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Sample records for 3d-2d registration methods

  1. 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

  2. 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

  3. 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).

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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.

  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. 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.

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. Automated 3D-2D registration of X-ray microcomputed tomography with histological sections for dental implants in bone using chamfer matching and simulated annealing.

    PubMed

    Becker, Kathrin; Stauber, Martin; Schwarz, Frank; Beißbarth, Tim

    2015-09-01

    We propose a novel 3D-2D registration approach for micro-computed tomography (μCT) and histology (HI), constructed for dental implant biopsies, that finds the position and normal vector of the oblique slice from μCT that corresponds to HI. During image pre-processing, the implants and the bone tissue are segmented using a combination of thresholding, morphological filters and component labeling. After this, chamfer matching is employed to register the implant edges and fine registration of the bone tissues is achieved using simulated annealing. The method was tested on n=10 biopsies, obtained at 20 weeks after non-submerged healing in the canine mandible. The specimens were scanned with μCT 100 and processed for hard tissue sectioning. After registration, we assessed the agreement of bone to implant contact (BIC) using automated and manual measurements. Statistical analysis was conducted to test the agreement of the BIC measurements in the registered samples. Registration was successful for all specimens and agreement of the respective binary images was high (median: 0.90, 1.-3. Qu.: 0.89-0.91). Direct comparison of BIC yielded that automated (median 0.82, 1.-3. Qu.: 0.75-0.85) and manual (median 0.61, 1.-3. Qu.: 0.52-0.67) measures from μCT were significant positively correlated with HI (median 0.65, 1.-3. Qu.: 0.59-0.72) between μCT and HI groups (manual: R(2)=0.87, automated: R(2)=0.75, p<0.001). The results show that this method yields promising results and that μCT may become a valid alternative to assess osseointegration in three dimensions. PMID:26026659

  4. Automatic localization of vertebral levels in x-ray fluoroscopy using 3D-2D registration: a tool to reduce wrong-site surgery

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

    Surgical targeting of the incorrect vertebral level (wrong-level surgery) is among the more common wrong-site surgical errors, attributed primarily to the lack of uniquely identifiable radiographic landmarks in the mid-thoracic spine. The conventional localization method involves manual counting of vertebral bodies under fluoroscopy, is prone to human error and carries additional time and dose. We propose an image registration and visualization system (referred to as LevelCheck), for decision support in spine surgery by automatically labeling vertebral levels in fluoroscopy using a GPU-accelerated, intensity-based 3D-2D (namely CT-to-fluoroscopy) registration. A gradient information (GI) similarity metric and a CMA-ES optimizer were chosen due to their robustness and inherent suitability for parallelization. Simulation studies involved ten patient CT datasets from which 50 000 simulated fluoroscopic images were generated from C-arm poses selected to approximate the C-arm operator and positioning variability. Physical experiments used an anthropomorphic chest phantom imaged under real fluoroscopy. The registration accuracy was evaluated as the mean projection distance (mPD) between the estimated and true center of vertebral levels. Trials were defined as successful if the estimated position was within the projection of the vertebral body (namely mPD <5 mm). Simulation studies showed a success rate of 99.998% (1 failure in 50 000 trials) and computation time of 4.7 s on a midrange GPU. Analysis of failure modes identified cases of false local optima in the search space arising from longitudinal periodicity in vertebral structures. Physical experiments demonstrated the robustness of the algorithm against quantum noise and x-ray scatter. The ability to automatically localize target anatomy in fluoroscopy in near-real-time could be valuable in reducing the occurrence of wrong-site surgery while helping to reduce radiation exposure. The method is applicable beyond

  5. 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

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. Color constancy in 3D-2D face recognition

    NASA Astrophysics Data System (ADS)

    Meyer, Manuel; Riess, Christian; Angelopoulou, Elli; Evangelopoulos, Georgios; Kakadiaris, Ioannis A.

    2013-05-01

    Face is one of the most popular biometric modalities. However, up to now, color is rarely actively used in face recognition. Yet, it is well-known that when a person recognizes a face, color cues can become as important as shape, especially when combined with the ability of people to identify the color of objects independent of illuminant color variations. In this paper, we examine the feasibility and effect of explicitly embedding illuminant color information in face recognition systems. We empirically examine the theoretical maximum gain of including known illuminant color to a 3D-2D face recognition system. We also investigate the impact of using computational color constancy methods for estimating the illuminant color, which is then incorporated into the face recognition framework. Our experiments show that under close-to-ideal illumination estimates, one can improve face recognition rates by 16%. When the illuminant color is algorithmically estimated, the improvement is approximately 5%. These results suggest that color constancy has a positive impact on face recognition, but the accuracy of the illuminant color estimate has a considerable effect on its benefits.

  11. Comparative study on 3D-2D convertible integral imaging systems

    NASA Astrophysics Data System (ADS)

    Choi, Heejin; Kim, Joohwan; Kim, Yunhee; Lee, Byoungho

    2006-02-01

    In spite of significant improvements in three-dimensional (3D) display fields, the commercialization of a 3D-only display system is not achieved yet. The mainstream of display market is a high performance two-dimensional (2D) flat panel display (FPD) and the beginning of the high-definition (HD) broadcasting accelerates the opening of the golden age of HD FPDs. Therefore, a 3D display system needs to be able to display a 2D image with high quality. In this paper, two different 3D-2D convertible methods based on integral imaging are compared and categorized for its applications. One method uses a point light source array and a polymer-dispersed liquid crystal and one display panel. The other system adopts two display panels and a lens array. The former system is suitable for mobile applications while the latter is for home applications such as monitors and TVs.

  12. The impact of specular highlights on 3D-2D face recognition

    NASA Astrophysics Data System (ADS)

    Christlein, Vincent; Riess, Christian; Angelopoulou, Elli; Evangelopoulos, Georgios; Kakadiaris, Ioannis

    2013-05-01

    One of the most popular form of biometrics is face recognition. Face recognition techniques typically assume that a face exhibits Lambertian reectance. However, a face often exhibits prominent specularities, especially in outdoor environments. These specular highlights can compromise an identity authentication. In this work, we analyze the impact of such highlights on a 3D-2D face recognition system. First, we investigate three different specularity removal methods as preprocessing steps for face recognition. Then, we explicitly model facial specularities within the face detection system with the Cook-Torrance reflectance model. In our experiments, specularity removal increases the recognition rate on an outdoor face database by about 5% at a false alarm rate of 10-3. The integration of the Cook-Torrance model further improves these results, increasing the verification rate by 19% at a FAR of 10-3.

  13. Spectroscopic investigation of the 3d 2D → nf 2F transitions in lithium

    NASA Astrophysics Data System (ADS)

    Shahzada, S.; Shah, M.; Haq, S. U.; Nawaz, M.; Ahmed, M.; Nadeem, Ali

    2016-05-01

    We report term energies and effective quantum numbers of the odd parity 3d 2D → nf 2F series of lithium using multi-step and multi-photon laser excitation schemes. The experiments were performed using three dye lasers simultaneously pumped by the second harmonic (532 nm) of a Q-switched Nd:YAG laser in conjunction with an atomic beam apparatus and thermionic diode ion detector. The first ionization potential of lithium has been determined as 43,487.13 ± 0.02 cm- 1 from the much extended 3d 2D → nf 2F (17 ≤ n ≤ 70) series. In addition, the oscillator strengths of the 3d 2D → nf 2F (15 ≤ n ≤ 48) transitions have been determined, showing a decreasing trend with the increase in principal quantum number n.

  14. 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.

  15. Spectroscopic Investigation of the Odd-Parity 3 d 2 D → nf 2 F Transitions of Neutral Sodium

    NASA Astrophysics Data System (ADS)

    Nadeem, A.; Shah, M.; Shahzada, S.; Ahmed, M.; Haq, S. U.

    2015-11-01

    We report new experimental data on term energies and effective quantum numbers of the odd parity Rydberg states of sodium in the 40687-41408 cm-1 energy range. The experiment was performed using a two-color scheme of three-photon laser excitation in conjunction with a thermionic diode ion detector. The new observation includes much extended nf 2 F (12 ≤ n ≤ 51) series excited from the 3 d 2 D intermediate state. In addition, oscillator strengths of the 3 d 2 D → nf 2 F (16 ≤ n ≤ 45) Rydberg transitions have been determined and a complete picture is presented from n = 4-45 incorporating the present work and earlier computed results.

  16. Application of a Hybrid 3D-2D Laser Scanning System to the Characterization of Slate Slabs

    PubMed Central

    López, Marcos; Martínez, Javier; Matías, José María; Vilán, José Antonio; Taboada, Javier

    2010-01-01

    Dimensional control based on 3D laser scanning techniques is widely used in practice. We describe the application of a hybrid 3D-2D laser scanning system to the characterization of slate slabs with structural defects that are difficult for the human eye to characterize objectively. Our study is based on automating the process using a 3D laser scanner and a 2D camera. Our results demonstrate that the application of this hybrid system optimally characterizes slate slabs in terms of the defects described by the Spanish UNE-EN 12326-1 standard. PMID:22219696

  17. Creating bio-inspired hierarchical 3D-2D photonic stacks via planar lithography on self-assembled inverse opals.

    PubMed

    Burgess, Ian B; Aizenberg, Joanna; Lončar, Marko

    2013-12-01

    Structural hierarchy and complex 3D architecture are characteristics of biological photonic designs that are challenging to reproduce in synthetic materials. Top-down lithography allows for designer patterning of arbitrary shapes, but is largely restricted to planar 2D structures. Self-assembly techniques facilitate easy fabrication of 3D photonic crystals, but controllable defect-integration is difficult. In this paper we combine the advantages of top-down and bottom-up fabrication, developing two techniques to deposit 2D-lithographically-patterned planar layers on top of or in between inverse-opal 3D photonic crystals and creating hierarchical structures that resemble the architecture of the bright green wing scales of the butterfly, Parides sesostris. These fabrication procedures, combining advantages of both top-down and bottom-up fabrication, may prove useful in the development of omnidirectional coloration elements and 3D-2D photonic crystal devices. PMID:24263010

  18. Experimental investigation of photoionization cross section for the 3d 2D excited states of lithium and sodium

    NASA Astrophysics Data System (ADS)

    Nadeem, Ali; Shah, Mehmood; Shahzada, Shaista; Ahmed, Mushtaq; Haq, Sami-ul-

    2013-09-01

    We report experimentally measured photoionization cross sections for the 3 d 2D excited states of lithium and sodium at first ionization threshold. The experiments were performed using two dye lasers simultaneously pumped by the second harmonic of a Nd:YAG laser. The vapor contentment and the detection system was a thermionic diode ion detector operating in a space charge limited mode. Photoionization cross sections of the excited states were deduced from the dependence of ion signal intensity on the ionizing laser energies as 19 ± 3 Mb and 21.5 ± 3.5 Mb for lithium and sodium respectively, which are in good agreement with the previously computed theoretical results.

  19. A computationally efficient method for automatic registration of orthogonal x-ray images with volumetric CT data

    NASA Astrophysics Data System (ADS)

    Chen, Xin; Varley, Martin R.; Shark, Lik-Kwan; Shentall, Glyn S.; Kirby, Mike C.

    2008-02-01

    The paper presents a computationally efficient 3D-2D image registration algorithm for automatic pre-treatment validation in radiotherapy. The novel aspects of the algorithm include (a) a hybrid cost function based on partial digitally reconstructed radiographs (DRRs) generated along projected anatomical contours and a level set term for similarity measurement; and (b) a fast search method based on parabola fitting and sensitivity-based search order. Using CT and orthogonal x-ray images from a skull and a pelvis phantom, the proposed algorithm is compared with the conventional ray-casting full DRR based registration method. Not only is the algorithm shown to be computationally more efficient with registration time being reduced by a factor of 8, but also the algorithm is shown to offer 50% higher capture range allowing the initial patient displacement up to 15 mm (measured by mean target registration error). For the simulated data, high registration accuracy with average errors of 0.53 mm ± 0.12 mm for translation and 0.61° ± 0.29° for rotation within the capture range has been achieved. For the tested phantom data, the algorithm has also shown to be robust without being affected by artificial markers in the image.

  20. Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance

    PubMed Central

    Dang, H.; Otake, Y.; Schafer, S.; Stayman, J. W.; Kleinszig, G.; Siewerdsen, J. H.

    2012-01-01

    Purpose: Real-time surgical navigation relies on accurate image-to-world registration to align the coordinate systems of the image and patient. Conventional manual registration can present a workflow bottleneck and is prone to manual error and intraoperator variability. This work reports alternative means of automatic image-to-world registration, each method involving an automatic registration marker (ARM) used in conjunction with C-arm cone-beam CT (CBCT). The first involves a Known-Model registration method in which the ARM is a predefined tool, and the second is a Free-Form method in which the ARM is freely configurable. Methods: Studies were performed using a prototype C-arm for CBCT and a surgical tracking system. A simple ARM was designed with markers comprising a tungsten sphere within infrared reflectors to permit detection of markers in both x-ray projections and by an infrared tracker. The Known-Model method exercised a predefined specification of the ARM in combination with 3D-2D registration to estimate the transformation that yields the optimal match between forward projection of the ARM and the measured projection images. The Free-Form method localizes markers individually in projection data by a robust Hough transform approach extended from previous work, backprojected to 3D image coordinates based on C-arm geometric calibration. Image-domain point sets were transformed to world coordinates by rigid-body point-based registration. The robustness and registration accuracy of each method was tested in comparison to manual registration across a range of body sites (head, thorax, and abdomen) of interest in CBCT-guided surgery, including cases with interventional tools in the radiographic scene. Results: The automatic methods exhibited similar target registration error (TRE) and were comparable or superior to manual registration for placement of the ARM within ∼200 mm of C-arm isocenter. Marker localization in projection data was robust across all

  1. Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance

    SciTech Connect

    Dang, H.; Otake, Y.; Schafer, S.; Stayman, J. W.; Kleinszig, G.; Siewerdsen, J. H.

    2012-10-15

    Purpose: Real-time surgical navigation relies on accurate image-to-world registration to align the coordinate systems of the image and patient. Conventional manual registration can present a workflow bottleneck and is prone to manual error and intraoperator variability. This work reports alternative means of automatic image-to-world registration, each method involving an automatic registration marker (ARM) used in conjunction with C-arm cone-beam CT (CBCT). The first involves a Known-Model registration method in which the ARM is a predefined tool, and the second is a Free-Form method in which the ARM is freely configurable. Methods: Studies were performed using a prototype C-arm for CBCT and a surgical tracking system. A simple ARM was designed with markers comprising a tungsten sphere within infrared reflectors to permit detection of markers in both x-ray projections and by an infrared tracker. The Known-Model method exercised a predefined specification of the ARM in combination with 3D-2D registration to estimate the transformation that yields the optimal match between forward projection of the ARM and the measured projection images. The Free-Form method localizes markers individually in projection data by a robust Hough transform approach extended from previous work, backprojected to 3D image coordinates based on C-arm geometric calibration. Image-domain point sets were transformed to world coordinates by rigid-body point-based registration. The robustness and registration accuracy of each method was tested in comparison to manual registration across a range of body sites (head, thorax, and abdomen) of interest in CBCT-guided surgery, including cases with interventional tools in the radiographic scene. Results: The automatic methods exhibited similar target registration error (TRE) and were comparable or superior to manual registration for placement of the ARM within {approx}200 mm of C-arm isocenter. Marker localization in projection data was robust across all

  2. Personal identification by the comparison of facial profiles: testing the reliability of a high-resolution 3D-2D comparison model.

    PubMed

    Cattaneo, Cristina; Cantatore, Angela; Ciaffi, Romina; Gibelli, Daniele; Cigada, Alfredo; De Angelis, Danilo; Sala, Remo

    2012-01-01

    Identification from video surveillance systems is frequently requested in forensic practice. The "3D-2D" comparison has proven to be reliable in assessing identification but still requires standardization; this study concerns the validation of the 3D-2D profile comparison. The 3D models of the faces of five individuals were compared with photographs from the same subjects as well as from another 45 individuals. The difference in area and distance between maxima (glabella, tip of nose, fore point of upper and lower lips, pogonion) and minima points (selion, subnasale, stomion, suprapogonion) were measured. The highest difference in area between the 3D model and the 2D image was between 43 and 133 mm(2) in the five matches, always greater than 157 mm(2) in mismatches; the mean distance between the points was greater than 1.96 mm in mismatches, <1.9 mm in five matches (p < 0.05). These results indicate that this difference in areas may point toward a manner of distinguishing "correct" from "incorrect" matches. PMID:22074112

  3. A multicore based parallel image registration method.

    PubMed

    Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L; Foran, David J

    2009-01-01

    Image registration is a crucial step for many image-assisted clinical applications such as surgery planning and treatment evaluation. In this paper we proposed a landmark based nonlinear image registration algorithm for matching 2D image pairs. The algorithm was shown to be effective and robust under conditions of large deformations. In landmark based registration, the most important step is establishing the correspondence among the selected landmark points. This usually requires an extensive search which is often computationally expensive. We introduced a nonregular data partition algorithm using the K-means clustering algorithm to group the landmarks based on the number of available processing cores. The step optimizes the memory usage and data transfer. We have tested our method using IBM Cell Broadband Engine (Cell/B.E.) platform. PMID:19964921

  4. Advanced Tsunami Numerical Simulations and Energy Considerations by use of 3D-2D Coupled Models: The October 11, 1918, Mona Passage Tsunami

    NASA Astrophysics Data System (ADS)

    López-Venegas, Alberto M.; Horrillo, Juan; Pampell-Manis, Alyssa; Huérfano, Victor; Mercado, Aurelio

    2015-06-01

    The most recent tsunami observed along the coast of the island of Puerto Rico occurred on October 11, 1918, after a magnitude 7.2 earthquake in the Mona Passage. The earthquake was responsible for initiating a tsunami that mostly affected the northwestern coast of the island. Runup values from a post-tsunami survey indicated the waves reached up to 6 m. A controversy regarding the source of the tsunami has resulted in several numerical simulations involving either fault rupture or a submarine landslide as the most probable cause of the tsunami. Here we follow up on previous simulations of the tsunami from a submarine landslide source off the western coast of Puerto Rico as initiated by the earthquake. Improvements on our previous study include: (1) higher-resolution bathymetry; (2) a 3D-2D coupled numerical model specifically developed for the tsunami; (3) use of the non-hydrostatic numerical model NEOWAVE (non-hydrostatic evolution of ocean WAVE) featuring two-way nesting capabilities; and (4) comprehensive energy analysis to determine the time of full tsunami wave development. The three-dimensional Navier-Stokes model tsunami solution using the Navier-Stokes algorithm with multiple interfaces for two fluids (water and landslide) was used to determine the initial wave characteristic generated by the submarine landslide. Use of NEOWAVE enabled us to solve for coastal inundation, wave propagation, and detailed runup. Our results were in agreement with previous work in which a submarine landslide is favored as the most probable source of the tsunami, and improvement in the resolution of the bathymetry yielded inundation of the coastal areas that compare well with values from a post-tsunami survey. Our unique energy analysis indicates that most of the wave energy is isolated in the wave generation region, particularly at depths near the landslide, and once the initial wave propagates from the generation region its energy begins to stabilize.

  5. 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.

  6. The fold-and-thrust tectonic setting of the Mesozoic carbonate units of Eastern Sardinia: insights from 3D (2D + t) modelling

    NASA Astrophysics Data System (ADS)

    Arragoni, Simone; Cianfarra, Paola; Maggi, Matteo; Salvini, Francesco

    2015-04-01

    Present-day Eastern Sardinia structural setting was mainly determined by Cenozoic strike-slip-to-oblique faulting in the Tacchi and Golfo di Orosei regions, where Mesozoic shallow water carbonates crop out (Costamagna and Barca, 2004 and references therein). These structures are interpreted as the effects of the rotation of the Sardinia-Corsica block during Oligocene and the successive opening of the Tyrrhenian sea starting from lower Miocene (Oggiano et al., 2009 and references therein). New structural data indicate the presence of dip-slip compressive tectonics and thrusting affecting the Mesozoic carbonates and involving the underlying Paleozoic basement. This event shows a westward vergence (top-to-the-W) and is cut by later strike-slip faults. The age of this tectonics is constrained between Eocene (Lutetian rocks involved) and Oligo-Miocene (post-dated by the strike-slip tectonic event). The integration between these new structural observations and the available geological and geophysical datasets allowed to construct a balanced and admissible geological cross section in order to study the tectonic evolution of eastern Sardinia before the opening of the Tyrrhenian basin. The orientation of the section is parallel to the direction of the tectonic transport, that is WSW-ENE. The balanced cross-section has been modelled with the "Forctre" software in order to get a 3D (2D + t) evolutionary model and check its admissibility through time. The final section shows a thin-skin geometry (flats sectors prevailing over ramps) and is composed of two main tectonic slices deeply involving the Paleozoic basement and secondary thrusting affecting the Mesozoic carbonate units. These are characterized by "younger-on-older" flat-over-flat tectonics evidenced by Cretaceous-over-Jurassic thrusting. Similar geometries have been described also in the Latium-Abruzzi sector of the Southern Apennines. Costamagna L.G. & Barca S. 2004. Stratigrafia, analisi di facies, paleogeografia ed

  7. A 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 Claude; Salvado, Olivier

    2010-03-01

    Micro-CT/PET imaging scanner provides a powerful tool to study tumor in small rodents in response to therapy. Accurate image registration is a necessary step to quantify the characteristics of images acquired in longitudinal studies. Small animal registration is challenging because of the very deformable body of the animal often resulting in different postures despite physical restraints. In this paper, we propose a non-rigid registration approach for the automatic registration of mouse whole body skeletons, which is based on our improved 3D shape context non-rigid registration method. The whole body skeleton registration approach has been tested on 21 pairs of mouse CT images with variations of individuals and time-instances. The experimental results demonstrated the stability and accuracy of the proposed method for automatic mouse whole body skeleton registration.

  8. Digital image registration method using boundary maps

    NASA Technical Reports Server (NTRS)

    Andrus, J. F.; Campbell, C. W.; Jayroe, R. R.

    1975-01-01

    A new method of automatic image registration (matching) is presented. It requires that the original single or multichannel images first be converted to binary boundary maps having elements equal to zero or unity. The method corrects for both translational and rotational errors. One feature of the technique is the rapid calculation of a pseudo correlation matrix NCOR using only integer additions. It is argued that the use of boundary maps is advisable when the data from the two images are acquired under different conditions; i.e., weather conditions, lighting conditions, etc.

  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. 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.

  12. Tools and Methods for the Registration and Fusion of Remotely Sensed Data

    NASA Technical Reports Server (NTRS)

    Goshtasby, Arthur Ardeshir; LeMoigne, Jacqueline

    2010-01-01

    Tools and methods for image registration were reviewed. Methods for the registration of remotely sensed data at NASA were discussed. Image fusion techniques were reviewed. Challenges in registration of remotely sensed data were discussed. Examples of image registration and image fusion were given.

  13. Gauss-Newton method for DEM co-registration

    NASA Astrophysics Data System (ADS)

    Wang, Kunlun; Zhang, Tonggang

    2015-12-01

    Digital elevation model (DEM) co-registration is one of the hottest research problems, and it is the critical technology for multi-temporal DEM analysis, which has wide potential application in many fields, such as geological hazards. Currently, the least-squares principle is used in most DEM co-registration methods, in which the matching parameters are obtained by iteration; the surface co-registration is then accomplished. To improve the iterative convergence rate, a Gauss-Newton method for DEM co-registration (G-N) is proposed in this paper. A gradient formula based on a gridded discrete surface is derived in theory, and then the difficulty of applying the Gauss-Newton method to DEM matching is solved. With the G-N algorithm, the surfaces approach each other along the maximal gradient direction, and therefore the iterative convergence and the performance efficiency of the new method can be enhanced greatly. According to experimental results based on the simulated datasets, the average convergence rates of rotation and translation parameters of the G-N algorithm are increased by 40 and 15% compared to those of the ICP algorithm, respectively. The performance efficiency of the G-N algorithm is 74.9% better.

  14. Ab initio and long-range investigation of the Ω(+/-) states of NaK dissociating adiabatically up to Na(3s 2S1/2) + K(3d 2D3/2)

    NASA Astrophysics Data System (ADS)

    Allouche, A. R.; Aubert-Frécon, M.

    2011-07-01

    A theoretical investigation of the electronic structure of the NaK molecule including spin-orbit effects has been performed for the 34 Ω(+/-) states dissociating adiabatically into the limits up to Na(3s2S1/2) + K(3d2D3/2) from both an ab initio approach and a long-range model. Equilibrium distances, transition energies, harmonic frequencies as well as depths of wells and heights of humps are reported for all the states. Formulas for calculating the long-range energies for all the 0+/-, 1, 2, and 3 states under investigation are also displayed. They are expressed in terms of the Cn (n = 6,8, …) long-range coefficients and exchange integrals for the 2S+1Λ(+) parent states, available from literature. As present data could help experimentalists we make available extensive tables of energy values versus internuclear distances in our database at the web address: http://www-lasim.univ-lyon1.fr/spip.php?rubrique99.

  15. Fourier method for large scale surface modeling and registration.

    PubMed

    Shen, Li; Kim, Sungeun; Saykin, Andrew J

    2009-06-01

    Spherical harmonic (SPHARM) description is a powerful Fourier shape modeling method for processing arbitrarily shaped but simply connected 3D objects. As a highly promising method, SPHARM has been widely used in several domains including medical imaging. However, its primary use has been focused on modeling small or moderately-sized surfaces that are relatively smooth, due to challenges related to its applicability, robustness and scalability. This paper presents an enhanced SPHARM framework that addresses these issues and show that the use of SPHARM can expand into broader areas. In particular, we present a simple and efficient Fourier expansion method on the sphere that enables large scale modeling, and propose a new SPHARM registration method that aims to preserve the important homological properties between 3D models. Although SPHARM is a global descriptor, our experimental results show that the proposed SPHARM framework can accurately describe complicated graphics models and highly convoluted 3D surfaces and the proposed registration method allows for effective alignment and registration of these 3D models for further processing or analysis. These methods greatly enable the potential of applying SPHARM to broader areas such as computer graphics, medical imaging, CAD/CAM, bioinformatics, and other related geometric modeling and processing fields. PMID:20161536

  16. 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.

  17. A novel parametric method for non-rigid image registration.

    PubMed

    Cuzol, Anne; Hellier, Pierre; Mémin, Etienne

    2005-01-01

    This paper presents a novel non-rigid registration method. The main contribution of the method is the modeling of the vorticity (respectively divergence) of the deformation field using vortex (respectively sink and source) particles. Two parameters are associated with a particle: the vorticity (or divergence) strength and the influence domain. This leads to a very compact representation of vorticity and divergence fields. In addition, the optimal position of these particles is determined using a mean shift process. 2D experiments of this method are presented and demonstrate its ability to recover evolving phenomena (MS lesions) so as to register images from 20 patients. PMID:17354717

  18. Robust image registration using adaptive coherent point drift method

    NASA Astrophysics Data System (ADS)

    Yang, Lijuan; Tian, Zheng; Zhao, Wei; Wen, Jinhuan; Yan, Weidong

    2016-04-01

    Coherent point drift (CPD) method is a powerful registration tool under the framework of the Gaussian mixture model (GMM). However, the global spatial structure of point sets is considered only without other forms of additional attribute information. The equivalent simplification of mixing parameters and the manual setting of the weight parameter in GMM make the CPD method less robust to outlier and have less flexibility. An adaptive CPD method is proposed to automatically determine the mixing parameters by embedding the local attribute information of features into the construction of GMM. In addition, the weight parameter is treated as an unknown parameter and automatically determined in the expectation-maximization algorithm. In image registration applications, the block-divided salient image disk extraction method is designed to detect sparse salient image features and local self-similarity is used as attribute information to describe the local neighborhood structure of each feature. The experimental results on optical images and remote sensing images show that the proposed method can significantly improve the matching performance.

  19. Warped document image correction method based on heterogeneous registration strategies

    NASA Astrophysics Data System (ADS)

    Tong, Lijing; Zhan, Guoliang; Peng, Quanyao; Li, Yang; Li, Yifan

    2013-03-01

    With the popularity of digital camera and the application requirement of digitalized document images, using digital cameras to digitalize document images has become an irresistible trend. However, the warping of the document surface impacts on the quality of the Optical Character Recognition (OCR) system seriously. To improve the warped document image's vision quality and the OCR rate, this paper proposed a warped document image correction method based on heterogeneous registration strategies. This method mosaics two warped images of the same document from different viewpoints. Firstly, two feature points are selected from one image. Then the two feature points are registered in the other image base on heterogeneous registration strategies. At last, image mosaics are done for the two images, and the best mosaiced image is selected by OCR recognition results. As a result, for the best mosaiced image, the distortions are mostly removed and the OCR results are improved markedly. Experimental results show that the proposed method can resolve the issue of warped document image correction more effectively.

