3D/2D registration is a step towards increasing the acceptance of this promising method for a wide number of clinical applications. PMID:12974581

  9. 3D nonrigid medical image registration using a new information theoretic measure.

    PubMed

    Li, Bicao; Yang, Guanyu; Coatrieux, Jean Louis; Li, Baosheng; Shu, Huazhong

    2015-11-21

    This work presents a novel method for the nonrigid registration of medical images based on the Arimoto entropy, a generalization of the Shannon entropy. The proposed method employed the Jensen-Arimoto divergence measure as a similarity metric to measure the statistical dependence between medical images. Free-form deformations were adopted as the transformation model and the Parzen window estimation was applied to compute the probability distributions. A penalty term is incorporated into the objective function to smooth the nonrigid transformation. The goal of registration is to optimize an objective function consisting of a dissimilarity term and a penalty term, which would be minimal when two deformed images are perfectly aligned using the limited memory BFGS optimization method, and thus to get the optimal geometric transformation. To validate the performance of the proposed method, experiments on both simulated 3D brain MR images and real 3D thoracic CT data sets were designed and performed on the open source elastix package. For the simulated experiments, the registration errors of 3D brain MR images with various magnitudes of known deformations and different levels of noise were measured. For the real data tests, four data sets of 4D thoracic CT from four patients were selected to assess the registration performance of the method, including ten 3D CT images for each 4D CT data covering an entire respiration cycle. These results were compared with the normalized cross correlation and the mutual information methods and show a slight but true improvement in registration accuracy. PMID:26528821

  10. Automatic 3D image registration using voxel similarity measurements based on a genetic algorithm

    NASA Astrophysics Data System (ADS)

    Huang, Wei; Sullivan, John M., Jr.; Kulkarni, Praveen; Murugavel, Murali

    2006-03-01

    An automatic 3D non-rigid body registration system based upon the genetic algorithm (GA) process is presented. The system has been successfully applied to 2D and 3D situations using both rigid-body and affine transformations. Conventional optimization techniques and gradient search strategies generally require a good initial start location. The GA approach avoids the local minima/maxima traps of conventional optimization techniques. Based on the principles of Darwinian natural selection (survival of the fittest), the genetic algorithm has two basic steps: 1. Randomly generate an initial population. 2. Repeated application of the natural selection operation until a termination measure is satisfied. The natural selection process selects individuals based on their fitness to participate in the genetic operations; and it creates new individuals by inheritance from both parents, genetic recombination (crossover) and mutation. Once the termination criteria are satisfied, the optimum is selected from the population. The algorithm was applied on 2D and 3D magnetic resonance images (MRI). It does not require any preprocessing such as threshold, smoothing, segmentation, or definition of base points or edges. To evaluate the performance of the GA registration, the results were compared with results of the Automatic Image Registration technique (AIR) and manual registration which was used as the gold standard. Results showed that our GA implementation was a robust algorithm and gives very close results to the gold standard. A pre-cropping strategy was also discussed as an efficient preprocessing step to enhance the registration accuracy.

  11. 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.

  12. Nonrigid 3D medical image registration and fusion based on deformable models.

    PubMed

    Liu, Peng; Eberhardt, Benjamin; Wybranski, Christian; Ricke, Jens; Lüdemann, Lutz

    2013-01-01

    For coregistration of medical images, rigid methods often fail to provide enough freedom, while reliable elastic methods are available clinically for special applications only. The number of degrees of freedom of elastic models must be reduced for use in the clinical setting to archive a reliable result. We propose a novel geometry-based method of nonrigid 3D medical image registration and fusion. The proposed method uses a 3D surface-based deformable model as guidance. In our twofold approach, the deformable mesh from one of the images is first applied to the boundary of the object to be registered. Thereafter, the non-rigid volume deformation vector field needed for registration and fusion inside of the region of interest (ROI) described by the active surface is inferred from the displacement of the surface mesh points. The method was validated using clinical images of a quasirigid organ (kidney) and of an elastic organ (liver). The reduction in standard deviation of the image intensity difference between reference image and model was used as a measure of performance. Landmarks placed at vessel bifurcations in the liver were used as a gold standard for evaluating registration results for the elastic liver. Our registration method was compared with affine registration using mutual information applied to the quasi-rigid kidney. The new method achieved 15.11% better quality with a high confidence level of 99% for rigid registration. However, when applied to the quasi-elastic liver, the method has an averaged landmark dislocation of 4.32 mm. In contrast, affine registration of extracted livers yields a significantly (P = 0.000001) smaller dislocation of 3.26 mm. In conclusion, our validation shows that the novel approach is applicable in cases where internal deformation is not crucial, but it has limitations in cases where internal displacement must also be taken into account. PMID:23690883

  13. Automatic 3D segmentation of ultrasound images using atlas registration and statistical texture prior

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Schuster, David; Master, Viraj; Nieh, Peter; Fenster, Aaron; Fei, Baowei

    2011-03-01

    We are developing a molecular image-directed, 3D ultrasound-guided, targeted biopsy system for improved detection of prostate cancer. In this paper, we propose an automatic 3D segmentation method for transrectal ultrasound (TRUS) images, which is based on multi-atlas registration and statistical texture prior. The atlas database includes registered TRUS images from previous patients and their segmented prostate surfaces. Three orthogonal Gabor filter banks are used to extract texture features from each image in the database. Patient-specific Gabor features from the atlas database are used to train kernel support vector machines (KSVMs) and then to segment the prostate image from a new patient. The segmentation method was tested in TRUS data from 5 patients. The average surface distance between our method and manual segmentation is 1.61 +/- 0.35 mm, indicating that the atlas-based automatic segmentation method works well and could be used for 3D ultrasound-guided prostate biopsy.

  14. Exact surface registration of retinal surfaces from 3-D optical coherence tomography images.

    PubMed

    Lee, Sieun; Lebed, Evgeniy; Sarunic, Marinko V; Beg, Mirza Faisal

    2015-02-01

    Nonrigid registration of optical coherence tomography (OCT) images is an important problem in studying eye diseases, evaluating the effect of pharmaceuticals in treating vision loss, and performing group-wise cross-sectional analysis. High dimensional nonrigid registration algorithms required for cross-sectional and longitudinal analysis are still being developed for accurate registration of OCT image volumes, with the speckle noise in images presenting a challenge for registration. Development of algorithms for segmentation of OCT images to generate surface models of retinal layers has advanced considerably and several algorithms are now available that can segment retinal OCT images into constituent retinal surfaces. Important morphometric measurements can be extracted if accurate surface registration algorithm for registering retinal surfaces onto corresponding template surfaces were available. In this paper, we present a novel method to perform multiple and simultaneous retinal surface registration, targeted to registering surfaces extracted from ocular volumetric OCT images. This enables a point-to-point correspondence (homology) between template and subject surfaces, allowing for a direct, vertex-wise comparison of morphometric measurements across subject groups. We demonstrate that this approach can be used to localize and analyze regional changes in choroidal and nerve fiber layer thickness among healthy and glaucomatous subjects, allowing for cross-sectional population wise analysis. We also demonstrate the method's ability to track longitudinal changes in optic nerve head morphometry, allowing for within-individual tracking of morphometric changes. This method can also, in the future, be used as a precursor to 3-D OCT image registration to better initialize nonrigid image registration algorithms closer to the desired solution. PMID:25312906

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

    NASA Astrophysics Data System (ADS)

    Li, Pan; Malsch, Urban; Bendl, Rolf

    2008-09-01

    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.

  16. 2D imaging and 3D sensing data acquisition and mutual registration for painting conservation

    NASA Astrophysics Data System (ADS)

    Fontana, Raffaella; Gambino, Maria Chiara; Greco, Marinella; Marras, Luciano; Pampaloni, Enrico M.; Pelagotti, Anna; Pezzati, Luca; Poggi, Pasquale

    2005-01-01

    We describe the application of 2D and 3D data acquisition and mutual registration to the conservation of paintings. RGB color image acquisition, IR and UV fluorescence imaging, together with the more recent hyperspectral imaging (32 bands) are among the most useful techniques in this field. They generally are meant to provide information on the painting materials, on the employed techniques and on the object state of conservation. However, only when the various images are perfectly registered on each other and on the 3D model, no ambiguity is possible and safe conclusions may be drawn. We present the integration of 2D and 3D measurements carried out on two different paintings: "Madonna of the Yarnwinder" by Leonardo da Vinci, and "Portrait of Lionello d'Este", by Pisanello, both painted in the XV century.

  17. 2D imaging and 3D sensing data acquisition and mutual registration for painting conservation

    NASA Astrophysics Data System (ADS)

    Fontana, Raffaella; Gambino, Maria Chiara; Greco, Marinella; Marras, Luciano; Pampaloni, Enrico M.; Pelagotti, Anna; Pezzati, Luca; Poggi, Pasquale

    2004-12-01

    We describe the application of 2D and 3D data acquisition and mutual registration to the conservation of paintings. RGB color image acquisition, IR and UV fluorescence imaging, together with the more recent hyperspectral imaging (32 bands) are among the most useful techniques in this field. They generally are meant to provide information on the painting materials, on the employed techniques and on the object state of conservation. However, only when the various images are perfectly registered on each other and on the 3D model, no ambiguity is possible and safe conclusions may be drawn. We present the integration of 2D and 3D measurements carried out on two different paintings: "Madonna of the Yarnwinder" by Leonardo da Vinci, and "Portrait of Lionello d'Este", by Pisanello, both painted in the XV century.

  18. SU-E-J-209: Verification of 3D Surface Registration Between Stereograms and CT Images

    SciTech Connect

    Han, T; Gifford, K; Smith, B; Salehpour, M

    2014-06-01

    Purpose: Stereography can provide a visualization of the skin surface for radiation therapy patients. The aim of this study was to verify the registration algorithm in a commercial image analysis software, 3dMDVultus, for the fusion of stereograms and CT images. Methods: CT and stereographic scans were acquired of a head phantom and a deformable phantom. CT images were imported in 3dMDVultus and the surface contours were generated by threshold segmentation. Stereograms were reconstructed in 3dMDVultus. The resulting surfaces were registered with Vultus algorithm and then exported to in-house registration software and compared with four algorithms: rigid, affine, non-rigid iterative closest point (ICP) and b-spline algorithm. RMS (root-mean-square residuals of the surface point distances) error between the registered CT and stereogram surfaces was calculated and analyzed. Results: For the head phantom, the maximum RMS error between registered CT surfaces to stereogram was 6.6 mm for Vultus algorithm, whereas the mean RMS error was 0.7 mm. For the deformable phantom, the maximum RMS error was 16.2 mm for Vultus algorithm, whereas the mean RMS error was 4.4 mm. Non-rigid ICP demonstrated the best registration accuracy, as the mean of RMS errors were both within 1 mm. Conclusion: The accuracy of registration algorithm in 3dMDVultus was verified and exceeded RMS of 2 mm for deformable cases. Non-rigid ICP and b-spline algorithms improve the registration accuracy for both phantoms, especially in deformable one. For those patients whose body habitus deforms during radiation therapy, more advanced nonrigid algorithms need to be used.

  19. Location constraint based 2D-3D registration of fluoroscopic images and CT volumes for image-guided EP procedures

    NASA Astrophysics Data System (ADS)

    Liao, Rui; Xu, Ning; Sun, Yiyong

    2008-03-01

    Presentation of detailed anatomical structures via 3D Computed Tomographic (CT) volumes helps visualization and navigation in electrophysiology procedures (EP). Registration of the CT volume with the online fluoroscopy however is a challenging task for EP applications due to the lack of discernable features in fluoroscopic images. In this paper, we propose to use the coronary sinus (CS) catheter in bi-plane fluoroscopic images and the coronary sinus in the CT volume as a location constraint to accomplish 2D-3D registration. Two automatic registration algorithms are proposed in this study, and their performances are investigated on both simulated and real data. It is shown that compared to registration using mono-plane fluoroscopy, registration using bi-plane images results in substantially higher accuracy in 3D and enhanced robustness. In addition, compared to registering the projection of CS to the 2D CS catheter, it is more desirable to reconstruct a 3D CS catheter from the bi-plane fluoroscopy and then perform a 3D-3D registration between the CS and the reconstructed CS catheter. Quantitative validation based on simulation and visual inspection on real data demonstrates the feasibility of the proposed workflow in EP procedures.

  20. Mars US rover traverse co-registration using multi-resolution Orbital 3D imaging datasets

    NASA Astrophysics Data System (ADS)

    Poole, W. D.

    2013-09-01

    Co-registered 3D Digital terrain Models (DTMs) and orthorectified imaging (ORI) orbital datasets have been produced of all the major US Mars landing sites. These have been sourced from HiRise, HRSC and MOLA. Co-registration was achieved using manual tiepointing within ARCgis v10. These DTM and ORI products were sourced from publicly available datasets or from EU-FP7-PRoViSG partners or generated using internal UCL 3D-RPIF [1] resources. For rover traverses, this results in substantial transformations which implies that all the SPICE kernels will need to be recomputed.

  1. Atlas-registration based image segmentation of MRI human thigh muscles in 3D space

    NASA Astrophysics Data System (ADS)

    Ahmad, Ezak; Yap, Moi Hoon; Degens, Hans; McPhee, Jamie S.

    2014-03-01

    Automatic segmentation of anatomic structures of magnetic resonance thigh scans can be a challenging task due to the potential lack of precisely defined muscle boundaries and issues related to intensity inhomogeneity or bias field across an image. In this paper, we demonstrate a combination framework of atlas construction and image registration methods to propagate the desired region of interest (ROI) between atlas image and the targeted MRI thigh scans for quadriceps muscles, femur cortical layer and bone marrow segmentations. The proposed system employs a semi-automatic segmentation method on an initial image in one dataset (from a series of images). The segmented initial image is then used as an atlas image to automate the segmentation of other images in the MRI scans (3-D space). The processes include: ROI labeling, atlas construction and registration, and morphological transform correspondence pixels (in terms of feature and intensity value) between the atlas (template) image and the targeted image based on the prior atlas information and non-rigid image registration methods.

  2. Pulmonary CT image registration and warping for tracking tissue deformation during the respiratory cycle through 3D consistent image registration

    PubMed Central

    Li, Baojun; Christensen, Gary E.; Hoffman, Eric A.; McLennan, Geoffrey; Reinhardt, Joseph M.

    2008-01-01

    Tracking lung tissues during the respiratory cycle has been a challenging task for diagnostic CT and CT-guided radiotherapy. We propose an intensity- and landmark-based image registration algorithm to perform image registration and warping of 3D pulmonary CT image data sets, based on consistency constraints and matching corresponding airway branchpoints. In this paper, we demonstrate the effectivenss and accuracy of this algorithm in tracking lung tissues by both animal and human data sets. In the animal study, the result showed a tracking accuracy of 1.9 mm between 50% functional residual capacity (FRC) and 85% total lung capacity (TLC) for 12 metal seeds implanted in the lungs of a breathing sheep under precise volume control using a pulmonary ventilator. Visual inspection of the human subject results revealed the algorithm’s potential not only in matching the global shapes, but also in registering the internal structures (e.g., oblique lobe fissures, pulmonary artery branches, etc.). These results suggest that our algorithm has significant potential for warping and tracking lung tissue deformation with applications in diagnostic CT, CT-guided radiotherapy treatment planning, and therapeutic effect evaluation. PMID:19175115

  3. Registration of 2D cardiac images to real-time 3D ultrasound volumes for 3D stress echocardiography

    NASA Astrophysics Data System (ADS)

    Leung, K. Y. Esther; van Stralen, Marijn; Voormolen, Marco M.; van Burken, Gerard; Nemes, Attila; ten Cate, Folkert J.; Geleijnse, Marcel L.; de Jong, Nico; van der Steen, Antonius F. W.; Reiber, Johan H. C.; Bosch, Johan G.

    2006-03-01

    Three-dimensional (3D) stress echocardiography is a novel technique for diagnosing cardiac dysfunction, by comparing wall motion of the left ventricle under different stages of stress. For quantitative comparison of this motion, it is essential to register the ultrasound data. We propose an intensity based rigid registration method to retrieve two-dimensional (2D) four-chamber (4C), two-chamber, and short-axis planes from the 3D data set acquired in the stress stage, using manually selected 2D planes in the rest stage as reference. The algorithm uses the Nelder-Mead simplex optimization to find the optimal transformation of one uniform scaling, three rotation, and three translation parameters. We compared registration using the SAD, SSD, and NCC metrics, performed on four resolution levels of a Gaussian pyramid. The registration's effectiveness was assessed by comparing the 3D positions of the registered apex and mitral valve midpoints and 4C direction with the manually selected results. The registration was tested on data from 20 patients. Best results were found using the NCC metric on data downsampled with factor two: mean registration errors were 8.1mm, 5.4mm, and 8.0° in the apex position, mitral valve position, and 4C direction respectively. The errors were close to the interobserver (7.1mm, 3.8mm, 7.4°) and intraobserver variability (5.2mm, 3.3mm, 7.0°), and better than the error before registration (9.4mm, 9.0mm, 9.9°). We demonstrated that the registration algorithm visually and quantitatively improves the alignment of rest and stress data sets, performing similar to manual alignment. This will improve automated analysis in 3D stress echocardiography.

  4. GPU accelerated generation of digitally reconstructed radiographs for 2-D/3-D image registration.

    PubMed

    Dorgham, Osama M; Laycock, Stephen D; Fisher, Mark H

    2012-09-01

    Recent advances in programming languages for graphics processing units (GPUs) provide developers with a convenient way of implementing applications which can be executed on the CPU and GPU interchangeably. GPUs are becoming relatively cheap, powerful, and widely available hardware components, which can be used to perform intensive calculations. The last decade of hardware performance developments shows that GPU-based computation is progressing significantly faster than CPU-based computation, particularly if one considers the execution of highly parallelisable algorithms. Future predictions illustrate that this trend is likely to continue. In this paper, we introduce a way of accelerating 2-D/3-D image registration by developing a hybrid system which executes on the CPU and utilizes the GPU for parallelizing the generation of digitally reconstructed radiographs (DRRs). Based on the advancements of the GPU over the CPU, it is timely to exploit the benefits of many-core GPU technology by developing algorithms for DRR generation. Although some previous work has investigated the rendering of DRRs using the GPU, this paper investigates approximations which reduce the computational overhead while still maintaining a quality consistent with that needed for 2-D/3-D registration with sufficient accuracy to be clinically acceptable in certain applications of radiation oncology. Furthermore, by comparing implementations of 2-D/3-D registration on the CPU and GPU, we investigate current performance and propose an optimal framework for PC implementations addressing the rigid registration problem. Using this framework, we are able to render DRR images from a 256×256×133 CT volume in ~24 ms using an NVidia GeForce 8800 GTX and in ~2 ms using NVidia GeForce GTX 580. In addition to applications requiring fast automatic patient setup, these levels of performance suggest image-guided radiation therapy at video frame rates is technically feasible using relatively low cost PC

  5. 2D Ultrasound and 3D MR Image Registration of the Prostate for Brachytherapy Surgical Navigation

    PubMed Central

    Zhang, Shihui; Jiang, Shan; Yang, Zhiyong; Liu, Ranlu

    2015-01-01

    Abstract Two-dimensional (2D) ultrasound (US) images are widely used in minimally invasive prostate procedure for its noninvasive nature and convenience. However, the poor quality of US image makes it difficult to be used as guiding utility. To improve the limitation, we propose a multimodality image guided navigation module that registers 2D US images with magnetic resonance imaging (MRI) based on high quality preoperative models. A 2-step spatial registration method is used to complete the procedure which combines manual alignment and rapid mutual information (MI) optimize algorithm. In addition, a 3-dimensional (3D) reconstruction model of prostate with surrounding organs is employed to combine with the registered images to conduct the navigation. Registration accuracy is measured by calculating the target registration error (TRE). The results show that the error between the US and preoperative MR images of a polyvinyl alcohol hydrogel model phantom is 1.37 ± 0.14 mm, with a similar performance being observed in patient experiments. PMID:26448009

  6. 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.

  7. Active illumination based 3D surface reconstruction and registration for image guided medialization laryngoplasty

    NASA Astrophysics Data System (ADS)

    Jin, Ge; Lee, Sang-Joon; Hahn, James K.; Bielamowicz, Steven; Mittal, Rajat; Walsh, Raymond

    2007-03-01

    The medialization laryngoplasty is a surgical procedure to improve the voice function of the patient with vocal fold paresis and paralysis. An image guided system for the medialization laryngoplasty will help the surgeons to accurately place the implant and thus reduce the failure rates of the surgery. One of the fundamental challenges in image guided system is to accurately register the preoperative radiological data to the intraoperative anatomical structure of the patient. In this paper, we present a combined surface and fiducial based registration method to register the preoperative 3D CT data to the intraoperative surface of larynx. To accurately model the exposed surface area, a structured light based stereo vision technique is used for the surface reconstruction. We combined the gray code pattern and multi-line shifting to generate the intraoperative surface of the larynx. To register the point clouds from the intraoperative stage to the preoperative 3D CT data, a shape priori based ICP method is proposed to quickly register the two surfaces. The proposed approach is capable of tracking the fiducial markers and reconstructing the surface of larynx with no damage to the anatomical structure. We used off-the-shelf digital cameras, LCD projector and rapid 3D prototyper to develop our experimental system. The final RMS error in the registration is less than 1mm.

  8. Evaluation of 3D multimodality image registration using receiver operating characteristic (ROC) analysis

    NASA Astrophysics Data System (ADS)

    Holton Tainter, Kerrie S.; Robb, Richard A.; Taneja, Udita; Gray, Joel E.

    1995-04-01

    Receiver operating characteristic analysis has evolved as a useful method for evaluating the discriminatory capability and efficacy of visualization. The ability of such analysis to account for the variance in decision criteria of multiple observers, multiple reading, and a wide range of difficulty in detection among case studies makes ROC especially useful for interpreting the results of a viewing experiment. We are currently using ROC analysis to evaluate the effectiveness of using fused multispectral, or complementary multimodality imaging data in the diagnostic process. The use of multispectral image recordings, gathered from multiple imaging modalities, to provide advanced image visualization and quantization capabilities in evaluating medical images is an important challenge facing medical imaging scientists. Such capabilities would potentially significantly enhance the ability of clinicians to extract scientific and diagnostic information from images. a first step in the effective use of multispectral information is the spatial registration of complementary image datasets so that a point-to-point correspondence exists between them. We are developing a paradigm of measuring the accuracy of existing image registration techniques which includes the ability to relate quantitative measurements, taken from the images themselves, to the decisions made by observers about the state of registration (SOR) of the 3D images. We have used ROC analysis to evaluate the ability of observers to discriminate between correctly registered and incorrectly registered multimodality fused images. We believe this experience is original and represents the first time that ROC analysis has been used to evaluate registered/fused images. We have simulated low-resolution and high-resolution images from real patient MR images of the brain, and fused them with the original MR to produce colorwash superposition images whose exact SOR is known. We have also attempted to extend this analysis to

  9. Evaluation and application of 3D lung warping and registration model using HRCT images

    NASA Astrophysics Data System (ADS)

    Fan, Li; Chen, Chang W.; Reinhardt, Joseph M.; Hoffman, Eric A.

    2001-05-01

    Image-based study of structure-function relationships is a challenging problem in that the structure or region of interest may vary in position and shape on images captured over time. Such variation may be caused by the change in body posture or the motion of breathing and heart beating. Therefore, the structure or region of interest should be registered before any further regional study can be carried out. In this paper, we propose a novel approach to study the structure-function relationship of ventilation using a previously developed 3D lung warping and registration model. First, we evaluate the effectiveness of the lung warping and registration model using a set of criteria, including apparent lung motion patterns and ground truths. Then, we study the ventilation by integrating the warping model with air content calibration. The warping model is applied to three CT lung data sets, obtained under volume control of FRC, 40% and 75% vital capacity (VC). Dense displacement fields are obtained to represent deformation between different lung volume steps. For any specific region of interest, we first register it between images over time using the dense displacement, and then estimate the corresponding regional inspired air content. Assessments include change of regional volume during inspiration, change of regional air content, and the distribution of regional ventilation. This is the first time that 3D warping of lung images is applied to assess clinically significant pulmonary functions.

  10. Rigid 2D/3D registration of intraoperative digital x-ray images and preoperative CT and MR images

    NASA Astrophysics Data System (ADS)

    Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo

    2002-05-01

    This paper describes a novel approach to register 3D computed tomography (CT) or magnetic resonance (MR) images to a set of 2D X-ray images. Such a registration may be a valuable tool for intraoperative determination of the precise position and orientation of some anatomy of interest, defined in preoperative images. The registration is based solely on the information present in 2D and 3D images. It does not require fiducial markers, X-ray image segmentation, or construction of digitally reconstructed radiographs. The originality of the approach is in using normals to bone surfaces, preoperatively defined in 3D MR or CT data, and gradients of intraoperative X-ray images, which are back-projected towards the X-ray source. The registration is then concerned with finding that rigid transformation of a CT or MR volume, which provides the best match between surface normals and back projected gradients, considering their amplitudes and orientations. The method is tested on a lumbar spine phantom. Gold standard registration is obtained by fidicual markers attached to the phantom. Volumes of interest, containing single vertebrae, are registered to different pairs of X-ray images from different starting positions, chosen randomly and uniformly around the gold standard position. Target registration errors and rotation errors are in order of 0.3 mm and 0.35 degrees for the CT to X-ray registration and 1.3 mm and 1.5 degrees for MR to X-ray registration. The registration is shown to be fast and accurate.

  11. Miniature stereoscopic video system provides real-time 3D registration and image fusion for minimally invasive surgery

    NASA Astrophysics Data System (ADS)

    Yaron, Avi; Bar-Zohar, Meir; Horesh, Nadav

    2007-02-01

    Sophisticated surgeries require the integration of several medical imaging modalities, like MRI and CT, which are three-dimensional. Many efforts are invested in providing the surgeon with this information in an intuitive & easy to use manner. A notable development, made by Visionsense, enables the surgeon to visualize the scene in 3D using a miniature stereoscopic camera. It also provides real-time 3D measurements that allow registration of navigation systems as well as 3D imaging modalities, overlaying these images on the stereoscopic video image in real-time. The real-time MIS 'see through tissue' fusion solutions enable the development of new MIS procedures in various surgical segments, such as spine, abdomen, cardio-thoracic and brain. This paper describes 3D surface reconstruction and registration methods using Visionsense camera, as a step toward fully automated multi-modality 3D registration.

  12. 3D non-rigid registration using surface and local salient features for transrectal ultrasound image-guided prostate biopsy

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Akbari, Hamed; Halig, Luma; Fei, Baowei

    2011-03-01

    We present a 3D non-rigid registration algorithm for the potential use in combining PET/CT and transrectal ultrasound (TRUS) images for targeted prostate biopsy. Our registration is a hybrid approach that simultaneously optimizes the similarities from point-based registration and volume matching methods. The 3D registration is obtained by minimizing the distances of corresponding points at the surface and within the prostate and by maximizing the overlap ratio of the bladder neck on both images. The hybrid approach not only capture deformation at the prostate surface and internal landmarks but also the deformation at the bladder neck regions. The registration uses a soft assignment and deterministic annealing process. The correspondences are iteratively established in a fuzzy-to-deterministic approach. B-splines are used to generate a smooth non-rigid spatial transformation. In this study, we tested our registration with pre- and postbiopsy TRUS images of the same patients. Registration accuracy is evaluated using manual defined anatomic landmarks, i.e. calcification. The root-mean-squared (RMS) of the difference image between the reference and floating images was decreased by 62.6+/-9.1% after registration. The mean target registration error (TRE) was 0.88+/-0.16 mm, i.e. less than 3 voxels with a voxel size of 0.38×0.38×0.38 mm3 for all five patients. The experimental results demonstrate the robustness and accuracy of the 3D non-rigid registration algorithm.

  13. Deformable image registration and 3D strain mapping for the quantitative assessment of cortical bone microdamage.

    PubMed

    Christen, David; Levchuk, Alina; Schori, Stefan; Schneider, Philipp; Boyd, Steven K; Müller, Ralph

    2012-04-01

    The resistance to forming microcracks is a key factor for bone to withstand critical loads without fracturing. In this study, we investigated the initiation and propagation of microcracks in murine cortical bone by combining three-dimensional images from synchrotron radiation-based computed tomography and time-lapsed biomechanical testing to observe microdamage accumulation over time. Furthermore, a novel deformable image registration procedure utilizing digital volume correlation and demons image registration was introduced to compute 3D strain maps allowing characterization of the mechanical environment of the microcracks. The displacement and strain maps were validated in a priori tests. At an image resolution of 740 nm the spatial resolution of the strain maps was 10 μm (MTF), while the errors of the displacements and strains were 130 nm and 0.013, respectively. The strain maps revealed a complex interaction of the propagating microcracks with the bone microstructure. In particular, we could show that osteocyte lacunae play a dual role as stress concentrating features reducing bone strength, while at the same time contributing to the bone toughness by blunting the crack tip. We conclude that time-lapsed biomechanical imaging in combination with three-dimensional strain mapping is suitable for the investigation of crack initiation and propagation in many porous materials under various loading scenarios. PMID:22402165

  14. GPU accelerated registration of a statistical shape model of the lumbar spine to 3D ultrasound images

    NASA Astrophysics Data System (ADS)

    Khallaghi, Siavash; Abolmaesumi, Purang; Gong, Ren Hui; Chen, Elvis; Gill, Sean; Boisvert, Jonathan; Pichora, David; Borschneck, Dan; Fichtinger, Gabor; Mousavi, Parvin

    2011-03-01

    We present a parallel implementation of a statistical shape model registration to 3D ultrasound images of the lumbar vertebrae (L2-L4). Covariance Matrix Adaptation Evolution Strategy optimization technique, along with Linear Correlation of Linear Combination similarity metric have been used, to improve the robustness and capture range of the registration approach. Instantiation and ultrasound simulation have been implemented on a graphics processing unit for a faster registration. Phantom studies show a mean target registration error of 3.2 mm, while 80% of all the cases yield target registration error of below 3.5 mm.

  15. Registration of Real-Time 3-D Ultrasound to Tomographic Images of the Abdominal Aorta.

    PubMed

    Brekken, Reidar; Iversen, Daniel Høyer; Tangen, Geir Arne; Dahl, Torbjørn

    2016-08-01

    The purpose of this study was to develop an image-based method for registration of real-time 3-D ultrasound to computed tomography (CT) of the abdominal aorta, targeting future use in ultrasound-guided endovascular intervention. We proposed a method in which a surface model of the aortic wall was segmented from CT, and the approximate initial location of this model relative to the ultrasound volume was manually indicated. The model was iteratively transformed to automatically optimize correspondence to the ultrasound data. Feasibility was studied using data from a silicon phantom and in vivo data from a volunteer with previously acquired CT. Through visual evaluation, the ultrasound and CT data were seen to correspond well after registration. Both aortic lumen and branching arteries were well aligned. The processing was done offline, and the registration took approximately 0.2 s per ultrasound volume. The results encourage further patient studies to investigate accuracy, robustness and clinical value of the approach. PMID:27156015

  16. 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.

  17. Registration of 2D x-ray images to 3D MRI by generating pseudo-CT data

    NASA Astrophysics Data System (ADS)

    van der Bom, M. J.; Pluim, J. P. W.; Gounis, M. J.; van de Kraats, E. B.; Sprinkhuizen, S. M.; Timmer, J.; Homan, R.; Bartels, L. W.

    2011-02-01

    Spatial and soft tissue information provided by magnetic resonance imaging can be very valuable during image-guided procedures, where usually only real-time two-dimensional (2D) x-ray images are available. Registration of 2D x-ray images to three-dimensional (3D) magnetic resonance imaging (MRI) data, acquired prior to the procedure, can provide optimal information to guide the procedure. However, registering x-ray images to MRI data is not a trivial task because of their fundamental difference in tissue contrast. This paper presents a technique that generates pseudo-computed tomography (CT) data from multi-spectral MRI acquisitions which is sufficiently similar to real CT data to enable registration of x-ray to MRI with comparable accuracy as registration of x-ray to CT. The method is based on a k-nearest-neighbors (kNN)-regression strategy which labels voxels of MRI data with CT Hounsfield Units. The regression method uses multi-spectral MRI intensities and intensity gradients as features to discriminate between various tissue types. The efficacy of using pseudo-CT data for registration of x-ray to MRI was tested on ex vivo animal data. 2D-3D registration experiments using CT and pseudo-CT data of multiple subjects were performed with a commonly used 2D-3D registration algorithm. On average, the median target registration error for registration of two x-ray images to MRI data was approximately 1 mm larger than for x-ray to CT registration. The authors have shown that pseudo-CT data generated from multi-spectral MRI facilitate registration of MRI to x-ray images. From the experiments it could be concluded that the accuracy achieved was comparable to that of registering x-ray images to CT data.

  18. A 2D to 3D ultrasound image registration algorithm for robotically assisted laparoscopic radical prostatectomy

    NASA Astrophysics Data System (ADS)

    Esteghamatian, Mehdi; Pautler, Stephen E.; McKenzie, Charles A.; Peters, Terry M.

    2011-03-01

    Robotically assisted laparoscopic radical prostatectomy (RARP) is an effective approach to resect the diseased organ, with stereoscopic views of the targeted tissue improving the dexterity of the surgeons. However, since the laparoscopic view acquires only the surface image of the tissue, the underlying distribution of the cancer within the organ is not observed, making it difficult to make informed decisions on surgical margins and sparing of neurovascular bundles. One option to address this problem is to exploit registration to integrate the laparoscopic view with images of pre-operatively acquired dynamic contrast enhanced (DCE) MRI that can demonstrate the regions of malignant tissue within the prostate. Such a view potentially allows the surgeon to visualize the location of the malignancy with respect to the surrounding neurovascular structures, permitting a tissue-sparing strategy to be formulated directly based on the observed tumour distribution. If the tumour is close to the capsule, it may be determined that the adjacent neurovascular bundle (NVB) needs to be sacrificed within the surgical margin to ensure that any erupted tumour was resected. On the other hand, if the cancer is sufficiently far from the capsule, one or both NVBs may be spared. However, in order to realize such image integration, the pre-operative image needs to be fused with the laparoscopic view of the prostate. During the initial stages of the operation, the prostate must be tracked in real time so that the pre-operative MR image remains aligned with patient coordinate system. In this study, we propose and investigate a novel 2D to 3D ultrasound image registration algorithm to track the prostate motion with an accuracy of 2.68+/-1.31mm.

  19. 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes

    PubMed Central

    Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun

    2016-01-01

    By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes. PMID:27019849

  20. Accurate quantification of local changes for carotid arteries in 3D ultrasound images using convex optimization-based deformable registration

    NASA Astrophysics Data System (ADS)

    Cheng, Jieyu; Qiu, Wu; Yuan, Jing; Fenster, Aaron; Chiu, Bernard

    2016-03-01

    Registration of longitudinally acquired 3D ultrasound (US) images plays an important role in monitoring and quantifying progression/regression of carotid atherosclerosis. We introduce an image-based non-rigid registration algorithm to align the baseline 3D carotid US with longitudinal images acquired over several follow-up time points. This algorithm minimizes the sum of absolute intensity differences (SAD) under a variational optical-flow perspective within a multi-scale optimization framework to capture local and global deformations. Outer wall and lumen were segmented manually on each image, and the performance of the registration algorithm was quantified by Dice similarity coefficient (DSC) and mean absolute distance (MAD) of the outer wall and lumen surfaces after registration. In this study, images for 5 subjects were registered initially by rigid registration, followed by the proposed algorithm. Mean DSC generated by the proposed algorithm was 79:3+/-3:8% for lumen and 85:9+/-4:0% for outer wall, compared to 73:9+/-3:4% and 84:7+/-3:2% generated by rigid registration. Mean MAD of 0:46+/-0:08mm and 0:52+/-0:13mm were generated for lumen and outer wall respectively by the proposed algorithm, compared to 0:55+/-0:08mm and 0:54+/-0:11mm generated by rigid registration. The mean registration time of our method per image pair was 143+/-23s.

  1. Fast myocardial strain estimation from 3D ultrasound through elastic image registration with analytic regularization

    NASA Astrophysics Data System (ADS)

    Chakraborty, Bidisha; Heyde, Brecht; Alessandrini, Martino; D'hooge, Jan

    2016-04-01

    Image registration techniques using free-form deformation models have shown promising results for 3D myocardial strain estimation from ultrasound. However, the use of this technique has mostly been limited to research institutes due to the high computational demand, which is primarily due to the computational load of the regularization term ensuring spatially smooth cardiac strain estimates. Indeed, this term typically requires evaluating derivatives of the transformation field numerically in each voxel of the image during every iteration of the optimization process. In this paper, we replace this time-consuming step with a closed-form solution directly associated with the transformation field resulting in a speed up factor of ~10-60,000, for a typical 3D B-mode image of 2503 and 5003 voxels, depending upon the size and the parametrization of the transformation field. The performance of the numeric and the analytic solutions was contrasted by computing tracking and strain accuracy on two realistic synthetic 3D cardiac ultrasound sequences, mimicking two ischemic motion patterns. Mean and standard deviation of the displacement errors over the cardiac cycle for the numeric and analytic solutions were 0.68+/-0.40 mm and 0.75+/-0.43 mm respectively. Correlations for the radial, longitudinal and circumferential strain components at end-systole were 0.89, 0.83 and 0.95 versus 0.90, 0.88 and 0.92 for the numeric and analytic regularization respectively. The analytic solution matched the performance of the numeric solution as no statistically significant differences (p>0.05) were found when expressed in terms of bias or limits-of-agreement.

  2. Statistical 3D Prostate Imaging Atlas Construction via Anatomically Constrained Registration

    PubMed Central

    Rusu, Mirabela; Bloch, B. Nicolas; Jaffe, Carl C.; Rofsky, Neil M.; Genega, Elizabeth M.; Feleppa, Ernest; Lenkinski, Robert E.; Madabhushi, Anant

    2013-01-01

    Statistical imaging atlases allow for integration of information from multiple patient studies collected across different image scales and modalities, such as multi-parametric (MP) MRI and histology, providing population statistics regarding a specific pathology within a single canonical representation. Such atlases are particularly valuable in the identification and validation of meaningful imaging signatures for disease characterization in vivo within a population. Despite the high incidence of prostate cancer, an imaging atlas focused on different anatomic structures of the prostate, i.e. an anatomic atlas, has yet to be constructed. In this work we introduce a novel framework for MRI atlas construction that uses an iterative, anatomically constrained registration (AnCoR) scheme to enable the proper alignment of the prostate (Pr) and central gland (CG) boundaries. Our current implementation uses endorectal, 1.5T or 3T, T2-weighted MRI from 51 patients with biopsy confirmed cancer; however, the prostate atlas is seamlessly extensible to include additional MRI parameters. In our cohort, radical prostatectomy is performed following MP-MR image acquisition; thus ground truth annotations for prostate cancer are available from the histological specimens. Once mapped onto MP-MRI through elastic registration of histological slices to corresponding T2-w MRI slices, the annotations are utilized by the AnCoR framework to characterize the 3D statistical distribution of cancer per anatomic structure. Such distributions are useful for guiding biopsies toward regions of higher cancer likelihood and understanding imaging profiles for disease extent in vivo. We evaluate our approach via the Dice similarity coefficient (DSC) for different anatomic structures (delineated by expert radiologists): Pr, CG and peripheral zone (PZ). The AnCoR-based atlas had a CG DSC of 90.36%, and Pr DSC of 89.37%. Moreover, we evaluated the deviation of anatomic landmarks, the urethra and

  3. Statistical 3D prostate imaging atlas construction via anatomically constrained registration

    NASA Astrophysics Data System (ADS)

    Rusu, Mirabela; Bloch, B. Nicolas; Jaffe, Carl C.; Rofsky, Neil M.; Genega, Elizabeth M.; Feleppa, Ernest; Lenkinski, Robert E.; Madabhushi, Anant

    2013-03-01

    Statistical imaging atlases allow for integration of information from multiple patient studies collected across different image scales and modalities, such as multi-parametric (MP) MRI and histology, providing population statistics regarding a specific pathology within a single canonical representation. Such atlases are particularly valuable in the identification and validation of meaningful imaging signatures for disease characterization in vivo within a population. Despite the high incidence of prostate cancer, an imaging atlas focused on different anatomic structures of the prostate, i.e. an anatomic atlas, has yet to be constructed. In this work we introduce a novel framework for MRI atlas construction that uses an iterative, anatomically constrained registration (AnCoR) scheme to enable the proper alignment of the prostate (Pr) and central gland (CG) boundaries. Our current implementation uses endorectal, 1.5T or 3T, T2-weighted MRI from 51 patients with biopsy confirmed cancer; however, the prostate atlas is seamlessly extensible to include additional MRI parameters. In our cohort, radical prostatectomy is performed following MP-MR image acquisition; thus ground truth annotations for prostate cancer are available from the histological specimens. Once mapped onto MP-MRI through elastic registration of histological slices to corresponding T2-w MRI slices, the annotations are utilized by the AnCoR framework to characterize the 3D statistical distribution of cancer per anatomic structure. Such distributions are useful for guiding biopsies toward regions of higher cancer likelihood and understanding imaging profiles for disease extent in vivo. We evaluate our approach via the Dice similarity coefficient (DSC) for different anatomic structures (delineated by expert radiologists): Pr, CG and peripheral zone (PZ). The AnCoR-based atlas had a CG DSC of 90.36%, and Pr DSC of 89.37%. Moreover, we evaluated the deviation of anatomic landmarks, the urethra and

  4. A comparison of the 3D kinematic measurements obtained by single-plane 2D-3D image registration and RSA.

    PubMed

    Muhit, Abdullah A; Pickering, Mark R; Ward, Tom; Scarvell, Jennie M; Smith, Paul N

    2010-01-01

    3D computed tomography (CT) to single-plane 2D fluoroscopy registration is an emerging technology for many clinical applications such as kinematic analysis of human joints and image-guided surgery. However, previous registration approaches have suffered from the inaccuracy of determining precise motion parameters for out-of-plane movements. In this paper we compare kinematic measurements obtained by a new 2D-3D registration algorithm with measurements provided by the gold standard Roentgen Stereo Analysis (RSA). In particular, we are interested in the out-of-plane translation and rotations which are difficult to measure precisely using a single plane approach. Our experimental results show that the standard deviation of the error for out-of-plane translation is 0.42 mm which compares favourably to RSA. It is also evident that our approach produces very similar flexion/extension, abduction/adduction and external knee rotation angles when compared to RSA. PMID:21097358

  5. Recovering 3D tumor locations from 2D bioluminescence images and registration with CT images

    NASA Astrophysics Data System (ADS)

    Huang, Xiaolei; Metaxas, Dimitris N.; Menon, Lata G.; Mayer-Kuckuk, Philipp; Bertino, Joseph R.; Banerjee, Debabrata

    2006-02-01

    In this paper, we introduce a novel and efficient algorithm for reconstructing the 3D locations of tumor sites from a set of 2D bioluminescence images which are taken by a same camera but after continually rotating the object by a small angle. Our approach requires a much simpler set up than those using multiple cameras, and the algorithmic steps in our framework are efficient and robust enough to facilitate its use in analyzing the repeated imaging of a same animal transplanted with gene marked cells. In order to visualize in 3D the structure of the tumor, we also co-register the BLI-reconstructed crude structure with detailed anatomical structure extracted from high-resolution microCT on a single platform. We present our method using both phantom studies and real studies on small animals.

  6. 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.

  7. Towards real-time 2D/3D registration for organ motion monitoring in image-guided radiation therapy

    NASA Astrophysics Data System (ADS)

    Gendrin, C.; Spoerk, J.; Bloch, C.; Pawiro, S. A.; Weber, C.; Figl, M.; Markelj, P.; Pernus, F.; Georg, D.; Bergmann, H.; Birkfellner, W.

    2010-02-01

    Nowadays, radiation therapy systems incorporate kV imaging units which allow for the real-time acquisition of intra-fractional X-ray images of the patient with high details and contrast. An application of this technology is tumor motion monitoring during irradiation. For tumor tracking, implanted markers or position sensors are used which requires an intervention. 2D/3D intensity based registration is an alternative, non-invasive method but the procedure must be accelerate to the update rate of the device, which lies in the range of 5 Hz. In this paper we investigate fast CT to a single kV X-ray 2D/3D image registration using a new porcine reference phantom with seven implanted fiducial markers. Several parameters influencing the speed and accuracy of the registrations are investigated. First, four intensity based merit functions, namely Cross-Correlation, Rank Correlation, Mutual Information and Correlation Ratio, are compared. Secondly, wobbled splatting and ray casting rendering techniques are implemented on the GPU and the influence of each algorithm on the performance of 2D/3D registration is evaluated. Rendering times for a single DRR of 20 ms were achieved. Different thresholds of the CT volume were also examined for rendering to find the setting that achieves the best possible correspondence with the X-ray images. Fast registrations below 4 s became possible with an inplane accuracy down to 0.8 mm.

  8. Robust initialization of 2D-3D image registration using the projection-slice theorem and phase correlation

    SciTech Connect

    Bom, M. J. van der; Bartels, L. W.; Gounis, M. J.; Homan, R.; Timmer, J.; Viergever, M. A.; Pluim, J. P. W.

    2010-04-15

    Purpose: The image registration literature comprises many methods for 2D-3D registration for which accuracy has been established in a variety of applications. However, clinical application is limited by a small capture range. Initial offsets outside the capture range of a registration method will not converge to a successful registration. Previously reported capture ranges, defined as the 95% success range, are in the order of 4-11 mm mean target registration error. In this article, a relatively computationally inexpensive and robust estimation method is proposed with the objective to enlarge the capture range. Methods: The method uses the projection-slice theorem in combination with phase correlation in order to estimate the transform parameters, which provides an initialization of the subsequent registration procedure. Results: The feasibility of the method was evaluated by experiments using digitally reconstructed radiographs generated from in vivo 3D-RX data. With these experiments it was shown that the projection-slice theorem provides successful estimates of the rotational transform parameters for perspective projections and in case of translational offsets. The method was further tested on ex vivo ovine x-ray data. In 95% of the cases, the method yielded successful estimates for initial mean target registration errors up to 19.5 mm. Finally, the method was evaluated as an initialization method for an intensity-based 2D-3D registration method. The uninitialized and initialized registration experiments had success rates of 28.8% and 68.6%, respectively. Conclusions: The authors have shown that the initialization method based on the projection-slice theorem and phase correlation yields adequate initializations for existing registration methods, thereby substantially enlarging the capture range of these methods.

  9. Joint detection of anatomical points on surface meshes and color images for visual registration of 3D dental models

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Computer aided planning for orthodontic treatment requires knowing occlusion of separately scanned dental casts. A visual guided registration is conducted starting by extracting corresponding features in both photographs and 3D scans. To achieve this, dental neck and occlusion surface are firstly extracted by image segmentation and 3D curvature analysis. Then, an iterative registration process is conducted during which feature positions are refined, guided by previously found anatomic edges. The occlusal edge image detection is improved by an original algorithm which follows Canny's poorly detected edges using a priori knowledge of tooth shapes. Finally, the influence of feature extraction and position optimization is evaluated in terms of the quality of the induced registration. Best combination of feature detection and optimization leads to a positioning average error of 1.10 mm and 2.03°.

  10. 2D-3D registration for prostate radiation therapy based on a statistical model of transmission images

    SciTech Connect

    Munbodh, Reshma; Tagare, Hemant D.; Chen Zhe; Jaffray, David A.; Moseley, Douglas J.; Knisely, Jonathan P. S.; Duncan, James S.

    2009-10-15

    Purpose: In external beam radiation therapy of pelvic sites, patient setup errors can be quantified by registering 2D projection radiographs acquired during treatment to a 3D planning computed tomograph (CT). We present a 2D-3D registration framework based on a statistical model of the intensity values in the two imaging modalities. Methods: The model assumes that intensity values in projection radiographs are independently but not identically distributed due to the nonstationary nature of photon counting noise. Two probability distributions are considered for the intensity values: Poisson and Gaussian. Using maximum likelihood estimation, two similarity measures, maximum likelihood with a Poisson (MLP) and maximum likelihood with Gaussian (MLG), distribution are derived. Further, we investigate the merit of the model-based registration approach for data obtained with current imaging equipment and doses by comparing the performance of the similarity measures derived to that of the Pearson correlation coefficient (ICC) on accurately collected data of an anthropomorphic phantom of the pelvis and on patient data. Results: Registration accuracy was similar for all three similarity measures and surpassed current clinical requirements of 3 mm for pelvic sites. For pose determination experiments with a kilovoltage (kV) cone-beam CT (CBCT) and kV projection radiographs of the phantom in the anterior-posterior (AP) view, registration accuracies were 0.42 mm (MLP), 0.29 mm (MLG), and 0.29 mm (ICC). For kV CBCT and megavoltage (MV) AP portal images of the same phantom, registration accuracies were 1.15 mm (MLP), 0.90 mm (MLG), and 0.69 mm (ICC). Registration of a kV CT and MV AP portal images of a patient was successful in all instances. Conclusions: The results indicate that high registration accuracy is achievable with multiple methods including methods that are based on a statistical model of a 3D CT and 2D projection images.

  11. Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments.

    PubMed

    Li, Guang; Xie, Huchen; Ning, Holly; Citrin, Deborah; Capala, Jacek; Maass-Moreno, Roberto; Guion, Peter; Arora, Barbara; Coleman, Norman; Camphausen, Kevin; Miller, Robert W

    2008-01-01

    Registration is critical for image-based treatment planning and image-guided treatment delivery. Although automatic registration is available, manual, visual-based image fusion using three orthogonal planar views (3P) is always employed clinically to verify and adjust an automatic registration result. However, the 3P fusion can be time consuming, observer dependent, as well as prone to errors, owing to the incomplete 3-dimensional (3D) volumetric image representations. It is also limited to single-pixel precision (the screen resolution). The 3D volumetric image registration (3DVIR) technique was developed to overcome these shortcomings. This technique introduces a 4th dimension in the registration criteria beyond the image volume, offering both visual and quantitative correlation of corresponding anatomic landmarks within the two registration images, facilitating a volumetric image alignment, and minimizing potential registration errors. The 3DVIR combines image classification in real-time to select and visualize a reliable anatomic landmark, rather than using all voxels for alignment. To determine the detection limit of the visual and quantitative 3DVIR criteria, slightly misaligned images were simulated and presented to eight clinical personnel for interpretation. Both of the criteria produce a detection limit of 0.1 mm and 0.1 degree. To determine the accuracy of the 3DVIR method, three imaging modalities (CT, MR and PET/CT) were used to acquire multiple phantom images with known spatial shifts. Lateral shifts were applied to these phantoms with displacement intervals of 5.0+/-0.1 mm. The accuracy of the 3DVIR technique was determined by comparing the image shifts determined through registration to the physical shifts made experimentally. The registration accuracy, together with precision, was found to be: 0.02+/-0.09 mm for CT/CT images, 0.03+/-0.07 mm for MR/MR images, and 0.03+/-0.35 mm for PET/CT images. This accuracy is consistent with the detection limit

  12. Curve-based 2D-3D registration of coronary vessels for image guided procedure

    NASA Astrophysics Data System (ADS)

    Duong, Luc; Liao, Rui; Sundar, Hari; Tailhades, Benoit; Meyer, Andreas; Xu, Chenyang

    2009-02-01

    3D roadmap provided by pre-operative volumetric data that is aligned with fluoroscopy helps visualization and navigation in Interventional Cardiology (IC), especially when contrast agent-injection used to highlight coronary vessels cannot be systematically used during the whole procedure, or when there is low visibility in fluoroscopy for partially or totally occluded vessels. The main contribution of this work is to register pre-operative volumetric data with intraoperative fluoroscopy for specific vessel(s) occurring during the procedure, even without contrast agent injection, to provide a useful 3D roadmap. In addition, this study incorporates automatic ECG gating for cardiac motion. Respiratory motion is identified by rigid body registration of the vessels. The coronary vessels are first segmented from a multislice computed tomography (MSCT) volume and correspondent vessel segments are identified on a single gated 2D fluoroscopic frame. Registration can be explicitly constrained using one or multiple branches of a contrast-enhanced vessel tree or the outline of guide wire used to navigate during the procedure. Finally, the alignment problem is solved by Iterative Closest Point (ICP) algorithm. To be computationally efficient, a distance transform is computed from the 2D identification of each vessel such that distance is zero on the centerline of the vessel and increases away from the centerline. Quantitative results were obtained by comparing the registration of random poses and a ground truth alignment for 5 datasets. We conclude that the proposed method is promising for accurate 2D-3D registration, even for difficult cases of occluded vessel without injection of contrast agent.

  13. 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.

  14. Known-component 3D-2D registration for image guidance and quality assurance in spine surgery pedicle screw placement

    NASA Astrophysics Data System (ADS)

    Uneri, A.; Stayman, J. W.; De Silva, T.; Wang, A. S.; Kleinszig, G.; Vogt, S.; Khanna, A. J.; Wolinsky, J.-P.; Gokaslan, Z. L.; Siewerdsen, J. H.

    2015-03-01

    Purpose. To extend the functionality of radiographic / fluoroscopic imaging systems already within standard spine surgery workflow to: 1) provide guidance of surgical device analogous to an external tracking system; and 2) provide intraoperative quality assurance (QA) of the surgical product. Methods. Using fast, robust 3D-2D registration in combination with 3D models of known components (surgical devices), the 3D pose determination was solved to relate known components to 2D projection images and 3D preoperative CT in near-real-time. Exact and parametric models of the components were used as input to the algorithm to evaluate the effects of model fidelity. The proposed algorithm employs the covariance matrix adaptation evolution strategy (CMA-ES) to maximize gradient correlation (GC) between measured projections and simulated forward projections of components. Geometric accuracy was evaluated in a spine phantom in terms of target registration error at the tool tip (TREx), and angular deviation (TREΦ) from planned trajectory. Results. Transpedicle surgical devices (probe tool and spine screws) were successfully guided with TREx<2 mm and TREΦ <0.5° given projection views separated by at least >30° (easily accommodated on a mobile C-arm). QA of the surgical product based on 3D-2D registration demonstrated the detection of pedicle screw breach with TREx<1 mm, demonstrating a trend of improved accuracy correlated to the fidelity of the component model employed. Conclusions. 3D-2D registration combined with 3D models of known surgical components provides a novel method for near-real-time guidance and quality assurance using a mobile C-arm without external trackers or fiducial markers. Ongoing work includes determination of optimal views based on component shape and trajectory, improved robustness to anatomical deformation, and expanded preclinical testing in spine and intracranial surgeries.

  15. Self-calibration of cone-beam CT geometry using 3D-2D image registration.

    PubMed

    Ouadah, S; Stayman, J W; Gang, G J; Ehtiati, T; Siewerdsen, J H

    2016-04-01

    Robotic C-arms are capable of complex orbits that can increase field of view, reduce artifacts, improve image quality, and/or reduce dose; however, it can be challenging to obtain accurate, reproducible geometric calibration required for image reconstruction for such complex orbits. This work presents a method for geometric calibration for an arbitrary source-detector orbit by registering 2D projection data to a previously acquired 3D image. It also yields a method by which calibration of simple circular orbits can be improved. The registration uses a normalized gradient information similarity metric and the covariance matrix adaptation-evolution strategy optimizer for robustness against local minima and changes in image content. The resulting transformation provides a 'self-calibration' of system geometry. The algorithm was tested in phantom studies using both a cone-beam CT (CBCT) test-bench and a robotic C-arm (Artis Zeego, Siemens Healthcare) for circular and non-circular orbits. Self-calibration performance was evaluated in terms of the full-width at half-maximum (FWHM) of the point spread function in CBCT reconstructions, the reprojection error (RPE) of steel ball bearings placed on each phantom, and the overall quality and presence of artifacts in CBCT images. In all cases, self-calibration improved the FWHM-e.g. on the CBCT bench, FWHM  =  0.86 mm for conventional calibration compared to 0.65 mm for self-calibration (p  <  0.001). Similar improvements were measured in RPE-e.g. on the robotic C-arm, RPE  =  0.73 mm for conventional calibration compared to 0.55 mm for self-calibration (p  <  0.001). Visible improvement was evident in CBCT reconstructions using self-calibration, particularly about high-contrast, high-frequency objects (e.g. temporal bone air cells and a surgical needle). The results indicate that self-calibration can improve even upon systems with presumably accurate geometric calibration and is

  16. Self-calibration of cone-beam CT geometry using 3D-2D image registration

    NASA Astrophysics Data System (ADS)

    Ouadah, S.; Stayman, J. W.; Gang, G. J.; Ehtiati, T.; Siewerdsen, J. H.

    2016-04-01

    Robotic C-arms are capable of complex orbits that can increase field of view, reduce artifacts, improve image quality, and/or reduce dose; however, it can be challenging to obtain accurate, reproducible geometric calibration required for image reconstruction for such complex orbits. This work presents a method for geometric calibration for an arbitrary source-detector orbit by registering 2D projection data to a previously acquired 3D image. It also yields a method by which calibration of simple circular orbits can be improved. The registration uses a normalized gradient information similarity metric and the covariance matrix adaptation-evolution strategy optimizer for robustness against local minima and changes in image content. The resulting transformation provides a ‘self-calibration’ of system geometry. The algorithm was tested in phantom studies using both a cone-beam CT (CBCT) test-bench and a robotic C-arm (Artis Zeego, Siemens Healthcare) for circular and non-circular orbits. Self-calibration performance was evaluated in terms of the full-width at half-maximum (FWHM) of the point spread function in CBCT reconstructions, the reprojection error (RPE) of steel ball bearings placed on each phantom, and the overall quality and presence of artifacts in CBCT images. In all cases, self-calibration improved the FWHM—e.g. on the CBCT bench, FWHM  =  0.86 mm for conventional calibration compared to 0.65 mm for self-calibration (p  <  0.001). Similar improvements were measured in RPE—e.g. on the robotic C-arm, RPE  =  0.73 mm for conventional calibration compared to 0.55 mm for self-calibration (p  <  0.001). Visible improvement was evident in CBCT reconstructions using self-calibration, particularly about high-contrast, high-frequency objects (e.g. temporal bone air cells and a surgical needle). The results indicate that self-calibration can improve even upon systems with presumably accurate geometric calibration and is

  17. High-accuracy 3D image-based registration of endoscopic video to C-arm cone-beam CT for image-guided skull base surgery

    NASA Astrophysics Data System (ADS)

    Mirota, Daniel J.; Uneri, Ali; Schafer, Sebastian; Nithiananthan, Sajendra; Reh, Douglas D.; Gallia, Gary L.; Taylor, Russell H.; Hager, Gregory D.; Siewerdsen, Jeffrey H.

    2011-03-01

    Registration of endoscopic video to preoperative CT facilitates high-precision surgery of the head, neck, and skull-base. Conventional video-CT registration is limited by the accuracy of the tracker and does not use the underlying video or CT image data. A new image-based video registration method has been developed to overcome the limitations of conventional tracker-based registration. This method adds to a navigation system based on intraoperative C-arm cone-beam CT (CBCT), in turn providing high-accuracy registration of video to the surgical scene. The resulting registration enables visualization of the CBCT and planning data within the endoscopic video. The system incorporates a mobile C-arm, integrated with an optical tracking system, video endoscopy, deformable registration of preoperative CT with intraoperative CBCT, and 3D visualization. Similarly to tracker-based approach, the image-based video-CBCT registration the endoscope is localized with optical tracking system followed by a direct 3D image-based registration of the video to the CBCT. In this way, the system achieves video-CBCT registration that is both fast and accurate. Application in skull-base surgery demonstrates overlay of critical structures (e.g., carotid arteries) and surgical targets with sub-mm accuracy. Phantom and cadaver experiments show consistent improvement of target registration error (TRE) in video overlay over conventional tracker-based registration-e.g., 0.92mm versus 1.82mm for image-based and tracker-based registration, respectively. The proposed method represents a two-fold advance-first, through registration of video to up-to-date intraoperative CBCT, and second, through direct 3D image-based video-CBCT registration, which together provide more confident visualization of target and normal tissues within up-to-date images.

  18. Auto-masked 2D/3D image registration and its validation with clinical cone-beam computed tomography

    NASA Astrophysics Data System (ADS)

    Steininger, P.; Neuner, M.; Weichenberger, H.; Sharp, G. C.; Winey, B.; Kametriser, G.; Sedlmayer, F.; Deutschmann, H.

    2012-07-01

    Image-guided alignment procedures in radiotherapy aim at minimizing discrepancies between the planned and the real patient setup. For that purpose, we developed a 2D/3D approach which rigidly registers a computed tomography (CT) with two x-rays by maximizing the agreement in pixel intensity between the x-rays and the corresponding reconstructed radiographs from the CT. Moreover, the algorithm selects regions of interest (masks) in the x-rays based on 3D segmentations from the pre-planning stage. For validation, orthogonal x-ray pairs from different viewing directions of 80 pelvic cone-beam CT (CBCT) raw data sets were used. The 2D/3D results were compared to corresponding standard 3D/3D CBCT-to-CT alignments. Outcome over 8400 2D/3D experiments showed that parametric errors in root mean square were <0.18° (rotations) and <0.73 mm (translations), respectively, using rank correlation as intensity metric. This corresponds to a mean target registration error, related to the voxels of the lesser pelvis, of <2 mm in 94.1% of the cases. From the results we conclude that 2D/3D registration based on sequentially acquired orthogonal x-rays of the pelvis is a viable alternative to CBCT-based approaches if rigid alignment on bony anatomy is sufficient, no volumetric intra-interventional data set is required and the expected error range fits the individual treatment prescription.

  19. Auto-masked 2D/3D image registration and its validation with clinical cone-beam computed tomography.

    PubMed

    Steininger, P; Neuner, M; Weichenberger, H; Sharp, G C; Winey, B; Kametriser, G; Sedlmayer, F; Deutschmann, H

    2012-07-01

    Image-guided alignment procedures in radiotherapy aim at minimizing discrepancies between the planned and the real patient setup. For that purpose, we developed a 2D/3D approach which rigidly registers a computed tomography (CT) with two x-rays by maximizing the agreement in pixel intensity between the x-rays and the corresponding reconstructed radiographs from the CT. Moreover, the algorithm selects regions of interest (masks) in the x-rays based on 3D segmentations from the pre-planning stage. For validation, orthogonal x-ray pairs from different viewing directions of 80 pelvic cone-beam CT (CBCT) raw data sets were used. The 2D/3D results were compared to corresponding standard 3D/3D CBCT-to-CT alignments. Outcome over 8400 2D/3D experiments showed that parametric errors in root mean square were <0.18° (rotations) and <0.73 mm (translations), respectively, using rank correlation as intensity metric. This corresponds to a mean target registration error, related to the voxels of the lesser pelvis, of <2 mm in 94.1% of the cases. From the results we conclude that 2D/3D registration based on sequentially acquired orthogonal x-rays of the pelvis is a viable alternative to CBCT-based approaches if rigid alignment on bony anatomy is sufficient, no volumetric intra-interventional data set is required and the expected error range fits the individual treatment prescription. PMID:22705709

  20. Geometry-based vs. intensity-based medical image registration: A comparative study on 3D CT data.

    PubMed

    Savva, Antonis D; Economopoulos, Theodore L; Matsopoulos, George K

    2016-02-01

    Spatial alignment of Computed Tomography (CT) data sets is often required in numerous medical applications and it is usually achieved by applying conventional exhaustive registration techniques, which are mainly based on the intensity of the subject data sets. Those techniques consider the full range of data points composing the data, thus negatively affecting the required processing time. Alternatively, alignment can be performed using the correspondence of extracted data points from both sets. Moreover, various geometrical characteristics of those data points can be used, instead of their chromatic properties, for uniquely characterizing each point, by forming a specific geometrical descriptor. This paper presents a comparative study reviewing variations of geometry-based, descriptor-oriented registration techniques, as well as conventional, exhaustive, intensity-based methods for aligning three-dimensional (3D) CT data pairs. In this context, three general image registration frameworks were examined: a geometry-based methodology featuring three distinct geometrical descriptors, an intensity-based methodology using three different similarity metrics, as well as the commonly used Iterative Closest Point algorithm. All techniques were applied on a total of thirty 3D CT data pairs with both known and unknown initial spatial differences. After an extensive qualitative and quantitative assessment, it was concluded that the proposed geometry-based registration framework performed similarly to the examined exhaustive registration techniques. In addition, geometry-based methods dramatically improved processing time over conventional exhaustive registration. PMID:26771247

  1. Evaluation and validation methods for intersubject nonrigid 3D image registration of the human brain

    NASA Astrophysics Data System (ADS)

    Guo, Ting; Starreveld, Yves P.; Peters, Terry M.

    2005-04-01

    This work presents methodologies for assessing the accuracy of non-rigid intersubject registration algorithms from both qualitative and quantitative perspectives. The first method was based on a set of 43 anatomical landmarks. MRI brain images of 12 subjects were non-rigidly registered to the standard MRI dataset. The "gold-standard" coordinates of the 43 landmarks in the target were estimated by averaging their coordinates after 6 tagging sessions. The Euclidean distance between each landmark of a subject after warping to the reference space and the homologous "gold-standard" landmark on the reference image was considered as the registration error. Another method based on visual inspection software displaying the spatial change of colour-coded spheres, before and after warping, was also developed to evaluate the performance of the non-rigid warping algorithms within the homogeneous regions in the deep-brain. Our methods were exemplified by assessing and comparing the accuracy of two intersubject non-rigid registration approaches, AtamaiWarp and ANIMAL algorithms. From the first method, the average registration error was 1.04mm +/- 0.65mm for AtamaiWarp, and 1.59mm +/- 1.47mm for ANIMAL. With maximum registration errors of 2.78mm and 3.90mm respectively, AtamaiWarp and ANIMAL located 58% and 35% landmarks respectively with registration errors less than 1mm. A paired t-test showed that the differences in registration error between AtamaiWarp and ANIMAL were significant (P < 0.002) demonstrating that AtamaiWarp, in addition to being over 60 times faster than ANIMAL, also provides more accurate results. From the second method, both algorithms treated the interior of homogeneous regions in an appropriate manner.

  2. 3D registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation

    PubMed Central

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

    2016-01-01

    High resolution, 100 frames/sec intravascular optical coherence tomography (IVOCT) can distinguish plaque types, but further validation is needed, especially for automated plaque characterization. We developed experimental and 3D registration methods, to provide validation of IVOCT pullback volumes using microscopic, brightfield and fluorescent cryo-image volumes, with optional, exactly registered cryo-histology. The innovation was a method to match an IVOCT pull-back images, acquired in the catheter reference frame, to a true 3D cryo-image volume. Briefly, an 11-parameter, 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. Local minima were possible, but when we started within reasonable ranges, every one of 24 digital phantom cases converged to a good solution with a registration error of only +1.34±2.65μm (signed distance). Registration was applied to 10 ex-vivo cadaver coronary arteries (LADs), resulting in 10 registered cryo and IVOCT volumes yielding a total of 421 registered 2D-image pairs. Image overlays demonstrated high continuity between vascular and plaque features. Bland-Altman analysis comparing cryo and IVOCT lumen area, showed mean and standard deviation of differences as 0.01±0.43 mm2. DICE coefficients were 0.91±0.04. Finally, visual assessment on 20 representative cases with easily identifiable features suggested registration accuracy within one frame of IVOCT (±200μm), eliminating significant misinterpretations introduced by 1mm errors in the literature. The method will provide 3D data for training of IVOCT plaque algorithms and can be used for validation of other intravascular imaging modalities. PMID:27162417

  3. 3D registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

    High resolution, 100 frames/sec intravascular optical coherence tomography (IVOCT) can distinguish plaque types, but further validation is needed, especially for automated plaque characterization. We developed experimental and 3D registration methods, to provide validation of IVOCT pullback volumes using microscopic, brightfield and fluorescent cryoimage volumes, with optional, exactly registered cryo-histology. The innovation was a method to match an IVOCT pullback images, acquired in the catheter reference frame, to a true 3D cryo-image volume. Briefly, an 11-parameter, 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. Local minima were possible, but when we started within reasonable ranges, every one of 24 digital phantom cases converged to a good solution with a registration error of only +1.34+/-2.65μm (signed distance). Registration was applied to 10 ex-vivo cadaver coronary arteries (LADs), resulting in 10 registered cryo and IVOCT volumes yielding a total of 421 registered 2D-image pairs. Image overlays demonstrated high continuity between vascular and plaque features. Bland- Altman analysis comparing cryo and IVOCT lumen area, showed mean and standard deviation of differences as 0.01+/-0.43 mm2. DICE coefficients were 0.91+/-0.04. Finally, visual assessment on 20 representative cases with easily identifiable features suggested registration accuracy within one frame of IVOCT (+/-200μm), eliminating significant misinterpretations introduced by 1mm errors in the literature. The method will provide 3D data for training of IVOCT plaque algorithms and can be used for validation of other intravascular imaging modalities.

  4. Deformable image registration with a featurelet algorithm: implementation as a 3D-slicer extension and validation

    NASA Astrophysics Data System (ADS)

    Renner, A.; Furtado, H.; Seppenwoolde, Y.; Birkfellner, W.; Georg, D.

    2016-03-01

    A radiotherapy (RT) treatment can last for several weeks. In that time organ motion and shape changes introduce uncertainty in dose application. Monitoring and quantifying the change can yield a more precise irradiation margin definition and thereby reduce dose delivery to healthy tissue and adjust tumor targeting. Deformable image registration (DIR) has the potential to fulfill this task by calculating a deformation field (DF) between a planning CT and a repeated CT of the altered anatomy. Application of the DF on the original contours yields new contours that can be used for an adapted treatment plan. DIR is a challenging method and therefore needs careful user interaction. Without a proper graphical user interface (GUI) a misregistration cannot be easily detected by visual inspection and the results cannot be fine-tuned by changing registration parameters. To provide a DIR algorithm with such a GUI available for everyone, we created the extension Featurelet-Registration for the open source software platform 3D Slicer. The registration logic is an upgrade of an in-house-developed DIR method, which is a featurelet-based piecewise rigid registration. The so called "featurelets" are equally sized rectangular subvolumes of the moving image which are rigidly registered to rectangular search regions on the fixed image. The output is a deformed image and a deformation field. Both can be visualized directly in 3D Slicer facilitating the interpretation and quantification of the results. For validation of the registration accuracy two deformable phantoms were used. The performance was benchmarked against a demons algorithm with comparable results.

  5. 3D PET image reconstruction including both motion correction and registration directly into an MR or stereotaxic spatial atlas

    NASA Astrophysics Data System (ADS)

    Gravel, Paul; Verhaeghe, Jeroen; Reader, Andrew J.

    2013-01-01

    This work explores the feasibility and impact of including both the motion correction and the image registration transformation parameters from positron emission tomography (PET) image space to magnetic resonance (MR), or stereotaxic, image space within the system matrix of PET image reconstruction. This approach is motivated by the fields of neuroscience and psychiatry, where PET is used to investigate differences in activation patterns between different groups of participants, requiring all images to be registered to a common spatial atlas. Currently, image registration is performed after image reconstruction which introduces interpolation effects into the final image. Furthermore, motion correction (also requiring registration) introduces a further level of interpolation, and the overall result of these operations can lead to resolution degradation and possibly artifacts. It is important to note that performing such operations on a post-reconstruction basis means, strictly speaking, that the final images are not ones which maximize the desired objective function (e.g. maximum likelihood (ML), or maximum a posteriori reconstruction (MAP)). To correctly seek parameter estimates in the desired spatial atlas which are in accordance with the chosen reconstruction objective function, it is necessary to include the transformation parameters for both motion correction and registration within the system modeling stage of image reconstruction. Such an approach not only respects the statistically chosen objective function (e.g. ML or MAP), but furthermore should serve to reduce the interpolation effects. To evaluate the proposed method, this work investigates registration (including motion correction) using 2D and 3D simulations based on the high resolution research tomograph (HRRT) PET scanner geometry, with and without resolution modeling, using the ML expectation maximization (MLEM) reconstruction algorithm. The quality of reconstruction was assessed using bias

  6. Development of fast patient position verification software using 2D-3D image registration and its clinical experience.

    PubMed

    Mori, Shinichiro; Kumagai, Motoki; Miki, Kentaro; Fukuhara, Riki; Haneishi, Hideaki

    2015-09-01

    To improve treatment workflow, we developed a graphic processing unit (GPU)-based patient positional verification software application and integrated it into carbon-ion scanning beam treatment. Here, we evaluated the basic performance of the software. The algorithm provides 2D/3D registration matching using CT and orthogonal X-ray flat panel detector (FPD) images. The participants were 53 patients with tumors of the head and neck, prostate or lung receiving carbon-ion beam treatment. 2D/3D-ITchi-Gime (ITG) calculation accuracy was evaluated in terms of computation time and registration accuracy. Registration calculation was determined using the similarity measurement metrics gradient difference (GD), normalized mutual information (NMI), zero-mean normalized cross-correlation (ZNCC), and their combination. Registration accuracy was dependent on the particular metric used. Representative examples were determined to have target registration error (TRE) = 0.45 ± 0.23 mm and angular error (AE) = 0.35 ± 0.18° with ZNCC + GD for a head and neck tumor; TRE = 0.12 ± 0.07 mm and AE = 0.16 ± 0.07° with ZNCC for a pelvic tumor; and TRE = 1.19 ± 0.78 mm and AE = 0.83 ± 0.61° with ZNCC for lung tumor. Calculation time was less than 7.26 s.The new registration software has been successfully installed and implemented in our treatment process. We expect that it will improve both treatment workflow and treatment accuracy. PMID:26081313

  7. Development of fast patient position verification software using 2D-3D image registration and its clinical experience

    PubMed Central

    Mori, Shinichiro; Kumagai, Motoki; Miki, Kentaro; Fukuhara, Riki; Haneishi, Hideaki

    2015-01-01

    To improve treatment workflow, we developed a graphic processing unit (GPU)-based patient positional verification software application and integrated it into carbon-ion scanning beam treatment. Here, we evaluated the basic performance of the software. The algorithm provides 2D/3D registration matching using CT and orthogonal X-ray flat panel detector (FPD) images. The participants were 53 patients with tumors of the head and neck, prostate or lung receiving carbon-ion beam treatment. 2D/3D-ITchi-Gime (ITG) calculation accuracy was evaluated in terms of computation time and registration accuracy. Registration calculation was determined using the similarity measurement metrics gradient difference (GD), normalized mutual information (NMI), zero-mean normalized cross-correlation (ZNCC), and their combination. Registration accuracy was dependent on the particular metric used. Representative examples were determined to have target registration error (TRE) = 0.45 ± 0.23 mm and angular error (AE) = 0.35 ± 0.18° with ZNCC + GD for a head and neck tumor; TRE = 0.12 ± 0.07 mm and AE = 0.16 ± 0.07° with ZNCC for a pelvic tumor; and TRE = 1.19 ± 0.78 mm and AE = 0.83 ± 0.61° with ZNCC for lung tumor. Calculation time was less than 7.26 s.The new registration software has been successfully installed and implemented in our treatment process. We expect that it will improve both treatment workflow and treatment accuracy. PMID:26081313

  8. A 3D space-time motion evaluation for image registration in digital subtraction angiography.

    PubMed

    Taleb, N; Bentoutou, Y; Deforges, O; Taleb, M

    2001-01-01

    In modern clinical practice, Digital Subtraction Angiography (DSA) is a powerful technique for the visualization of blood vessels in a sequence of X-ray images. A serious problem encountered in this technique is the presence of artifacts due to patient motion. The resulting artifacts frequently lead to misdiagnosis or rejection of a DSA image sequence. In this paper, a new technique for removing both global and local motion artifacts is presented. It is based on a 3D space-time motion evaluation for separating pixels changing values because of motion from those changing values because of contrast flow. This technique is proved to be very efficient to correct for patient motion artifacts and is computationally cheap. Experimental results with several clinical data sets show that this technique is very fast and results in higher quality images. PMID:11179698

  9. 3D optical coherence tomography image registration for guiding cochlear implant insertion

    NASA Astrophysics Data System (ADS)

    Cheon, Gyeong-Woo; Jeong, Hyun-Woo; Chalasani, Preetham; Chien, Wade W.; Iordachita, Iulian; Taylor, Russell; Niparko, John; Kang, Jin U.

    2014-03-01

    In cochlear implant surgery, an electrode array is inserted into the cochlear canal to restore hearing to a person who is profoundly deaf or significantly hearing impaired. One critical part of the procedure is the insertion of the electrode array, which looks like a thin wire, into the cochlear canal. Although X-ray or computed tomography (CT) could be used as a reference to evaluate the pathway of the whole electrode array, there is no way to depict the intra-cochlear canal and basal turn intra-operatively to help guide insertion of the electrode array. Optical coherent tomography (OCT) is a highly effective way of visualizing internal structures of cochlea. Swept source OCT (SSOCT) having center wavelength of 1.3 micron and 2D Galvonometer mirrors was used to achieve 7-mm depth 3-D imaging. Graphics processing unit (GPU), OpenGL, C++ and C# were integrated for real-time volumetric rendering simultaneously. The 3D volume images taken by the OCT system were assembled and registered which could be used to guide a cochlear implant. We performed a feasibility study using both dry and wet temporal bones and the result is presented.

  10. A fast rigid-registration method of inferior limb X-ray image and 3D CT images for TKA surgery

    NASA Astrophysics Data System (ADS)

    Ito, Fumihito; O. D. A, Prima; Uwano, Ikuko; Ito, Kenzo

    2010-03-01

    In this paper, we propose a fast rigid-registration method of inferior limb X-ray films (two-dimensional Computed Radiography (CR) images) and three-dimensional Computed Tomography (CT) images for Total Knee Arthroplasty (TKA) surgery planning. The position of the each bone, such as femur and tibia (shin bone), in X-ray film and 3D CT images is slightly different, and we must pay attention how to use the two different images, since X-ray film image is captured in the standing position, and 3D CT is captured in decubitus (face up) position, respectively. Though the conventional registration mainly uses cross-correlation function between two images,and utilizes optimization techniques, it takes enormous calculation time and it is difficult to use it in interactive operations. In order to solve these problems, we calculate the center line (bone axis) of femur and tibia (shin bone) automatically, and we use them as initial positions for the registration. We evaluate our registration method by using three patient's image data, and we compare our proposed method and a conventional registration, which uses down-hill simplex algorithm. The down-hill simplex method is an optimization algorithm that requires only function evaluations, and doesn't need the calculation of derivatives. Our registration method is more effective than the downhill simplex method in computational time and the stable convergence. We have developed the implant simulation system on a personal computer, in order to support the surgeon in a preoperative planning of TKA. Our registration method is implemented in the simulation system, and user can manipulate 2D/3D translucent templates of implant components on X-ray film and 3D CT images.

  11. Clinical Assessment of 2D/3D Registration Accuracy in 4 Major Anatomic Sites Using On-Board 2D Kilovoltage Images for 6D Patient Setup

    PubMed Central

    Li, Guang; Yang, T. Jonathan; Furtado, Hugo; Birkfellner, Wolfgang; Ballangrud, Åse; Powell, Simon N.; Mechalakos, James

    2015-01-01

    To provide a comprehensive assessment of patient setup accuracy in 6 degrees of freedom (DOFs) using 2-dimensional/3-dimensional (2D/3D) image registration with on-board 2-dimensional kilovoltage (OB-2DkV) radiographic images, we evaluated cranial, head and neck (HN), and thoracic and abdominal sites under clinical conditions. A fast 2D/3D image registration method using graphics processing unit GPU was modified for registration between OB-2DkV and 3D simulation computed tomography (simCT) images, with 3D/3D registration as the gold standard for 6DOF alignment. In 2D/3D registration, body roll rotation was obtained solely by matching orthogonal OB-2DkV images with a series of digitally reconstructed radiographs (DRRs) from simCT with a small rotational increment along the gantry rotation axis. The window/level adjustments for optimal visualization of the bone in OB-2DkV and DRRs were performed prior to registration. Ideal patient alignment at the isocenter was calculated and used as an initial registration position. In 3D/3D registration, cone-beam CT (CBCT) was aligned to simCT on bony structures using a bone density filter in 6DOF. Included in this retrospective study were 37 patients treated in 55 fractions with frameless stereotactic radiosurgery or stereotactic body radiotherapy for cranial and paraspinal cancer. A cranial phantom was used to serve as a control. In all cases, CBCT images were acquired for patient setup with subsequent OB-2DkV verification. It was found that the accuracy of the 2D/3D registration was 0.0 ± 0.5 mm and 0.1° ± 0.4° in phantom. In patient, it is site dependent due to deformation of the anatomy: 0.2 ± 1.6 mm and −0.4° ± 1.2° on average for each dimension for the cranial site, 0.7 ± 1.6 mm and 0.3° ± 1.3° for HN, 0.7 ± 2.0 mm and −0.7° ± 1.1° for the thorax, and 1.1 ± 2.6 mm and −0.5° ± 1.9° for the abdomen. Anatomical deformation and presence of soft tissue in 2D/3D registration affect the consistency with

  12. Clinical Assessment of 2D/3D Registration Accuracy in 4 Major Anatomic Sites Using On-Board 2D Kilovoltage Images for 6D Patient Setup.

    PubMed

    Li, Guang; Yang, T Jonathan; Furtado, Hugo; Birkfellner, Wolfgang; Ballangrud, Åse; Powell, Simon N; Mechalakos, James

    2015-06-01

    To provide a comprehensive assessment of patient setup accuracy in 6 degrees of freedom (DOFs) using 2-dimensional/3-dimensional (2D/3D) image registration with on-board 2-dimensional kilovoltage (OB-2 DkV) radiographic images, we evaluated cranial, head and neck (HN), and thoracic and abdominal sites under clinical conditions. A fast 2D/3D image registration method using graphics processing unit GPU was modified for registration between OB-2 DkV and 3D simulation computed tomography (simCT) images, with 3D/3D registration as the gold standard for 6 DOF alignment. In 2D/3D registration, body roll rotation was obtained solely by matching orthogonal OB-2 DkV images with a series of digitally reconstructed radiographs (DRRs) from simCT with a small rotational increment along the gantry rotation axis. The window/level adjustments for optimal visualization of the bone in OB-2 DkV and DRRs were performed prior to registration. Ideal patient alignment at the isocenter was calculated and used as an initial registration position. In 3D/3D registration, cone-beam CT (CBCT) was aligned to simCT on bony structures using a bone density filter in 6DOF. Included in this retrospective study were 37 patients treated in 55 fractions with frameless stereotactic radiosurgery or stereotactic body radiotherapy for cranial and paraspinal cancer. A cranial phantom was used to serve as a control. In all cases, CBCT images were acquired for patient setup with subsequent OB-2 DkV verification. It was found that the accuracy of the 2D/3D registration was 0.0 ± 0.5 mm and 0.1° ± 0.4° in phantom. In patient, it is site dependent due to deformation of the anatomy: 0.2 ± 1.6 mm and -0.4° ± 1.2° on average for each dimension for the cranial site, 0.7 ± 1.6 mm and 0.3° ± 1.3° for HN, 0.7 ± 2.0 mm and -0.7° ± 1.1° for the thorax, and 1.1 ± 2.6 mm and -0.5° ± 1.9° for the abdomen. Anatomical deformation and presence of soft tissue in 2D/3D registration affect the consistency with

  13. Registration of 2D C-Arm and 3D CT Images for a C-Arm Image-Assisted Navigation System for Spinal Surgery.

    PubMed

    Chang, Chih-Ju; Lin, Geng-Li; Tse, Alex; Chu, Hong-Yu; Tseng, Ching-Shiow

    2015-01-01

    C-Arm image-assisted surgical navigation system has been broadly applied to spinal surgery. However, accurate path planning on the C-Arm AP-view image is difficult. This research studies 2D-3D image registration methods to obtain the optimum transformation matrix between C-Arm and CT image frames. Through the transformation matrix, the surgical path planned on preoperative CT images can be transformed and displayed on the C-Arm images for surgical guidance. The positions of surgical instruments will also be displayed on both CT and C-Arm in the real time. Five similarity measure methods of 2D-3D image registration including Normalized Cross-Correlation, Gradient Correlation, Pattern Intensity, Gradient Difference Correlation, and Mutual Information combined with three optimization methods including Powell's method, Downhill simplex algorithm, and genetic algorithm are applied to evaluate their performance in converge range, efficiency, and accuracy. Experimental results show that the combination of Normalized Cross-Correlation measure method with Downhill simplex algorithm obtains maximum correlation and similarity in C-Arm and Digital Reconstructed Radiograph (DRR) images. Spine saw bones are used in the experiment to evaluate 2D-3D image registration accuracy. The average error in displacement is 0.22 mm. The success rate is approximately 90% and average registration time takes 16 seconds. PMID:27018859

  14. Automatic registration between 3D intra-operative ultrasound and pre-operative CT images of the liver based on robust edge matching

    NASA Astrophysics Data System (ADS)

    Nam, Woo Hyun; Kang, Dong-Goo; Lee, Duhgoon; Lee, Jae Young; Ra, Jong Beom

    2012-01-01

    The registration of a three-dimensional (3D) ultrasound (US) image with a computed tomography (CT) or magnetic resonance image is beneficial in various clinical applications such as diagnosis and image-guided intervention of the liver. However, conventional methods usually require a time-consuming and inconvenient manual process for pre-alignment, and the success of this process strongly depends on the proper selection of initial transformation parameters. In this paper, we present an automatic feature-based affine registration procedure of 3D intra-operative US and pre-operative CT images of the liver. In the registration procedure, we first segment vessel lumens and the liver surface from a 3D B-mode US image. We then automatically estimate an initial registration transformation by using the proposed edge matching algorithm. The algorithm finds the most likely correspondences between the vessel centerlines of both images in a non-iterative manner based on a modified Viterbi algorithm. Finally, the registration is iteratively refined on the basis of the global affine transformation by jointly using the vessel and liver surface information. The proposed registration algorithm is validated on synthesized datasets and 20 clinical datasets, through both qualitative and quantitative evaluations. Experimental results show that automatic registration can be successfully achieved between 3D B-mode US and CT images even with a large initial misalignment.

  15. 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

  16. 3D reconstruction of 2D fluorescence histology images and registration with in vivo MR images: application in a rodent stroke model.

    PubMed

    Stille, Maik; Smith, Edward J; Crum, William R; Modo, Michel

    2013-09-30

    To validate and add value to non-invasive imaging techniques, the corresponding histology is required to establish biological correlates. We present an efficient, semi-automated image-processing pipeline that uses immunohistochemically stained sections to reconstruct a 3D brain volume from 2D histological images before registering these with the corresponding 3D in vivo magnetic resonance images (MRI). A multistep registration procedure that first aligns the "global" volume by using the centre of mass and then applies a rigid and affine alignment based on signal intensities is described. This technique was applied to a training set of three rat brain volumes before being validated on three normal brains. Application of the approach to register "abnormal" images from a rat model of stroke allowed the neurobiological correlates of the variations in the hyper-intense MRI signal intensity caused by infarction to be investigated. For evaluation, the corresponding anatomical landmarks in MR and histology were defined to measure the registration accuracy. A registration error of 0.249 mm (approximately one in-plane voxel dimension) was evident in healthy rat brains and of 0.323 mm in a rodent model of stroke. The proposed reconstruction and registration pipeline allowed for the precise analysis of non-invasive MRI and corresponding microstructural histological features in 3D. We were thus able to interrogate histology to deduce the cause of MRI signal variations in the lesion cavity and the peri-infarct area. PMID:23816399

  17. Significant acceleration of 2D-3D registration-based fusion of ultrasound and x-ray images by mesh-based DRR rendering

    NASA Astrophysics Data System (ADS)

    Kaiser, Markus; John, Matthias; Borsdorf, Anja; Mountney, Peter; Ionasec, Razvan; Nöttling, Alois; Kiefer, Philipp; Seeburger, Jörg; Neumuth, Thomas

    2013-03-01

    For transcatheter-based minimally invasive procedures in structural heart disease ultrasound and X-ray are the two enabling imaging modalities. A live fusion of both real-time modalities can potentially improve the workflow and the catheter navigation by combining the excellent instrument imaging of X-ray with the high-quality soft tissue imaging of ultrasound. A recently published approach to fuse X-ray fluoroscopy with trans-esophageal echo (TEE) registers the ultrasound probe to X-ray images by a 2D-3D registration method which inherently provides a registration of ultrasound images to X-ray images. In this paper, we significantly accelerate the 2D-3D registration method in this context. The main novelty is to generate the projection images (DRR) of the 3D object not via volume ray-casting but instead via a fast rendering of triangular meshes. This is possible, because in the setting for TEE/X-ray fusion the 3D geometry of the ultrasound probe is known in advance and their main components can be described by triangular meshes. We show that the new approach can achieve a speedup factor up to 65 and does not affect the registration accuracy when used in conjunction with the gradient correlation similarity measure. The improvement is independent of the underlying registration optimizer. Based on the results, a TEE/X-ray fusion could be performed with a higher frame rate and a shorter time lag towards real-time registration performance. The approach could potentially accelerate other applications of 2D-3D registrations, e.g. the registration of implant models with X-ray images.

  18. The Ultrasound Brain Helmet: New Transducers and Volume Registration for In Vivo Simultaneous Multi-Transducer 3-D Transcranial Imaging

    PubMed Central

    Lindsey, Brooks D.; Light, Edward D.; Nicoletto, Heather A.; Bennett, Ellen R.; Laskowitz, Daniel T.; Smith, Stephen W.

    2012-01-01

    Because stroke remains an important and time-sensitive health concern in developed nations, we present a system capable of fusing 3-D transcranial ultrasound volumes acquired from two sides of the head. This system uses custom sparse array transducers built on flexible multilayer circuits that can be positioned for simultaneous imaging through both temporal acoustic windows, allowing for potential registration of multiple real-time 3-D scans of cerebral vasculature. We examine hardware considerations for new matrix arrays—transducer design and interconnects—in this application. Specifically, it is proposed that SNR may be increased by reducing the length of probe cables. This claim is evaluated as part of the presented system through simulation, experimental data, and in vivo imaging. Ultimately, gains in SNR of 7 dB are realized by replacing a standard probe cable with a much shorter flex interconnect; higher gains may be possible using ribbon-based probe cables. In vivo images are presented, showing cerebral arteries with and without the use of microbubble contrast agent; they have been registered and fused using a simple algorithm which maximizes normalized cross-correlation. PMID:21693401

  19. 3D Imaging.

    ERIC Educational Resources Information Center

    Hastings, S. K.

    2002-01-01

    Discusses 3 D imaging as it relates to digital representations in virtual library collections. Highlights include X-ray computed tomography (X-ray CT); the National Science Foundation (NSF) Digital Library Initiatives; output peripherals; image retrieval systems, including metadata; and applications of 3 D imaging for libraries and museums. (LRW)

  20. Instantiation and registration of statistical shape models of the femur and pelvis using 3D ultrasound imaging.

    PubMed

    Barratt, Dean C; Chan, Carolyn S K; Edwards, Philip J; Penney, Graeme P; Slomczykowski, Mike; Carter, Timothy J; Hawkes, David J

    2008-06-01

    Statistical shape modelling potentially provides a powerful tool for generating patient-specific, 3D representations of bony anatomy for computer-aided orthopaedic surgery (CAOS) without the need for a preoperative CT scan. Furthermore, freehand 3D ultrasound (US) provides a non-invasive method for digitising bone surfaces in the operating theatre that enables a much greater region to be sampled compared with conventional direct-contact (i.e., pointer-based) digitisation techniques. In this paper, we describe how these approaches can be combined to simultaneously generate and register a patient-specific model of the femur and pelvis to the patient during surgery. In our implementation, a statistical deformation model (SDM) was constructed for the femur and pelvis by performing a principal component analysis on the B-spline control points that parameterise the freeform deformations required to non-rigidly register a training set of CT scans to a carefully segmented template CT scan. The segmented template bone surface, represented by a triangulated surface mesh, is instantiated and registered to a cloud of US-derived surface points using an iterative scheme in which the weights corresponding to the first five principal modes of variation of the SDM are optimised in addition to the rigid-body parameters. The accuracy of the method was evaluated using clinically realistic data obtained on three intact human cadavers (three whole pelves and six femurs). For each bone, a high-resolution CT scan and rigid-body registration transformation, calculated using bone-implanted fiducial markers, served as the gold standard bone geometry and registration transformation, respectively. After aligning the final instantiated model and CT-derived surfaces using the iterative closest point (ICP) algorithm, the average root-mean-square distance between the surfaces was 3.5mm over the whole bone and 3.7mm in the region of surgical interest. The corresponding distances after aligning the

  1. Position tracking of moving liver lesion based on real-time registration between 2D ultrasound and 3D preoperative images

    SciTech Connect

    Weon, Chijun; Hyun Nam, Woo; Lee, Duhgoon; Ra, Jong Beom; Lee, Jae Young

    2015-01-15

    Purpose: Registration between 2D ultrasound (US) and 3D preoperative magnetic resonance (MR) (or computed tomography, CT) images has been studied recently for US-guided intervention. However, the existing techniques have some limits, either in the registration speed or the performance. The purpose of this work is to develop a real-time and fully automatic registration system between two intermodal images of the liver, and subsequently an indirect lesion positioning/tracking algorithm based on the registration result, for image-guided interventions. Methods: The proposed position tracking system consists of three stages. In the preoperative stage, the authors acquire several 3D preoperative MR (or CT) images at different respiratory phases. Based on the transformations obtained from nonrigid registration of the acquired 3D images, they then generate a 4D preoperative image along the respiratory phase. In the intraoperative preparatory stage, they properly attach a 3D US transducer to the patient’s body and fix its pose using a holding mechanism. They then acquire a couple of respiratory-controlled 3D US images. Via the rigid registration of these US images to the 3D preoperative images in the 4D image, the pose information of the fixed-pose 3D US transducer is determined with respect to the preoperative image coordinates. As feature(s) to use for the rigid registration, they may choose either internal liver vessels or the inferior vena cava. Since the latter is especially useful in patients with a diffuse liver disease, the authors newly propose using it. In the intraoperative real-time stage, they acquire 2D US images in real-time from the fixed-pose transducer. For each US image, they select candidates for its corresponding 2D preoperative slice from the 4D preoperative MR (or CT) image, based on the predetermined pose information of the transducer. The correct corresponding image is then found among those candidates via real-time 2D registration based on a

  2. An Automatic Registration Algorithm for 3D Maxillofacial Model

    NASA Astrophysics Data System (ADS)

    Qiu, Luwen; Zhou, Zhongwei; Guo, Jixiang; Lv, Jiancheng

    2016-09-01

    3D image registration aims at aligning two 3D data sets in a common coordinate system, which has been widely used in computer vision, pattern recognition and computer assisted surgery. One challenging problem in 3D registration is that point-wise correspondences between two point sets are often unknown apriori. In this work, we develop an automatic algorithm for 3D maxillofacial models registration including facial surface model and skull model. Our proposed registration algorithm can achieve a good alignment result between partial and whole maxillofacial model in spite of ambiguous matching, which has a potential application in the oral and maxillofacial reparative and reconstructive surgery. The proposed algorithm includes three steps: (1) 3D-SIFT features extraction and FPFH descriptors construction; (2) feature matching using SAC-IA; (3) coarse rigid alignment and refinement by ICP. Experiments on facial surfaces and mandible skull models demonstrate the efficiency and robustness of our algorithm.

  3. Automatic Generation of Boundary Conditions Using Demons Nonrigid Image Registration for Use in 3-D Modality-Independent Elastography

    PubMed Central

    Ou, Jao J.; Ong, Rowena E.; Miga, Michael I.

    2013-01-01

    Modality-independent elastography (MIE) is a method of elastography that reconstructs the elastic properties of tissue using images acquired under different loading conditions and a biomechanical model. Boundary conditions are a critical input to the algorithm and are often determined by time-consuming point correspondence methods requiring manual user input. This study presents a novel method of automatically generating boundary conditions by nonrigidly registering two image sets with a demons diffusion-based registration algorithm. The use of this method was successfully performed in silico using magnetic resonance and X-ray-computed tomography image data with known boundary conditions. These preliminary results produced boundary conditions with an accuracy of up to 80% compared to the known conditions. Demons-based boundary conditions were utilized within a 3-D MIE reconstruction to determine an elasticity contrast ratio between tumor and normal tissue. Two phantom experiments were then conducted to further test the accuracy of the demons boundary conditions and the MIE reconstruction arising from the use of these conditions. Preliminary results show a reasonable characterization of the material properties on this first attempt and a significant improvement in the automation level and viability of the method. PMID:21690002

  4. Optic disc boundary segmentation from diffeomorphic demons registration of monocular fundus image sequences versus 3D visualization of stereo fundus image pairs for automated early stage glaucoma assessment

    NASA Astrophysics Data System (ADS)

    Gatti, Vijay; Hill, Jason; Mitra, Sunanda; Nutter, Brian

    2014-03-01

    Despite the current availability in resource-rich regions of advanced technologies in scanning and 3-D imaging in current ophthalmology practice, world-wide screening tests for early detection and progression of glaucoma still consist of a variety of simple tools, including fundus image-based parameters such as CDR (cup to disc diameter ratio) and CAR (cup to disc area ratio), especially in resource -poor regions. Reliable automated computation of the relevant parameters from fundus image sequences requires robust non-rigid registration and segmentation techniques. Recent research work demonstrated that proper non-rigid registration of multi-view monocular fundus image sequences could result in acceptable segmentation of cup boundaries for automated computation of CAR and CDR. This research work introduces a composite diffeomorphic demons registration algorithm for segmentation of cup boundaries from a sequence of monocular images and compares the resulting CAR and CDR values with those computed manually by experts and from 3-D visualization of stereo pairs. Our preliminary results show that the automated computation of CDR and CAR from composite diffeomorphic segmentation of monocular image sequences yield values comparable with those from the other two techniques and thus may provide global healthcare with a cost-effective yet accurate tool for management of glaucoma in its early stage.

  5. Automatic localization of target vertebrae in spine surgery using fast CT-to-fluoroscopy (3D-2D) image registration

    NASA Astrophysics Data System (ADS)

    Otake, Y.; Schafer, S.; Stayman, J. W.; Zbijewski, W.; Kleinszig, G.; Graumann, R.; Khanna, A. J.; Siewerdsen, J. H.

    2012-02-01

    Localization of target vertebrae is an essential step in minimally invasive spine surgery, with conventional methods relying on "level counting" - i.e., manual counting of vertebrae under fluoroscopy starting from readily identifiable anatomy (e.g., the sacrum). The approach requires an undesirable level of radiation, time, and is prone to counting errors due to the similar appearance of vertebrae in projection images; wrong-level surgery occurs in 1 of every ~3000 cases. This paper proposes a method to automatically localize target vertebrae in x-ray projections using 3D-2D registration between preoperative CT (in which vertebrae are preoperatively labeled) and intraoperative fluoroscopy. The registration uses an intensity-based approach with a gradient-based similarity metric and the CMA-ES algorithm for optimization. Digitally reconstructed radiographs (DRRs) and a robust similarity metric are computed on GPU to accelerate the process. Evaluation in clinical CT data included 5,000 PA and LAT projections randomly perturbed to simulate human variability in setup of mobile intraoperative C-arm. The method demonstrated 100% success for PA view (projection error: 0.42mm) and 99.8% success for LAT view (projection error: 0.37mm). Initial implementation on GPU provided automatic target localization within about 3 sec, with further improvement underway via multi-GPU. The ability to automatically label vertebrae in fluoroscopy promises to streamline surgical workflow, improve patient safety, and reduce wrong-site surgeries, especially in large patients for whom manual methods are time consuming and error prone.

  6. SU-C-18A-04: 3D Markerless Registration of Lung Based On Coherent Point Drift: Application in Image Guided Radiotherapy

    SciTech Connect

    Nasehi Tehrani, J; Wang, J; Guo, X; Yang, Y

    2014-06-01

    Purpose: This study evaluated a new probabilistic non-rigid registration method called coherent point drift for real time 3D markerless registration of the lung motion during radiotherapy. Method: 4DCT image datasets Dir-lab (www.dir-lab.com) have been used for creating 3D boundary element model of the lungs. For the first step, the 3D surface of the lungs in respiration phases T0 and T50 were segmented and divided into a finite number of linear triangular elements. Each triangle is a two dimensional object which has three vertices (each vertex has three degree of freedom). One of the main features of the lungs motion is velocity coherence so the vertices that creating the mesh of the lungs should also have features and degree of freedom of lung structure. This means that the vertices close to each other tend to move coherently. In the next step, we implemented a probabilistic non-rigid registration method called coherent point drift to calculate nonlinear displacement of vertices between different expiratory phases. Results: The method has been applied to images of 10-patients in Dir-lab dataset. The normal distribution of vertices to the origin for each expiratory stage were calculated. The results shows that the maximum error of registration between different expiratory phases is less than 0.4 mm (0.38 SI, 0.33 mm AP, 0.29 mm RL direction). This method is a reliable method for calculating the vector of displacement, and the degrees of freedom (DOFs) of lung structure in radiotherapy. Conclusions: We evaluated a new 3D registration method for distribution set of vertices inside lungs mesh. In this technique, lungs motion considering velocity coherence are inserted as a penalty in regularization function. The results indicate that high registration accuracy is achievable with CPD. This method is helpful for calculating of displacement vector and analyzing possible physiological and anatomical changes during treatment.

  7. Fully automated 2D-3D registration and verification.

    PubMed

    Varnavas, Andreas; Carrell, Tom; Penney, Graeme

    2015-12-01

    Clinical application of 2D-3D registration technology often requires a significant amount of human interaction during initialisation and result verification. This is one of the main barriers to more widespread clinical use of this technology. We propose novel techniques for automated initial pose estimation of the 3D data and verification of the registration result, and show how these techniques can be combined to enable fully automated 2D-3D registration, particularly in the case of a vertebra based system. The initialisation method is based on preoperative computation of 2D templates over a wide range of 3D poses. These templates are used to apply the Generalised Hough Transform to the intraoperative 2D image and the sought 3D pose is selected with the combined use of the generated accumulator arrays and a Gradient Difference Similarity Measure. On the verification side, two algorithms are proposed: one using normalised features based on the similarity value and the other based on the pose agreement between multiple vertebra based registrations. The proposed methods are employed here for CT to fluoroscopy registration and are trained and tested with data from 31 clinical procedures with 417 low dose, i.e. low quality, high noise interventional fluoroscopy images. When similarity value based verification is used, the fully automated system achieves a 95.73% correct registration rate, whereas a no registration result is produced for the remaining 4.27% of cases (i.e. incorrect registration rate is 0%). The system also automatically detects input images outside its operating range. PMID:26387052

  8. 3D affine registration using teaching-learning based optimization

    NASA Astrophysics Data System (ADS)

    Jani, Ashish; Savsani, Vimal; Pandya, Abhijit

    2013-09-01

    3D image registration is an emerging research field in the study of computer vision. In this paper, two effective global optimization methods are considered for the 3D registration of point clouds. Experiments were conducted by applying each algorithm and their performance was evaluated with respect to rigidity, similarity and affine transformations. Comparison of algorithms and its effectiveness was tested for the average performance to find the global solution for minimizing the error in the terms of distance between the model cloud and the data cloud. The parameters for the transformation matrix were considered as the design variables. Further comparisons of the considered methods were done for the computational effort, computational time and the convergence of the algorithm. The results reveal that the use of TLBO was outstanding for image processing application involving 3D registration. [Figure not available: see fulltext.

  9. A novel approach for a 2D/3D image registration routine for medical tool navigation in minimally invasive vascular interventions.

    PubMed

    Schwerter, Michael; Lietzmann, Florian; Schad, Lothar R

    2016-09-01

    Minimally invasive interventions are frequently aided by 2D projective image guidance. To facilitate the navigation of medical tools within the patient, information from preoperative 3D images can supplement interventional data. This work describes a novel approach to perform a 3D CT data registration to a single interventional native fluoroscopic frame. The goal of this procedure is to recover and visualize a current 2D interventional tool position in its corresponding 3D dataset. A dedicated routine was developed and tested on a phantom. The 3D position of a guidewire inserted into the phantom could successfully be reconstructed for varying 2D image acquisition geometries. The scope of the routine includes projecting the CT data into the plane of the fluoroscopy. A subsequent registration of the real and virtual projections is performed with an accuracy within the range of 1.16±0.17mm for fixed landmarks. The interventional tool is extracted from the fluoroscopy and matched to the corresponding part of the projected and transformed arterial vasculature. A root mean square error of up to 0.56mm for matched point pairs is reached. The desired 3D view is provided by backprojecting the matched guidewire through the CT array. Due to its potential to reduce patient dose and treatment times, the proposed routine has the capability of reducing patient stress at lower overall treatment costs. PMID:27157275

  10. Model-based measurement of food portion size for image-based dietary assessment using 3D/2D registration

    NASA Astrophysics Data System (ADS)

    Chen, Hsin-Chen; Jia, Wenyan; Yue, Yaofeng; Li, Zhaoxin; Sun, Yung-Nien; Fernstrom, John D.; Sun, Mingui

    2013-10-01

    Dietary assessment is important in health maintenance and intervention in many chronic conditions, such as obesity, diabetes and cardiovascular disease. However, there is currently a lack of convenient methods for measuring the volume of food (portion size) in real-life settings. We present a computational method to estimate food volume from a single photographic image of food contained on a typical dining plate. First, we calculate the food location with respect to a 3D camera coordinate system using the plate as a scale reference. Then, the food is segmented automatically from the background in the image. Adaptive thresholding and snake modeling are implemented based on several image features, such as color contrast, regional color homogeneity and curve bending degree. Next, a 3D model representing the general shape of the food (e.g., a cylinder, a sphere, etc) is selected from a pre-constructed shape model library. The position, orientation and scale of the selected shape model are determined by registering the projected 3D model and the food contour in the image, where the properties of the reference are used as constraints. Experimental results using various realistically shaped foods with known volumes demonstrated satisfactory performance of our image-based food volume measurement method even if the 3D geometric surface of the food is not completely represented in the input image.

  11. Real-time intensity based 2D/3D registration using kV-MV image pairs for tumor motion tracking in image guided radiotherapy

    NASA Astrophysics Data System (ADS)

    Furtado, H.; Steiner, E.; Stock, M.; Georg, D.; Birkfellner, W.

    2014-03-01

    Intra-fractional respiratorymotion during radiotherapy is one of themain sources of uncertainty in dose application creating the need to extend themargins of the planning target volume (PTV). Real-time tumormotion tracking by 2D/3D registration using on-board kilo-voltage (kV) imaging can lead to a reduction of the PTV. One limitation of this technique when using one projection image, is the inability to resolve motion along the imaging beam axis. We present a retrospective patient study to investigate the impact of paired portal mega-voltage (MV) and kV images, on registration accuracy. We used data from eighteen patients suffering from non small cell lung cancer undergoing regular treatment at our center. For each patient we acquired a planning CT and sequences of kV and MV images during treatment. Our evaluation consisted of comparing the accuracy of motion tracking in 6 degrees-of-freedom(DOF) using the anterior-posterior (AP) kV sequence or the sequence of kV-MV image pairs. We use graphics processing unit rendering for real-time performance. Motion along cranial-caudal direction could accurately be extracted when using only the kV sequence but in AP direction we obtained large errors. When using kV-MV pairs, the average error was reduced from 3.3 mm to 1.8 mm and the motion along AP was successfully extracted. The mean registration time was of 190+/-35ms. Our evaluation shows that using kVMV image pairs leads to improved motion extraction in 6 DOF. Therefore, this approach is suitable for accurate, real-time tumor motion tracking with a conventional LINAC.

  12. A frequency-based approach to locate common structure for 2D-3D intensity-based registration of setup images in prostate radiotherapy

    SciTech Connect

    Munbodh, Reshma; Chen Zhe; Jaffray, David A.; Moseley, Douglas J.; Knisely, Jonathan P. S.; Duncan, James S.

    2007-07-15

    In many radiotherapy clinics, geometric uncertainties in the delivery of 3D conformal radiation therapy and intensity modulated radiation therapy of the prostate are reduced by aligning the patient's bony anatomy in the planning 3D CT to corresponding bony anatomy in 2D portal images acquired before every treatment fraction. In this paper, we seek to determine if there is a frequency band within the portal images and the digitally reconstructed radiographs (DRRs) of the planning CT in which bony anatomy predominates over non-bony anatomy such that portal images and DRRs can be suitably filtered to achieve high registration accuracy in an automated 2D-3D single portal intensity-based registration framework. Two similarity measures, mutual information and the Pearson correlation coefficient were tested on carefully collected gold-standard data consisting of a kilovoltage cone-beam CT (CBCT) and megavoltage portal images in the anterior-posterior (AP) view of an anthropomorphic phantom acquired under clinical conditions at known poses, and on patient data. It was found that filtering the portal images and DRRs during the registration considerably improved registration performance. Without filtering, the registration did not always converge while with filtering it always converged to an accurate solution. For the pose-determination experiments conducted on the anthropomorphic phantom with the correlation coefficient, the mean (and standard deviation) of the absolute errors in recovering each of the six transformation parameters were {theta}{sub x}:0.18(0.19) deg., {theta}{sub y}:0.04(0.04) deg., {theta}{sub z}:0.04(0.02) deg., t{sub x}:0.14(0.15) mm, t{sub y}:0.09(0.05) mm, and t{sub z}:0.49(0.40) mm. The mutual information-based registration with filtered images also resulted in similarly small errors. For the patient data, visual inspection of the superimposed registered images showed that they were correctly aligned in all instances. The results presented in this

  13. 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

    SciTech Connect

    Xu, H; Song, K; Chetty, I; Kim, J; Wen, N

    2015-06-15

    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 also 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, 6 DOF

  14. High-performance GPU-based rendering for real-time, rigid 2D/3D-image registration and motion prediction in radiation oncology

    PubMed Central

    Spoerk, Jakob; Gendrin, Christelle; Weber, Christoph; Figl, Michael; Pawiro, Supriyanto Ardjo; Furtado, Hugo; Fabri, Daniella; Bloch, Christoph; Bergmann, Helmar; Gröller, Eduard; Birkfellner, Wolfgang

    2012-01-01

    A common problem in image-guided radiation therapy (IGRT) of lung cancer as well as other malignant diseases is the compensation of periodic and aperiodic motion during dose delivery. Modern systems for image-guided radiation oncology allow for the acquisition of cone-beam computed tomography data in the treatment room as well as the acquisition of planar radiographs during the treatment. A mid-term research goal is the compensation of tumor target volume motion by 2D/3D registration. In 2D/3D registration, spatial information on organ location is derived by an iterative comparison of perspective volume renderings, so-called digitally rendered radiographs (DRR) from computed tomography volume data, and planar reference x-rays. Currently, this rendering process is very time consuming, and real-time registration, which should at least provide data on organ position in less than a second, has not come into existence. We present two GPU-based rendering algorithms which generate a DRR of 512 × 512 pixels size from a CT dataset of 53 MB size at a pace of almost 100 Hz. This rendering rate is feasible by applying a number of algorithmic simplifications which range from alternative volume-driven rendering approaches – namely so-called wobbled splatting – to sub-sampling of the DRR-image by means of specialized raycasting techniques. Furthermore, general purpose graphics processing unit (GPGPU) programming paradigms were consequently utilized. Rendering quality and performance as well as the influence on the quality and performance of the overall registration process were measured and analyzed in detail. The results show that both methods are competitive and pave the way for fast motion compensation by rigid and possibly even non-rigid 2D/3D registration and, beyond that, adaptive filtering of motion models in IGRT. PMID:21782399

  15. Determination of 3D location and rotation of lumbar vertebrae in CT images by symmetry-based auto-registration

    NASA Astrophysics Data System (ADS)

    Vrtovec, Tomaž; Likar, Boštjan; Pernuš, Franjo

    2007-03-01

    Quantitative measurement of vertebral rotation is important in surgical planning, analysis of surgical results, and monitoring of the progression of spinal deformities. However, many established and newly developed techniques for measuring axial vertebral rotation do not exploit three-dimensional (3D) information, which may result in virtual axial rotation because of the sagittal and coronal rotation of vertebrae. We propose a novel automatic approach to the measurement of the location and rotation of vertebrae in 3D without prior volume reformation, identification of appropriate cross-sections or aid by statistical models. The vertebra under investigation is encompassed by a mask in the form of an elliptical cylinder in 3D, defined by its center of rotation and the rotation angles. We exploit the natural symmetry of the vertebral body, vertebral column and vertebral canal by dividing the vertebral mask by its mid-axial, mid-sagittal and mid-coronal plane, so that the obtained volume pairs contain symmetrical parts of the observed anatomy. Mirror volume pairs are then simultaneously registered to each other by robust rigid auto-registration, using the weighted sum of absolute differences between the intensities of the corresponding volume pairs as the similarity measure. The method was evaluated on 50 lumbar vertebrae from normal and scoliotic computed tomography (CT) spinal scans, showing relatively large capture ranges and distinctive maxima at the correct locations and rotation angles. The proposed method may aid the measurement of the dimensions of vertebral pedicles, foraminae and canal, and may be a valuable tool for clinical evaluation of the spinal deformities in 3D.

  16. 3D-2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch.

    PubMed

    De Silva, T; Uneri, A; Ketcha, M D; Reaungamornrat, S; Kleinszig, G; Vogt, S; Aygun, N; Lo, S-F; Wolinsky, J-P; Siewerdsen, J H

    2016-04-21

    In image-guided spine surgery, robust three-dimensional to two-dimensional (3D-2D) registration of preoperative computed tomography (CT) and intraoperative radiographs can be challenged by the image content mismatch associated with the presence of surgical instrumentation and implants as well as soft-tissue resection or deformation. This work investigates image similarity metrics in 3D-2D registration offering improved robustness against mismatch, thereby improving performance and reducing or eliminating the need for manual masking. The performance of four gradient-based image similarity metrics (gradient information (GI), gradient correlation (GC), gradient information with linear scaling (GS), and gradient orientation (GO)) with a multi-start optimization strategy was evaluated in an institutional review board-approved retrospective clinical study using 51 preoperative CT images and 115 intraoperative mobile radiographs. Registrations were tested with and without polygonal masks as a function of the number of multistarts employed during optimization. Registration accuracy was evaluated in terms of the projection distance error (PDE) and assessment of failure modes (PDE  >  30 mm) that could impede reliable vertebral level localization. With manual polygonal masking and 200 multistarts, the GC and GO metrics exhibited robust performance with 0% gross failures and median PDE  <  6.4 mm (±4.4 mm interquartile range (IQR)) and a median runtime of 84 s (plus upwards of 1-2 min for manual masking). Excluding manual polygonal masks and decreasing the number of multistarts to 50 caused the GC-based registration to fail at a rate of  >14%; however, GO maintained robustness with a 0% gross failure rate. Overall, the GI, GC, and GS metrics were susceptible to registration errors associated with content mismatch, but GO provided robust registration (median PDE  =  5.5 mm, 2.6 mm IQR) without manual masking and with an improved

  17. 3D-2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch

    NASA Astrophysics Data System (ADS)

    De Silva, T.; Uneri, A.; Ketcha, M. D.; Reaungamornrat, S.; Kleinszig, G.; Vogt, S.; Aygun, N.; Lo, S.-F.; Wolinsky, J.-P.; Siewerdsen, J. H.