  20. Intensity based methods for brain MRI longitudinal registration. A study on multiple sclerosis patients.

    PubMed

    Diez, Yago; Oliver, Arnau; Cabezas, Mariano; Valverde, Sergi; Martí, Robert; Vilanova, Joan Carles; Ramió-Torrentà, Lluís; Rovira, Alex; Lladó, Xavier

    2014-07-01

    Registration is a key step in many automatic brain Magnetic Resonance Imaging (MRI) applications. In this work we focus on longitudinal registration of brain MRI for Multiple Sclerosis (MS) patients. First of all, we analyze the effect that MS lesions have on registration by synthetically eliminating some of the lesions. Our results show how a widely used method for longitudinal registration such as rigid registration is practically unconcerned by the presence of MS lesions while several non-rigid registration methods produce outputs that are significantly different. We then focus on assessing which is the best registration method for longitudinal MRI images of MS patients. In order to analyze the results obtained for all studied criteria, we use both descriptive statistics and statistical inference: one way ANOVA, pairwise t-tests and permutation tests. PMID:24338728

  1. SU-E-J-196: New Visualization Methods for Longitudinal MRI Registrations and Segmentations

    SciTech Connect

    Veeraraghavan, H; Deasy, J

    2014-06-01

    Purpose: To develop visualization techniques to facilitate easy assessment of (a) registration and (b) tracking volumetric changes in structures during radiation therapy from MRI. Method: The frequently used method for visualizing registrations between scans is a multi-color overlay technique or deformation vector fields. However, the overlay technique is unintuitive and does not help to appreciate the quality of registration particularly when the registration mismatches are not very large. Similarly, the deformation fields give an indication of extent of deformation but do not help to assess the differences in registration. We present a mirroring and edge-augmented mirroring technique that places the fixed and moving image next to each other and allows the user to quickly assess the small differences in registration. Next, we present a volumetric intersection based 3D model to visualize the changes in diseased lymph node volumes in head and neck cancer. 3D model-based visualization provides more information about the location-specific changes in volume rather than the simplistic one dimensional information obtained from 2D plot of nodal volume changes. Result: We show results comparing our approach with the standard colorbased overlay method for comparing registrations of intra-patient registrations using T2-MRI. Upon comparing the mirroring technique with the color-overlay, one can more easily appreciate the differences in registration. Adding edge-based mirroring seems to further assist in evaluating the registration. Our approach for viewing registrations seems to be more intuitive and easy to use in order to help assess the quality of registration compared to color-based overlays. Similarly, the change volumetric model together with a 2D plot reveals more information including the locations undergoing changes and responding to treatment. Conclusions: Better approaches are necessary for assessing the quality of registrations and changes in diseased structures

  2. An Innovative Class Registration Method Based on Bar Code Input.

    ERIC Educational Resources Information Center

    Freeman, Raoul J.

    1983-01-01

    Describes system of computerized class registration utilizing bar code input which is part of the Student Data System, developed by Management Information Division of the Los Angeles Unified School District. An explanation of the system notes the hardware used, printing of bar code labels, registration procedures, and operational aspects. (EJS)

  3. Digital image registration method based upon binary boundary maps

    NASA Technical Reports Server (NTRS)

    Jayroe, R. R., Jr.; Andrus, J. F.; Campbell, C. W.

    1974-01-01

    A relatively fast method is presented for matching or registering the digital data of imagery from the same ground scene acquired at different times, or from different multispectral images, sensors, or both. It is assumed that the digital images can be registed by using translations and rotations only, that the images are of the same scale, and that little or no distortion exists between images. It is further assumed that by working with several local areas of the image, the rotational effects in the local areas can be neglected. Thus, by treating the misalignments of local areas as translations, it is possible to determine rotational and translational misalignments for a larger portion of the image containing the local areas. This procedure of determining the misalignment and then registering the data according to the misalignment can be repeated until the desired degree of registration is achieved. The method to be presented is based upon the use of binary boundary maps produced from the raw digital imagery rather than the raw digital data.

  4. Wobbled splatting--a fast perspective volume rendering method for simulation of x-ray images from CT.

    PubMed

    Birkfellner, Wolfgang; Seemann, Rudolf; Figl, Michael; Hummel, Johann; Ede, Christopher; Homolka, Peter; Yang, Xinhui; Niederer, Peter; Bergmann, Helmar

    2005-05-01

    3D/2D registration, the automatic assignment of a global rigid-body transformation matching the coordinate systems of patient and preoperative volume scan using projection images, is an important topic in image-guided therapy and radiation oncology. A crucial part of most 3D/2D registration algorithms is the fast computation of digitally rendered radiographs (DRRs) to be compared iteratively to radiographs or portal images. Since registration is an iterative process, fast generation of DRRs-which are perspective summed voxel renderings-is desired. In this note, we present a simple and rapid method for generation of DRRs based on splat rendering. As opposed to conventional splatting, antialiasing of the resulting images is not achieved by means of computing a discrete point spread function (a so-called footprint), but by stochastic distortion of either the voxel positions in the volume scan or by the simulation of a focal spot of the x-ray tube with non-zero diameter. Our method generates slightly blurred DRRs suitable for registration purposes at framerates of approximately 10 Hz when rendering volume images with a size of 30 MB. PMID:15843725

  5. A comparison of seven methods of within-subjects rigid-body pedobarographic image registration.

    PubMed

    Pataky, Todd C; Goulermas, John Y; Crompton, Robin H

    2008-10-20

    Image registration, the process of transforming images such that homologous structures optimally overlap, provides the pre-processing foundation for pixel-level functional image analysis. The purpose of this study was to compare the performances of seven methods of within-subjects pedobarographic image registration: (1) manual, (2) principal axes, (3) centre of pressure trajectory, (4) mean squared error, (5) probability-weighted variance, (6) mutual information, and (7) exclusive OR. We assumed that foot-contact geometry changes were negligibly small trial-to-trial and thus that a rigid-body transformation could yield optimum registration performance. Thirty image pairs were randomly selected from our laboratory database and were registered using each method. To compensate for inter-rater variability, the mean registration parameters across 10 raters were taken as representative of manual registration. Registration performance was assessed using four dissimilarity metrics (#4-7 above). One-way MANOVA found significant differences between the methods (p<0.001). Bonferroni post-hoc tests revealed that the centre of pressure method performed the poorest (p<0.001) and that the principal axes method tended to perform more poorly than remaining methods (p<0.070). Average manual registration was not different from the remaining methods (p=1.000). The results suggest that a variety of linear registration methods are appropriate for within-subjects pedobarographic images, and that manual image registration is a viable alternative to algorithmic registration when parameters are averaged across raters. The latter finding, in particular, may be useful for cases of image peculiarities resulting from outlier trials or from experimental manipulations that induce substantial changes in contact area or pressure profile geometry. PMID:18790481

  6. Data on the verification and validation of segmentation and registration methods for diffusion MRI.

    PubMed

    Esteban, Oscar; Zosso, Dominique; Daducci, Alessandro; Bach-Cuadra, Meritxell; Ledesma-Carbayo, María J; Thiran, Jean-Philippe; Santos, Andres

    2016-09-01

    The verification and validation of segmentation and registration methods is a necessary assessment in the development of new processing methods. However, verification and validation of diffusion MRI (dMRI) processing methods is challenging for the lack of gold-standard data. The data described here are related to the research article entitled "Surface-driven registration method for the structure-informed segmentation of diffusion MR images" [1], in which publicly available data are used to derive golden-standard reference-data to validate and evaluate segmentation and registration methods in dMRI. PMID:27508235

  7. Comparative study of multimodal intra-subject image registration methods on a publicly available database

    NASA Astrophysics Data System (ADS)

    Miri, Mohammad Saleh; Ghayoor, Ali; Johnson, Hans J.; Sonka, Milan

    2016-03-01

    This work reports on a comparative study between five manual and automated methods for intra-subject pair-wise registration of images from different modalities. The study includes a variety of inter-modal image registrations (MR-CT, PET-CT, PET-MR) utilizing different methods including two manual point-based techniques using rigid and similarity transformations, one automated point-based approach based on Iterative Closest Point (ICP) algorithm, and two automated intensity-based methods using mutual information (MI) and normalized mutual information (NMI). These techniques were employed for inter-modal registration of brain images of 9 subjects from a publicly available dataset, and the results were evaluated qualitatively via checkerboard images and quantitatively using root mean square error and MI criteria. In addition, for each inter-modal registration, a paired t-test was performed on the quantitative results in order to find any significant difference between the results of the studied registration techniques.

  8. An Automatic Optical and SAR Image Registration Method Using Iterative Multi-Level and Refinement Model

    NASA Astrophysics Data System (ADS)

    Xu, C.; Sui, H. G.; Li, D. R.; Sun, K. M.; Liu, J. Y.

    2016-06-01

    Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using -level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM) to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

  9. Automatic Localization of Target Vertebrae in Spine Surgery: Clinical Evaluation of the LevelCheck Registration Algorithm

    PubMed Central

    Lo, Sheng-fu L.; Otake, Yoshito; Puvanesarajah, Varun; Wang, Adam S.; Uneri, Ali; De Silva, Tharindu; Vogt, Sebastian; Kleinszig, Gerhard; Elder, Benjamin D; Goodwin, C. Rory; Kosztowski, Thomas A.; Liauw, Jason A.; Groves, Mari; Bydon, Ali; Sciubba, Daniel M.; Witham, Timothy F.; Wolinsky, Jean-Paul; Aygun, Nafi; Gokaslan, Ziya L.; Siewerdsen, Jeffrey H.

    2015-01-01

    Study Design A 3D-2D image registration algorithm, “LevelCheck,” was used to automatically label vertebrae in intraoperative mobile radiographs obtained during spine surgery. Accuracy, computation time, and potential failure modes were evaluated in a retrospective study of 20 patients. Objective To measurethe performance of the LevelCheck algorithm using clinical images acquired during spine surgery. Summary of Background Data In spine surgery, the potential for wrong level surgery is significant due to the difficulty of localizing target vertebrae based solely on visual impression, palpation, and fluoroscopy. To remedy this difficulty and reduce the risk of wrong-level surgery, our team introduced a program (dubbed LevelCheck) to automatically localize target vertebrae in mobile radiographs using robust 3D-2D image registration to preoperative CT. Methods Twenty consecutive patients undergoing thoracolumbar spine surgery, for whom both a preoperative CT scan and an intraoperative mobile radiograph were available, were retrospectively analyzed. A board-certified neuroradiologist determined the “true” vertebra levels in each radiograph. Registration of the preoperative CT to the intraoperative radiographwere calculated via LevelCheck, and projection distance errors were analyzed. Five hundred random initializations were performed for eachpatient, andalgorithm settings (viz., the number of robust multi-starts, ranging 50 to 200) were varied to evaluate the tradeoff between registration error and computation time. Failure mode analysis was performed by individually analyzing unsuccessful registrations (>5 mm distance error) observed with 50 multi-starts. Results At 200 robust multi-starts (computation time of ∼26 seconds), the registration accuracy was 100% across all 10,000 trials. As the number of multi-starts (and computation time) decreased, the registration remained fairly robust, down to 99.3% registration accuracy at 50 multi-starts (computation time

  10. A hybrid biomechanical model-based image registration method for sliding objects

    NASA Astrophysics Data System (ADS)

    Han, Lianghao; Hawkes, David; Barratt, Dean

    2014-03-01

    The sliding motion between two anatomic structures, such as lung against chest wall, liver against surrounding tissues, produces a discontinuous displacement field between their boundaries. Capturing the sliding motion is quite challenging for intensity-based image registration methods in which a smoothness condition has commonly been applied to ensure the deformation consistency of neighborhood voxels. Such a smoothness constraint contradicts motion physiology at the boundaries of these anatomic structures. Although various regularisation schemes have been developed to handle sliding motion under the framework of non-rigid intensity-based image registration, the recovered displacement field may still not be physically plausible. In this study, a new framework that incorporates a patient-specific biomechanical model with a non-rigid image registration scheme for motion estimation of sliding objects has been developed. The patient-specific model provides the motion estimation with an explicit simulation of sliding motion, while the subsequent non-rigid image registration compensates for smaller residuals of the deformation due to the inaccuracy of the physical model. The algorithm was tested against the results of the published literature using 4D CT data from 10 lung cancer patients. The target registration error (TRE) of 3000 landmarks with the proposed method (1.37+/-0.89 mm) was significantly lower than that with the popular B-spline based free form deformation (FFD) registration (4.5+/-3.9 mm), and was smaller than that using the B-spline based FFD registration with the sliding constraint (1.66+/-1.14 mm) or using the B-spline based FFD registration on segmented lungs (1.47+/-1.1 mm). A paired t-test showed that the improvement of registration performance with the proposed method was significant (p<0.01). The propose method also achieved the best registration performance on the landmarks near lung surfaces. Since biomechanical models captured most of the lung

  11. [Registration of accidents and injuries in primary health care. Methods and the users' experiences].

    PubMed

    Lund, H; Lium, E

    1997-11-10

    The registration of accidents and injuries in primary health care is inadequate. One of the reasons for this inadequacy is most certainly lack of enthusiasm although lack of to-the-point registration methods is just as much to blame. We have used an automatic accident registration mode in the PC programme Profdoc. This accident registration programme is very useful and time cost-effective. In Os municipality, where the registration took place in 1996, the results have proved to be very helpful in accident prevention. Nevertheless, the programme still needs EDB-knowledgeable doctors, to collect the data. In the near future it will hopefully be possible to feed the raw material to a server, which would then organize the data. This would provide general practitioners with a completed report in exchange for raw material. PMID:9441426

  12. Comparison of time-series registration methods in breast dynamic infrared imaging

    NASA Astrophysics Data System (ADS)

    Riyahi-Alam, S.; Agostini, V.; Molinari, F.; Knaflitz, M.

    2015-03-01

    Automated motion reduction in dynamic infrared imaging is on demand in clinical applications, since movement disarranges time-temperature series of each pixel, thus originating thermal artifacts that might bias the clinical decision. All previously proposed registration methods are feature based algorithms requiring manual intervention. The aim of this work is to optimize the registration strategy specifically for Breast Dynamic Infrared Imaging and to make it user-independent. We implemented and evaluated 3 different 3D time-series registration methods: 1. Linear affine, 2. Non-linear Bspline, 3. Demons applied to 12 datasets of healthy breast thermal images. The results are evaluated through normalized mutual information with average values of 0.70 ±0.03, 0.74 ±0.03 and 0.81 ±0.09 (out of 1) for Affine, Bspline and Demons registration, respectively, as well as breast boundary overlap and Jacobian determinant of the deformation field. The statistical analysis of the results showed that symmetric diffeomorphic Demons' registration method outperforms also with the best breast alignment and non-negative Jacobian values which guarantee image similarity and anatomical consistency of the transformation, due to homologous forces enforcing the pixel geometric disparities to be shortened on all the frames. We propose Demons' registration as an effective technique for time-series dynamic infrared registration, to stabilize the local temperature oscillation.

  13. Tracking and registration method based on vector operation for augmented reality system

    NASA Astrophysics Data System (ADS)

    Gao, Yanfei; Wang, Hengyou; Bian, Xiaoning

    2015-08-01

    Tracking and registration is one key issue for an augmented reality (AR) system. For the marker-based AR system, the research focuses on detecting the real-time position and orientation of camera. In this paper, we describe a method of tracking and registration using the vector operations. Our method is proved to be stable and accurate, and have a good real-time performance.

  14. A nonlinear biomechanical model based registration method for aligning prone and supine MR breast images.

    PubMed

    Han, Lianghao; Hipwell, John H; Eiben, Björn; Barratt, Dean; Modat, Marc; Ourselin, Sebastien; Hawkes, David J

    2014-03-01

    Preoperative diagnostic magnetic resonance (MR) breast images can provide good contrast between different tissues and 3-D information about suspicious tissues. Aligning preoperative diagnostic MR images with a patient in the theatre during breast conserving surgery could assist surgeons in achieving the complete excision of cancer with sufficient margins. Typically, preoperative diagnostic MR breast images of a patient are obtained in the prone position, while surgery is performed in the supine position. The significant shape change of breasts between these two positions due to gravity loading, external forces and related constraints makes the alignment task extremely difficult. Our previous studies have shown that either nonrigid intensity-based image registration or biomechanical modelling alone are limited in their ability to capture such a large deformation. To tackle this problem, we proposed in this paper a nonlinear biomechanical model-based image registration method with a simultaneous optimization procedure for both the material parameters of breast tissues and the direction of the gravitational force. First, finite element (FE) based biomechanical modelling is used to estimate a physically plausible deformation of the pectoral muscle and the major deformation of breast tissues due to gravity loading. Then, nonrigid intensity-based image registration is employed to recover the remaining deformation that FE analyses do not capture due to the simplifications and approximations of biomechanical models and the uncertainties of external forces and constraints. We assess the registration performance of the proposed method using the target registration error of skin fiducial markers and the Dice similarity coefficient (DSC) of fibroglandular tissues. The registration results on prone and supine MR image pairs are compared with those from two alternative nonrigid registration methods for five breasts. Overall, the proposed algorithm achieved the best registration

  15. Robust registration method for interventional MRI-guided thermal ablation of prostate cancer

    NASA Astrophysics Data System (ADS)

    Fei, Baowei; Wheaton, Andrew; Lee, Zhenghong; Nagano, Kenichi; Duerk, Jeffrey L.; Wilson, David L.

    2001-05-01

    We are investigating methods to register live-time interventional magnetic resonance imaging (iMRI) slice images with a previously obtained, high resolution MRI image volume. The immediate application is for iMRI-guided treatments of prostate cancer. We created and evaluated a slice-to-volume mutual information registration algorithm for MR images with special features to improve robustness. Features included a multi-resolution approach and automatic restarting to avoid local minima. We acquired 3D volume images from a 1.5 T MRI system and simulated iMRI images. To assess the quality of registration, we calculated 3D displacement on a voxel-by-voxel basis over a volume of interest between slice-to-volume registration and volume-to- volume registrations that were previously shown to be quite accurate. More than 500 registration experiments were performed on MR images of volunteers. The slice-to-volume registration algorithm was very robust for transverse images covering the prostate. A 100% success rate was achieved with an acceptance criterion of <1.0 mm displacement error over the prostate. Our automatic slice-to-volume mutual information registration algorithm is robust and probably sufficiently accurate to aid in the application of iMRI- guided thermal ablation of prostate cancer.

  16. The heritability of the functional connectome is robust to common nonlinear registration methods

    NASA Astrophysics Data System (ADS)

    Hafzalla, George W.; Prasad, Gautam; Baboyan, Vatche G.; Faskowitz, Joshua; Jahanshad, Neda; McMahon, Katie L.; de Zubicaray, Greig I.; Wright, Margaret J.; Braskie, Meredith N.; Thompson, Paul M.

    2016-03-01

    Nonlinear registration algorithms are routinely used in brain imaging, to align data for inter-subject and group comparisons, and for voxelwise statistical analyses. To understand how the choice of registration method affects maps of functional brain connectivity in a sample of 611 twins, we evaluated three popular nonlinear registration methods: Advanced Normalization Tools (ANTs), Automatic Registration Toolbox (ART), and FMRIB's Nonlinear Image Registration Tool (FNIRT). Using both structural and functional MRI, we used each of the three methods to align the MNI152 brain template, and 80 regions of interest (ROIs), to each subject's T1-weighted (T1w) anatomical image. We then transformed each subject's ROIs onto the associated resting state functional MRI (rs-fMRI) scans and computed a connectivity network or functional connectome for each subject. Given the different degrees of genetic similarity between pairs of monozygotic (MZ) and same-sex dizygotic (DZ) twins, we used structural equation modeling to estimate the additive genetic influences on the elements of the function networks, or their heritability. The functional connectome and derived statistics were relatively robust to nonlinear registration effects.

  17. Self-Registration Methods for Increasing Membrane Utilization within Compression-Sealed Microchannel Hemodialysers

    PubMed Central

    Paul, Brian K.; Porter, Spencer D.

    2015-01-01

    More than 1.2 million people worldwide require regular hemodialysis therapy to treat end stage renal failure. Current hemodialysis systems are too expensive to support at-home hemodialysis where more frequent and longer duration treatment can lead to better patient outcomes. The key cost driver for hemodialysers is the cost of the hemodialysis membrane. Microchannel hemodialysers are smaller providing the potential to use significantly less membrane. Prior work has demonstrated the use of sealing bosses to form compression seals in microchannel hemodialysers. In this paper, estimates show that the percentage of the membrane utilized for mass transfer is highly dependent on the design and registration accuracy of adjacent blood and dialysate laminae. Efforts here focus on the development of a self-registration method to align polycarbonate laminae compatible with compression sealing schemes for membrane separation applications. Self-nesting registration methods were demonstrated with average registration accuracies of 11.4 ± 7.2 μm measured over a 50 mm scale. Analysis shows that the registration accuracy is constrained by tolerances in the embossing process. A dialysis test article was produced using the self-nesting registration method showing a measured average one-dimensional misregistration of 18.5 μm allowing a potential 41.4% of the membrane to be utilized for mass transfer when considering both microchannel and header regions. Mass transfer results provide evidence of a twofold to threefold increase in membrane utilization over other designs in the existing literature. PMID:25642151

  18. A method of image registration for small animal, multi-modality imaging.

    PubMed

    Chow, Patrick L; Stout, David B; Komisopoulou, Evangelia; Chatziioannou, Arion F

    2006-01-21

    Many research institutions have a full suite of preclinical tomographic scanners to answer biomedical questions in vivo. Routine multi-modality imaging requires robust registration of images generated by various tomographs. We have implemented a hardware registration method for preclinical imaging that is similar to that used in the combined positron emission tomography (PET)/computed tomography (CT) scanners in the clinic. We designed an imaging chamber which can be rigidly and reproducibly mounted on separate microPET and microCT scanners. We have also designed a three-dimensional grid phantom with 1288 lines that is used to generate the spatial transformation matrix from software registration using a 15-parameter perspective model. The imaging chamber works in combination with the registration phantom synergistically to achieve the image registration goal. We verified that the average registration error between two imaging modalities is 0.335 mm using an in vivo mouse bone scan. This paper also estimates the impact of image misalignment on PET quantitation using attenuation corrections generated from misregistered images. Our technique is expected to produce PET quantitation errors of less than 5%. The methods presented are robust and appropriate for routine use in high throughput animal imaging facilities. PMID:16394345

  19. Automatic registration method for multisensor datasets adopted for dimensional measurements on cutting tools

    NASA Astrophysics Data System (ADS)

    Shaw, L.; Ettl, S.; Mehari, F.; Weckenmann, A.; Häusler, G.

    2013-04-01

    Multisensor systems with optical 3D sensors are frequently employed to capture complete surface information by measuring workpieces from different views. During coarse and fine registration the resulting datasets are afterward transformed into one common coordinate system. Automatic fine registration methods are well established in dimensional metrology, whereas there is a deficit in automatic coarse registration methods. The advantage of a fully automatic registration procedure is twofold: it enables a fast and contact-free alignment and further a flexible application to datasets of any kind of optical 3D sensor. In this paper, an algorithm adapted for a robust automatic coarse registration is presented. The method was originally developed for the field of object reconstruction or localization. It is based on a segmentation of planes in the datasets to calculate the transformation parameters. The rotation is defined by the normals of three corresponding segmented planes of two overlapping datasets, while the translation is calculated via the intersection point of the segmented planes. First results have shown that the translation is strongly shape dependent: 3D data of objects with non-orthogonal planar flanks cannot be registered with the current method. In the novel supplement for the algorithm, the translation is additionally calculated via the distance between centroids of corresponding segmented planes, which results in more than one option for the transformation. A newly introduced measure considering the distance between the datasets after coarse registration evaluates the best possible transformation. Results of the robust automatic registration method are presented on the example of datasets taken from a cutting tool with a fringe-projection system and a focus-variation system. The successful application in dimensional metrology is proven with evaluations of shape parameters based on the registered datasets of a calibrated workpiece.

  20. 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.

  1. Artificial feature-based multiview registration method for three-dimensional free-form object modeling

    NASA Astrophysics Data System (ADS)

    Ren, Tongqun; Zhu, Jigui; Guo, Yinbiao; Luo, Wei

    2010-05-01

    Two integral registration methods based on artificial features are described. In method one, independent global control points are designed to build a global coordinate system. Registration target and camera are also introduced to create intermediary coordinate systems. For each local scanning, one image of the whole measuring scene is shot by registration camera. Then local data can be unified to the global coordinate system by solving transition chains of various coordinate systems from this single image based on the projective geometry principle. In the other method, control points are placed on the object surface evenly and shot by registration camera from different positions and orientations. We solve their coordinates by employing the bundle adjustment method to build a global control network. The range sensor shoots at least three control points during each local scan. Then registration can be completed by mapping these control points into the global control network. In this work, the range sensor is untracked. Error accumulation and propagation are also effectively conquered, since overlapping of neighboring subregions is unessential. Experimental results are presented to show the feasibility of the proposed methods.

  2. The plant virus microscope image registration method based on mismatches removing.

    PubMed

    Wei, Lifang; Zhou, Shucheng; Dong, Heng; Mao, Qianzhuo; Lin, Jiaxiang; Chen, Riqing

    2016-01-01

    The electron microscopy is one of the major means to observe the virus. The view of virus microscope images is limited by making specimen and the size of the camera's view field. To solve this problem, the virus sample is produced into multi-slice for information fusion and image registration techniques are applied to obtain large field and whole sections. Image registration techniques have been developed in the past decades for increasing the camera's field of view. Nevertheless, these approaches typically work in batch mode and rely on motorized microscopes. Alternatively, the methods are conceived just to provide visually pleasant registration for high overlap ratio image sequence. This work presents a method for virus microscope image registration acquired with detailed visual information and subpixel accuracy, even when overlap ratio of image sequence is 10% or less. The method proposed focus on the correspondence set and interimage transformation. A mismatch removal strategy is proposed by the spatial consistency and the components of keypoint to enrich the correspondence set. And the translation model parameter as well as tonal inhomogeneities is corrected by the hierarchical estimation and model select. In the experiments performed, we tested different registration approaches and virus images, confirming that the translation model is not always stationary, despite the fact that the images of the sample come from the same sequence. The mismatch removal strategy makes building registration of virus microscope images at subpixel accuracy easier and optional parameters for building registration according to the hierarchical estimation and model select strategies make the proposed method high precision and reliable for low overlap ratio image sequence. PMID:26519816

  3. Joint image registration and fusion method with a gradient strength regularization

    NASA Astrophysics Data System (ADS)

    Lidong, Huang; Wei, Zhao; Jun, Wang

    2015-05-01

    Image registration is an essential process for image fusion, and fusion performance can be used to evaluate registration accuracy. We propose a maximum likelihood (ML) approach to joint image registration and fusion instead of treating them as two independent processes in the conventional way. To improve the visual quality of a fused image, a gradient strength (GS) regularization is introduced in the cost function of ML. The GS of the fused image is controllable by setting the target GS value in the regularization term. This is useful because a larger target GS brings a clearer fused image and a smaller target GS makes the fused image smoother and thus restrains noise. Hence, the subjective quality of the fused image can be improved whether the source images are polluted by noise or not. We can obtain the fused image and registration parameters successively by minimizing the cost function using an iterative optimization method. Experimental results show that our method is effective with transformation, rotation, and scale parameters in the range of [-2.0, 2.0] pixel, [-1.1 deg, 1.1 deg], and [0.95, 1.05], respectively, and variances of noise smaller than 300. It also demonstrated that our method yields a more visual pleasing fused image and higher registration accuracy compared with a state-of-the-art algorithm.