    2016-04-01

    In image-guided spine surgery, robust three-dimensional to two-dimensional (3D-2D) registration of preoperative computed tomography (CT) and intraoperative radiographs can be challenged by the image content mismatch associated with the presence of surgical instrumentation and implants as well as soft-tissue resection or deformation. This work investigates image similarity metrics in 3D-2D registration offering improved robustness against mismatch, thereby improving performance and reducing or eliminating the need for manual masking. The performance of four gradient-based image similarity metrics (gradient information (GI), gradient correlation (GC), gradient information with linear scaling (GS), and gradient orientation (GO)) with a multi-start optimization strategy was evaluated in an institutional review board-approved retrospective clinical study using 51 preoperative CT images and 115 intraoperative mobile radiographs. Registrations were tested with and without polygonal masks as a function of the number of multistarts employed during optimization. Registration accuracy was evaluated in terms of the projection distance error (PDE) and assessment of failure modes (PDE  >  30 mm) that could impede reliable vertebral level localization. With manual polygonal masking and 200 multistarts, the GC and GO metrics exhibited robust performance with 0% gross failures and median PDE  <  6.4 mm (±4.4 mm interquartile range (IQR)) and a median runtime of 84 s (plus upwards of 1-2 min for manual masking). Excluding manual polygonal masks and decreasing the number of multistarts to 50 caused the GC-based registration to fail at a rate of  >14% however, GO maintained robustness with a 0% gross failure rate. Overall, the GI, GC, and GS metrics were susceptible to registration errors associated with content mismatch, but GO provided robust registration (median PDE  =  5.5 mm, 2.6 mm IQR) without manual masking and with an improved

  18. Registration of 3D spectral OCT volumes using 3D SIFT feature point matching

    NASA Astrophysics Data System (ADS)

    Niemeijer, Meindert; Garvin, Mona K.; Lee, Kyungmoo; van Ginneken, Bram; Abràmoff, Michael D.; Sonka, Milan

    2009-02-01

    The recent introduction of next generation spectral OCT scanners has enabled routine acquisition of high resolution, 3D cross-sectional volumetric images of the retina. 3D OCT is used in the detection and management of serious eye diseases such as glaucoma and age-related macular degeneration. For follow-up studies, image registration is a vital tool to enable more precise, quantitative comparison of disease states. This work presents a registration method based on a recently introduced extension of the 2D Scale-Invariant Feature Transform (SIFT) framework1 to 3D.2 The SIFT feature extractor locates minima and maxima in the difference of Gaussian scale space to find salient feature points. It then uses histograms of the local gradient directions around each found extremum in 3D to characterize them in a 4096 element feature vector. Matching points are found by comparing the distance between feature vectors. We apply this method to the rigid registration of optic nerve head- (ONH) and macula-centered 3D OCT scans of the same patient that have only limited overlap. Three OCT data set pairs with known deformation were used for quantitative assessment of the method's robustness and accuracy when deformations of rotation and scaling were considered. Three-dimensional registration accuracy of 2.0+/-3.3 voxels was observed. The accuracy was assessed as average voxel distance error in N=1572 matched locations. The registration method was applied to 12 3D OCT scans (200 x 200 x 1024 voxels) of 6 normal eyes imaged in vivo to demonstrate the clinical utility and robustness of the method in a real-world environment.

  19. Automating measurement of subtle changes in articular cartilage from MRI of the knee by combining 3D image registration and segmentation

    NASA Astrophysics Data System (ADS)

    Lynch, John A.; Zaim, Souhil; Zhao, Jenny; Peterfy, Charles G.; Genant, Harry K.

    2001-07-01

    In osteoarthritis, articular cartilage loses integrity and becomes thinned. This usually occurs at sites which bear weight during normal use. Measurement of such loss from MRI scans, requires precise and reproducible techniques, which can overcome the difficulties of patient repositioning within the scanner. In this study, we combine a previously described technique for segmentation of cartilage from MRI of the knee, with a technique for 3D image registration that matches localized regions of interest at followup and baseline. Two patients, who had recently undergone meniscal surgery, and developed lesions during the 12 month followup period were examined. Image registration matched regions of interest (ROI) between baseline and followup, and changes within the cartilage lesions were estimate to be about a 16% reduction in cartilage volume within each ROI. This was more than 5 times the reproducibility of the measurement, but only represented a change of between 1 and 2% in total femoral cartilage volume. Changes in total cartilage volume may be insensitive for quantifying changes in cartilage morphology. A combined used of automated image segmentation, with 3D image registration could be a useful tool for the precise and sensitive measurement of localized changes in cartilage from MRI of the knee.

  20. 2D–3D radiograph to cone-beam computed tomography (CBCT) registration for C-arm image-guided robotic surgery

    PubMed Central

    Liu, Wen Pei; Otake, Yoshito; Azizian, Mahdi; Wagner, Oliver J.; Sorger, Jonathan M.; Armand, Mehran; Taylor, Russell H.

    2015-01-01

    Purpose C-arm radiographs are commonly used for intraoperative image guidance in surgical interventions. Fluoroscopy is a cost-effective real-time modality, although image quality can vary greatly depending on the target anatomy. Cone-beam computed tomography (CBCT) scans are sometimes available, so 2D–3D registration is needed for intra-procedural guidance. C-arm radiographs were registered to CBCT scans and used for 3D localization of peritumor fiducials during a minimally invasive thoracic intervention with a da Vinci Si robot. Methods Intensity-based 2D–3D registration of intraoperative radiographs to CBCT was performed. The feasible range of X-ray projections achievable by a C-arm positioned around a da Vinci Si surgical robot, configured for robotic wedge resection, was determined using phantom models. Experiments were conducted on synthetic phantoms and animals imaged with an OEC 9600 and a Siemens Artis zeego, representing the spectrum of different C-arm systems currently available for clinical use. Results The image guidance workflow was feasible using either an optically tracked OEC 9600 or a Siemens Artis zeego C-arm, resulting in an angular difference of Δθ : ~ 30°. The two C-arm systems provided TREmean ≤ 2.5 mm and TREmean ≤ 2.0 mm, respectively (i.e., comparable to standard clinical intraoperative navigation systems). Conclusions C-arm 3D localization from dual 2D–3D registered radiographs was feasible and applicable for intraoperative image guidance during da Vinci robotic thoracic interventions using the proposed workflow. Tissue deformation and in vivo experiments are required before clinical evaluation of this system. PMID:25503592

  1. Image fusion of Ultrasound Computer Tomography volumes with X-ray mammograms using a biomechanical model based 2D/3D registration.

    PubMed

    Hopp, T; Duric, N; Ruiter, N V

    2015-03-01

    Ultrasound Computer Tomography (USCT) is a promising breast imaging modality under development. Comparison to a standard method like mammography is essential for further development. Due to significant differences in image dimensionality and compression state of the breast, correlating USCT images and X-ray mammograms is challenging. In this paper we present a 2D/3D registration method to improve the spatial correspondence and allow direct comparison of the images. It is based on biomechanical modeling of the breast and simulation of the mammographic compression. We investigate the effect of including patient-specific material parameters estimated automatically from USCT images. The method was systematically evaluated using numerical phantoms and in-vivo data. The average registration accuracy using the automated registration was 11.9mm. Based on the registered images a method for analysis of the diagnostic value of the USCT images was developed and initially applied to analyze sound speed and attenuation images based on X-ray mammograms as ground truth. Combining sound speed and attenuation allows differentiating lesions from surrounding tissue. Overlaying this information on mammograms, combines quantitative and morphological information for multimodal diagnosis. PMID:25456144

  2. Efficient framework for deformable 2D-3D registration

    NASA Astrophysics Data System (ADS)

    Fluck, Oliver; Aharon, Shmuel; Khamene, Ali

    2008-03-01

    Using 2D-3D registration it is possible to extract the body transformation between the coordinate systems of X-ray and volumetric CT images. Our initial motivation is the improvement of accuracy of external beam radiation therapy, an effective method for treating cancer, where CT data play a central role in radiation treatment planning. Rigid body transformation is used to compute the correct patient setup. The drawback of such approaches is that the rigidity assumption on the imaged object is not valid for most of the patient cases, mainly due to respiratory motion. In the present work, we address this limitation by proposing a flexible framework for deformable 2D-3D registration consisting of a learning phase incorporating 4D CT data sets and hardware accelerated free form DRR generation, 2D motion computation, and 2D-3D back projection.

  3. 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

  4. Interactive initialization of 2D/3D rigid registration

    SciTech Connect

    Gong, Ren Hui; Güler, Özgür; Kürklüoglu, Mustafa; Lovejoy, John; Yaniv, Ziv

    2013-12-15

    Purpose: Registration is one of the key technical components in an image-guided navigation system. A large number of 2D/3D registration algorithms have been previously proposed, but have not been able to transition into clinical practice. The authors identify the primary reason for the lack of adoption with the prerequisite for a sufficiently accurate initial transformation, mean target registration error of about 10 mm or less. In this paper, the authors present two interactive initialization approaches that provide the desired accuracy for x-ray/MR and x-ray/CT registration in the operating room setting. Methods: The authors have developed two interactive registration methods based on visual alignment of a preoperative image, MR, or CT to intraoperative x-rays. In the first approach, the operator uses a gesture based interface to align a volume rendering of the preoperative image to multiple x-rays. The second approach uses a tracked tool available as part of a navigation system. Preoperatively, a virtual replica of the tool is positioned next to the anatomical structures visible in the volumetric data. Intraoperatively, the physical tool is positioned in a similar manner and subsequently used to align a volume rendering to the x-ray images using an augmented reality (AR) approach. Both methods were assessed using three publicly available reference data sets for 2D/3D registration evaluation. Results: In the authors' experiments, the authors show that for x-ray/MR registration, the gesture based method resulted in a mean target registration error (mTRE) of 9.3 ± 5.0 mm with an average interaction time of 146.3 ± 73.0 s, and the AR-based method had mTREs of 7.2 ± 3.2 mm with interaction times of 44 ± 32 s. For x-ray/CT registration, the gesture based method resulted in a mTRE of 7.4 ± 5.0 mm with an average interaction time of 132.1 ± 66.4 s, and the AR-based method had mTREs of 8.3 ± 5.0 mm with interaction times of 58 ± 52 s. Conclusions: Based on the

  5. 3D TEE registration with MR for cardiac interventional applications

    NASA Astrophysics Data System (ADS)

    Woo, Jonghye; Parthasarathy, Vijay; Sandeep, Dalal; Jain, Ameet

    2010-02-01

    Live three dimensional (3D) transesophageal echocardiography (TEE) provides real-time imaging of cardiac structure and function, and has been shown to be useful in interventional cardiac procedures. Its application in catheter based cardiac procedures is, however, limited by its limited field of view (FOV). In order to mitigate this limitation, we register pre-operative magnetic resonance (MR) images to live 3D TEE images. Conventional multimodal image registration techniques that use mutual information (MI) as the similarity measure use statistics from the entire image. In these cases, correct registration, however, may not coincide with the global maximum of MI metric. In order to address this problem, we present an automated registration algorithm that balances a combination global and local edge-based statistics. The weighted sum of global and local statistics is computed as the similarity measure, where the weights are decided based on the strength of the local statistics. Phantom validation experiments shows improved capture ranges when compared with conventional MI based methods. The proposed method provided robust results with accuracy better than 3 mm (5°) in the range of -10 to 12 mm (-6 to 3°), -14 to 12 mm (-6 to 6°) and -16 to 6 mm (-6 to 3°) in x-, y-, and z- axes respectively. We believe that the proposed registration method has the potential for real time intra-operative image fusion during percutaneous cardiac interventions.

  6. Non-rigid registration of a 3D ultrasound and a MR image data set of the female pelvic floor using a biomechanical model

    PubMed Central

    Verhey, Janko F; Wisser, Josef; Warfield, Simon K; Rexilius, Jan; Kikinis, Ron

    2005-01-01

    Background The visual combination of different modalities is essential for many medical imaging applications in the field of Computer-Assisted medical Diagnosis (CAD) to enhance the clinical information content. Clinically, incontinence is a diagnosis with high clinical prevalence and morbidity rate. The search for a method to identify risk patients and to control the success of operations is still a challenging task. The conjunction of magnetic resonance (MR) and 3D ultrasound (US) image data sets could lead to a new clinical visual representation of the morphology as we show with corresponding data sets of the female anal canal with this paper. Methods We present a feasibility study for a non-rigid registration technique based on a biomechanical model for MR and US image data sets of the female anal canal as a base for a new innovative clinical visual representation. Results It is shown in this case study that the internal and external sphincter region could be registered elastically and the registration partially corrects the compression induced by the ultrasound transducer, so the MR data set showing the native anatomy is used as a frame for the US data set showing the same region with higher resolution but distorted by the transducer Conclusion The morphology is of special interest in the assessment of anal incontinence and the non-rigid registration of normal clinical MR and US image data sets is a new field of the adaptation of this method incorporating the advantages of both technologies. PMID:15777475

  7. A computerized framework for monitoring four-dimensional dose distributions during stereotactic body radiation therapy using a portal dose image-based 2D/3D registration approach.

    PubMed

    Nakamoto, Takahiro; Arimura, Hidetaka; Nakamura, Katsumasa; Shioyama, Yoshiyuki; Mizoguchi, Asumi; Hirose, Taka-Aki; Honda, Hiroshi; Umezu, Yoshiyuki; Nakamura, Yasuhiko; Hirata, Hideki

    2015-03-01

    A computerized framework for monitoring four-dimensional (4D) dose distributions during stereotactic body radiation therapy based on a portal dose image (PDI)-based 2D/3D registration approach has been proposed in this study. Using the PDI-based registration approach, simulated 4D "treatment" CT images were derived from the deformation of 3D planning CT images so that a 2D planning PDI could be similar to a 2D dynamic clinical PDI at a breathing phase. The planning PDI was calculated by applying a dose calculation algorithm (a pencil beam convolution algorithm) to the geometry of the planning CT image and a virtual water equivalent phantom. The dynamic clinical PDIs were estimated from electronic portal imaging device (EPID) dynamic images including breathing phase data obtained during a treatment. The parameters of the affine transformation matrix were optimized based on an objective function and a gamma pass rate using a Levenberg-Marquardt (LM) algorithm. The proposed framework was applied to the EPID dynamic images of ten lung cancer patients, which included 183 frames (mean: 18.3 per patient). The 4D dose distributions during the treatment time were successfully obtained by applying the dose calculation algorithm to the simulated 4D "treatment" CT images. The mean±standard deviation (SD) of the percentage errors between the prescribed dose and the estimated dose at an isocenter for all cases was 3.25±4.43%. The maximum error for the ten cases was 14.67% (prescribed dose: 1.50Gy, estimated dose: 1.72Gy), and the minimum error was 0.00%. The proposed framework could be feasible for monitoring the 4D dose distribution and dose errors within a patient's body during treatment. PMID:25592290

  8. 2D/3D registration algorithm for lung brachytherapy

    SciTech Connect

    Zvonarev, P. S.; Farrell, T. J.; Hunter, R.; Wierzbicki, M.; Hayward, J. E.; Sur, R. K.

    2013-02-15

    Purpose: A 2D/3D registration algorithm is proposed for registering orthogonal x-ray images with a diagnostic CT volume for high dose rate (HDR) lung brachytherapy. Methods: The algorithm utilizes a rigid registration model based on a pixel/voxel intensity matching approach. To achieve accurate registration, a robust similarity measure combining normalized mutual information, image gradient, and intensity difference was developed. The algorithm was validated using a simple body and anthropomorphic phantoms. Transfer catheters were placed inside the phantoms to simulate the unique image features observed during treatment. The algorithm sensitivity to various degrees of initial misregistration and to the presence of foreign objects, such as ECG leads, was evaluated. Results: The mean registration error was 2.2 and 1.9 mm for the simple body and anthropomorphic phantoms, respectively. The error was comparable to the interoperator catheter digitization error of 1.6 mm. Preliminary analysis of data acquired from four patients indicated a mean registration error of 4.2 mm. Conclusions: Results obtained using the proposed algorithm are clinically acceptable especially considering the complications normally encountered when imaging during lung HDR brachytherapy.

  9. FIRE: an open-software suite for real-time 2D/3D image registration for image guided radiotherapy research

    NASA Astrophysics Data System (ADS)

    Furtado, H.; Gendrin, C.; Spoerk, J.; Steiner, E.; Underwood, T.; Kuenzler, T.; Georg, D.; Birkfellner, W.

    2016-03-01

    Radiotherapy treatments have changed at a tremendously rapid pace. Dose delivered to the tumor has escalated while organs at risk (OARs) are better spared. The impact of moving tumors during dose delivery has become higher due to very steep dose gradients. Intra-fractional tumor motion has to be managed adequately to reduce errors in dose delivery. For tumors with large motion such as tumors in the lung, tracking is an approach that can reduce position uncertainty. Tumor tracking approaches range from purely image intensity based techniques to motion estimation based on surrogate tracking. Research efforts are often based on custom designed software platforms which take too much time and effort to develop. To address this challenge we have developed an open software platform especially focusing on tumor motion management. FLIRT is a freely available open-source software platform. The core method for tumor tracking is purely intensity based 2D/3D registration. The platform is written in C++ using the Qt framework for the user interface. The performance critical methods are implemented on the graphics processor using the CUDA extension. One registration can be as fast as 90ms (11Hz). This is suitable to track tumors moving due to respiration (~0.3Hz) or heartbeat (~1Hz). Apart from focusing on high performance, the platform is designed to be flexible and easy to use. Current use cases range from tracking feasibility studies, patient positioning and method validation. Such a framework has the potential of enabling the research community to rapidly perform patient studies or try new methods.

  10. Heterodyne 3D ghost imaging

    NASA Astrophysics Data System (ADS)

    Yang, Xu; Zhang, Yong; Yang, Chenghua; Xu, Lu; Wang, Qiang; Zhao, Yuan

    2016-06-01

    Conventional three dimensional (3D) ghost imaging measures range of target based on pulse fight time measurement method. Due to the limit of data acquisition system sampling rate, range resolution of the conventional 3D ghost imaging is usually low. In order to take off the effect of sampling rate to range resolution of 3D ghost imaging, a heterodyne 3D ghost imaging (HGI) system is presented in this study. The source of HGI is a continuous wave laser instead of pulse laser. Temporal correlation and spatial correlation of light are both utilized to obtain the range image of target. Through theory analysis and numerical simulations, it is demonstrated that HGI can obtain high range resolution image with low sampling rate.

  11. An automatic approach for 3D registration of CT scans

    NASA Astrophysics Data System (ADS)

    Hu, Yang; Saber, Eli; Dianat, Sohail; Vantaram, Sreenath Rao; Abhyankar, Vishwas

    2012-03-01

    CT (Computed tomography) is a widely employed imaging modality in the medical field. Normally, a volume of CT scans is prescribed by a doctor when a specific region of the body (typically neck to groin) is suspected of being abnormal. The doctors are required to make professional diagnoses based upon the obtained datasets. In this paper, we propose an automatic registration algorithm that helps healthcare personnel to automatically align corresponding scans from 'Study' to 'Atlas'. The proposed algorithm is capable of aligning both 'Atlas' and 'Study' into the same resolution through 3D interpolation. After retrieving the scanned slice volume in the 'Study' and the corresponding volume in the original 'Atlas' dataset, a 3D cross correlation method is used to identify and register various body parts.

  12. Kinematic Analysis of Healthy Hips during Weight-Bearing Activities by 3D-to-2D Model-to-Image Registration Technique

    PubMed Central

    Hara, Daisuke; Nakashima, Yasuharu; Hamai, Satoshi; Higaki, Hidehiko; Ikebe, Satoru; Shimoto, Takeshi; Hirata, Masanobu; Kanazawa, Masayuki; Kohno, Yusuke; Iwamoto, Yukihide

    2014-01-01

    Dynamic hip kinematics during weight-bearing activities were analyzed for six healthy subjects. Continuous X-ray images of gait, chair-rising, squatting, and twisting were taken using a flat panel X-ray detector. Digitally reconstructed radiographic images were used for 3D-to-2D model-to-image registration technique. The root-mean-square errors associated with tracking the pelvis and femur were less than 0.3 mm and 0.3° for translations and rotations. For gait, chair-rising, and squatting, the maximum hip flexion angles averaged 29.6°, 81.3°, and 102.4°, respectively. The pelvis was tilted anteriorly around 4.4° on average during full gait cycle. For chair-rising and squatting, the maximum absolute value of anterior/posterior pelvic tilt averaged 12.4°/11.7° and 10.7°/10.8°, respectively. Hip flexion peaked on the way of movement due to further anterior pelvic tilt during both chair-rising and squatting. For twisting, the maximum absolute value of hip internal/external rotation averaged 29.2°/30.7°. This study revealed activity dependent kinematics of healthy hip joints with coordinated pelvic and femoral dynamic movements. Kinematics' data during activities of daily living may provide important insight as to the evaluating kinematics of pathological and reconstructed hips. PMID:25506056

  13. Automatic generation of boundary conditions using Demons non-rigid image registration for use in 3D modality-independent elastography

    NASA Astrophysics Data System (ADS)

    Pheiffer, Thomas S.; Ou, Jao J.; Miga, Michael I.

    2010-02-01

    Modality-independent elastography (MIE) is a method of elastography that reconstructs the elastic properties of tissue using images acquired under different loading conditions and a biomechanical model. Boundary conditions are a critical input to the algorithm, and are often determined by time-consuming point correspondence methods requiring manual user input. Unfortunately, generation of accurate boundary conditions for the biomechanical model is often difficult due to the challenge of accurately matching points between the source and target surfaces and consequently necessitates the use of large numbers of fiducial markers. This study presents a novel method of automatically generating boundary conditions by non-rigidly registering two image sets with a Demons diffusion-based registration algorithm. The use of this method was successfully performed in silico using magnetic resonance and X-ray computed tomography image data with known boundary conditions. These preliminary results have produced boundary conditions with accuracy of up to 80% compared to the known conditions. Finally, these boundary conditions were utilized within a 3D MIE reconstruction to determine an elasticity contrast ratio between tumor and normal tissue. Preliminary results show a reasonable characterization of the material properties on this first attempt and a significant improvement in the automation level and viability of the method.

  14. Imaging of prostate cancer: a platform for 3D co-registration of in-vivo MRI ex-vivo MRI and pathology

    NASA Astrophysics Data System (ADS)

    Orczyk, Clément; Mikheev, Artem; Rosenkrantz, Andrew; Melamed, Jonathan; Taneja, Samir S.; Rusinek, Henry

    2012-02-01

    Objectives: Multi-parametric MRI is emerging as a promising method for prostate cancer diagnosis. prognosis and treatment planning. However, the localization of in-vivo detected lesions and pathologic sites of cancer remains a significant challenge. To overcome this limitation we have developed and tested a system for co-registration of in-vivo MRI, ex-vivo MRI and histology. Materials and Methods: Three men diagnosed with localized prostate cancer (ages 54-72, PSA levels 5.1-7.7 ng/ml) were prospectively enrolled in this study. All patients underwent 3T multi-parametric MRI that included T2W, DCEMRI, and DWI prior to robotic-assisted prostatectomy. Ex-vivo multi-parametric MRI was performed on fresh prostate specimen. Excised prostates were then sliced at regular intervals and photographed both before and after fixation. Slices were perpendicular to the main axis of the posterior capsule, i.e., along the direction of the rectal wall. Guided by the location of the urethra, 2D digital images were assembled into 3D models. Cancer foci, extra-capsular extensions and zonal margins were delineated by the pathologist and included in 3D histology data. A locally-developed software was applied to register in-vivo, ex-vivo and histology using an over-determined set of anatomical landmarks placed in anterior fibro-muscular stroma, central. transition and peripheral zones. The mean root square distance across corresponding control points was used to assess co-registration error. Results: Two specimens were pT3a and one pT2b (negative margin) at pathology. The software successfully fused invivo MRI. ex-vivo MRI fresh specimen and histology using appropriate (rigid and affine) transformation models with mean square error of 1.59 mm. Coregistration accuracy was confirmed by multi-modality viewing using operator-guided variable transparency. Conclusion: The method enables successful co-registration of pre-operative MRI, ex-vivo MRI and pathology and it provides initial evidence

  15. Oriented Gaussian mixture models for nonrigid 2D/3D coronary artery registration.

    PubMed

    Baka, N; Metz, C T; Schultz, C J; van Geuns, R-J; Niessen, W J; van Walsum, T

    2014-05-01

    2D/3D registration of patient vasculature from preinterventional computed tomography angiography (CTA) to interventional X-ray angiography is of interest to improve guidance in percutaneous coronary interventions. In this paper we present a novel feature based 2D/3D registration framework, that is based on probabilistic point correspondences, and show its usefulness on aligning 3D coronary artery centerlines derived from CTA images with their 2D projection derived from interventional X-ray angiography. The registration framework is an extension of the Gaussian mixture model (GMM) based point-set registration to the 2D/3D setting, with a modified distance metric. We also propose a way to incorporate orientation in the registration, and show its added value for artery registration on patient datasets as well as in simulation experiments. The oriented GMM registration achieved a median accuracy of 1.06 mm, with a convergence rate of 81% for nonrigid vessel centerline registration on 12 patient datasets, using a statistical shape model. The method thereby outperformed the iterative closest point algorithm, the GMM registration without orientation, and two recently published methods on 2D/3D coronary artery registration. PMID:24770908

  16. An improved 3D shape context registration method for non-rigid surface registration

    NASA Astrophysics Data System (ADS)

    Xiao, Di; Zahra, David; Bourgeat, Pierrick; Berghofer, Paula; Acosta Tamayo, Oscar; Wimberley, Catriona; Gregoire, Marie-Claude; Salvado, Olivier

    2010-03-01

    3D shape context is a method to define matching points between similar shapes as a pre-processing step to non-rigid registration. The main limitation of the approach is point mismatching, which includes long geodesic distance mismatch and neighbors crossing mismatch. In this paper, we propose a topological structure verification method to correct the long geodesic distance mismatch and a correspondence field smoothing method to correct the neighbors crossing mismatch. A robust 3D shape context model is proposed and further combined with thin-plate spline model for non-rigid surface registration. The method was tested on phantoms and rat hind limb skeletons from micro CT images. The results from experiments on mouse hind limb skeletons indicate that the approach is robust.

  17. Locally adaptive 2D-3D registration using vascular structure model for liver catheterization.

    PubMed

    Kim, Jihye; Lee, Jeongjin; Chung, Jin Wook; Shin, Yeong-Gil

    2016-03-01

    Two-dimensional-three-dimensional (2D-3D) registration between intra-operative 2D digital subtraction angiography (DSA) and pre-operative 3D computed tomography angiography (CTA) can be used for roadmapping purposes. However, through the projection of 3D vessels, incorrect intersections and overlaps between vessels are produced because of the complex vascular structure, which makes it difficult to obtain the correct solution of 2D-3D registration. To overcome these problems, we propose a registration method that selects a suitable part of a 3D vascular structure for a given DSA image and finds the optimized solution to the partial 3D structure. The proposed algorithm can reduce the registration errors because it restricts the range of the 3D vascular structure for the registration by using only the relevant 3D vessels with the given DSA. To search for the appropriate 3D partial structure, we first construct a tree model of the 3D vascular structure and divide it into several subtrees in accordance with the connectivity. Then, the best matched subtree with the given DSA image is selected using the results from the coarse registration between each subtree and the vessels in the DSA image. Finally, a fine registration is conducted to minimize the difference between the selected subtree and the vessels of the DSA image. In experimental results obtained using 10 clinical datasets, the average distance errors in the case of the proposed method were 2.34±1.94mm. The proposed algorithm converges faster and produces more correct results than the conventional method in evaluations on patient datasets. PMID:26824922

  18. 2D-3D rigid registration to compensate for prostate motion during 3D TRUS-guided biopsy

    NASA Astrophysics Data System (ADS)

    De Silva, Tharindu; Fenster, Aaron; Bax, Jeffrey; Gardi, Lori; Romagnoli, Cesare; Samarabandu, Jagath; Ward, Aaron D.

    2012-02-01

    Prostate biopsy is the clinical standard for prostate cancer diagnosis. To improve the accuracy of targeting suspicious locations, systems have been developed that can plan and record biopsy locations in a 3D TRUS image acquired at the beginning of the procedure. Some systems are designed for maximum compatibility with existing ultrasound equipment and are thus designed around the use of a conventional 2D TRUS probe, using controlled axial rotation of this probe to acquire a 3D TRUS reference image at the start of the biopsy procedure. Prostate motion during the biopsy procedure causes misalignments between the prostate in the live 2D TRUS images and the pre-acquired 3D TRUS image. We present an image-based rigid registration technique that aligns live 2D TRUS images, acquired immediately prior to biopsy needle insertion, with the pre-acquired 3D TRUS image to compensate for this motion. Our method was validated using 33 manually identified intrinsic fiducials in eight subjects and the target registration error was found to be 1.89 mm. We analysed the suitability of two image similarity metrics (normalized cross correlation and mutual information) for this task by plotting these metrics as a function of varying parameters in the six degree-of-freedom transformation space, with the ground truth plane obtained from registration as the starting point for the parameter exploration. We observed a generally convex behaviour of the similarity metrics. This encourages their use for this registration problem, and could assist in the design of a tool for the detection of misalignment, which could trigger the execution of a non-real-time registration, when needed during the procedure.

  19. Validation for 2D/3D registration I: A new gold standard data set

    PubMed Central

    Pawiro, S. A.; Markelj, P.; Pernuš, F.; Gendrin, C.; Figl, M.; Weber, C.; Kainberger, F.; Nöbauer-Huhmann, I.; Bergmeister, H.; Stock, M.; Georg, D.; Bergmann, H.; Birkfellner, W.

    2011-01-01

    Purpose In this article, the authors propose a new gold standard data set for the validation of two-dimensional/three-dimensional (2D/3D) and 3D/3D image registration algorithms. Methods A gold standard data set was produced using a fresh cadaver pig head with attached fiducial markers. The authors used several imaging modalities common in diagnostic imaging or radiotherapy, which include 64-slice computed tomography (CT), magnetic resonance imaging using Tl, T2, and proton density sequences, and cone beam CT imaging data. Radiographic data were acquired using kilovoltage and megavoltage imaging techniques. The image information reflects both anatomy and reliable fiducial marker information and improves over existing data sets by the level of anatomical detail, image data quality, and soft-tissue content. The markers on the 3D and 2D image data were segmented using analyze 10.0 (AnalyzeDirect, Inc., Kansas City, KN) and an in-house software. Results The projection distance errors and the expected target registration errors over all the image data sets were found to be less than 2.71 and 1.88 mm, respectively. Conclusions The gold standard data set, obtained with state-of-the-art imaging technology, has the potential to improve the validation of 2D/3D and 3D/3D registration algorithms for image guided therapy. PMID:21520860

  20. Validation for 2D/3D registration I: A new gold standard data set

    SciTech Connect

    Pawiro, S. A.; Markelj, P.; Pernus, F.; Gendrin, C.; Figl, M.; Weber, C.; Kainberger, F.; Noebauer-Huhmann, I.; Bergmeister, H.; Stock, M.; Georg, D.; Bergmann, H.; Birkfellner, W.

    2011-03-15

    Purpose: In this article, the authors propose a new gold standard data set for the validation of two-dimensional/three-dimensional (2D/3D) and 3D/3D image registration algorithms. Methods: A gold standard data set was produced using a fresh cadaver pig head with attached fiducial markers. The authors used several imaging modalities common in diagnostic imaging or radiotherapy, which include 64-slice computed tomography (CT), magnetic resonance imaging using Tl, T2, and proton density sequences, and cone beam CT imaging data. Radiographic data were acquired using kilovoltage and megavoltage imaging techniques. The image information reflects both anatomy and reliable fiducial marker information and improves over existing data sets by the level of anatomical detail, image data quality, and soft-tissue content. The markers on the 3D and 2D image data were segmented using ANALYZE 10.0 (AnalyzeDirect, Inc., Kansas City, KN) and an in-house software. Results: The projection distance errors and the expected target registration errors over all the image data sets were found to be less than 2.71 and 1.88 mm, respectively. Conclusions: The gold standard data set, obtained with state-of-the-art imaging technology, has the potential to improve the validation of 2D/3D and 3D/3D registration algorithms for image guided therapy.

  1. Self-calibration of cone-beam CT geometry using 3D-2D image registration: development and application to tasked-based imaging with a robotic C-arm

    NASA Astrophysics Data System (ADS)

    Ouadah, S.; Stayman, J. W.; Gang, G.; Uneri, A.; Ehtiati, T.; Siewerdsen, J. H.

    2015-03-01

    Purpose: Robotic C-arm systems are capable of general noncircular orbits whose trajectories can be driven by the particular imaging task. However obtaining accurate calibrations for reconstruction in such geometries can be a challenging problem. This work proposes a method to perform a unique geometric calibration of an arbitrary C-arm orbit by registering 2D projections to a previously acquired 3D image to determine the transformation parameters representing the system geometry. Methods: Experiments involved a cone-beam CT (CBCT) bench system, a robotic C-arm, and three phantoms. A robust 3D-2D registration process was used to compute the 9 degree of freedom (DOF) transformation between each projection and an existing 3D image by maximizing normalized gradient information with a digitally reconstructed radiograph (DRR) of the 3D volume. The quality of the resulting "self-calibration" was evaluated in terms of the agreement with an established calibration method using a BB phantom as well as image quality in the resulting CBCT reconstruction. Results: The self-calibration yielded CBCT images without significant difference in spatial resolution from the standard ("true") calibration methods (p-value >0.05 for all three phantoms), and the differences between CBCT images reconstructed using the "self" and "true" calibration methods were on the order of 10-3 mm-1. Maximum error in magnification was 3.2%, and back-projection ray placement was within 0.5 mm. Conclusion: The proposed geometric "self" calibration provides a means for 3D imaging on general noncircular orbits in CBCT systems for which a geometric calibration is either not available or not reproducible. The method forms the basis of advanced "task-based" 3D imaging methods now in development for robotic C-arms.

  2. Reconstruction of 3D lung models from 2D planning data sets for Hodgkin's lymphoma patients using combined deformable image registration and navigator channels

    SciTech Connect

    Ng, Angela; Nguyen, Thao-Nguyen; Moseley, Joanne L.; Hodgson, David C.; Sharpe, Michael B.; Brock, Kristy K.

    2010-03-15

    Purpose: Late complications (cardiac toxicities, secondary lung, and breast cancer) remain a significant concern in the radiation treatment of Hodgkin's lymphoma (HL). To address this issue, predictive dose-risk models could potentially be used to estimate radiotherapy-related late toxicities. This study investigates the use of deformable image registration (DIR) and navigator channels (NCs) to reconstruct 3D lung models from 2D radiographic planning images, in order to retrospectively calculate the treatment dose exposure to HL patients treated with 2D planning, which are now experiencing late effects. Methods: Three-dimensional planning CT images of 52 current HL patients were acquired. 12 image sets were used to construct a male and a female population lung model. 23 ''Reference'' images were used to generate lung deformation adaptation templates, constructed by deforming the population model into each patient-specific lung geometry using a biomechanical-based DIR algorithm, MORFEUS. 17 ''Test'' patients were used to test the accuracy of the reconstruction technique by adapting existing templates using 2D digitally reconstructed radiographs. The adaptation process included three steps. First, a Reference patient was matched to a Test patient by thorax measurements. Second, four NCs (small regions of interest) were placed on the lung boundary to calculate 1D differences in lung edges. Third, the Reference lung model was adapted to the Test patient's lung using the 1D edge differences. The Reference-adapted Test model was then compared to the 3D lung contours of the actual Test patient by computing their percentage volume overlap (POL) and Dice coefficient. Results: The average percentage overlapping volumes and Dice coefficient expressed as a percentage between the adapted and actual Test models were found to be 89.2{+-}3.9% (Right lung=88.8%; Left lung=89.6%) and 89.3{+-}2.7% (Right=88.5%; Left=90.2%), respectively. Paired T-tests demonstrated that the

  3. 2D-3D registration of coronary angiograms for cardiac procedure planning and guidance.

    PubMed

    Turgeon, Guy-Anne; Lehmann, Glen; Guiraudon, Gerard; Drangova, Maria; Holdsworth, David; Peters, Terry

    2005-12-01

    We present a completely automated 2D-3D registration technique that accurately maps a patient-specific heart model, created from preoperative images, to the patient's orientation in the operating room. This mapping is based on the registration of preoperatively acquired 3D vascular data with intraoperatively acquired angiograms. Registration using both single and dual-plane angiograms is explored using simulated but realistic datasets that were created from clinical images. Heart deformations and cardiac phase mismatches are taken into account in our validation using a digital 4D human heart model. In an ideal situation where the pre- and intraoperative images were acquired at identical time points within the cardiac cycle, the single-plane and the dual-plane registrations resulted in 3D root-mean-square (rms) errors of 1.60 +/- 0.21 and 0.53 +/- 0.08 mm, respectively. When a 10% timing offset was added between the pre- and the intraoperative acquisitions, the single-plane registration approach resulted in inaccurate registrations in the out-of-plane axis, whereas the dual-plane registration exhibited a 98% success rate with a 3D rms error of 1.33 +/- 0.28 mm. When all potential sources of error were included, namely, the anatomical background, timing offset, and typical errors in the vascular tree reconstruction, the dual-plane registration performed at 94% with an accuracy of 2.19 +/- 0.77 mm. PMID:16475773

  4. Image registration of proximal femur with substantial bone changes: application in 3D visualization of bone loss of astronauts after long-duration spaceflight

    NASA Astrophysics Data System (ADS)

    Li, Wenjun; Sode, Miki; Saeed, Isra; Lang, Thomas

    2006-03-01

    We recently studied bone loss in crewmembers making 4 to 6 months flights on the International Space Station. We employed Quantitative Computed Tomography (QCT) technology (Lang et. al., J Bone Miner Res. 2004; v. 19, p. 1006), which made measurements of both cortical and trabecular bone loss that could not be obtained by using 2-dimensional dual x-ray absorptiometry (DXA) imaging technology. To further investigate the bone loss after spaceflight, we have developed image registration technologies to align serial scans so that bone changes can be directly visualized in a subregional level, which can provide more detailed information for understanding bone physiology during long-term spaceflight. To achieve effective and robust registration when large bone changes exist, we have developed technical adaptations to standard registration methods. Our automated image registration is mutual-information based. We have applied an automatically adaptive binning method in calculating the mutual information. After the pre- and post-flight scans are geometrically aligned, the interior bone changes can be clearly visualized. Image registration can also be applied to Finite Element Modeling (FEM) to compare bone strength change, where consistent loading conditions must be applied to serial scans.

  5. On averaging multiview relations for 3D scan registration.

    PubMed

    Govindu, Venu Madhav; Pooja, A

    2014-03-01

    In this paper, we present an extension of the iterative closest point (ICP) algorithm that simultaneously registers multiple 3D scans. While ICP fails to utilize the multiview constraints available, our method exploits the information redundancy in a set of 3D scans by using the averaging of relative motions. This averaging method utilizes the Lie group structure of motions, resulting in a 3D registration method that is both efficient and accurate. In addition, we present two variants of our approach, i.e., a method that solves for multiview 3D registration while obeying causality and a transitive correspondence variant that efficiently solves the correspondence problem across multiple scans. We present experimental results to characterize our method and explain its behavior as well as those of some other multiview registration methods in the literature. We establish the superior accuracy of our method in comparison to these multiview methods with registration results on a set of well-known real datasets of 3D scans. PMID:23412615

  6. Noninvasive MR to 3D Rotational x-ray registration of vetebral bodies

    NASA Astrophysics Data System (ADS)

    van de Kraats, Everine B.; van Walsum, Theo; Verlaan, Jorrit-Jan; Niessen, Wiro J.

    2003-05-01

    3D Rotational X-ray (3DRX) imaging can be used to intraoperatively acquire 3D volumes depicting bone structures in the patient. Registration of 3DRX to MR images, containing soft tissue information, facilitates image guided surgery on both soft tissue and bone tissue information simultaneously. In this paper, automated noninvasive registration using maximization of mutual information is compared to conventional interactive and invasive point-based registration using the least squares fit of corresponding point sets. Both methods were evaluated on 3DRX images (with a resolution of 0.62x0.62x0.62 mm3) and MRI images (with resolutions of 2x2x2 mm3, 1.5x1.5x1.5 mm3 and 1x1x1 mm3) of seven defrosted spinal segments implanted with six or seven markers. The markers were used for the evaluation of the registration transformations found by both point- and maximization of mutual information based registration. The root-mean-squared-error on markers that were left out during registration was calculated after transforming the marker set with the computed registration transformation. The results show that the noninvasive registration method performs significantly better (p<=0.01) for all MRI resolutions than point-based registration using four or five markers, which is the number of markers conventionally used in image guided surgery systems.

  7. Device and methods for "gold standard" registration of clinical 3D and 2D cerebral angiograms

    NASA Astrophysics Data System (ADS)

    Madan, Hennadii; Likar, Boštjan; Pernuš, Franjo; Å piclin, Žiga

    2015-03-01

    Translation of any novel and existing 3D-2D image registration methods into clinical image-guidance systems is limited due to lack of their objective validation on clinical image datasets. The main reason is that, besides the calibration of the 2D imaging system, a reference or "gold standard" registration is very difficult to obtain on clinical image datasets. In the context of cerebral endovascular image-guided interventions (EIGIs), we present a calibration device in the form of a headband with integrated fiducial markers and, secondly, propose an automated pipeline comprising 3D and 2D image processing, analysis and annotation steps, the result of which is a retrospective calibration of the 2D imaging system and an optimal, i.e., "gold standard" registration of 3D and 2D images. The device and methods were used to create the "gold standard" on 15 datasets of 3D and 2D cerebral angiograms, whereas each dataset was acquired on a patient undergoing EIGI for either aneurysm coiling or embolization of arteriovenous malformation. The use of the device integrated seamlessly in the clinical workflow of EIGI. While the automated pipeline eliminated all manual input or interactive image processing, analysis or annotation. In this way, the time to obtain the "gold standard" was reduced from 30 to less than one minute and the "gold standard" of 3D-2D registration on all 15 datasets of cerebral angiograms was obtained with a sub-0.1 mm accuracy.

  8. Non-Iterative Rigid 2D/3D Point-Set Registration Using Semidefinite Programming

    NASA Astrophysics Data System (ADS)

    Khoo, Yuehaw; Kapoor, Ankur

    2016-07-01

    We describe a convex programming framework for pose estimation in 2D/3D point-set registration with unknown point correspondences. We give two mixed-integer nonlinear program (MINP) formulations of the 2D/3D registration problem when there are multiple 2D images, and propose convex relaxations for both of the MINPs to semidefinite programs (SDP) that can be solved efficiently by interior point methods. Our approach to the 2D/3D registration problem is non-iterative in nature as we jointly solve for pose and correspondence. Furthermore, these convex programs can readily incorporate feature descriptors of points to enhance registration results. We prove that the convex programs exactly recover the solution to the original nonconvex 2D/3D registration problem under noiseless condition. We apply these formulations to the registration of 3D models of coronary vessels to their 2D projections obtained from multiple intra-operative fluoroscopic images. For this application, we experimentally corroborate the exact recovery property in the absence of noise and further demonstrate robustness of the convex programs in the presence of noise.

  9. 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

  10. Deformable 3D-2D registration for CT and its application to low dose tomographic fluoroscopy.

    PubMed

    Flach, Barbara; Brehm, Marcus; Sawall, Stefan; Kachelrieß, Marc

    2014-12-21

    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

  11. Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks

    PubMed Central

    Grocott, Timothy; Thomas, Paul; Münsterberg, Andrea E.

    2016-01-01

    Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states. PMID:26864723

  12. Multibeam 3D Underwater SLAM with Probabilistic Registration

    PubMed Central

    Palomer, Albert; Ridao, Pere; Ribas, David

    2016-01-01

    This paper describes a pose-based underwater 3D Simultaneous Localization and Mapping (SLAM) using a multibeam echosounder to produce high consistency underwater maps. The proposed algorithm compounds swath profiles of the seafloor with dead reckoning localization to build surface patches (i.e., point clouds). An Iterative Closest Point (ICP) with a probabilistic implementation is then used to register the point clouds, taking into account their uncertainties. The registration process is divided in two steps: (1) point-to-point association for coarse registration and (2) point-to-plane association for fine registration. The point clouds of the surfaces to be registered are sub-sampled in order to decrease both the computation time and also the potential of falling into local minima during the registration. In addition, a heuristic is used to decrease the complexity of the association step of the ICP from O(n2) to O(n). The performance of the SLAM framework is tested using two real world datasets: First, a 2.5D bathymetric dataset obtained with the usual down-looking multibeam sonar configuration, and second, a full 3D underwater dataset acquired with a multibeam sonar mounted on a pan and tilt unit. PMID:27104538

  13. Multibeam 3D Underwater SLAM with Probabilistic Registration.

    PubMed

    Palomer, Albert; Ridao, Pere; Ribas, David

    2016-01-01

    This paper describes a pose-based underwater 3D Simultaneous Localization and Mapping (SLAM) using a multibeam echosounder to produce high consistency underwater maps. The proposed algorithm compounds swath profiles of the seafloor with dead reckoning localization to build surface patches (i.e., point clouds). An Iterative Closest Point (ICP) with a probabilistic implementation is then used to register the point clouds, taking into account their uncertainties. The registration process is divided in two steps: (1) point-to-point association for coarse registration and (2) point-to-plane association for fine registration. The point clouds of the surfaces to be registered are sub-sampled in order to decrease both the computation time and also the potential of falling into local minima during the registration. In addition, a heuristic is used to decrease the complexity of the association step of the ICP from O(n2) to O(n) . The performance of the SLAM framework is tested using two real world datasets: First, a 2.5D bathymetric dataset obtained with the usual down-looking multibeam sonar configuration, and second, a full 3D underwater dataset acquired with a multibeam sonar mounted on a pan and tilt unit. PMID:27104538

  14. 3D-2D registration of cerebral angiograms based on vessel directions and intensity gradients

    NASA Astrophysics Data System (ADS)

    Mitrovic, Uroš; Špiclin, Žiga; Štern, Darko; Markelj, Primož; Likar, Boštjan; Miloševic, Zoran; Pernuš, Franjo

    2012-02-01

    Endovascular treatment of cerebral aneurysms and arteriovenous malformations (AVM) involves navigation of a catheter through the femoral artery and vascular system to the site of pathology. Intra-interventional navigation is done under the guidance of one or at most two two-dimensional (2D) X-ray fluoroscopic images or 2D digital subtracted angiograms (DSA). Due to the projective nature of 2D images, the interventionist needs to mentally reconstruct the position of the catheter in respect to the three-dimensional (3D) patient vasculature, which is not a trivial task. By 3D-2D registration of pre-interventional 3D images like CTA, MRA or 3D-DSA and intra-interventional 2D images, intra-interventional tools such as catheters can be visualized on the 3D model of patient vasculature, allowing easier and faster navigation. Such a navigation may consequently lead to the reduction of total ionizing dose and delivered contrast medium. In the past, development and evaluation of 3D-2D registration methods for endovascular treatments received considerable attention. The main drawback of these methods is that they have to be initialized rather close to the correct position as they mostly have a rather small capture range. In this paper, a novel registration method that has a higher capture range and success rate is proposed. The proposed method and a state-of-the-art method were tested and evaluated on synthetic and clinical 3D-2D image-pairs. The results on both databases indicate that although the proposed method was slightly less accurate, it significantly outperformed the state-of-the-art 3D-2D registration method in terms of robustness measured by capture range and success rate.

  15. An accurate 3D shape context based non-rigid registration method for mouse whole-body skeleton registration

    NASA Astrophysics Data System (ADS)

    Xiao, Di; Zahra, David; Bourgeat, Pierrick; Berghofer, Paula; Acosta Tamayo, Oscar; Wimberley, Catriona; Gregoire, Marie C.; Salvado, Olivier

    2011-03-01

    Small animal image registration is challenging because of its joint structure, and posture and position difference in each acquisition without a standard scan protocol. In this paper, we face the issue of mouse whole-body skeleton registration from CT images. A novel method is developed for analyzing mouse hind-limb and fore-limb postures based on geodesic path descriptor and then registering the major skeletons and fore limb skeletons initially by thin-plate spline (TPS) transform based on the obtained geodesic paths and their enhanced correspondence fields. A target landmark correction method is proposed for improving the registration accuracy of the improved 3D shape context non-rigid registration method we previously proposed. A novel non-rigid registration framework, combining the skeleton posture analysis, geodesic path based initial alignment and 3D shape context model, is proposed for mouse whole-body skeleton registration. The performance of the proposed methods and framework was tested on 12 pairs of mouse whole-body skeletons. The experimental results demonstrated the flexibility, stability and accuracy of the proposed framework for automatic mouse whole body skeleton registration.

  16. 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.

  17. Automatic pose initialization for accurate 2D/3D registration applied to abdominal aortic aneurysm endovascular repair

    NASA Astrophysics Data System (ADS)

    Miao, Shun; Lucas, Joseph; Liao, Rui

    2012-02-01

    Minimally invasive abdominal aortic aneurysm (AAA) stenting can be greatly facilitated by overlaying the preoperative 3-D model of the abdominal aorta onto the intra-operative 2-D X-ray images. Accurate 2-D/3-D registration in 3-D space makes the 2-D/3-D overlay robust to the change of C-Arm angulations. By far, the 2-D/3-D registration methods based on simulated X-ray projection images using multiple image planes have been shown to be able to provide satisfactory 3-D registration accuracy. However, one drawback of the intensity-based 2-D/3-D registration methods is that the similarity measure is usually highly non-convex and hence the optimizer can easily be trapped into local minima. User interaction therefore is often needed in the initialization of the position of the 3-D model in order to get a successful 2-D/3-D registration. In this paper, a novel 3-D pose initialization technique is proposed, as an extension of our previously proposed bi-plane 2-D/3-D registration method for AAA intervention [4]. The proposed method detects vessel bifurcation points and spine centerline in both 2-D and 3-D images, and utilizes landmark information to bring the 3-D volume into a 15mm capture range. The proposed landmark detection method was validated on real dataset, and is shown to be able to provide a good initialization for 2-D/3-D registration in [4], thus making the workflow fully automatic.

  18. 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.

  19. Localization of Metal Electrodes in the Intact Rat Brain Using Registration of 3D Microcomputed Tomography Images to a Magnetic Resonance Histology Atlas1,2,3

    PubMed Central

    Borg, Jana Schaich; Vu, Mai-Anh; Badea, Cristian; Badea, Alexandra; Johnson, G. Allan

    2015-01-01

    Abstract Simultaneous neural recordings taken from multiple areas of the rodent brain are garnering growing interest because of the insight they can provide about spatially distributed neural circuitry. The promise of such recordings has inspired great progress in methods for surgically implanting large numbers of metal electrodes into intact rodent brains. However, methods for localizing the precise location of these electrodes have remained severely lacking. Traditional histological techniques that require slicing and staining of physical brain tissue are cumbersome and become increasingly impractical as the number of implanted electrodes increases. Here we solve these problems by describing a method that registers 3D computed tomography (CT) images of intact rat brains implanted with metal electrode bundles to a magnetic resonance imaging histology (MRH) atlas. Our method allows accurate visualization of each electrode bundle’s trajectory and location without removing the electrodes from the brain or surgically implanting external markers. In addition, unlike physical brain slices, once the 3D images of the electrode bundles and the MRH atlas are registered, it is possible to verify electrode placements from many angles by “reslicing” the images along different planes of view. Furthermore, our method can be fully automated and easily scaled to applications with large numbers of specimens. Our digital imaging approach to efficiently localizing metal electrodes offers a substantial addition to currently available methods, which, in turn, may help accelerate the rate at which insights are gleaned from rodent network neuroscience. PMID:26322331

  20. Registration of 3-D holograms of diamond crystals (Abstract Only)

    NASA Astrophysics Data System (ADS)

    Marchenko, S. N.; Smirnova, S. N.

    1991-02-01

    Registration of 3D ho1orarns broadens the possibility of using single-crystal tool for imagining and investigating inner inhomogeneities and dynamic stresses in top area of gem diamond, study of which by other techniques,e.g. polarization optics, is difficult or impossible. The difficulty is that the diamond with significant refractive index of 2.42 has comparatively small angle of total internal reflection of 24°50. As a result, with random illumination of the tops of octahedron diamond crystals, both smooth- faceted and with polycentric facets, illuminating light is successively reflected from different farets and absorbed in the crystal or comes out of it in a spot and direction that are difficult to calculate. Optimal schemes of illuminating crystals for recording 3D holograms of smooth faceted octahedron diamonds are given. Analysis of illumination of the crystal with polycentric facets shows that correction of light in the diamond is determined by directivity diagram the width of which depends in inhomogeneity size of the diamond. 3D holograms of diamonds with different reflectivity were produced. For the first time the possibility is shown for registration of holograms for studying stresses in diamond top using single-crystal tool.

  1. A 3D neurovascular bundles segmentation method based on MR-TRUS deformable registration

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Rossi, Peter; Jani, Ashesh B.; Mao, Hui; Ogunleye, Tomi; Curran, Walter J.; Liu, Tian

    2015-03-01

    In this paper, we propose a 3D neurovascular bundles (NVB) segmentation method for ultrasound (US) image by integrating MR and transrectal ultrasound (TRUS) images through MR-TRUS deformable registration. First, 3D NVB was contoured by a physician in MR images, and the 3D MRdefined NVB was then transformed into US images using a MR-TRUS registration method, which models the prostate tissue as an elastic material, and jointly estimates the boundary deformation and the volumetric deformations under the elastic constraint. This technique was validated with a clinical study of 6 patients undergoing radiation therapy (RT) treatment for prostate cancer. The accuracy of our approach was assessed through the locations of landmarks, as well as previous ultrasound Doppler images of patients. MR-TRUS registration was successfully performed for all patients. The mean displacement of the landmarks between the post-registration MR and TRUS images was less than 2 mm, and the average NVB volume Dice Overlap Coefficient was over 89%. This NVB segmentation technique could be a useful tool as we try to spare the NVB in prostate RT, monitor NVB response to RT, and potentially improve post-RT potency outcomes.

  2. 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).

  3. Low Dose, Low Energy 3d Image Guidance during Radiotherapy

    NASA Astrophysics Data System (ADS)

    Moore, C. J.; Marchant, T.; Amer, A.; Sharrock, P.; Price, P.; Burton, D.

    2006-04-01

    Patient kilo-voltage X-ray cone beam volumetric imaging for radiotherapy was first demonstrated on an Elekta Synergy mega-voltage X-ray linear accelerator. Subsequently low dose, reduced profile reconstruction imaging was shown to be practical for 3D geometric setup registration to pre-treatment planning images without compromising registration accuracy. Reconstruction from X-ray profiles gathered between treatment beam deliveries was also introduced. The innovation of zonal cone beam imaging promises significantly reduced doses to patients and improved soft tissue contrast in the tumour target zone. These developments coincided with the first dynamic 3D monitoring of continuous body topology changes in patients, at the moment of irradiation, using a laser interferometer. They signal the arrival of low dose, low energy 3D image guidance during radiotherapy itself.

  4. Registration of 3D ultrasound computer tomography and MRI for evaluation of tissue correspondences

    NASA Astrophysics Data System (ADS)

    Hopp, T.; Dapp, R.; Zapf, M.; Kretzek, E.; Gemmeke, H.; Ruiter, N. V.

    2015-03-01

    3D Ultrasound Computer Tomography (USCT) is a new imaging method for breast cancer diagnosis. In the current state of development it is essential to correlate USCT with a known imaging modality like MRI to evaluate how different tissue types are depicted. Due to different imaging conditions, e.g. with the breast subject to buoyancy in USCT, a direct correlation is demanding. We present a 3D image registration method to reduce positioning differences and allow direct side-by-side comparison of USCT and MRI volumes. It is based on a two-step approach including a buoyancy simulation with a biomechanical model and free form deformations using cubic B-Splines for a surface refinement. Simulation parameters are optimized patient-specifically in a simulated annealing scheme. The method was evaluated with in-vivo datasets resulting in an average registration error below 5mm. Correlating tissue structures can thereby be located in the same or nearby slices in both modalities and three-dimensional non-linear deformations due to the buoyancy are reduced. Image fusion of MRI volumes and USCT sound speed volumes was performed for intuitive display. By applying the registration to data of our first in-vivo study with the KIT 3D USCT, we could correlate several tissue structures in MRI and USCT images and learn how connective tissue, carcinomas and breast implants observed in the MRI are depicted in the USCT imaging modes.

  5. Accuracy in Quantitative 3D Image Analysis

    PubMed Central

    Bassel, George W.

    2015-01-01

    Quantitative 3D imaging is becoming an increasingly popular and powerful approach to investigate plant growth and development. With the increased use of 3D image analysis, standards to ensure the accuracy and reproducibility of these data are required. This commentary highlights how image acquisition and postprocessing can introduce artifacts into 3D image data and proposes steps to increase both the accuracy and reproducibility of these analyses. It is intended to aid researchers entering the field of 3D image processing of plant cells and tissues and to help general readers in understanding and evaluating such data. PMID:25804539

  6. Non-rigid registration of small animal skeletons from micro-CT using 3D shape context

    NASA Astrophysics Data System (ADS)

    Xiao, Di; Bourgeat, Pierrick; Fripp, Jurgen; Acosta Tamayo, Oscar; Gregoire, Marie Claude; Salvado, Olivier

    2009-02-01

    Small animal registration is an important step for molecular image analysis. Skeleton registration from whole-body or only partial micro Computerized Tomography (CT) image is often performed to match individual rats to atlases and templates, for example to identify organs in positron emission tomography (PET). In this paper, we extend the shape context matching technique for 3D surface registration and apply it for rat hind limb skeleton registration from CT images. Using the proposed method, after standard affine iterative closest point (ICP) registration, correspondences between the 3D points from sour and target objects were robustly found and used to deform the limb skeleton surface with thin-plate-spline (TPS). Experiments are described using phantoms and actual rat hind limb skeletons. On animals, mean square errors were decreased by the proposed registration compared to that of its initial alignment. Visually, skeletons were successfully registered even in cases of very different animal poses.

  7. Feature-Based Quality Evaluation of 3d Point Clouds - Study of the Performance of 3d Registration Algorithms

    NASA Astrophysics Data System (ADS)

    Ridene, T.; Goulette, F.; Chendeb, S.

    2013-08-01

    The production of realistic 3D map databases is continuously growing. We studied an approach of 3D mapping database producing based on the fusion of heterogeneous 3D data. In this term, a rigid registration process was performed. Before starting the modeling process, we need to validate the quality of the registration results, and this is one of the most difficult and open research problems. In this paper, we suggest a new method of evaluation of 3D point clouds based on feature extraction and comparison with a 2D reference model. This method is based on tow metrics: binary and fuzzy.

  8. An enhanced method for registration of dental surfaces partially scanned by a 3D dental laser scanning.

    PubMed

    Park, Seongjin; Kang, Ho Chul; Lee, Jeongjin; Shin, Juneseuk; Shin, Yeong Gil

    2015-01-01

    In this paper, we propose the fast and accurate registration method of partially scanned dental surfaces in a 3D dental laser scanning. To overcome the multiple point correspondence problems of conventional surface registration methods, we propose the novel depth map-based registration method to register 3D surface models. First, we convert a partially scanned 3D dental surface into a 2D image by generating the 2D depth map image of the surface model by applying a 3D rigid transformation into this model. Then, the image-based registration method using 2D depth map images accurately estimates the initial transformation between two consequently acquired surface models. To further increase the computational efficiency, we decompose the 3D rigid transformation into out-of-plane (i.e. x-, y-rotation, and z-translation) and in-plane (i.e. x-, y-translation, and z-rotation) transformations. For the in-plane transformation, we accelerate the transformation process by transforming the 2D depth map image instead of transforming the 3D surface model. For the more accurate registration of 3D surface models, we enhance iterative closest point (ICP) method for the subsequent fine registration. Our initial depth map-based registration well aligns each surface model. Therefore, our subsequent ICP method can accurately register two surface models since it is highly probable that the closest point pairs are the exact corresponding point pairs. The experimental results demonstrated that our method accurately registered partially scanned dental surfaces. Regarding the computational performance, our method delivered about 1.5 times faster registration than the conventional method. Our method can be successfully applied to the accurate reconstruction of 3D dental objects for orthodontic and prosthodontic treatment. PMID:25453381

  9. Image Registration Workshop Proceedings

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline (Editor)

    1997-01-01

    Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research.

  10. 3D nonrigid registration via optimal mass transport on the GPU.

    PubMed

    Ur Rehman, Tauseef; Haber, Eldad; Pryor, Gallagher; Melonakos, John; Tannenbaum, Allen

    2009-12-01

    In this paper, we present a new computationally efficient numerical scheme for the minimizing flow approach for optimal mass transport (OMT) with applications to non-rigid 3D image registration. The approach utilizes all of the gray-scale data in both images, and the optimal mapping from image A to image B is the inverse of the optimal mapping from B to A. Further, no landmarks need to be specified, and the minimizer of the distance functional involved is unique. Our implementation also employs multigrid, and parallel methodologies on a consumer graphics processing unit (GPU) for fast computation. Although computing the optimal map has been shown to be computationally expensive in the past, we show that our approach is orders of magnitude faster then previous work and is capable of finding transport maps with optimality measures (mean curl) previously unattainable by other works (which directly influences the accuracy of registration). We give results where the algorithm was used to compute non-rigid registrations of 3D synthetic data as well as intra-patient pre-operative and post-operative 3D brain MRI datasets. PMID:19135403

  11. 3D nonrigid registration via optimal mass transport on the GPU

    PubMed Central

    Rehman, Tauseef ur; Haber, Eldad; Pryor, Gallagher; Melonakos, John; Tannenbaum, Allen

    2009-01-01

    In this paper, we present a new computationally efficient numerical scheme for the minimizing flow approach for optimal mass transport (OMT) with applications to non-rigid 3D image registration. The approach utilizes all of the gray-scale data in both images, and the optimal mapping from image A to image B is the inverse of the optimal mapping from B to A. Further, no landmarks need to be specified, and the minimizer of the distance functional involved is unique. Our implementation also employs multigrid, and parallel methodologies on a consumer graphics processing unit (GPU) for fast computation. Although computing the optimal map has been shown to be computationally expensive in the past, we show that our approach is orders of magnitude faster then previous work and is capable of finding transport maps with optimality measures (mean curl) previously unattainable by other works (which directly influences the accuracy of registration). We give results where the algorithm was used to compute non-rigid registrations of 3D synthetic data as well as intra-patient pre-operative and post-operative 3D brain MRI datasets. PMID:19135403

  12. 3D ultrafast ultrasound imaging in vivo

    NASA Astrophysics Data System (ADS)

    Provost, Jean; Papadacci, Clement; Esteban Arango, Juan; Imbault, Marion; Fink, Mathias; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu

    2014-10-01

    Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in 3D based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32  ×  32 matrix-array probe. Its ability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3D Shear-Wave Imaging, 3D Ultrafast Doppler Imaging, and, finally, 3D Ultrafast combined Tissue and Flow Doppler Imaging. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3D Ultrafast Doppler was used to obtain 3D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, at thousands of volumes per second, the complex 3D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, as well as the 3D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3D Ultrafast Ultrasound Imaging for the 3D mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra—and inter-observer variability.

  13. Nonrigid point registration for 2D curves and 3D surfaces and its various applications

    NASA Astrophysics Data System (ADS)

    Wang, Hesheng; Fei, Baowei

    2013-06-01

    A nonrigid B-spline-based point-matching (BPM) method is proposed to match dense surface points. The method solves both the point correspondence and nonrigid transformation without features extraction. The registration method integrates a motion model, which combines a global transformation and a B-spline-based local deformation, into a robust point-matching framework. The point correspondence and deformable transformation are estimated simultaneously by fuzzy correspondence and by a deterministic annealing technique. Prior information about global translation, rotation and scaling is incorporated into the optimization. A local B-spline motion model decreases the degrees of freedom for optimization and thus enables the registration of a larger number of feature points. The performance of the BPM method has been demonstrated and validated using synthesized 2D and 3D data, mouse MRI and micro-CT images. The proposed BPM method can be used to register feature point sets, 2D curves, 3D surfaces and various image data.

  14. SU-F-BRF-08: Conformal Mapping-Based 3D Surface Matching and Registration

    SciTech Connect

    Song, Y; Zeng, W; Gu, X; Liu, C

    2014-06-15

    Purpose: Recently, non-rigid 3D surface matching and registration has been used extensively in engineering and medicine. However, matching 3D surfaces undergoing non-rigid deformation accurately is still a challenging mathematical problem. In this study, we present a novel algorithm to address this issue by introducing intrinsic symmetry to the registration Methods: Our computational algorithm for symmetric conformal mapping is divided into three major steps: 1) Finding the symmetric plane; 2) Finding feature points; and 3) Performing cross registration. The key strategy is to preserve the symmetry during the conformal mapping, such that the image on the parameter domain is symmetric and the area distortion factor on the parameter image is also symmetric. Several novel algorithms were developed using different conformal geometric tools. One was based on solving Riemann-Cauchy equation and the other one employed curvature flow Results: Our algorithm was implemented using generic C++ on Windows XP and used conjugate gradient search optimization for acceleration. The human face 3D surface images were acquired using a high speed 3D scanner based on the phase-shifting method. The scanning speed was 30 frames/sec. The image resolution for each frame was 640 × 480. For 3D human face surfaces with different expressions, postures, and boundaries, our algorithms were able to produce consistent result on the texture pattern on the overlapping region Conclusion: We proposed a novel algorithm to improve the robustness of conformal geometric methods by incorporating the symmetric information into the mapping process. To objectively evaluate its performance, we compared it with most existing techniques. Experimental results indicated that our method outperformed all the others in terms of robustness. The technique has a great potential in real-time patient monitoring and tracking in image-guided radiation therapy.

  15. Evaluating Similarity Measures for Brain Image Registration

    PubMed Central

    Razlighi, Q. R.; Kehtarnavaz, N.; Yousefi, S.

    2013-01-01

    Evaluation of similarity measures for image registration is a challenging problem due to its complex interaction with the underlying optimization, regularization, image type and modality. We propose a single performance metric, named robustness, as part of a new evaluation method which quantifies the effectiveness of similarity measures for brain image registration while eliminating the effects of the other parts of the registration process. We show empirically that similarity measures with higher robustness are more effective in registering degraded images and are also more successful in performing intermodal image registration. Further, we introduce a new similarity measure, called normalized spatial mutual information, for 3D brain image registration whose robustness is shown to be much higher than the existing ones. Consequently, it tolerates greater image degradation and provides more consistent outcomes for intermodal brain image registration. PMID:24039378

  16. Local Metric Learning in 2D/3D Deformable Registration With Application in the Abdomen

    PubMed Central

    Chou, Chen-Rui; Mageras, Gig; Pizer, Stephen

    2015-01-01

    In image-guided radiotherapy (IGRT) of disease sites subject to respiratory motion, soft tissue deformations can affect localization accuracy. We describe the application of a method of 2D/3D deformable registration to soft tissue localization in abdomen. The method, called registration efficiency and accuracy through learning a metric on shape (REALMS), is designed to support real-time IGRT. In a previously developed version of REALMS, the method interpolated 3D deformation parameters for any credible deformation in a deformation space using a single globally-trained Riemannian metric for each parameter. We propose a refinement of the method in which the metric is trained over a particular region of the deformation space, such that interpolation accuracy within that region is improved. We report on the application of the proposed algorithm to IGRT in abdominal disease sites, which is more challenging than in lung because of low intensity contrast and nonrespiratory deformation. We introduce a rigid translation vector to compensate for nonrespiratory deformation, and design a special region-of-interest around fiducial markers implanted near the tumor to produce a more reliable registration. Both synthetic data and actual data tests on abdominal datasets show that the localized approach achieves more accurate 2D/3D deformable registration than the global approach. PMID:24771575

  17. Fast and robust 3D ultrasound registration--block and game theoretic matching.

    PubMed

    Banerjee, Jyotirmoy; Klink, Camiel; Peters, Edward D; Niessen, Wiro J; Moelker, Adriaan; van Walsum, Theo

    2015-02-01

    Real-time 3D US has potential for image guidance in minimally invasive liver interventions. However, motion caused by patient breathing makes it hard to visualize a localized area, and to maintain alignment with pre-operative information. In this work we develop a fast affine registration framework to compensate in real-time for liver motion/displacement due to breathing. The affine registration of two consecutive ultrasound volumes in time is performed using block-matching. For a set of evenly distributed points in one volume and their correspondences in the other volume, we propose a robust outlier rejection method to reject false matches. The inliers are then used to determine the affine transformation. The approach is evaluated on 13 4D ultrasound sequences acquired from 8 subjects. For 91 pairs of 3D ultrasound volumes selected from these sequences, a mean registration error of 1.8mm is achieved. A graphics processing unit (GPU) implementation runs the 3D US registration at 8 Hz. PMID:25484018

  18. 3D Ultrafast Ultrasound Imaging In Vivo

    PubMed Central

    Provost, Jean; Papadacci, Clement; Arango, Juan Esteban; Imbault, Marion; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu

    2014-01-01

    Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative real-time imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in three dimensions based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32×32 matrix-array probe. Its capability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3-D Shear-Wave Imaging, 3-D Ultrafast Doppler Imaging and finally 3D Ultrafast combined Tissue and Flow Doppler. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3-D Ultrafast Doppler was used to obtain 3-D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, for the first time, the complex 3-D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, and the 3-D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3-D Ultrafast Ultrasound Imaging for the 3-D real-time mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra- and inter-observer variability. PMID:25207828

  19. Evaluation of optimization methods for intensity-based 2D-3D registration in x-ray guided interventions

    NASA Astrophysics Data System (ADS)

    van der Bom, I. M. J.; Klein, S.; Staring, M.; Homan, R.; Bartels, L. W.; Pluim, J. P. W.

    2011-03-01

    The advantage of 2D-3D image registration methods versus direct image-to-patient registration, is that these methods generally do not require user interaction (such as manual annotations), additional machinery or additional acquisition of 3D data. A variety of intensity-based similarity measures has been proposed and evaluated for different applications. These studies showed that the registration accuracy and capture range are influenced by the choice of similarity measure. However, the influence of the optimization method on intensity-based 2D-3D image registration has not been investigated. We have compared the registration performance of seven optimization methods in combination with three similarity measures: gradient difference, gradient correlation, and pattern intensity. Optimization methods included in this study were: regular step gradient descent, Nelder-Mead, Powell-Brent, Quasi-Newton, nonlinear conjugate gradient, simultaneous perturbation stochastic approximation, and evolution strategy. Registration experiments were performed on multiple patient data sets that were obtained during cerebral interventions. Various component combinations were evaluated on registration accuracy, capture range, and registration time. The results showed that for the same similarity measure, different registration accuracies and capture ranges were obtained when different optimization methods were used. For gradient difference, largest capture ranges were obtained with Powell-Brent and simultaneous perturbation stochastic approximation. Gradient correlation and pattern intensity had the largest capture ranges in combination with Powell-Brent, Nelder-Mead, nonlinear conjugate gradient, and Quasi-Newton. Average registration time, expressed in the number of DRRs required for convergence, was the lowest for Powell-Brent. Based on these results, we conclude that Powell-Brent is a reliable optimization method for intensity-based 2D-3D registration of x-ray images to CBCT

  20. Registration of 3D spectral OCT volumes combining ICP with a graph-based approach

    NASA Astrophysics Data System (ADS)

    Niemeijer, Meindert; Lee, Kyungmoo; Garvin, Mona K.; Abràmoff, Michael D.; Sonka, Milan

    2012-02-01

    The introduction of spectral Optical Coherence Tomography (OCT) scanners has enabled acquisition of high resolution, 3D cross-sectional volumetric images of the retina. 3D-OCT is used to detect and manage eye diseases such as glaucoma and age-related macular degeneration. To follow-up patients over time, image registration is a vital tool to enable more precise, quantitative comparison of disease states. In this work we present a 3D registrationmethod based on a two-step approach. In the first step we register both scans in the XY domain using an Iterative Closest Point (ICP) based algorithm. This algorithm is applied to vessel segmentations obtained from the projection image of each scan. The distance minimized in the ICP algorithm includes measurements of the vessel orientation and vessel width to allow for a more robust match. In the second step, a graph-based method is applied to find the optimal translation along the depth axis of the individual A-scans in the volume to match both scans. The cost image used to construct the graph is based on the mean squared error (MSE) between matching A-scans in both images at different translations. We have applied this method to the registration of Optic Nerve Head (ONH) centered 3D-OCT scans of the same patient. First, 10 3D-OCT scans of 5 eyes with glaucoma imaged in vivo were registered for a qualitative evaluation of the algorithm performance. Then, 17 OCT data set pairs of 17 eyes with known deformation were used for quantitative assessment of the method's robustness.

  1. Framework for quantitative evaluation of 3D vessel segmentation approaches using vascular phantoms in conjunction with 3D landmark localization and registration

    NASA Astrophysics Data System (ADS)

    Wörz, Stefan; Hoegen, Philipp; Liao, Wei; Müller-Eschner, Matthias; Kauczor, Hans-Ulrich; von Tengg-Kobligk, Hendrik; Rohr, Karl

    2016-03-01

    We introduce a framework for quantitative evaluation of 3D vessel segmentation approaches using vascular phantoms. Phantoms are designed using a CAD system and created with a 3D printer, and comprise realistic shapes including branches and pathologies such as abdominal aortic aneurysms (AAA). To transfer ground truth information to the 3D image coordinate system, we use a landmark-based registration scheme utilizing fiducial markers integrated in the phantom design. For accurate 3D localization of the markers we developed a novel 3D parametric intensity model that is directly fitted to the markers in the images. We also performed a quantitative evaluation of different vessel segmentation approaches for a phantom of an AAA.

  2. Elastic registration using 3D ChainMail: application to virtual colonoscopy

    NASA Astrophysics Data System (ADS)

    Castro-Pareja, Carlos R.; Daly, Barry; Shekhar, Raj

    2006-03-01

    We present an elastic registration algorithm based on local deformations modeled using cubic B-splines and controlled using 3D ChainMail. Our algorithm eliminates the appearance of folding artifacts and allows local rigidity and compressibility control independent of the image similarity metric being used. 3D ChainMail propagates large internal deformations between neighboring B-Spline control points, thereby preserving the topology of the transformed image without requiring the addition of penalty terms based on rigidity of the transformation field to the equation used to maximize image similarity. A novel application to virtual colonoscopy is presented where the algorithm is used to significantly improve cross-localization between colon locations in prone and supine CT images.

  3. Evaluation of 3D imaging.

    PubMed

    Vannier, M W

    2000-10-01

    Interactive computer-based simulation is gaining acceptance for craniofacial surgical planning. Subjective visualization without objective measurement capability, however, severely limits the value of simulation since spatial accuracy must be maintained. This study investigated the error sources involved in one method of surgical simulation evaluation. Linear and angular measurement errors were found to be within +/- 1 mm and 1 degree. Surface match of scanned objects was slightly less accurate, with errors up to 3 voxels and 4 degrees, and Boolean subtraction methods were 93 to 99% accurate. Once validated, these testing methods were applied to objectively compare craniofacial surgical simulations to post-operative outcomes, and verified that the form of simulation used in this study yields accurate depictions of surgical outcome. However, to fully evaluate surgical simulation, future work is still required to test the new methods in sufficient numbers of patients to achieve statistically significant results. Once completely validated, simulation cannot only be used in pre-operative surgical planning, but also as a post-operative descriptor of surgical and traumatic physical changes. Validated image comparison methods can also show discrepancy of surgical outcome to surgical plan, thus allowing evaluation of surgical technique. PMID:11098409

  4. Intensity-based femoral atlas 2D/3D registration using Levenberg-Marquardt optimisation

    NASA Astrophysics Data System (ADS)

    Klima, Ondrej; Kleparnik, Petr; Spanel, Michal; Zemcik, Pavel

    2016-03-01

    The reconstruction of a patient-specific 3D anatomy is the crucial step in the computer-aided preoperative planning based on plain X-ray images. In this paper, we propose a robust and fast reconstruction methods based on fitting the statistical shape and intensity model of a femoral bone onto a pair of calibrated X-ray images. We formulate the registration as a non-linear least squares problem, allowing for the involvement of Levenberg-Marquardt optimisation. The proposed methods have been tested on a set of 96 virtual X-ray images. The reconstruction accuracy was evaluated using the symmetric Hausdorff distance between reconstructed and ground-truth bones. The accuracy of the intensity-based method reached 1.18 +/- 1.57mm on average, the registration took 8.76 seconds on average.

  5. 3D holoscopic video imaging system

    NASA Astrophysics Data System (ADS)

    Steurer, Johannes H.; Pesch, Matthias; Hahne, Christopher

    2012-03-01

    Since many years, integral imaging has been discussed as a technique to overcome the limitations of standard still photography imaging systems where a three-dimensional scene is irrevocably projected onto two dimensions. With the success of 3D stereoscopic movies, a huge interest in capturing three-dimensional motion picture scenes has been generated. In this paper, we present a test bench integral imaging camera system aiming to tailor the methods of light field imaging towards capturing integral 3D motion picture content. We estimate the hardware requirements needed to generate high quality 3D holoscopic images and show a prototype camera setup that allows us to study these requirements using existing technology. The necessary steps that are involved in the calibration of the system as well as the technique of generating human readable holoscopic images from the recorded data are discussed.

  6. Intraoperative patient registration using volumetric true 3D ultrasound without fiducials

    PubMed Central

    Ji, Songbai; Roberts, David W.; Hartov, Alex; Paulsen, Keith D.

    2012-01-01

    Purpose: Accurate patient registration is crucial for effective image-guidance in open cranial surgery. Typically, it is accomplished by matching skin-affixed fiducials manually identified in the operating room (OR) with their counterparts in the preoperative images, which not only consumes OR time and personnel resources but also relies on the presence (and subsequent fixation) of the fiducials during the preoperative scans (until the procedure begins). In this study, the authors present a completely automatic, volumetric image-based patient registration technique that does not rely on fiducials by registering tracked (true) 3D ultrasound (3DUS) directly with preoperative magnetic resonance (MR) images. Methods: Multistart registrations between binary 3DUS and MR volumes were first executed to generate an initial starting point without incorporating prior information on the US transducer contact point location or orientation for subsequent registration between grayscale 3DUS and MR via maximization of either mutual information (MI) or correlation ratio (CR). Patient registration was then computed through concatenation of spatial transformations. Results: In ten (N = 10) patient cases, an average fiducial (marker) distance error (FDE) of 5.0 mm and 4.3 mm was achieved using MI or CR registration (FDE was smaller with CR vs MI in eight of ten cases), which are comparable to values reported for typical fiducial- or surface-based patient registrations. The translational and rotational capture ranges were found to be 24.0 mm and 27.0° for binary registrations (up to 32.8 mm and 36.4°), 12.2 mm and 25.6° for MI registrations (up to 18.3 mm and 34.4°), and 22.6 mm and 40.8° for CR registrations (up to 48.5 mm and 65.6°), respectively. The execution time to complete a patient registration was 12–15 min with parallel processing, which can be significantly reduced by confining the 3DUS transducer location to the center of craniotomy in MR before registration (an

  7. Nonlaser-based 3D surface imaging

    SciTech Connect

    Lu, Shin-yee; Johnson, R.K.; Sherwood, R.J.

    1994-11-15

    3D surface imaging refers to methods that generate a 3D surface representation of objects of a scene under viewing. Laser-based 3D surface imaging systems are commonly used in manufacturing, robotics and biomedical research. Although laser-based systems provide satisfactory solutions for most applications, there are situations where non laser-based approaches are preferred. The issues that make alternative methods sometimes more attractive are: (1) real-time data capturing, (2) eye-safety, (3) portability, and (4) work distance. The focus of this presentation is on generating a 3D surface from multiple 2D projected images using CCD cameras, without a laser light source. Two methods are presented: stereo vision and depth-from-focus. Their applications are described.

  8. 3D Mandibular Superimposition: Comparison of Regions of Reference for Voxel-Based Registration

    PubMed Central

    Ruellas, Antonio Carlos de Oliveira; Yatabe, Marilia Sayako; Souki, Bernardo Quiroga; Benavides, Erika; Nguyen, Tung; Luiz, Ronir Raggio; Franchi, Lorenzo; Cevidanes, Lucia Helena Soares

    2016-01-01

    Introduction The aim was to evaluate three regions of reference (Björk, Modified Björk and mandibular Body) for mandibular registration testing them in a patients’ CBCT sample. Methods Mandibular 3D volumetric label maps were built from CBCTs taken before (T1) and after treatment (T2) in a sample of 16 growing subjects and labeled with eight landmarks. Registrations of T1 and T2 images relative to the different regions of reference were performed, and 3D surface models were generated. Seven mandibular dimensions were measured separately for each time-point (T1 and T2) in relation to a stable reference structure (lingual cortical of symphysis), and the T2-T1 differences were calculated. These differences were compared to differences measured between the superimposed T2 (generated from different regions of reference: Björk, Modified Björk and Mandibular Body) over T1 surface models. ICC and the Bland-Altman method tested the agreement of the changes obtained by nonsuperimposition measurements from the patients’ sample, and changes between the overlapped surfaces after registration using the different regions of reference. Results The Björk region of reference (or mask) did work properly only in 2 of 16 patients. Evaluating the two other masks (Modified Björk and Mandibular body) on patients’ scans registration, the concordance and agreement of the changes obtained from superimpositions (registered T2 over T1) compared to results obtained from non superimposed T1 and T2 separately, indicated that Mandibular Body mask displayed more consistent results. Conclusions The mandibular body mask (mandible without teeth, alveolar bone, rami and condyles) is a reliable reference for 3D regional registration. PMID:27336366

  9. Image registration by parts

    NASA Technical Reports Server (NTRS)

    Chalermwat, Prachya; El-Ghazawi, Tarek; LeMoigne, Jacqueline

    1997-01-01

    In spite of the large number of different image registration techniques, most of these techniques use the correlation operation to match spatial image characteristics. Correlation is known to be one of the most computationally intensive operations and its computational needs grow rapidly with the increase in the image sizes. In this article, we show that, in many cases, it might be sufficient to determine image transformations by considering only one or several parts of the image rather than the entire image, which could result in substantial computational savings. This paper introduces the concept of registration by parts and investigates its viability. It describes alternative techniques for such image registration by parts and presents early empirical results that address the underlying trade-offs.

  10. Miniaturized 3D microscope imaging system

    NASA Astrophysics Data System (ADS)

    Lan, Yung-Sung; Chang, Chir-Weei; Sung, Hsin-Yueh; Wang, Yen-Chang; Chang, Cheng-Yi

    2015-05-01

    We designed and assembled a portable 3-D miniature microscopic image system with the size of 35x35x105 mm3 . By integrating a microlens array (MLA) into the optical train of a handheld microscope, the biological specimen's image will be captured for ease of use in a single shot. With the light field raw data and program, the focal plane can be changed digitally and the 3-D image can be reconstructed after the image was taken. To localize an object in a 3-D volume, an automated data analysis algorithm to precisely distinguish profundity position is needed. The ability to create focal stacks from a single image allows moving or specimens to be recorded. Applying light field microscope algorithm to these focal stacks, a set of cross sections will be produced, which can be visualized using 3-D rendering. Furthermore, we have developed a series of design rules in order to enhance the pixel using efficiency and reduce the crosstalk between each microlens for obtain good image quality. In this paper, we demonstrate a handheld light field microscope (HLFM) to distinguish two different color fluorescence particles separated by a cover glass in a 600um range, show its focal stacks, and 3-D position.

  11. Structured light field 3D imaging.

    PubMed

    Cai, Zewei; Liu, Xiaoli; Peng, Xiang; Yin, Yongkai; Li, Ameng; Wu, Jiachen; Gao, Bruce Z

    2016-09-01

    In this paper, we propose a method by means of light field imaging under structured illumination to deal with high dynamic range 3D imaging. Fringe patterns are projected onto a scene and modulated by the scene depth then a structured light field is detected using light field recording devices. The structured light field contains information about ray direction and phase-encoded depth, via which the scene depth can be estimated from different directions. The multidirectional depth estimation can achieve high dynamic 3D imaging effectively. We analyzed and derived the phase-depth mapping in the structured light field and then proposed a flexible ray-based calibration approach to determine the independent mapping coefficients for each ray. Experimental results demonstrated the validity of the proposed method to perform high-quality 3D imaging for highly and lowly reflective surfaces. PMID:27607639

  12. 3D EIT image reconstruction with GREIT.

    PubMed

    Grychtol, Bartłomiej; Müller, Beat; Adler, Andy

    2016-06-01

    Most applications of thoracic EIT use a single plane of electrodes on the chest from which a transverse image 'slice' is calculated. However, interpretation of EIT images is made difficult by the large region above and below the electrode plane to which EIT is sensitive. Volumetric EIT images using two (or more) electrode planes should help compensate, but are little used currently. The Graz consensus reconstruction algorithm for EIT (GREIT) has become popular in lung EIT. One shortcoming of the original formulation of GREIT is its restriction to reconstruction onto a 2D planar image. We present an extension of the GREIT algorithm to 3D and develop open-source tools to evaluate its performance as a function of the choice of stimulation and measurement pattern. Results show 3D GREIT using two electrode layers has significantly more uniform sensitivity profiles through the chest region. Overall, the advantages of 3D EIT are compelling. PMID:27203184

  13. The application of iterative closest point (ICP) registration to improve 3D terrain mapping estimates using the flash 3D ladar system

    NASA Astrophysics Data System (ADS)

    Woods, Jack; Armstrong, Ernest E.; Armbruster, Walter; Richmond, Richard

    2010-04-01

    The primary purpose of this research was to develop an effective means of creating a 3D terrain map image (point-cloud) in GPS denied regions from a sequence of co-bore sighted visible and 3D LIDAR images. Both the visible and 3D LADAR cameras were hard mounted to a vehicle. The vehicle was then driven around the streets of an abandoned village used as a training facility by the German Army and imagery was collected. The visible and 3D LADAR images were then fused and 3D registration performed using a variation of the Iterative Closest Point (ICP) algorithm. The ICP algorithm is widely used for various spatial and geometric alignment of 3D imagery producing a set of rotation and translation transformations between two 3D images. ICP rotation and translation information obtain from registering the fused visible and 3D LADAR imagery was then used to calculate the x-y plane, range and intensity (xyzi) coordinates of various structures (building, vehicles, trees etc.) along the driven path. The xyzi coordinates information was then combined to create a 3D terrain map (point-cloud). In this paper, we describe the development and application of 3D imaging techniques (most specifically the ICP algorithm) used to improve spatial, range and intensity estimates of imagery collected during urban terrain mapping using a co-bore sighted, commercially available digital video camera with focal plan of 640×480 pixels and a 3D FLASH LADAR. Various representations of the reconstructed point-clouds for the drive through data will also be presented.

  14. Contrast-Based 3D/2D Registration of the Left Atrium: Fast versus Consistent

    PubMed Central

    Kowalewski, Christopher; Kurzidim, Klaus; Strobel, Norbert; Hornegger, Joachim

    2016-01-01

    For augmented fluoroscopy during cardiac ablation, a preoperatively acquired 3D model of a patient's left atrium (LA) can be registered to X-ray images recorded during a contrast agent (CA) injection. An automatic registration method that works also for small amounts of CA is desired. We propose two similarity measures: The first focuses on edges of the patient anatomy. The second computes a contrast agent distribution estimate (CADE) inside the 3D model and rates its consistency with the CA as seen in biplane fluoroscopic images. Moreover, temporal filtering on the obtained registration results of a sequence is applied using a Markov chain framework. Evaluation was performed on 11 well-contrasted clinical angiographic sequences and 10 additional sequences with less CA. For well-contrasted sequences, the error for all 73 frames was 7.9 ± 6.3 mm and it dropped to 4.6 ± 4.0 mm when registering to an automatically selected, well enhanced frame in each sequence. Temporal filtering reduced the error for all frames from 7.9 ± 6.3 mm to 5.7 ± 4.6 mm. The error was typically higher if less CA was used. A combination of both similarity measures outperforms a previously proposed similarity measure. The mean accuracy for well contrasted sequences is in the range of other proposed manual registration methods. PMID:27051412

  15. Contrast-Based 3D/2D Registration of the Left Atrium: Fast versus Consistent.

    PubMed

    Hoffmann, Matthias; Kowalewski, Christopher; Maier, Andreas; Kurzidim, Klaus; Strobel, Norbert; Hornegger, Joachim

    2016-01-01

    For augmented fluoroscopy during cardiac ablation, a preoperatively acquired 3D model of a patient's left atrium (LA) can be registered to X-ray images recorded during a contrast agent (CA) injection. An automatic registration method that works also for small amounts of CA is desired. We propose two similarity measures: The first focuses on edges of the patient anatomy. The second computes a contrast agent distribution estimate (CADE) inside the 3D model and rates its consistency with the CA as seen in biplane fluoroscopic images. Moreover, temporal filtering on the obtained registration results of a sequence is applied using a Markov chain framework. Evaluation was performed on 11 well-contrasted clinical angiographic sequences and 10 additional sequences with less CA. For well-contrasted sequences, the error for all 73 frames was 7.9 ± 6.3 mm and it dropped to 4.6 ± 4.0 mm when registering to an automatically selected, well enhanced frame in each sequence. Temporal filtering reduced the error for all frames from 7.9 ± 6.3 mm to 5.7 ± 4.6 mm. The error was typically higher if less CA was used. A combination of both similarity measures outperforms a previously proposed similarity measure. The mean accuracy for well contrasted sequences is in the range of other proposed manual registration methods. PMID:27051412

  16. Efficient implementation of the rank correlation merit function for 2D/3D registration.

    PubMed

    Figl, M; Bloch, C; Gendrin, C; Weber, C; Pawiro, S A; Hummel, J; Markelj, P; Pernus, F; Bergmann, H; Birkfellner, W

    2010-10-01

    A growing number of clinical applications using 2D/3D registration have been presented recently. Usually, a digitally reconstructed radiograph is compared iteratively to an x-ray image of the known projection geometry until a match is achieved, thus providing six degrees of freedom of rigid motion which can be used for patient setup in image-guided radiation therapy or computer-assisted interventions. Recently, stochastic rank correlation, a merit function based on Spearman's rank correlation coefficient, was presented as a merit function especially suitable for 2D/3D registration. The advantage of this measure is its robustness against variations in image histogram content and its wide convergence range. The considerable computational expense of computing an ordered rank list is avoided here by comparing randomly chosen subsets of the DRR and reference x-ray. In this work, we show that it is possible to omit the sorting step and to compute the rank correlation coefficient of the full image content as fast as conventional merit functions. Our evaluation of a well-calibrated cadaver phantom also confirms that rank correlation-type merit functions give the most accurate results if large differences in the histogram content for the DRR and the x-ray image are present. PMID:20844334

  17. Personalized x-ray reconstruction of the proximal femur via a non-rigid 2D-3D registration

    NASA Astrophysics Data System (ADS)

    Yu, Weimin; Zysset, Philippe; Zheng, Guoyan

    2015-03-01

    In this paper we present a new approach for a personalized X-ray reconstruction of the proximal femur via a non-rigid registration of a 3D volumetric template to 2D calibrated C-arm images. The 2D-3D registration is done with a hierarchical two-stage strategy: the global scaled rigid registration stage followed by a regularized deformable b-spline registration stage. In both stages, a set of control points with uniform spacing are placed over the domain of the 3D volumetric template and the registrations are driven by computing updated positions of these control points, which then allows to accurately register the 3D volumetric template to the reference space of the C-arm images. Comprehensive experiments on simulated images, on images of cadaveric femurs and on clinical datasets are designed and conducted to evaluate the performance of the proposed approach. Quantitative and qualitative evaluation results are given, which demonstrate the efficacy of the present approach.

  18. Automatic digital image registration

    NASA Technical Reports Server (NTRS)

    Goshtasby, A.; Jain, A. K.; Enslin, W. R.

    1982-01-01

    This paper introduces a general procedure for automatic registration of two images which may have translational, rotational, and scaling differences. This procedure involves (1) segmentation of the images, (2) isolation of dominant objects from the images, (3) determination of corresponding objects in the two images, and (4) estimation of transformation parameters using the center of gravities of objects as control points. An example is given which uses this technique to register two images which have translational, rotational, and scaling differences.

  19. Evaluation of feature-based 3-d registration of probabilistic volumetric scenes

    NASA Astrophysics Data System (ADS)

    Restrepo, Maria I.; Ulusoy, Ali O.; Mundy, Joseph L.

    2014-12-01

    Automatic estimation of the world surfaces from aerial images has seen much attention and progress in recent years. Among current modeling technologies, probabilistic volumetric models (PVMs) have evolved as an alternative representation that can learn geometry and appearance in a dense and probabilistic manner. Recent progress, in terms of storage and speed, achieved in the area of volumetric modeling, opens the opportunity to develop new frameworks that make use of the PVM to pursue the ultimate goal of creating an entire map of the earth, where one can reason about the semantics and dynamics of the 3-d world. Aligning 3-d models collected at different time-instances constitutes an important step for successful fusion of large spatio-temporal information. This paper evaluates how effectively probabilistic volumetric models can be aligned using robust feature-matching techniques, while considering different scenarios that reflect the kind of variability observed across aerial video collections from different time instances. More precisely, this work investigates variability in terms of discretization, resolution and sampling density, errors in the camera orientation, and changes in illumination and geographic characteristics. All results are given for large-scale, outdoor sites. In order to facilitate the comparison of the registration performance of PVMs to that of other 3-d reconstruction techniques, the registration pipeline is also carried out using Patch-based Multi-View Stereo (PMVS) algorithm. Registration performance is similar for scenes that have favorable geometry and the appearance characteristics necessary for high quality reconstruction. In scenes containing trees, such as a park, or many buildings, such as a city center, registration performance is significantly more accurate when using the PVM.

  20. Automatic registration of optical imagery with 3d lidar data using local combined mutual information

    NASA Astrophysics Data System (ADS)

    Parmehr, E. G.; Fraser, C. S.; Zhang, C.; Leach, J.

    2013-10-01

    Automatic registration of multi-sensor data is a basic step in data fusion for photogrammetric and remote sensing applications. The effectiveness of intensity-based methods such as Mutual Information (MI) for automated registration of multi-sensor image has been previously reported for medical and remote sensing applications. In this paper, a new multivariable MI approach that exploits complementary information of inherently registered LiDAR DSM and intensity data to improve the robustness of registering optical imagery and LiDAR point cloud, is presented. LiDAR DSM and intensity information has been utilised in measuring the similarity of LiDAR and optical imagery via the Combined MI. An effective histogramming technique is adopted to facilitate estimation of a 3D probability density function (pdf). In addition, a local similarity measure is introduced to decrease the complexity of optimisation at higher dimensions and computation cost. Therefore, the reliability of registration is improved due to the use of redundant observations of similarity. The performance of the proposed method for registration of satellite and aerial images with LiDAR data in urban and rural areas is experimentally evaluated and the results obtained are discussed.

  1. ICER-3D Hyperspectral Image Compression Software

    NASA Technical Reports Server (NTRS)

    Xie, Hua; Kiely, Aaron; Klimesh, matthew; Aranki, Nazeeh

    2010-01-01

    Software has been developed to implement the ICER-3D algorithm. ICER-3D effects progressive, three-dimensional (3D), wavelet-based compression of hyperspectral images. If a compressed data stream is truncated, the progressive nature of the algorithm enables reconstruction of hyperspectral data at fidelity commensurate with the given data volume. The ICER-3D software is capable of providing either lossless or lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The compression algorithm, which was derived from the ICER image compression algorithm, includes wavelet-transform, context-modeling, and entropy coding subalgorithms. The 3D wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of sets of hyperspectral image data, while facilitating elimination of spectral ringing artifacts, using a technique summarized in "Improving 3D Wavelet-Based Compression of Spectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. Correlation is further exploited by a context-modeling subalgorithm, which exploits spectral dependencies in the wavelet-transformed hyperspectral data, using an algorithm that is summarized in "Context Modeler for Wavelet Compression of Hyperspectral Images" (NPO-43239), which follows this article. An important feature of ICER-3D is a scheme for limiting the adverse effects of loss of data during transmission. In this scheme, as in the similar scheme used by ICER, the spatial-frequency domain is partitioned into rectangular error-containment regions. In ICER-3D, the partitions extend through all the wavelength bands. The data in each partition are compressed independently of those in the other partitions, so that loss or corruption of data from any partition does not affect the other partitions. Furthermore, because compression is progressive within each partition, when data are lost, any data from that partition received

  2. Fast DRR generation for 2D to 3D registration on GPUs

    SciTech Connect

    Tornai, Gabor Janos; Cserey, Gyoergy

    2012-08-15

    Purpose: The generation of digitally reconstructed radiographs (DRRs) is the most time consuming step on the CPU in intensity based two-dimensional x-ray to three-dimensional (CT or 3D rotational x-ray) medical image registration, which has application in several image guided interventions. This work presents optimized DRR rendering on graphical processor units (GPUs) and compares performance achievable on four commercially available devices. Methods: A ray-cast based DRR rendering was implemented for a 512 Multiplication-Sign 512 Multiplication-Sign 72 CT volume. The block size parameter was optimized for four different GPUs for a region of interest (ROI) of 400 Multiplication-Sign 225 pixels with different sampling ratios (1.1%-9.1% and 100%). Performance was statistically evaluated and compared for the four GPUs. The method and the block size dependence were validated on the latest GPU for several parameter settings with a public gold standard dataset (512 Multiplication-Sign 512 Multiplication-Sign 825 CT) for registration purposes. Results: Depending on the GPU, the full ROI is rendered in 2.7-5.2 ms. If sampling ratio of 1.1%-9.1% is applied, execution time is in the range of 0.3-7.3 ms. On all GPUs, the mean of the execution time increased linearly with respect to the number of pixels if sampling was used. Conclusions: The presented results outperform other results from the literature. This indicates that automatic 2D to 3D registration, which typically requires a couple of hundred DRR renderings to converge, can be performed quasi on-line, in less than a second or depending on the application and hardware in less than a couple of seconds. Accordingly, a whole new field of applications is opened for image guided interventions, where the registration is continuously performed to match the real-time x-ray.

  3. Acquisition and applications of 3D images

    NASA Astrophysics Data System (ADS)

    Sterian, Paul; Mocanu, Elena

    2007-08-01

    The moiré fringes method and their analysis up to medical and entertainment applications are discussed in this paper. We describe the procedure of capturing 3D images with an Inspeck Camera that is a real-time 3D shape acquisition system based on structured light techniques. The method is a high-resolution one. After processing the images, using computer, we can use the data for creating laser fashionable objects by engraving them with a Q-switched Nd:YAG. In medical field we mention the plastic surgery and the replacement of X-Ray especially in pediatric use.

  4. Semiautomated Multimodal Breast Image Registration

    PubMed Central

    Curtis, Charlotte; Frayne, Richard; Fear, Elise

    2012-01-01

    Consideration of information from multiple modalities has been shown to have increased diagnostic power in breast imaging. As a result, new techniques such as microwave imaging continue to be developed. Interpreting these novel image modalities is a challenge, requiring comparison to established techniques such as the gold standard X-ray mammography. However, due to the highly deformable nature of breast tissues, comparison of 3D and 2D modalities is a challenge. To enable this comparison, a registration technique was developed to map features from 2D mammograms to locations in the 3D image space. This technique was developed and tested using magnetic resonance (MR) images as a reference 3D modality, as MR breast imaging is an established technique in clinical practice. The algorithm was validated using a numerical phantom then successfully tested on twenty-four image pairs. Dice's coefficient was used to measure the external goodness of fit, resulting in an excellent overall average of 0.94. Internal agreement was evaluated by examining internal features in consultation with a radiologist, and subjective assessment concludes that reasonable alignment was achieved. PMID:22481910

  5. 3D camera tracking from disparity images

    NASA Astrophysics Data System (ADS)

    Kim, Kiyoung; Woo, Woontack

    2005-07-01

    In this paper, we propose a robust camera tracking method that uses disparity images computed from known parameters of 3D camera and multiple epipolar constraints. We assume that baselines between lenses in 3D camera and intrinsic parameters are known. The proposed method reduces camera motion uncertainty encountered during camera tracking. Specifically, we first obtain corresponding feature points between initial lenses using normalized correlation method. In conjunction with matching features, we get disparity images. When the camera moves, the corresponding feature points, obtained from each lens of 3D camera, are robustly tracked via Kanade-Lukas-Tomasi (KLT) tracking algorithm. Secondly, relative pose parameters of each lens are calculated via Essential matrices. Essential matrices are computed from Fundamental matrix calculated using normalized 8-point algorithm with RANSAC scheme. Then, we determine scale factor of translation matrix by d-motion. This is required because the camera motion obtained from Essential matrix is up to scale. Finally, we optimize camera motion using multiple epipolar constraints between lenses and d-motion constraints computed from disparity images. The proposed method can be widely adopted in Augmented Reality (AR) applications, 3D reconstruction using 3D camera, and fine surveillance systems which not only need depth information, but also camera motion parameters in real-time.

  6. High definition 3D ultrasound imaging.

    PubMed

    Morimoto, A K; Krumm, J C; Kozlowski, D M; Kuhlmann, J L; Wilson, C; Little, C; Dickey, F M; Kwok, K S; Rogers, B; Walsh, N

    1997-01-01

    We have demonstrated high definition and improved resolution using a novel scanning system integrated with a commercial ultrasound machine. The result is a volumetric 3D ultrasound data set that can be visualized using standard techniques. Unlike other 3D ultrasound images, image quality is improved from standard 2D data. Image definition and bandwidth is improved using patent pending techniques. The system can be used to image patients or wounded soldiers for general imaging of anatomy such as abdominal organs, extremities, and the neck. Although the risks associated with x-ray carcinogenesis are relatively low at diagnostic dose levels, concerns remain for individuals in high risk categories. In addition, cost and portability of CT and MRI machines can be prohibitive. In comparison, ultrasound can provide portable, low-cost, non-ionizing imaging. Previous clinical trials comparing ultrasound to CT were used to demonstrate qualitative and quantitative improvements of ultrasound using the Sandia technologies. Transverse leg images demonstrated much higher clarity and lower noise than is seen in traditional ultrasound images. An x-ray CT scan was provided of the same cross-section for comparison. The results of our most recent trials demonstrate the advantages of 3D ultrasound and motion compensation compared with 2D ultrasound. Metal objects can also be observed within the anatomy. PMID:10168958

  7. Walker Ranch 3D seismic images

    DOE Data Explorer

    Robert J. Mellors

    2016-03-01

    Amplitude images (both vertical and depth slices) extracted from 3D seismic reflection survey over area of Walker Ranch area (adjacent to Raft River). Crossline spacing of 660 feet and inline of 165 feet using a Vibroseis source. Processing included depth migration. Micro-earthquake hypocenters on images. Stratigraphic information and nearby well tracks added to images. Images are embedded in a Microsoft Word document with additional information. Exact location and depth restricted for proprietary reasons. Data collection and processing funded by Agua Caliente. Original data remains property of Agua Caliente.

  8. Stereotactic mammography imaging combined with 3D US imaging for image guided breast biopsy

    SciTech Connect

    Surry, K. J. M.; Mills, G. R.; Bevan, K.; Downey, D. B.; Fenster, A.

    2007-11-15

    Stereotactic X-ray mammography (SM) and ultrasound (US) guidance are both commonly used for breast biopsy. While SM provides three-dimensional (3D) targeting information and US provides real-time guidance, both have limitations. SM is a long and uncomfortable procedure and the US guided procedure is inherently two dimensional (2D), requiring a skilled physician for both safety and accuracy. The authors developed a 3D US-guided biopsy system to be integrated with, and to supplement SM imaging. Their goal is to be able to biopsy a larger percentage of suspicious masses using US, by clarifying ambiguous structures with SM imaging. Features from SM and US guided biopsy were combined, including breast stabilization, a confined needle trajectory, and dual modality imaging. The 3D US guided biopsy system uses a 7.5 MHz breast probe and is mounted on an upright SM machine for preprocedural imaging. Intraprocedural targeting and guidance was achieved with real-time 2D and near real-time 3D US imaging. Postbiopsy 3D US imaging allowed for confirmation that the needle was penetrating the target. The authors evaluated 3D US-guided biopsy accuracy of their system using test phantoms. To use mammographic imaging information, they registered the SM and 3D US coordinate systems. The 3D positions of targets identified in the SM images were determined with a target localization error (TLE) of 0.49 mm. The z component (x-ray tube to image) of the TLE dominated with a TLE{sub z} of 0.47 mm. The SM system was then registered to 3D US, with a fiducial registration error (FRE) and target registration error (TRE) of 0.82 and 0.92 mm, respectively. Analysis of the FRE and TRE components showed that these errors were dominated by inaccuracies in the z component with a FRE{sub z} of 0.76 mm and a TRE{sub z} of 0.85 mm. A stereotactic mammography and 3D US guided breast biopsy system should include breast compression for stability and safety and dual modality imaging for target localization

  9. Cross modality registration of video and magnetic tracker data for 3D appearance and structure modeling

    NASA Astrophysics Data System (ADS)

    Sargent, Dusty; Chen, Chao-I.; Wang, Yuan-Fang

    2010-02-01

    The paper reports a fully-automated, cross-modality sensor data registration scheme between video and magnetic tracker data. This registration scheme is intended for use in computerized imaging systems to model the appearance, structure, and dimension of human anatomy in three dimensions (3D) from endoscopic videos, particularly colonoscopic videos, for cancer research and clinical practices. The proposed cross-modality calibration procedure operates this way: Before a colonoscopic procedure, the surgeon inserts a magnetic tracker into the working channel of the endoscope or otherwise fixes the tracker's position on the scope. The surgeon then maneuvers the scope-tracker assembly to view a checkerboard calibration pattern from a few different viewpoints for a few seconds. The calibration procedure is then completed, and the relative pose (translation and rotation) between the reference frames of the magnetic tracker and the scope is determined. During the colonoscopic procedure, the readings from the magnetic tracker are used to automatically deduce the pose (both position and orientation) of the scope's reference frame over time, without complicated image analysis. Knowing the scope movement over time then allows us to infer the 3D appearance and structure of the organs and tissues in the scene. While there are other well-established mechanisms for inferring the movement of the camera (scope) from images, they are often sensitive to mistakes in image analysis, error accumulation, and structure deformation. The proposed method using a magnetic tracker to establish the camera motion parameters thus provides a robust and efficient alternative for 3D model construction. Furthermore, the calibration procedure does not require special training nor use expensive calibration equipment (except for a camera calibration pattern-a checkerboard pattern-that can be printed on any laser or inkjet printer).

  10. Backhoe 3D "gold standard" image

    NASA Astrophysics Data System (ADS)

    Gorham, LeRoy; Naidu, Kiranmai D.; Majumder, Uttam; Minardi, Michael A.

    2005-05-01

    ViSUAl-D (VIsual Sar Using ALl Dimensions), a 2004 DARPA/IXO seedling effort, is developing a capability for reliable high confidence ID from standoff ranges. Recent conflicts have demonstrated that the warfighter would greatly benefit from the ability to ID targets beyond visual and electro-optical ranges[1]. Forming optical-quality SAR images while exploiting full polarization, wide angles, and large bandwidth would be key evidence such a capability is achievable. Using data generated by the Xpatch EM scattering code, ViSUAl-D investigates all degrees of freedom available to the radar designer, including 6 GHz bandwidth, full polarization and angle sampling over 2π steradians (upper hemisphere), in order to produce a "literal" image or representation of the target. This effort includes the generation of a "Gold Standard" image that can be produced at X-band utilizing all available target data. This "Gold Standard" image of the backhoe will serve as a test bed for future more relevant military targets and their image development. The seedling team produced a public release data which was released at the 2004 SPIE conference, as well as a 3D "Gold Standard" backhoe image using a 3D image formation algorithm. This paper describes the full backhoe data set, the image formation algorithm, the visualization process and the resulting image.

  11. Compact camera for 3D position registration of cancer in radiation treatment

    NASA Astrophysics Data System (ADS)

    Wakayama, Toshitaka; Hiratsuka, Shun; Kamakura, Yoshihisa; Nakamura, Katsumasa; Yoshizawa, Toru

    2014-11-01

    Radiation treatments have been attracted many interests as one of revolutionary cancer therapies. Today, it is possible to treat cancers without any surgical operations. In the fields of the radiation treatments, it is important to regist the 3D position of the cancer inside the body precisely and instantaneously. To achieve 3D position registrations, we aim at developing a compact camera for 3D measurements. In this trial, we have developed a high-speed pattern projector based on the spatiotemporal conversion technique. In experiments, we show some experimental results for the 3D registrations.

  12. Metrological characterization of 3D imaging devices

    NASA Astrophysics Data System (ADS)

    Guidi, G.

    2013-04-01

    Manufacturers often express the performance of a 3D imaging device in various non-uniform ways for the lack of internationally recognized standard requirements for metrological parameters able to identify the capability of capturing a real scene. For this reason several national and international organizations in the last ten years have been developing protocols for verifying such performance. Ranging from VDI/VDE 2634, published by the Association of German Engineers and oriented to the world of mechanical 3D measurements (triangulation-based devices), to the ASTM technical committee E57, working also on laser systems based on direct range detection (TOF, Phase Shift, FM-CW, flash LADAR), this paper shows the state of the art about the characterization of active range devices, with special emphasis on measurement uncertainty, accuracy and resolution. Most of these protocols are based on special objects whose shape and size are certified with a known level of accuracy. By capturing the 3D shape of such objects with a range device, a comparison between the measured points and the theoretical shape they should represent is possible. The actual deviations can be directly analyzed or some derived parameters can be obtained (e.g. angles between planes, distances between barycenters of spheres rigidly connected, frequency domain parameters, etc.). This paper shows theoretical aspects and experimental results of some novel characterization methods applied to different categories of active 3D imaging devices based on both principles of triangulation and direct range detection.

  13. 3D MR imaging in real time

    NASA Astrophysics Data System (ADS)

    Guttman, Michael A.; McVeigh, Elliot R.

    2001-05-01

    A system has been developed to produce live 3D volume renderings from an MR scanner. Whereas real-time 2D MR imaging has been demonstrated by several groups, 3D volumes are currently rendered off-line to gain greater understanding of anatomical structures. For example, surgical planning is sometimes performed by viewing 2D images or 3D renderings from previously acquired image data. A disadvantage of this approach is misregistration which could occur if the anatomy changes due to normal muscle contractions or surgical manipulation. The ability to produce volume renderings in real-time and present them in the magnet room could eliminate this problem, and enable or benefit other types of interventional procedures. The system uses the data stream generated by a fast 2D multi- slice pulse sequence to update a volume rendering immediately after a new slice is available. We demonstrate some basic types of user interaction with the rendering during imaging at a rate of up to 20 frames per second.

  14. Known-component 3D-2D registration for quality assurance of spine surgery pedicle screw placement.

    PubMed

    Uneri, A; De Silva, T; Stayman, J W; Kleinszig, G; Vogt, S; Khanna, A J; Gokaslan, Z L; Wolinsky, J-P; Siewerdsen, J H

    2015-10-21

    A 3D-2D image registration method is presented that exploits knowledge of interventional devices (e.g. K-wires or spine screws-referred to as 'known components') to extend the functionality of intraoperative radiography/fluoroscopy by providing quantitative measurement and quality assurance (QA) of the surgical product. The known-component registration (KC-Reg) algorithm uses robust 3D-2D registration combined with 3D component models of surgical devices known to be present in intraoperative 2D radiographs. Component models were investigated that vary in fidelity from simple parametric models (e.g. approximation of a screw as a simple cylinder, referred to as 'parametrically-known' component [pKC] registration) to precise models based on device-specific CAD drawings (referred to as 'exactly-known' component [eKC] registration). 3D-2D registration from three intraoperative radiographs was solved using the covariance matrix adaptation evolution strategy (CMA-ES) to maximize image-gradient similarity, relating device placement relative to 3D preoperative CT of the patient. Spine phantom and cadaver studies were conducted to evaluate registration accuracy and demonstrate QA of the surgical product by verification of the type of devices delivered and conformance within the 'acceptance window' of the spinal pedicle. Pedicle screws were successfully registered to radiographs acquired from a mobile C-arm, providing TRE 1-4 mm and  <5° using simple parametric (pKC) models, further improved to  <1 mm and  <1° using eKC registration. Using advanced pKC models, screws that did not match the device models specified in the surgical plan were detected with an accuracy of  >99%. Visualization of registered devices relative to surgical planning and the pedicle acceptance window provided potentially valuable QA of the surgical product and reliable detection of pedicle screw breach. 3D-2D registration combined with 3D models of known surgical devices offers a

  15. Known-component 3D-2D registration for quality assurance of spine surgery pedicle screw placement

    NASA Astrophysics Data System (ADS)

    Uneri, A.; De Silva, T.; Stayman, J. W.; Kleinszig, G.; Vogt, S.; Khanna, A. J.; Gokaslan, Z. L.; Wolinsky, J.-P.; Siewerdsen, J. H.