  4. A Comparison of Phase and Speckle Tracking Registration Methods for Motion Correction during HIFU Treatment

    NASA Astrophysics Data System (ADS)

    Yates, Tara; Smith, Penny Probert; Noble, Alison; Leslie, Tom; Kennedy, James

    2007-05-01

    The accuracy of treatment monitoring and planning is instrumental to the acceptance of HIFU surgery. The ability to locate, analyze and track a feature of interest during treatment will be affected by patient motion. Additionally, statistical analysis and temperature monitoring algorithms would benefit from the registration of successive frames. In this work two registration algorithms, which have had extensive trials in other imaging applications, are investigated. Their ability to reduce patient respiratory and cardiac motion is within ultrasound sequences, taken during HIFU treatments, is compared. The first algorithm is based on an intensity block matching approach with a similarity measure that incorporates speckle statistics explicitly. The second method registers phase representations of the image with a more general similarity measure. These methods would be expected to succeed on different aspects of the image: phase measurements give weight to features and are rotation and contrast invariant, whereas methods to track speckle are successful in images that lack strong features. In general phase based methods of registration are more robust and have the potential to be extended to multimodality registration (such as MRI to Ultrasound), however in this case tracking speckle may produce better results due to the low signal to noise ratio in ultrasound images taken during HIFU treatments. Numerous examples from HIFU surgery are presented to highlight the performance of each method under a various motion constraints. It is shown that the phase based algorithm is generally superior, except in the close proximity to the skin.

  5. Evaluation of rigid registration methods for whole head imaging in diffuse optical tomography.

    PubMed

    Wu, Xue; Eggebrecht, Adam T; Ferradal, Silvina L; Culver, Joseph P; Dehghani, Hamid

    2015-07-01

    Functional brain imaging has become an important neuroimaging technique for the study of brain organization and development. Compared to other imaging techniques, diffuse optical tomography (DOT) is a portable and low-cost technique that can be applied to infants and hospitalized patients using an atlas-based light model. For DOT imaging, the accuracy of the forward model has a direct effect on the resulting recovered brain function within a field of view and so the accuracy of the spatially normalized atlas-based forward models must be evaluated. Herein, the accuracy of atlas-based DOT is evaluated on models that are spatially normalized via a number of different rigid registration methods on 24 subjects. A multileveled approach is developed to evaluate the correlation of the geometrical and sensitivity accuracies across the full field of view as well as within specific functional subregions. Results demonstrate that different registration methods are optimal for recovery of different sets of functional brain regions. However, the "nearest point to point" registration method, based on the EEG 19 landmark system, is shown to be the most appropriate registration method for image quality throughout the field of view of the high-density cap that covers the whole of the optically accessible cortex. PMID:26217675

  6. Combining morphometric evidence from multiple registration methods using dempster-shafer theory

    NASA Astrophysics Data System (ADS)

    Rajagopalan, Vidya; Wyatt, Christopher

    2010-03-01

    In tensor-based morphometry (TBM) group-wise differences in brain structure are measured using high degreeof- freedom registration and some form of statistical test. However, it is known that TBM results are sensitive to both the registration method and statistical test used. Given the lack of an objective model of group variation is it difficult to determine a best registration method for TBM. The use of statistical tests is also problematic given the corrections required for multiple testing and the notorius difficulty selecting and intepreting signigance values. This paper presents an approach to address both of these issues by combining multiple registration methods using Dempster-Shafer Evidence theory to produce belief maps of categorical changes between groups. This approach is applied to the comparison brain morphometry in aging, a typical application of TBM, using the determinant of the Jacobian as a measure of volume change. We show that the Dempster-Shafer combination produces a unique and easy to interpret belief map of regional changes between and within groups without the complications associated with hypothesis testing.

  7. A MR-TRUS registration method for ultrasound-guided prostate interventions

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

    In this paper, we reported a MR-TRUS prostate registration method that uses a subject-specific prostate strain model to improve MR-targeted, US-guided prostate interventions (e.g., biopsy and radiotherapy). The proposed algorithm combines a subject-specific prostate strain model with a Bspline transformation to register the prostate gland of the MRI to the TRUS images. The prostate strain model was obtained through US elastography and a 3D strain map of the prostate was generated. The B-spline transformation was calculated by minimizing Euclidean distance between MR and TRUS prostate surfaces. This prostate stain map was used to constrain the B-spline-based transformation to predict and compensate for the internal prostate-gland deformation. This method was validated with a prostate-phantom experiment and a pilot study of 5 prostate-cancer patients. For the phantom study, the mean target registration error (TRE) was 1.3 mm. MR-TRUS registration was also successfully performed for 5 patients with a mean TRE less than 2 mm. The proposed registration method may provide an accurate and robust means of estimating internal prostate-gland deformation, and could be valuable for prostate-cancer diagnosis and treatment.

  8. 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

  9. A novel registration method for image-guided neurosurgery system based on stereo vision.

    PubMed

    An, Yong; Wang, Manning; Song, Zhijian

    2015-01-01

    This study presents a novel spatial registration method of Image-guided neurosurgery system (IGNS) based on stereo-vision. Images of the patient's head are captured by a video camera, which is calibrated and tracked by an optical tracking system. Then, a set of sparse facial data points are reconstructed from them by stereo vision in the patient space. Surface matching method is utilized to register the reconstructed sparse points and the facial surface reconstructed from preoperative images of the patient. Simulation experiments verified the feasibility of the proposed method. The proposed method it is a new low-cost and easy-to-use spatial registration method for IGNS, with good prospects for clinical application. PMID:26406100

  10. Using shape contexts method for registration of contra lateral breasts in thermal images

    PubMed Central

    Etehadtavakol, Mahnaz; Ng, Eddie Yin-Kwee; Gheissari, Niloofar

    2014-01-01

    AIM: To achieve symmetric boundaries for left and right breasts boundaries in thermal images by registration. METHODS: The proposed method for registration consists of two steps. In the first step, shape context, an approach as presented by Belongie and Malik was applied for registration of two breast boundaries. The shape context is an approach to measure shape similarity. Two sets of finite sample points from shape contours of two breasts are then presented. Consequently, the correspondences between the two shapes are found. By finding correspondences, the sample point which has the most similar shape context is obtained. RESULTS: In this study, a line up transformation which maps one shape onto the other has been estimated in order to complete shape. The used of a thin plate spline permitted good estimation of a plane transformation which has capability to map unselective points from one shape onto the other. The obtained aligning transformation of boundaries points has been applied successfully to map the two breasts interior points. Some of advantages for using shape context method in this work are as follows: (1) no special land marks or key points are needed; (2) it is tolerant to all common shape deformation; and (3) although it is uncomplicated and straightforward to use, it gives remarkably powerful descriptor for point sets significantly upgrading point set registration. Results are very promising. The proposed algorithm was implemented for 32 cases. Boundary registration is done perfectly for 28 cases. CONCLUSION: We used shape contexts method that is simple and easy to implement to achieve symmetric boundaries for left and right breasts boundaries in thermal images. PMID:25493241

  11. 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.

  12. Comparison of demons deformable registration-based methods for texture analysis of serial thoracic CT scans

    NASA Astrophysics Data System (ADS)

    Cunliffe, Alexandra R.; Al-Hallaq, Hania A.; Fei, Xianhan M.; Tuohy, Rachel E.; Armato, Samuel G.

    2013-02-01

    To determine how 19 image texture features may be altered by three image registration methods, "normal" baseline and follow-up computed tomography (CT) scans from 27 patients were analyzed. Nineteen texture feature values were calculated in over 1,000 32x32-pixel regions of interest (ROIs) randomly placed in each baseline scan. All three methods used demons registration to map baseline scan ROIs to anatomically matched locations in the corresponding transformed follow-up scan. For the first method, the follow-up scan transformation was subsampled to achieve a voxel size identical to that of the baseline scan. For the second method, the follow-up scan was transformed through affine registration to achieve global alignment with the baseline scan. For the third method, the follow-up scan was directly deformed to the baseline scan using demons deformable registration. Feature values in matched ROIs were compared using Bland- Altman 95% limits of agreement. For each feature, the range spanned by the 95% limits was normalized to the mean feature value to obtain the normalized range of agreement, nRoA. Wilcoxon signed-rank tests were used to compare nRoA values across features for the three methods. Significance for individual tests was adjusted using the Bonferroni method. nRoA was significantly smaller for affine-registered scans than for the resampled scans (p=0.003), indicating lower feature value variability between baseline and follow-up scan ROIs using this method. For both of these methods, however, nRoA was significantly higher than when feature values were calculated directly on demons-deformed followup scans (p<0.001). Across features and methods, nRoA values remained below 26%.

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

    SciTech Connect

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

    2012-02-15

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

  14. Seed-based transrectal ultrasound-fluoroscopy registration method for intraoperative dosimetry analysis of prostate brachytherapy

    SciTech Connect

    Tutar, Ismail B.; Gong Lixin; Narayanan, Sreeram; Pathak, Sayan D.; Cho, Paul S.; Wallner, Kent; Kim, Yongmin

    2008-03-15

    Prostate brachytherapy is an effective treatment option for early-stage prostate cancer. During a prostate brachytherapy procedure, transrectal ultrasound (TRUS) and fluoroscopy imaging modalities complement each other by providing good visualization of soft tissue and implanted seeds, respectively. Therefore, the registration of these two imaging modalities, which are readily available in the operating room, could facilitate intraoperative dosimetry, thus enabling physicians to implant additional seeds into the underdosed portions of the prostate while the patient is still on the operating table. It is desirable to register TRUS and fluoroscopy images by using the seeds as fiducial markers. Although the locations of all the implanted seeds can be reconstructed from three fluoroscopy images, only a fraction of these seeds can be located in TRUS images. It is challenging to register the TRUS and fluoroscopy images by using the identified seeds, since the correspondence between them is unknown. Furthermore, misdetection of nonseed structures as seeds can lead to the inclusion of spurious points in the data set. We developed a new method called iterative optimal assignment (IOA) to overcome these challenges in TRUS-fluoroscopy registration. By using the Hungarian method in an optimization framework, IOA computes a set of transformation parameters that yield the one-to-one correspondence with minimum cost. We have evaluated our registration method at varying noise levels, seed detection rates, and number of spurious points using data collected from 25 patients. We have found that IOA can perform registration with an average root mean square error of about 0.2 cm even when the seed detection rate is only 10%. We believe that IOA can offer a robust solution to seed-based TRUS-fluoroscopy registration, thus making intraoperative dosimetry possible.

  15. Comparison of landmark-based and automatic methods for cortical surface registration.

    PubMed

    Pantazis, Dimitrios; Joshi, Anand; Jiang, Jintao; Shattuck, David W; Bernstein, Lynne E; Damasio, Hanna; Leahy, Richard M

    2010-02-01

    Group analysis of structure or function in cerebral cortex typically involves, as a first step, the alignment of cortices. A surface-based approach to this problem treats the cortex as a convoluted surface and coregisters across subjects so that cortical landmarks or features are aligned. This registration can be performed using curves representing sulcal fundi and gyral crowns to constrain the mapping. Alternatively, registration can be based on the alignment of curvature metrics computed over the entire cortical surface. The former approach typically involves some degree of user interaction in defining the sulcal and gyral landmarks while the latter methods can be completely automated. Here we introduce a cortical delineation protocol consisting of 26 consistent landmarks spanning the entire cortical surface. We then compare the performance of a landmark-based registration method that uses this protocol with that of two automatic methods implemented in the software packages FreeSurfer and BrainVoyager. We compare performance in terms of discrepancy maps between the different methods, the accuracy with which regions of interest are aligned, and the ability of the automated methods to correctly align standard cortical landmarks. Our results show similar performance for ROIs in the perisylvian region for the landmark-based method and FreeSurfer. However, the discrepancy maps showed larger variability between methods in occipital and frontal cortex and automated methods often produce misalignment of standard cortical landmarks. Consequently, selection of the registration approach should consider the importance of accurate sulcal alignment for the specific task for which coregistration is being performed. When automatic methods are used, the users should ensure that sulci in regions of interest in their studies are adequately aligned before proceeding with subsequent analysis. PMID:19796696

  16. Assessment of Thematic Mapper Band-to-band Registration by the Block Correlation Method

    NASA Technical Reports Server (NTRS)

    Card, D. H.; Wrigley, R. C.; Mertz, F. C.; Hall, J. R.

    1984-01-01

    The design of the Thematic Mapper (TM) multispectral radiometer makes it susceptible to band-to-band misregistration. To estimate band-to-band misregistration a block correlation method is employed. This method is chosen over other possible techniques (band differencing and flickering) because quantitative results are produced. The method correlates rectangular blocks of pixels from one band against blocks centered on identical pixels from a second band. The block pairs are shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient for each shift position is computed. The displacement corresponding to the maximum correlation is taken as the best estimate of registration error for each block pair. Subpixel shifts are estimated by a bi-quadratic interpolation of the correlation values surrounding the maximum correlation. To obtain statistical summaries for each band combination post processing of the block correlation results performed. The method results in estimates of registration error that are consistent with expectations.

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

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

    PubMed

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

    2016-01-21

    The problem of accurate dose accumulation in fractionated radiotherapy treatment for highly deformable organs, such as bladder, has garnered increasing interest over the past few years. However, more research is required in order to find a robust and efficient solution and to increase the accuracy over the current methods. The purpose of this study was to evaluate the feasibility and accuracy of utilizing non-rigid (affine or deformable) point-set registration in accumulating dose in bladder of different sizes and shapes. A pelvic phantom was built to house an ex vivo porcine bladder with fiducial landmarks adhered onto its surface. Four different volume fillings of the bladder were used (90, 180, 360 and 480 cc). The performance of MATLAB implementations of five different methods were compared, in aligning the bladder contour point-sets. The approaches evaluated were coherent point drift (CPD), gaussian mixture model, shape context, thin-plate spline robust point matching (TPS-RPM) and finite iterative closest point (ICP-finite). The evaluation metrics included registration runtime, target registration error (TRE), root-mean-square error (RMS) and Hausdorff distance (HD). The reference (source) dataset was alternated through all four points-sets, in order to study the effect of reference volume on the registration outcomes. While all deformable algorithms provided reasonable registration results, CPD provided the best TRE values (6.4 mm), and TPS-RPM yielded the best mean RMS and HD values (1.4 and 6.8 mm, respectively). ICP-finite was the fastest technique and TPS-RPM, the slowest. PMID:26740511

  19. A fast inverse consistent deformable image registration method based on symmetric optical flow computation

    PubMed Central

    Li, Hua; Low, Daniel A; Deasy, Joseph O; Naqa, Issam El

    2014-01-01

    Deformable image registration is widely used in various radiation therapy applications including daily treatment planning adaptation to map planned tissue or dose to changing anatomy. In this work, a simple and efficient inverse consistency deformable registration method is proposed with aims of higher registration accuracy and faster convergence speed. Instead of registering image I to a second image J, the two images are symmetrically deformed toward one another in multiple passes, until both deformed images are matched and correct registration is therefore achieved. In each pass, a delta motion field is computed by minimizing a symmetric optical flow system cost function using modified optical flow algorithms. The images are then further deformed with the delta motion field in the positive and negative directions respectively, and then used for the next pass. The magnitude of the delta motion field is forced to be less than 0.4 voxel for every pass in order to guarantee smoothness and invertibility for the two overall motion fields that are accumulating the delta motion fields in both positive and negative directions, respectively. The final motion fields to register the original images I and J, in either direction, are calculated by inverting one overall motion field and combining the inversion result with the other overall motion field. The final motion fields are inversely consistent and this is ensured by the symmetric way that registration is carried out. The proposed method is demonstrated with phantom images, artificially deformed patient images and 4D-CT images. Our results suggest that the proposed method is able to improve the overall accuracy (reducing registration error by 30% or more, compared to the original and inversely inconsistent optical flow algorithms), reduce the inverse consistency error (by 95% or more) and increase the convergence rate (by 100% or more). The overall computation speed may slightly decrease, or increase in most cases

  20. A liver registration method for segmented multi-phase CT images

    NASA Astrophysics Data System (ADS)

    Shi, Shuyue; Yuan, Rong; Sun, Zhi; Xie, Qingguo

    2015-03-01

    In order to build high quality geometric models for liver containing vascular system, multi-phase CT series used in a computer-aided diagnosis and surgical planning system aims at liver diseases have to be accurately registered. In this paper we model the segmented liver containing vascular system as a complex shape and propose a two-step registration method. Without any tree modeling for vessel this method can carry out a simultaneous registration for both liver tissue and vascular system inside. Firstly a rigid aligning using vessel as feature is applied on the complex shape model while genetic algorithm is used as the optimization method. Secondly we achieve the elastic shape registration by combine the incremental free form deformation (IFFD) with a modified iterative closest point (ICP) algorithm. Inspired by the concept of demons method, we propose to calculate a fastest diffusion vector (FDV) for each control point on the IFFD lattice to replace the points correspondence needed in ICP iterations. Under the iterative framework of the modified ICP, the optimal solution of control points' displacement in every IFFD level can be obtained efficiently. The method has been quantitatively evaluated on clinical multi-phase CT series.

  1. Evaluation of deformable image registration methods for dose monitoring in head and neck radiotherapy.

    PubMed

    Rigaud, Bastien; Simon, Antoine; Castelli, Joël; Gobeli, Maxime; Ospina Arango, Juan-David; Cazoulat, Guillaume; Henry, Olivier; Haigron, Pascal; De Crevoisier, Renaud

    2015-01-01

    In the context of head and neck cancer (HNC) adaptive radiation therapy (ART), the two purposes of the study were to compare the performance of multiple deformable image registration (DIR) methods and to quantify their impact for dose accumulation, in healthy structures. Fifteen HNC patients had a planning computed tomography (CT0) and weekly CTs during the 7 weeks of intensity-modulated radiation therapy (IMRT). Ten DIR approaches using different registration methods (demons or B-spline free form deformation (FFD)), preprocessing, and similarity metrics were tested. Two observers identified 14 landmarks (LM) on each CT-scan to compute LM registration error. The cumulated doses estimated by each method were compared. The two most effective DIR methods were the demons and the FFD, with both the mutual information (MI) metric and the filtered CTs. The corresponding LM registration accuracy (precision) was 2.44 mm (1.30 mm) and 2.54 mm (1.33 mm), respectively. The corresponding LM estimated cumulated dose accuracy (dose precision) was 0.85 Gy (0.93 Gy) and 0.88 Gy (0.95 Gy), respectively. The mean uncertainty (difference between maximal and minimal dose considering all the 10 methods) to estimate the cumulated mean dose to the parotid gland (PG) was 4.03 Gy (SD = 2.27 Gy, range: 1.06-8.91 Gy). PMID:25759821

  2. A Comparative Study of Registration Methods for RGB-D Video of Static Scenes

    PubMed Central

    Morell-Gimenez, Vicente; Saval-Calvo, Marcelo; Azorin-Lopez, Jorge; Garcia-Rodriguez, Jose; Cazorla, Miguel; Orts-Escolano, Sergio; Fuster-Guillo, Andres

    2014-01-01

    The use of RGB-D sensors for mapping and recognition tasks in robotics or, in general, for virtual reconstruction has increased in recent years. The key aspect of these kinds of sensors is that they provide both depth and color information using the same device. In this paper, we present a comparative analysis of the most important methods used in the literature for the registration of subsequent RGB-D video frames in static scenarios. The analysis begins by explaining the characteristics of the registration problem, dividing it into two representative applications: scene modeling and object reconstruction. Then, a detailed experimentation is carried out to determine the behavior of the different methods depending on the application. For both applications, we used standard datasets and a new one built for object reconstruction. PMID:24834909

  3. Comparison and evaluation of joint histogram estimation methods for mutual information based image registration

    NASA Astrophysics Data System (ADS)

    Liang, Yongfang; Chen, Hua-mei

    2005-04-01

    Joint histogram is the only quantity required to calculate the mutual information (MI) between two images. For MI based image registration, joint histograms are often estimated through linear interpolation or partial volume interpolation (PVI). It has been pointed out that both methods may result in a phenomenon known as interpolation induced artifacts. In this paper, we implemented a wide range of interpolation/approximation kernels for joint histogram estimation. Some kernels are nonnegative. In this case, these kernels are applied in two ways as the linear kernel is applied in linear interpolation and PVI. In addition, we implemented two other joint histogram estimation methods devised to overcome the interpolation artifact problem. They are nearest neighbor interpolation with jittered sampling with/without histogram blurring and data resampling. We used the clinical data obtained from Vanderbilt University for all of the experiments. The objective of this study is to perform a comprehensive comparison and evaluation of different joint histogram estimation methods for MI based image registration in terms of artifacts reduction and registration accuracy.

  4. Automatic and robust method for registration of optical imagery with point cloud data

    NASA Astrophysics Data System (ADS)

    Wu, Yingdan; Ming, Yang

    2015-12-01

    Aim to the difficulty of automatic and robust registration of optical imagery with point cloud data, this paper propose a new method based on SIFT and Mutual Information (MI). The SIFT features are firstly extracted and matched, whose result is used to derive the coarse geometric relationship between the optical imagery and the point cloud data. Secondly, the MI-based similarity measure is used to derive the conjugate points. And then the RANSAC algorithm is adopted to eliminate the erroneous matching points. Repeating the procedure of MI matching and mismatching points deletion until the finest pyramid image level. Using the matching results, the transform model is determined. The experiments have been made and they demonstrate the potential of the MI-based measure for the registration of optical imagery with the point cloud data, and this highlight the feasibility and robustness of the method proposed in this paper to automated registration of multi-modal, multi-temporal remote sensing data for a wide range of applications.

  5. Text messaging as a new method for injury registration in sports: a methodological study in elite female football.

    PubMed

    Nilstad, A; Bahr, R; Andersen, T E

    2014-02-01

    Methodological differences in epidemiologic studies have led to significant discrepancies in injury incidences reported. The aim of this study was to evaluate text messaging as a new method for injury registration in elite female football players and to compare this method with routine medical staff registration. Twelve teams comprising 228 players prospectively recorded injuries and exposure through one competitive football season. Players reported individually by answering three text messages once a week. A designated member of the medical staff conducted concurrent registrations of injuries and exposure. Injuries and exposure were compared between medical staff registrations from nine teams and their 159 affiliated players. During the football season, a total of 232 time-loss injuries were recorded. Of these, 62% were captured through individual registration only, 10% by the medical staff only, and 28% were reported through both methods. The incidence of training injuries was 3.7 per 1000 player hours when calculated from individual registration vs 2.2 from medical staff registration [rate ratio (RR): 1.7, 1.2-2.4]. For match injuries, the corresponding incidences were 18.6 vs 5.4 (RR: 3.4, 2.4-4.9), respectively. There was moderate agreement for severity classifications in injury cases reported by both methods (kappa correlation coefficient: 0.48, confidence interval: 0.30-0.66). PMID:22537065

  6. A contrast correction method for dental images based on histogram registration

    PubMed Central

    Economopoulos, TL; Asvestas, PA; Matsopoulos, GK; Gröndahl, K; Gröndahl, H-G

    2010-01-01

    Contrast correction is often required in digital subtraction radiography when comparing medical data acquired over different time periods owing to dissimilarities in the acquisition process. This paper focuses on dental radiographs and introduces a novel approach for correcting the contrast in dental image pairs. The proposed method modifies the subject images by applying typical registration techniques on their histograms. The proposed histogram registration method reshapes the histograms of the two subject images in such a way that these images are matched in terms of their contrast deviation. The method was extensively tested over 4 sets of dental images, consisting of 72 registered dental image pairs with unknown contrast differences as well as 20 dental pairs with known contrast differences. The proposed method was directly compared against the well-known histogram-based contrast correction method. The two methods were qualitatively and quantitatively evaluated for all 92 available dental image pairs. The two methods were compared in terms of the contrast root mean square difference between the reference image and the corrected image in each case. The obtained results were also verified statistically using appropriate t-tests in each set. The proposed method exhibited superior performance compared with the well-established method, in terms of the contrast root mean square difference between the reference and the corrected images. After suitable statistical analysis, it was deduced that the performance advantage of the proposed approach was statistically significant. PMID:20587655

  7. 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

  8. An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy

    NASA Astrophysics Data System (ADS)

    Zhong, Hualiang; Wen, Ning; Gordon, James J.; Elshaikh, Mohamed A.; Movsas, Benjamin; Chetty, Indrin J.

    2015-04-01

    Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm-3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume

  9. A Combined Method for Segmentation and Registration for an Advanced and Progressive Evaluation of Thermal Images

    PubMed Central

    Barcelos, Emilio Z.; Caminhas, Walmir M.; Ribeiro, Eraldo; Pimenta, Eduardo M.; Palhares, Reinaldo M.

    2014-01-01

    In this paper, a method that combines image analysis techniques, such as segmentation and registration, is proposed for an advanced and progressive evaluation of thermograms. The method is applied for the prevention of muscle injury in high-performance athletes, in collaboration with a Brazilian professional soccer club. The goal is to produce information on spatio-temporal variations of thermograms favoring the investigation of the athletes' conditions along the competition. The proposed method improves on current practice by providing a means for automatically detecting adaptive body-shaped regions of interest, instead of the manual selection of simple shapes. Specifically, our approach combines the optimization features in Otsu's method with a correction factor and post-processing techniques, enhancing thermal-image segmentation when compared to other methods. Additional contributions resulting from the combination of the segmentation and registration steps of our approach are the progressive analyses of thermograms in a unique spatial coordinate system and the accurate extraction of measurements and isotherms. PMID:25414972

  10. Uniscale multi-view registration using double dog-leg method

    NASA Astrophysics Data System (ADS)

    Chen, Chao-I.; Sargent, Dusty; Tsai, Chang-Ming; Wang, Yuan-Fang; Koppel, Dan

    2009-02-01

    3D computer models of body anatomy can have many uses in medical research and clinical practices. This paper describes a robust method that uses videos of body anatomy to construct multiple, partial 3D structures and then fuse them to form a larger, more complete computer model using the structure-from-motion framework. We employ the Double Dog-Leg (DDL) method, a trust-region based nonlinear optimization method, to jointly optimize the camera motion parameters (rotation and translation) and determine a global scale that all partial 3D structures should agree upon. These optimized motion parameters are used for constructing local structures, and the global scale is essential for multi-view registration after all these partial structures are built. In order to provide a good initial guess of the camera movement parameters and outlier free 2D point correspondences for DDL, we also propose a two-stage scheme where multi-RANSAC with a normalized eight-point algorithm is first performed and then a few iterations of an over-determined five-point algorithm is used to polish the results. Our experimental results using colonoscopy video show that the proposed scheme always produces more accurate outputs than the standard RANSAC scheme. Furthermore, since we have obtained many reliable point correspondences, time-consuming and error-prone registration methods like the iterative closest points (ICP) based algorithms can be replaced by a simple rigid-body transformation solver when merging partial structures into a larger model.

  11. 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.

  12. An automatic high precision registration method between large area aerial images and aerial light detection and ranging data

    NASA Astrophysics Data System (ADS)

    Du, Q.; Xie, D.; Sun, Y.

    2015-06-01

    The integration of digital aerial photogrammetry and Light Detetion And Ranging (LiDAR) is an inevitable trend in Surveying and Mapping field. We calculate the external orientation elements of images which identical with LiDAR coordinate to realize automatic high precision registration between aerial images and LiDAR data. There are two ways to calculate orientation elements. One is single image spatial resection using image matching 3D points that registered to LiDAR. The other one is Position and Orientation System (POS) data supported aerotriangulation. The high precision registration points are selected as Ground Control Points (GCPs) instead of measuring GCPs manually during aerotriangulation. The registration experiments indicate that the method which registering aerial images and LiDAR points has a great advantage in higher automation and precision compare with manual registration.

  13. A bounded iterative closest point method for minimally invasive registration of the femur.

    PubMed

    Rodriguez y Baena, Ferdinando; Hawke, Trevor; Jakopec, Matjaz

    2013-10-01

    This article describes a novel method for image-based, minimally invasive registration of the femur, for application to computer-assisted unicompartmental knee arthroplasty. The method is adapted from the well-known iterative closest point algorithm. By utilising an estimate of the hip centre on both the preoperative model and intraoperative patient anatomy, the proposed 'bounded' iterative closest point algorithm robustly produces accurate varus-valgus and anterior-posterior femoral alignment with minimal distal access requirements. Similar to the original iterative closest point implementation, the bounded iterative closest point algorithm converges monotonically to the closest minimum, and the presented case includes a common method for global minimum identification. The bounded iterative closest point method has shown to have exceptional resistance to noise during feature acquisition through simulations and in vitro plastic bone trials, where its performance is compared to a standard form of the iterative closest point algorithm. PMID:23959859

  14. Comparison of template registration methods for multi-site meta-analysis of brain morphometry

    NASA Astrophysics Data System (ADS)

    Faskowitz, Joshua; de Zubicaray, Greig I.; McMahon, Katie L.; Wright, Margaret J.; Thompson, Paul M.; Jahanshad, Neda

    2016-03-01

    Neuroimaging consortia such as ENIGMA can significantly improve power to discover factors that affect the human brain by pooling statistical inferences across cohorts to draw generalized conclusions from populations around the world. Voxelwise analyses such as tensor-based morphometry also allow an unbiased search for effects throughout the brain. Even so, such consortium-based analyses are limited by a lack of high-powered methods to harmonize voxelwise information across study populations and scanners. While the simplest approach may be to map all images to a single standard space, the benefits of cohort-specific templates have long been established. Here we studied methods to pool voxel-wise data across sites using templates customized for each cohort but providing a meaningful common space across all studies for voxelwise comparisons. As non-linear 3D MRI registrations represent mappings between images at millimeter resolution, we need to consider the reliability of these mappings. To evaluate these mappings, we calculated test-retest statistics on the volumetric maps of expansion and contraction. Further, we created study-specific brain templates for ten T1-weighted MRI datasets, and a common space from four study-specific templates. We evaluated the efficacy of using a two-step registration framework versus a single standard space. We found that the two-step framework more reliably mapped subjects to a common space.

  15. Note: A simple image processing based fiducial auto-alignment method for sample registration.

    PubMed

    Robertson, Wesley D; Porto, Lucas R; Ip, Candice J X; Nantel, Megan K T; Tellkamp, Friedjof; Lu, Yinfei; Miller, R J Dwayne

    2015-08-01

    A simple method for the location and auto-alignment of sample fiducials for sample registration using widely available MATLAB/LabVIEW software is demonstrated. The method is robust, easily implemented, and applicable to a wide variety of experiment types for improved reproducibility and increased setup speed. The software uses image processing to locate and measure the diameter and center point of circular fiducials for distance self-calibration and iterative alignment and can be used with most imaging systems. The method is demonstrated to be fast and reliable in locating and aligning sample fiducials, provided here by a nanofabricated array, with accuracy within the optical resolution of the imaging system. The software was further demonstrated to register, load, and sample the dynamically wetted array. PMID:26329245

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

    SciTech Connect

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

    2012-11-15

    Purpose: This study introduces a probabilistic nonrigid registration method for use in image-guided prostate brachytherapy. Intraoperative imaging for prostate procedures, usually transrectal ultrasound (TRUS), is typically inferior to diagnostic-quality imaging of the pelvis such as endorectal magnetic resonance imaging (MRI). MR images contain superior detail of the prostate boundaries and provide substructure features not otherwise visible. Previous efforts to register diagnostic prostate images with the intraoperative coordinate system have been deterministic and did not offer a measure of the registration uncertainty. The authors developed a Bayesian registration method to estimate the posterior distribution on deformations and provide a case-specific measure of the associated registration uncertainty. Methods: The authors adapted a biomechanical-based probabilistic nonrigid method to register diagnostic to intraoperative images by aligning a physician's segmentations of the prostate in the two images. The posterior distribution was characterized with a Markov Chain Monte Carlo method; the maximum a posteriori deformation and the associated uncertainty were estimated from the collection of deformation samples drawn from the posterior distribution. The authors validated the registration method using a dataset created from ten patients with MRI-guided prostate biopsies who had both diagnostic and intraprocedural 3 Tesla MRI scans. The accuracy and precision of the estimated posterior distribution on deformations were evaluated from two predictive distance distributions: between the deformed central zone-peripheral zone (CZ-PZ) interface and the physician-labeled interface, and based on physician-defined landmarks. Geometric margins on the registration of the prostate's peripheral zone were determined from the posterior predictive distance to the CZ-PZ interface separately for the base, mid-gland, and apical regions of the prostate. Results: The authors observed

  17. Quantitative evaluation of an image registration method for a NIPAM gel dosimeter

    NASA Astrophysics Data System (ADS)

    Chang, Yuan-Jen; Yao, Chun-Hsu; Wu, Jay; Hsieh, Bor-Tsung; Tsang, Yuk-Wah; Chen, Chin-Hsing

    2015-06-01

    One of the problems in obtaining quality results is image registration when a gel dosimeter is used in conjunction with optical computed tomography (CT). This study proposes a passive alignment mechanism to obtain a precisely measured dose map. A holder plate with two pin-hole pairs is placed on the gel container cap. These two pin-hole pairs attach the gel container to the vertical shaft and can be precisely aligned with the rotation center of the vertical shaft at any time. Accordingly, a better reconstructed image quality is obtained. After obtaining a precisely measured dose map, the scale invariant feature transform (SIFT)-flow algorithm is utilized as an image registration method to align the treatment plan software (TPS) image with the measured dose map image. The results show that the gamma pass rate for the single-field irradiation increases from 83.39% to 94.03% when the algorithm is applied. And the gamma pass rate for the five-field irradiation treatment plan increases from 87.36% to 94.34%. The translation, scaling, and rotation occurring in the dose map image constructed using an optical CT scanner are also aligned with those in the TPS image using the SIFT-flow algorithm. Accordingly, improved gamma comparison results and a higher gamma pass rate are obtained.

  18. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Registration. 1615.1 Section 1615.1 National... REGISTRATION § 1615.1 Registration. (a) Registration under selective service law consists of: (1) Completing a registration card or other method of registration prescribed by the Director of Selective Service by a...

  19. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 6 2011-07-01 2011-07-01 false Registration. 1615.1 Section 1615.1 National... REGISTRATION § 1615.1 Registration. (a) Registration under selective service law consists of: (1) Completing a registration card or other method of registration prescribed by the Director of Selective Service by a...

  20. PSO-based methods for medical image registration and change assessment of pigmented skin

    NASA Astrophysics Data System (ADS)

    Kacenjar, Steve; Zook, Matthew; Balint, Michael

    2011-03-01

    There are various scientific and technological areas in which it is imperative to rapidly detect and quantify changes in imagery over time. In fields such as earth remote sensing, aerospace systems, and medical imaging, searching for timedependent, regional changes across deformable topographies is complicated by varying camera acquisition geometries, lighting environments, background clutter conditions, and occlusion. Under these constantly-fluctuating conditions, the use of standard, rigid-body registration approaches often fail to provide sufficient fidelity to overlay image scenes together. This is problematic because incorrect assessments of the underlying changes of high-level topography can result in systematic errors in the quantification and classification of interested areas. For example, in the current naked-eye detection strategies of melanoma, a dermatologist often uses static morphological attributes to identify suspicious skin lesions for biopsy. This approach does not incorporate temporal changes which suggest malignant degeneration. By performing the co-registration of time-separated skin imagery, a dermatologist may more effectively detect and identify early morphological changes in pigmented lesions; enabling the physician to detect cancers at an earlier stage resulting in decreased morbidity and mortality. This paper describes an image processing system which will be used to detect changes in the characteristics of skin lesions over time. The proposed system consists of three main functional elements: 1.) coarse alignment of timesequenced imagery, 2.) refined alignment of local skin topographies, and 3.) assessment of local changes in lesion size. During the coarse alignment process, various approaches can be used to obtain a rough alignment, including: 1.) a manual landmark/intensity-based registration method1, and 2.) several flavors of autonomous optical matched filter methods2. These procedures result in the rough alignment of a patient

  1. Nonrigid registration method to assess reproducibility of breath-holding with ABC in lung cancer

    SciTech Connect

    Sarrut, David . E-mail: dsarrut@univ-lyon2.fr; Boldea, Vlad; Ayadi, Myriam; Badel, Jean-Noel; Ginestet, Chantal; Clippe, Sebastien; Carrie, Christian

    2005-02-01

    Purpose: To study the interfraction reproducibility of breath-holding using active breath control (ABC), and to develop computerized tools to evaluate three-dimensional (3D) intrathoracic motion in each patient. Methods and materials: Since June 2002, 11 patients with non-small-cell lung cancer enrolled in a Phase II trial have undergone four CT scans: one during free-breathing (reference) and three using ABC. Patients left the room between breath-hold scans. The patient's breath was held at the same predefined phase of the breathing cycle (about 70% of the vital capacity) using the ABC device, then patients received 3D-conformal radiotherapy. Automated computerized tools for breath-hold CT scans were developed to analyze lung and tumor interfraction residual motions with 3D nonrigid registration. Results: All patients but one were safely treated with ABC for 7 weeks. For 6 patients, the lung volume differences were <5%. The mean 3D displacement inside the lungs was between 2.3 mm (SD 1.4) and 4 mm (SD 3.3), and the gross tumor volume residual motion was 0.9 mm (SD 0.4) to 5.9 mm (SD 0.7). The residual motion was slightly greater in the inferior part of the lung than the superior. For 2 patients, we detected volume changes >300 cm{sup 3} and displacements >10 mm, probably owing to atelectasia and emphysema. One patient was excluded, and two others had incomplete data sets. Conclusion: Breath-holding with ABC was effective in 6 patients, and discrepancies were clinically accountable in 2. The proposed 3D nonrigid registration method allows for personalized evaluation of breath-holding reproducibility with ABC. It will be used to adapt the patient-specific internal margins.

  2. Scene-based nonuniformity correction using multiframe registration and iteration method

    NASA Astrophysics Data System (ADS)

    Ren, Jianle; Chen, Qian; Qian, Weixian; Yu, Xuelian; Li, Danping

    2014-05-01

    In this paper, an improved scene-based nonuniformity correction (NC) algorithm for infrared focal plane arrays (IRFPAs) using multiframe registration and iteration method is proposed. This method estimates the global translation and iterates between several adjacent frames. Then mean square error between any two properly registered images is minimized to obtain nonuniformity correction parameters. The detailed method includes three main steps: First, we assume that brightness along the motion trajectory is constant, and a linear detector response and model the nonuniformity of each detector with a gain and a bias. Second, several adjacent frames are used to compute relative motion of any two adjacent frames. Here we use the Fourier shift theorem, their relative translation can be obtained by calculating their normalized cross-power spectrum. We choose K adjacent frames, so the total number of iteration is K*(K-1)/2. Then the mean square error function is defined as the corresponding difference between the two adjacent corrected frames, and it is minimized making use of the least mean square algorithm. The use of correlation of adjacent frames sufficiently, together with iteration strategy between them, can get fast and reliable fixed-pattern noise reduction with low few ghosting artifacts. We define the algorithm and present a number of experimental results to demonstrate the efficacy of the proposed method in comparison to several previously published methods. The performance of the proposed method is thoroughly evaluated with clean infrared image sequences with synthetic nonuniformity and real infrared imagery.

  3. Automatic Registration between Real-Time Ultrasonography and Pre-Procedural Magnetic Resonance Images: A Prospective Comparison between Two Registration Methods by Liver Surface and Vessel and by Liver Surface Only.

    PubMed

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

    2016-07-01

    The aim of this study was to compare the accuracy of and the time required for image fusion between real-time ultrasonography (US) and pre-procedural magnetic resonance (MR) images using automatic registration by a liver surface only method and automatic registration by a liver surface and vessel method. This study consisted of 20 patients referred for planning US to assess the feasibility of percutaneous radiofrequency ablation or biopsy for focal hepatic lesions. The first 10 consecutive patients were evaluated by an experienced radiologist using the automatic registration by liver surface and vessel method, whereas the remaining 10 patients were evaluated using the automatic registration by liver surface only method. For all 20 patients, image fusion was automatically executed after following the protocols and fused real-time US and MR images moved synchronously. The accuracy of each method was evaluated by measuring the registration error, and the time required for image fusion was assessed by evaluating the recorded data using in-house software. The results obtained using the two automatic registration methods were compared using the Mann-Whitney U-test. Image fusion was successful in all 20 patients, and the time required for image fusion was significantly shorter with the automatic registration by liver surface only method than with the automatic registration by liver surface and vessel method (median: 43.0 s, range: 29-74 s vs. median: 83.0 s, range: 46-101 s; p = 0.002). The registration error did not significantly differ between the two methods (median: 4.0 mm, range: 2.1-9.9 mm vs. median: 3.7 mm, range: 1.8-5.2 mm; p = 0.496). The automatic registration by liver surface only method offers faster image fusion between real-time US and pre-procedural MR images than does the automatic registration by liver surface and vessel method. However, the degree of accuracy was similar for the two methods. PMID:27085384

  4. Registration and three-dimensional reconstruction of autoradiographic images by the disparity analysis method

    SciTech Connect

    Zhao, Weizhao; Ginsberg, M. . Cerebral Vascular Disease Research Center); Young, T.Y. . Dept. of Electrical and Computer Engineering)

    1993-12-01

    Quantitative autoradiography is a powerful radio-isotopic-imaging method for neuroscientists to study local cerebral blood flow and glucose-metabolic rate at rest, in response to physiologic activation of the visual, auditory, somatosensory, and motor systems, and in pathologic conditions. Most autoradiographic studies analyze glucose utilization and blood flow in two-dimensional (2-D) coronal sections. With modern digital computer and image-processing techniques, a large number of closely spaced coronal sections can be stacked appropriately to form a three-dimensional (3-d) image. 3-D autoradiography allows investigators to observe cerebral sections and surfaces from any viewing angle. A fundamental problem in 3-D reconstruction is the alignment (registration) of the coronal sections. A new alignment method based on disparity analysis is presented which can overcome many of the difficulties encountered by previous methods. The disparity analysis method can deal with asymmetric, damaged, or tilted coronal sections under the same general framework, and it can be used to match coronal sections of different sizes and shapes. Experimental results on alignment and 3-D reconstruction are presented.

  5. Diagnostic possibilities with multidimensional images in head and neck area using efficient registration and visualization methods

    NASA Astrophysics Data System (ADS)

    Zeilhofer, Hans-Florian U.; Krol, Zdzislaw; Sader, Robert; Hoffmann, Karl-Heinz; Gerhardt, Paul; Schweiger, Markus; Horch, Hans-Henning

    1997-05-01

    For several diseases in the head and neck area different imaging modalities are applied to the same patient.Each of these image data sets has its specific advantages and disadvantages. The combination of different methods allows to make the best use of the advantageous properties of each method while minimizing the impact of its negative aspects. Soft tissue alterations can be judged better in an MRI image while it may be unrecognizable in the relating CT. Bone tissue, on the other hand, is optimally imaged in CT. Inflammatory nuclei of the bone can be detected best by their increased signal in SPECT. Only the combination of all modalities let the physical come to an exact statement on pathological processes that involve multiple tissue structures. Several surfaces and voxel based matching functions we have tested allowed a precise merging by means of numerical optimization methods like e.g. simulated annealing without the complicated assertion of fiducial markers or the localization landmarks in 2D cross sectional slice images. The quality of the registration depends on the choice of the optimization procedure according to the complexity of the matching function landscape. Precise correlation of the multimodal head and neck area images together with its 2D and 3D presentation techniques provides a valuable tool for physicians.

  6. 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.

  7. A fast alignment method for breast MRI follow-up studies using automated breast segmentation and current-prior registration

    NASA Astrophysics Data System (ADS)

    Wang, Lei; Strehlow, Jan; Rühaak, Jan; Weiler, Florian; Diez, Yago; Gubern-Merida, Albert; Diekmann, Susanne; Laue, Hendrik; Hahn, Horst K.

    2015-03-01

    In breast cancer screening for high-risk women, follow-up magnetic resonance images (MRI) are acquired with a time interval ranging from several months up to a few years. Prior MRI studies may provide additional clinical value when examining the current one and thus have the potential to increase sensitivity and specificity of screening. To build a spatial correlation between suspicious findings in both current and prior studies, a reliable alignment method between follow-up studies is desirable. However, long time interval, different scanners and imaging protocols, and varying breast compression can result in a large deformation, which challenges the registration process. In this work, we present a fast and robust spatial alignment framework, which combines automated breast segmentation and current-prior registration techniques in a multi-level fashion. First, fully automatic breast segmentation is applied to extract the breast masks that are used to obtain an initial affine transform. Then, a non-rigid registration algorithm using normalized gradient fields as similarity measure together with curvature regularization is applied. A total of 29 subjects and 58 breast MR images were collected for performance assessment. To evaluate the global registration accuracy, the volume overlap and boundary surface distance metrics are calculated, resulting in an average Dice Similarity Coefficient (DSC) of 0.96 and root mean square distance (RMSD) of 1.64 mm. In addition, to measure local registration accuracy, for each subject a radiologist annotated 10 pairs of markers in the current and prior studies representing corresponding anatomical locations. The average distance error of marker pairs dropped from 67.37 mm to 10.86 mm after applying registration.

  8. An efficient strategy based on an individualized selection of registration methods. Application to the coregistration of MR and SPECT images in neuro-oncology

    NASA Astrophysics Data System (ADS)

    Tacchella, Jean-Marc; Roullot, Elodie; Lefort, Muriel; Cohen, Mike-Ely; Guillevin, Rémy; Petrirena, Grégorio; Delattre, Jean-Yves; Habert, Marie-Odile; Yeni, Nathanaëlle; Kas, Aurélie; Frouin, Frédérique

    2014-11-01

    An efficient registration strategy is described that aims to help solve delicate medical imaging registration problems. It consists of running several registration methods for each dataset and selecting the best one for each specific dataset, according to an evaluation criterion. Finally, the quality of the registration results, obtained with the best method, is visually scored by an expert as excellent, correct or poor. The strategy was applied to coregister Technetium-99m Sestamibi SPECT and MRI data in the framework of a follow-up protocol in patients with high grade gliomas receiving antiangiogenic therapy. To adapt the strategy to this clinical context, a robust semi-automatic evaluation criterion based on the physiological uptake of the Sestamibi tracer was defined. A panel of eighteen multimodal registration algorithms issued from BrainVisa, SPM or AIR software environments was systematically applied to the clinical database composed of sixty-two datasets. According to the expert visual validation, this new strategy provides 85% excellent registrations, 12% correct ones and only 3% poor ones. These results compare favorably to the ones obtained by the globally most efficient registration method over the whole database, for which only 61% of excellent registration results have been reported. Thus the registration strategy in its current implementation proves to be suitable for clinical application.

  9. Studying primate carpal kinematics in three dimensions using a computed-tomography-based markerless registration method.

    PubMed

    Orr, Caley M; Leventhal, Evan L; Chivers, Spencer F; Marzke, Mary W; Wolfe, Scott W; Crisco, Joseph J

    2010-04-01

    The functional morphology of the wrist pertains to a number of important questions in primate evolutionary biology, including that of hominins. Reconstructing locomotor and manipulative capabilities of the wrist in extinct species requires a detailed understanding of wrist biomechanics in extant primates and the relationship between carpal form and function. The kinematics of carpal movement, and the role individual joints play in providing mobility and stability of the wrist, is central to such efforts. However, there have been few detailed biomechanical studies of the nonhuman primate wrist. This is largely because of the complexity of wrist morphology and the considerable technical challenges involved in tracking the movements of the many small bones that compose the carpus. The purpose of this article is to introduce and outline a method adapted from human clinical studies of three-dimensional (3D) carpal kinematics for use in a comparative context. The method employs computed tomography of primate cadaver forelimbs in increments throughout the wrist's range of motion, coupled with markerless registration of 3D polygon models based on inertial properties of each bone. The 3D kinematic principles involved in extracting motion axis parameters that describe bone movement are reviewed. In addition, a set of anatomically based coordinate systems embedded in the radius, capitate, hamate, lunate, and scaphoid is presented for the benefit of other primate functional morphologists interested in studying carpal kinematics. Finally, a brief demonstration of how the application of these methods can elucidate the mechanics of the wrist in primates illustrates the closer-packing of carpals in chimpanzees than in orangutans, which may help to stabilize the midcarpus and produce a more rigid wrist beneficial for efficient hand posturing during knuckle-walking locomotion. PMID:20235325

  10. African American Organ Donor Registration: A Mixed Methods Design using the Theory of Planned Behavior

    PubMed Central

    DuBay, Derek A.; Ivankova, Nataliya; Herby, Ivan; Wynn, Theresa A.; Kohler, Connie; Berry, Beverly; Foushee, Herman; Carson, April; Redden, David T.; Holt, Cheryl; Siminoff, Laura; Fouad, Mona; Martin, Michelle Y.

    2015-01-01

    Context A large racial disparity exists in organ donation. Objective The purpose of this study was to identify factors associated with becoming a registered organ donor in among African Americans in Alabama. Methods The study utilized a concurrent mixed methods design guided by the Theory of Planned Behavior to analyze African American’s decisions to become a registered organ donor using both qualitative (focus groups) and quantitative (survey) methods. Results The sample consisted of 22 registered organ donors (ROD) and 65 non-registered participants (NRP) from six focus groups completed in urban (n=3) and rural (n=3) areas. Participants emphasized the importance of the autonomy to make one’s own organ donation decision and have this decision honored posthumously. One novel barrier to becoming a ROD was the perception that organs from African Americans were often unusable due to high prevalence of chronic medical conditions such as diabetes and hypertension. Another novel theme discussed as an advantage to becoming a ROD was the subsequent motivation to take responsibility for one’s health. Family and friends were the most common groups of persons identified as approving and disapproving of the decision to become a ROD. The most common facilitator to becoming a ROD was information, while fear and the lack of information were the most common barriers. In contrast, religious beliefs, mistrust and social justice themes were infrequently referenced as barriers to becoming a ROD. Discussion Findings from this study may be useful for prioritizing organ donation community-based educational interventions in campaigns to increase donor registration. PMID:25193729

  11. Student Engagement and Course Registration Methods as Possible Predictors of Freshman Retention

    ERIC Educational Resources Information Center

    Bass, Laura H.; Ballard, Angela S.

    2012-01-01

    A study by Kenney, Kenney, and Dumont (2005) identified a supportive learning environment as one of the five indicators for collegiate student engagement, a concept that extends beyond the classroom to permeate the entire educational environment. A student's level of engagement can be impacted as early as orientation and registration, when he is…

  12. Voter Registration and Canvassing.

    ERIC Educational Resources Information Center

    Institute for Political/Legal Education, Sewell, NJ.

    Detailed procedures for community voter registration surveys to be conducted by high school students are presented. Methods for organizational structure, selection of canvassing districts, conducting the survey, processing the data, and initiating a registration drive are outlined. Student personnel include a general coordinator, a field staff to…

  13. 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.

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

    SciTech Connect

    Vijayan, Sinara; Klein, Stefan; Hofstad, Erlend Fagertun; Langø, Thomas; Lindseth, Frank; Ystgaard, Brynjulf

    2014-08-15

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

  15. A method for quantitative analysis of regional lung ventilation using deformable image registration of CT and hybrid hyperpolarized gas/1H MRI.

    PubMed

    Tahir, Bilal A; Swift, Andrew J; Marshall, Helen; Parra-Robles, Juan; Hatton, Matthew Q; Hartley, Ruth; Kay, Richard; Brightling, Christopher E; Vos, Wim; Wild, Jim M; Ireland, Rob H

    2014-12-01

    Hyperpolarized gas magnetic resonance imaging (MRI) generates highly detailed maps of lung ventilation and physiological function while CT provides corresponding anatomical and structural information. Fusion of such complementary images enables quantitative analysis of pulmonary structure-function. However, direct image registration of hyperpolarized gas MRI to CT is problematic, particularly in lungs whose boundaries are difficult to delineate due to ventilation heterogeneity. This study presents a novel indirect method of registering hyperpolarized gas MRI to CT utilizing (1)H-structural MR images that are acquired in the same breath-hold as the gas MRI. The feasibility of using this technique for regional quantification of ventilation of specific pulmonary structures is demonstrated for the lobes.The direct and indirect methods of hyperpolarized gas MRI to CT image registration were compared using lung images from 15 asthma patients. Both affine and diffeomorphic image transformations were implemented. Registration accuracy was evaluated using the target registration error (TRE) of anatomical landmarks identified on (1)H MRI and CT. The Wilcoxon signed-rank test was used to test statistical significance.For the affine transformation, the indirect method of image registration was significantly more accurate than the direct method (TRE = 14.7 ± 3.2 versus 19.6 ± 12.7 mm, p = 0.036). Using a deformable transformation, the indirect method was also more accurate than the direct method (TRE = 13.5 ± 3.3 versus 20.4 ± 12.8 mm, p = 0.006).Accurate image registration is critical for quantification of regional lung ventilation with hyperpolarized gas MRI within the anatomy delineated by CT. Automatic deformable image registration of hyperpolarized gas MRI to CT via same breath-hold (1)H MRI is more accurate than direct registration. Potential applications include improved multi-modality image fusion, functionally weighted radiotherapy planning, and quantification of

  16. A non-rigid registration method for cerebral DSA images based on forward and inverse stretching - avoiding bilinear interpolation.

    PubMed

    Liu, Bin; Zhang, Bingbing; Wan, Chao; Dong, Yihuan

    2014-01-01

    In order to reduce the motion artifact caused by the patient in cerebral DSA images, a non-rigid registration method based on stretching transformation is presented in this paper. Unlike other traditional methods, it does not need bilinear interpolation which is rather time-consuming and even produce 'originally non-existent gray value'. By this method, the mask image is rasterized to generate appropriate control points. The Energy of Histogram of Differences criterion is adopted as similarity measurement, and the Powell algorithm is utilized for acceleration. A forward stretching transformation is used to complete motion estimation and an inverse stretching transformation to generate target image by pixel mapping strategy. This method is effective to maintain the topological relationships of the gray value before and after the image deformation. The mask image remains clear and accurate contours, and the quality of the subtraction image after the registration is favorable. This method can provide support for clinical treatment and diagnosis of cerebral disease. PMID:24212008

  17. Feature-Based Registration Techniques

    NASA Astrophysics Data System (ADS)

    Lorenz, Cristian; Klinder, Tobias; von Berg, Jens

    In contrast to intensity-based image registration, where a similarity measure is typically evaluated at each voxel location, feature-based registration works on a sparse set of image locations. Therefore, it needs an explicit step of interpolation to supply a dense deformation field. In this chapter, the application of feature-based registration to pulmonary image registration as well as hybrid methods, combining feature-based with intensity-based registration, is discussed. In contrast to pure feature based registration methods, hybrid methods are increasingly proposed in the pulmonary context and have the potential to out-perform purely intensity based registration methods. Available approaches will be classified along the categories feature type, correspondence definition, and interpolation type to finally achieve a dense deformation field.

  18. An accuracy assessment of different rigid body image registration methods and robotic couch positional corrections using a novel phantom

    SciTech Connect

    Arumugam, Sankar; Xing Aitang; Jameson, Michael G.; Holloway, Lois

    2013-03-15

    Purpose: Image guided radiotherapy (IGRT) using cone beam computed tomography (CBCT) images greatly reduces interfractional patient positional uncertainties. An understanding of uncertainties in the IGRT process itself is essential to ensure appropriate use of this technology. The purpose of this study was to develop a phantom capable of assessing the accuracy of IGRT hardware and software including a 6 degrees of freedom patient positioning system and to investigate the accuracy of the Elekta XVI system in combination with the HexaPOD robotic treatment couch top. Methods: The constructed phantom enabled verification of the three automatic rigid body registrations (gray value, bone, seed) available in the Elekta XVI software and includes an adjustable mount that introduces known rotational offsets to the phantom from its reference position. Repeated positioning of the phantom was undertaken to assess phantom rotational accuracy. Using this phantom the accuracy of the XVI registration algorithms was assessed considering CBCT hardware factors and image resolution together with the residual error in the overall image guidance process when positional corrections were performed through the HexaPOD couch system. Results: The phantom positioning was found to be within 0.04 ({sigma}= 0.12) Degree-Sign , 0.02 ({sigma}= 0.13) Degree-Sign , and -0.03 ({sigma}= 0.06) Degree-Sign in X, Y, and Z directions, respectively, enabling assessment of IGRT with a 6 degrees of freedom patient positioning system. The gray value registration algorithm showed the least error in calculated offsets with maximum mean difference of -0.2({sigma}= 0.4) mm in translational and -0.1({sigma}= 0.1) Degree-Sign in rotational directions for all image resolutions. Bone and seed registration were found to be sensitive to CBCT image resolution. Seed registration was found to be most sensitive demonstrating a maximum mean error of -0.3({sigma}= 0.9) mm and -1.4({sigma}= 1.7) Degree-Sign in translational

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  1. Lung texture in serial thoracic CT scans: Registration-based methods to compare anatomically matched regions1

    PubMed Central

    Cunliffe, Alexandra R.; Armato, Samuel G.; Fei, Xianhan M.; Tuohy, Rachel E.; Al-Hallaq, Hania A.