    2015-10-01

    A 3D-2D image registration method is presented that exploits knowledge of interventional devices (e.g. K-wires or spine screws—referred to as ‘known components’) to extend the functionality of intraoperative radiography/fluoroscopy by providing quantitative measurement and quality assurance (QA) of the surgical product. The known-component registration (KC-Reg) algorithm uses robust 3D-2D registration combined with 3D component models of surgical devices known to be present in intraoperative 2D radiographs. Component models were investigated that vary in fidelity from simple parametric models (e.g. approximation of a screw as a simple cylinder, referred to as ‘parametrically-known’ component [pKC] registration) to precise models based on device-specific CAD drawings (referred to as ‘exactly-known’ component [eKC] registration). 3D-2D registration from three intraoperative radiographs was solved using the covariance matrix adaptation evolution strategy (CMA-ES) to maximize image-gradient similarity, relating device placement relative to 3D preoperative CT of the patient. Spine phantom and cadaver studies were conducted to evaluate registration accuracy and demonstrate QA of the surgical product by verification of the type of devices delivered and conformance within the ‘acceptance window’ of the spinal pedicle. Pedicle screws were successfully registered to radiographs acquired from a mobile C-arm, providing TRE 1-4 mm and  <5° using simple parametric (pKC) models, further improved to  <1 mm and  <1° using eKC registration. Using advanced pKC models, screws that did not match the device models specified in the surgical plan were detected with an accuracy of  >99%. Visualization of registered devices relative to surgical planning and the pedicle acceptance window provided potentially valuable QA of the surgical product and reliable detection of pedicle screw breach. 3D-2D registration combined with 3D models of known surgical

  16. Nonrigid image registration using an entropic similarity.

    PubMed

    Khader, Mohammed; Ben Hamza, A

    2011-09-01

    In this paper, we propose a nonrigid image registration technique by optimizing a generalized information-theoretic similarity measure using the quasi-Newton method as an optimization scheme and cubic B-splines for modeling the nonrigid deformation field between the fixed and moving 3-D image pairs. To achieve a compromise between the nonrigid registration accuracy and the associated computational cost, we implement a three-level hierarchical multiresolution approach such that the image resolution is increased in a coarse to fine fashion. Experimental results are provided to demonstrate the registration accuracy of our approach. The feasibility of the proposed method is demonstrated on a 3-D magnetic resonance data volume and also on clinically acquired 4-D CT image datasets. PMID:21690017

  17. Fusion of CTA and XA data using 3D centerline registration for plaque visualization during coronary intervention

    NASA Astrophysics Data System (ADS)

    Kaila, Gaurav; Kitslaar, Pieter; Tu, Shengxian; Penicka, Martin; Dijkstra, Jouke; Lelieveldt, Boudewijn

    2016-03-01

    Coronary Artery Disease (CAD) results in the buildup of plaque below the intima layer inside the vessel wall of the coronary arteries causing narrowing of the vessel and obstructing blood flow. Percutaneous coronary intervention (PCI) is usually done to enlarge the vessel lumen and regain back normal flow of blood to the heart. During PCI, X-ray imaging is done to assist guide wire movement through the vessels to the area of stenosis. While X-ray imaging allows for good lumen visualization, information on plaque type is unavailable. Also due to the projection nature of the X-ray imaging, additional drawbacks such as foreshortening and overlap of vessels limit the efficacy of the cardiac intervention. Reconstruction of 3D vessel geometry from biplane X-ray acquisitions helps to overcome some of these projection drawbacks. However, the plaque type information remains an issue. In contrast, imaging using computed tomography angiography (CTA) can provide us with information on both lumen and plaque type and allows us to generate a complete 3D coronary vessel tree unaffected by the foreshortening and overlap problems of the X-ray imaging. In this paper, we combine x-ray biplane images with CT angiography to visualize three plaque types (dense calcium, fibrous fatty and necrotic core) on x-ray images. 3D registration using three different registration methods is done between coronary centerlines available from x-ray images and from the CTA volume along with 3D plaque information available from CTA. We compare the different registration methods and evaluate their performance based on 3D root mean squared errors. Two methods are used to project this 3D information onto 2D plane of the x-ray biplane images. Validation of our approach is performed using artificial biplane x-ray datasets.

  18. Geomatics for precise 3D breast imaging.

    PubMed

    Alto, Hilary

    2005-02-01

    Canadian women have a one in nine chance of developing breast cancer during their lifetime. Mammography is the most common imaging technology used for breast cancer detection in its earliest stages through screening programs. Clusters of microcalcifications are primary indicators of breast cancer; the shape, size and number may be used to determine whether they are malignant or benign. However, overlapping images of calcifications on a mammogram hinder the classification of the shape and size of each calcification and a misdiagnosis may occur resulting in either an unnecessary biopsy being performed or a necessary biopsy not being performed. The introduction of 3D imaging techniques such as standard photogrammetry may increase the confidence of the radiologist when making his/her diagnosis. In this paper, traditional analytical photogrammetric techniques for the 3D mathematical reconstruction of microcalcifications are presented. The techniques are applied to a specially designed and constructed x-ray transparent Plexiglas phantom (control object). The phantom was embedded with 1.0 mm x-ray opaque lead pellets configured to represent overlapping microcalcifications. Control points on the phantom were determined by standard survey methods and hand measurements. X-ray films were obtained using a LORAD M-III mammography machine. The photogrammetric techniques of relative and absolute orientation were applied to the 2D mammographic films to analytically generate a 3D depth map with an overall accuracy of 0.6 mm. A Bundle Adjustment and the Direct Linear Transform were used to confirm the results. PMID:15649085

  19. 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.

  20. Image registration under symmetric conditions: novel approach

    NASA Astrophysics Data System (ADS)

    Duraisamy, Prakash; Yousef, Amr; Buckles, Bill; Jackson, Steve

    2015-03-01

    Registering the 2D images is one of the important pre-processing steps in many computer vision applications like 3D reconstruction, building panoramic images. Contemporary registration algorithm like SIFT (Scale Invariant Feature transform) was not quite success in registering the images under symmetric conditions and under poor illuminations using DoF (Difference of Gaussian) features. In this paper, we introduced a novel approach for registering the images under symmetric conditions.

  1. CT image registration in sinogram space

    SciTech Connect

    Mao Weihua; Li Tianfang; Wink, Nicole; Xing Lei

    2007-09-15

    Object displacement in a CT scan is generally reflected in CT projection data or sinogram. In this work, the direct relationship between object motion and the change of CT projection data (sinogram) is investigated and this knowledge is applied to create a novel algorithm for sinogram registration. Calculated and experimental results demonstrate that the registration technique works well for registering rigid 2D or 3D motion in parallel and fan beam samplings. Problem and solution for 3D sinogram-based registration of metallic fiducials are also addressed. Since the motion is registered before image reconstruction, the presented algorithm is particularly useful when registering images with metal or truncation artifacts. In addition, this algorithm is valuable for dealing with situations where only limited projection data are available, making it appealing for various applications in image guided radiation therapy.

  2. Validation of bone segmentation and improved 3-D registration using contour coherency in CT data.

    PubMed

    Wang, Liping Ingrid; Greenspan, Michael; Ellis, Randy

    2006-03-01

    A method is presented to validate the segmentation of computed tomography (CT) image sequences, and improve the accuracy and efficiency of the subsequent registration of the three-dimensional surfaces that are reconstructed from the segmented slices. The method compares the shapes of contours extracted from neighborhoods of slices in CT stacks of tibias. The bone is first segmented by an automatic segmentation technique, and the bone contour for each slice is parameterized as a one-dimensional function of normalized arc length versus inscribed angle. These functions are represented as vectors within a K-dimensional space comprising the first K amplitude coefficients of their Fourier Descriptors. The similarity or coherency of neighboring contours is measured by comparing statistical properties of their vector representations within this space. Experimentation has demonstrated this technique to be very effective at identifying low-coherency segmentations. Compared with experienced human operators, in a set of 23 CT stacks (1,633 slices), the method correctly detected 87.5% and 80% of the low-coherency and 97.7% and 95.5% of the high coherency segmentations, respectively from two different automatic segmentation techniques. Removal of the automatically detected low-coherency segmentations also significantly improved the accuracy and time efficiency of the registration of 3-D bone surface models. The registration error was reduced by over 500% (i.e., a factor of 5) and 280%, and the computational performance was improved by 540% and 791% for the two respective segmentation methods. PMID:16524088

  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. Pattern based 3D image Steganography

    NASA Astrophysics Data System (ADS)

    Thiyagarajan, P.; Natarajan, V.; Aghila, G.; Prasanna Venkatesan, V.; Anitha, R.

    2013-03-01

    This paper proposes a new high capacity Steganographic scheme using 3D geometric models. The novel algorithm re-triangulates a part of a triangle mesh and embeds the secret information into newly added position of triangle meshes. Up to nine bits of secret data can be embedded into vertices of a triangle without causing any changes in the visual quality and the geometric properties of the cover image. Experimental results show that the proposed algorithm is secure, with high capacity and low distortion rate. Our algorithm also resists against uniform affine transformations such as cropping, rotation and scaling. Also, the performance of the method is compared with other existing 3D Steganography algorithms. [Figure not available: see fulltext.

  5. Image registration with uncertainty analysis

    DOEpatents

    Simonson, Katherine M.

    2011-03-22

    In an image registration method, edges are detected in a first image and a second image. A percentage of edge pixels in a subset of the second image that are also edges in the first image shifted by a translation is calculated. A best registration point is calculated based on a maximum percentage of edges matched. In a predefined search region, all registration points other than the best registration point are identified that are not significantly worse than the best registration point according to a predetermined statistical criterion.

  6. Teat Morphology Characterization With 3D Imaging.

    PubMed

    Vesterinen, Heidi M; Corfe, Ian J; Sinkkonen, Ville; Iivanainen, Antti; Jernvall, Jukka; Laakkonen, Juha

    2015-07-01

    The objective of this study was to visualize, in a novel way, the morphological characteristics of bovine teats to gain a better understanding of the detailed teat morphology. We applied silicone casting and 3D digital imaging in order to obtain a more detailed image of the teat structures than that seen in previous studies. Teat samples from 65 dairy cows over 12 months of age were obtained from cows slaughtered at an abattoir. The teats were classified according to the teat condition scoring used in Finland and the lengths of the teat canals were measured. Silicone molds were made from the external teat surface surrounding the teat orifice and from the internal surface of the teat consisting of the papillary duct, Fürstenberg's rosette, and distal part of the teat cistern. The external and internal surface molds of 35 cows were scanned with a 3D laser scanner. The molds and the digital 3D models were used to evaluate internal and external teat surface morphology. A number of measurements were taken from the silicone molds. The 3D models reproduced the morphology of the teats accurately with high repeatability. Breed didn't correlate with the teat classification score. The rosette was found to have significant variation in its size and number of mucosal folds. The internal surface morphology of the rosette did not correlate with the external surface morphology of the teat implying that it is relatively independent of milking parameters that may impact the teat canal and the external surface of the teat. PMID:25382725

  7. Noninvasive CT to Iso-C3D registration for improved intraoperative visualization in computer assisted orthopedic surgery

    NASA Astrophysics Data System (ADS)

    Rudolph, Tobias; Ebert, Lars; Kowal, Jens

    2006-03-01

    Supporting surgeons in performing minimally invasive surgeries can be considered as one of the major goals of computer assisted surgery. Excellent intraoperative visualization is a prerequisite to achieve this aim. The Siremobil Iso-C 3D has become a widely used imaging device, which, in combination with a navigation system, enables the surgeon to directly navigate within the acquired 3D image volume without any extra registration steps. However, the image quality is rather low compared to a CT scan and the volume size (approx. 12 cm 3) limits its application. A regularly used alternative in computer assisted orthopedic surgery is to use of a preoperatively acquired CT scan to visualize the operating field. But, the additional registration step, necessary in order to use CT stacks for navigation is quite invasive. Therefore the objective of this work is to develop a noninvasive registration technique. In this article a solution is being proposed that registers a preoperatively acquired CT scan to the intraoperatively acquired Iso-C 3D image volume, thereby registering the CT to the tracked anatomy. The procedure aligns both image volumes by maximizing the mutual information, an algorithm that has already been applied to similar registration problems and demonstrated good results. Furthermore the accuracy of such a registration method was investigated in a clinical setup, integrating a navigated Iso-C 3D in combination with an tracking system. Initial tests based on cadaveric animal bone resulted in an accuracy ranging from 0.63mm to 1.55mm mean error.

  8. 3D seismic image processing for interpretation

    NASA Astrophysics Data System (ADS)

    Wu, Xinming

    Extracting fault, unconformity, and horizon surfaces from a seismic image is useful for interpretation of geologic structures and stratigraphic features. Although interpretation of these surfaces has been automated to some extent by others, significant manual effort is still required for extracting each type of these geologic surfaces. I propose methods to automatically extract all the fault, unconformity, and horizon surfaces from a 3D seismic image. To a large degree, these methods just involve image processing or array processing which is achieved by efficiently solving partial differential equations. For fault interpretation, I propose a linked data structure, which is simpler than triangle or quad meshes, to represent a fault surface. In this simple data structure, each sample of a fault corresponds to exactly one image sample. Using this linked data structure, I extract complete and intersecting fault surfaces without holes from 3D seismic images. I use the same structure in subsequent processing to estimate fault slip vectors. I further propose two methods, using precomputed fault surfaces and slips, to undo faulting in seismic images by simultaneously moving fault blocks and faults themselves. For unconformity interpretation, I first propose a new method to compute a unconformity likelihood image that highlights both the termination areas and the corresponding parallel unconformities and correlative conformities. I then extract unconformity surfaces from the likelihood image and use these surfaces as constraints to more accurately estimate seismic normal vectors that are discontinuous near the unconformities. Finally, I use the estimated normal vectors and use the unconformities as constraints to compute a flattened image, in which seismic reflectors are all flat and vertical gaps correspond to the unconformities. Horizon extraction is straightforward after computing a map of image flattening; we can first extract horizontal slices in the flattened space

  9. An image registration based ultrasound probe calibration

    NASA Astrophysics Data System (ADS)

    Li, Xin; Kumar, Dinesh; Sarkar, Saradwata; Narayanan, Ram

    2012-02-01

    Reconstructed 3D ultrasound of prostate gland finds application in several medical areas such as image guided biopsy, therapy planning and dose delivery. In our application, we use an end-fire probe rotated about its axis to acquire a sequence of rotational slices to reconstruct 3D TRUS (Transrectal Ultrasound) image. The image acquisition system consists of an ultrasound transducer situated on a cradle directly attached to a rotational sensor. However, due to system tolerances, axis of probe does not align exactly with the designed axis of rotation resulting in artifacts in the 3D reconstructed ultrasound volume. We present a rigid registration based automatic probe calibration approach. The method uses a sequence of phantom images, each pair acquired at angular separation of 180 degrees and registers corresponding image pairs to compute the deviation from designed axis. A modified shadow removal algorithm is applied for preprocessing. An attribute vector is constructed from image intensity and a speckle-insensitive information-theoretic feature. We compare registration between the presented method and expert-corrected images in 16 prostate phantom scans. Images were acquired at multiple resolutions, and different misalignment settings from two ultrasound machines. Screenshots from 3D reconstruction are shown before and after misalignment correction. Registration parameters from automatic and manual correction were found to be in good agreement. Average absolute differences of translation and rotation between automatic and manual methods were 0.27 mm and 0.65 degree, respectively. The registration parameters also showed lower variability for automatic registration (pooled standard deviation σtranslation = 0.50 mm, σrotation = 0.52 degree) compared to the manual approach (pooled standard deviation σtranslation = 0.62 mm, σrotation = 0.78 degree).

  10. 3D GPR Imaging of Wooden Logs

    NASA Astrophysics Data System (ADS)

    Halabe, Udaya B.; Pyakurel, Sandeep

    2007-03-01

    There has been a lack of an effective NDE technique to locate internal defects within wooden logs. The few available elastic wave propagation based techniques are limited to predicting E values. Other techniques such as X-rays have not been very successful in detecting internal defects in logs. If defects such as embedded metals could be identified before the sawing process, the saw mills could significantly increase their production by reducing the probability of damage to the saw blade and the associated downtime and the repair cost. Also, if the internal defects such as knots and decayed areas could be identified in logs, the sawing blade can be oriented to exclude the defective portion and optimize the volume of high valued lumber that can be obtained from the logs. In this research, GPR has been successfully used to locate internal defects (knots, decays and embedded metals) within the logs. This paper discusses GPR imaging and mapping of the internal defects using both 2D and 3D interpretation methodology. Metal pieces were inserted in a log and the reflection patterns from these metals were interpreted from the radargrams acquired using 900 MHz antenna. Also, GPR was able to accurately identify the location of knots and decays. Scans from several orientations of the log were collected to generate 3D cylindrical volume. The actual location of the defects showed good correlation with the interpreted defects in the 3D volume. The time/depth slices from 3D cylindrical volume data were useful in understanding the extent of defects inside the log.

  11. 3-D SAR image formation from sparse aperture data using 3-D target grids

    NASA Astrophysics Data System (ADS)

    Bhalla, Rajan; Li, Junfei; Ling, Hao

    2005-05-01

    The performance of ATR systems can potentially be improved by using three-dimensional (3-D) SAR images instead of the traditional two-dimensional SAR images or one-dimensional range profiles. 3-D SAR image formation of targets from radar backscattered data collected on wide angle, sparse apertures has been identified by AFRL as fundamental to building an object detection and recognition capability. A set of data has been released as a challenge problem. This paper describes a technique based on the concept of 3-D target grids aimed at the formation of 3-D SAR images of targets from sparse aperture data. The 3-D target grids capture the 3-D spatial and angular scattering properties of the target and serve as matched filters for SAR formation. The results of 3-D SAR formation using the backhoe public release data are presented.

  12. Rapid 360 degree imaging and stitching of 3D objects using multiple precision 3D cameras

    NASA Astrophysics Data System (ADS)

    Lu, Thomas; Yin, Stuart; Zhang, Jianzhong; Li, Jiangan; Wu, Frank

    2008-02-01

    In this paper, we present the system architecture of a 360 degree view 3D imaging system. The system consists of multiple 3D sensors synchronized to take 3D images around the object. Each 3D camera employs a single high-resolution digital camera and a color-coded light projector. The cameras are synchronized to rapidly capture the 3D and color information of a static object or a live person. The color encoded structure lighting ensures the precise reconstruction of the depth of the object. A 3D imaging system architecture is presented. The architecture employs the displacement of the camera and the projector to triangulate the depth information. The 3D camera system has achieved high depth resolution down to 0.1mm on a human head sized object and 360 degree imaging capability.

  13. 3D Buildings Extraction from Aerial Images

    NASA Astrophysics Data System (ADS)

    Melnikova, O.; Prandi, F.

    2011-09-01

    This paper introduces a semi-automatic method for buildings extraction through multiple-view aerial image analysis. The advantage of the used semi-automatic approach is that it allows processing of each building individually finding the parameters of buildings features extraction more precisely for each area. On the early stage the presented technique uses an extraction of line segments that is done only inside of areas specified manually. The rooftop hypothesis is used further to determine a subset of quadrangles, which could form building roofs from a set of extracted lines and corners obtained on the previous stage. After collecting of all potential roof shapes in all images overlaps, the epipolar geometry is applied to find matching between images. This allows to make an accurate selection of building roofs removing false-positive ones and to identify their global 3D coordinates given camera internal parameters and coordinates. The last step of the image matching is based on geometrical constraints in contrast to traditional correlation. The correlation is applied only in some highly restricted areas in order to find coordinates more precisely, in such a way significantly reducing processing time of the algorithm. The algorithm has been tested on a set of Milan's aerial images and shows highly accurate results.

  14. Robust 2D/3D registration for fast-flexion motion of the knee joint using hybrid optimization.

    PubMed

    Ohnishi, Takashi; Suzuki, Masahiko; Kobayashi, Tatsuya; Naomoto, Shinji; Sukegawa, Tomoyuki; Nawata, Atsushi; Haneishi, Hideaki

    2013-01-01

    Previously, we proposed a 2D/3D registration method that uses Powell's algorithm to obtain 3D motion of a knee joint by 3D computed-tomography and bi-plane fluoroscopic images. The 2D/3D registration is performed consecutively and automatically for each frame of the fluoroscopic images. This method starts from the optimum parameters of the previous frame for each frame except for the first one, and it searches for the next set of optimum parameters using Powell's algorithm. However, if the flexion motion of the knee joint is fast, it is likely that Powell's algorithm will provide a mismatch because the initial parameters are far from the correct ones. In this study, we applied a hybrid optimization algorithm (HPS) combining Powell's algorithm with the Nelder-Mead simplex (NM-simplex) algorithm to overcome this problem. The performance of the HPS was compared with the separate performances of Powell's algorithm and the NM-simplex algorithm, the Quasi-Newton algorithm and hybrid optimization algorithm with the Quasi-Newton and NM-simplex algorithms with five patient data sets in terms of the root-mean-square error (RMSE), target registration error (TRE), success rate, and processing time. The RMSE, TRE, and the success rate of the HPS were better than those of the other optimization algorithms, and the processing time was similar to that of Powell's algorithm alone. PMID:23138929

  15. 2D and 3D registration methods for dual-energy contrast-enhanced digital breast tomosynthesis

    NASA Astrophysics Data System (ADS)

    Lau, Kristen C.; Roth, Susan; Maidment, Andrew D. A.

    2014-03-01

    Contrast-enhanced digital breast tomosynthesis (CE-DBT) uses an iodinated contrast agent to image the threedimensional breast vasculature. The University of Pennsylvania is conducting a CE-DBT clinical study in patients with known breast cancers. The breast is compressed continuously and imaged at four time points (1 pre-contrast; 3 postcontrast). A hybrid subtraction scheme is proposed. First, dual-energy (DE) images are obtained by a weighted logarithmic subtraction of the high-energy and low-energy image pairs. Then, post-contrast DE images are subtracted from the pre-contrast DE image. This hybrid temporal subtraction of DE images is performed to analyze iodine uptake, but suffers from motion artifacts. Employing image registration further helps to correct for motion, enhancing the evaluation of vascular kinetics. Registration using ANTS (Advanced Normalization Tools) is performed in an iterative manner. Mutual information optimization first corrects large-scale motions. Normalized cross-correlation optimization then iteratively corrects fine-scale misalignment. Two methods have been evaluated: a 2D method using a slice-by-slice approach, and a 3D method using a volumetric approach to account for out-of-plane breast motion. Our results demonstrate that iterative registration qualitatively improves with each iteration (five iterations total). Motion artifacts near the edge of the breast are corrected effectively and structures within the breast (e.g. blood vessels, surgical clip) are better visualized. Statistical and clinical evaluations of registration accuracy in the CE-DBT images are ongoing.

  16. 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.

  17. Automatic needle segmentation in 3D ultrasound images using 3D Hough transform

    NASA Astrophysics Data System (ADS)

    Zhou, Hua; Qiu, Wu; Ding, Mingyue; Zhang, Songgeng

    2007-12-01

    3D ultrasound (US) is a new technology that can be used for a variety of diagnostic applications, such as obstetrical, vascular, and urological imaging, and has been explored greatly potential in the applications of image-guided surgery and therapy. Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese woman, and a minimally invasive ablation system using an RF button electrode which is needle-like is being used to destroy tumor cells or stop bleeding currently. Now a 3D US guidance system has been developed to avoid accidents or death of the patient by inaccurate localizations of the electrode and the tumor position during treatment. In this paper, we described two automated techniques, the 3D Hough Transform (3DHT) and the 3D Randomized Hough Transform (3DRHT), which is potentially fast, accurate, and robust to provide needle segmentation in 3D US image for use of 3D US imaging guidance. Based on the representation (Φ , θ , ρ , α ) of straight lines in 3D space, we used the 3DHT algorithm to segment needles successfully assumed that the approximate needle position and orientation are known in priori. The 3DRHT algorithm was developed to detect needles quickly without any information of the 3D US images. The needle segmentation techniques were evaluated using the 3D US images acquired by scanning water phantoms. The experiments demonstrated the feasibility of two 3D needle segmentation algorithms described in this paper.

  18. Photogrammetric 3D reconstruction using mobile imaging

    NASA Astrophysics Data System (ADS)

    Fritsch, Dieter; Syll, Miguel

    2015-03-01

    In our paper we demonstrate the development of an Android Application (AndroidSfM) for photogrammetric 3D reconstruction that works on smartphones and tablets likewise. The photos are taken with mobile devices, and can thereafter directly be calibrated using standard calibration algorithms of photogrammetry and computer vision, on that device. Due to still limited computing resources on mobile devices, a client-server handshake using Dropbox transfers the photos to the sever to run AndroidSfM for the pose estimation of all photos by Structure-from-Motion and, thereafter, uses the oriented bunch of photos for dense point cloud estimation by dense image matching algorithms. The result is transferred back to the mobile device for visualization and ad-hoc on-screen measurements.

  19. Real-time computer-generated integral imaging and 3D image calibration for augmented reality surgical navigation.

    PubMed

    Wang, Junchen; Suenaga, Hideyuki; Liao, Hongen; Hoshi, Kazuto; Yang, Liangjing; Kobayashi, Etsuko; Sakuma, Ichiro

    2015-03-01

    Autostereoscopic 3D image overlay for augmented reality (AR) based surgical navigation has been studied and reported many times. For the purpose of surgical overlay, the 3D image is expected to have the same geometric shape as the original organ, and can be transformed to a specified location for image overlay. However, how to generate a 3D image with high geometric fidelity and quantitative evaluation of 3D image's geometric accuracy have not been addressed. This paper proposes a graphics processing unit (GPU) based computer-generated integral imaging pipeline for real-time autostereoscopic 3D display, and an automatic closed-loop 3D image calibration paradigm for displaying undistorted 3D images. Based on the proposed methods, a novel AR device for 3D image surgical overlay is presented, which mainly consists of a 3D display, an AR window, a stereo camera for 3D measurement, and a workstation for information processing. The evaluation on the 3D image rendering performance with 2560×1600 elemental image resolution shows the rendering speeds of 50-60 frames per second (fps) for surface models, and 5-8 fps for large medical volumes. The evaluation of the undistorted 3D image after the calibration yields sub-millimeter geometric accuracy. A phantom experiment simulating oral and maxillofacial surgery was also performed to evaluate the proposed AR overlay device in terms of the image registration accuracy, 3D image overlay accuracy, and the visual effects of the overlay. The experimental results show satisfactory image registration and image overlay accuracy, and confirm the system usability. PMID:25465067

  20. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network

    PubMed Central

    Fedorov, Andriy; Beichel, Reinhard; Kalpathy-Cramer, Jayashree; Finet, Julien; Fillion-Robin, Jean-Christophe; Pujol, Sonia; Bauer, Christian; Jennings, Dominique; Fennessy, Fiona; Sonka, Milan; Buatti, John; Aylward, Stephen; Miller, James V.; Pieper, Steve; Kikinis, Ron

    2012-01-01

    Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm, and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future

  1. 3D Slicer as an image computing platform for the Quantitative Imaging Network.

    PubMed

    Fedorov, Andriy; Beichel, Reinhard; Kalpathy-Cramer, Jayashree; Finet, Julien; Fillion-Robin, Jean-Christophe; Pujol, Sonia; Bauer, Christian; Jennings, Dominique; Fennessy, Fiona; Sonka, Milan; Buatti, John; Aylward, Stephen; Miller, James V; Pieper, Steve; Kikinis, Ron

    2012-11-01

    Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open-source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future

  2. Imaging a Sustainable Future in 3D

    NASA Astrophysics Data System (ADS)

    Schuhr, W.; Lee, J. D.; Kanngieser, E.

    2012-07-01

    It is the intention of this paper, to contribute to a sustainable future by providing objective object information based on 3D photography as well as promoting 3D photography not only for scientists, but also for amateurs. Due to the presentation of this article by CIPA Task Group 3 on "3D Photographs in Cultural Heritage", the presented samples are masterpieces of historic as well as of current 3D photography concentrating on cultural heritage. In addition to a report on exemplarily access to international archives of 3D photographs, samples for new 3D photographs taken with modern 3D cameras, as well as by means of a ground based high resolution XLITE staff camera and also 3D photographs taken from a captive balloon and the use of civil drone platforms are dealt with. To advise on optimum suited 3D methodology, as well as to catch new trends in 3D, an updated synoptic overview of the 3D visualization technology, even claiming completeness, has been carried out as a result of a systematic survey. In this respect, e.g., today's lasered crystals might be "early bird" products in 3D, which, due to lack in resolution, contrast and color, remember to the stage of the invention of photography.

  3. Robust registration for removing vibrations in 3D reconstruction of web material

    NASA Astrophysics Data System (ADS)

    Usamentiaga, Rubén; Garcia, Daniel F.

    2015-05-01

    Vibrations are a major challenge in laser-based 3D reconstruction of web material. In uncontrolled environments, the movement of web material forward along a track is inevitably affected by vibrations. These oscillations significantly degrade the performance of the 3D reconstruction system, as they are incorrectly interpreted as irregularities on the surface of the material, leading to an erroneous reconstruction of the 3D surface. This work proposes a method to estimate and remove these vibrations based on a robust registration procedure. Registration is used to estimate vibrations and a rigid transformation is used to compensate the movements, removing the effects of vibrations on 3D reconstruction. The proposed method is applied to an extensive dataset, both synthetic and real, with very good results.

  4. Lossless 3-D reconstruction and registration of semi-quantitative gene expression data in the mouse brain.

    PubMed

    Enlow, Matthew A; Ju, Tao; Kakadiaris, Ioannis A; Carson, James P

    2011-01-01

    As imaging, computing, and data storage technologies improve, there is an increasing opportunity for multiscale analysis of three-dimensional datasets (3-D). Such analysis enables, for example, microscale elements of multiple macroscale specimens to be compared throughout the entire macroscale specimen. Spatial comparisons require bringing datasets into co-alignment. One approach for co-alignment involves elastic deformations of data in addition to rigid alignments. The elastic deformations distort space, and if not accounted for, can distort the information at the microscale. The algorithms developed in this work address this issue by allowing multiple data points to be encoded into a single image pixel, appropriately tracking each data point to ensure lossless data mapping during elastic spatial deformation. This approach was developed and implemented for both 2-D and 3D registration of images. Lossless reconstruction and registration was applied to semi-quantitative cellular gene expression data in the mouse brain, enabling comparison of multiple spatially registered 3-D datasets without any augmentation of the cellular data. Standard reconstruction and registration without the lossless approach resulted in errors in cellular quantities of ∼ 8%. PMID:22256218

  5. Ames Lab 101: Real-Time 3D Imaging

    ScienceCinema

    Zhang, Song

    2012-08-29

    Ames Laboratory scientist Song Zhang explains his real-time 3-D imaging technology. The technique can be used to create high-resolution, real-time, precise, 3-D images for use in healthcare, security, and entertainment applications.

  6. Remapping of digital subtraction angiography on a standard fluoroscopy system using 2D-3D registration

    NASA Astrophysics Data System (ADS)

    Alhrishy, Mazen G.; Varnavas, Andreas; Guyot, Alexis; Carrell, Tom; King, Andrew; Penney, Graeme

    2015-03-01

    Fluoroscopy-guided endovascular interventions are being performing for more and more complex cases with longer screening times. However, X-ray is much better at visualizing interventional devices and dense structures compared to vasculature. To visualise vasculature, angiography screening is essential but requires the use of iodinated contrast medium (ICM) which is nephrotoxic. Acute kidney injury is the main life-threatening complication of ICM. Digital subtraction angiography (DSA) is also often a major contributor to overall patient radiation dose (81% reported). Furthermore, a DSA image is only valid for the current interventional view and not the new view once the C-arm is moved. In this paper, we propose the use of 2D-3D image registration between intraoperative images and the preoperative CT volume to facilitate DSA remapping using a standard fluoroscopy system. This allows repeated ICM-free DSA and has the potential to enable a reduction in ICM usage and radiation dose. Experiments were carried out using 9 clinical datasets. In total, 41 DSA images were remapped. For each dataset, the maximum and averaged remapping accuracy error were calculated and presented. Numerical results showed an overall averaged error of 2.50 mm, with 7 patients scoring averaged errors < 3 mm and 2 patients < 6 mm.

  7. Advances in image registration and fusion

    NASA Astrophysics Data System (ADS)

    Steer, Christopher; Rogers, Jeremy; Smith, Moira; Heather, Jamie; Bernhardt, Mark; Hickman, Duncan

    2008-03-01

    Many image fusion systems involving passive sensors require the accurate registration of the sensor data prior to performing fusion. Since depth information is not readily available in such systems, all registration algorithms are intrinsically approximations based upon various assumption about the depth field. Although often overlooked, many registration algorithms can break down in certain situations and this may adversely affect the image fusion performance. In this paper, we discuss a framework for quantifying the accuracy and robustness of image registration algorithms which allows a more precise understanding of their shortcomings. In addition, some novel algorithms have been investigated that overcome some of these limitations. A second aspect of this work has considered the treatment of images from multiple sensors whose angular and spatial separation is large and where conventional registration algorithms break down (typically greater than a few degrees of separation). A range of novel approaches is reported which exploit the use of parallax to estimate depth information and reconstruct a geometrical model of the scene. The imagery can then be combined with this geometrical model to render a variety of useful representations of the data. These techniques (which we term Volume Registration) show great promise as a means of gathering and presenting 3D and 4D scene information for both military and civilian applications.

  8. Progress in 3D imaging and display by integral imaging

    NASA Astrophysics Data System (ADS)

    Martinez-Cuenca, R.; Saavedra, G.; Martinez-Corral, M.; Pons, A.; Javidi, B.

    2009-05-01

    Three-dimensionality is currently considered an important added value in imaging devices, and therefore the search for an optimum 3D imaging and display technique is a hot topic that is attracting important research efforts. As main value, 3D monitors should provide the observers with different perspectives of a 3D scene by simply varying the head position. Three-dimensional imaging techniques have the potential to establish a future mass-market in the fields of entertainment and communications. Integral imaging (InI), which can capture true 3D color images, has been seen as the right technology to 3D viewing to audiences of more than one person. Due to the advanced degree of development, InI technology could be ready for commercialization in the coming years. This development is the result of a strong research effort performed along the past few years by many groups. Since Integral Imaging is still an emerging technology, the first aim of the "3D Imaging and Display Laboratory" at the University of Valencia, has been the realization of a thorough study of the principles that govern its operation. Is remarkable that some of these principles have been recognized and characterized by our group. Other contributions of our research have been addressed to overcome some of the classical limitations of InI systems, like the limited depth of field (in pickup and in display), the poor axial and lateral resolution, the pseudoscopic-to-orthoscopic conversion, the production of 3D images with continuous relief, or the limited range of viewing angles of InI monitors.

  9. Interactive initialization for 2D/3D intra-operative registration using the Microsoft Kinect

    NASA Astrophysics Data System (ADS)

    Gong, Ren Hui; Güler, Özgur; Yaniv, Ziv

    2013-03-01

    All 2D/3D anatomy based rigid registration algorithms are iterative, requiring an initial estimate of the 3D data pose. Current initialization methods have limited applicability in the operating room setting, due to the constraints imposed by this environment or due to insufficient accuracy. In this work we use the Microsoft Kinect device to allow the surgeon to interactively initialize the registration process. A Kinect sensor is used to simulate the mouse-based operations in a conventional manual initialization approach, obviating the need for physical contact with an input device. Different gestures from both arms are detected from the sensor in order to set or switch the required working contexts. 3D hand motion provides the six degree-of-freedom controls for manipulating the pre-operative data in the 3D space. We evaluated our method for both X-ray/CT and X-ray/MR initialization using three publicly available reference data sets. Results show that, with initial target registration errors of 117:7 +/- 28:9 mm a user is able to achieve final errors of 5:9 +/- 2:6 mm within 158 +/- 65 sec using the Kinect-based approach, compared to 4:8+/-2:0 mm and 88+/-60 sec when using the mouse for interaction. Based on these results we conclude that this method is sufficiently accurate for initialization of X-ray/CT and X-ray/MR registration in the OR.

  10. A hybrid framework of multiple active appearance models and global registration for 3D prostate segmentation in MRI

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

    Real-time fusion of Magnetic Resonance (MR) and Trans Rectal Ultra Sound (TRUS) images aid in the localization of malignant tissues in TRUS guided prostate biopsy. Registration performed on segmented contours of the prostate reduces computational complexity and improves the multimodal registration accuracy. However, accurate and computationally efficient 3D segmentation of the prostate in MR images could be a challenging task due to inter-patient shape and intensity variability of the prostate gland. In this work, we propose to use multiple statistical shape and appearance models to segment the prostate in 2D and a global registration framework to impose shape restriction in 3D. Multiple mean parametric models of the shape and appearance corresponding to the apex, central and base regions of the prostate gland are derived from principal component analysis (PCA) of prior shape and intensity information of the prostate from the training data. The estimated parameters are then modified with the prior knowledge of the optimization space to achieve segmentation in 2D. The 2D segmented slices are then rigidly registered with the average 3D model produced by affine registration of the ground truth of the training datasets to minimize pose variations and impose 3D shape restriction. The proposed method achieves a mean Dice similarity coefficient (DSC) value of 0.88+/-0.11, and mean Hausdorff distance (HD) of 3.38+/-2.81 mm when validated with 15 prostate volumes of a public dataset in leave-one-out validation framework. The results achieved are better compared to some of the works in the literature.

  11. Real-time SPECT and 2D ultrasound image registration.

    PubMed

    Bucki, Marek; Chassat, Fabrice; Galdames, Francisco; Asahi, Takeshi; Pizarro, Daniel; Lobo, Gabriel

    2007-01-01

    In this paper we present a technique for fully automatic, real-time 3D SPECT (Single Photon Emitting Computed Tomography) and 2D ultrasound image registration. We use this technique in the context of kidney lesion diagnosis. Our registration algorithm allows a physician to perform an ultrasound exam after a SPECT image has been acquired and see in real time the registration of both modalities. An automatic segmentation algorithm has been implemented in order to display in 3D the positions of the acquired US images with respect to the organs. PMID:18044572

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

    SciTech Connect

    Chen Ting; Kim, Sung; Goyal, Sharad; Jabbour, Salma; Zhou Jinghao; Rajagopal, Gunaretnum; Haffty, Bruce; Yue Ning

    2010-01-15

    Purpose: High-speed nonrigid registration between the planning CT and the treatment CBCT data is critical for real time image guided radiotherapy (IGRT) to improve the dose distribution and to reduce the toxicity to adjacent organs. The authors propose a new fully automatic 3D registration framework that integrates object-based global and seed constraints with the grayscale-based ''demons'' algorithm. Methods: Clinical objects were segmented on the planning CT images and were utilized as meshless deformable models during the nonrigid registration process. The meshless models reinforced a global constraint in addition to the grayscale difference between CT and CBCT in order to maintain the shape and the volume of geometrically complex 3D objects during the registration. To expedite the registration process, the framework was stratified into hierarchies, and the authors used a frequency domain formulation to diffuse the displacement between the reference and the target in each hierarchy. Also during the registration of pelvis images, they replaced the air region inside the rectum with estimated pixel values from the surrounding rectal wall and introduced an additional seed constraint to robustly track and match the seeds implanted into the prostate. The proposed registration framework and algorithm were evaluated on 15 real prostate cancer patients. For each patient, prostate gland, seminal vesicle, bladder, and rectum were first segmented by a radiation oncologist on planning CT images for radiotherapy planning purpose. The same radiation oncologist also manually delineated the tumor volumes and critical anatomical structures in the corresponding CBCT images acquired at treatment. These delineated structures on the CBCT were only used as the ground truth for the quantitative validation, while structures on the planning CT were used both as the input to the registration method and the ground truth in validation. By registering the planning CT to the CBCT, a

  13. Image Segmentation, Registration, Compression, and Matching

    NASA Technical Reports Server (NTRS)

    Yadegar, Jacob; Wei, Hai; Yadegar, Joseph; Ray, Nilanjan; Zabuawala, Sakina

    2011-01-01

    A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity

  14. Concurrent 3-D motion segmentation and 3-D interpretation of temporal sequences of monocular images.

    PubMed

    Sekkati, Hicham; Mitiche, Amar

    2006-03-01

    The purpose of this study is to investigate a variational method for joint multiregion three-dimensional (3-D) motion segmentation and 3-D interpretation of temporal sequences of monocular images. Interpretation consists of dense recovery of 3-D structure and motion from the image sequence spatiotemporal variations due to short-range image motion. The method is direct insomuch as it does not require prior computation of image motion. It allows movement of both viewing system and multiple independently moving objects. The problem is formulated following a variational statement with a functional containing three terms. One term measures the conformity of the interpretation within each region of 3-D motion segmentation to the image sequence spatiotemporal variations. The second term is of regularization of depth. The assumption that environmental objects are rigid accounts automatically for the regularity of 3-D motion within each region of segmentation. The third and last term is for the regularity of segmentation boundaries. Minimization of the functional follows the corresponding Euler-Lagrange equations. This results in iterated concurrent computation of 3-D motion segmentation by curve evolution, depth by gradient descent, and 3-D motion by least squares within each region of segmentation. Curve evolution is implemented via level sets for topology independence and numerical stability. This algorithm and its implementation are verified on synthetic and real image sequences. Viewers presented with anaglyphs of stereoscopic images constructed from the algorithm's output reported a strong perception of depth. PMID:16519351

  15. Fast multi-core based multimodal registration of 2D cross-sections and 3D datasets

    PubMed Central

    2010-01-01

    Background Solving bioinformatics tasks often requires extensive computational power. Recent trends in processor architecture combine multiple cores into a single chip to improve overall performance. The Cell Broadband Engine (CBE), a heterogeneous multi-core processor, provides power-efficient and cost-effective high-performance computing. One application area is image analysis and visualisation, in particular registration of 2D cross-sections into 3D image datasets. Such techniques can be used to put different image modalities into spatial correspondence, for example, 2D images of histological cuts into morphological 3D frameworks. Results We evaluate the CBE-driven PlayStation 3 as a high performance, cost-effective computing platform by adapting a multimodal alignment procedure to several characteristic hardware properties. The optimisations are based on partitioning, vectorisation, branch reducing and loop unrolling techniques with special attention to 32-bit multiplies and limited local storage on the computing units. We show how a typical image analysis and visualisation problem, the multimodal registration of 2D cross-sections and 3D datasets, benefits from the multi-core based implementation of the alignment algorithm. We discuss several CBE-based optimisation methods and compare our results to standard solutions. More information and the source code are available from http://cbe.ipk-gatersleben.de. Conclusions The results demonstrate that the CBE processor in a PlayStation 3 accelerates computational intensive multimodal registration, which is of great importance in biological/medical image processing. The PlayStation 3 as a low cost CBE-based platform offers an efficient option to conventional hardware to solve computational problems in image processing and bioinformatics. PMID:20064262

  16. 3D-2D registration in mobile radiographs: algorithm development and preliminary clinical evaluation

    NASA Astrophysics Data System (ADS)

    Otake, Yoshito; Wang, Adam S.; Uneri, Ali; Kleinszig, Gerhard; Vogt, Sebastian; Aygun, Nafi; Lo, Sheng-fu L.; Wolinsky, Jean-Paul; Gokaslan, Ziya L.; Siewerdsen, Jeffrey H.

    2015-03-01

    An image-based 3D-2D registration method is presented using radiographs acquired in the uncalibrated, unconstrained geometry of mobile radiography. The approach extends a previous method for six degree-of-freedom (DOF) registration in C-arm fluoroscopy (namely ‘LevelCheck’) to solve the 9-DOF estimate of geometry in which the position of the source and detector are unconstrained. The method was implemented using a gradient correlation similarity metric and stochastic derivative-free optimization on a GPU. Development and evaluation were conducted in three steps. First, simulation studies were performed that involved a CT scan of an anthropomorphic body phantom and 1000 randomly generated digitally reconstructed radiographs in posterior-anterior and lateral views. A median projection distance error (PDE) of 0.007 mm was achieved with 9-DOF registration compared to 0.767 mm for 6-DOF. Second, cadaver studies were conducted using mobile radiographs acquired in three anatomical regions (thorax, abdomen and pelvis) and three levels of source-detector distance (~800, ~1000 and ~1200 mm). The 9-DOF method achieved a median PDE of 0.49 mm (compared to 2.53 mm for the 6-DOF method) and demonstrated robustness in the unconstrained imaging geometry. Finally, a retrospective clinical study was conducted with intraoperative radiographs of the spine exhibiting real anatomical deformation and image content mismatch (e.g. interventional devices in the radiograph that were not in the CT), demonstrating a PDE = 1.1 mm for the 9-DOF approach. Average computation time was 48.5 s, involving 687 701 function evaluations on average, compared to 18.2 s for the 6-DOF method. Despite the greater computational load, the 9-DOF method may offer a valuable tool for target localization (e.g. decision support in level counting) as well as safety and quality assurance checks at the conclusion of a procedure (e.g. overlay of planning data on the radiograph for verification of

  17. A molecular image-directed, 3D ultrasound-guided biopsy system for the prostate

    NASA Astrophysics Data System (ADS)

    Fei, Baowei; Schuster, David M.; Master, Viraj; Akbari, Hamed; Fenster, Aaron; Nieh, Peter

    2012-02-01

    Systematic transrectal ultrasound (TRUS)-guided biopsy is the standard method for a definitive diagnosis of prostate cancer. However, this biopsy approach uses two-dimensional (2D) ultrasound images to guide biopsy and can miss up to 30% of prostate cancers. We are developing a molecular image-directed, three-dimensional (3D) ultrasound imageguided biopsy system for improved detection of prostate cancer. The system consists of a 3D mechanical localization system and software workstation for image segmentation, registration, and biopsy planning. In order to plan biopsy in a 3D prostate, we developed an automatic segmentation method based wavelet transform. In order to incorporate PET/CT images into ultrasound-guided biopsy, we developed image registration methods to fuse TRUS and PET/CT images. The segmentation method was tested in ten patients with a DICE overlap ratio of 92.4% +/- 1.1 %. The registration method has been tested in phantoms. The biopsy system was tested in prostate phantoms and 3D ultrasound images were acquired from two human patients. We are integrating the system for PET/CT directed, 3D ultrasound-guided, targeted biopsy in human patients.

  18. Automatic needle segmentation in 3D ultrasound images using 3D improved Hough transform

    NASA Astrophysics Data System (ADS)

    Zhou, Hua; Qiu, Wu; Ding, Mingyue; Zhang, Songgen

    2008-03-01

    3D ultrasound (US) is a new technology that can be used for a variety of diagnostic applications, such as obstetrical, vascular, and urological imaging, and has been explored greatly potential in the applications of image-guided surgery and therapy. Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese woman, and a minimally invasive ablation system using a needle-like RF button electrode is widely used to destroy tumor cells or stop bleeding. To avoid accidents or death of the patient by inaccurate localizations of the electrode and the tumor position during treatment, 3D US guidance system was developed. In this paper, a new automated technique, the 3D Improved Hough Transform (3DIHT) algorithm, which is potentially fast, accurate, and robust to provide needle segmentation in 3D US image for use of 3D US imaging guidance, was presented. Based on the coarse-fine search strategy and a four parameter representation of lines in 3D space, 3DIHT algorithm can segment needles quickly, accurately and robustly. The technique was evaluated using the 3D US images acquired by scanning a water phantom. The segmentation position deviation of the line was less than 2mm and angular deviation was much less than 2°. The average computational time measured on a Pentium IV 2.80GHz PC computer with a 381×381×250 image was less than 2s.

  19. 2D-3D Registration of CT Vertebra Volume to Fluoroscopy Projection: A Calibration Model Assessment

    NASA Astrophysics Data System (ADS)

    Bifulco, P.; Cesarelli, M.; Allen, R.; Romano, M.; Fratini, A.; Pasquariello, G.

    2009-12-01

    This study extends a previous research concerning intervertebral motion registration by means of 2D dynamic fluoroscopy to obtain a more comprehensive 3D description of vertebral kinematics. The problem of estimating the 3D rigid pose of a CT volume of a vertebra from its 2D X-ray fluoroscopy projection is addressed. 2D-3D registration is obtained maximising a measure of similarity between Digitally Reconstructed Radiographs (obtained from the CT volume) and real fluoroscopic projection. X-ray energy correction was performed. To assess the method a calibration model was realised a sheep dry vertebra was rigidly fixed to a frame of reference including metallic markers. Accurate measurement of 3D orientation was obtained via single-camera calibration of the markers and held as true 3D vertebra position; then, vertebra 3D pose was estimated and results compared. Error analysis revealed accuracy of the order of 0.1 degree for the rotation angles of about 1 mm for displacements parallel to the fluoroscopic plane, and of order of 10 mm for the orthogonal displacement.

  20. Lucas-Kanade image registration using camera parameters

    NASA Astrophysics Data System (ADS)

    Cho, Sunghyun; Cho, Hojin; Tai, Yu-Wing; Moon, Young Su; Cho, Junguk; Lee, Shihwa; Lee, Seungyong

    2012-01-01

    The Lucas-Kanade algorithm and its variants have been successfully used for numerous works in computer vision, which include image registration as a component in the process. In this paper, we propose a Lucas-Kanade based image registration method using camera parameters. We decompose a homography into camera intrinsic and extrinsic parameters, and assume that the intrinsic parameters are given, e.g., from the EXIF information of a photograph. We then estimate only the extrinsic parameters for image registration, considering two types of camera motions, 3D rotations and full 3D motions with translations and rotations. As the known information about the camera is fully utilized, the proposed method can perform image registration more reliably. In addition, as the number of extrinsic parameters is smaller than the number of homography elements, our method runs faster than the Lucas-Kanade based registration method that estimates a homography itself.

  1. 3D spatial resolution and spectral resolution of interferometric 3D imaging spectrometry.

    PubMed

    Obara, Masaki; Yoshimori, Kyu

    2016-04-01

    Recently developed interferometric 3D imaging spectrometry (J. Opt. Soc. Am A18, 765 [2001]1084-7529JOAOD610.1364/JOSAA.18.000765) enables obtainment of the spectral information and 3D spatial information for incoherently illuminated or self-luminous object simultaneously. Using this method, we can obtain multispectral components of complex holograms, which correspond directly to the phase distribution of the wavefronts propagated from the polychromatic object. This paper focuses on the analysis of spectral resolution and 3D spatial resolution in interferometric 3D imaging spectrometry. Our analysis is based on a novel analytical impulse response function defined over four-dimensional space. We found that the experimental results agree well with the theoretical prediction. This work also suggests a new criterion and estimate method regarding 3D spatial resolution of digital holography. PMID:27139648

  2. Towards 3D ultrasound image based soft tissue tracking: a transrectal ultrasound prostate image alignment system.

    PubMed

    Baumann, Michael; Mozer, Pierre; Daanen, Vincent; Troccaz, Jocelyne

    2007-01-01

    The emergence of real-time 3D ultrasound (US) makes it possible to consider image-based tracking of subcutaneous soft tissue targets for computer guided diagnosis and therapy. We propose a 3D transrectal US based tracking system for precise prostate biopsy sample localisation. The aim is to improve sample distribution, to enable targeting of unsampled regions for repeated biopsies, and to make post-interventional quality controls possible. Since the patient is not immobilized, since the prostate is mobile and due to the fact that probe movements are only constrained by the rectum during biopsy acquisition, the tracking system must be able to estimate rigid transformations that are beyond the capture range of common image similarity measures. We propose a fast and robust multi-resolution attribute-vector registration approach that combines global and local optimization methods to solve this problem. Global optimization is performed on a probe movement model that reduces the dimensionality of the search space and thus renders optimization efficient. The method was tested on 237 prostate volumes acquired from 14 different patients for 3D to 3D and 3D to orthogonal 2D slices registration. The 3D-3D version of the algorithm converged correctly in 96.7% of all cases in 6.5s with an accuracy of 1.41mm (r.m.s.) and 3.84mm (max). The 3D to slices method yielded a success rate of 88.9% in 2.3s with an accuracy of 1.37mm (r.m.s.) and 4.3mm (max). PMID:18044549

  3. 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

  4. Automatic 2D-to-3D image conversion using 3D examples from the internet

    NASA Astrophysics Data System (ADS)

    Konrad, J.; Brown, G.; Wang, M.; Ishwar, P.; Wu, C.; Mukherjee, D.

    2012-03-01

    The availability of 3D hardware has so far outpaced the production of 3D content. Although to date many methods have been proposed to convert 2D images to 3D stereopairs, the most successful ones involve human operators and, therefore, are time-consuming and costly, while the fully-automatic ones have not yet achieved the same level of quality. This subpar performance is due to the fact that automatic methods usually rely on assumptions about the captured 3D scene that are often violated in practice. In this paper, we explore a radically different approach inspired by our work on saliency detection in images. Instead of relying on a deterministic scene model for the input 2D image, we propose to "learn" the model from a large dictionary of stereopairs, such as YouTube 3D. Our new approach is built upon a key observation and an assumption. The key observation is that among millions of stereopairs available on-line, there likely exist many stereopairs whose 3D content matches that of the 2D input (query). We assume that two stereopairs whose left images are photometrically similar are likely to have similar disparity fields. Our approach first finds a number of on-line stereopairs whose left image is a close photometric match to the 2D query and then extracts depth information from these stereopairs. Since disparities for the selected stereopairs differ due to differences in underlying image content, level of noise, distortions, etc., we combine them by using the median. We apply the resulting median disparity field to the 2D query to obtain the corresponding right image, while handling occlusions and newly-exposed areas in the usual way. We have applied our method in two scenarios. First, we used YouTube 3D videos in search of the most similar frames. Then, we repeated the experiments on a small, but carefully-selected, dictionary of stereopairs closely matching the query. This, to a degree, emulates the results one would expect from the use of an extremely large 3D

  5. High-accuracy registration of intraoperative CT imaging

    NASA Astrophysics Data System (ADS)

    Oentoro, A.; Ellis, R. E.

    2010-02-01

    Image-guided interventions using intraoperative 3D imaging can be less cumbersome than systems dependent on preoperative images, especially by needing neither potentially invasive image-to-patient registration nor a lengthy process of segmenting and generating a 3D surface model. In this study, a method for computer-assisted surgery using direct navigation on intraoperative imaging is presented. In this system the registration step of a navigated procedure was divided into two stages: preoperative calibration of images to a ceiling-mounted optical tracking system, and intraoperative tracking during acquisition of the 3D medical image volume. The preoperative stage used a custom-made multi-modal calibrator that could be optically tracked and also contained fiducial spheres for radiological detection; a robust registration algorithm was used to compensate for the very high false-detection rate that was due to the high physical density of the optical light-emitting diodes. Intraoperatively, a tracking device was attached to plastic bone models that were also instrumented with radio-opaque spheres; A calibrated pointer was used to contact the latter spheres as a validation of the registration. Experiments showed that the fiducial registration error of the preoperative calibration stage was approximately 0.1 mm. The target registration error in the validation stage was approximately 1.2 mm. This study suggests that direct registration, coupled with procedure-specific graphical rendering, is potentially a highly accurate means of performing image-guided interventions in a fast, simple manner.

  6. A Framework for 3D Vessel Analysis using Whole Slide Images of Liver Tissue Sections

    PubMed Central

    Liang, Yanhui; Wang, Fusheng; Treanor, Darren; Magee, Derek; Roberts, Nick; Teodoro, George; Zhu, Yangyang; Kong, Jun

    2015-01-01

    Three-dimensional (3D) high resolution microscopic images have high potential for improving the understanding of both normal and disease processes where structural changes or spatial relationship of disease features are significant. In this paper, we develop a complete framework applicable to 3D pathology analytical imaging, with an application to whole slide images of sequential liver slices for 3D vessel structure analysis. The analysis workflow consists of image registration, segmentation, vessel cross-section association, interpolation, and volumetric rendering. To identify biologically-meaningful correspondence across adjacent slides, we formulate a similarity function for four association cases. The optimal solution is then obtained by constrained Integer Programming. We quantitatively and qualitatively compare our vessel reconstruction results with human annotations. Validation results indicate a satisfactory concordance as measured both by region-based and distance-based metrics. These results demonstrate a promising 3D vessel analysis framework for whole slide images of liver tissue sections. PMID:27034719

  7. 3D ultrasound imaging for prosthesis fabrication and diagnostic imaging

    SciTech Connect

    Morimoto, A.K.; Bow, W.J.; Strong, D.S.

    1995-06-01

    The fabrication of a prosthetic socket for a below-the-knee amputee requires knowledge of the underlying bone structure in order to provide pressure relief for sensitive areas and support for load bearing areas. The goal is to enable the residual limb to bear pressure with greater ease and utility. Conventional methods of prosthesis fabrication are based on limited knowledge about the patient`s underlying bone structure. A 3D ultrasound imaging system was developed at Sandia National Laboratories. The imaging system provides information about the location of the bones in the residual limb along with the shape of the skin surface. Computer assisted design (CAD) software can use this data to design prosthetic sockets for amputees. Ultrasound was selected as the imaging modality. A computer model was developed to analyze the effect of the various scanning parameters and to assist in the design of the overall system. The 3D ultrasound imaging system combines off-the-shelf technology for image capturing, custom hardware, and control and image processing software to generate two types of image data -- volumetric and planar. Both volumetric and planar images reveal definition of skin and bone geometry with planar images providing details on muscle fascial planes, muscle/fat interfaces, and blood vessel definition. The 3D ultrasound imaging system was tested on 9 unilateral below-the- knee amputees. Image data was acquired from both the sound limb and the residual limb. The imaging system was operated in both volumetric and planar formats. An x-ray CT (Computed Tomography) scan was performed on each amputee for comparison. Results of the test indicate beneficial use of ultrasound to generate databases for fabrication of prostheses at a lower cost and with better initial fit as compared to manually fabricated prostheses.