    2013-01-01

    Purpose: The aim of this study was to compare three demons registration-based methods to identify spatially matched regions in serial computed tomography (CT) scans for use in texture analysis. Methods: Two thoracic CT scans containing no lung abnormalities and acquired during serial examinations separated by at least one week were retrospectively collected from 27 patients. Over 1000 regions of interest (ROIs) were randomly placed in the lungs of each baseline scan. Anatomically matched ROIs in the corresponding follow-up scan were placed by mapping the baseline scan ROI center pixel to (1) the original follow-up scan, (2) the follow-up scan resampled to match the baseline scan voxel size, and (3) the follow-up scan aligned to the baseline scan through affine registration. Mappings used the vector field obtained through demons deformable registration of each follow-up scan variant to the baseline scan. 140 texture features distributed among five feature classes were calculated in all ROIs. Feature value differences between paired ROIs were evaluated using Bland-Altman 95% limits of agreement. For each feature, (1) the mean feature value change and (2) the difference between the upper and lower limits of agreement were normalized to the mean feature value to obtain, respectively, the normalized bias and normalized range of agreement (nRoA). Nonparametric tests were used to evaluate differences in normalized bias and nRoA across the three methods. Results: Because patient CT scans contained no pathology, minimal changes in feature values were expected (i.e., low nRoA and normalized bias). Seventy-five features with very large feature value variability (nRoA ≥ 100%) were excluded from further analysis. Across the remaining 65 features, significant differences in normalized bias were observed among the three methods. The lowest normalized bias (median: 0.06%) was achieved when feature values were calculated on original follow-up scans. The affine registration method

  2. 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.

  3. SU-E-J-58: Comparison of Conformal Tracking Methods Using Initial, Adaptive and Preceding Image Frames for Image Registration

    SciTech Connect

    Teo, P; Guo, K; Alayoubi, N; Kehler, K; Pistorius, S

    2015-06-15

    Purpose: Accounting for tumor motion during radiation therapy is important to ensure that the tumor receives the prescribed dose. Increasing the field size to account for this motion exposes the surrounding healthy tissues to unnecessary radiation. In contrast to using motion-encompassing techniques to treat moving tumors, conformal radiation therapy (RT) uses a smaller field to track the tumor and adapts the beam aperture according to the motion detected. This work investigates and compares the performance of three markerless, EPID based, optical flow methods to track tumor motion with conformal RT. Methods: Three techniques were used to track the motions of a 3D printed lung tumor programmed to move according to the tumor of seven lung cancer patients. These techniques utilized a multi-resolution optical flow algorithm as the core computation for image registration. The first method (DIR) registers the incoming images with an initial reference frame, while the second method (RFSF) uses an adaptive reference frame and the third method (CU) uses preceding image frames for registration. The patient traces and errors were evaluated for the seven patients. Results: The average position errors for all patient traces were 0.12 ± 0.33 mm, −0.05 ± 0.04 mm and −0.28 ± 0.44 mm for CU, DIR and RFSF method respectively. The position errors distributed within 1 standard deviation are 0.74 mm, 0.37 mm and 0.96 mm respectively. The CU and RFSF algorithms are sensitive to the characteristics of the patient trace and produce a wider distribution of errors amongst patients. Although the mean error for the DIR method is negatively biased (−0.05 mm) for all patients, it has the narrowest distribution of position error, which can be corrected using an offset calibration. Conclusion: Three techniques of image registration and position update were studied. Using direct comparison with an initial frame yields the best performance. The authors would like to thank Dr.YeLin Suh for

  4. 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

  5. Assessment of Thematic Mapper Band-to-band Registration by the Block Correlation Method

    NASA Technical Reports Server (NTRS)

    Card, D. H.; Wrigley, R. C.; Mertz, F. C.; Hall, J. R.

    1985-01-01

    Rectangular blocks of pixels from one band image were statistically correlated against blocks centered on identical pixels from a second band image. The block pairs were shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient to the maximum correlation was taken as the best estimate of registration error for each block pair. For the band combinations of the Arkansas scene studied, the misregistration of TM spectral bands within the noncooled focal plane lie well within the 0.2 pixel target specification. Misregistration between the middle IR bands is well within this specification also. The thermal IR band has an apparent misregistration with TM band 7 of approximately 3 pixels in each direction. The TM band 3 has a misregistration of approximately 0.2 pixel in the across-scan direction and 0.5 pixel in the along-scan direction, with both TM bands 5 and 7.

  6. Assessment of Thematic Mapper band-to-band registration by the block correlation method

    NASA Technical Reports Server (NTRS)

    Card, D. H.; Wrigley, R. C.; Mertz, F. C.; Hall, J. R.

    1983-01-01

    Rectangular blocks of pixels from one band image were statistically correlated against blocks centered on identical pixels from a second band image. The block pairs were shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient to the maximum correlation was taken as the best estimate of registration error for each block pair. For the band combinations of the Arkansas scene studied, the misregistration of TM spectral bands within the noncooled focal plane lie well within the 0.2 pixel target specification. Misregistration between the middle IR bands is well within this specification also. The thermal IR band has an apparent misregistration with TM band 7 of approximately 3 pixels in each direction. The TM band 3 has a misregistration of approximately 0.2 pixel in the across-scan direction and 0.5 pixel in the along-scan direction, with both TM bands 5 and 7.

  7. A multiple-image-based method to evaluate the performance of deformable image registration in the pelvis

    NASA Astrophysics Data System (ADS)

    Saleh, Ziad; Thor, Maria; Apte, Aditya P.; Sharp, Gregory; Tang, Xiaoli; Veeraraghavan, Harini; Muren, Ludvig; Deasy, Joseph

    2016-08-01

    Deformable image registration (DIR) is essential for adaptive radiotherapy (RT) for tumor sites subject to motion, changes in tumor volume, as well as changes in patient normal anatomy due to weight loss. Several methods have been published to evaluate DIR-related uncertainties but they are not widely adopted. The aim of this study was, therefore, to evaluate intra-patient DIR for two highly deformable organs—the bladder and the rectum—in prostate cancer RT using a quantitative metric based on multiple image registration, the distance discordance metric (DDM). Voxel-by-voxel DIR uncertainties of the bladder and rectum were evaluated using DDM on weekly CT scans of 38 subjects previously treated with RT for prostate cancer (six scans/subject). The DDM was obtained from group-wise B-spline registration of each patient’s collection of repeat CT scans. For each structure, registration uncertainties were derived from DDM-related metrics. In addition, five other quantitative measures, including inverse consistency error (ICE), transitivity error (TE), Dice similarity (DSC) and volume ratios between corresponding structures from pre- and post- registered images were computed and compared with the DDM. The DDM varied across subjects and structures; DDMmean of the bladder ranged from 2 to 13 mm and from 1 to 11 mm for the rectum. There was a high correlation between DDMmean of the bladder and the rectum (Pearson’s correlation coefficient, R p  =  0.62). The correlation between DDMmean and the volume ratios post-DIR was stronger (R p  =  0.51 0.68) than the correlation with the TE (bladder: R p  =  0.46 rectum: R p  =  0.47), or the ICE (bladder: R p  =  0.34 rectum: R p  =  0.37). There was a negative correlation between DSC and DDMmean of both the bladder (R p  =  ‑0.23) and the rectum (R p  =  ‑0.63). The DDM uncertainty metric indicated considerable DIR variability across subjects and

  8. A multiple-image-based method to evaluate the performance of deformable image registration in the pelvis.

    PubMed

    Saleh, Ziad; Thor, Maria; Apte, Aditya P; Sharp, Gregory; Tang, Xiaoli; Veeraraghavan, Harini; Muren, Ludvig; Deasy, Joseph

    2016-08-21

    Deformable image registration (DIR) is essential for adaptive radiotherapy (RT) for tumor sites subject to motion, changes in tumor volume, as well as changes in patient normal anatomy due to weight loss. Several methods have been published to evaluate DIR-related uncertainties but they are not widely adopted. The aim of this study was, therefore, to evaluate intra-patient DIR for two highly deformable organs-the bladder and the rectum-in prostate cancer RT using a quantitative metric based on multiple image registration, the distance discordance metric (DDM). Voxel-by-voxel DIR uncertainties of the bladder and rectum were evaluated using DDM on weekly CT scans of 38 subjects previously treated with RT for prostate cancer (six scans/subject). The DDM was obtained from group-wise B-spline registration of each patient's collection of repeat CT scans. For each structure, registration uncertainties were derived from DDM-related metrics. In addition, five other quantitative measures, including inverse consistency error (ICE), transitivity error (TE), Dice similarity (DSC) and volume ratios between corresponding structures from pre- and post- registered images were computed and compared with the DDM. The DDM varied across subjects and structures; DDMmean of the bladder ranged from 2 to 13 mm and from 1 to 11 mm for the rectum. There was a high correlation between DDMmean of the bladder and the rectum (Pearson's correlation coefficient, R p  =  0.62). The correlation between DDMmean and the volume ratios post-DIR was stronger (R p  =  0.51; 0.68) than the correlation with the TE (bladder: R p  =  0.46; rectum: R p  =  0.47), or the ICE (bladder: R p  =  0.34; rectum: R p  =  0.37). There was a negative correlation between DSC and DDMmean of both the bladder (R p  =  -0.23) and the rectum (R p  =  -0.63). The DDM uncertainty metric indicated considerable DIR variability across subjects and structures. Our

  9. A comparative study between evaluation methods for quality control procedures for determining the accuracy of PET/CT registration

    NASA Astrophysics Data System (ADS)

    Cha, Min Kyoung; Ko, Hyun Soo; Jung, Woo Young; Ryu, Jae Kwang; Choe, Bo-Young

    2015-08-01

    The Accuracy of registration between positron emission tomography (PET) and computed tomography (CT) images is one of the important factors for reliable diagnosis in PET/CT examinations. Although quality control (QC) for checking alignment of PET and CT images should be performed periodically, the procedures have not been fully established. The aim of this study is to determine optimal quality control (QC) procedures that can be performed at the user level to ensure the accuracy of PET/CT registration. Two phantoms were used to carry out this study: the American college of Radiology (ACR)-approved PET phantom and National Electrical Manufacturers Association (NEMA) International Electrotechnical Commission (IEC) body phantom, containing fillable spheres. All PET/CT images were acquired on a Biograph TruePoint 40 PET/CT scanner using routine protocols. To measure registration error, the spatial coordinates of the estimated centers of the target slice (spheres) was calculated independently for the PET and the CT images in two ways. We compared the images from the ACR-approved PET phantom to that from the NEMA IEC body phantom. Also, we measured the total time required from phantom preparation to image analysis. The first analysis method showed a total difference of 0.636 ± 0.11 mm for the largest hot sphere and 0.198 ± 0.09 mm for the largest cold sphere in the case of the ACR-approved PET phantom. In the NEMA IEC body phantom, the total difference was 3.720 ± 0.97 mm for the largest hot sphere and 4.800 ± 0.85 mm for the largest cold sphere. The second analysis method showed that the differences in the x location at the line profile of the lesion on PET and CT were (1.33, 1.33) mm for a bone lesion, (-1.26, -1.33) mm for an air lesion and (-1.67, -1.60) mm for a hot sphere lesion for the ACR-approved PET phantom. For the NEMA IEC body phantom, the differences in the x location at the line profile of the lesion on PET and CT were (-1.33, 4.00) mm for the air

  10. The Intego database: background, methods and basic results of a Flemish general practice-based continuous morbidity registration project

    PubMed Central

    2014-01-01

    Background Intego is the only operational computerized morbidity registration network in Belgium based on general practice data. Intego collects data from over 90 general practitioners. All the information is routinely collected in the electronic health record during daily practice. Methods In this article we describe the design and methods used within the Intego network together with some of its basic results. The collected data, the quality control procedures, the ethical-legal aspects and the statistical procedures are discussed. Results Intego contains longitudinal information on 285 357 different patients, corresponding to over 2.3% of the Flemish population representative in terms of age and sex. More than 3 million diagnoses, 12 million drug prescriptions and 29 million laboratory tests have been recorded. Conclusions Intego enables us to present and compare data on health parameters, incidence and prevalence rates, laboratory results, and prescribed drugs for all relevant subgroups on a routine basis and is unique in Belgium. PMID:24906941

  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. WE-D-9A-01: A Novel Mesh-Based Deformable Surface-Contour Registration

    SciTech Connect

    Zhong, Z; Cai, Y; Guo, X; Jia, X; Chiu, T; Kearney, V; Liu, H; Jiang, L; Chen, S; Yordy, J; Nedzi, L; Mao, W

    2014-06-15

    Purpose: Initial guess is vital for 3D-2D deformable image registration (DIR) while dealing with large deformations for adaptive radiation therapy. A fast procedure has been developed to deform body surface to match 2D body contour on projections. This surface-contour DIR will provide an initial deformation for further complete 3D DIR or image reconstruction. Methods: Both planning CT images and come-beam CT (CBCT) projections are preprocessed to create 0–1 binary mask. Then the body surface and CBCT projection body contours are extracted by Canny edge detector. A finite element modeling system was developed to automatically generate adaptive meshes based on the image surface. After that, the projections of the CT surface voxels are computed and compared with corresponding 2D projection contours from CBCT scans. As a result, the displacement vector field (DVF) on mesh vertices around the surface was optimized iteratively until the shortest Euclidean distance between the pixels on the projections of the deformed CT surface and the corresponding CBCT projection contour is minimized. With the help of the tetrahedral meshes, we can smoothly diffuse the deformation from the surface into the interior of the volume. Finally, the deformed CT images are obtained by the optimal DVF applied on the original planning CT images. Results: The accuracy of the surface-contour registration is evaluated by 3D normalized cross correlation increased from 0.9176 to 0.9957 (sphere-ellipsoid phantom) and from 0.7627 to 0.7919 (H and N cancer patient data). Under the GPU-based implementation, our surface-contour-guided method on H and N cancer patient data takes 8 seconds/iteration, about 7.5 times faster than direct 3D method (60 seconds/iteration), and it needs fewer optimization iterations (30 iterations vs 50 iterations). Conclusion: The proposed surface-contour DIR method can substantially improve both the accuracy and the speed of reconstructing volumetric images, which is helpful

  13. A coarse-to-fine automatic and robust registration method for multi-source remote sensing images based on Harris and phase information

    NASA Astrophysics Data System (ADS)

    Li, Haichao; Man, Yiyun

    2015-10-01

    The image phase coherences (PCs) remain invariant when brightness and contrast changes. A new method of remote sensing image registration is proposed. PCs are firstly extracted from the reference image and the input image. In order to improve the registration efficiency, in the first step the PCs are firstly down-sampled using Gaussian pyramid method, and the coarse translation parameters are calculated using phase correlation. In the second step, Harris corners are detected from the two images, and normalized cross-correlation (NCC) function based on PCs is used to find the corresponding matching corners of the two images, and then obtain parameters of an alignment transform model. Experiments have demonstrated that the coarse-to-fine method can be successfully applied to multi-source images registration.

  14. Hierarchical causality explorer: making complemental use of 3D/2D visualizations

    NASA Astrophysics Data System (ADS)

    Azuma, Shizuka; Fujishiro, Issei; Horii, Hideyuki

    2006-01-01

    Hierarchical causality relationships reside ubiquitously in the reality. Since the relationships take intricate forms with two kinds of links - hierarchical abstraction and causal association, there exists no single visualization style that allows the user to comprehend them effectively. This paper introduces a novel information visualization framework which can change existing 3D and 2D display styles interactively according to the user's visual analysis demands. The two visualization styles play a complementary role, and the change in the style relies on morphing so as to maintain the user's cognitive map. Based on this framework, we have developed a general-purpose prototype system, which provides the user with an enriched set of functions not only for supporting fundamental information seeking, but bridging analytic gaps to accomplishing high-level analytic tasks such as knowledge discovery and decision making. The effectiveness of the system is illustrated with an application to the analysis of a nuclear-hazard cover-up problem.

  15. Simulating HFIR Core Thermal Hydraulics Using 3D-2D Model Coupling

    SciTech Connect

    Travis, Adam R; Freels, James D; Ekici, Kivanc

    2013-01-01

    A model utilizing interdimensional variable coupling is presented for simulating the thermal hydraulic interactions of the High Flux Isotope Reactor (HFIR) core at Oak Ridge National Laboratory (ORNL). The model s domain consists of a single, explicitly represented three-dimensional fuel plate and a simplified two-dimensional coolant channel slice. In simplifying the coolant channel, and thus the number of mesh points in which the Navier-Stokes equations must be solved, the computational cost and solution time are both greatly reduced. In order for the reduced-dimension coolant channel to interact with the explicitly represented fuel plate, however, interdimensional variable coupling must be enacted along all shared boundaries. The primary focus of this paper is in detailing the collection, storage, passage, and application of variables across this interdimensional interface. Comparisons are made showing the general speed-up associated with this simplified coupled model.

  16. Preliminary experience with a novel method of three-dimensional co-registration of prostate cancer digital histology and in vivo multiparametric MRI

    PubMed Central

    Orczyk, C.; Rusinek, H.; Rosenkrantz, A.B.; Mikheev, A.; Deng, F.-M.; Melamed, J.; Taneja, S.S.

    2013-01-01

    AIM To assess a novel method of three-dimensional (3D) co-registration of prostate cancer digital histology and in-vivo multiparametric magnetic resonance imaging (mpMRI) image sets for clinical usefulness. MATERIAL AND METHODS A software platform was developed to achieve 3D co- registration. This software was prospectively applied to three patients who underwent radical prostatectomy. Data comprised in-vivo mpMRI [T2-weighted, dynamic contrast-enhanced weighted images (DCE); apparent diffusion coefficient (ADC)], ex-vivo T2-weighted imaging, 3D-rebuilt pathological specimen, and digital histology. Internal landmarks from zonal anatomy served as reference points for assessing co-registration accuracy and precision. RESULTS Applying a method of deformable transformation based on 22 internal landmarks, a 1.6 mm accuracy was reached to align T2-weighted images and the 3D-rebuilt pathological specimen, an improvement over rigid transformation of 32% (p = 0.003). The 22 zonal anatomy landmarks were more accurately mapped using deformable transformation than rigid transformation (p = 0.0008). An automatic method based on mutual information, enabled automation of the process and to include perfusion and diffusion MRI images. Evaluation of co-registration accuracy using the volume overlap index (Dice index) met clinically relevant requirements, ranging from 0.81–0.96 for sequences tested. Ex-vivo images of the specimen did not significantly improve co-registration accuracy. CONCLUSION This preliminary analysis suggests that deformable transformation based on zonal anatomy landmarks is accurate in the co-registration of mpMRI and histology. Including diffusion and perfusion sequences in the same 3D space as histology is essential further clinical information. The ability to localize cancer in 3D space may improve targeting for image-guided biopsy, focal therapy, and disease quantification in surveillance protocols. PMID:23993149

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

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  18. A registration-based segmentation method with application to adiposity analysis of mice microCT images

    NASA Astrophysics Data System (ADS)

    Bai, Bing; Joshi, Anand; Brandhorst, Sebastian; Longo, Valter D.; Conti, Peter S.; Leahy, Richard M.

    2014-04-01

    Obesity is a global health problem, particularly in the U.S. where one third of adults are obese. A reliable and accurate method of quantifying obesity is necessary. Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) are two measures of obesity that reflect different associated health risks, but accurate measurements in humans or rodent models are difficult. In this paper we present an automatic, registration-based segmentation method for mouse adiposity studies using microCT images. We co-register the subject CT image and a mouse CT atlas. Our method is based on surface matching of the microCT image and an atlas. Surface-based elastic volume warping is used to match the internal anatomy. We acquired a whole body scan of a C57BL6/J mouse injected with contrast agent using microCT and created a whole body mouse atlas by manually delineate the boundaries of the mouse and major organs. For method verification we scanned a C57BL6/J mouse from the base of the skull to the distal tibia. We registered the obtained mouse CT image to our atlas. Preliminary results show that we can warp the atlas image to match the posture and shape of the subject CT image, which has significant differences from the atlas. We plan to use this software tool in longitudinal obesity studies using mouse models.

  19. Computed tomography calcium score scan for attenuation correction of N-13 ammonia cardiac positron emission tomography: effect of respiratory phase and registration method.

    PubMed

    Zaidi, Habib; Nkoulou, Rene; Bond, Sarah; Baskin, Aylin; Schindler, Thomas; Ratib, Osman; Declerck, Jerome

    2013-08-01

    The use of coronary calcium scoring (CaScCT) for attenuation correction (AC) of (13)N-ammonia PET/CT studies (NH3) is still being debated. We compare standard ACCT to CaScCT using various respiratory phases and co-registration methods for AC. Forty-one patients underwent a stress/rest NH3. Standard ACCT scans and CaScCT acquired during inspiration (CaScCTinsp, 26 patients) or expiration (CaScCTexp, 15 patients) were used to correct PET data for photon attenuation. Resulting images were compared using Pearson's correlation and Bland-Altman (BA) limits of agreement (LA) on segmental relative and absolute coronary blood flow (CBF) using both manual and automatic co-registration methods (rigid-body and deformable). For relative perfusion, CaScCTexp correlates better than CaScCTinsp with ACCT when using manual co-registration (r = 0.870; P < 0.001 and r = 0.732; P < 0.001, respectively). Automatic co-registration provides the best correlation between CaScCTexp and ACCT for relative perfusion (r = 0.956; P < 0.001). Both CaScCTinsp and CaScCTexp yielded excellent correlations with ACCT for CBF when using manual co-registration (r = 0.918; P < 0.001; BA mean bias 0.05 ml/min/g; LA: -0.42 to +0.3 ml/min/g and r = 0.97; P < 0.001; BA mean bias 0.1 ml/min/g; LA: -0.65 to +0.5 ml/min/g, respectively). The use of CaScCTexp and deformable co-registration is best suited for AC to quantify relative perfusion and CBF enabling substantial radiation dose reduction. PMID:23504215

  20. SU-E-J-114: A Practical Hybrid Method for Improving the Quality of CT-CBCT Deformable Image Registration for Head and Neck Radiotherapy

    SciTech Connect

    Liu, C; Kumarasiri, A; Chetvertkov, M; Gordon, J; Chetty, I; Siddiqui, F; Kim, J

    2015-06-15

    Purpose: Accurate deformable image registration (DIR) between CT and CBCT in H&N is challenging. In this study, we propose a practical hybrid method that uses not only the pixel intensities but also organ physical properties, structure volume of interest (VOI), and interactive local registrations. Methods: Five oropharyngeal cancer patients were selected retrospectively. For each patient, the planning CT was registered to the last fraction CBCT, where the anatomy difference was largest. A three step registration strategy was tested; Step1) DIR using pixel intensity only, Step2) DIR with additional use of structure VOI and rigidity penalty, and Step3) interactive local correction. For Step1, a public-domain open-source DIR algorithm was used (cubic B-spline, mutual information, steepest gradient optimization, and 4-level multi-resolution). For Step2, rigidity penalty was applied on bony anatomies and brain, and a structure VOI was used to handle the body truncation such as the shoulder cut-off on CBCT. Finally, in Step3, the registrations were reviewed on our in-house developed software and the erroneous areas were corrected via a local registration using level-set motion algorithm. Results: After Step1, there were considerable amount of registration errors in soft tissues and unrealistic stretching in the posterior to the neck and near the shoulder due to body truncation. The brain was also found deformed to a measurable extent near the superior border of CBCT. Such errors could be effectively removed by using a structure VOI and rigidity penalty. The rest of the local soft tissue error could be corrected using the interactive software tool. The estimated interactive correction time was approximately 5 minutes. Conclusion: The DIR using only the image pixel intensity was vulnerable to noise and body truncation. A corrective action was inevitable to achieve good quality of registrations. We found the proposed three-step hybrid method efficient and practical for CT

  1. Accuracy assessment of a marker-free method for registration of CT and stereo images applied in image-guided implantology: a phantom study.

    PubMed

    Mohagheghi, Saeed; Ahmadian, Alireza; Yaghoobee, Siamak

    2014-12-01

    To assess the accuracy of a proposed marker-free registration method as opposed to the conventional marker-based method using an image-guided dental system, and investigating the best configurations of anatomical landmarks for various surgical fields in a phantom study, a CT-compatible dental phantom consisting of implanted targets was used. Two marker-free registration methods were evaluated, first using dental anatomical landmarks and second, using a reference marker tool. Six implanted markers, distributed in the inner space of the phantom were used as the targets; the values of target registration error (TRE) for each target were measured and compared with the marker-based method. Then, the effects of different landmark configurations on TRE values, measured using the Parsiss IV Guided Navigation system (Parsiss, Tehran, Iran), were investigated to find the best landmark arrangement for reaching the minimum registration error in each target region. It was proved that marker-free registration can be as precise as the marker-based method. This has a great impact on image-guided implantology systems whereby the drawbacks of fiducial markers for patient and surgeon are removed. It was also shown that smaller values of TRE could be achieved by using appropriate landmark configurations and moving the center of the landmark set closer to the surgery target. Other common factors would not necessarily decrease the TRE value so the conventional rules accepted in the clinical community about the ways to reduce TRE should be adapted to the selected field of dental surgery. PMID:25441868

  2. A novel coarse-to-fine method for registration of multispectral images

    NASA Astrophysics Data System (ADS)

    Jin, Hongbin; Fan, Chunxiao; Li, Yong; Xu, Liangpeng

    2016-07-01

    Due to non-linear intensity changes between multispectral images, the existed descriptors often yield low matching performance. In order to build reliable keypoint mappings on multispectral images, a novel coarse-to-fine method is designed using projective transformation and the information of edge overlap. The method consists of a coarse process and a fine-tuning process. In the coarse process, initial keypoint mappings are built with the descriptors associated with keypoints and the relative distance constraints are employed on them to remove outliers. In the fine-tuning process, the edge overlap information is utilized as similarity metric and an iterative framework is applied to search correct keypoint mappings. The performance of the proposed is investigated with keypoints extracted by speeded-up robust features. The experiment results show that the proposed method can build more reliable keypoint mappings on multispectral images than existed methods.

  3. SU-C-17A-03: Evaluation of Deformable Image Registration Methods Between MRI and CT for Prostate Cancer Radiotherapy

    SciTech Connect

    Wen, N; Glide-Hurst, C; Zhong, H; Chin, K; Kumarasiri, A; Liu, C; Liu, M; Siddiqui, S

    2014-06-15

    Purpose: We evaluated the performance of two commercially available and one open source B-Spline deformable image registration (DIR) algorithms between T2-weighted MRI and treatment planning CT using the DICE indices. Methods: CT simulation (CT-SIM) and MR simulation (MR-SIM) for four prostate cancer patients were conducted on the same day using the same setup and immobilization devices. CT images (120 kVp, 500 mAs, voxel size = 1.1x1.1x3.0 mm3) were acquired using an open-bore CT scanner. T2-weighted Turbo Spine Echo (T2W-TSE) images (TE/TR/α = 80/4560 ms/90°, voxel size = 0.7×0.7×2.5 mm3) were scanned on a 1.0T high field open MR-SIM. Prostates, seminal vesicles, rectum and bladders were delineated on both T2W-TSE and CT images by the attending physician. T2W-TSE images were registered to CT images using three DIR algorithms, SmartAdapt (Varian), Velocity AI (Velocity) and Elastix (Klein et al 2010) and contours were propagated. DIR results were evaluated quantitatively or qualitatively by image comparison and calculating organ DICE indices. Results: Significant differences in the contours of prostate and seminal vesicles were observed between MR and CT. On average, volume changes of the propagated contours were 5%, 2%, 160% and 8% for the prostate, seminal vesicles, bladder and rectum respectively. Corresponding mean DICE indices were 0.7, 0.5, 0.8, and 0.7. The intraclass correlation coefficient (ICC) was 0.9 among three algorithms for the Dice indices. Conclusion: Three DIR algorithms for CT/MR registration yielded similar results for organ propagation. Due to the different soft tissue contrasts between MRI and CT, organ delineation of prostate and SVs varied significantly, thus efforts to develop other DIR evaluation metrics are warranted. Conflict of interest: Submitting institution has research agreements with Varian Medical System and Philips Healthcare.

  4. Robust registration of longitudinal spine CT.

    PubMed

    Glocker, Ben; Zikic, Darko; Haynor, David R

    2014-01-01

    Accurate and reliable registration of longitudinal spine images is essential for assessment of disease progression and surgical outcome. Implementing a fully automatic and robust registration for clinical use, however, is challenging since standard registration techniques often fail due to poor initial alignment. The main causes of registration failure are the small overlap between scans which focus on different parts of the spine and/or substantial change in shape (e.g. after correction of abnormal curvature) and appearance (e.g. due to surgical implants). To overcome these issues we propose a registration approach which incorporates estimates of vertebrae locations obtained from a learning-based classification method. These location priors are used to initialize the registration and to provide semantic information within the optimization process. Quantitative evaluation on a database of 93 patients with a total of 276 registrations on longitudinal spine CT demonstrate that our registration method significantly reduces the number of failure cases. PMID:25333125

  5. Method for nanoscale spatial registration of scanning probes with substrates and surfaces

    NASA Technical Reports Server (NTRS)

    Wade, Lawrence A. (Inventor)

    2010-01-01

    Embodiments in accordance with the present invention relate to methods and apparatuses for aligning a scanning probe used to pattern a substrate, by comparing the position of the probe to a reference location or spot on the substrate. A first light beam is focused on a surface of the substrate as a spatial reference point. A second light beam then illuminates the scanning probe being used for patterning. An optical microscope images both the focused light beam, and a diffraction pattern, shadow, or light backscattered by the illuminated scanning probe tip of a scanning probe microscope (SPM), which is typically the tip of the scanning probe on an atomic force microscope (AFM). Alignment of the scanning probe tip relative to the mark is then determined by visual observation of the microscope image. This alignment process may be repeated to allow for modification or changing of the scanning probe microscope tip.

  6. An automated, fast and accurate registration method to link stranded seeds in permanent prostate implants.

    PubMed

    Westendorp, Hendrik; Nuver, Tonnis T; Moerland, Marinus A; Minken, André W

    2015-10-21

    The geometry of a permanent prostate implant varies over time. Seeds can migrate and edema of the prostate affects the position of seeds. Seed movements directly influence dosimetry which relates to treatment quality. We present a method that tracks all individual seeds over time allowing quantification of seed movements. This linking procedure was tested on transrectal ultrasound (TRUS) and cone-beam CT (CBCT) datasets of 699 patients. These datasets were acquired intraoperatively during a dynamic implantation procedure, that combines both imaging modalities. The procedure was subdivided in four automatic linking steps. (I) The Hungarian Algorithm was applied to initially link seeds in CBCT and the corresponding TRUS datasets. (II) Strands were identified and optimized based on curvature and linefits: non optimal links were removed. (III) The positions of unlinked seeds were reviewed and were linked to incomplete strands if within curvature- and distance-thresholds. (IV) Finally, seeds close to strands were linked, also if the curvature-threshold was violated. After linking the seeds an affine transformation was applied. The procedure was repeated until the results were stable or the 6th iteration ended. All results were visually reviewed for mismatches and uncertainties. Eleven implants showed a mismatch and in 12 cases an uncertainty was identified. On average the linking procedure took 42 ms per case. This accurate and fast method has the potential to be used for other time spans, like Day 30, and other imaging modalities. It can potentially be used during a dynamic implantation procedure to faster and better evaluate the quality of the permanent prostate implant. PMID:26439900

  7. An automated, fast and accurate registration method to link stranded seeds in permanent prostate implants

    NASA Astrophysics Data System (ADS)

    Westendorp, Hendrik; Nuver, Tonnis T.; Moerland, Marinus A.; Minken, André W.

    2015-10-01

    The geometry of a permanent prostate implant varies over time. Seeds can migrate and edema of the prostate affects the position of seeds. Seed movements directly influence dosimetry which relates to treatment quality. We present a method that tracks all individual seeds over time allowing quantification of seed movements. This linking procedure was tested on transrectal ultrasound (TRUS) and cone-beam CT (CBCT) datasets of 699 patients. These datasets were acquired intraoperatively during a dynamic implantation procedure, that combines both imaging modalities. The procedure was subdivided in four automatic linking steps. (I) The Hungarian Algorithm was applied to initially link seeds in CBCT and the corresponding TRUS datasets. (II) Strands were identified and optimized based on curvature and linefits: non optimal links were removed. (III) The positions of unlinked seeds were reviewed and were linked to incomplete strands if within curvature- and distance-thresholds. (IV) Finally, seeds close to strands were linked, also if the curvature-threshold was violated. After linking the seeds an affine transformation was applied. The procedure was repeated until the results were stable or the 6th iteration ended. All results were visually reviewed for mismatches and uncertainties. Eleven implants showed a mismatch and in 12 cases an uncertainty was identified. On average the linking procedure took 42 ms per case. This accurate and fast method has the potential to be used for other time spans, like Day 30, and other imaging modalities. It can potentially be used during a dynamic implantation procedure to faster and better evaluate the quality of the permanent prostate implant.

  8. A Method For Simultaneous Registration Of Motion And Electromyography During Walking

    NASA Astrophysics Data System (ADS)

    Giith, V.; Abbink, F.; Heinrichs, W.; Theysohn, H.

    1980-07-01

    The points the movements of which are to be registered are marked by little light sensitive photoamplifiers. These are periodically (50 times per second) exposed to a VÖshaped bright figure projected by a rotating mirror. The pattern of the resulting electrical impulses is analysed by a computer controlled fast digital time counting apparatus with a clock of 100 ns. Is this way we get every 20 ms the respective position of the marked points (up to nine). The results of this method are simular to the well known photographic chronocyclography with the advantage, however, that the momentary positions of the points are calculated on line (accuracy ± 2 mm). In the intervals between the sweeps of the light-figure the computer picks up 8 lines of analogue data, actually the electromyogram of eight different muscles, and stores them, together with the optical data on digital magnetic tape for further evaluation. After the investigation the obtained data are analysed in the following way : 1) Plotting several parameters of positions (angles, c.g.) together with the electromyogram ver-sus time during one step of walking. 2) Calculating the correlation between the patterns of electrical activity of different muscles. 3) Comparison of the results of 1) and 2) between healthy persons and handicapped persons (C.P.), scoliosis, desease of spine, hip and pelvis, etc...).

  9. The investigation of moving dunes over Mars using very high resolution topography and sub pixel co-registration method.

    NASA Astrophysics Data System (ADS)

    Kim, J.; Baik, H.; Seol, H.

    2015-12-01

    Although the origins and processes of Martian aeolian features, especially dunes, have not been fully identified yet, it has been better understood by the orbital observation method which has led to the identification of Martian dune migration such as a case in Nili Patera (Bridges, 2012), and the numerical model employing advanced computational fluid dynamics. Specifically, the recent introduction of very high-resolution image products, such as 25 cm-resolution HiRISE imagery and its precise photogrammetric processor, allows us to trace the estimated, although tiny, dune migration over the Martian surface. In this study, we attempted to improve the accuracy of active dune migration measurements by 1) the introduction of very high resolution ortho images and stereo analysis based on the hierarchical geodetic control (Kim and Muller, 2009) for better initial point settings; and 2) the improved sub-pixel co-registration algorithms using optical flow with a refinement stage based on a least squares correlation conducted on a pyramidal processor. Consequently, this scheme not only measured Martian dune migration more precisely, but it also achieved the extension of 3D observations combining stereo analysis and photoclinometry. The established algorithms have been tested using the HiRISE time series images over several dune fields, such as the Kaiser, Procter, and Rabe craters, which were reported by the Mars Global Digital Dune Database (Hayward et al., 2013). The detected dune migrations were significantly larger than previously reported values. The outcomes in our study will be demonstrated with the quantified values in 2D and volumetric direction. In the future, the method will be further applied to the dune fields in the Mars Global dune database comprehensively and can be compared with the improved General Circulation Model and the numerical simulation.

  10. [The new technologies for the intraoperative registration of the electrically evoked compound action potentials of the acoustical nerve by means of the neural response telemetry method].

    PubMed

    Bakhshinian, V V; Fedoseev, V I; Tavartkiladze, G A

    2015-01-01

    The present article reports the results of a clinical study of the new wireless device CR120 designed for the intraoperative registration of electrode resistance and the electrically evoked compound action potential (EAP) of the acoustical nerve by means of neural response telemetry. The study has demonstrated the high effectiveness of the application of the new wireless device in clinical practice. It was shown that the registration of electrically evoked compound action potential with the help of the CR120 Intraoperative Remote Assistant took 22% less time than by the conventional method (p<0.001). Moreover, the trial revealed the strong correlation between the threshold EAP values recorded with the use of the new device and by the classical method. PMID:26288202

  11. Registration of video sequences from multiple sensors

    NASA Technical Reports Server (NTRS)

    Sharma, Ravi K.; Pavel, Misha

    1997-01-01

    In this paper, we describe an approach for registration of video sequences from a suite of multiple sensors including television, infrared and radar. Video sequences generated by these sensors may contain abrupt changes in local contrast and inconsistent image features, which pose additional difficulties for registration. Our approach to registration addresses the difficulties caused by using multiple sensors. We use a representation for registration that is invariant to local contrast changes, followed by smoothing of the resulting error measure used for registration, for robust estimation of registration parameters. We use an iterative procedure to reduce the effect of inconsistent features. Finally, we describe a method that uses same-sensor registration to aide in performing registration of sequences of video frames across multiple sensors.

  12. Comparisons of surface vs. volumetric model-based registration methods using single-plane vs. bi-plane fluoroscopy in measuring spinal kinematics.

    PubMed

    Lin, Cheng-Chung; Lu, Tung-Wu; Wang, Ting-Ming; Hsu, Chao-Yu; Shih, Ting-Fang

    2014-02-01

    Several 2D-to-3D image registration methods are available for measuring 3D vertebral motion but their performance has not been evaluated under the same experimental protocol. In this study, four major types of fluoroscopy-to-CT registration methods, with different use of surface vs. volumetric models, and single-plane vs. bi-plane fluoroscopy, were evaluated: STS (surface, single-plane), VTS (volumetric, single-plane), STB (surface, bi-plane) and VTB (volumetric, bi-plane). Two similarity measures were used: 'Contour Difference' for STS and STB and 'Weighted Edge-Matching Score' for VTS and VTB. Two cadaveric porcine cervical spines positioned in a box filled with paraffin and embedded with four radiopaque markers were CT scanned to obtain vertebral models and marker coordinates, and imaged at ten static positions using bi-plane fluoroscopy for subsequent registrations using different methods. The registered vertebral poses were compared to the gold standard poses defined by the marker positions determined using CT and Roentgen stereophotogrammetry analysis. The VTB was found to have the highest precision (translation: 0.4mm; rotation: 0.3°), comparable with the VTS in rotations (0.3°), and the STB in translations (0.6mm). The STS had the lowest precision (translation: 4.1mm; rotation: 2.1°). PMID:24011956

  13. A hybrid method for reliable registration of digitally reconstructed radiographs and kV x-ray images for image-guided radiation therapy for prostate cancer

    NASA Astrophysics Data System (ADS)

    Song, Yulin; Mueller, Boris; Chan, Maria F.; Sim, Sang E.; Mychalczak, Borys; Huang, Xiaolei

    2008-03-01

    Prostate cancer is the most common tumor site treated with intensity modulated radiation therapy (IMRT). However, due to patient and organ motions, treatment-induced physiological changes, and different daily filling in the bladder and rectum, the position of the prostate in relation to the fixed pelvic bone can change significantly. Without a reliable guiding technique, this could result in underdosing the target and overdosing the critical organs. Therefore, image-guided localization of the prostate must be performed prior to each treatment, which led to the development of a new radiation treatment modality, the image-guided radiation therapy (IGRT). One form of IGRT is to implant three gold seed markers into the prostate gland to serve as a fixed reference system. Daily patient setup verification is performed by using the gold seed markers-based image registration rather than the commonly used bony landmarks-based approach. In this paper, we present an efficient and automated method for registering digitally reconstructed radiographs (DRR) and kV X-ray images of the prostate with high accuracy using a hybrid method. Our technique relies on both internal fiducial markers (i.e. gold seed markers) implanted into the prostate and a robust, hybrid 2D registration method using a salient-region based image registration technique. The registration procedure consists of several novel steps. Validation experiments were performed to register DRR and kV X-ray images in anterior-posterior (AP) or lateral views and the results were reviewed by experienced radiation oncology physicists.

  14. MO-C-17A-11: A Segmentation and Point Matching Enhanced Deformable Image Registration Method for Dose Accumulation Between HDR CT Images

    SciTech Connect

    Zhen, X; Chen, H; Zhou, L; Yan, H; Jiang, S; Jia, X; Gu, X; Mell, L; Yashar, C; Cervino, L

    2014-06-15

    Purpose: To propose and validate a novel and accurate deformable image registration (DIR) scheme to facilitate dose accumulation among treatment fractions of high-dose-rate (HDR) gynecological brachytherapy. Method: We have developed a method to adapt DIR algorithms to gynecologic anatomies with HDR applicators by incorporating a segmentation step and a point-matching step into an existing DIR framework. In the segmentation step, random walks algorithm is used to accurately segment and remove the applicator region (AR) in the HDR CT image. A semi-automatic seed point generation approach is developed to obtain the incremented foreground and background point sets to feed the random walks algorithm. In the subsequent point-matching step, a feature-based thin-plate spline-robust point matching (TPS-RPM) algorithm is employed for AR surface point matching. With the resulting mapping, a DVF characteristic of the deformation between the two AR surfaces is generated by B-spline approximation, which serves as the initial DVF for the following Demons DIR between the two AR-free HDR CT images. Finally, the calculated DVF via Demons combined with the initial one serve as the final DVF to map doses between HDR fractions. Results: The segmentation and registration accuracy are quantitatively assessed by nine clinical HDR cases from three gynecological cancer patients. The quantitative results as well as the visual inspection of the DIR indicate that our proposed method can suppress the interference of the applicator with the DIR algorithm, and accurately register HDR CT images as well as deform and add interfractional HDR doses. Conclusions: We have developed a novel and robust DIR scheme that can perform registration between HDR gynecological CT images and yield accurate registration results. This new DIR scheme has potential for accurate interfractional HDR dose accumulation. This work is supported in part by the National Natural ScienceFoundation of China (no 30970866 and no

  15. Prostate CT segmentation method based on nonrigid registration in ultrasound-guided CT-based HDR prostate brachytherapy

    SciTech Connect

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

    2014-11-01

    Purpose: The technological advances in real-time ultrasound image guidance for high-dose-rate (HDR) prostate brachytherapy have placed this treatment modality at the forefront of innovation in cancer radiotherapy. Prostate HDR treatment often involves placing the HDR catheters (needles) into the prostate gland under the transrectal ultrasound (TRUS) guidance, then generating a radiation treatment plan based on CT prostate images, and subsequently delivering high dose of radiation through these catheters. The main challenge for this HDR procedure is to accurately segment the prostate volume in the CT images for the radiation treatment planning. In this study, the authors propose a novel approach that integrates the prostate volume from 3D TRUS images into the treatment planning CT images to provide an accurate prostate delineation for prostate HDR treatment. Methods: The authors’ approach requires acquisition of 3D TRUS prostate images in the operating room right after the HDR catheters are inserted, which takes 1–3 min. These TRUS images are used to create prostate contours. The HDR catheters are reconstructed from the intraoperative TRUS and postoperative CT images, and subsequently used as landmarks for the TRUS–CT image fusion. After TRUS–CT fusion, the TRUS-based prostate volume is deformed to the CT images for treatment planning. This method was first validated with a prostate-phantom study. In addition, a pilot study of ten patients undergoing HDR prostate brachytherapy was conducted to test its clinical feasibility. The accuracy of their approach was assessed through the locations of three implanted fiducial (gold) markers, as well as T2-weighted MR prostate images of patients. Results: For the phantom study, the target registration error (TRE) of gold-markers was 0.41 ± 0.11 mm. For the ten patients, the TRE of gold markers was 1.18 ± 0.26 mm; the prostate volume difference between the authors’ approach and the MRI-based volume was 7.28% ± 0

  16. Earth Science Imagery Registration

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; Morisette, Jeffrey; Cole-Rhodes, Arlene; Johnson, Kisha; Netanyahu, Nathan S.; Eastman, Roger; Stone, Harold; Zavorin, Ilya

    2003-01-01

    The study of global environmental changes involves the comparison, fusion, and integration of multiple types of remotely-sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, as well as for the validation of new instruments or for new data analysis. Furthermore, future multiple satellite missions will include many different sensors carried on separate platforms, and the amount of remote sensing data to be combined is increasing tremendously. For all of these applications, the first required step is fast and automatic image registration, and as this need for automating registration techniques is being recognized, it becomes necessary to survey all the registration methods which may be applicable to Earth and space science problems and to evaluate their performances on a large variety of existing remote sensing data as well as on simulated data of soon-to-be-flown instruments. In this paper we present one of the first steps toward such an exhaustive quantitative evaluation. First, the different components of image registration algorithms are reviewed, and different choices for each of these components are described. Then, the results of the evaluation of the corresponding algorithms combining these components are presented o n several datasets. The algorithms are based on gray levels or wavelet features and compute rigid transformations (including scale, rotation, and shifts). Test datasets include synthetic data as well as data acquired over several EOS Land Validation Core Sites with the IKONOS and the Landsat-7 sensors.

  17. Intervertebral anticollision constraints improve out-of-plane translation accuracy of a single-plane fluoroscopy-to-CT registration method for measuring spinal motion

    SciTech Connect

    Lin, Cheng-Chung; Tsai, Tsung-Yuan; Hsu, Shih-Jung; Lu, Tung-Wu; Shih, Ting-Fang; Wang, Ting-Ming

    2013-03-15

    Purpose: The study aimed to propose a new single-plane fluoroscopy-to-CT registration method integrated with intervertebral anticollision constraints for measuring three-dimensional (3D) intervertebral kinematics of the spine; and to evaluate the performance of the method without anticollision and with three variations of the anticollision constraints via an in vitro experiment. Methods: The proposed fluoroscopy-to-CT registration approach, called the weighted edge-matching with anticollision (WEMAC) method, was based on the integration of geometrical anticollision constraints for adjacent vertebrae and the weighted edge-matching score (WEMS) method that matched the digitally reconstructed radiographs of the CT models of the vertebrae and the measured single-plane fluoroscopy images. Three variations of the anticollision constraints, namely, T-DOF, R-DOF, and A-DOF methods, were proposed. An in vitro experiment using four porcine cervical spines in different postures was performed to evaluate the performance of the WEMS and the WEMAC methods. Results: The WEMS method gave high precision and small bias in all components for both vertebral pose and intervertebral pose measurements, except for relatively large errors for the out-of-plane translation component. The WEMAC method successfully reduced the out-of-plane translation errors for intervertebral kinematic measurements while keeping the measurement accuracies for the other five degrees of freedom (DOF) more or less unaltered. The means (standard deviations) of the out-of-plane translational errors were less than -0.5 (0.6) and -0.3 (0.8) mm for the T-DOF method and the R-DOF method, respectively. Conclusions: The proposed single-plane fluoroscopy-to-CT registration method reduced the out-of-plane translation errors for intervertebral kinematic measurements while keeping the measurement accuracies for the other five DOF more or less unaltered. With the submillimeter and subdegree accuracy, the WEMAC method was

  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. A survey of medical image registration - under review.

    PubMed

    Viergever, Max A; Maintz, J B Antoine; Klein, Stefan; Murphy, Keelin; Staring, Marius; Pluim, Josien P W

    2016-10-01

    A retrospective view on the past two decades of the field of medical image registration is presented, guided by the article "A survey of medical image registration" (Maintz and Viergever, 1998). It shows that the classification of the field introduced in that article is still usable, although some modifications to do justice to advances in the field would be due. The main changes over the last twenty years are the shift from extrinsic to intrinsic registration, the primacy of intensity-based registration, the breakthrough of nonlinear registration, the progress of inter-subject registration, and the availability of generic image registration software packages. Two problems that were called urgent already 20 years ago, are even more urgent nowadays: Validation of registration methods, and translation of results of image registration research to clinical practice. It may be concluded that the field of medical image registration has evolved, but still is in need of further development in various aspects. PMID:27427472

  20. A volumetric model-based 2D to 3D registration method for measuring kinematics of natural knees with single-plane fluoroscopy

    SciTech Connect

    Tsai, Tsung-Yuan; Lu, Tung-Wu; Chen, Chung-Ming; Kuo, Mei-Ying; Hsu, Horng-Chaung

    2010-03-15

    Purpose: Accurate measurement of the three-dimensional (3D) rigid body and surface kinematics of the natural human knee is essential for many clinical applications. Existing techniques are limited either in their accuracy or lack more realistic experimental evaluation of the measurement errors. The purposes of the study were to develop a volumetric model-based 2D to 3D registration method, called the weighted edge-matching score (WEMS) method, for measuring natural knee kinematics with single-plane fluoroscopy to determine experimentally the measurement errors and to compare its performance with that of pattern intensity (PI) and gradient difference (GD) methods. Methods: The WEMS method gives higher priority to matching of longer edges of the digitally reconstructed radiograph and fluoroscopic images. The measurement errors of the methods were evaluated based on a human cadaveric knee at 11 flexion positions. Results: The accuracy of the WEMS method was determined experimentally to be less than 0.77 mm for the in-plane translations, 3.06 mm for out-of-plane translation, and 1.13 deg. for all rotations, which is better than that of the PI and GD methods. Conclusions: A new volumetric model-based 2D to 3D registration method has been developed for measuring 3D in vivo kinematics of natural knee joints with single-plane fluoroscopy. With the equipment used in the current study, the accuracy of the WEMS method is considered acceptable for the measurement of the 3D kinematics of the natural knee in clinical applications.

  1. DR-BUDDI (Diffeomorphic Registration for Blip-Up blip-Down Diffusion Imaging) Method for Correcting Echo Planar Imaging Distortions

    PubMed Central

    Irfanoglu, M. Okan; Modi, Pooja; Nayak, Amritha; Hutchinson, Elizabeth B.; Sarlls, Joelle; Pierpaoli, Carlo

    2014-01-01

    We propose an echo planar imaging (EPI) distortion correction method (DR-BUDDI), specialized for diffusion MRI, which uses data acquired twice with reversed phase encoding directions, often referred to as blip-up blip-down acquisitions. DR-BUDDI can incorporate information from an undistorted structural MRI and also use diffusion-weighted images (DWI) to guide the registration, improving the quality of the registration in the presence of large deformations and in white matter regions. DR-BUDDI does not require the transformations for correcting blip-up and blip-down images to be the exact inverse of each other. Imposing the theoretical “blip-up blip-down distortion symmetry” may not be appropriate in the presence of common clinical scanning artifacts such as motion, ghosting, Gibbs ringing, vibrations, and low signal-to-noise. The performance of DR-BUDDI is evaluated with several data sets and compared to other existing blip-up blip-down correction approaches. The proposed method is robust and generally outperforms existing approaches. The inclusion of the DWIs in the correction process proves to be very important to obtain a reliable correction of distortions in the brain stem. Methods that do not use DWIs may produce a visually appealing correction of the non-diffusion weighted b = 0 s/mm2 images, but the directionally encoded color maps computed from the tensor reveal an abnormal anatomy of the white matter pathways. PMID:25433212

  2. Bi-modal imaging of atherosclerotic plaques: Automated method for co-registration between fluorescence lifetime imaging and intravascular ultrasound data

    NASA Astrophysics Data System (ADS)

    Gorpas, Dimitris; Fatakdawala, Hussain; Bec, Julien; Ma, Dinglong; Yankelevich, Diego R.; Bishop, John W.; Qi, Jinyi; Marcu, Laura

    2014-03-01

    The risk of atherosclerosis plaque rupture cannot be assessed by the current imaging systems and thus new multi-modal technologies are under investigation. This includes combining a new fluorescence lifetime imaging (FLIm) technique, which is sensitive to plaque biochemical features, with conventional intravascular ultrasound (IVUS), which provides information on plaque morphology. In this study we present an automated method allowing for the co-registration of imaging data acquired based on these two techniques. Intraluminal studies were conducted in ex-vivo segments of human coronaries with a multimodal catheter integrating a commercial IVUS (40 MHz) and a rotational side-viewing fiber based multispectral FLIm system (355 nm excitation, 390+/-20, 452+/-22 and 542+/-25 nm acquisition wavelengths). The proposed method relies on the lumen/intima boundary extraction from the IVUS polar images. Image restoration is applied for the noise reduction and edge enhancement, while gray-scale peak tracing over the A-lines of the IVUS polar images is applied for the lumen boundary extraction. The detection of the guide-wire artifact is used for the angular registration between FLIm and IVUS data, after which the lifetime values can be mapped onto the segmented lumen/intima interface. The segmentation accuracy has been assessed against manual tracings, providing 0.120+/-0.054 mm mean Hausdorff distance. This method makes the bi-modal FLIm and IVUS approach feasible for comprehensive intravascular diagnostic by providing co-registered biochemical and morphological information about atherosclerotic plaques.

  3. Consistency-based rectification of nonrigid registrations

    PubMed Central

    Gass, Tobias; Székely, Gábor; Goksel, Orcun

    2015-01-01

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

  4. Effect of Registration on Cyclical Kinematic Data

    PubMed Central

    Crane, Elizabeth A.; Cassidy, Ruth B.; Rothman, Edward D.; Gerstner, Geoffrey E.

    2010-01-01

    Given growing interest in Functional Data Analysis (FDA) as a useful method for analyzing human movement data, it is critical to understand the effects of standard FDA procedures, including registration, on biomechanical analyses. Registration is used to reduce phase variability between curves while preserving the individual curves shape and amplitude. The application of three methods available to assess registration could benefit those in the biomechanics community using FDA techniques: comparison of mean curves, comparison of average RMS values, and assessment of time-warping functions. Therefore, the present study has two purposes. First, the necessity of registration applied to cyclical data after time normalization is assessed. Second, we illustrate the three methods for evaluating registration effects. Masticatory jaw movements of 22 healthy adults (2 males, 21 females) were tracked while subjects chewed a gum-based pellet for 20 seconds. Motion data were captured at 60 Hz with two gen-locked video cameras. Individual chewing cycles were time normalized and then transformed into functional observations. Registration did not affect mean curves and warping functions were linear. Although registration decreased the RMS, indicating a decrease in inter-subject variability, the difference was not statistically significant. Together these results indicate that registration may not always be necessary for cyclical chewing data. An important contribution of this paper is the illustration of three methods for evaluating registration that are easy to apply and useful for judging whether the extra data manipulation is necessary. PMID:20537335

  5. Deformable medical image registration of pleural cavity for photodynamic therapy by using finite-element based method

    NASA Astrophysics Data System (ADS)

    Penjweini, Rozhin; Kim, Michele M.; Dimofte, Andrea; Finlay, Jarod C.; Zhu, Timothy C.

    2016-03-01

    When the pleural cavity is opened during the surgery portion of pleural photodynamic therapy (PDT) of malignant mesothelioma, the pleural volume will deform. This impacts the delivered dose when using highly conformal treatment techniques. To track the anatomical changes and contour the lung and chest cavity, an infrared camera-based navigation system (NDI) is used during PDT. In the same patient, a series of computed tomography (CT) scans of the lungs are also acquired before the surgery. The reconstructed three-dimensional contours from both NDI and CTs are imported into COMSOL Multiphysics software, where a finite element-based (FEM) deformable image registration is obtained. The CT contour is registered to the corresponding NDI contour by overlapping the center of masses and aligning their orientations. The NDI contour is considered as the reference contour, and the CT contour is used as the target one, which will be deformed. Deformed Geometry model is applied in COMSOL to obtain a deformed target contour. The distortion of the volume at X, Y and Z is mapped to illustrate the transformation of the target contour. The initial assessment shows that FEM-based image deformable registration can fuse images acquired by different modalities. It provides insights into the deformation of anatomical structures along X, Y and Z-axes. The deformed contour has good matches to the reference contour after the dynamic matching process. The resulting three-dimensional deformation map can be used to obtain the locations of other critical anatomic structures, e.g., heart, during surgery.

  6. Deformable medical image registration of pleural cavity for photodynamic therapy by using finite-element based method

    PubMed Central

    Penjweini, Rozhin; Kim, Michele M.; Dimofte, Andrea; Finlay, Jarod C; Zhu, Timothy C.