  8. A 3D image analysis tool for SPECT imaging

    NASA Astrophysics Data System (ADS)

    Kontos, Despina; Wang, Qiang; Megalooikonomou, Vasileios; Maurer, Alan H.; Knight, Linda C.; Kantor, Steve; Fisher, Robert S.; Simonian, Hrair P.; Parkman, Henry P.

    2005-04-01

    We have developed semi-automated and fully-automated tools for the analysis of 3D single-photon emission computed tomography (SPECT) images. The focus is on the efficient boundary delineation of complex 3D structures that enables accurate measurement of their structural and physiologic properties. We employ intensity based thresholding algorithms for interactive and semi-automated analysis. We also explore fuzzy-connectedness concepts for fully automating the segmentation process. We apply the proposed tools to SPECT image data capturing variation of gastric accommodation and emptying. These image analysis tools were developed within the framework of a noninvasive scintigraphic test to measure simultaneously both gastric emptying and gastric volume after ingestion of a solid or a liquid meal. The clinical focus of the particular analysis was to probe associations between gastric accommodation/emptying and functional dyspepsia. Employing the proposed tools, we outline effectively the complex three dimensional gastric boundaries shown in the 3D SPECT images. We also perform accurate volume calculations in order to quantitatively assess the gastric mass variation. This analysis was performed both with the semi-automated and fully-automated tools. The results were validated against manual segmentation performed by a human expert. We believe that the development of an automated segmentation tool for SPECT imaging of the gastric volume variability will allow for other new applications of SPECT imaging where there is a need to evaluate complex organ function or tumor masses.

  9. Enhanced ICP for the Registration of Large-Scale 3D Environment Models: An Experimental Study

    PubMed Central

    Han, Jianda; Yin, Peng; He, Yuqing; Gu, Feng

    2016-01-01

    One of the main applications of mobile robots is the large-scale perception of the outdoor environment. One of the main challenges of this application is fusing environmental data obtained by multiple robots, especially heterogeneous robots. This paper proposes an enhanced iterative closest point (ICP) method for the fast and accurate registration of 3D environmental models. First, a hierarchical searching scheme is combined with the octree-based ICP algorithm. Second, an early-warning mechanism is used to perceive the local minimum problem. Third, a heuristic escape scheme based on sampled potential transformation vectors is used to avoid local minima and achieve optimal registration. Experiments involving one unmanned aerial vehicle and one unmanned surface vehicle were conducted to verify the proposed technique. The experimental results were compared with those of normal ICP registration algorithms to demonstrate the superior performance of the proposed method. PMID:26891298

  10. Registration of Feature-Poor 3D Measurements from Fringe Projection

    PubMed Central

    von Enzberg, Sebastian; Al-Hamadi, Ayoub; Ghoneim, Ahmed

    2016-01-01

    We propose a novel method for registration of partly overlapping three-dimensional surface measurements for stereo-based optical sensors using fringe projection. Based on two-dimensional texture matching, it allows global registration of surfaces with poor and ambiguous three-dimensional features, which are common to surface inspection applications. No prior information about relative sensor position is necessary, which makes our approach suitable for semi-automatic and manual measurement. The algorithm is robust and works with challenging measurements, including uneven illumination, surfaces with specular reflection as well as sparsely textured surfaces. We show that precisions of 1 mm and below can be achieved along the surfaces, which is necessary for further local 3D registration. PMID:26927106

  11. Registration of Feature-Poor 3D Measurements from Fringe Projection.

    PubMed

    von Enzberg, Sebastian; Al-Hamadi, Ayoub; Ghoneim, Ahmed

    2016-01-01

    We propose a novel method for registration of partly overlapping three-dimensional surface measurements for stereo-based optical sensors using fringe projection. Based on two-dimensional texture matching, it allows global registration of surfaces with poor and ambiguous three-dimensional features, which are common to surface inspection applications. No prior information about relative sensor position is necessary, which makes our approach suitable for semi-automatic and manual measurement. The algorithm is robust and works with challenging measurements, including uneven illumination, surfaces with specular reflection as well as sparsely textured surfaces. We show that precisions of 1 mm and below can be achieved along the surfaces, which is necessary for further local 3D registration. PMID:26927106

  12. Enhanced ICP for the Registration of Large-Scale 3D Environment Models: An Experimental Study.

    PubMed

    Han, Jianda; Yin, Peng; He, Yuqing; Gu, Feng

    2016-01-01

    One of the main applications of mobile robots is the large-scale perception of the outdoor environment. One of the main challenges of this application is fusing environmental data obtained by multiple robots, especially heterogeneous robots. This paper proposes an enhanced iterative closest point (ICP) method for the fast and accurate registration of 3D environmental models. First, a hierarchical searching scheme is combined with the octree-based ICP algorithm. Second, an early-warning mechanism is used to perceive the local minimum problem. Third, a heuristic escape scheme based on sampled potential transformation vectors is used to avoid local minima and achieve optimal registration. Experiments involving one unmanned aerial vehicle and one unmanned surface vehicle were conducted to verify the proposed technique. The experimental results were compared with those of normal ICP registration algorithms to demonstrate the superior performance of the proposed method. PMID:26891298

  13. Articulated Non-Rigid Point Set Registration for Human Pose Estimation from 3D Sensors

    PubMed Central

    Ge, Song; Fan, Guoliang

    2015-01-01

    We propose a generative framework for 3D human pose estimation that is able to operate on both individual point sets and sequential depth data. We formulate human pose estimation as a point set registration problem, where we propose three new approaches to address several major technical challenges in this research. First, we integrate two registration techniques that have a complementary nature to cope with non-rigid and articulated deformations of the human body under a variety of poses. This unique combination allows us to handle point sets of complex body motion and large pose variation without any initial conditions, as required by most existing approaches. Second, we introduce an efficient pose tracking strategy to deal with sequential depth data, where the major challenge is the incomplete data due to self-occlusions and view changes. We introduce a visible point extraction method to initialize a new template for the current frame from the previous frame, which effectively reduces the ambiguity and uncertainty during registration. Third, to support robust and stable pose tracking, we develop a segment volume validation technique to detect tracking failures and to re-initialize pose registration if needed. The experimental results on both benchmark 3D laser scan and depth datasets demonstrate the effectiveness of the proposed framework when compared with state-of-the-art algorithms. PMID:26131673

  14. 3D Imaging with Holographic Tomography

    NASA Astrophysics Data System (ADS)

    Sheppard, Colin J. R.; Kou, Shan Shan

    2010-04-01

    There are two main types of tomography that enable the 3D internal structures of objects to be reconstructed from scattered data. The commonly known computerized tomography (CT) give good results in the x-ray wavelength range where the filtered back-projection theorem and Radon transform can be used. These techniques rely on the Fourier projection-slice theorem where rays are considered to propagate straight through the object. Another type of tomography called `diffraction tomography' applies in applications in optics and acoustics where diffraction and scattering effects must be taken into account. The latter proves to be a more difficult problem, as light no longer travels straight through the sample. Holographic tomography is a popular way of performing diffraction tomography and there has been active experimental research on reconstructing complex refractive index data using this approach recently. However, there are two distinct ways of doing tomography: either by rotation of the object or by rotation of the illumination while fixing the detector. The difference between these two setups is intuitive but needs to be quantified. From Fourier optics and information transformation point of view, we use 3D transfer function analysis to quantitatively describe how spatial frequencies of the object are mapped to the Fourier domain. We first employ a paraxial treatment by calculating the Fourier transform of the defocused OTF. The shape of the calculated 3D CTF for tomography, by scanning the illumination in one direction only, takes on a form that we might call a 'peanut,' compared to the case of object rotation, where a diablo is formed, the peanut exhibiting significant differences and non-isotropy. In particular, there is a line singularity along one transverse direction. Under high numerical aperture conditions, the paraxial treatment is not accurate, and so we make use of 3D analytical geometry to calculate the behaviour in the non-paraxial case. This time, we

  15. Edge features extraction from 3D laser point cloud based on corresponding images

    NASA Astrophysics Data System (ADS)

    Li, Xin-feng; Zhao, Zi-ming; Xu, Guo-qing; Geng, Yan-long

    2013-09-01

    An extraction method of edge features from 3D laser point cloud based on corresponding images was proposed. After the registration of point cloud and corresponding image, the sub-pixel edge can be extracted from the image using gray moment algorithm. Then project the sub-pixel edge to the point cloud in fitting scan-lines. At last the edge features were achieved by linking the crossing points. The experimental results demonstrate that the method guarantees accurate fine extraction.

  16. Automatic intensity-based 3D-to-2D registration of CT volume and dual-energy digital radiography for the detection of cardiac calcification

    NASA Astrophysics Data System (ADS)

    Chen, Xiang; Gilkeson, Robert; Fei, Baowei

    2007-03-01

    We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DR) for the detection of coronary artery calcification. CT is an established tool for the diagnosis of coronary artery diseases (CADs). Dual-energy digital radiography could be a cost-effective alternative for screening coronary artery calcification. In order to utilize CT as the "gold standard" to evaluate the ability of DR images for the detection and localization of calcium, we developed an automatic intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DR images. To generate digital rendering radiographs (DRR) from the CT volumes, we developed three projection methods, i.e. Gaussian-weighted projection, threshold-based projection, and average-based projection. We tested normalized cross correlation (NCC) and normalized mutual information (NMI) as similarity measurement. We used the Downhill Simplex method as the search strategy. Simulated projection images from CT were fused with the corresponding DR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with mean errors of less 0.8 mm and 0.2 degree for both NCC and NMI. The registration accuracy of the physical phantoms is 0.34 +/- 0.27 mm. Color overlay and 3D visualization of the clinical data show that the two images are registered well. This is consistent with the improvement of the NMI values from 0.20 +/- 0.03 to 0.25 +/- 0.03 after registration. The automatic 3D-to-2D registration method is accurate and robust and may provide a useful tool to evaluate the dual-energy DR images for the detection of coronary artery calcification.

  17. Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification

    PubMed Central

    Chen, Xiang; Gilkeson, Robert; Fei, Baowei

    2013-01-01

    We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DR) for the detection of coronary artery calcification. CT is an established tool for the diagnosis of coronary artery diseases (CADs). Dual-energy digital radiography could be a cost-effective alternative for screening coronary artery calcification. In order to utilize CT as the “gold standard” to evaluate the ability of DR images for the detection and localization of calcium, we developed an automatic intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DR images. To generate digital rendering radiographs (DRR) from the CT volumes, we developed three projection methods, i.e. Gaussian-weighted projection, threshold-based projection, and average-based projection. We tested normalized cross correlation (NCC) and normalized mutual information (NMI) as similarity measurement. We used the Downhill Simplex method as the search strategy. Simulated projection images from CT were fused with the corresponding DR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with mean errors of less 0.8 mm and 0.2 degree for both NCC and NMI. The registration accuracy of the physical phantoms is 0.34 ± 0.27 mm. Color overlay and 3D visualization of the clinical data show that the two images are registered well. This is consistent with the improvement of the NMI values from 0.20 ± 0.03 to 0.25 ± 0.03 after registration. The automatic 3D-to-2D registration method is accurate and robust and may provide a useful tool to evaluate the dual-energy DR images for the detection of coronary artery calcification. PMID:24386527

  18. Evaluation of similarity measures for use in the intensity-based rigid 2D-3D registration for patient positioning in radiotherapy

    SciTech Connect

    Wu Jian; Kim, Minho; Peters, Jorg; Chung, Heeteak; Samant, Sanjiv S.

    2009-12-15

    Purpose: Rigid 2D-3D registration is an alternative to 3D-3D registration for cases where largely bony anatomy can be used for patient positioning in external beam radiation therapy. In this article, the authors evaluated seven similarity measures for use in the intensity-based rigid 2D-3D registration using a variation in Skerl's similarity measure evaluation protocol. Methods: The seven similarity measures are partitioned intensity uniformity, normalized mutual information (NMI), normalized cross correlation (NCC), entropy of the difference image, pattern intensity (PI), gradient correlation (GC), and gradient difference (GD). In contrast to traditional evaluation methods that rely on visual inspection or registration outcomes, the similarity measure evaluation protocol probes the transform parameter space and computes a number of similarity measure properties, which is objective and optimization method independent. The variation in protocol offers an improved property in the quantification of the capture range. The authors used this protocol to investigate the effects of the downsampling ratio, the region of interest, and the method of the digitally reconstructed radiograph (DRR) calculation [i.e., the incremental ray-tracing method implemented on a central processing unit (CPU) or the 3D texture rendering method implemented on a graphics processing unit (GPU)] on the performance of the similarity measures. The studies were carried out using both the kilovoltage (kV) and the megavoltage (MV) images of an anthropomorphic cranial phantom and the MV images of a head-and-neck cancer patient. Results: Both the phantom and the patient studies showed the 2D-3D registration using the GPU-based DRR calculation yielded better robustness, while providing similar accuracy compared to the CPU-based calculation. The phantom study using kV imaging suggested that NCC has the best accuracy and robustness, but its slow function value change near the global maximum requires a

  19. 3D reconstruction of outdoor environments from omnidirectional range and color images

    NASA Astrophysics Data System (ADS)

    Asai, Toshihiro; Kanbara, Masayuki; Yokoya, Naokazu

    2005-03-01

    This paper describes a 3D modeling method for wide area outdoor environments which is based on integrating omnidirectional range and color images. In the proposed method, outdoor scenes can be efficiently digitized by an omnidirectional laser rangefinder which can obtain a 3D shape with high-accuracy and an omnidirectional multi-camera system (OMS) which can capture a high-resolution color image. Multiple range images are registered by minimizing the distances between corresponding points in the different range images. In order to register multiple range images stably, the points on the plane portions detected from the range data are used in registration process. The position and orientation acquired by the RTK-GPS and the gyroscope are used as initial value of simultaneous registration. The 3D model which is obtained by registration of range data is mapped by the texture selected from omnidirectional images in consideration of the resolution of the texture and occlusions of the model. In experiments, we have carried out 3D modeling of our campus with the proposed method.

  20. SU-D-9A-06: 3D Localization of Neurovascular Bundles Through MR-TRUS Registration in Prostate Radiotherapy

    SciTech Connect

    Yang, X; Rossi, P; Ogunleye, T; Jani, A; Curran, W; Liu, T

    2014-06-01

    Purpose: Erectile dysfunction (ED) is the most common complication of prostate-cancer radiotherapy (RT) and the major mechanism is radiation-induced neurovascular bundle (NVB) damage. However, the localization of the NVB remains challenging. This study's purpose is to accurately localize 3D NVB by integrating MR and transrectal ultrasound (TRUS) images through MR-TRUS fusion. Methods: T1 and T2-weighted MR prostate images were acquired using a Philips 1.5T MR scanner and a pelvic phase-array coil. The 3D TRUS images were captured with a clinical scanner and a 7.5 MHz biplane probe. The TRUS probe was attached to a stepper; the B-mode images were captured from the prostate base to apex at a 1-mm step and the Doppler images were acquired in a 5-mm step. The registration method modeled the prostate tissue as an elastic material, and jointly estimated the boundary condition (surface deformation) and the volumetric deformations under elastic constraint. This technique was validated with a clinical study of 7 patients undergoing RT treatment for prostate cancer. The accuracy of our approach was assessed through the locations of landmarks, as well as previous ultrasound Doppler images of patients. Results: MR-TRUS registration was successfully performed for all patients. The mean displacement of the landmarks between the post-registration MR and TRUS images was 1.37±0.42 mm, which demonstrated the precision of the registration based on the biomechanical model; and the NVB volume Dice Overlap Coefficient was 92.1±3.2%, which demonstrated the accuracy of the NVB localization. Conclusion: We have developed a novel approach to improve 3D NVB localization through MR-TRUS fusion for prostate RT, demonstrated its clinical feasibility, and validated its accuracy with ultrasound Doppler data. This technique could be a useful tool as we try to spare the NVB in prostate RT, monitor NBV response to RT, and potentially improve post-RT potency outcomes.

  1. Needle placement for piriformis injection using 3-D imaging.

    PubMed

    Clendenen, Steven R; Candler, Shawn A; Osborne, Michael D; Palmer, Scott C; Duench, Stephanie; Glynn, Laura; Ghazi, Salim M

    2013-01-01

    Piriformis syndrome is a pain syndrome originating in the buttock and is attributed to 6% - 8% of patients referred for the treatment of back and leg pain. The treatment for piriformis syndrome using fluoroscopy, computed tomography (CT), electromyography (EMG), and ultrasound (US) has become standard practice. The treatment of Piriformis Syndrome has evolved to include fluoroscopy and EMG with CT guidance. We present a case study of 5 successful piriformis injections using 3-D computer-assisted electromagnet needle tracking coupled with ultrasound. A 6-degree of freedom electromagnetic position tracker was attached to the ultrasound probe that allowed the system to detect the position and orientation of the probe in the magnetic field. The tracked ultrasound probe was used to find the posterior superior iliac spine. Subsequently, 3 points were captured to register the ultrasound image with the CT or magnetic resonance image scan. Moreover, after the registration was obtained, the navigation system visualized the tracked needle relative to the CT scan in real-time using 2 orthogonal multi-planar reconstructions centered at the tracked needle tip. Conversely, a recent study revealed that fluoroscopically guided injections had 30% accuracy compared to ultrasound guided injections, which tripled the accuracy percentage. This novel technique exhibited an accurate needle guidance injection precision of 98% while advancing to the piriformis muscle and avoiding the sciatic nerve. The mean (± SD) procedure time was 19.08 (± 4.9) minutes. This technique allows for electromagnetic instrument tip tracking with real-time 3-D guidance to the selected target. As with any new technique, a learning curve is expected; however, this technique could offer an alternative, minimizing radiation exposure. PMID:23703429

  2. Registration of 3D and multispectral data for the study of cultural heritage surfaces.

    PubMed

    Chane, Camille Simon; Schütze, Rainer; Boochs, Frank; Marzani, Franck S

    2013-01-01

    We present a technique for the multi-sensor registration of featureless datasets based on the photogrammetric tracking of the acquisition systems in use. This method is developed for the in situ study of cultural heritage objects and is tested by digitizing a small canvas successively with a 3D digitization system and a multispectral camera while simultaneously tracking the acquisition systems with four cameras and using a cubic target frame with a side length of 500 mm. The achieved tracking accuracy is better than 0.03 mm spatially and 0.150 mrad angularly. This allows us to seamlessly register the 3D acquisitions and to project the multispectral acquisitions on the 3D model. PMID:23322103

  3. Light field display and 3D image reconstruction

    NASA Astrophysics Data System (ADS)

    Iwane, Toru

    2016-06-01

    Light field optics and its applications become rather popular in these days. With light field optics or light field thesis, real 3D space can be described in 2D plane as 4D data, which we call as light field data. This process can be divided in two procedures. First, real3D scene is optically reduced with imaging lens. Second, this optically reduced 3D image is encoded into light field data. In later procedure we can say that 3D information is encoded onto a plane as 2D data by lens array plate. This transformation is reversible and acquired light field data can be decoded again into 3D image with the arrayed lens plate. "Refocusing" (focusing image on your favorite point after taking a picture), light-field camera's most popular function, is some kind of sectioning process from encoded 3D data (light field data) to 2D image. In this paper at first I show our actual light field camera and our 3D display using acquired and computer-simulated light field data, on which real 3D image is reconstructed. In second I explain our data processing method whose arithmetic operation is performed not in Fourier domain but in real domain. Then our 3D display system is characterized by a few features; reconstructed image is of finer resolutions than density of arrayed lenses and it is not necessary to adjust lens array plate to flat display on which light field data is displayed.

  4. 3D Imaging with Structured Illumination for Advanced Security Applications

    SciTech Connect

    Birch, Gabriel Carisle; Dagel, Amber Lynn; Kast, Brian A.; Smith, Collin S.

    2015-09-01

    Three-dimensional (3D) information in a physical security system is a highly useful dis- criminator. The two-dimensional data from an imaging systems fails to provide target dis- tance and three-dimensional motion vector, which can be used to reduce nuisance alarm rates and increase system effectiveness. However, 3D imaging devices designed primarily for use in physical security systems are uncommon. This report discusses an architecture favorable to physical security systems; an inexpensive snapshot 3D imaging system utilizing a simple illumination system. The method of acquiring 3D data, tests to understand illumination de- sign, and software modifications possible to maximize information gathering capability are discussed.

  5. Bi-planar 2D-to-3D registration in Fourier domain for stereoscopic x-ray motion tracking

    NASA Astrophysics Data System (ADS)

    Zosso, Dominique; Le Callennec, Benoît; Bach Cuadra, Meritxell; Aminian, Kamiar; Jolles, Brigitte M.; Thiran, Jean-Philippe

    2008-03-01

    In this paper we present a new method to track bone movements in stereoscopic X-ray image series of the knee joint. The method is based on two different X-ray image sets: a rotational series of acquisitions of the still subject knee that allows the tomographic reconstruction of the three-dimensional volume (model), and a stereoscopic image series of orthogonal projections as the subject performs movements. Tracking the movements of bones throughout the stereoscopic image series means to determine, for each frame, the best pose of every moving element (bone) previously identified in the 3D reconstructed model. The quality of a pose is reflected in the similarity between its theoretical projections and the actual radiographs. We use direct Fourier reconstruction to approximate the three-dimensional volume of the knee joint. Then, to avoid the expensive computation of digitally rendered radiographs (DRR) for pose recovery, we develop a corollary to the 3-dimensional central-slice theorem and reformulate the tracking problem in the Fourier domain. Under the hypothesis of parallel X-ray beams, the heavy 2D-to-3D registration of projections in the signal domain is replaced by efficient slice-to-volume registration in the Fourier domain. Focusing on rotational movements, the translation-relevant phase information can be discarded and we only consider scalar Fourier amplitudes. The core of our motion tracking algorithm can be implemented as a classical frame-wise slice-to-volume registration task. Results on both synthetic and real images confirm the validity of our approach.

  6. Full 3D microwave quasi-holographic imaging

    NASA Astrophysics Data System (ADS)

    Castelli, Juan-Carlos; Tardivel, Francois

    A full 3D quasi-holographic image processing technique developed by ONERA is described. A complex backscattering coefficient of a drone scale model was measured for discrete values of the 3D backscattered wave vector in a frequency range between 4.5-8 GHz. The 3D image processing is implemented on a HP 1000 mini-computer and will be part of LASER 2 software to be used in three RCS measurement indoor facilities.

  7. Volumetric image display for complex 3D data visualization

    NASA Astrophysics Data System (ADS)

    Tsao, Che-Chih; Chen, Jyh Shing

    2000-05-01

    A volumetric image display is a new display technology capable of displaying computer generated 3D images in a volumetric space. Many viewers can walk around the display and see the image from omni-directions simultaneously without wearing any glasses. The image is real and possesses all major elements in both physiological and psychological depth cues. Due to the volumetric nature of its image, the VID can provide the most natural human-machine interface in operations involving 3D data manipulation and 3D targets monitoring. The technology creates volumetric 3D images by projecting a series of profiling images distributed in the space form a volumetric image because of the after-image effect of human eyes. Exemplary applications in biomedical image visualization were tested on a prototype display, using different methods to display a data set from Ct-scans. The features of this display technology make it most suitable for applications that require quick understanding of the 3D relations, need frequent spatial interactions with the 3D images, or involve time-varying 3D data. It can also be useful for group discussion and decision making.

  8. On Alternative Approaches to 3D Image Perception: Monoscopic 3D Techniques

    NASA Astrophysics Data System (ADS)

    Blundell, Barry G.

    2015-06-01

    In the eighteenth century, techniques that enabled a strong sense of 3D perception to be experienced without recourse to binocular disparities (arising from the spatial separation of the eyes) underpinned the first significant commercial sales of 3D viewing devices and associated content. However following the advent of stereoscopic techniques in the nineteenth century, 3D image depiction has become inextricably linked to binocular parallax and outside the vision science and arts communities relatively little attention has been directed towards earlier approaches. Here we introduce relevant concepts and terminology and consider a number of techniques and optical devices that enable 3D perception to be experienced on the basis of planar images rendered from a single vantage point. Subsequently we allude to possible mechanisms for non-binocular parallax based 3D perception. Particular attention is given to reviewing areas likely to be thought-provoking to those involved in 3D display development, spatial visualization, HCI, and other related areas of interdisciplinary research.

  9. Automated 2D-3D registration of a radiograph and a cone beam CT using line-segment enhancement

    SciTech Connect

    Munbodh, Reshma; Jaffray, David A.; Moseley, Douglas J.; Chen Zhe; Knisely, Jonathan P.S.; Cathier, Pascal; Duncan, James S.

    2006-05-15

    The objective of this study was to develop a fully automated two-dimensional (2D)-three-dimensional (3D) registration framework to quantify setup deviations in prostate radiation therapy from cone beam CT (CBCT) data and a single AP radiograph. A kilovoltage CBCT image and kilovoltage AP radiograph of an anthropomorphic phantom of the pelvis were acquired at 14 accurately known positions. The shifts in the phantom position were subsequently estimated by registering digitally reconstructed radiographs (DRRs) from the 3D CBCT scan to the AP radiographs through the correlation of enhanced linear image features mainly representing bony ridges. Linear features were enhanced by filtering the images with ''sticks,'' short line segments which are varied in orientation to achieve the maximum projection value at every pixel in the image. The mean (and standard deviations) of the absolute errors in estimating translations along the three orthogonal axes in millimeters were 0.134 (0.096) AP(out-of-plane), 0.021 (0.023) ML and 0.020 (0.020) SI. The corresponding errors for rotations in degrees were 0.011 (0.009) AP, 0.029 (0.016) ML (out-of-plane), and 0.030 (0.028) SI (out-of-plane). Preliminary results with megavoltage patient data have also been reported. The results suggest that it may be possible to enhance anatomic features that are common to DRRs from a CBCT image and a single AP radiography of the pelvis for use in a completely automated and accurate 2D-3D registration framework for setup verification in prostate radiotherapy. This technique is theoretically applicable to other rigid bony structures such as the cranial vault or skull base and piecewise rigid structures such as the spine.

  10. 3D augmented reality with integral imaging display

    NASA Astrophysics Data System (ADS)

    Shen, Xin; Hua, Hong; Javidi, Bahram

    2016-06-01

    In this paper, a three-dimensional (3D) integral imaging display for augmented reality is presented. By implementing the pseudoscopic-to-orthoscopic conversion method, elemental image arrays with different capturing parameters can be transferred into the identical format for 3D display. With the proposed merging algorithm, a new set of elemental images for augmented reality display is generated. The newly generated elemental images contain both the virtual objects and real world scene with desired depth information and transparency parameters. The experimental results indicate the feasibility of the proposed 3D augmented reality with integral imaging.

  11. A new method for real-time co-registration of 3D coronary angiography and intravascular ultrasound or optical coherence tomography.

    PubMed

    Carlier, Stéphane; Didday, Rich; Slots, Tristan; Kayaert, Peter; Sonck, Jeroen; El-Mourad, Mike; Preumont, Nicolas; Schoors, Dany; Van Camp, Guy

    2014-06-01

    We present a new clinically practical method for online co-registration of 3D quantitative coronary angiography (QCA) and intravascular ultrasound (IVUS) or optical coherence tomography (OCT). The workflow is based on two modified commercially available software packages. Reconstruction steps are explained and compared to previously available methods. The feasibility for different clinical scenarios is illustrated. The co-registration appears accurate, robust and induced a minimal delay on the normal cath lab activities. This new method is based on the 3D angiographic reconstruction of the catheter path and does not require operator's identification of landmarks to establish the image synchronization. PMID:24746102

  12. FPGA-based real-time anisotropic diffusion filtering of 3D ultrasound images

    NASA Astrophysics Data System (ADS)

    Castro-Pareja, Carlos R.; Dandekar, Omkar S.; Shekhar, Raj

    2005-02-01

    Three-dimensional ultrasonic imaging, especially the emerging real-time version of it, is particularly valuable in medical applications such as echocardiography, obstetrics and surgical navigation. A known problem with ultrasound images is their high level of speckle noise. Anisotropic diffusion filtering has been shown to be effective in enhancing the visual quality of 3D ultrasound images and as preprocessing prior to advanced image processing. However, due to its arithmetic complexity and the sheer size of 3D ultrasound images, it is not possible to perform online, real-time anisotropic diffusion filtering using standard software implementations. We present an FPGA-based architecture that allows performing anisotropic diffusion filtering of 3D images at acquisition rates, thus enabling the use of this filtering technique in real-time applications, such as visualization, registration and volume rendering.

  13. Quantitative 3D Optical Imaging: Applications in Dosimetry and Biophysics

    NASA Astrophysics Data System (ADS)

    Thomas, Andrew Stephen

    Optical-CT has been shown to be a potentially useful imaging tool for the two very different spheres of biologists and radiation therapy physicists, but it has yet to live up to that potential. In radiation therapy, researchers have used optical-CT for the readout of 3D dosimeters, but it is yet to be a clinically relevant tool as the technology is too slow to be considered practical. Biologists have used the technique for structural imaging, but have struggled with emission tomography as the reality of photon attenuation for both excitation and emission have made the images quantitatively irrelevant. Dosimetry. The DLOS (Duke Large field of view Optical-CT Scanner) was designed and constructed to make 3D dosimetry utilizing optical-CT a fast and practical tool while maintaining the accuracy of readout of the previous, slower readout technologies. Upon construction/optimization/implementation of several components including a diffuser, band pass filter, registration mount & fluid filtration system the dosimetry system provides high quality data comparable to or exceeding that of commercial products. In addition, a stray light correction algorithm was tested and implemented. The DLOS in combination with the 3D dosimeter it was designed for, PREAGETM, then underwent rigorous commissioning and benchmarking tests validating its performance against gold standard data including a set of 6 irradiations. DLOS commissioning tests resulted in sub-mm isotropic spatial resolution (MTF >0.5 for frequencies of 1.5lp/mm) and a dynamic range of ˜60dB. Flood field uniformity was 10% and stable after 45minutes. Stray light proved to be small, due to telecentricity, but even the residual can be removed through deconvolution. Benchmarking tests showed the mean 3D passing gamma rate (3%, 3mm, 5% dose threshold) over the 6 benchmark data sets was 97.3% +/- 0.6% (range 96%-98%) scans totaling ˜10 minutes, indicating excellent ability to perform 3D dosimetry while improving the speed of

  14. Towards real-time 3D US-CT registration on the beating heart for guidance of minimally invasive cardiac interventions

    NASA Astrophysics Data System (ADS)

    Li, Feng; Lang, Pencilla; Rajchl, Martin; Chen, Elvis C. S.; Guiraudon, Gerard; Peters, Terry M.

    2012-02-01

    Compared to conventional open-heart surgeries, minimally invasive cardiac interventions cause less trauma and sideeffects to patients. However, the direct view of surgical targets and tools is usually not available in minimally invasive procedures, which makes image-guided navigation systems essential. The choice of imaging modalities used in the navigation systems must consider the capability of imaging soft tissues, spatial and temporal resolution, compatibility and flexibility in the OR, and financial cost. In this paper, we propose a new means of guidance for minimally invasive cardiac interventions using 3D real-time ultrasound images to show the intra-operative heart motion together with preoperative CT image(s) employed to demonstrate high-quality 3D anatomical context. We also develop a method to register intra-operative ultrasound and pre-operative CT images in close to real-time. The registration method has two stages. In the first, anatomical features are segmented from the first frame of ultrasound images and the CT image(s). A feature based registration is used to align those features. The result of this is used as an initialization in the second stage, in which a mutual information based registration is used to register every ultrasound frame to the CT image(s). A GPU based implementation is used to accelerate the registration.

  15. Fast voxel-based 2D/3D registration algorithm using a volume rendering method based on the shear-warp factorization

    NASA Astrophysics Data System (ADS)

    Weese, Juergen; Goecke, Roland; Penney, Graeme P.; Desmedt, Paul; Buzug, Thorsten M.; Schumann, Heidrun

    1999-05-01

    2D/3D registration makes it possible to use pre-operative CT scans for navigation purposes during X-ray fluoroscopy guided interventions. We present a fast voxel-based method for this registration task, which uses a recently introduced similarity measure (pattern intensity). This measure is especially suitable for 2D/3D registration, because it is robust with respect to structures such as a stent visible in the X-ray fluoroscopy image but not in the CT scan. The method uses only a part of the CT scan for the generation of digitally reconstructed radiographs (DRRs) to accelerate their computation. Nevertheless, computation time is crucial for intra-operative application and a further speed-up is required, because numerous DRRs must be computed. For that reason, the suitability of different volume rendering methods for 2D/3D registration has been investigated. A method based on the shear-warp factorization of the viewing transformation turned out to be especially suitable and builds the basis of the registration algorithm. The algorithm has been applied to images of a spine phantom and to clinical images. For comparison, registration results have been calculated using ray-casting. The shear-warp factorization based rendering method accelerates registration by a factor of up to seven compared to ray-casting without degrading registration accuracy. Using a vertebra as feature for registration, computation time is in the range of 3-4s (Sun UltraSparc, 300 MHz) which is acceptable for intra-operative application.

  16. Consequences of Intermodality Registration Errors for Intramodality 3D Ultrasound IGRT.

    PubMed

    van der Meer, Skadi; Seravalli, Enrica; Fontanarosa, Davide; Bloemen-van Gurp, Esther J; Verhaegen, Frank

    2016-08-01

    Intramodality ultrasound image-guided radiotherapy systems compare daily ultrasound to reference ultrasound images. Nevertheless, because the actual treatment planning is based on a reference computed tomography image, and not on a reference ultrasound image, their accuracy depends partially on the correct intermodality registration of the reference ultrasound and computed tomography images for treatment planning. The error propagation in daily patient positioning due to potential registration errors at the planning stage was assessed in this work. Five different scenarios were simulated involving shifts or rotations of ultrasound or computed tomography images. The consequences of several workflow procedures were tested with a phantom setup. As long as the reference ultrasound and computed tomography images are made to match, the patient will be in the correct treatment position. In an example with a phantom measurement, the accuracy of the performed manual fusion was found to be ≤2 mm. In clinical practice, manual registration of patient images is expected to be more difficult. Uncorrected mismatches will lead to a systematically incorrect final patient position because there will be no indication that there was a misregistration between the computed tomography and reference ultrasound images. In the treatment room, the fusion with the computed tomography image will not be visible and based on the ultrasound images the patient position seems correct. PMID:26048909

  17. 2D and 3D MALDI-imaging: conceptual strategies for visualization and data mining.

    PubMed

    Thiele, Herbert; Heldmann, Stefan; Trede, Dennis; Strehlow, Jan; Wirtz, Stefan; Dreher, Wolfgang; Berger, Judith; Oetjen, Janina; Kobarg, Jan Hendrik; Fischer, Bernd; Maass, Peter

    2014-01-01

    registration techniques. Different strategies for automatic serial image registration applied to MS datasets are outlined in detail. The third image modality is histology driven, i.e. a digital scan of the histological stained slices in high-resolution. After fusion of reconstructed scan images and MRI the slice-related coordinates of the mass spectra can be propagated into 3D-space. After image registration of scan images and histological stained images, the anatomical information from histology is fused with the mass spectra from MALDI-MSI. As a result of the described pipeline we have a set of 3 dimensional images representing the same anatomies, i.e. the reconstructed slice scans, the spectral images as well as corresponding clustering results, and the acquired MRI. Great emphasis is put on the fact that the co-registered MRI providing anatomical details improves the interpretation of 3D MALDI images. The ability to relate mass spectrometry derived molecular information with in vivo and in vitro imaging has potentially important implications. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. PMID:23467008

  18. Registration of interferometric SAR images

    NASA Technical Reports Server (NTRS)

    Lin, Qian; Vesecky, John F.; Zebker, Howard A.

    1992-01-01

    Interferometric synthetic aperture radar (INSAR) is a new way of performing topography mapping. Among the factors critical to mapping accuracy is the registration of the complex SAR images from repeated orbits. A new algorithm for registering interferometric SAR images is presented. A new figure of merit, the average fluctuation function of the phase difference image, is proposed to evaluate the fringe pattern quality. The process of adjusting the registration parameters according to the fringe pattern quality is optimized through a downhill simplex minimization algorithm. The results of applying the proposed algorithm to register two pairs of Seasat SAR images with a short baseline (75 m) and a long baseline (500 m) are shown. It is found that the average fluctuation function is a very stable measure of fringe pattern quality allowing very accurate registration.

  19. Weakly supervised automatic segmentation and 3D modeling of the knee joint from MR images

    NASA Astrophysics Data System (ADS)

    Amami, Amal; Ben Azouz, Zouhour

    2013-12-01

    Automatic segmentation and 3D modeling of the knee joint from MR images, is a challenging task. Most of the existing techniques require the tedious manual segmentation of a training set of MRIs. We present an approach that necessitates the manual segmentation of one MR image. It is based on a volumetric active appearance model. First, a dense tetrahedral mesh is automatically created on a reference MR image that is arbitrary selected. Second, a pairwise non-rigid registration between each MRI from a training set and the reference MRI is computed. The non-rigid registration is based on a piece-wise affine deformation using the created tetrahedral mesh. The minimum description length is then used to bring all the MR images into a correspondence. An average image and tetrahedral mesh, as well as a set of main modes of variations, are generated using the established correspondence. Any manual segmentation of the average MRI can be mapped to other MR images using the AAM. The proposed approach has the advantage of simultaneously generating 3D reconstructions of the surface as well as a 3D solid model of the knee joint. The generated surfaces and tetrahedral meshes present the interesting property of fulfilling a correspondence between different MR images. This paper shows preliminary results of the proposed approach. It demonstrates the automatic segmentation and 3D reconstruction of a knee joint obtained by mapping a manual segmentation of a reference image.

  20. Comparison of anatomic coordinate systems with rigid multi-resolution 3D registration for the reproducible positioning of analysis volumes of interest in QCT

    NASA Astrophysics Data System (ADS)

    Eisa, Fabian; Museyko, Oleg; Hess, Andreas; Kalender, Willi A.; Engelke, Klaus

    2010-03-01

    In this study we compared two approaches that have recently been used to minimize precision errors in 3D quantitative computed tomography (QCT) images of the hip and the spine in order to optimize the detection of longitudinal changes in bone mineral density (BMD). In 30 subjects we obtained baseline and 1 year follow-up 3D CT scans of the proximal femur and the spine. QCT analysis was applied to a variety of volumes of interest (VOIs) automatically positioned relative to anatomic coordinate systems (ACS). In the first approach (A1) baseline and follow-up scans were analyzed independently. In the second approach (A2) a 3D versor-based rigid intensity registration method was applied to match baseline and follow-up images, and the baseline ACS was mapped on the follow-up image using the registration transformation. Afterwards, the analysis VOIs were again independently calculated for baseline and follow-up images. There were no significant differences of percent BMD changes between baseline and follow-up images between A1 and A2 for any of the VOIs investigated. With advanced image processing methods a time-consuming 3D registration between baseline and follow-up images before the analysis does not improve analysis precision compared to the use of anatomical coordinate systems.

  1. 3D model-based still image object categorization

    NASA Astrophysics Data System (ADS)

    Petre, Raluca-Diana; Zaharia, Titus

    2011-09-01

    This paper proposes a novel recognition scheme algorithm for semantic labeling of 2D object present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to infer the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Results obtained show promising performances, with recognition rate up to 84%, which opens interesting perspectives in terms of semantic metadata extraction from still images/videos.

  2. 3D Cell Culture Imaging with Digital Holographic Microscopy

    NASA Astrophysics Data System (ADS)

    Dimiduk, Thomas; Nyberg, Kendra; Almeda, Dariela; Koshelva, Ekaterina; McGorty, Ryan; Kaz, David; Gardel, Emily; Auguste, Debra; Manoharan, Vinothan

    2011-03-01

    Cells in higher organisms naturally exist in a three dimensional (3D) structure, a fact sometimes ignored by in vitro biological research. Confinement to a two dimensional culture imposes significant deviations from the native 3D state. One of the biggest obstacles to wider use of 3D cultures is the difficulty of 3D imaging. The confocal microscope, the dominant 3D imaging instrument, is expensive, bulky, and light-intensive; live cells can be observed for only a short time before they suffer photodamage. We present an alternative 3D imaging techinque, digital holographic microscopy, which can capture 3D information with axial resolution better than 2 μm in a 100 μm deep volume. Capturing a 3D image requires only a single camera exposure with a sub-millisecond laser pulse, allowing us to image cell cultures using five orders of magnitude less light energy than with confocal. This can be done with hardware costing ~ 1000. We use the instrument to image growth of MCF7 breast cancer cells and p. pastoras yeast. We acknowledge support from NSF GRFP.

  3. 3D imaging using projected dynamic fringes

    NASA Astrophysics Data System (ADS)

    Shaw, Michael M.; Atkinson, John T.; Harvey, David M.; Hobson, Clifford A.; Lalor, Michael J.

    1994-12-01

    An instrument capable of highly accurate, non-contact range measurement has been developed, which is based upon the principle of projected rotating fringes. More usually known as dynamic fringe projection, it is this technique which is exploited in the dynamic automated range transducer (DART). The intensity waveform seen at the target and sensed by the detector, contains all the information required to accurately determine the fringe order. This, in turn, allows the range to be evaluated by the substitution of the fringe order into a simple algebraic expression. Various techniques for the analysis of the received intensity signals from the surface of the target have been investigated. The accuracy to which the range can be determined ultimately depends upon the accuracy to which the fringe order can be evaluated from the received intensity waveform. It is extremely important to be able to closely determine the fractional fringe order value, to achieve any meaningful results. This paper describes a number of techniques which have been used to analyze the intensity waveform, and critically appraises their suitability in terms of accuracy and required speed of operation. This work also examines the development of this instrument for three-dimensional measurements based on single or two beam systems. Using CCD array detectors, a 3-D range map of the object's surface may be produced.

  4. Imaging hypoxia using 3D photoacoustic spectroscopy

    NASA Astrophysics Data System (ADS)

    Stantz, Keith M.

    2010-02-01

    Purpose: The objective is to develop a multivariate in vivo hemodynamic model of tissue oxygenation (MiHMO2) based on 3D photoacoustic spectroscopy. Introduction: Low oxygen levels, or hypoxia, deprives cancer cells of oxygen and confers resistance to irradiation, some chemotherapeutic drugs, and oxygen-dependent therapies (phototherapy) leading to treatment failure and poor disease-free and overall survival. For example, clinical studies of patients with breast carcinomas, cervical cancer, and head and neck carcinomas (HNC) are more likely to suffer local reoccurrence and metastasis if their tumors are hypoxic. A novel method to non invasively measure tumor hypoxia, identify its type, and monitor its heterogeneity is devised by measuring tumor hemodynamics, MiHMO2. Material and Methods: Simulations are performed to compare tumor pO2 levels and hypoxia based on physiology - perfusion, fractional plasma volume, fractional cellular volume - and its hemoglobin status - oxygen saturation and hemoglobin concentration - based on in vivo measurements of breast, prostate, and ovarian tumors. Simulations of MiHMO2 are performed to assess the influence of scanner resolutions and different mathematic models of oxygen delivery. Results: Sensitivity of pO2 and hypoxic fraction to photoacoustic scanner resolution and dependencies on model complexity will be presented using hemodynamic parameters for different tumors. Conclusions: Photoacoustic CT spectroscopy provides a unique ability to monitor hemodynamic and cellular physiology in tissue, which can be used to longitudinally monitor tumor oxygenation and its response to anti-angiogenic therapies.

  5. Highway 3D model from image and lidar data

    NASA Astrophysics Data System (ADS)

    Chen, Jinfeng; Chu, Henry; Sun, Xiaoduan

    2014-05-01

    We present a new method of highway 3-D model construction developed based on feature extraction in highway images and LIDAR data. We describe the processing road coordinate data that connect the image frames to the coordinates of the elevation data. Image processing methods are used to extract sky, road, and ground regions as well as significant objects (such as signs and building fronts) in the roadside for the 3D model. LIDAR data are interpolated and processed to extract the road lanes as well as other features such as trees, ditches, and elevated objects to form the 3D model. 3D geometry reasoning is used to match the image features to the 3D model. Results from successive frames are integrated to improve the final model.

  6. Compression of 3D integral images using wavelet decomposition

    NASA Astrophysics Data System (ADS)

    Mazri, Meriem; Aggoun, Amar

    2003-06-01

    This paper presents a wavelet-based lossy compression technique for unidirectional 3D integral images (UII). The method requires the extraction of different viewpoint images from the integral image. A single viewpoint image is constructed by extracting one pixel from each microlens, then each viewpoint image is decomposed using a Two Dimensional Discrete Wavelet Transform (2D-DWT). The resulting array of coefficients contains several frequency bands. The lower frequency bands of the viewpoint images are assembled and compressed using a 3 Dimensional Discrete Cosine Transform (3D-DCT) followed by Huffman coding. This will achieve decorrelation within and between 2D low frequency bands from the different viewpoint images. The remaining higher frequency bands are Arithmetic coded. After decoding and decompression of the viewpoint images using an inverse 3D-DCT and an inverse 2D-DWT, each pixel from every reconstructed viewpoint image is put back into its original position within the microlens to reconstruct the whole 3D integral image. Simulations were performed on a set of four different grey level 3D UII using a uniform scalar quantizer with deadzone. The results for the average of the four UII intensity distributions are presented and compared with previous use of 3D-DCT scheme. It was found that the algorithm achieves better rate-distortion performance, with respect to compression ratio and image quality at very low bit rates.

  7. Relative Scale Estimation and 3D Registration of Multi-Modal Geometry Using Growing Least Squares.

    PubMed

    Mellado, Nicolas; Dellepiane, Matteo; Scopigno, Roberto

    2016-09-01

    The advent of low cost scanning devices and the improvement of multi-view stereo techniques have made the acquisition of 3D geometry ubiquitous. Data gathered from different devices, however, result in large variations in detail, scale, and coverage. Registration of such data is essential before visualizing, comparing and archiving them. However, state-of-the-art methods for geometry registration cannot be directly applied due to intrinsic differences between the models, e.g., sampling, scale, noise. In this paper we present a method for the automatic registration of multi-modal geometric data, i.e., acquired by devices with different properties (e.g., resolution, noise, data scaling). The method uses a descriptor based on Growing Least Squares, and is robust to noise, variation in sampling density, details, and enables scale-invariant matching. It allows not only the measurement of the similarity between the geometry surrounding two points, but also the estimation of their relative scale. As it is computed locally, it can be used to analyze large point clouds composed of millions of points. We implemented our approach in two registration procedures (assisted and automatic) and applied them successfully on a number of synthetic and real cases. We show that using our method, multi-modal models can be automatically registered, regardless of their differences in noise, detail, scale, and unknown relative coverage. PMID:26672045

  8. Diffractive optical element for creating visual 3D images.

    PubMed

    Goncharsky, Alexander; Goncharsky, Anton; Durlevich, Svyatoslav

    2016-05-01

    A method is proposed to compute and synthesize the microrelief of a diffractive optical element to produce a new visual security feature - the vertical 3D/3D switch effect. The security feature consists in the alternation of two 3D color images when the diffractive element is tilted up/down. Optical security elements that produce the new security feature are synthesized using electron-beam technology. Sample optical security elements are manufactured that produce 3D to 3D visual switch effect when illuminated by white light. Photos and video records of the vertical 3D/3D switch effect of real optical elements are presented. The optical elements developed can be replicated using standard equipment employed for manufacturing security holograms. The new optical security feature is easy to control visually, safely protected against counterfeit, and designed to protect banknotes, documents, ID cards, etc. PMID:27137530

  9. 3D scene reconstruction from multi-aperture images

    NASA Astrophysics Data System (ADS)

    Mao, Miao; Qin, Kaihuai

    2014-04-01

    With the development of virtual reality, there is a growing demand for 3D modeling of real scenes. This paper proposes a novel 3D scene reconstruction framework based on multi-aperture images. Our framework consists of four parts. Firstly, images with different apertures are captured via programmable aperture. Secondly, we use SIFT method for feature point matching. Then we exploit binocular stereo vision to calculate camera parameters and 3D positions of matching points, forming a sparse 3D scene model. Finally, we apply patch-based multi-view stereo to obtain a dense 3D scene model. Experimental results show that our method is practical and effective to reconstruct dense 3D scene.

  10. Dedicated 3D photoacoustic breast imaging

    PubMed Central

    Kruger, Robert A.; Kuzmiak, Cherie M.; Lam, Richard B.; Reinecke, Daniel R.; Del Rio, Stephen P.; Steed, Doreen

    2013-01-01

    Purpose: To report the design and imaging methodology of a photoacoustic scanner dedicated to imaging hemoglobin distribution throughout a human breast. Methods: The authors developed a dedicated breast photoacoustic mammography (PAM) system using a spherical detector aperture based on our previous photoacoustic tomography scanner. The system uses 512 detectors with rectilinear scanning. The scan shape is a spiral pattern whose radius varies from 24 to 96 mm, thereby allowing a field of view that accommodates a wide range of breast sizes. The authors measured the contrast-to-noise ratio (CNR) using a target comprised of 1-mm dots printed on clear plastic. Each dot absorption coefficient was approximately the same as a 1-mm thickness of whole blood at 756 nm, the output wavelength of the Alexandrite laser used by this imaging system. The target was immersed in varying depths of an 8% solution of stock Liposyn II-20%, which mimics the attenuation of breast tissue (1.1 cm−1). The spatial resolution was measured using a 6 μm-diameter carbon fiber embedded in agar. The breasts of four healthy female volunteers, spanning a range of breast size from a brassiere C cup to a DD cup, were imaged using a 96-mm spiral protocol. Results: The CNR target was clearly visualized to a depth of 53 mm. Spatial resolution, which was estimated from the full width at half-maximum of a profile across the PAM image of a carbon fiber, was 0.42 mm. In the four human volunteers, the vasculature was well visualized throughout the breast tissue, including to the chest wall. Conclusions: CNR, lateral field-of-view and penetration depth of our dedicated PAM scanning system is sufficient to image breasts as large as 1335 mL, which should accommodate up to 90% of the women in the United States. PMID:24320471

  11. 3-D seismic imaging of complex geologies

    SciTech Connect

    Womble, D.E.; Dosanjh, S.S.; VanDyke, J.P.; Oldfield, R.A.; Greenberg, D.S.

    1995-02-01

    We present three codes for the Intel Paragon that address the problem of three-dimensional seismic imaging of complex geologies. The first code models acoustic wave propagation and can be used to generate data sets to calibrate and validate seismic imaging codes. This code reported the fastest timings for acoustic wave propagation codes at a recent SEG (Society of Exploration Geophysicists) meeting. The second code implements a Kirchhoff method for pre-stack depth migration. Development of this code is almost complete, and preliminary results are presented. The third code implements a wave equation approach to seismic migration and is a Paragon implementation of a code from the ARCO Seismic Benchmark Suite.

  12. 3-D capacitance density imaging system

    DOEpatents

    Fasching, G.E.

    1988-03-18

    A three-dimensional capacitance density imaging of a gasified bed or the like in a containment vessel is achieved using a plurality of electrodes provided circumferentially about the bed in levels and along the bed in channels. The electrodes are individually and selectively excited electrically at each level to produce a plurality of current flux field patterns generated in the bed at each level. The current flux field patterns are suitably sensed and a density pattern of the bed at each level determined. By combining the determined density patterns at each level, a three-dimensional density image of the bed is achieved. 7 figs.

  13. Polarimetric 3D integral imaging in photon-starved conditions.

    PubMed

    Carnicer, Artur; Javidi, Bahram

    2015-03-01

    We develop a method for obtaining 3D polarimetric integral images from elemental images recorded in low light illumination conditions. Since photon-counting images are very sparse, calculation of the Stokes parameters and the degree of polarization should be handled carefully. In our approach, polarimetric 3D integral images are generated using the Maximum Likelihood Estimation and subsequently reconstructed by means of a Total Variation Denoising filter. In this way, polarimetric results are comparable to those obtained in conventional illumination conditions. We also show that polarimetric information retrieved from photon starved images can be used in 3D object recognition problems. To the best of our knowledge, this is the first report on 3D polarimetric photon counting integral imaging. PMID:25836861

  14. Image performance evaluation of a 3D surgical imaging platform

    NASA Astrophysics Data System (ADS)

    Petrov, Ivailo E.; Nikolov, Hristo N.; Holdsworth, David W.; Drangova, Maria

    2011-03-01

    The O-arm (Medtronic Inc.) is a multi-dimensional surgical imaging platform. The purpose of this study was to perform a quantitative evaluation of the imaging performance of the O-arm in an effort to understand its potential for future nonorthopedic applications. Performance of the reconstructed 3D images was evaluated, using a custom-built phantom, in terms of resolution, linearity, uniformity and geometrical accuracy. Both the standard (SD, 13 s) and high definition (HD, 26 s) modes were evaluated, with the imaging parameters set to image the head (120 kVp, 100 mAs and 150 mAs, respectively). For quantitative noise characterization, the images were converted to Hounsfield units (HU) off-line. Measurement of the modulation transfer function revealed a limiting resolution (at 10% level) of 1.0 mm-1 in the axial dimension. Image noise varied between 15 and 19 HU for the HD and SD modes, respectively. Image intensities varied linearly over the measured range, up to 1300 HU. Geometric accuracy was maintained in all three dimensions over the field of view. The present study has evaluated the performance characteristics of the O-arm, and demonstrates feasibility for use in interventional applications and quantitative imaging tasks outside those currently targeted by the manufacturer. Further improvements to the reconstruction algorithms may further enhance performance for lower-contrast applications.

  15. Phase Sensitive Cueing for 3D Objects in Overhead Images

    SciTech Connect

    Paglieroni, D

    2005-02-04

    Locating specific 3D objects in overhead images is an important problem in many remote sensing applications. 3D objects may contain either one connected component or multiple disconnected components. Solutions must accommodate images acquired with diverse sensors at various times of the day, in various seasons of the year, or under various weather conditions. Moreover, the physical manifestation of a 3D object with fixed physical dimensions in an overhead image is highly dependent on object physical dimensions, object position/orientation, image spatial resolution, and imaging geometry (e.g., obliqueness). This paper describes a two-stage computer-assisted approach for locating 3D objects in overhead images. In the matching stage, the computer matches models of 3D objects to overhead images. The strongest degree of match over all object orientations is computed at each pixel. Unambiguous local maxima in the degree of match as a function of pixel location are then found. In the cueing stage, the computer sorts image thumbnails in descending order of figure-of-merit and presents them to human analysts for visual inspection and interpretation. The figure-of-merit associated with an image thumbnail is computed from the degrees of match to a 3D object model associated with unambiguous local maxima that lie within the thumbnail. This form of computer assistance is invaluable when most of the relevant thumbnails are highly ranked, and the amount of inspection time needed is much less for the highly ranked thumbnails than for images as a whole.

  16. 3D laser imaging for concealed object identification

    NASA Astrophysics Data System (ADS)

    Berechet, Ion; Berginc, Gérard; Berechet, Stefan

    2014-09-01

    This paper deals with new optical non-conventional 3D laser imaging. Optical non-conventional imaging explores the advantages of laser imaging to form a three-dimensional image of the scene. 3D laser imaging can be used for threedimensional medical imaging, topography, surveillance, robotic vision because of ability to detect and recognize objects. In this paper, we present a 3D laser imaging for concealed object identification. The objective of this new 3D laser imaging is to provide the user a complete 3D reconstruction of the concealed object from available 2D data limited in number and with low representativeness. The 2D laser data used in this paper come from simulations that are based on the calculation of the laser interactions with the different interfaces of the scene of interest and from experimental results. We show the global 3D reconstruction procedures capable to separate objects from foliage and reconstruct a threedimensional image of the considered object. In this paper, we present examples of reconstruction and completion of three-dimensional images and we analyse the different parameters of the identification process such as resolution, the scenario of camouflage, noise impact and lacunarity degree.

  17. A 3D Level Set Method for Microwave Breast Imaging

    PubMed Central

    Colgan, Timothy J.; Hagness, Susan C.; Van Veen, Barry D.

    2015-01-01

    Objective Conventional inverse-scattering algorithms for microwave breast imaging result in moderate resolution images with blurred boundaries between tissues. Recent 2D numerical microwave imaging studies demonstrate that the use of a level set method preserves dielectric boundaries, resulting in a more accurate, higher resolution reconstruction of the dielectric properties distribution. Previously proposed level set algorithms are computationally expensive and thus impractical in 3D. In this paper we present a computationally tractable 3D microwave imaging algorithm based on level sets. Methods We reduce the computational cost of the level set method using a Jacobian matrix, rather than an adjoint method, to calculate Frechet derivatives. We demonstrate the feasibility of 3D imaging using simulated array measurements from 3D numerical breast phantoms. We evaluate performance by comparing full 3D reconstructions to those from a conventional microwave imaging technique. We also quantitatively assess the efficacy of our algorithm in evaluating breast density. Results Our reconstructions of 3D numerical breast phantoms improve upon those of a conventional microwave imaging technique. The density estimates from our level set algorithm are more accurate than those of conventional microwave imaging, and the accuracy is greater than that reported for mammographic density estimation. Conclusion Our level set method leads to a feasible level of computational complexity for full 3D imaging, and reconstructs the heterogeneous dielectric properties distribution of the breast more accurately than conventional microwave imaging methods. Significance 3D microwave breast imaging using a level set method is a promising low-cost, non-ionizing alternative to current breast imaging techniques. PMID:26011863

  18. Critical comparison of 3D imaging approaches

    SciTech Connect

    Bennett, C L

    1999-06-03

    Currently three imaging spectrometer architectures, tunable filter, dispersive, and Fourier transform, are viable for imaging the universe in three dimensions. There are domains of greatest utility for each of these architectures. The optimum choice among the various alternative architectures is dependent on the nature of the desired observations, the maturity of the relevant technology, and the character of the backgrounds. The domain appropriate for each of the alternatives is delineated; both for instruments having ideal performance as well as for instrumentation based on currently available technology. The environment and science objectives for the Next Generation Space Telescope will be used as a specific representative case to provide a basis for comparison of the various alternatives.