    2016-01-01

    When the pleural cavity is opened during the surgery portion of pleural photodynamic therapy (PDT) of malignant mesothelioma, the pleural volume will deform. This impacts the delivered dose when using highly conformal treatment techniques. To track the anatomical changes and contour the lung and chest cavity, an infrared camera–based navigation system (NDI) is used during PDT. In the same patient, a series of computed tomography (CT) scans of the lungs are also acquired before the surgery. The reconstructed three-dimensional contours from both NDI and CTs are imported into COMSOL Multiphysics software, where a finite element-based (FEM) deformable image registration is obtained. The CT contour is registered to the corresponding NDI contour by overlapping the center of masses and aligning their orientations. The NDI contour is considered as the reference contour, and the CT contour is used as the target one, which will be deformed. Deformed Geometry model is applied in COMSOL to obtain a deformed target contour. The distortion of the volume at X, Y and Z is mapped to illustrate the transformation of the target contour. The initial assessment shows that FEM-based image deformable registration can fuse images acquired by different modalities. It provides insights into the deformation of anatomical structures along X, Y and Z-axes. The deformed contour has good matches to the reference contour after the dynamic matching process. The resulting three-dimensional deformation map can be used to obtain the locations of other critical anatomic structures, e.g., heart, during surgery. PMID:27053826

  7. A segmentation and point-matching enhanced efficient deformable image registration method for dose accumulation between HDR CT images

    NASA Astrophysics Data System (ADS)

    Zhen, Xin; Chen, Haibin; Yan, Hao; Zhou, Linghong; Mell, Loren K.; Yashar, Catheryn M.; Jiang, Steve; Jia, Xun; Gu, Xuejun; Cervino, Laura

    2015-04-01

    Deformable image registration (DIR) of fractional high-dose-rate (HDR) CT images is challenging due to the presence of applicators in the brachytherapy image. Point-to-point correspondence fails because of the undesired deformation vector fields (DVF) propagated from the applicator region (AR) to the surrounding tissues, which can potentially introduce significant DIR errors in dose mapping. This paper proposes a novel segmentation and point-matching enhanced efficient DIR (named SPEED) scheme to facilitate dose accumulation among HDR treatment fractions. In SPEED, a semi-automatic seed point generation approach is developed to obtain the incremented fore/background point sets to feed the random walks algorithm, which is used to segment and remove the AR, leaving empty AR cavities in the HDR CT images. A feature-based ‘thin-plate-spline robust point matching’ algorithm is then employed for AR cavity surface points matching. With the resulting mapping, a DVF defining on each voxel is estimated by B-spline approximation, which serves as the initial DVF for the subsequent Demons-based DIR between the AR-free HDR CT images. The calculated DVF via Demons combined with the initial one serve as the final DVF to map doses between HDR fractions. The segmentation and registration accuracy are quantitatively assessed by nine clinical HDR cases from three gynecological cancer patients. The quantitative analysis and visual inspection of the DIR results indicate that SPEED can suppress the impact of applicator on DIR, and accurately register HDR CT images as well as deform and add interfractional HDR doses.

  8. A segmentation and point-matching enhanced efficient deformable image registration method for dose accumulation between HDR CT images.

    PubMed

    Zhen, Xin; Chen, Haibin; Yan, Hao; Zhou, Linghong; Mell, Loren K; Yashar, Catheryn M; Jiang, Steve; Jia, Xun; Gu, Xuejun; Cervino, Laura

    2015-04-01

    Deformable image registration (DIR) of fractional high-dose-rate (HDR) CT images is challenging due to the presence of applicators in the brachytherapy image. Point-to-point correspondence fails because of the undesired deformation vector fields (DVF) propagated from the applicator region (AR) to the surrounding tissues, which can potentially introduce significant DIR errors in dose mapping. This paper proposes a novel segmentation and point-matching enhanced efficient DIR (named SPEED) scheme to facilitate dose accumulation among HDR treatment fractions. In SPEED, a semi-automatic seed point generation approach is developed to obtain the incremented fore/background point sets to feed the random walks algorithm, which is used to segment and remove the AR, leaving empty AR cavities in the HDR CT images. A feature-based 'thin-plate-spline robust point matching' algorithm is then employed for AR cavity surface points matching. With the resulting mapping, a DVF defining on each voxel is estimated by B-spline approximation, which serves as the initial DVF for the subsequent Demons-based DIR between the AR-free HDR CT images. The calculated DVF via Demons combined with the initial one serve as the final DVF to map doses between HDR fractions. The segmentation and registration accuracy are quantitatively assessed by nine clinical HDR cases from three gynecological cancer patients. The quantitative analysis and visual inspection of the DIR results indicate that SPEED can suppress the impact of applicator on DIR, and accurately register HDR CT images as well as deform and add interfractional HDR doses. PMID:25790059

  9. SU-E-J-119: What Effect Have the Volume Defined in the Alignment Clipbox for Cervical Cancer Using Automatic Registration Methods for Cone- Beam CT Verification?

    SciTech Connect

    Wang, W; Yang, H; Wang, Y; Jia, H; Xie, Y

    2014-06-01

    Purpose: To investigate the impact of different clipbox volumes with automated registration techniques using commercially available software with on board volumetric imaging(OBI) for treatment verification in cervical cancer patients. Methods: Fifty cervical cancer patients received daily CBCT scans(on-board imaging v1.5 system, Varian Medical Systems) during the first treatment week and weekly thereafter were included this analysis. A total of 450 CBCT scans were registered to the planning CTscan using pelvic clipbox(clipbox-Pelvic) and around PTV clip box(clipbox- PTV). The translations(anterior-posterior, left-right, superior-inferior) and the rotations(yaw, pitch and roll) errors for each matches were recorded. The setup errors and the systematic and random errors for both of the clip-boxes were calculated. Paired Samples t test was used to analysis the differences between clipbox-Pelvic and clipbox-PTV. Results: . The SD of systematic error(σ) was 1.0mm, 2.0mm,3.2mm and 1.9mm,2.3mm, 3.0mm in the AP, LR and SI directions for clipbox-Pelvic and clipbox-PTV, respectively. The average random error(Σ)was 1.7mm, 2.0mm,4.2mm and 1.7mm,3.4mm, 4.4mm in the AP, LR and SI directions for clipbox-Pelvic and clipbox-PTV, respectively. But, only the SI direction was acquired significantly differences between two image registration volumes(p=0.002,p=0.01 for mean and SD). For rotations, the yaw mean/SD and the pitch SD were acquired significantly differences between clipbox-Pelvic and clipbox-PTV. Conclusion: The defined volume for Image registration is important for cervical cancer when 3D/3D match was used. The alignment clipbox can effect the setup errors obtained. Further analysis is need to determine the optimal defined volume to use the image registration in cervical cancer. Conflict of interest: none.

  10. Unbiased rigid registration using transfer functions

    NASA Astrophysics Data System (ADS)

    Hahn, Dieter A.; Hornegger, Joachim; Bautz, Werner; Kuwert, Torsten; Roemer, Wolfgang

    2005-04-01

    The evaluation of tumor growth as regression under therapy is an important clinical issue. Rigid registration of sequentially acquired 3D-images has proven its value for this purpose. Existing approaches to rigid image registration use the whole volume for the estimation of the rigid transform. Non-rigid soft tissue deformation, however, will imply a bias to the registration result, because local deformations cannot be modeled by rigid transforms. Anatomical substructures, like bones or teeth, are not affected by these deformations, but follow a rigid transform. This important observation is incorporated in the proposed registration algorithm. The selection of anatomical substructure is done by manual interaction of medical experts adjusting the transfer function of the volume rendering software. The parameters of the transfer function are used to identify the voxels that are considered for registration. A rigid transform is estimated by a quaternion gradient descent algorithm based on the intensity values of the specified tissue classes. Commonly used voxel intensity measures are adjusted to the modified registration algorithm. The contribution describes the mathematical framework of the proposed registration method and its implementation in a commercial software package. The experimental evaluation includes the discussion of different similarity measures, the comparison of the proposed method to established rigid registration techniques and the evaluation of the efficiency of the new method. We conclude with the discussion of potential medical applications of the proposed registration algorithm.

  11. Scan registration using planar features

    NASA Astrophysics Data System (ADS)

    Previtali, M.; Barazzetti, L.; Brumana, R.; Scaioni, M.

    2014-06-01

    Point cloud acquisition by using laser scanners provides an efficient way for 3D as-built modelling of indoor/outdoor urban environments. In the case of large structures, multiple scans may be required to cover the entire scene and registration is needed to merge them together. In general, the identification of corresponding geometric features among a series of scans can be used to compute the 3D rigid-body transformation useful for the registration of each scan into the reference system of the final point cloud. Different automatic or semi-automatic methods have been developed to this purpose. Several solutions based on artificial targets are available, which however may not be suitable in any situations. Methods based on surface matching (like ICP and LS3D) can be applied if the scans to align have a proper geometry and surface texture. In the case of urban and architectural scenes that present the prevalence of a few basic geometric shapes ("Legoland" scenes) the availability of many planar features is exploited here for registration. The presented technique does not require artificial targets to be added to the scanned scene. In addition, unlike other surface-based techniques (like ICP) the planar feature-based registration technique is not limited to work in a pairwise manner but it can handle the simultaneous alignment of multiple scans. Finally, some applications are presented and discussed to show how this technique can achieve accuracy comparable to a consolidated registration method.

  12. 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

  13. Quantitative characterization of metastatic disease in the spine. Part I. Semiautomated segmentation using atlas-based deformable registration and the level set method

    SciTech Connect

    Hardisty, M.; Gordon, L.; Agarwal, P.; Skrinskas, T.; Whyne, C.

    2007-08-15

    Quantitative assessment of metastatic disease in bone is often considered immeasurable and, as such, patients with skeletal metastases are often excluded from clinical trials. In order to effectively quantify the impact of metastatic tumor involvement in the spine, accurate segmentation of the vertebra is required. Manual segmentation can be accurate but involves extensive and time-consuming user interaction. Potential solutions to automating segmentation of metastatically involved vertebrae are demons deformable image registration and level set methods. The purpose of this study was to develop a semiautomated method to accurately segment tumor-bearing vertebrae using the aforementioned techniques. By maintaining morphology of an atlas, the demons-level set composite algorithm was able to accurately differentiate between trans-cortical tumors and surrounding soft tissue of identical intensity. The algorithm successfully segmented both the vertebral body and trabecular centrum of tumor-involved and healthy vertebrae. This work validates our approach as equivalent in accuracy to an experienced user.

  14. Evaluation of Mail Registration.

    ERIC Educational Resources Information Center

    San Diego Community Coll. District, CA. Research and Planning.

    The San Diego Community College District (SDCCD) implemented mail registration for all continuing students in spring 1986. In fall 1986, a comprehensive evaluation of the registration system was conducted to assess the impact of mail registration on student enrollment, to determine the impact of mailing class schedules to students' homes, to…

  15. Local image registration a comparison for bilateral registration mammography

    NASA Astrophysics Data System (ADS)

    Celaya-Padilaa, José M.; Rodriguez-Rojas, Juan; Trevino, Victor; Tamez-Pena, José G.

    2013-11-01

    Early tumor detection is key in reducing the number of breast cancer death and screening mammography is one of the most widely available and reliable method for early detection. However, it is difficult for the radiologist to process with the same attention each case, due the large amount of images to be read. Computer aided detection (CADe) systems improve tumor detection rate; but the current efficiency of these systems is not yet adequate and the correct interpretation of CADe outputs requires expert human intervention. Computer aided diagnosis systems (CADx) are being designed to improve cancer diagnosis accuracy, but they have not been efficiently applied in breast cancer. CADx efficiency can be enhanced by considering the natural mirror symmetry between the right and left breast. The objective of this work is to evaluate co-registration algorithms for the accurate alignment of the left to right breast for CADx enhancement. A set of mammograms were artificially altered to create a ground truth set to evaluate the registration efficiency of DEMONs , and SPLINE deformable registration algorithms. The registration accuracy was evaluated using mean square errors, mutual information and correlation. The results on the 132 images proved that the SPLINE deformable registration over-perform the DEMONS on mammography images.

  16. An improved method for precise automatic co-registration of moderate and high-resolution spacecraft imagery

    NASA Technical Reports Server (NTRS)

    Bryant, Nevin A.; Logan, Thomas L.; Zobrist, Albert L.

    2006-01-01

    Improvements to the automated co-registration and change detection software package, AFIDS (Automatic Fusion of Image Data System) has recently completed development for and validation by NGA/GIAT. The improvements involve the integration of the AFIDS ultra-fine gridding technique for horizontal displacement compensation with the recently evolved use of Rational Polynomial Functions/ Coefficients (RPFs/RPCs) for image raster pixel position to Latitude/Longitude indexing. Mapping and orthorectification (correction for elevation effects) of satellite imagery defies exact projective solutions because the data are not obtained from a single point (like a camera), but as a continuous process from the orbital path. Standard image processing techniques can apply approximate solutions, but advances in the state-of-the-art had to be made for precision change-detection and time-series applications where relief offsets become a controlling factor. The earlier AFIDS procedure required the availability of a camera model and knowledge of the satellite platform ephemeredes. The recent design advances connect the spacecraft sensor Rational Polynomial Function, a deductively developed model, with the AFIDS ultrafine grid, an inductively developed representation of the relationship raster pixel position to latitude /longitude. As a result, RPCs can be updated by AFIDS, a situation often necessary due to the accuracy limits of spacecraft navigation systems. An example of precision change detection will be presented from Quickbird.

  17. Projection Registration Applied to Nondestructive Testing

    SciTech Connect

    Bingham, Philip R; Arrowood, Lloyd

    2010-01-01

    Registration of radiographic and computed tomography (CT) data has the potential to allow automated metrology and defect detection. While registration of the three-dimensional reconstructed data is a common task in the medical industry for registration of data sets from multiple detection systems, registration of projection sets has only seen development in the area of tomotherapy. Efforts in projection registration have employed a method named Fourier phase matching (FPM). This work discusses implementation and results for the application of the FPM method to industrial applications for the nondestructive testing (NDT) community. The FPM method has been implemented and modified for industrial application. Testing with simulated and experimental x-ray CT data shows excellent performance with respect to the resolution of the imaging system.

  18. High-throughput morphometric analysis of pulmonary airways in MSCT via a mixed 3D/2D approach

    NASA Astrophysics Data System (ADS)

    Ortner, Margarete; Fetita, Catalin; Brillet, Pierre-Yves; Pr"teux, Françoise; Grenier, Philippe

    2011-03-01

    Asthma and COPD are complex airway diseases with an increased incidence estimated for the next decade. Today, the mechanisms and relationships between airway structure/physiology and the clinical phenotype and genotype are not completely understood. We thus lack the tools to predict disease progression or therapeutic responses. One of the main causes is our limited ability to assess the complexity of airway diseases in large populations of patients with appropriate controls. Multi-slice computed tomography (MSCT) imaging opened the way to the non-invasive assessment of airway physiology and structure, but the use of such technology in large cohorts requires a high degree of automation of the measurements. This paper develops an investigation framework and the associated image quantification tools for high-throughput analysis of airways in MSCT. A mixed approach is proposed, combining 3D and cross-section measurements of the airway tree where the user-interaction is limited to the choice of the desired analysis patterns. Such approach relies on the fully-automated segmentation of the 3D airway tree, caliber estimation and visualization based on morphologic granulometry, central axis computation and tree segment selection, cross-section morphometry of airway lumen and wall, and bronchus longitudinal shape analysis for stenosis/bronciectasis detection and measure validation. The developed methodology has been successfully applied to a cohort of 96 patients from a multi-center clinical study of asthma control in moderate and persistent asthma.

  19. Verification Test Suite (VERTS) For Rail Gun Applications using ALE3D: 2-D Hydrodynamics & Thermal Cases

    SciTech Connect

    Najjar, F M; Solberg, J; White, D

    2008-04-17

    A verification test suite has been assessed with primary focus on low reynolds number flow of liquid metals. This is representative of the interface between the armature and rail in gun applications. The computational multiphysics framework, ALE3D, is used. The main objective of the current study is to provide guidance and gain confidence in the results obtained with ALE3D. A verification test suite based on 2-D cases is proposed and includes the lid-driven cavity and the Couette flow are investigated. The hydro and thermal fields are assumed to be steady and laminar in nature. Results are compared with analytical solutions and previously published data. Mesh resolution studies are performed along with various models for the equation of state.

  20. Results of automatic image registration are dependent on initial manual registration.

    PubMed

    Johnson, Joshua E; Fischer, Kenneth J

    2015-01-01

    Measurement of static alignment of articulating joints is of clinical benefit and can be determined using image-based registration. We propose a method that could potentially improve the outcome of image-based registration by using initial manual registration. Magnetic resonance images of two wrist specimens were acquired in the relaxed position and during simulated grasp. Transformations were determined from voxel-based image registration between the two volumes. The volumes were manually aligned to match as closely as possible before auto-registration, from which standard transformations were obtained. Then, translation/rotation perturbations were applied to the manual registration to obtain altered initial positions, from which altered auto-registration transformations were obtained. Models of the radiolunate joint were also constructed from the images to simulate joint contact mechanics. We compared the sensitivity of transformations (translations and rotations) and contact mechanics to altering the initial registration condition from the defined standard. We observed that with increasing perturbation, transformation errors appeared to increase and values for contact force and contact area appeared to decrease. Based on these preliminary findings, it appears that the final registration outcome is sensitive to the initial registration. PMID:25408167

  1. Segmentation of three-dimensional images using non-rigid registration: methods and validation with application to confocal microscopy images of bee brains

    NASA Astrophysics Data System (ADS)

    Rohlfing, Torsten; Brandt, Robert; Menzel, Randolf; Maurer, Calvin R., Jr.

    2003-05-01

    This paper describes the application and validation of automatic segmentation of three-dimensional images by non-rigid registration to atlas images. The registration-based segmentation technique is applied to confocal microscopy images acquired from the brains of 20 bees. Each microscopy image is registered to an already segmented reference atlas image using an intensity-based non-rigid image registration algorithm. This paper evaluates and compares four different approaches: registration to an individual atlas image (IND), registration to an average shape atlas image (AVG), registration to the most similar image from a database of individual atlas images (SIM), and registration to all images from a database of individual atlas images with subsequent fuzzy segmentation (FUZ). For each strategy, the segmentation performance of the algorithm was quantified using both a global segmentation correctness measure and the similarity index. Manual segmentation of all microscopy images served as a gold standard. The best segmentation result (median correctness 91 percent of all voxels) was achieved using the FUZ paradigm. Robustness was also the best for this strategy (minimum correctness over all individuals 84 percent). The mean similarity index value of segmentations produced by the FUZ paradigm is 0.86 (IND, 0.81; AVG, 0.84; SIM, 0.82). The superiority of the FUZ paradigm is statistically significant (two-sided paired t-test, P<0.001).

  2. 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.

  3. An acousto-optical method for registration of erythrocytes' agglutination reaction—sera color influence on the resolving power

    NASA Astrophysics Data System (ADS)

    Doubrovski, V. A.; Medvedeva, M. F.; Torbin, S. O.

    2016-01-01

    The absorption spectra of agglutinating sera were used to determine blood groups. It was shown experimentally that the sera color significantly affects the resolving power of the acousto-optical method of blood typing. In order to increase the resolving power of the method and produce an invariance of the method for sera color, we suggested introducing a probing light beam individually for different sera. The proposed technique not only improves the resolving power of the method, but also reduces the risk of false interpretation of the experimental results and, hence, error in determining the blood group of the sample. The latter is especially important for the typing of blood samples with weak agglutination of erythrocytes. This study can be used in the development of an instrument for instrumental human blood group typing based on the acousto-optical method.

  4. Cadaver validation of intensity-based ultrasound to CT registration.

    PubMed

    Penney, G P; Barratt, D C; Chan, C S K; Slomczykowski, M; Carter, T J; Edwards, P J; Hawkes, D J

    2006-06-01

    A method is presented for the rigid registration of tracked B-mode ultrasound images to a CT volume of a femur and pelvis. This registration can allow tracked surgical instruments to be aligned with the CT image or an associated preoperative plan. Our method is fully automatic and requires no manual segmentation of either the ultrasound images or the CT volume. The parameter which is directly related to the speed of sound through tissue has also been included in the registration optimisation process. Experiments have been carried out on six cadaveric femurs and three cadaveric pelves. Registration results were compared with a "gold standard" registration acquired using bone implanted fiducial markers. Results show the registration method to be accurate, on average, to 1.6 mm root-mean-square target registration error. PMID:16520083

  5. An ITK implementation of a physics-based non-rigid registration method for brain deformation in image-guided neurosurgery

    PubMed Central

    Liu, Yixun; Kot, Andriy; Drakopoulos, Fotis; Yao, Chengjun; Fedorov, Andriy; Enquobahrie, Andinet; Clatz, Olivier; Chrisochoides, Nikos P.

    2014-01-01

    As part of the ITK v4 project efforts, we have developed ITK filters for physics-based non-rigid registration (PBNRR), which satisfies the following requirements: account for tissue properties in the registration, improve accuracy compared to rigid registration, and reduce execution time using GPU and multi-core accelerators. The implementation has three main components: (1) Feature Point Selection, (2) Block Matching (mapped to both multi-core and GPU processors), and (3) a Robust Finite Element Solver. The use of multi-core and GPU accelerators in ITK v4 provides substantial performance improvements. For example, for the non-rigid registration of brain MRIs, the performance of the block matching filter on average is about 10 times faster when 12 hyperthreaded multi-cores are used and about 83 times faster when the NVIDIA Tesla GPU is used in Dell Workstation. PMID:24778613

  6. Registration and Marking Requirements for UAS. Unmanned Aircraft System (UAS) Registration

    NASA Technical Reports Server (NTRS)

    2005-01-01

    The registration of an aircraft is a prerequisite for issuance of a U.S. certificate of airworthiness by the FAA. The procedures and requirements for aircraft registration, and the subsequent issuance of registration numbers, are contained in FAR Part 47. However, the process/method(s) for applying the requirements of Parts 45 & 47 to Unmanned Aircraft Systems (UAS) has not been defined. This task resolved the application of 14 CFR Parts 45 and 47 to UAS. Key Findings: UAS are aircraft systems and as such the recommended approach to registration is to follow the same process for registration as manned aircraft. This will require manufacturers to comply with the requirements for 14 CFR 47, Aircraft Registration and 14 CFR 45, Identification and Registration Marking. In addition, only the UA should be identified with the N number registration markings. There should also be a documentation link showing the applicability of the control station and communication link to the UA. The documentation link can be in the form of a Type Certificate Data Sheet (TCDS) entry or a UAS logbook entry. The recommended process for the registration of UAS is similar to the manned aircraft process and is outlined in a 6-step process in the paper.

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

    PubMed

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

    2014-04-01

    We introduce a boosting algorithm to improve on existing methods for deformable image registration (DIR). The proposed DIRBoost algorithm is inspired by the theory on hypothesis boosting, well known in the field of machine learning. DIRBoost utilizes a method for automatic registration error detection to obtain estimates of local registration quality. All areas detected as erroneously registered are subjected to boosting, i.e. undergo iterative registrations by employing boosting masks on both the fixed and moving image. We validated the DIRBoost algorithm on three different DIR methods (ANTS gSyn, NiftyReg, and DROP) on three independent reference datasets of pulmonary image scan pairs. DIRBoost reduced registration errors significantly and consistently on all reference datasets for each DIR algorithm, yielding an improvement of the registration accuracy by 5-34% depending on the dataset and the registration algorithm employed. PMID:24556079

  8. Adaptive deformable image registration of inhomogeneous tissues

    NASA Astrophysics Data System (ADS)

    Ren, Jing

    2015-03-01

    Physics based deformable registration can provide physically consistent image match of deformable soft tissues. In order to help radiologist/surgeons to determine the status of malicious tumors, we often need to accurately align the regions with embedded tumors. This is a very challenging task since the tumor and the surrounding tissues have very different tissue properties such as stiffness and elasticity. In order to address this problem, based on minimum strain energy principle in elasticity theory, we propose to partition the whole region of interest into smaller sub-regions and dynamically adjust weights of vessel segments and bifurcation points in each sub-region in the registration objective function. Our previously proposed fast vessel registration is used as a component in the inner loop. We have validated the proposed method using liver MR images from human subjects. The results show that our method can detect the large registration errors and improve the registration accuracy in the neighborhood of the tumors and guarantee the registration errors to be within acceptable accuracy. The proposed technique has the potential to significantly improve the registration capability and the quality of clinical diagnosis and treatment planning.

  9. A Multistage Approach for Image Registration.

    PubMed

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

    2016-09-01

    Successful image registration is an important step for object recognition, target detection, remote sensing, multimodal content fusion, scene blending, and disaster assessment and management. The geometric and photometric variations between images adversely affect the ability for an algorithm to estimate the transformation parameters that relate the two images. Local deformations, lighting conditions, object obstructions, and perspective differences all contribute to the challenges faced by traditional registration techniques. In this paper, a novel multistage registration approach is proposed that is resilient to view point differences, image content variations, and lighting conditions. Robust registration is realized through the utilization of a novel region descriptor which couples with the spatial and texture characteristics of invariant feature points. The proposed region descriptor is exploited in a multistage approach. A multistage process allows the utilization of the graph-based descriptor in many scenarios thus allowing the algorithm to be applied to a broader set of images. Each successive stage of the registration technique is evaluated through an effective similarity metric which determines subsequent action. The registration of aerial and street view images from pre- and post-disaster provide strong evidence that the proposed method estimates more accurate global transformation parameters than traditional feature-based methods. Experimental results show the robustness and accuracy of the proposed multistage image registration methodology. PMID:26292357

  10. Fast musculoskeletal registration based on shape matching.

    PubMed

    Gilles, Benjamin; Pai, Dinesh K

    2008-01-01

    This paper presents a new method for computing elastic and plastic deformations in the context of discrete deformable model-based registration. Internal forces are estimated by averaging local transforms between reference and current particle positions. Our technique can accommodate large non-linear deformations, and is unconditionally stable. Moreover, it is simple to implement and versatile. We show how to tune model stiffness and computational cost, which is important for efficient registration, and demonstrate our technique in the complex problem of inter-patient musculoskeletal registration. PMID:18982681

  11. 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.

  12. Performance Evaluation of Automatic Anatomy Segmentation Algorithm on Repeat or Four-Dimensional Computed Tomography Images Using Deformable Image Registration Method

    SciTech Connect

    Wang He; Garden, Adam S.; Zhang Lifei; Wei Xiong; Ahamad, Anesa; Kuban, Deborah A.; Komaki, Ritsuko; O'Daniel, Jennifer; Zhang Yongbin; Mohan, Radhe; Dong Lei

    2008-09-01

    Purpose: Auto-propagation of anatomic regions of interest from the planning computed tomography (CT) scan to the daily CT is an essential step in image-guided adaptive radiotherapy. The goal of this study was to quantitatively evaluate the performance of the algorithm in typical clinical applications. Methods and Materials: We had previously adopted an image intensity-based deformable registration algorithm to find the correspondence between two images. In the present study, the regions of interest delineated on the planning CT image were mapped onto daily CT or four-dimensional CT images using the same transformation. Postprocessing methods, such as boundary smoothing and modification, were used to enhance the robustness of the algorithm. Auto-propagated contours for 8 head-and-neck cancer patients with a total of 100 repeat CT scans, 1 prostate patient with 24 repeat CT scans, and 9 lung cancer patients with a total of 90 four-dimensional CT images were evaluated against physician-drawn contours and physician-modified deformed contours using the volume overlap index and mean absolute surface-to-surface distance. Results: The deformed contours were reasonably well matched with the daily anatomy on the repeat CT images. The volume overlap index and mean absolute surface-to-surface distance was 83% and 1.3 mm, respectively, compared with the independently drawn contours. Better agreement (>97% and <0.4 mm) was achieved if the physician was only asked to correct the deformed contours. The algorithm was also robust in the presence of random noise in the image. Conclusion: The deformable algorithm might be an effective method to propagate the planning regions of interest to subsequent CT images of changed anatomy, although a final review by physicians is highly recommended.

  13. Fusion of intraoperative cortical images with preoperative models for neurosurgical planning and guidance

    NASA Astrophysics Data System (ADS)

    Wang, An; Mirsattari, Seyed M.; Parrent, Andrew G.; Peters, Terry M.

    2009-02-01

    During surgery for epilepsy it is important for the surgeon to correlate the preoperative cortical morphology (from preoperative images) with the intraoperative environment. We extend our visualization method presented earlier, to achieves this goal by fusing a direct (photographic) view of the surgical field with the 3D patient model. To correlate the preoperative plan with the intraoperative surgical scene, an intensity-based perspective 3D-2D registration was employed for camera pose estimation. The 2D photographic image was then texture-mapped onto the 3D preoperative model using the solved camera pose. In the proposed method, we employ direct volume rendering to obtain a perspective view of the brain image using GPU-accelerated ray-casting. This is advantageous compared to the point-based or other feature-based registration since no intermediate processing is required. To validate our registration algorithm, we used a point-based 3D-2D registration, that was validated using ground truth from simulated data, and then the intensity-based 3D-2D registration method was validated using the point-based registration result as the gold standard. The registration error of the intensity-based 3D- 2D method was around 3mm when the initial pose is close to the gold standard. Application of the proposed method for correlating fMRI maps with intraoperative cortical stimulation is shown for surgical planning in an epilepsy patient.