  19. 3-D Imaging Based, Radiobiological Dosimetry

    PubMed Central

    Sgouros, George; Frey, Eric; Wahl, Richard; He, Bin; Prideaux, Andrew; Hobbs, Robert

    2008-01-01

    Targeted radionuclide therapy holds promise as a new treatment against cancer. Advances in imaging are making it possible to evaluate the spatial distribution of radioactivity in tumors and normal organs over time. Matched anatomical imaging such as combined SPECT/CT and PET/CT have also made it possible to obtain tissue density information in conjunction with the radioactivity distribution. Coupled with sophisticated iterative reconstruction algorithims, these advances have made it possible to perform highly patient-specific dosimetry that also incorporates radiobiological modeling. Such sophisticated dosimetry techniques are still in the research investigation phase. Given the attendant logistical and financial costs, a demonstrated improvement in patient care will be a prerequisite for the adoption of such highly-patient specific internal dosimetry methods. PMID:18662554

  20. Acoustic 3D imaging of dental structures

    SciTech Connect

    Lewis, D.K.; Hume, W.R.; Douglass, G.D.

    1997-02-01

    Our goals for the first year of this three dimensional electodynamic imaging project was to determine how to combine flexible, individual addressable; preprocessing of array source signals; spectral extrapolation or received signals; acoustic tomography codes; and acoustic propagation modeling code. We investigated flexible, individually addressable acoustic array material to find the best match in power, sensitivity and cost and settled on PVDF sheet arrays and 3-1 composite material.

  1. Towards 3D lidar point cloud registration improvement using optimal neighborhood knowledge

    NASA Astrophysics Data System (ADS)

    Gressin, Adrien; Mallet, Clément; Demantké, Jérôme; David, Nicolas

    2013-05-01

    Automatic 3D point cloud registration is a main issue in computer vision and remote sensing. One of the most commonly adopted solution is the well-known Iterative Closest Point (ICP) algorithm. This standard approach performs a fine registration of two overlapping point clouds by iteratively estimating the transformation parameters, assuming good a priori alignment is provided. A large body of literature has proposed many variations in order to improve each step of the process (namely selecting, matching, rejecting, weighting and minimizing). The aim of this paper is to demonstrate how the knowledge of the shape that best fits the local geometry of each 3D point neighborhood can improve the speed and the accuracy of each of these steps. First we present the geometrical features that form the basis of this work. These low-level attributes indeed describe the neighborhood shape around each 3D point. They allow to retrieve the optimal size to analyze the neighborhoods at various scales as well as the privileged local dimension (linear, planar, or volumetric). Several variations of each step of the ICP process are then proposed and analyzed by introducing these features. Such variants are compared on real datasets with the original algorithm in order to retrieve the most efficient algorithm for the whole process. Therefore, the method is successfully applied to various 3D lidar point clouds from airborne, terrestrial, and mobile mapping systems. Improvement for two ICP steps has been noted, and we conclude that our features may not be relevant for very dissimilar object samplings.

  2. Registration of Optical Data with High-Resolution SAR Data: a New Image Registration Solution

    NASA Astrophysics Data System (ADS)

    Bahr, T.; Jin, X.

    2013-04-01

    Accurate image-to-image registration is critical for many image processing workflows, including georeferencing, change detection, data fusion, image mosaicking, DEM extraction and 3D modeling. Users need a solution to generate tie points accurately and geometrically align the images automatically. To solve these requirements we developed the Hybrid Powered Auto-Registration Engine (HyPARE). HyPARE combines all available spatial reference information with a number of image registration approaches to improve the accuracy, performance, and automation of tie point generation and image registration. We demonstrate this approach by the registration of a Pléiades-1a image with a TerraSAR-X SpotLight image of Hannover, Germany. Registering images with different modalities is a known challenging problem; e.g. manual tie point collection is prone to error. The registration engine allows to generate tie points automatically, using an optimized mutual information-based matching method. It produces more accurate results than traditional correlation-based measures. In this example the resulting tie points are well distributed across the overlapping areas, even as the images have significant local feature differences.

  3. MR image denoising method for brain surface 3D modeling

    NASA Astrophysics Data System (ADS)

    Zhao, De-xin; Liu, Peng-jie; Zhang, De-gan

    2014-11-01

    Three-dimensional (3D) modeling of medical images is a critical part of surgical simulation. In this paper, we focus on the magnetic resonance (MR) images denoising for brain modeling reconstruction, and exploit a practical solution. We attempt to remove the noise existing in the MR imaging signal and preserve the image characteristics. A wavelet-based adaptive curve shrinkage function is presented in spherical coordinates system. The comparative experiments show that the denoising method can preserve better image details and enhance the coefficients of contours. Using these denoised images, the brain 3D visualization is given through surface triangle mesh model, which demonstrates the effectiveness of the proposed method.

  4. 3D-spectral domain computational imaging

    NASA Astrophysics Data System (ADS)

    Anderson, Trevor; Segref, Armin; Frisken, Grant; Ferra, Herman; Lorenser, Dirk; Frisken, Steven

    2016-03-01

    We present a proof-of-concept experiment utilizing a novel "snap-shot" spectral domain OCT technique that captures a phase coherent volume in a single frame. The sample is illuminated with a collimated beam of 75 μm diameter and the back-reflected light is analyzed by a 2-D matrix of spectral interferograms. A key challenge that is addressed is simultaneously maintaining lateral and spectral phase coherence over the imaged volume in the presence of sample motion. Digital focusing is demonstrated for 5.0 μm lateral resolution over an 800 μm axial range.

  5. Morphometrics, 3D Imaging, and Craniofacial Development.

    PubMed

    Hallgrimsson, Benedikt; Percival, Christopher J; Green, Rebecca; Young, Nathan M; Mio, Washington; Marcucio, Ralph

    2015-01-01

    Recent studies have shown how volumetric imaging and morphometrics can add significantly to our understanding of morphogenesis, the developmental basis for variation, and the etiology of structural birth defects. On the other hand, the complex questions and diverse imaging data in developmental biology present morphometrics with more complex challenges than applications in virtually any other field. Meeting these challenges is necessary in order to understand the mechanistic basis for variation in complex morphologies. This chapter reviews the methods and theory that enable the application of modern landmark-based morphometrics to developmental biology and craniofacial development, in particular. We discuss the theoretical foundations of morphometrics as applied to development and review the basic approaches to the quantification of morphology. Focusing on geometric morphometrics, we discuss the principal statistical methods for quantifying and comparing morphological variation and covariation structure within and among groups. Finally, we discuss the future directions for morphometrics in developmental biology that will be required for approaches that enable quantitative integration across the genotype-phenotype map. PMID:26589938

  6. 3D quantitative phase imaging of neural networks using WDT

    NASA Astrophysics Data System (ADS)

    Kim, Taewoo; Liu, S. C.; Iyer, Raj; Gillette, Martha U.; Popescu, Gabriel

    2015-03-01

    White-light diffraction tomography (WDT) is a recently developed 3D imaging technique based on a quantitative phase imaging system called spatial light interference microscopy (SLIM). The technique has achieved a sub-micron resolution in all three directions with high sensitivity granted by the low-coherence of a white-light source. Demonstrations of the technique on single cell imaging have been presented previously; however, imaging on any larger sample, including a cluster of cells, has not been demonstrated using the technique. Neurons in an animal body form a highly complex and spatially organized 3D structure, which can be characterized by neuronal networks or circuits. Currently, the most common method of studying the 3D structure of neuron networks is by using a confocal fluorescence microscope, which requires fluorescence tagging with either transient membrane dyes or after fixation of the cells. Therefore, studies on neurons are often limited to samples that are chemically treated and/or dead. WDT presents a solution for imaging live neuron networks with a high spatial and temporal resolution, because it is a 3D imaging method that is label-free and non-invasive. Using this method, a mouse or rat hippocampal neuron culture and a mouse dorsal root ganglion (DRG) neuron culture have been imaged in order to see the extension of processes between the cells in 3D. Furthermore, the tomogram is compared with a confocal fluorescence image in order to investigate the 3D structure at synapses.

  7. Real-time estimation of FLE statistics for 3-D tracking with point-based registration.

    PubMed

    Wiles, Andrew D; Peters, Terry M

    2009-09-01

    Target registration error (TRE) has become a widely accepted error metric in point-based registration since the error metric was introduced in the 1990s. It is particularly prominent in image-guided surgery (IGS) applications where point-based registration is used in both image registration and optical tracking. In point-based registration, the TRE is a function of the fiducial marker geometry, location of the target and the fiducial localizer error (FLE). While the first two items are easily obtained, the FLE is usually estimated using an a priori technique and applied without any knowledge of real-time information. However, if the FLE can be estimated in real-time, particularly as it pertains to optical tracking, then the TRE can be estimated more robustly. In this paper, a method is presented where the FLE statistics are estimated from the latest measurement of the fiducial registration error (FRE) statistics. The solution is obtained by solving a linear system of equations of the form Ax=b for each marker at each time frame where x are the six independent FLE covariance parameters and b are the six independent estimated FRE covariance parameters. The A matrix is only a function of the tool geometry and hence the inverse of the matrix can be computed a priori and used at each instant in which the FLE estimation is required, hence minimizing the level of computation at each frame. When using a good estimate of the FRE statistics, Monte Carlo simulations demonstrate that the root mean square of the FLE can be computed within a range of 70-90 microm. Robust estimation of the TRE for an optically tracked tool, using a good estimate of the FLE, will provide two enhancements in IGS. First, better patient to image registration will be obtained by using the TRE of the optical tool as a weighting factor of point-based registration used to map the patient to image space. Second, the directionality of the TRE can be relayed back to the surgeon giving the surgeon the option

  8. Accommodation response measurements for integral 3D image

    NASA Astrophysics Data System (ADS)

    Hiura, H.; Mishina, T.; Arai, J.; Iwadate, Y.

    2014-03-01

    We measured accommodation responses under integral photography (IP), binocular stereoscopic, and real object display conditions, and viewing conditions of binocular and monocular viewing conditions. The equipment we used was an optometric device and a 3D display. We developed the 3D display for IP and binocular stereoscopic images that comprises a high-resolution liquid crystal display (LCD) and a high-density lens array. The LCD has a resolution of 468 dpi and a diagonal size of 4.8 inches. The high-density lens array comprises 106 x 69 micro lenses that have a focal length of 3 mm and diameter of 1 mm. The lenses are arranged in a honeycomb pattern. The 3D display was positioned 60 cm from an observer under IP and binocular stereoscopic display conditions. The target was presented at eight depth positions relative to the 3D display: 15, 10, and 5 cm in front of the 3D display, on the 3D display panel, and 5, 10, 15 and 30 cm behind the 3D display under the IP and binocular stereoscopic display conditions. Under the real object display condition, the target was displayed on the 3D display panel, and the 3D display was placed at the eight positions. The results suggest that the IP image induced more natural accommodation responses compared to the binocular stereoscopic image. The accommodation responses of the IP image were weaker than those of a real object; however, they showed a similar tendency with those of the real object under the two viewing conditions. Therefore, IP can induce accommodation to the depth positions of 3D images.

  9. Non-rigid registration of medical images based on estimation of deformation states.

    PubMed

    Marami, Bahram; Sirouspour, Shahin; Capson, David W

    2014-11-21

    A unified framework for automatic non-rigid 3D-3D and 3D-2D registration of medical images with static and dynamic deformations is proposed in this paper. The problem of non-rigid image registration is approached as a classical state estimation problem using a generic deformation model for the soft tissue. The registration technique employs a dynamic linear elastic continuum mechanics model of the tissue deformation, which is discretized using the finite element method. In the proposed method, the registration is achieved through a Kalman-like filtering process, which incorporates information from the deformation model and a vector of observation prediction errors computed from an intensity-based similarity/distance metric between images. With this formulation, single and multiple-modality, 3D-3D and 3D-2D image registration problems can all be treated within the same framework. The performance of the proposed registration technique was evaluated in a number of different registration scenarios. First, 3D magnetic resonance (MR) images of uncompressed and compressed breast tissue were co-registered. 3D MR images of the uncompressed breast tissue were also registered to a sequence of simulated 2D interventional MR images of the compressed breast. Finally, the registration algorithm was employed to dynamically track a target sub-volume inside the breast tissue during the process of the biopsy needle insertion based on registering pre-insertion 3D MR images to a sequence of real-time simulated 2D interventional MR images. Registration results indicate that the proposed method can be effectively employed for the registration of medical images in image-guided procedures, such as breast biopsy in which the tissue undergoes static and dynamic deformations. PMID:25350234

  10. Non-rigid registration of medical images based on estimation of deformation states

    NASA Astrophysics Data System (ADS)

    Marami, Bahram; Sirouspour, Shahin; Capson, David W.

    2014-11-01

    A unified framework for automatic non-rigid 3D-3D and 3D-2D registration of medical images with static and dynamic deformations is proposed in this paper. The problem of non-rigid image registration is approached as a classical state estimation problem using a generic deformation model for the soft tissue. The registration technique employs a dynamic linear elastic continuum mechanics model of the tissue deformation, which is discretized using the finite element method. In the proposed method, the registration is achieved through a Kalman-like filtering process, which incorporates information from the deformation model and a vector of observation prediction errors computed from an intensity-based similarity/distance metric between images. With this formulation, single and multiple-modality, 3D-3D and 3D-2D image registration problems can all be treated within the same framework. The performance of the proposed registration technique was evaluated in a number of different registration scenarios. First, 3D magnetic resonance (MR) images of uncompressed and compressed breast tissue were co-registered. 3D MR images of the uncompressed breast tissue were also registered to a sequence of simulated 2D interventional MR images of the compressed breast. Finally, the registration algorithm was employed to dynamically track a target sub-volume inside the breast tissue during the process of the biopsy needle insertion based on registering pre-insertion 3D MR images to a sequence of real-time simulated 2D interventional MR images. Registration results indicate that the proposed method can be effectively employed for the registration of medical images in image-guided procedures, such as breast biopsy in which the tissue undergoes static and dynamic deformations.

  11. Matching Aerial Images to 3d Building Models Based on Context-Based Geometric Hashing

    NASA Astrophysics Data System (ADS)

    Jung, J.; Bang, K.; Sohn, G.; Armenakis, C.

    2016-06-01

    In this paper, a new model-to-image framework to automatically align a single airborne image with existing 3D building models using geometric hashing is proposed. As a prerequisite process for various applications such as data fusion, object tracking, change detection and texture mapping, the proposed registration method is used for determining accurate exterior orientation parameters (EOPs) of a single image. This model-to-image matching process consists of three steps: 1) feature extraction, 2) similarity measure and matching, and 3) adjustment of EOPs of a single image. For feature extraction, we proposed two types of matching cues, edged corner points representing the saliency of building corner points with associated edges and contextual relations among the edged corner points within an individual roof. These matching features are extracted from both 3D building and a single airborne image. A set of matched corners are found with given proximity measure through geometric hashing and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on co-linearity equations. The result shows that acceptable accuracy of single image's EOP can be achievable by the proposed registration approach as an alternative to labour-intensive manual registration process.

  12. Image based 3D city modeling : Comparative study

    NASA Astrophysics Data System (ADS)

    Singh, S. P.; Jain, K.; Mandla, V. R.

    2014-06-01

    3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing rapidly for various engineering and non-engineering applications. Generally four main image based approaches were used for virtual 3D city models generation. In first approach, researchers were used Sketch based modeling, second method is Procedural grammar based modeling, third approach is Close range photogrammetry based modeling and fourth approach is mainly based on Computer Vision techniques. SketchUp, CityEngine, Photomodeler and Agisoft Photoscan are the main softwares to represent these approaches respectively. These softwares have different approaches & methods suitable for image based 3D city modeling. Literature study shows that till date, there is no complete such type of comparative study available to create complete 3D city model by using images. This paper gives a comparative assessment of these four image based 3D modeling approaches. This comparative study is mainly based on data acquisition methods, data processing techniques and output 3D model products. For this research work, study area is the campus of civil engineering department, Indian Institute of Technology, Roorkee (India). This 3D campus acts as a prototype for city. This study also explains various governing parameters, factors and work experiences. This research work also gives a brief introduction, strengths and weakness of these four image based techniques. Some personal comment is also given as what can do or what can't do from these softwares. At the last, this study shows; it concluded that, each and every software has some advantages and limitations. Choice of software depends on user requirements of 3D project. For normal visualization project, SketchUp software is a good option. For 3D documentation record, Photomodeler gives good result. For Large city

  13. Registration Of SAR Images With Multisensor Images

    NASA Technical Reports Server (NTRS)

    Evans, Diane L.; Burnette, Charles F.; Van Zyl, Jakob J.

    1993-01-01

    Semiautomated technique intended primarily to facilitate registration of polarimetric synthetic-aperture-radar (SAR) images with other images of same or partly overlapping terrain while preserving polarization information conveyed by SAR data. Technique generally applicable in sense one or both of images to be registered with each other generated by polarimetric or nonpolarimetric SAR, infrared radiometry, conventional photography, or any other applicable sensing method.

  14. Medical image registration using sparse coding of image patches.

    PubMed

    Afzali, Maryam; Ghaffari, Aboozar; Fatemizadeh, Emad; Soltanian-Zadeh, Hamid

    2016-06-01

    Image registration is a basic task in medical image processing applications like group analysis and atlas construction. Similarity measure is a critical ingredient of image registration. Intensity distortion of medical images is not considered in most previous similarity measures. Therefore, in the presence of bias field distortions, they do not generate an acceptable registration. In this paper, we propose a sparse based similarity measure for mono-modal images that considers non-stationary intensity and spatially-varying distortions. The main idea behind this measure is that the aligned image is constructed by an analysis dictionary trained using the image patches. For this purpose, we use "Analysis K-SVD" to train the dictionary and find the sparse coefficients. We utilize image patches to construct the analysis dictionary and then we employ the proposed sparse similarity measure to find a non-rigid transformation using free form deformation (FFD). Experimental results show that the proposed approach is able to robustly register 2D and 3D images in both simulated and real cases. The proposed method outperforms other state-of-the-art similarity measures and decreases the transformation error compared to the previous methods. Even in the presence of bias field distortion, the proposed method aligns images without any preprocessing. PMID:27085311

  15. Visualization of 3D images from multiple texel images created from fused LADAR/digital imagery

    NASA Astrophysics Data System (ADS)

    Killpack, Cody C.; Budge, Scott E.

    2015-05-01

    The ability to create 3D models, using registered texel images (fused ladar and digital imagery), is an important topic in remote sensing. These models are automatically generated by matching multiple texel images into a single common reference frame. However, rendering a sequence of independently registered texel images often provides challenges. Although accurately registered, the model textures are often incorrectly overlapped and interwoven when using standard rendering techniques. Consequently, corrections must be done after all the primitives have been rendered, by determining the best texture for any viewable fragment in the model. Determining the best texture is difficult, as each texel image remains independent after registration. The depth data is not merged to form a single 3D mesh, thus eliminating the possibility of generating a fused texture atlas. It is therefore necessary to determine which textures are overlapping and how to best combine them dynamically during the render process. The best texture for a particular pixel can be defined using 3D geometric criteria, in conjunction with a real-time, view-dependent ranking algorithm. As a result, overlapping texture fragments can now be hidden, exposed, or blended according to their computed measure of reliability.

  16. Imaging fault zones using 3D seismic image processing techniques

    NASA Astrophysics Data System (ADS)

    Iacopini, David; Butler, Rob; Purves, Steve

    2013-04-01

    Significant advances in structural analysis of deep water structure, salt tectonic and extensional rift basin come from the descriptions of fault system geometries imaged in 3D seismic data. However, even where seismic data are excellent, in most cases the trajectory of thrust faults is highly conjectural and still significant uncertainty exists as to the patterns of deformation that develop between the main faults segments, and even of the fault architectures themselves. Moreover structural interpretations that conventionally define faults by breaks and apparent offsets of seismic reflectors are commonly conditioned by a narrow range of theoretical models of fault behavior. For example, almost all interpretations of thrust geometries on seismic data rely on theoretical "end-member" behaviors where concepts as strain localization or multilayer mechanics are simply avoided. Yet analogue outcrop studies confirm that such descriptions are commonly unsatisfactory and incomplete. In order to fill these gaps and improve the 3D visualization of deformation in the subsurface, seismic attribute methods are developed here in conjunction with conventional mapping of reflector amplitudes (Marfurt & Chopra, 2007)). These signal processing techniques recently developed and applied especially by the oil industry use variations in the amplitude and phase of the seismic wavelet. These seismic attributes improve the signal interpretation and are calculated and applied to the entire 3D seismic dataset. In this contribution we will show 3D seismic examples of fault structures from gravity-driven deep-water thrust structures and extensional basin systems to indicate how 3D seismic image processing methods can not only build better the geometrical interpretations of the faults but also begin to map both strain and damage through amplitude/phase properties of the seismic signal. This is done by quantifying and delineating the short-range anomalies on the intensity of reflector amplitudes

  17. Robust image registration of biological microscopic images.

    PubMed

    Wang, Ching-Wei; Ka, Shuk-Man; Chen, Ann

    2014-01-01

    Image registration of biological data is challenging as complex deformation problems are common. Possible deformation effects can be caused in individual data preparation processes, involving morphological deformations, stain variations, stain artifacts, rotation, translation, and missing tissues. The combining deformation effects tend to make existing automatic registration methods perform poor. In our experiments on serial histopathological images, the six state of the art image registration techniques, including TrakEM2, SURF + affine transformation, UnwarpJ, bUnwarpJ, CLAHE + bUnwarpJ and BrainAligner, achieve no greater than 70% averaged accuracies, while the proposed method achieves 91.49% averaged accuracy. The proposed method has also been demonstrated to be significantly better in alignment of laser scanning microscope brain images and serial ssTEM images than the benchmark automatic approaches (p < 0.001). The contribution of this study is to introduce a fully automatic, robust and fast image registration method for 2D image registration. PMID:25116443

  18. Optical 3D watermark based digital image watermarking for telemedicine

    NASA Astrophysics Data System (ADS)

    Li, Xiao Wei; Kim, Seok Tae

    2013-12-01

    Region of interest (ROI) of a medical image is an area including important diagnostic information and must be stored without any distortion. This algorithm for application of watermarking technique for non-ROI of the medical image preserving ROI. The paper presents a 3D watermark based medical image watermarking scheme. In this paper, a 3D watermark object is first decomposed into 2D elemental image array (EIA) by a lenslet array, and then the 2D elemental image array data is embedded into the host image. The watermark extraction process is an inverse process of embedding. The extracted EIA through the computational integral imaging reconstruction (CIIR) technique, the 3D watermark can be reconstructed. Because the EIA is composed of a number of elemental images possesses their own perspectives of a 3D watermark object. Even though the embedded watermark data badly damaged, the 3D virtual watermark can be successfully reconstructed. Furthermore, using CAT with various rule number parameters, it is possible to get many channels for embedding. So our method can recover the weak point having only one transform plane in traditional watermarking methods. The effectiveness of the proposed watermarking scheme is demonstrated with the aid of experimental results.

  19. EISCAT Aperture Synthesis Imaging (EASI _3D) for the EISCAT_3D Project

    NASA Astrophysics Data System (ADS)

    La Hoz, Cesar; Belyey, Vasyl

    2012-07-01

    Aperture Synthesis Imaging Radar (ASIR) is one of the technologies adopted by the EISCAT_3D project to endow it with imaging capabilities in 3-dimensions that includes sub-beam resolution. Complemented by pulse compression, it will provide 3-dimensional images of certain types of incoherent scatter radar targets resolved to about 100 metres at 100 km range, depending on the signal-to-noise ratio. This ability will open new research opportunities to map small structures associated with non-homogeneous, unstable processes such as aurora, summer and winter polar radar echoes (PMSE and PMWE), Natural Enhanced Ion Acoustic Lines (NEIALs), structures excited by HF ionospheric heating, meteors, space debris, and others. The underlying physico-mathematical principles of the technique are the same as the technique employed in radioastronomy to image stellar objects; both require sophisticated inversion techniques to obtain reliable images.

  20. 3D city models completion by fusing lidar and image data

    NASA Astrophysics Data System (ADS)

    Grammatikopoulos, L.; Kalisperakis, I.; Petsa, E.; Stentoumis, C.

    2015-05-01

    A fundamental step in the generation of visually detailed 3D city models is the acquisition of high fidelity 3D data. Typical approaches employ DSM representations usually derived from Lidar (Light Detection and Ranging) airborne scanning or image based procedures. In this contribution, we focus on the fusion of data from both these methods in order to enhance or complete them. Particularly, we combine an existing Lidar and orthomosaic dataset (used as reference), with a new aerial image acquisition (including both vertical and oblique imagery) of higher resolution, which was carried out in the area of Kallithea, in Athens, Greece. In a preliminary step, a digital orthophoto and a DSM is generated from the aerial images in an arbitrary reference system, by employing a Structure from Motion and dense stereo matching framework. The image-to-Lidar registration is performed by 2D feature (SIFT and SURF) extraction and matching among the two orthophotos. The established point correspondences are assigned with 3D coordinates through interpolation on the reference Lidar surface, are then backprojected onto the aerial images, and finally matched with 2D image features located in the vicinity of the backprojected 3D points. Consequently, these points serve as Ground Control Points with appropriate weights for final orientation and calibration of the images through a bundle adjustment solution. By these means, the aerial imagery which is optimally aligned to the reference dataset can be used for the generation of an enhanced and more accurately textured 3D city model.

  1. 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.

  2. Faster, higher quality volume visualization for 3D medical imaging

    NASA Astrophysics Data System (ADS)

    Kalvin, Alan D.; Laine, Andrew F.; Song, Ting

    2008-03-01

    The two major volume visualization methods used in biomedical applications are Maximum Intensity Projection (MIP) and Volume Rendering (VR), both of which involve the process of creating sets of 2D projections from 3D images. We have developed a new method for very fast, high-quality volume visualization of 3D biomedical images, based on the fact that the inverse of this process (transforming 2D projections into a 3D image) is essentially equivalent to tomographic image reconstruction. This new method uses the 2D projections acquired by the scanner, thereby obviating the need for the two computationally expensive steps currently required in the complete process of biomedical visualization, that is, (i) reconstructing the 3D image from 2D projection data, and (ii) computing the set of 2D projections from the reconstructed 3D image As well as improvements in computation speed, this method also results in improvements in visualization quality, and in the case of x-ray CT we can exploit this quality improvement to reduce radiation dosage. In this paper, demonstrate the benefits of developing biomedical visualization techniques by directly processing the sensor data acquired by body scanners, rather than by processing the image data reconstructed from the sensor data. We show results of using this approach for volume visualization for tomographic modalities, like x-ray CT, and as well as for MRI.

  3. Correction of a Depth-Dependent Lateral Distortion in 3D Super-Resolution Imaging.

    PubMed

    Carlini, Lina; Holden, Seamus J; Douglass, Kyle M; Manley, Suliana

    2015-01-01

    Three-dimensional (3D) localization-based super-resolution microscopy (SR) requires correction of aberrations to accurately represent 3D structure. Here we show how a depth-dependent lateral shift in the apparent position of a fluorescent point source, which we term `wobble`, results in warped 3D SR images and provide a software tool to correct this distortion. This system-specific, lateral shift is typically > 80 nm across an axial range of ~ 1 μm. A theoretical analysis based on phase retrieval data from our microscope suggests that the wobble is caused by non-rotationally symmetric phase and amplitude aberrations in the microscope's pupil function. We then apply our correction to the bacterial cytoskeletal protein FtsZ in live bacteria and demonstrate that the corrected data more accurately represent the true shape of this vertically-oriented ring-like structure. We also include this correction method in a registration procedure for dual-color, 3D SR data and show that it improves target registration error (TRE) at the axial limits over an imaging depth of 1 μm, yielding TRE values of < 20 nm. This work highlights the importance of correcting aberrations in 3D SR to achieve high fidelity between the measurements and the sample. PMID:26600467

  4. Correction of a Depth-Dependent Lateral Distortion in 3D Super-Resolution Imaging

    PubMed Central

    Manley, Suliana

    2015-01-01

    Three-dimensional (3D) localization-based super-resolution microscopy (SR) requires correction of aberrations to accurately represent 3D structure. Here we show how a depth-dependent lateral shift in the apparent position of a fluorescent point source, which we term `wobble`, results in warped 3D SR images and provide a software tool to correct this distortion. This system-specific, lateral shift is typically > 80 nm across an axial range of ~ 1 μm. A theoretical analysis based on phase retrieval data from our microscope suggests that the wobble is caused by non-rotationally symmetric phase and amplitude aberrations in the microscope’s pupil function. We then apply our correction to the bacterial cytoskeletal protein FtsZ in live bacteria and demonstrate that the corrected data more accurately represent the true shape of this vertically-oriented ring-like structure. We also include this correction method in a registration procedure for dual-color, 3D SR data and show that it improves target registration error (TRE) at the axial limits over an imaging depth of 1 μm, yielding TRE values of < 20 nm. This work highlights the importance of correcting aberrations in 3D SR to achieve high fidelity between the measurements and the sample. PMID:26600467

  5. 3D thermography imaging standardization technique for inflammation diagnosis

    NASA Astrophysics Data System (ADS)

    Ju, Xiangyang; Nebel, Jean-Christophe; Siebert, J. Paul

    2005-01-01

    We develop a 3D thermography imaging standardization technique to allow quantitative data analysis. Medical Digital Infrared Thermal Imaging is very sensitive and reliable mean of graphically mapping and display skin surface temperature. It allows doctors to visualise in colour and quantify temperature changes in skin surface. The spectrum of colours indicates both hot and cold responses which may co-exist if the pain associate with an inflammatory focus excites an increase in sympathetic activity. However, due to thermograph provides only qualitative diagnosis information, it has not gained acceptance in the medical and veterinary communities as a necessary or effective tool in inflammation and tumor detection. Here, our technique is based on the combination of visual 3D imaging technique and thermal imaging technique, which maps the 2D thermography images on to 3D anatomical model. Then we rectify the 3D thermogram into a view independent thermogram and conform it a standard shape template. The combination of these imaging facilities allows the generation of combined 3D and thermal data from which thermal signatures can be quantified.

  6. SNR analysis of 3D magnetic resonance tomosynthesis (MRT) imaging

    NASA Astrophysics Data System (ADS)

    Kim, Min-Oh; Kim, Dong-Hyun

    2012-03-01

    In conventional 3D Fourier transform (3DFT) MR imaging, signal-to-noise ratio (SNR) is governed by the well-known relationship of being proportional to the voxel size and square root of the imaging time. Here, we introduce an alternative 3D imaging approach, termed MRT (Magnetic Resonance Tomosynthesis), which can generate a set of tomographic MR images similar to multiple 2D projection images in x-ray. A multiple-oblique-view (MOV) pulse sequence is designed to acquire the tomography-like images used in tomosynthesis process and an iterative back-projection (IBP) reconstruction method is used to reconstruct 3D images. SNR analysis is performed and shows that resolution and SNR tradeoff is not governed as with typical 3DFT MR imaging case. The proposed method provides a higher SNR than the conventional 3D imaging method with a partial loss of slice-direction resolution. It is expected that this method can be useful for extremely low SNR cases.

  7. Midsagittal plane extraction from brain images based on 3D SIFT

    NASA Astrophysics Data System (ADS)

    Wu, Huisi; Wang, Defeng; Shi, Lin; Wen, Zhenkun; Ming, Zhong

    2014-03-01

    Midsagittal plane (MSP) extraction from 3D brain images is considered as a promising technique for human brain symmetry analysis. In this paper, we present a fast and robust MSP extraction method based on 3D scale-invariant feature transform (SIFT). Unlike the existing brain MSP extraction methods, which mainly rely on the gray similarity, 3D edge registration or parameterized surface matching to determine the fissure plane, our proposed method is based on distinctive 3D SIFT features, in which the fissure plane is determined by parallel 3D SIFT matching and iterative least-median of squares plane regression. By considering the relative scales, orientations and flipped descriptors between two 3D SIFT features, we propose a novel metric to measure the symmetry magnitude for 3D SIFT features. By clustering and indexing the extracted SIFT features using a k-dimensional tree (KD-tree) implemented on graphics processing units, we can match multiple pairs of 3D SIFT features in parallel and solve the optimal MSP on-the-fly. The proposed method is evaluated by synthetic and in vivo datasets, of normal and pathological cases, and validated by comparisons with the state-of-the-art methods. Experimental results demonstrated that our method has achieved a real-time performance with better accuracy yielding an average yaw angle error below 0.91° and an average roll angle error no more than 0.89°.

  8. 3D gesture recognition from serial range image

    NASA Astrophysics Data System (ADS)

    Matsui, Yasuyuki; Miyasaka, Takeo; Hirose, Makoto; Araki, Kazuo

    2001-10-01

    In this research, the recognition of gesture in 3D space is examined by using serial range images obtained by a real-time 3D measurement system developed in our laboratory. Using this system, it is possible to obtain time sequences of range, intensity and color data for a moving object in real-time without assigning markers to the targets. At first, gestures are tracked in 2D space by calculating 2D flow vectors at each points using an ordinal optical flow estimation method, based on time sequences of the intensity data. Then, location of each point after 2D movement is detected on the x-y plane using thus obtained 2D flow vectors. Depth information of each point after movement is then obtained from the range data and 3D flow vectors are assigned to each point. Time sequences of thus obtained 3D flow vectors allow us to track the 3D movement of the target. So, based on time sequences of 3D flow vectors of the targets, it is possible to classify the movement of the targets using continuous DP matching technique. This tracking of 3D movement using time sequences of 3D flow vectors may be applicable for a robust gesture recognition system.

  9. A 3D surface imaging system for assessing human obesity

    NASA Astrophysics Data System (ADS)

    Xu, B.; Yu, W.; Yao, M.; Yao, X.; Li, Q.; Pepper, M. R.; Freeland-Graves, J. H.

    2009-08-01

    The increasing prevalence of obesity suggests a need to develop a convenient, reliable and economical tool for assessment of this condition. Three-dimensional (3D) body surface imaging has emerged as an exciting technology for estimation of body composition. This paper presents a new 3D body imaging system, which was designed for enhanced portability, affordability, and functionality. In this system, stereo vision technology was used to satisfy the requirements for a simple hardware setup and fast image acquisitions. The portability of the system was created via a two-stand configuration, and the accuracy of body volume measurements was improved by customizing stereo matching and surface reconstruction algorithms that target specific problems in 3D body imaging. Body measurement functions dedicated to body composition assessment also were developed. The overall performance of the system was evaluated in human subjects by comparison to other conventional anthropometric methods, as well as air displacement plethysmography, for body fat assessment.

  10. 3D Image Display Courses for Information Media Students.

    PubMed

    Yanaka, Kazuhisa; Yamanouchi, Toshiaki

    2016-01-01

    Three-dimensional displays are used extensively in movies and games. These displays are also essential in mixed reality, where virtual and real spaces overlap. Therefore, engineers and creators should be trained to master 3D display technologies. For this reason, the Department of Information Media at the Kanagawa Institute of Technology has launched two 3D image display courses specifically designed for students who aim to become information media engineers and creators. PMID:26960028

  11. Hybrid segmentation framework for 3D medical image analysis

    NASA Astrophysics Data System (ADS)

    Chen, Ting; Metaxas, Dimitri N.

    2003-05-01

    Medical image segmentation is the process that defines the region of interest in the image volume. Classical segmentation methods such as region-based methods and boundary-based methods cannot make full use of the information provided by the image. In this paper we proposed a general hybrid framework for 3D medical image segmentation purposes. In our approach we combine the Gibbs Prior model, and the deformable model. First, Gibbs Prior models are applied onto each slice in a 3D medical image volume and the segmentation results are combined to a 3D binary masks of the object. Then we create a deformable mesh based on this 3D binary mask. The deformable model will be lead to the edge features in the volume with the help of image derived external forces. The deformable model segmentation result can be used to update the parameters for Gibbs Prior models. These methods will then work recursively to reach a global segmentation solution. The hybrid segmentation framework has been applied to images with the objective of lung, heart, colon, jaw, tumor, and brain. The experimental data includes MRI (T1, T2, PD), CT, X-ray, Ultra-Sound images. High quality results are achieved with relatively efficient time cost. We also did validation work using expert manual segmentation as the ground truth. The result shows that the hybrid segmentation may have further clinical use.

  12. 3-D Terahertz Synthetic-Aperture Imaging and Spectroscopy

    NASA Astrophysics Data System (ADS)

    Henry, Samuel C.

    Terahertz (THz) wavelengths have attracted recent interest in multiple disciplines within engineering and science. Situated between the infrared and the microwave region of the electromagnetic spectrum, THz energy can propagate through non-polar materials such as clothing or packaging layers. Moreover, many chemical compounds, including explosives and many drugs, reveal strong absorption signatures in the THz range. For these reasons, THz wavelengths have great potential for non-destructive evaluation and explosive detection. Three-dimensional (3-D) reflection imaging with considerable depth resolution is also possible using pulsed THz systems. While THz imaging (especially 3-D) systems typically operate in transmission mode, reflection offers the most practical configuration for standoff detection, especially for objects with high water content (like human tissue) which are opaque at THz frequencies. In this research, reflection-based THz synthetic-aperture (SA) imaging is investigated as a potential imaging solution. THz SA imaging results presented in this dissertation are unique in that a 2-D planar synthetic array was used to generate a 3-D image without relying on a narrow time-window for depth isolation cite [Shen 2005]. Novel THz chemical detection techniques are developed and combined with broadband THz SA capabilities to provide concurrent 3-D spectral imaging. All algorithms are tested with various objects and pressed pellets using a pulsed THz time-domain system in the Northwest Electromagnetics and Acoustics Research Laboratory (NEAR-Lab).

  13. Registration of untypical 3D objects in Polish cadastre - do we need 3D cadastre? / Rejestracja nietypowych obiektów 3D w polskim katastrze - czy istnieje potrzeba wdrożenia katastru 3D?

    NASA Astrophysics Data System (ADS)

    Marcin, Karabin

    2012-11-01

    Polish cadastral system consists of two registers: cadastre and land register. The cadastre register data on cadastral objects (land, buildings and premises) in particular location (in a two-dimensional coordinate system) and their attributes as well as data about the owners. The land register contains data concerned ownerships and other rights to the property. Registration of a land parcel without spatial objects located on the surface is not problematic. Registration of buildings and premises in typical cases is not a problem either. The situation becomes more complicated in cases of multiple use of space above the parcel and with more complex construction of the buildings. The paper presents rules concerning the registration of various untypical 3D objects located within the city of Warsaw. The analysis of the data concerning those objects registered in the cadastre and land register is presented in the paper. And this is the next part of the author's detailed research. The aim of this paper is to answer the question if we really need 3D cadastre in Poland. Polski system katastralny składa się z dwóch rejestrów: ewidencji gruntów i budynków (katastru nieruchomosci) oraz ksiąg wieczystych. W ewidencji gruntów i budynków (katastrze nieruchomości) rejestrowane są dane o położeniu (w dwuwymiarowym układzie współrzędnych), atrybuty oraz dane o właścicielach obiektów katastralnych (działek, budynków i lokali), w księgach wieczystych oprócz danych właścicielskich, inne prawa do nieruchomości. Rejestracja działki bez obiektów przestrzennych położonych na jej powierzchni nie stanowi problemu. Także rejestracja budynków i lokali w typowych przypadkach nie stanowi trudności. Sytuacja staje się bardziej skomplikowana w przypadku wielokrotnego użytkowania przestrzeni powyzej lub poniżej powierzchni działki oraz w przypadku budynków o złożonej konstrukcji. W artykule przedstawiono zasady związane z rejestracją nietypowych obiektów 3

  14. Computerized analysis of pelvic incidence from 3D images

    NASA Astrophysics Data System (ADS)

    Vrtovec, Tomaž; Janssen, Michiel M. A.; Pernuš, Franjo; Castelein, René M.; Viergever, Max A.

    2012-02-01

    The sagittal alignment of the pelvis can be evaluated by the angle of pelvic incidence (PI), which is constant for an arbitrary subject position and orientation and can be therefore compared among subjects in standing, sitting or supine position. In this study, PI was measured from three-dimensional (3D) computed tomography (CT) images of normal subjects that were acquired in supine position. A novel computerized method, based on image processing techniques, was developed to automatically determine the anatomical references required to measure PI, i.e. the centers of the femoral heads in 3D, and the center and inclination of the sacral endplate in 3D. Multiplanar image reformation was applied to obtain perfect sagittal views with all anatomical structures completely in line with the hip axis, from which PI was calculated. The resulting PI (mean+/-standard deviation) was equal to 46.6°+/-9.2° for male subjects (N = 189), 47.6°+/-10.7° for female subjects (N = 181), and 47.1°+/-10.0° for all subjects (N = 370). The obtained measurements of PI from 3D images were not biased by acquisition projection or structure orientation, because all anatomical structures were completely in line with the hip axis. The performed measurements in 3D therefore represent PI according to the actual geometrical relationships among anatomical structures of the sacrum, pelvis and hips, as observed from the perfect sagittal views.

  15. Single 3D cell segmentation from optical CT microscope images

    NASA Astrophysics Data System (ADS)

    Xie, Yiting; Reeves, Anthony P.

    2014-03-01

    The automated segmentation of the nucleus and cytoplasm regions in 3D optical CT microscope images has been achieved with two methods, a global threshold gradient based approach and a graph-cut approach. For the first method, the first two peaks of a gradient figure of merit curve are selected as the thresholds for cytoplasm and nucleus segmentation. The second method applies a graph-cut segmentation twice: the first identifies the nucleus region and the second identifies the cytoplasm region. Image segmentation of single cells is important for automated disease diagnostic systems. The segmentation methods were evaluated with 200 3D images consisting of 40 samples of 5 different cell types. The cell types consisted of columnar, macrophage, metaplastic and squamous human cells and cultured A549 cancer cells. The segmented cells were compared with both 2D and 3D reference images and the quality of segmentation was determined by the Dice Similarity Coefficient (DSC). In general, the graph-cut method had a superior performance to the gradient-based method. The graph-cut method achieved an average DSC of 86% and 72% for nucleus and cytoplasm segmentations respectively for the 2D reference images and 83% and 75% for the 3D reference images. The gradient method achieved an average DSC of 72% and 51% for nucleus and cytoplasm segmentation for the 2D reference images and 71% and 51% for the 3D reference images. The DSC of cytoplasm segmentation was significantly lower than for the nucleus since the cytoplasm was not differentiated as well by image intensity from the background.

  16. Spatio-temporal registration in multiplane MRI acquisitions for 3D colon motiliy analysis

    NASA Astrophysics Data System (ADS)

    Kutter, Oliver; Kirchhoff, Sonja; Berkovich, Marina; Reiser, Maximilian; Navab, Nassir

    2008-03-01

    In this paper we present a novel method for analyzing and visualizing dynamic peristaltic motion of the colon in 3D from two series of differently oriented 2D MRI images. To this end, we have defined an MRI examination protocol, and introduced methods for spatio-temporal alignment of the two MRI image series into a common reference. This represents the main contribution of this paper, which enables the 3D analysis of peristaltic motion. The objective is to provide a detailed insight into this complex motion, aiding in the diagnosis and characterization of colon motion disorders. We have applied the proposed spatio-temporal method on Cine MRI data sets of healthy volunteers. The results have been inspected and validated by an expert radiologist. Segmentation and cylindrical approximation of the colon results in a 4D visualization of the peristaltic motion.

  17. Image registration method for medical image sequences

    DOEpatents

    Gee, Timothy F.; Goddard, James S.

    2013-03-26

    Image registration of low contrast image sequences is provided. In one aspect, a desired region of an image is automatically segmented and only the desired region is registered. Active contours and adaptive thresholding of intensity or edge information may be used to segment the desired regions. A transform function is defined to register the segmented region, and sub-pixel information may be determined using one or more interpolation methods.

  18. Integrated optical 3D digital imaging based on DSP scheme

    NASA Astrophysics Data System (ADS)

    Wang, Xiaodong; Peng, Xiang; Gao, Bruce Z.

    2008-03-01

    We present a scheme of integrated optical 3-D digital imaging (IO3DI) based on digital signal processor (DSP), which can acquire range images independently without PC support. This scheme is based on a parallel hardware structure with aid of DSP and field programmable gate array (FPGA) to realize 3-D imaging. In this integrated scheme of 3-D imaging, the phase measurement profilometry is adopted. To realize the pipeline processing of the fringe projection, image acquisition and fringe pattern analysis, we present a multi-threads application program that is developed under the environment of DSP/BIOS RTOS (real-time operating system). Since RTOS provides a preemptive kernel and powerful configuration tool, with which we are able to achieve a real-time scheduling and synchronization. To accelerate automatic fringe analysis and phase unwrapping, we make use of the technique of software optimization. The proposed scheme can reach a performance of 39.5 f/s (frames per second), so it may well fit into real-time fringe-pattern analysis and can implement fast 3-D imaging. Experiment results are also presented to show the validity of proposed scheme.

  19. Utilization of 3-D elastic transformation in the registration of chest x-ray CT and whole body PET

    SciTech Connect

    Tai, Yuan-Chuan; Hoh, C.K.; Hoffman, E.J.

    1996-12-31

    X-ray CT is widely used for detection and localization of lesions in the thorax. Whole Body PET with 18-FDG is becoming accepted for staging of cancer because of its ability to detect malignancy. Combining information from these two modalities has a significant value to improve lung cancer staging and treatment planning. Due to the non-rigid nature of the thorax and the differences in the acquisition conventions, the subject is stretched non-uniformly and the images of these two modalities requires non-rigid transformation for proper registration. Techniques to register chest x-ray CT and Whole Body PET images were developed and evaluated. Accuracy of 3-D elastic transformation was tested by phantom study. Studies on patients with lung carcinoma were used to validate the technique in localizing the 18-FDG uptake and in correlating PET to x-ray CT images. The fused images showed an accurate alignment and provided confident identification of the detailed anatomy of the CT with the functional information of the PET images.

  20. A Unified Approach to Diffusion Direction Sensitive Slice Registration and 3-D DTI Reconstruction From Moving Fetal Brain Anatomy

    PubMed Central

    Fogtmann, Mads; Seshamani, Sharmishtaa; Kroenke, Christopher; Cheng, Xi; Chapman, Teresa; Wilm, Jakob; Rousseau, François

    2014-01-01

    This paper presents an approach to 3-D diffusion tensor image (DTI) reconstruction from multi-slice diffusion weighted (DW) magnetic resonance imaging acquisitions of the moving fetal brain. Motion scatters the slice measurements in the spatial and spherical diffusion domain with respect to the underlying anatomy. Previous image registration techniques have been described to estimate the between slice fetal head motion, allowing the reconstruction of 3-D a diffusion estimate on a regular grid using interpolation. We propose Approach to Unified Diffusion Sensitive Slice Alignment and Reconstruction (AUDiSSAR) that explicitly formulates a process for diffusion direction sensitive DW-slice-to-DTI-volume alignment. This also incorporates image resolution modeling to iteratively deconvolve the effects of the imaging point spread function using the multiple views provided by thick slices acquired in different anatomical planes. The algorithm is implemented using a multi-resolution iterative scheme and multiple real and synthetic data are used to evaluate the performance of the technique. An accuracy experiment using synthetically created motion data of an adult head and a experiment using synthetic motion added to sedated fetal monkey dataset show a significant improvement in motion-trajectory estimation compared to a state-of-the-art approaches. The performance of the method is then evaluated on challenging but clinically typical in utero fetal scans of four different human cases, showing improved rendition of cortical anatomy and extraction of white matter tracts. While the experimental work focuses on DTI reconstruction (second-order tensor model), the proposed reconstruction framework can employ any 5-D diffusion volume model that can be represented by the spatial parameterizations of an orientation distribution function. PMID:24108711

  1. A miniature high resolution 3-D imaging sonar.

    PubMed

    Josserand, Tim; Wolley, Jason

    2011-04-01

    This paper discusses the design and development of a miniature, high resolution 3-D imaging sonar. The design utilizes frequency steered phased arrays (FSPA) technology. FSPAs present a small, low-power solution to the problem of underwater imaging sonars. The technology provides a method to build sonars with a large number of beams without the proportional power, circuitry and processing complexity. The design differs from previous methods in that the array elements are manufactured from a monolithic material. With this technique the arrays are flat and considerably smaller element dimensions are achievable which allows for higher frequency ranges and smaller array sizes. In the current frequency range, the demonstrated array has ultra high image resolution (1″ range×1° azimuth×1° elevation) and small size (<3″×3″). The design of the FSPA utilizes the phasing-induced frequency-dependent directionality of a linear phased array to produce multiple beams in a forward sector. The FSPA requires only two hardware channels per array and can be arranged in single and multiple array configurations that deliver wide sector 2-D images. 3-D images can be obtained by scanning the array in a direction perpendicular to the 2-D image field and applying suitable image processing to the multiple scanned 2-D images. This paper introduces the 3-D FSPA concept, theory and design methodology. Finally, results from a prototype array are presented and discussed. PMID:21112066

  2. Automated segmentation of breast in 3-D MR images using a robust atlas.

    PubMed

    Khalvati, Farzad; Gallego-Ortiz, Cristina; Balasingham, Sharmila; Martel, Anne L

    2015-01-01

    This paper presents a robust atlas-based segmentation (ABS) algorithm for segmentation of the breast boundary in 3-D MR images. The proposed algorithm combines the well-known methodologies of ABS namely probabilistic atlas and atlas selection approaches into a single framework where two configurations are realized. The algorithm uses phase congruency maps to create an atlas which is robust to intensity variations. This allows an atlas derived from images acquired with one MR imaging sequence to be used to segment images acquired with a different MR imaging sequence and eliminates the need for intensity-based registration. Images acquired using a Dixon sequence were used to create an atlas which was used to segment both Dixon images (intra-sequence) and T1-weighted images (inter-sequence). In both cases, highly accurate results were achieved with the median Dice similarity coefficient values of 94% ±4% and 87 ±6.5%, respectively. PMID:25137725

  3. 3D reconstruction based on CT image and its application

    NASA Astrophysics Data System (ADS)

    Zhang, Jianxun; Zhang, Mingmin

    2004-03-01

    Reconstitute the 3-D model of the liver and its internal piping system and simulation of the liver surgical operation can increase the accurate and security of the liver surgical operation, attain a purpose for the biggest limit decrease surgical operation wound, shortening surgical operation time, increasing surgical operation succeeding rate, reducing medical treatment expenses and promoting patient recovering from illness. This text expatiated technology and method that the author constitutes 3-D the model of the liver and its internal piping system and simulation of the liver surgical operation according to the images of CT. The direct volume rendering method establishes 3D the model of the liver. Under the environment of OPENGL adopt method of space point rendering to display liver's internal piping system and simulation of the liver surgical operation. Finally, we adopt the wavelet transform method compressed the medical image data.

  4. 3-D Display Of Magnetic Resonance Imaging Of The Spine

    NASA Astrophysics Data System (ADS)

    Nelson, Alan C.; Kim, Yongmin; Haralick, Robert M.; Anderson, Paul A.; Johnson, Roger H.; DeSoto, Larry A.

    1988-06-01

    The original data is produced through standard magnetic resonance imaging (MRI) procedures with a surface coil applied to the lower back of a normal human subject. The 3-D spine image data consists of twenty-six contiguous slices with 256 x 256 pixels per slice. Two methods for visualization of the 3-D spine are explored. One method utilizes a verifocal mirror system which creates a true 3-D virtual picture of the object. Another method uses a standard high resolution monitor to simultaneously show the three orthogonal sections which intersect at any user-selected point within the object volume. We discuss the application of these systems in assessment of low back pain.

  5. Reconstruction of 3D scenes from sequences of images

    NASA Astrophysics Data System (ADS)

    Niu, Bei; Sang, Xinzhu; Chen, Duo; Cai, Yuanfa

    2013-08-01

    Reconstruction of three-dimensional (3D) scenes is an active research topic in the field of computer vision and 3D display. It's a challenge to model 3D objects rapidly and effectively. A 3D model can be extracted from multiple images. The system only requires a sequence of images taken with cameras without knowing the parameters of camera, which provide flexibility to a high degree. We focus on quickly merging point cloud of the object from depth map sequences. The whole system combines algorithms of different areas in computer vision, such as camera calibration, stereo correspondence, point cloud splicing and surface reconstruction. The procedure of 3D reconstruction is decomposed into a number of successive steps. Firstly, image sequences are received by the camera freely moving around the object. Secondly, the scene depth is obtained by a non-local stereo matching algorithm. The pairwise is realized with the Scale Invariant Feature Transform (SIFT) algorithm. An initial matching is then made for the first two images of the sequence. For the subsequent image that is processed with previous image, the point of interest corresponding to ones in previous images are refined or corrected. The vertical parallax between the images is eliminated. The next step is to calibrate camera, and intrinsic parameters and external parameters of the camera are calculated. Therefore, The relative position and orientation of camera are gotten. A sequence of depth maps are acquired by using a non-local cost aggregation method for stereo matching. Then point cloud sequence is achieved by the scene depths, which consists of point cloud model using the external parameters of camera and the point cloud sequence. The point cloud model is then approximated by a triangular wire-frame mesh to reduce geometric complexity and to tailor the model to the requirements of computer graphics visualization systems. Finally, the texture is mapped onto the wire-frame model, which can also be used for 3

  6. Wave-CAIPI for Highly Accelerated 3D Imaging

    PubMed Central

    Bilgic, Berkin; Gagoski, Borjan A.; Cauley, Stephen F.; Fan, Audrey P.; Polimeni, Jonathan R.; Grant, P. Ellen; Wald, Lawrence L.; Setsompop, Kawin

    2014-01-01

    Purpose To introduce the Wave-CAIPI (Controlled Aliasing in Parallel Imaging) acquisition and reconstruction technique for highly accelerated 3D imaging with negligible g-factor and artifact penalties. Methods The Wave-CAIPI 3D acquisition involves playing sinusoidal gy and gz gradients during the readout of each kx encoding line, while modifying the 3D phase encoding strategy to incur inter-slice shifts as in 2D-CAIPI acquisitions. The resulting acquisition spreads the aliasing evenly in all spatial directions, thereby taking full advantage of 3D coil sensitivity distribution. By expressing the voxel spreading effect as a convolution in image space, an efficient reconstruction scheme that does not require data gridding is proposed. Rapid acquisition and high quality image reconstruction with Wave-CAIPI is demonstrated for high-resolution magnitude and phase imaging and Quantitative Susceptibility Mapping (QSM). Results Wave-CAIPI enables full-brain gradient echo (GRE) acquisition at 1 mm isotropic voxel size and R=3×3 acceleration with maximum g-factors of 1.08 at 3T, and 1.05 at 7T. Relative to the other advanced Cartesian encoding strategies 2D-CAIPI and Bunched Phase Encoding, Wave-CAIPI yields up to 2-fold reduction in maximum g-factor for 9-fold acceleration at both field strengths. Conclusion Wave-CAIPI allows highly accelerated 3D acquisitions with low artifact and negligible g-factor penalties, and may facilitate clinical application of high-resolution volumetric imaging. PMID:24986223

  7. Automated curved planar reformation of 3D spine images

    NASA Astrophysics Data System (ADS)

    Vrtovec, Tomaz; Likar, Bostjan; Pernus, Franjo

    2005-10-01

    Traditional techniques for visualizing anatomical structures are based on planar cross-sections from volume images, such as images obtained by computed tomography (CT) or magnetic resonance imaging (MRI). However, planar cross-sections taken in the coordinate system of the 3D image often do not provide sufficient or qualitative enough diagnostic information, because planar cross-sections cannot follow curved anatomical structures (e.g. arteries, colon, spine, etc). Therefore, not all of the important details can be shown simultaneously in any planar cross-section. To overcome this problem, reformatted images in the coordinate system of the inspected structure must be created. This operation is usually referred to as curved planar reformation (CPR). In this paper we propose an automated method for CPR of 3D spine images, which is based on the image transformation from the standard image-based to a novel spine-based coordinate system. The axes of the proposed spine-based coordinate system are determined on the curve that represents the vertebral column, and the rotation of the vertebrae around the spine curve, both of which are described by polynomial models. The optimal polynomial parameters are obtained in an image analysis based optimization framework. The proposed method was qualitatively and quantitatively evaluated on five CT spine images. The method performed well on both normal and pathological cases and was consistent with manually obtained ground truth data. The proposed spine-based CPR benefits from reduced structural complexity in favour of improved feature perception of the spine. The reformatted images are diagnostically valuable and enable easier navigation, manipulation and orientation in 3D space. Moreover, reformatted images may prove useful for segmentation and other image analysis tasks.

  8. A method of 2D/3D registration of a statistical mouse atlas with a planar X-ray projection and an optical photo

    PubMed Central

    Wang, Hongkai; Stout, David B; Chatziioannou, Arion F

    2013-01-01

    The development of sophisticated and high throughput whole body small animal imaging technologies has created a need for improved image analysis and increased automation. The registration of a digital mouse atlas to individual images is a prerequisite for automated organ segmentation and uptake quantification. This paper presents a fully-automatic method for registering a statistical mouse atlas with individual subjects based on an anterior-posterior X-ray projection and a lateral optical photo of the mouse silhouette. The mouse atlas was trained as a statistical shape model based on 83 organ-segmented micro-CT images. For registration, a hierarchical approach is applied which first registers high contrast organs, and then estimates low contrast organs based on the registered high contrast organs. To register the high contrast organs, a 2D-registration-back-projection strategy is used that deforms the 3D atlas based on the 2D registrations of the atlas projections. For validation, this method was evaluated using 55 subjects of preclinical mouse studies. The results showed that this method can compensate for moderate variations of animal postures and organ anatomy. Two different metrics, the Dice coefficient and the average surface distance, were used to assess the registration accuracy of major organs. The Dice coefficients vary from 0.31±0.16 for the spleen to 0.88±0.03 for the whole body, and the average surface distance varies from 0.54±0.06 mm for the lungs to 0.85±0.10 mm for the skin. The method was compared with a direct 3D deformation optimization (without 2D-registration-back-projection) and a single-subject atlas registration (instead of using the statistical atlas). The comparison revealed that the 2D-registration-back-projection strategy significantly improved the registration accuracy, and the use of the statistical mouse atlas led to more plausible organ shapes than the single-subject atlas. This method was also tested with shoulder xenograft

  9. Imaging thin-bed reservoirs with 3-D seismic

    SciTech Connect

    Hardage, B.A.

    1996-12-01

    This article explains how a 3-D seismic data volume, a vertical seismic profile (VSP), electric well logs and reservoir pressure data can be used to image closely stacked thin-bed reservoirs. This interpretation focuses on the Oligocene Frio reservoir in South Texas which has multiple thin-beds spanning a vertical interval of about 3,000 ft.

  10. 3D wavefront image formation for NIITEK GPR

    NASA Astrophysics Data System (ADS)

    Soumekh, Mehrdad; Ton, Tuan; Howard, Pete

    2009-05-01

    The U.S. Department of Defense Humanitarian Demining (HD) Research and Development Program focuses on developing, testing, demonstrating, and validating new technology for immediate use in humanitarian demining operations around the globe. Beginning in the late 1990's, the U.S. Army Countermine Division funded the development of the NIITEK ground penetrating radar (GPR) for detection of anti-tank (AT) landmines. This work is concerned with signal processing algorithms to suppress sources of artifacts in the NIITEK GPR, and formation of three-dimensional (3D) imagery from the resultant data. We first show that the NIITEK GPR data correspond to a 3D Synthetic Aperture Radar (SAR) database. An adaptive filtering method is utilized to suppress ground return and self-induced resonance (SIR) signals that are generated by the interaction of the radar-carrying platform and the transmitted radar signal. We examine signal processing methods to improve the fidelity of imagery for this 3D SAR system using pre-processing methods that suppress Doppler aliasing as well as other side lobe leakage artifacts that are introduced by the radar radiation pattern. The algorithm, known as digital spotlighting, imposes a filtering scheme on the azimuth-compressed SAR data, and manipulates the resultant spectral data to achieve a higher PRF to suppress the Doppler aliasing. We also present the 3D version of the Fourier-based wavefront reconstruction, a computationally-efficient and approximation-free SAR imaging method, for image formation with the NIITEK 3D SAR database.

  11. Optimizing 3D image quality and performance for stereoscopic gaming

    NASA Astrophysics Data System (ADS)

    Flack, Julien; Sanderson, Hugh; Pegg, Steven; Kwok, Simon; Paterson, Daniel

    2009-02-01

    The successful introduction of stereoscopic TV systems, such as Samsung's 3D Ready Plasma, requires high quality 3D content to be commercially available to the consumer. Console and PC games provide the most readily accessible source of high quality 3D content. This paper describes innovative developments in a generic, PC-based game driver architecture that addresses the two key issues affecting 3D gaming: quality and speed. At the heart of the quality issue are the same considerations that studios face producing stereoscopic renders from CG movies: how best to perform the mapping from a geometric CG environment into the stereoscopic display volume. The major difference being that for game drivers this mapping cannot be choreographed by hand but must be automatically calculated in real-time without significant impact on performance. Performance is a critical issue when dealing with gaming. Stereoscopic gaming has traditionally meant rendering the scene twice with the associated performance overhead. An alternative approach is to render the scene from one virtual camera position and use information from the z-buffer to generate a stereo pair using Depth-Image-Based Rendering (DIBR). We analyze this trade-off in more detail and provide some results relating to both 3D image quality and render performance.

  12. Graph-regularized 3D shape reconstruction from highly anisotropic and noisy images

    PubMed Central

    Heinrich, Stephanie; Drewe, Philipp; Lou, Xinghua; Umrania, Shefali; Rätsch, Gunnar

    2014-01-01

    Analysis of microscopy images can provide insight into many biological processes. One particularly challenging problem is cellular nuclear segmentation in highly anisotropic and noisy 3D image data. Manually localizing and segmenting each and every cellular nucleus is very time-consuming, which remains a bottleneck in large-scale biological experiments. In this work, we present a tool for automated segmentation of cellular nuclei from 3D fluorescent microscopic data. Our tool is based on state-of-the-art image processing and machine learning techniques and provides a user-friendly graphical user interface. We show that our tool is as accurate as manual annotation and greatly reduces the time for the registration. PMID:25866587

  13. Iterative closest curve: a framework for curvilinear structure registration application to 2D/3D coronary arteries registration.

    PubMed

    Benseghir, Thomas; Malandain, Grégoire; Vaillant, Régis

    2013-01-01

    Treatment coronary arteries endovascular involves catheter navigation through patient vasculature. The projective angiography guidance is limited in the case of chronic total occlusion where occluded vessel can not be seen. Integrating standard preoperative CT angiography information with live fluoroscopic images addresses this limitation but requires alignment of both modalities. This article proposes a structure-based registration method that intrinsically preserves both the geometrical and topological coherencies of the vascular centrelines to be registered, by the means of a dedicated curve-to-curve distance pairs of closest curves are identified, while pairing their points. Preliminary experiments demonstrate that the proposed approach performs better than the standard Iterative Closest Point method giving a wider attraction basin and improved accuracy. PMID:24505664

  14. 3-D object-oriented image analysis of geophysical data

    NASA Astrophysics Data System (ADS)

    Fadel, I.; Kerle, N.; van der Meijde, M.

    2014-07-01

    Geophysical data are the main source of information about the subsurface. Geophysical techniques are, however, highly non-unique in determining specific physical parameters and boundaries of subsurface objects. To obtain actual physical information, an inversion process is often applied, in which measurements at or above the Earth surface are inverted into a 2- or 3-D subsurface spatial distribution of the physical property. Interpreting these models into structural objects, related to physical processes, requires a priori knowledge and expert analysis which is susceptible to subjective choices and is therefore often non-repeatable. In this research, we implemented a recently introduced object-based approach to interpret the 3-D inversion results of a single geophysical technique using the available a priori information and the physical and geometrical characteristics of the interpreted objects. The introduced methodology is semi-automatic and repeatable, and allows the extraction of subsurface structures using 3-D object-oriented image analysis (3-D OOA) in an objective knowledge-based classification scheme. The approach allows for a semi-objective setting of thresholds that can be tested and, if necessary, changed in a very fast and efficient way. These changes require only changing the thresholds used in a so-called ruleset, which is composed of algorithms that extract objects from a 3-D data cube. The approach is tested on a synthetic model, which is based on a priori knowledge on objects present in the study area (Tanzania). Object characteristics and thresholds were well defined in a 3-D histogram of velocity versus depth, and objects were fully retrieved. The real model results showed how 3-D OOA can deal with realistic 3-D subsurface conditions in which the boundaries become fuzzy, the object extensions become unclear and the model characteristics vary with depth due to the different physical conditions. As expected, the 3-D histogram of the real data was

  15. Practical applications of 3D sonography in gynecologic imaging.

    PubMed

    Andreotti, Rochelle F; Fleischer, Arthur C

    2014-11-01

    Volume imaging in the pelvis has been well demonstrated to be an extremely useful technique, largely based on its ability to reconstruct the coronal plane of the uterus that usually cannot be visualized using traditional 2-dimensional (2D) imaging. As a result, this technique is now a part of the standard pelvic ultrasound protocol in many institutions. A variety of valuable applications of 3D sonography in the pelvis are discussed in this article. PMID:25444101

  16. 3D Winding Number: Theory and Application to Medical Imaging

    PubMed Central

    Becciu, Alessandro; Fuster, Andrea; Pottek, Mark; van den Heuvel, Bart; ter Haar Romeny, Bart; van Assen, Hans

    2011-01-01

    We develop a new formulation, mathematically elegant, to detect critical points of 3D scalar images. It is based on a topological number, which is the generalization to three dimensions of the 2D winding number. We illustrate our method by considering three different biomedical applications, namely, detection and counting of ovarian follicles and neuronal cells and estimation of cardiac motion from tagged MR images. Qualitative and quantitative evaluation emphasizes the reliability of the results. PMID:21317978

  17. Accurate registration of random radiographic projections based on three spherical references for the purpose of few-view 3D reconstruction

    SciTech Connect

    Schulze, Ralf; Heil, Ulrich; Weinheimer, Oliver; Gross, Daniel; Bruellmann, Dan; Thomas, Eric; Schwanecke, Ulrich; Schoemer, Elmar

    2008-02-15

    Precise registration of radiographic projection images acquired in almost arbitrary geometries for the purpose of three-dimensional (3D) reconstruction is beset with difficulties. We modify and enhance a registration method [R. Schulze, D. D. Bruellmann, F. Roeder, and B. d'Hoedt, Med. Phys. 31, 2849-2854 (2004)] based on coupling a minimum amount of three reference spheres in arbitrary positions to a rigid object under study for precise a posteriori pose estimation. Two consecutive optimization procedures (a, initial guess; b, iterative coordinate refinement) are applied to completely exploit the reference's shadow information for precise registration of the projections. The modification has been extensive, i.e., only the idea of using the sphere shadows to locate each sphere in three dimensions from each projection was retained whereas the approach to extract the shadow information has been changed completely and extended. The registration information is used for subsequent algebraic reconstruction of the 3D information inherent in the projections. We present a detailed mathematical theory of the registration process as well as simulated data investigating its performance in the presence of error. Simulation of the initial guess revealed a mean relative error in the critical depth coordinate ranging between 2.1% and 4.4%, and an evident error reduction by the subsequent iterative coordinate refinement. To prove the applicability of the method for real-world data, algebraic 3D reconstructions from few ({<=}9) projection radiographs of a human skull, a human mandible and a teeth-containing mandible segment are presented. The method facilitates extraction of 3D information from only few projections obtained from off-the-shelf radiographic projection units without the need for costly hardware. Technical requirements as well as radiation dose are low.

  18. Interactive multigrid refinement for deformable image registration.

    PubMed

    Zhou, Wu; Xie, Yaoqin

    2013-01-01

    Deformable image registration is the spatial mapping of corresponding locations between images and can be used for important applications in radiotherapy. Although numerous methods have attempted to register deformable medical images automatically, such as salient-feature-based registration (SFBR), free-form deformation (FFD), and demons, no automatic method for registration is perfect, and no generic automatic algorithm has shown to work properly for clinical applications due to the fact that the deformation field is often complex and cannot be estimated well by current automatic deformable registration methods. This paper focuses on how to revise registration results interactively for deformable image registration. We can manually revise the transformed image locally in a hierarchical multigrid manner to make the transformed image register well with the reference image. The proposed method is based on multilevel B-spline to interactively revise the deformable transformation in the overlapping region between the reference image and the transformed image. The resulting deformation controls the shape of the transformed image and produces a nice registration or improves the registration results of other registration methods. Experimental results in clinical medical images for adaptive radiotherapy demonstrated the effectiveness of the proposed method. PMID:24232828

  19. An automated 3D reconstruction method of UAV images

    NASA Astrophysics Data System (ADS)

    Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

    2015-10-01

    In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

  20. 3D ultrasound image segmentation using wavelet support vector machines

    PubMed Central

    Akbari, Hamed; Fei, Baowei

    2012-01-01

    Purpose: Transrectal ultrasound (TRUS) imaging is clinically used in prostate biopsy and therapy. Segmentation of the prostate on TRUS images has many applications. In this study, a three-dimensional (3D) segmentation method for TRUS images of the prostate is presented for 3D ultrasound-guided biopsy. Methods: This segmentation method utilizes a statistical shape, texture information, and intensity profiles. A set of wavelet support vector machines (W-SVMs) is applied to the images at various subregions of the prostate. The W-SVMs are trained to adaptively capture the features of the ultrasound images in order to differentiate the prostate and nonprostate tissue. This method consists of a set of wavelet transforms for extraction of prostate texture features and a kernel-based support vector machine to classify the textures. The voxels around the surface of the prostate are labeled in sagittal, coronal, and transverse planes. The weight functions are defined for each labeled voxel on each plane and on the model at each region. In the 3D segmentation procedure, the intensity profiles around the boundary between the tentatively labeled prostate and nonprostate tissue are compared to the prostate model. Consequently, the surfaces are modified based on the model intensity profiles. The segmented prostate is updated and compared to the shape model. These two steps are repeated until they converge. Manual segmentation of the prostate serves as the gold standard and a variety of methods are used to evaluate the performance of the segmentation method. Results: The results from 40 TRUS image volumes of 20 patients show that the Dice overlap ratio is 90.3% ± 2.3% and that the sensitivity is 87.7% ± 4.9%. Conclusions: The proposed method provides a useful tool in our 3D ultrasound image-guided prostate biopsy and can also be applied to other applications in the prostate. PMID:22755682

  1. Hierarchical estimation of a dense deformation field for 3-D robust registration.

    PubMed

    Hellier, P; Barillot, C; Mémin, E; Pérez, P

    2001-05-01

    A new method for medical image registration is formulated as a minimization problem involving robust estimators. We propose an efficient hierarchical optimization framework which is both multiresolution and multigrid. An anatomical segmentation of the cortex is introduced in the adaptive partitioning of the volume on which the multigrid minimization is based. This allows to limit the estimation to the areas of interest, to accelerate the algorithm, and to refine the estimation in specified areas. At each stage of the hierarchical estimation, we refine current estimate by seeking a piecewise affine model for the incremental deformation field. The performance of this method is numerically evaluated on simulated data and its benefits and robustness are shown on a database of 18 magnetic resonance imaging scans of the head. PMID:11403198

  2. 2D and 3D visualization methods of endoscopic panoramic bladder images

    NASA Astrophysics Data System (ADS)

    Behrens, Alexander; Heisterklaus, Iris; Müller, Yannick; Stehle, Thomas; Gross, Sebastian; Aach, Til

    2011-03-01

    While several mosaicking algorithms have been developed to compose endoscopic images of the internal urinary bladder wall into panoramic images, the quantitative evaluation of these output images in terms of geometrical distortions have often not been discussed. However, the visualization of the distortion level is highly desired for an objective image-based medical diagnosis. Thus, we present in this paper a method to create quality maps from the characteristics of transformation parameters, which were applied to the endoscopic images during the registration process of the mosaicking algorithm. For a global first view impression, the quality maps are laid over the panoramic image and highlight image regions in pseudo-colors according to their local distortions. This illustration supports then surgeons to identify geometrically distorted structures easily in the panoramic image, which allow more objective medical interpretations of tumor tissue in shape and size. Aside from introducing quality maps in 2-D, we also discuss a visualization method to map panoramic images onto a 3-D spherical bladder model. Reference points are manually selected by the surgeon in the panoramic image and the 3-D model. Then the panoramic image is mapped by the Hammer-Aitoff equal-area projection onto the 3-D surface using texture mapping. Finally the textured bladder model can be freely moved in a virtual environment for inspection. Using a two-hemisphere bladder representation, references between panoramic image regions and their corresponding space coordinates within the bladder model are reconstructed. This additional spatial 3-D information thus assists the surgeon in navigation, documentation, as well as surgical planning.

  3. 1024 pixels single photon imaging array for 3D ranging

    NASA Astrophysics Data System (ADS)

    Bellisai, S.; Guerrieri, F.; Tisa, S.; Zappa, F.; Tosi, A.; Giudice, A.

    2011-01-01

    Three dimensions (3D) acquisition systems are driving applications in many research field. Nowadays 3D acquiring systems are used in a lot of applications, such as cinema industry or in automotive (for active security systems). Depending on the application, systems present different features, for example color sensitivity, bi-dimensional image resolution, distance measurement accuracy and acquisition frame rate. The system we developed acquires 3D movie using indirect Time of Flight (iTOF), starting from phase delay measurement of a sinusoidally modulated light. The system acquires live movie with a frame rate up to 50frame/s in a range distance between 10 cm up to 7.5 m.

  4. 3-D segmentation of human sternum in lung MDCT images.

    PubMed

    Pazokifard, Banafsheh; Sowmya, Arcot

    2013-01-01

    A fully automatic novel algorithm is presented for accurate 3-D segmentation of the human sternum in lung multi detector computed tomography (MDCT) images. The segmentation result is refined by employing active contours to remove calcified costal cartilage that is attached to the sternum. For each dataset, costal notches (sternocostal joints) are localized in 3-D by using a sternum mask and positions of the costal notches on it as reference. The proposed algorithm for sternum segmentation was tested on 16 complete lung MDCT datasets and comparison of the segmentation results to the reference delineation provided by a radiologist, shows high sensitivity (92.49%) and specificity (99.51%) and small mean distance (dmean=1.07 mm). Total average of the Euclidean distance error for costal notches positioning in 3-D is 4.2 mm. PMID:24110446

  5. Incremental volume reconstruction and rendering for 3-D ultrasound imaging

    NASA Astrophysics Data System (ADS)

    Ohbuchi, Ryutarou; Chen, David; Fuchs, Henry

    1992-09-01

    In this paper, we present approaches toward an interactive visualization of a real time input, applied to 3-D visualizations of 2-D ultrasound echography data. The first, 3 degrees-of- freedom (DOF) incremental system visualizes a 3-D volume acquired as a stream of 2-D slices with location and orientation with 3 DOF. As each slice arrives, the system reconstructs a regular 3-D volume and renders it. Rendering is done by an incremental image-order ray- casting algorithm which stores and reuses the results of expensive resampling along the rays for speed. The second is our first experiment toward real-time 6 DOF acquisition and visualization. Two-dimensional slices with 6 DOF are reconstructed off-line, and visualized at an interactive rate using a parallel volume rendering code running on the graphics multicomputer Pixel-Planes 5.

  6. Real-time 3D image reconstruction guidance in liver resection surgery

    PubMed Central

    Nicolau, Stephane; Pessaux, Patrick; Mutter, Didier; Marescaux, Jacques

    2014-01-01

    Background Minimally invasive surgery represents one of the main evolutions of surgical techniques. However, minimally invasive surgery adds difficulty that can be reduced through computer technology. Methods From a patient’s medical image [US, computed tomography (CT) or MRI], we have developed an Augmented Reality (AR) system that increases the surgeon’s intraoperative vision by providing a virtual transparency of the patient. AR is based on two major processes: 3D modeling and visualization of anatomical or pathological structures appearing in the medical image, and the registration of this visualization onto the real patient. We have thus developed a new online service, named Visible Patient, providing efficient 3D modeling of patients. We have then developed several 3D visualization and surgical planning software tools to combine direct volume rendering and surface rendering. Finally, we have developed two registration techniques, one interactive and one automatic providing intraoperative augmented reality view. Results From January 2009 to June 2013, 769 clinical cases have been modeled by the Visible Patient service. Moreover, three clinical validations have been realized demonstrating the accuracy of 3D models and their great benefit, potentially increasing surgical eligibility in liver surgery (20% of cases). From these 3D models, more than 50 interactive AR-assisted surgical procedures have been realized illustrating the potential clinical benefit of such assistance to gain safety, but also current limits that automatic augmented reality will overcome. Conclusions Virtual patient modeling should be mandatory for certain interventions that have now to be defined, such as liver surgery. Augmented reality is clearly the next step of the new surgical instrumentation but remains currently limited due to the complexity of organ deformations during surgery. Intraoperative medical imaging used in new generation of automated augmented reality should solve this

  7. Automatic needle segmentation in 3D ultrasound images

    NASA Astrophysics Data System (ADS)

    Ding, Mingyue; Cardinal, H. Neale; Guan, Weiguang; Fenster, Aaron

    2002-05-01

    In this paper, we propose to use 2D image projections to automatically segment a needle in a 3D ultrasound image. This approach is motivated by the twin observations that the needle is more conspicuous in a projected image, and its projected area is a minimum when the rays are cast parallel to the needle direction. To avoid the computational burden of an exhaustive 2D search for the needle direction, a faster 1D search procedure is proposed. First, a plane which contains the needle direction is determined by the initial projection direction and the (estimated) direction of the needle in the corresponding projection image. Subsequently, an adaptive 1D search technique is used to adjust the projection direction iteratively until the projected needle area is minimized. In order to remove noise and complex background structure from the projection images, a priori information about the needle position and orientation is used to crop the 3D volume, and the cropped volume is rendered with Gaussian transfer functions. We have evaluated this approach experimentally using agar and turkey breast phantoms. The results show that it can find the 3D needle orientation within 1 degree, in about 1 to 3 seconds on a 500 MHz computer.

  8. Respiratory motion compensation for simultaneous PET/MR based on a 3D-2D registration of strongly undersampled radial MR data: a simulation study

    NASA Astrophysics Data System (ADS)

    Rank, Christopher M.; Heußer, Thorsten; Flach, Barbara; Brehm, Marcus; Kachelrieß, Marc

    2015-03-01

    We propose a new method for PET/MR respiratory motion compensation, which is based on a 3D-2D registration of strongly undersampled MR data and a) runs in parallel with the PET acquisition, b) can be interlaced with clinical MR sequences, and c) requires less than one minute of the total MR acquisition time per bed position. In our simulation study, we applied a 3D encoded radial stack-of-stars sampling scheme with 160 radial spokes per slice and an acquisition time of 38 s. Gated 4D MR images were reconstructed using a 4D iterative reconstruction algorithm. Based on these images, motion vector fields were estimated using our newly-developed 3D-2D registration framework. A 4D PET volume of a patient with eight hot lesions in the lungs and upper abdomen was simulated and MoCo 4D PET images were reconstructed based on the motion vector fields derived from MR. For evaluation, average SUVmean values of the artificial lesions were determined for a 3D, a gated 4D, a MoCo 4D and a reference (with ten-fold measurement time) gated 4D reconstruction. Compared to the reference, 3D reconstructions yielded an underestimation of SUVmean values due to motion blurring. In contrast, gated 4D reconstructions showed the highest variation of SUVmean due to low statistics. MoCo 4D reconstructions were only slightly affected by these two sources of uncertainty resulting in a significant visual and quantitative improvement in terms of SUVmean values. Whereas temporal resolution was comparable to the gated 4D images, signal-to-noise ratio and contrast-to-noise ratio were close to the 3D reconstructions.

  9. Vhrs Stereo Images for 3d Modelling of Buildings

    NASA Astrophysics Data System (ADS)

    Bujakiewicz, A.; Holc, M.

    2012-07-01

    The paper presents the project which was carried out in the Photogrammetric Laboratory of Warsaw University of Technology. The experiment is concerned with the extraction of 3D vector data for buildings creation from 3D photogrammetric model based on the Ikonos stereo images. The model was reconstructed with photogrammetric workstation - Summit Evolution combined with ArcGIS 3D platform. Accuracy of 3D model was significantly improved by use for orientation of pair of satellite images the stereo measured tie points distributed uniformly around the model area in addition to 5 control points. The RMS for model reconstructed on base of the RPC coefficients only were 16,6 m, 2,7 m and 47,4 m, for X, Y and Z coordinates, respectively. By addition of 5 control points the RMS were improved to 0,7 m, 0,7 m 1,0 m, where the best results were achieved when RMS were estimated from deviations in 17 check points (with 5 control points)and amounted to 0,4 m, 0,5 m and 0,6 m, for X, Y, and Z respectively. The extracted 3D vector data for buildings were integrated with 2D data of the ground footprints and afterwards they were used for 3D modelling of buildings in Google SketchUp software. The final results were compared with the reference data obtained from other sources. It was found that the shape of buildings (in concern to the number of details) had been reconstructed on level of LoD1, when the accuracy of these models corresponded to the level of LoD2.

  10. 3D Reconstruction of Human Motion from Monocular Image Sequences.

    PubMed

    Wandt, Bastian; Ackermann, Hanno; Rosenhahn, Bodo

    2016-08-01

    This article tackles the problem of estimating non-rigid human 3D shape and motion from image sequences taken by uncalibrated cameras. Similar to other state-of-the-art solutions we factorize 2D observations in camera parameters, base poses and mixing coefficients. Existing methods require sufficient camera motion during the sequence to achieve a correct 3D reconstruction. To obtain convincing 3D reconstructions from arbitrary camera motion, our method is based on a-priorly trained base poses. We show that strong periodic assumptions on the coefficients can be used to define an efficient and accurate algorithm for estimating periodic motion such as walking patterns. For the extension to non-periodic motion we propose a novel regularization term based on temporal bone length constancy. In contrast to other works, the proposed method does not use a predefined skeleton or anthropometric constraints and can handle arbitrary camera motion. We achieve convincing 3D reconstructions, even under the influence of noise and occlusions. Multiple experiments based on a 3D error metric demonstrate the stability of the proposed method. Compared to other state-of-the-art methods our algorithm shows a significant improvement. PMID:27093439

  11. Large distance 3D imaging of hidden objects

    NASA Astrophysics Data System (ADS)

    Rozban, Daniel; Aharon Akram, Avihai; Kopeika, N. S.; Abramovich, A.; Levanon, Assaf

    2014-06-01

    Imaging systems in millimeter waves are required for applications in medicine, communications, homeland security, and space technology. This is because there is no known ionization hazard for biological tissue, and atmospheric attenuation in this range of the spectrum is low compared to that of infrared and optical rays. The lack of an inexpensive room temperature detector makes it difficult to give a suitable real time implement for the above applications. A 3D MMW imaging system based on chirp radar was studied previously using a scanning imaging system of a single detector. The system presented here proposes to employ a chirp radar method with Glow Discharge Detector (GDD) Focal Plane Array (FPA of plasma based detectors) using heterodyne detection. The intensity at each pixel in the GDD FPA yields the usual 2D image. The value of the I-F frequency yields the range information at each pixel. This will enable 3D MMW imaging. In this work we experimentally demonstrate the feasibility of implementing an imaging system based on radar principles and FPA of inexpensive detectors. This imaging system is shown to be capable of imaging objects from distances of at least 10 meters.

  12. Automated reconstruction of 3D scenes from sequences of images

    NASA Astrophysics Data System (ADS)

    Pollefeys, M.; Koch, R.; Vergauwen, M.; Van Gool, L.

    Modelling of 3D objects from image sequences is a challenging problem and has been an important research topic in the areas of photogrammetry and computer vision for many years. In this paper, a system is presented which automatically extracts a textured 3D surface model from a sequence of images of a scene. The system can deal with unknown camera settings. In addition, the parameters of this camera are allowed to change during acquisition (e.g., by zooming or focusing). No prior knowledge about the scene is necessary to build the 3D models. Therefore, this system offers a high degree of flexibility. The system is based on state-of-the-art algorithms recently developed in computer vision. The 3D modelling task is decomposed into a number of successive steps. Gradually, more knowledge of the scene and the camera setup is retrieved. At this point, the obtained accuracy is not yet at the level required for most metrology applications, but the visual quality is very convincing. This system has been applied to a number of applications in archaeology. The Roman site of Sagalassos (southwest Turkey) was used as a test case to illustrate the potential of this new approach.

  13. 3D imaging of fetus vertebra by synchrotron radiation microtomography

    NASA Astrophysics Data System (ADS)

    Peyrin, Francoise; Pateyron-Salome, Murielle; Denis, Frederic; Braillon, Pierre; Laval-Jeantet, Anne-Marie; Cloetens, Peter

    1997-10-01

    A synchrotron radiation computed microtomography system allowing high resolution 3D imaging of bone samples has been developed at ESRF. The system uses a high resolution 2D detector based on a CCd camera coupled to a fluorescent screen through light optics. The spatial resolution of the device is particularly well adapted to the imaging of bone structure. In view of studying growth, vertebra samples of fetus with differential gestational ages were imaged. The first results show that fetus vertebra is quite different from adult bone both in terms of density and organization.

  14. Texture blending on 3D models using casual images

    NASA Astrophysics Data System (ADS)

    Liu, Xingming; Liu, Xiaoli; Li, Ameng; Liu, Junyao; Wang, Huijing

    2013-12-01

    In this paper, a method for constructing photorealistic textured model using 3D structured light digitizer is presented. Our method acquisition of range images and texture images around object, and range images are registered and integrated to construct geometric model of object. System is calibrated and poses of texture-camera are determined so that the relationship between texture and geometric model is established. After that, a global optimization is applied to assign compatible texture to adjacent surface and followed with a level procedure to remove artifacts due to vary lighting, approximate geometric model and so on. Lastly, we demonstrate the effect of our method on constructing a real model of world.

  15. Uniformly spaced 3D modeling of human face from two images using parallel particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Chang, Yau-Zen; Hou, Jung-Fu; Tsao, Yi Hsiang; Lee, Shih-Tseng

    2011-09-01

    This paper proposes a scheme for finding the correspondence between uniformly spaced locations on the images of human face captured from different viewpoints at the same instant. The correspondence is dedicated for 3D reconstruction to be used in the registration procedure for neurosurgery where the exposure to projectors must be seriously restricted. The approach utilizes structured light to enhance patterns on the images and is initialized with the scale-invariant feature transform (SIFT). Successive locations are found according to spatial order using a parallel version of the particle swarm optimization algorithm. Furthermore, false locations are singled out for correction by searching for outliers from fitted curves. Case studies show that the scheme is able to correctly generate 456 evenly spaced 3D coordinate points in 23 seconds from a single shot of projected human face using a PC with 2.66 GHz Intel Q9400 CPU and 4GB RAM.

  16. Advanced 3D imaging lidar concepts for long range sensing

    NASA Astrophysics Data System (ADS)

    Gordon, K. J.; Hiskett, P. A.; Lamb, R. A.

    2014-06-01

    Recent developments in 3D imaging lidar are presented. Long range 3D imaging using photon counting is now a possibility, offering a low-cost approach to integrated remote sensing with step changing advantages in size, weight and power compared to conventional analogue active imaging technology. We report results using a Geiger-mode array for time-of-flight, single photon counting lidar for depth profiling and determination of the shape and size of tree canopies and distributed surface reflections at a range of 9km, with 4μJ pulses with a frame rate of 100kHz using a low-cost fibre laser operating at a wavelength of λ=1.5 μm. The range resolution is less than 4cm providing very high depth resolution for target identification. This specification opens up several additional functionalities for advanced lidar, for example: absolute rangefinding and depth profiling for long range identification, optical communications, turbulence sensing and time-of-flight spectroscopy. Future concepts for 3D time-of-flight polarimetric and multispectral imaging lidar, with optical communications in a single integrated system are also proposed.

  17. High-performance computing in image registration

    NASA Astrophysics Data System (ADS)

    Zanin, Michele; Remondino, Fabio; Dalla Mura, Mauro

    2012-10-01

    Thanks to the recent technological advances, a large variety of image data is at our disposal with variable geometric, radiometric and temporal resolution. In many applications the processing of such images needs high performance computing techniques in order to deliver timely responses e.g. for rapid decisions or real-time actions. Thus, parallel or distributed computing methods, Digital Signal Processor (DSP) architectures, Graphical Processing Unit (GPU) programming and Field-Programmable Gate Array (FPGA) devices have become essential tools for the challenging issue of processing large amount of geo-data. The article focuses on the processing and registration of large datasets of terrestrial and aerial images for 3D reconstruction, diagnostic purposes and monitoring of the environment. For the image alignment procedure, sets of corresponding feature points need to be automatically extracted in order to successively compute the geometric transformation that aligns the data. The feature extraction and matching are ones of the most computationally demanding operations in the processing chain thus, a great degree of automation and speed is mandatory. The details of the implemented operations (named LARES) exploiting parallel architectures and GPU are thus presented. The innovative aspects of the implementation are (i) the effectiveness on a large variety of unorganized and complex datasets, (ii) capability to work with high-resolution images and (iii) the speed of the computations. Examples and comparisons with standard CPU processing are also reported and commented.

  18. Elastic image registration via rigid object motion induced deformation

    NASA Astrophysics Data System (ADS)

    Zheng, Xiaofen; Udupa, Jayaram K.; Hirsch, Bruce E.

    2011-03-01

    In this paper, we estimate the deformations induced on soft tissues by the rigid independent movements of hard objects and create an admixture of rigid and elastic adaptive image registration transformations. By automatically segmenting and independently estimating the movement of rigid objects in 3D images, we can maintain rigidity in bones and hard tissues while appropriately deforming soft tissues. We tested our algorithms on 20 pairs of 3D MRI datasets pertaining to a kinematic study of the flexibility of the ankle complex of normal feet as well as ankles affected by abnormalities in foot architecture and ligament injuries. The results show that elastic image registration via rigid object-induced deformation outperforms purely rigid and purely nonrigid approaches.

  19. 3D change detection at street level using mobile laser scanning point clouds and terrestrial images

    NASA Astrophysics Data System (ADS)

    Qin, Rongjun; Gruen, Armin

    2014-04-01

    consistency between point clouds and stereo images. Finally, an over-segmentation based graph cut optimization is carried out, taking into account the color, depth and class information to compute the changed area in the image space. The proposed method is invariant to light changes, robust to small co-registration errors between images and point clouds, and can be applied straightforwardly to 3D polyhedral models. This method can be used for 3D street data updating, city infrastructure management and damage monitoring in complex urban scenes.

  20. Image Appraisal for 2D and 3D Electromagnetic Inversion

    SciTech Connect

    Alumbaugh, D.L.; Newman, G.A.

    1999-01-28

    Linearized methods are presented for appraising image resolution and parameter accuracy in images generated with two and three dimensional non-linear electromagnetic inversion schemes. When direct matrix inversion is employed, the model resolution and posterior model covariance matrices can be directly calculated. A method to examine how the horizontal and vertical resolution varies spatially within the electromagnetic property image is developed by examining the columns of the model resolution matrix. Plotting the square root of the diagonal of the model covariance matrix yields an estimate of how errors in the inversion process such as data noise and incorrect a priori assumptions about the imaged model map into parameter error. This type of image is shown to be useful in analyzing spatial variations in the image sensitivity to the data. A method is analyzed for statistically estimating the model covariance matrix when the conjugate gradient method is employed rather than a direct inversion technique (for example in 3D inversion). A method for calculating individual columns of the model resolution matrix using the conjugate gradient method is also developed. Examples of the image analysis techniques are provided on 2D and 3D synthetic cross well EM data sets, as well as a field data set collected at the Lost Hills Oil Field in Central California.

  1. Image Registration for Stability Testing of MEMS

    NASA Technical Reports Server (NTRS)

    Memarsadeghi, Nargess; LeMoigne, Jacqueline; Blake, Peter N.; Morey, Peter A.; Landsman, Wayne B.; Chambers, Victor J.; Moseley, Samuel H.

    2011-01-01

    Image registration, or alignment of two or more images covering the same scenes or objects, is of great interest in many disciplines such as remote sensing, medical imaging. astronomy, and computer vision. In this paper, we introduce a new application of image registration algorithms. We demonstrate how through a wavelet based image registration algorithm, engineers can evaluate stability of Micro-Electro-Mechanical Systems (MEMS). In particular, we applied image registration algorithms to assess alignment stability of the MicroShutters Subsystem (MSS) of the Near Infrared Spectrograph (NIRSpec) instrument of the James Webb Space Telescope (JWST). This work introduces a new methodology for evaluating stability of MEMS devices to engineers as well as a new application of image registration algorithms to computer scientists.

  2. Right main bronchus perforation detected by 3D-image

    PubMed Central

    Bense, László; Eklund, Gunnar; Jorulf, Hakan; Farkas, Árpád; Balásházy, Imre; Hedenstierna, Göran; Krebsz, Ádám; Madas, Balázs Gergely; Strindberg, Jerker Eden

    2011-01-01

    A male metal worker, who has never smoked, contracted debilitating dyspnoea in 2003 which then deteriorated until 2007. Spirometry and chest x-rays provided no diagnosis. A 3D-image of the airways was reconstructed from a high-resolution CT (HRCT) in 2007, showing peribronchial air on the right side, mostly along the presegmental airways. After digital subtraction of the image of the peribronchial air, a hole on the cranial side of the right main bronchus was detected. The perforation could be identified at the re-examination of HRCTs in 2007 and 2009, but not in 2010 when it had possibly healed. The occupational exposure of the patient to evaporating chemicals might have contributed to the perforation and hampered its healing. A 3D HRCT reconstruction should be considered to detect bronchial anomalies, including wall-perforation, when unexplained dyspnoea or other chest symptoms call for extended investigation. PMID:22679238

  3. Ultra-High Resolution 3D Imaging of Whole Cells.

    PubMed

    Huang, Fang; Sirinakis, George; Allgeyer, Edward S; Schroeder, Lena K; Duim, Whitney C; Kromann, Emil B; Phan, Thomy; Rivera-Molina, Felix E; Myers, Jordan R; Irnov, Irnov; Lessard, Mark; Zhang, Yongdeng; Handel, Mary Ann; Jacobs-Wagner, Christine; Lusk, C Patrick; Rothman, James E; Toomre, Derek; Booth, Martin J; Bewersdorf, Joerg

    2016-08-11

    Fluorescence nanoscopy, or super-resolution microscopy, has become an important tool in cell biological research. However, because of its usually inferior resolution in the depth direction (50-80 nm) and rapidly deteriorating resolution in thick samples, its practical biological application has been effectively limited to two dimensions and thin samples. Here, we present the development of whole-cell 4Pi single-molecule switching nanoscopy (W-4PiSMSN), an optical nanoscope that allows imaging of three-dimensional (3D) structures at 10- to 20-nm resolution throughout entire mammalian cells. We demonstrate the wide applicability of W-4PiSMSN across diverse research fields by imaging complex molecular architectures ranging from bacteriophages to nuclear pores, cilia, and synaptonemal complexes in large 3D cellular volumes. PMID:27397506

  4. 3D scene reconstruction based on 3D laser point cloud combining UAV images

    NASA Astrophysics Data System (ADS)

    Liu, Huiyun; Yan, Yangyang; Zhang, Xitong; Wu, Zhenzhen

    2016-03-01

    It is a big challenge capturing and modeling 3D information of the built environment. A number of techniques and technologies are now in use. These include GPS, and photogrammetric application and also remote sensing applications. The experiment uses multi-source data fusion technology for 3D scene reconstruction based on the principle of 3D laser scanning technology, which uses the laser point cloud data as the basis and Digital Ortho-photo Map as an auxiliary, uses 3DsMAX software as a basic tool for building three-dimensional scene reconstruction. The article includes data acquisition, data preprocessing, 3D scene construction. The results show that the 3D scene has better truthfulness, and the accuracy of the scene meet the need of 3D scene construction.

  5. Automated Recognition of 3D Features in GPIR Images

    NASA Technical Reports Server (NTRS)

    Park, Han; Stough, Timothy; Fijany, Amir

    2007-01-01

    A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

  6. 3D VSP imaging in the Deepwater GOM

    NASA Astrophysics Data System (ADS)

    Hornby, B. E.

    2005-05-01

    Seismic imaging challenges in the Deepwater GOM include surface and sediment related multiples and issues arising from complicated salt bodies. Frequently, wells encounter geologic complexity not resolved on conventional surface seismic section. To help address these challenges BP has been acquiring 3D VSP (Vertical Seismic Profile) surveys in the Deepwater GOM. The procedure involves placing an array of seismic sensors in the borehole and acquiring a 3D seismic dataset with a surface seismic gunboat that fires airguns in a spiral pattern around the wellbore. Placing the seismic geophones in the borehole provides a higher resolution and more accurate image near the borehole, as well as other advantages relating to the unique position of the sensors relative to complex structures. Technical objectives are to complement surface seismic with improved resolution (~2X seismic), better high dip structure definition (e.g. salt flanks) and to fill in "imaging holes" in complex sub-salt plays where surface seismic is blind. Business drivers for this effort are to reduce risk in well placement, improved reserve calculation and understanding compartmentalization and stratigraphic variation. To date, BP has acquired 3D VSP surveys in ten wells in the DW GOM. The initial results are encouraging and show both improved resolution and structural images in complex sub-salt plays where the surface seismic is blind. In conjunction with this effort BP has influenced both contractor borehole seismic tool design and developed methods to enable the 3D VSP surveys to be conducted offline thereby avoiding the high daily rig costs associated with a Deepwater drilling rig.

  7. 3D tongue motion from tagged and cine MR images.

    PubMed

    Xing, Fangxu; Woo, Jonghye; Murano, Emi Z; Lee, Junghoon; Stone, Maureen; Prince, Jerry L

    2013-01-01

    Understanding the deformation of the tongue during human speech is important for head and neck surgeons and speech and language scientists. Tagged magnetic resonance (MR) imaging can be used to image 2D motion, and data from multiple image planes can be combined via post-processing to yield estimates of 3D motion. However, lacking boundary information, this approach suffers from inaccurate estimates near the tongue surface. This paper describes a method that combines two sources of information to yield improved estimation of 3D tongue motion. The method uses the harmonic phase (HARP) algorithm to extract motion from tags and diffeomorphic demons to provide surface deformation. It then uses an incompressible deformation estimation algorithm to incorporate both sources of displacement information to form an estimate of the 3D whole tongue motion. Experimental results show that use of combined information improves motion estimation near the tongue surface, a problem that has previously been reported as problematic in HARP analysis, while preserving accurate internal motion estimates. Results on both normal and abnormal tongue motions are shown. PMID:24505742

  8. Discrete Method of Images for 3D Radio Propagation Modeling

    NASA Astrophysics Data System (ADS)

    Novak, Roman

    2016-09-01

    Discretization by rasterization is introduced into the method of images (MI) in the context of 3D deterministic radio propagation modeling as a way to exploit spatial coherence of electromagnetic propagation for fine-grained parallelism. Traditional algebraic treatment of bounding regions and surfaces is replaced by computer graphics rendering of 3D reflections and double refractions while building the image tree. The visibility of reception points and surfaces is also resolved by shader programs. The proposed rasterization is shown to be of comparable run time to that of the fundamentally parallel shooting and bouncing rays. The rasterization does not affect the signal evaluation backtracking step, thus preserving its advantage over the brute force ray-tracing methods in terms of accuracy. Moreover, the rendering resolution may be scaled back for a given level of scenario detail with only marginal impact on the image tree size. This allows selection of scene optimized execution parameters for faster execution, giving the method a competitive edge. The proposed variant of MI can be run on any GPU that supports real-time 3D graphics.

  9. Radiometric Quality Evaluation of INSAT-3D Imager Data

    NASA Astrophysics Data System (ADS)

    Prakash, S.; Jindal, D.; Badal, N.; Kartikeyan, B.; Gopala Krishna, B.

    2014-11-01

    INSAT-3D is an advanced meteorological satellite of ISRO which acquires imagery in optical and infra-red (IR) channels for study of weather dynamics in Indian sub-continent region. In this paper, methodology of radiometric quality evaluation for Level-1 products of Imager, one of the payloads onboard INSAT-3D, is described. Firstly, overall visual quality of scene in terms of dynamic range, edge sharpness or modulation transfer function (MTF), presence of striping and other image artefacts is computed. Uniform targets in Desert and Sea region are identified for which detailed radiometric performance evaluation for IR channels is carried out. Mean brightness temperature (BT) of targets is computed and validated with independently generated radiometric references. Further, diurnal/seasonal trends in target BT values and radiometric uncertainty or sensor noise are studied. Results of radiometric quality evaluation over duration of eight months (January to August 2014) and comparison of radiometric consistency pre/post yaw flip of satellite are presented. Radiometric Analysis indicates that INSAT-3D images have high contrast (MTF > 0.2) and low striping effects. A bias of <4K is observed in the brightness temperature values of TIR-1 channel measured during January-August 2014 indicating consistent radiometric calibration. Diurnal and seasonal analysis shows that Noise equivalent differential temperature (NEdT) for IR channels is consistent and well within specifications.

  10. Automated Identification of Fiducial Points on 3D Torso Images

    PubMed Central

    Kawale, Manas M; Reece, Gregory P; Crosby, Melissa A; Beahm, Elisabeth K; Fingeret, Michelle C; Markey, Mia K; Merchant, Fatima A

    2013-01-01

    Breast reconstruction is an important part of the breast cancer treatment process for many women. Recently, 2D and 3D images have been used by plastic surgeons for evaluating surgical outcomes. Distances between different fiducial points are frequently used as quantitative measures for characterizing breast morphology. Fiducial points can be directly marked on subjects for direct anthropometry, or can be manually marked on images. This paper introduces novel algorithms to automate the identification of fiducial points in 3D images. Automating the process will make measurements of breast morphology more reliable, reducing the inter- and intra-observer bias. Algorithms to identify three fiducial points, the nipples, sternal notch, and umbilicus, are described. The algorithms used for localization of these fiducial points are formulated using a combination of surface curvature and 2D color information. Comparison of the 3D co-ordinates of automatically detected fiducial points and those identified manually, and geodesic distances between the fiducial points are used to validate algorithm performance. The algorithms reliably identified the location of all three of the fiducial points. We dedicate this article to our late colleague and friend, Dr. Elisabeth K. Beahm. Elisabeth was both a talented plastic surgeon and physician-scientist; we deeply miss her insight and her fellowship. PMID:25288903

  11. Femoroacetabular impingement with chronic acetabular rim fracture - 3D computed tomography, 3D magnetic resonance imaging and arthroscopic correlation

    PubMed Central

    Chhabra, Avneesh; Nordeck, Shaun; Wadhwa, Vibhor; Madhavapeddi, Sai; Robertson, William J

    2015-01-01

    Femoroacetabular impingement is uncommonly associated with a large rim fragment of bone along the superolateral acetabulum. We report an unusual case of femoroacetabular impingement (FAI) with chronic acetabular rim fracture. Radiographic, 3D computed tomography, 3D magnetic resonance imaging and arthroscopy correlation is presented with discussion of relative advantages and disadvantages of various modalities in the context of FAI. PMID:26191497

  12. Pavement cracking measurements using 3D laser-scan images

    NASA Astrophysics Data System (ADS)

    Ouyang, W.; Xu, B.

    2013-10-01

    Pavement condition surveying is vital for pavement maintenance programs that ensure ride quality and traffic safety. This paper first introduces an automated pavement inspection system which uses a three-dimensional (3D) camera and a structured laser light to acquire dense transverse profiles of a pavement lane surface when it carries a moving vehicle. After the calibration, the 3D system can yield a depth resolution of 0.5 mm and a transverse resolution of 1.56 mm pixel-1 at 1.4 m camera height from the ground. The scanning rate of the camera can be set to its maximum at 5000 lines s-1, allowing the density of scanned profiles to vary with the vehicle's speed. The paper then illustrates the algorithms that utilize 3D information to detect pavement distress, such as transverse, longitudinal and alligator cracking, and presents the field tests on the system's repeatability when scanning a sample pavement in multiple runs at the same vehicle speed, at different vehicle speeds and under different weather conditions. The results show that this dedicated 3D system can capture accurate pavement images that detail surface distress, and obtain consistent crack measurements in repeated tests and under different driving and lighting conditions.

  13. Triangulation Based 3D Laser Imaging for Fracture Orientation Analysis

    NASA Astrophysics Data System (ADS)

    Mah, J.; Claire, S.; Steve, M.

    2009-05-01

    Laser imaging has recently been identified as a potential tool for rock mass characterization. This contribution focuses on the application of triangulation based, short-range laser imaging to determine fracture orientation and surface texture. This technology measures the distance to the target by triangulating the projected and reflected laser beams, and also records the reflection intensity. In this study, we acquired 3D laser images of rock faces using the Laser Camera System (LCS), a portable instrument developed by Neptec Design Group (Ottawa, Canada). The LCS uses an infrared laser beam and is immune to the lighting conditions. The maximum image resolution is 1024 x 1024 volumetric image elements. Depth resolution is 0.5 mm at 5 m. An above ground field trial was conducted at a blocky road cut with well defined joint sets (Kingston, Ontario). An underground field trial was conducted at the Inco 175 Ore body (Sudbury, Ontario) where images were acquired in the dark and the joint set features were more subtle. At each site, from a distance of 3 m away from the rock face, a grid of six images (approximately 1.6 m by 1.6 m) was acquired at maximum resolution with 20% overlap between adjacent images. This corresponds to a density of 40 image elements per square centimeter. Polyworks, a high density 3D visualization software tool, was used to align and merge the images into a single digital triangular mesh. The conventional method of determining fracture orientations is by manual measurement using a compass. In order to be accepted as a substitute for this method, the LCS should be capable of performing at least to the capabilities of manual measurements. To compare fracture orientation estimates derived from the 3D laser images to manual measurements, 160 inclinometer readings were taken at the above ground site. Three prominent joint sets (strike/dip: 236/09, 321/89, 325/01) were identified by plotting the joint poles on a stereonet. Underground, two main joint

  14. Virtual image display as a backlight for 3D.

    PubMed

    Travis, Adrian; MacCrann, Niall; Emerton, Neil; Kollin, Joel; Georgiou, Andreas; Lanier, Jaron; Bathiche, Stephen

    2013-07-29

    We describe a device which has the potential to be used both as a virtual image display and as a backlight. The pupil of the emitted light fills the device approximately to its periphery and the collimated emission can be scanned both horizontally and vertically in the manner needed to illuminate an eye in any position. The aim is to reduce the power needed to illuminate a liquid crystal panel but also to enable a smooth transition from 3D to a virtual image as the user nears the screen. PMID:23938645

  15. 3D imaging of soil pore network: two different approaches

    NASA Astrophysics Data System (ADS)

    Matrecano, M.; Di Matteo, B.; Mele, G.; Terribile, F.

    2009-04-01

    Pore geometry imaging and its quantitative description is a key factor for advances in the knowledge of physical, chemical and biological soil processes. For many years photos from flattened surfaces of undisturbed soil samples impregnated with fluorescent resin and from soil thin sections under microscope have been the only way available for exploring pore architecture at different scales. Earlier 3D representations of the internal structure of the soil based on not destructive methods have been obtained using medical tomographic systems (NMR and X-ray CT). However, images provided using such equipments, show strong limitations in terms of spatial resolution. In the last decade very good results have then been obtained using imaging from very expensive systems based on synchrotron radiation. More recently, X-ray Micro-Tomography has resulted the most widely applied being the technique showing the best compromise between costs, resolution and size of the images. Conversely, the conceptually simpler but destructive method of "serial sectioning" has been progressively neglected for technical problems in sample preparation and time consumption needed to obtain an adequate number of serial sections for correct 3D reconstruction of soil pore geometry. In this work a comparison between the two methods above has been carried out in order to define advantages, shortcomings and to point out their different potential. A cylindrical undisturbed soil sample 6.5cm in diameter and 6.5cm height of an Ap horizon of an alluvial soil showing vertic characteristics, has been reconstructed using both a desktop X-ray micro-tomograph Skyscan 1172 and the new automatic serial sectioning system SSAT (Sequential Section Automatic Tomography) set up at CNR ISAFOM in Ercolano (Italy) with the aim to overcome most of the typical limitations of such a technique. Image best resolution of 7.5 µm per voxel resulted using X-ray Micro CT while 20 µm was the best value using the serial sectioning

  16. A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery.

    PubMed

    Nowell, Mark; Rodionov, Roman; Zombori, Gergely; Sparks, Rachel; Rizzi, Michele; Ourselin, Sebastien; Miserocchi, Anna; McEvoy, Andrew; Duncan, John

    2016-01-01

    Epilepsy surgery is challenging and the use of 3D multimodality image integration (3DMMI) to aid presurgical planning is well-established. Multimodality image integration can be technically demanding, and is underutilised in clinical practice. We have developed a single software platform for image integration, 3D visualization and surgical planning. Here, our pipeline is described in step-by-step fashion, starting with image acquisition, proceeding through image co-registration, manual segmentation, brain and vessel extraction, 3D visualization and manual planning of stereoEEG (SEEG) implantations. With dissemination of the software this pipeline can be reproduced in other centres, allowing other groups to benefit from 3DMMI. We also describe the use of an automated, multi-trajectory planner to generate stereoEEG implantation plans. Preliminary studies suggest this is a rapid, safe and efficacious adjunct for planning SEEG implantations. Finally, a simple solution for the export of plans and models to commercial neuronavigation systems for implementation of plans in the operating theater is described. This software is a valuable tool that can support clinical decision making throughout the epilepsy surgery pathway. PMID:27286266

  17. A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

    PubMed Central

    Nowell, Mark; Rodionov, Roman; Zombori, Gergely; Sparks, Rachel; Rizzi, Michele; Ourselin, Sebastien; Miserocchi, Anna; McEvoy, Andrew; Duncan, John

    2016-01-01

    Epilepsy surgery is challenging and the use of 3D multimodality image integration (3DMMI) to aid presurgical planning is well-established. Multimodality image integration can be technically demanding, and is underutilised in clinical practice. We have developed a single software platform for image integration, 3D visualization and surgical planning. Here, our pipeline is described in step-by-step fashion, starting with image acquisition, proceeding through image co-registration, manual segmentation, brain and vessel extraction, 3D visualization and manual planning of stereoEEG (SEEG) implantations. With dissemination of the software this pipeline can be reproduced in other centres, allowing other groups to benefit from 3DMMI. We also describe the use of an automated, multi-trajectory planner to generate stereoEEG implantation plans. Preliminary studies suggest this is a rapid, safe and efficacious adjunct for planning SEEG implantations. Finally, a simple solution for the export of plans and models to commercial neuronavigation systems for implementation of plans in the operating theater is described. This software is a valuable tool that can support clinical decision making throughout the epilepsy surgery pathway. PMID:27286266

  18. On-line range images registration with GPGPU

    NASA Astrophysics Data System (ADS)

    Będkowski, J.; Naruniec, J.

    2013-03-01

    This paper concerns implementation of algorithms in the two important aspects of modern 3D data processing: data registration and segmentation. Solution proposed for the first topic is based on the 3D space decomposition, while the latter on image processing and local neighbourhood search. Data processing is implemented by using NVIDIA compute unified device architecture (NIVIDIA CUDA) parallel computation. The result of the segmentation is a coloured map where different colours correspond to different objects, such as walls, floor and stairs. The research is related to the problem of collecting 3D data with a RGB-D camera mounted on a rotated head, to be used in mobile robot applications. Performance of the data registration algorithm is aimed for on-line processing. The iterative closest point (ICP) approach is chosen as a registration method. Computations are based on the parallel fast nearest neighbour search. This procedure decomposes 3D space into cubic buckets and, therefore, the time of the matching is deterministic. First technique of the data segmentation uses accele-rometers integrated with a RGB-D sensor to obtain rotation compensation and image processing method for defining pre-requisites of the known categories. The second technique uses the adapted nearest neighbour search procedure for obtaining normal vectors for each range point.

  19. Automatic structural matching of 3D image data

    NASA Astrophysics Data System (ADS)

    Ponomarev, Svjatoslav; Lutsiv, Vadim; Malyshev, Igor

    2015-10-01

    A new image matching technique is described. It is implemented as an object-independent hierarchical structural juxtaposition algorithm based on an alphabet of simple object-independent contour structural elements. The structural matching applied implements an optimized method of walking through a truncated tree of all possible juxtapositions of two sets of structural elements. The algorithm was initially developed for dealing with 2D images such as the aerospace photographs, and it turned out to be sufficiently robust and reliable for matching successfully the pictures of natural landscapes taken in differing seasons from differing aspect angles by differing sensors (the visible optical, IR, and SAR pictures, as well as the depth maps and geographical vector-type maps). At present (in the reported version), the algorithm is enhanced based on additional use of information on third spatial coordinates of observed points of object surfaces. Thus, it is now capable of matching the images of 3D scenes in the tasks of automatic navigation of extremely low flying unmanned vehicles or autonomous terrestrial robots. The basic principles of 3D structural description and matching of images are described, and the examples of image matching are presented.

  20. Mesh generation from 3D multi-material images.

    PubMed

    Boltcheva, Dobrina; Yvinec, Mariette; Boissonnat, Jean-Daniel

    2009-01-01

    The problem of generating realistic computer models of objects represented by 3D segmented images is important in many biomedical applications. Labelled 3D images impose particular challenges for meshing algorithms because multi-material junctions form features such as surface pacthes, edges and corners which need to be preserved into the output mesh. In this paper, we propose a feature preserving Delaunay refinement algorithm which can be used to generate high-quality tetrahedral meshes from segmented images. The idea is to explicitly sample corners and edges from the input image and to constrain the Delaunay refinement algorithm to preserve these features in addition to the surface patches. Our experimental results on segmented medical images have shown that, within a few seconds, the algorithm outputs a tetrahedral mesh in which each material is represented as a consistent submesh without gaps and overlaps. The optimization property of the Delaunay triangulation makes these meshes suitable for the purpose of realistic visualization or finite element simulations. PMID:20426123