  14. Deformable Medical Image Registration: A Survey

    PubMed Central

    Sotiras, Aristeidis; Davatzikos, Christos; Paragios, Nikos

    2013-01-01

    Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: i) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; ii) longitudinal studies, where temporal structural or anatomical changes are investigated; and iii) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner. PMID:23739795

  15. TU-B-19A-01: Image Registration II: TG132-Quality Assurance for Image Registration

    SciTech Connect

    Brock, K; Mutic, S

    2014-06-15

    AAPM Task Group 132 was charged with a review of the current approaches and solutions for image registration in radiotherapy and to provide recommendations for quality assurance and quality control of these clinical processes. As the results of image registration are always used as the input of another process for planning or delivery, it is important for the user to understand and document the uncertainty associate with the algorithm in general and the Result of a specific registration. The recommendations of this task group, which at the time of abstract submission are currently being reviewed by the AAPM, include the following components. The user should understand the basic image registration techniques and methods of visualizing image fusion. The disclosure of basic components of the image registration by commercial vendors is critical in this respect. The physicists should perform end-to-end tests of imaging, registration, and planning/treatment systems if image registration is performed on a stand-alone system. A comprehensive commissioning process should be performed and documented by the physicist prior to clinical use of the system. As documentation is important to the safe implementation of this process, a request and report system should be integrated into the clinical workflow. Finally, a patient specific QA practice should be established for efficient evaluation of image registration results. The implementation of these recommendations will be described and illustrated during this educational session. Learning Objectives: Highlight the importance of understanding the image registration techniques used in their clinic. Describe the end-to-end tests needed for stand-alone registration systems. Illustrate a comprehensive commissioning program using both phantom data and clinical images. Describe a request and report system to ensure communication and documentation. Demonstrate an clinically-efficient patient QA practice for efficient evaluation of image

  16. Ensemble learning incorporating uncertain registration.

    PubMed

    Simpson, Ivor J A; Woolrich, Mark W; Andersson, Jesper L R; Groves, Adrian R; Schnabel, Julia A

    2013-04-01

    This paper proposes a novel approach for improving the accuracy of statistical prediction methods in spatially normalized analysis. This is achieved by incorporating registration uncertainty into an ensemble learning scheme. A probabilistic registration method is used to estimate a distribution of probable mappings between subject and atlas space. This allows the estimation of the distribution of spatially normalized feature data, e.g., grey matter probability maps. From this distribution, samples are drawn for use as training examples. This allows the creation of multiple predictors, which are subsequently combined using an ensemble learning approach. Furthermore, extra testing samples can be generated to measure the uncertainty of prediction. This is applied to separating subjects with Alzheimer's disease from normal controls using a linear support vector machine on a region of interest in magnetic resonance images of the brain. We show that our proposed method leads to an improvement in discrimination using voxel-based morphometry and deformation tensor-based morphometry over bootstrap aggregating, a common ensemble learning framework. The proposed approach also generates more reasonable soft-classification predictions than bootstrap aggregating. We expect that this approach could be applied to other statistical prediction tasks where registration is important. PMID:23288332

  17. Smartphone app speeds registration.

    PubMed

    2011-03-01

    Two Denver area EDs have entered the digital world with the use of a mobile application that allows patients to pre-register before coming to the ED. Patients can use their smart phones to determine if they need to go to the ED and which one is closest. The ED registration desk receives the pre-registration form, which provides basic information, via fax. Once the information is received, registration notifies the charge nurse so the ED can prepare to receive the patient. PMID:21449510

  18. MO-C-17A-03: A GPU-Based Method for Validating Deformable Image Registration in Head and Neck Radiotherapy Using Biomechanical Modeling

    SciTech Connect

    Neylon, J; Min, Y; Qi, S; Kupelian, P; Santhanam, A

    2014-06-15

    Purpose: Deformable image registration (DIR) plays a pivotal role in head and neck adaptive radiotherapy but a systematic validation of DIR algorithms has been limited by a lack of quantitative high-resolution groundtruth. We address this limitation by developing a GPU-based framework that provides a systematic DIR validation by generating (a) model-guided synthetic CTs representing posture and physiological changes, and (b) model-guided landmark-based validation. Method: The GPU-based framework was developed to generate massive mass-spring biomechanical models from patient simulation CTs and contoured structures. The biomechanical model represented soft tissue deformations for known rigid skeletal motion. Posture changes were simulated by articulating skeletal anatomy, which subsequently applied elastic corrective forces upon the soft tissue. Physiological changes such as tumor regression and weight loss were simulated in a biomechanically precise manner. Synthetic CT data was then generated from the deformed anatomy. The initial and final positions for one hundred randomly-chosen mass elements inside each of the internal contoured structures were recorded as ground truth data. The process was automated to create 45 synthetic CT datasets for a given patient CT. For instance, the head rotation was varied between +/− 4 degrees along each axis, and tumor volumes were systematically reduced up to 30%. Finally, the original CT and deformed synthetic CT were registered using an optical flow based DIR. Results: Each synthetic data creation took approximately 28 seconds of computation time. The number of landmarks per data set varied between two and three thousand. The validation method is able to perform sub-voxel analysis of the DIR, and report the results by structure, giving a much more in depth investigation of the error. Conclusions: We presented a GPU based high-resolution biomechanical head and neck model to validate DIR algorithms by generating CT equivalent 3D

  19. Analytic regularization for landmark-based image registration

    NASA Astrophysics Data System (ADS)

    Shusharina, Nadezhda; Sharp, Gregory

    2012-03-01

    Landmark-based registration using radial basis functions (RBF) is an efficient and mathematically transparent method for the registration of medical images. To ensure invertibility and diffeomorphism of the RBF-based vector field, various regularization schemes have been suggested. Here, we report a novel analytic method of RBF regularization and demonstrate its power for Gaussian RBF. Our analytic formula can be used to obtain a regularized vector field from the solution of a system of linear equations, exactly as in traditional RBF, and can be generalized to any RBF with infinite support. We statistically validate the method on global registration of synthetic and pulmonary images. Furthermore, we present several clinical examples of multistage intensity/landmark-based registrations, where regularized Gaussian RBF are successful in correcting locally misregistered areas resulting from automatic B-spline registration. The intended ultimate application of our method is rapid, interactive local correction of deformable registration with a small number of mouse clicks.

  20. Biomechanical model as a registration tool for image-guided neurosurgery: evaluation against BSpline registration

    PubMed Central

    Mostayed, Ahmed; Garlapati, Revanth Reddy; Joldes, Grand Roman; Wittek, Adam; Roy, Aditi; Kikinis, Ron; Warfield, Simon K.; Miller, Karol

    2013-01-01

    In this paper we evaluate the accuracy of warping of neuro-images using brain deformation predicted by means of a patient-specific biomechanical model against registration using a BSpline-based free form deformation algorithm. Unlike the Bspline algorithm, biomechanics-based registration does not require an intra-operative MR image which is very expensive and cumbersome to acquire. Only sparse intra-operative data on the brain surface is sufficient to compute deformation for the whole brain. In this contribution the deformation fields obtained from both methods are qualitatively compared and overlaps of Canny edges extracted from the images are examined. We define an edge based Hausdorff distance metric to quantitatively evaluate the accuracy of registration for these two algorithms. The qualitative and quantitative evaluations indicate that our biomechanics-based registration algorithm, despite using much less input data, has at least as high registration accuracy as that of the BSpline algorithm. PMID:23771299

  1. Estimation of line-based target registration error

    NASA Astrophysics Data System (ADS)

    Ma, Burton; Peters, Terry M.; Chen, Elvis C. S.

    2016-03-01

    We present a novel method for estimating target registration error (TRE) in point-to-line registration. We develop a spatial stiffness model of the registration problem and derive the stiffness matrix of the model which leads to an analytic expression for predicting the root-mean-square (RMS) TRE. Under the assumption of isotropic localization noise, we show that the stiffness matrix for line-based registration is equal to the difference of the stiffness matrices for fiducial registration and surface-based registration. The expression for TRE is validated in the context of freehand ultrasound calibration performed using a tracked line fiducial as a calibration phantom. Measurements taken during calibration of a tracked linear ultrasound probe were used in simulations to assess TRE of point-to-line registration and the results were compared to the values predicted by the analytic expression. The difference between predicted and simulated RMS TRE magnitude for targets near the centroid of the registration points was less than 5% of the simulated magnitude when using more than 6 registration points. The difference between predicted and simulated RMS TRE magnitude for targets over the entire ultrasound image was almost always less than 10% of the simulated magnitude when using more than 10 registration points. TRE magnitude was minimized near the centroid of the registration points and the isocontours of TRE were elliptic in shape.

  2. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic...

  3. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic...

  4. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic...

  5. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic...

  6. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic...

  7. SULFUR PESTICIDE REGISTRATION STANDARD

    EPA Science Inventory

    The document contains information regarding reregistration of pesticide products containing the subject active ingredient. The document includes how to register under a registration standard, regulatory position and rationale, and summaries of data requirements and data gaps. Als...

  8. Vision-based registration for augmented reality system using monocular and binocular vision

    NASA Astrophysics Data System (ADS)

    Vallerand, Steve; Kanbara, Masayuki; Yokoya, Naokazu

    2003-05-01

    In vision-based augmented reality systems, the relation between the real and virtual worlds needs to be estimated to perform the registration of virtual objects. This paper suggests a vision-based registration method for video see-through augmented reality systems using binocular cameras which increases the quality of the registration performed using three points of a known marker. The originality of this work is the use of both monocular vision-based and stereoscopic vision-based techniques in order to complete the registration. Also, a method that performs a correction of the 2D positions in the images of the marker points is proposed. The correction improves the registration stability and accuracy of the system. The stability of the registration obtained with the proposed registration method combined or not with the correction method is compared to the registration obtained with standard stereoscopic registration.

  9. Intensity-Based Registration for Lung Motion Estimation

    NASA Astrophysics Data System (ADS)

    Cao, Kunlin; Ding, Kai; Amelon, Ryan E.; Du, Kaifang; Reinhardt, Joseph M.; Raghavan, Madhavan L.; Christensen, Gary E.

    Image registration plays an important role within pulmonary image analysis. The task of registration is to find the spatial mapping that brings two images into alignment. Registration algorithms designed for matching 4D lung scans or two 3D scans acquired at different inflation levels can catch the temporal changes in position and shape of the region of interest. Accurate registration is critical to post-analysis of lung mechanics and motion estimation. In this chapter, we discuss lung-specific adaptations of intensity-based registration methods for 3D/4D lung images and review approaches for assessing registration accuracy. Then we introduce methods for estimating tissue motion and studying lung mechanics. Finally, we discuss methods for assessing and quantifying specific volume change, specific ventilation, strain/ stretch information and lobar sliding.

  10. MO-C-17A-02: A Novel Method for Evaluating Hepatic Stiffness Based On 4D-MRI and Deformable Image Registration

    SciTech Connect

    Cui, T; Liang, X; Czito, B; Palta, M; Bashir, M; Yin, F; Cai, J

    2014-06-15

    Purpose: Quantitative imaging of hepatic stiffness has significant potential in radiation therapy, ranging from treatment planning to response assessment. This study aims to develop a novel, noninvasive method to quantify liver stiffness with 3D strains liver maps using 4D-MRI and deformable image registration (DIR). Methods: Five patients with liver cancer were imaged with an institutionally developed 4D-MRI technique under an IRB-approved protocol. Displacement vector fields (DVFs) across the liver were generated via DIR of different phases of 4D-MRI. Strain tensor at each voxel of interest (VOI) was computed from the relative displacements between the VOI and each of the six adjacent voxels. Three principal strains (E{sub 1}, E{sub 2} and E{sub 3}) of the VOI were derived as the eigenvalue of the strain tensor, which represent the magnitudes of the maximum and minimum stretches. Strain tensors for two regions of interest (ROIs) were calculated and compared for each patient, one within the tumor (ROI{sub 1}) and the other in normal liver distant from the heart (ROI{sub 2}). Results: 3D strain maps were successfully generated fort each respiratory phase of 4D-MRI for all patients. Liver deformations induced by both respiration and cardiac motion were observed. Differences in strain values adjacent to the distant from the heart indicate significant deformation caused by cardiac expansion during diastole. The large E{sub 1}/E{sub 2} (∼2) and E{sub 1}/E{sub 2} (∼10) ratios reflect the predominance of liver deformation in the superior-inferior direction. The mean E{sub 1} in ROI{sub 1} (0.12±0.10) was smaller than in ROI{sub 2} (0.15±0.12), reflecting a higher degree of stiffness of the cirrhotic tumor. Conclusion: We have successfully developed a novel method for quantitatively evaluating regional hepatic stiffness based on DIR of 4D-MRI. Our initial findings indicate that liver strain is heterogeneous, and liver tumors may have lower principal strain values

  11. Real-time automatic registration in optical surgical navigation

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  12. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Registration number. 47.15 Section 47.15... REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft registration must place a U.S. registration number (registration mark) on the Aircraft Registration Application,...

  13. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Registration number. 47.15 Section 47.15... REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft registration must place a U.S. registration number (registration mark) on the Aircraft Registration Application,...

  14. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Registration number. 47.15 Section 47.15... REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft registration must place a U.S. registration number (registration mark) on the Aircraft Registration Application,...

  15. Point-to-Volume Registration of Prostate Implants to Ultrasound★

    PubMed Central

    Dehghan, Ehsan; Lee, Junghoon; Fallavollita, Pascal; Kuo, Nathanael; Deguet, Anton; Burdette, E. Clif; Song, Danny; Prince, Jerry L.; Fichtinger, Gabor

    2011-01-01

    Ultrasound-Fluoroscopy fusion is a key step toward intra-operative dosimetry for prostate brachytherapy. We propose a method for intensity-based registration of fluoroscopy to ultrasound that obviates the need for seed segmentation required for seed-based registration. We employ image thresholding and morphological and Gaussian filtering to enhance the image intensity distribution of ultrasound volume. Finally, we find the registration parameters by maximizing a point-to-volume similarity metric. We conducted an experiment on a ground truth phantom and achieved registration error of 0.7±0.2 mm. Our clinical results on 5 patient data sets show excellent visual agreement between the registered seeds and the ultrasound volume with a seed-to-seed registration error of 1.8±0.9 mm. With low registration error, high computational speed and no need for manual seed segmentation, our method is promising for clinical application. PMID:21995080

  16. Longitudinal brain MRI analysis with uncertain registration.

    PubMed

    Simpson, Ivor J A; Woolrich, Mark W; Groves, Adrian R; Schnabel, Julia A

    2011-01-01

    In this paper we propose a novel approach for incorporating measures of spatial uncertainty, which are derived from non-rigid registration, into spatially normalised statistics. Current approaches to spatially normalised statistical analysis use point-estimates of the registration parameters. This is limiting as the registration will rarely be completely accurate, and therefore data smoothing is often used to compensate for the uncertainty of the mapping. We derive localised measurements of spatial uncertainty from a probabilistic registration framework, which provides a principled approach to image smoothing. We evaluate our method using longitudinal deformation features from a set of MR brain images acquired from the Alzheimer's Disease Neuroimaging Initiative. These images are spatially normalised using our probabilistic registration algorithm. The spatially normalised longitudinal features are adaptively smoothed according to the registration uncertainty. The proposed adaptive smoothing shows improved classification results, (84% correct Alzheimer's Disease vs. controls), over either not smoothing (79.6%), or using a Gaussian filter with sigma = 2mm (78.8%). PMID:21995084

  17. Robust Deformable Image Registration using Prior Shape Information for Atlas to Patient Registration

    PubMed Central

    Ellingsen, Lotta M.; Chintalapani, Gouthami; Taylor, Russell H.; Prince, Jerry L.

    2009-01-01

    Statistical atlases enable the individualization of atlas information for patient specific applications such as surgical planning. In this paper, a statistical atlas comprising a point distribution model defined on the vertices of a tetrahedral mesh is registered to a subject’s computed tomography scan of the human pelvis. The approach consists of a volumetric deformable registration method augmented to maintain the topology of the atlas mesh after deformation as well as incorporating the dominant three-dimensional shape modes in the atlas. Experimental results demonstrate that incorporation of the statistical shape atlas helps to stabilize the registration and improves robustness and registration accuracy. PMID:19515532

  18. User Registration in EOSDIS

    NASA Astrophysics Data System (ADS)

    Murphy, K. J.; Mitchell, A. E.

    2009-12-01

    Throughout the lifetime of EOSDIS the topic of user registration has received varied attention. Initially, for example, users ordering data from the Earth Science Data Gateway were required to register for delivery of media orders, to check order status and save profile information for future interactions. As EOSDIS embraced evolution of its data systems, the mostly centralized search and order system was replaced with a more diverse set of interfaces allowing (mostly) anonymous online access to data, tools and services. The changes to EOSDIS were embraced by users but the anonymous nature of the interaction made it more difficult to characterize users, capture metrics and provide customized services that benefit users. Additionally, new tools and interfaces have been developed without a centralized registration system. Currently a patchwork of independent registration systems exists throughout EOSDIS for ordering data and interacting with online tools and services. Each requires a separate username and password that must be managed by users. A consolidation of registration systems presents an opportunity to improve not only the user experience through tool customization and simplification of password management, but the understanding of users. This work discusses the options for implementing a common user registration for the EOSDIS, anticipated benefits and pitfalls.

  19. 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

  20. Mass preserving registration for lung CT

    NASA Astrophysics Data System (ADS)

    Gorbunova, Vladlena; Lo, Pechin; Loeve, Martine; Tiddens, Harm A.; Sporring, Jon; Nielsen, Mads; de Bruijne, Marleen

    2009-02-01

    In this paper, we evaluate a novel image registration method on a set of expiratory-inspiratory pairs of computed tomography (CT) lung scans. A free-form multi resolution image registration technique is used to match two scans of the same subject. To account for the differences in the lung intensities due to differences in inspiration level, we propose to adjust the intensity of lung tissue according to the local expansion or compression. An image registration method without intensity adjustment is compared to the proposed method. Both approaches are evaluated on a set of 10 pairs of expiration and inspiration CT scans of children with cystic fibrosis lung disease. The proposed method with mass preserving adjustment results in significantly better alignment of the vessel trees. Analysis of local volume change for regions with trapped air compared to normally ventilated regions revealed larger differences between these regions in the case of mass preserving image registration, indicating that mass preserving registration is better at capturing localized differences in lung deformation.

  1. 3D–2D registration for surgical guidance: effect of projection view angles on registration accuracy

    PubMed Central

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

    2016-01-01

    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. PMID:24351769

  2. Surface-based prostate registration with biomechanical regularization

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  3. 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.

  4. Towards operational multisensor registration

    NASA Technical Reports Server (NTRS)

    Rignot, Eric J. M.; Kwok, Ronald; Curlander, John C.

    1991-01-01

    To use data from a number of different remote sensors in a synergistic manner, a multidimensional analysis of the data is necessary. However, prior to this analysis, processing to correct for the systematic geometric distortion characteristic of each sensor is required. Furthermore, the registration process must be fully automated to handle a large volume of data and high data rates. A conceptual approach towards an operational multisensor registration algorithm is presented. The performance requirements of the algorithm are first formulated given the spatially, temporally, and spectrally varying factors that influence the image characteristics and the science requirements of various applications. Several registration techniques that fit within the structure of this algorithm are also presented. Their performance was evaluated using a multisensor test data set assembled from LANDSAT TM, SEASAT, SIR-B, Thermal Infrared Multispectral Scanner (TIMS), and SPOT sensors.

  5. Medical image registration using fuzzy theory.

    PubMed

    Pan, Meisen; Tang, Jingtian; Xiong, Qi

    2012-01-01

    Mutual information (MI)-based registration, which uses MI as the similarity measure, is a representative method in medical image registration. It has an excellent robustness and accuracy, but with the disadvantages of a large amount of calculation and a long processing time. In this paper, by computing the medical image moments, the centroid is acquired. By applying fuzzy c-means clustering, the coordinates of the medical image are divided into two clusters to fit a straight line, and the rotation angles of the reference and floating images are computed, respectively. Thereby, the initial values for registering the images are determined. When searching the optimal geometric transformation parameters, we put forward the two new concepts of fuzzy distance and fuzzy signal-to-noise ratio (FSNR), and we select FSNR as the similarity measure between the reference and floating images. In the experiments, the Simplex method is chosen as multi-parameter optimisation. The experimental results show that this proposed method has a simple implementation, a low computational cost, a fast registration and good registration accuracy. Moreover, it can effectively avoid trapping into the local optima. It is adapted to both mono-modality and multi-modality image registrations. PMID:21442490

  6. 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.

  7. Automatic sub-volume registration by probabilistic random search

    NASA Astrophysics Data System (ADS)

    Han, Jingfeng; Qiao, Min; Hornegger, Joachim; Kuwert, Torsten; Bautz, Werner; Römer, Wolfgang

    2006-03-01

    Registration of an individual's image data set to an anatomical atlas provides valuable information to the physician. In many cases, the individual image data sets are partial data, which may be mapped to one part or one organ of the entire atlas data. Most of the existing intensity based image registration approaches are designed to align images of the entire view. When they are applied to the registration with partial data, a manual pre-registration is usually required. This paper proposes a fully automatic approach to the registration of the incomplete image data to an anatomical atlas. The spatial transformations are modelled as any parametric functions. The proposed method is built upon a random search mechanism, which allows to find the optimal transformation randomly and globally even when the initialization is not ideal. It works more reliably than the existing methods for the partial data registration because it successfully overcomes the local optimum problem. With appropriate similarity measures, this framework is applicable to both mono-modal and multi-modal registration problems with partial data. The contribution of this work is the description of the mathematical framework of the proposed algorithm and the implementation of the related software. The medical evaluation on the MRI data and the comparison of the proposed method with different existing registration methods show the feasibility and superiority of the proposed method.

  8. Distributed Continuous Registration.

    ERIC Educational Resources Information Center

    Myers, Donald L.

    1981-01-01

    The development, implementation, and features of Northern Colorado's continuous registration system are described. The system is an online distributed processing system, written in COBOL for an IBM Series I under the CPS operating system. Course selection, permit to enroll, and drop/add forms are provided. (Author/MLW)

  9. CUNY's Voter Registration System.

    ERIC Educational Resources Information Center

    Hershenson, Jay; And Others

    This collection of items including public testimony by the Vice Chancellor, Jay Hershenson, a formal resolution, a press release, and brochures, documents the City University of New York's (CUNY) unique voter registration system, "CUNY Project Vote". As the press release describes it, Project Vote is the nation's largest student voter registration…

  10. Registration Study. Research Note.

    ERIC Educational Resources Information Center

    Baratta, Mary Kathryne

    During spring 1977 registration, 3,255 or 45% of Moraine Valley Community College (MVCC) registering students responded to a scheduling preferences and problems questionnaire covering enrollment status, curriculum load, program preference, ability to obtain courses, schedule conflicts, preferred times for class offerings, actual scheduling of…

  11. 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

  12. The hidden KPI registration accuracy.

    PubMed

    Shorrosh, Paul

    2011-09-01

    Determining the registration accuracy rate is fundamental to improving revenue cycle key performance indicators. A registration quality assurance (QA) process allows errors to be corrected before bills are sent and helps registrars learn from their mistakes. Tools are available to help patient access staff who perform registration QA manually. PMID:21923052

  13. Outline of Programe Registration System

    NASA Astrophysics Data System (ADS)

    Kono, Masamichi

    After the outline of the copyright registration system was described in this paper, the program registration system, which has started from April l, 1987, was introduced in focussing on the subjects as the special case and a methodology of registration procedures and how to submit the application.

  14. Multimodality imaging combination in small animal via point-based registration

    NASA Astrophysics Data System (ADS)

    Yang, C. C.; Wu, T. H.; Lin, M. H.; Huang, Y. H.; Guo, W. Y.; Chen, C. L.; Wang, T. C.; Yin, W. H.; Lee, J. S.

    2006-12-01

    We present a system of image co-registration in small animal study. Marker-based registration is chosen because of its considerable advantage that the fiducial feature is independent of imaging modality. We also experimented with different scanning protocols and different fiducial marker sizes to improve registration accuracy. Co-registration was conducted using rat phantom fixed by stereotactic frame. Overall, the co-registration accuracy was in sub-millimeter level and close to intrinsic system error. Therefore, we conclude that the system is an accurate co-registration method to be used in small animal studies.

  15. 14 CFR 47.43 - Invalid registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Invalid registration. 47.43 Section 47.43... REGISTRATION Certificates of Aircraft Registration § 47.43 Invalid registration. (a) The registration of an...) compliance with 49 U.S.C. 44101-44104. (b) If the registration of an aircraft is invalid under paragraph...

  16. Image registration with auto-mapped control volumes

    SciTech Connect

    Schreibmann, Eduard; Xing Lei

    2006-04-15

    Many image registration algorithms rely on the use of homologous control points on the two input image sets to be registered. In reality, the interactive identification of the control points on both images is tedious, difficult, and often a source of error. We propose a two-step algorithm to automatically identify homologous regions that are used as a priori information during the image registration procedure. First, a number of small control volumes having distinct anatomical features are identified on the model image in a somewhat arbitrary fashion. Instead of attempting to find their correspondences in the reference image through user interaction, in the proposed method, each of the control regions is mapped to the corresponding part of the reference image by using an automated image registration algorithm. A normalized cross-correlation (NCC) function or mutual information was used as the auto-mapping metric and a limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS) was employed to optimize the function to find the optimal mapping. For rigid registration, the transformation parameters of the system are obtained by averaging that derived from the individual control volumes. In our deformable calculation, the mapped control volumes are treated as the nodes or control points with known positions on the two images. If the number of control volumes is not enough to cover the whole image to be registered, additional nodes are placed on the model image and then located on the reference image in a manner similar to the conventional BSpline deformable calculation. For deformable registration, the established correspondence by the auto-mapped control volumes provides valuable guidance for the registration calculation and greatly reduces the dimensionality of the problem. The performance of the two-step registrations was applied to three rigid registration cases (two PET-CT registrations and a brain MRI-CT registration) and one deformable registration of

  17. The Effect of Late Registration for College Classes

    ERIC Educational Resources Information Center

    Safer, Alan M.

    2009-01-01

    Objective: To assess the outcome of late registration for college classes and early class withdrawal. Method: Computerized 2007-9 school record data on 7,200 college students were analyzed to evaluate the effect of late class registration on the class grade--relative to the average class grade--and on class withdrawal. Assessed by multiple…

  18. 78 FR 20619 - Customer Account Registration and Maintenance

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-05

    ... United States Patent and Trademark Office Customer Account Registration and Maintenance ACTION: Proposed... methods: Email: InformationCollection@uspto.gov . Include ``0651- 00xx Customer Account Registration and... optional customer portal that will serve as a central point for access to online system interfaces...

  19. Temporal mammogram image registration using optimized curvilinear coordinates.

    PubMed

    Abdel-Nasser, Mohamed; Moreno, Antonio; Puig, Domenec

    2016-04-01

    Registration of mammograms plays an important role in breast cancer computer-aided diagnosis systems. Radiologists usually compare mammogram images in order to detect abnormalities. The comparison of mammograms requires a registration between them. A temporal mammogram registration method is proposed in this paper. It is based on the curvilinear coordinates, which are utilized to cope both with global and local deformations in the breast area. Temporal mammogram pairs are used to validate the proposed method. After registration, the similarity between the mammograms is maximized, and the distance between manually defined landmarks is decreased. In addition, a thorough comparison with the state-of-the-art mammogram registration methods is performed to show its effectiveness. PMID:27000285

  20. PROFESSIONAL REGISTRATION OF GOVERNMENT ENGINEERS.

    USGS Publications Warehouse

    Buchanan, Thomas J.

    1985-01-01

    The American Society of Civil Engineers views professional registration as an appropriate requirement for engineers, including those in government. The National Society of Professional Engineers makes registration a requirement for the grade of member and full privileges in the society. Some Federal agencies require engineering registration for certain positions in their agencies. Engineers in government service should consider the value of engineering registration to themselves and to their agencies and take pride in their professions and in their own capabilities by becoming registered engineers. They should also take steps to encourage their agencies to give more attention to engineering registration.

  1. Image registration using redundant wavelet transforms

    NASA Astrophysics Data System (ADS)

    Brown, Richard K.; Claypoole, Roger L., Jr.

    2001-12-01

    Imagery is collected much faster and in significantly greater quantities today compared to a few years ago. Accurate registration of this imagery is vital for comparing the similarities and differences between multiple images. Image registration is a significant component in computer vision and other pattern recognition problems, medical applications such as Medical Resonance Images (MRI) and Positron Emission Tomography (PET), remotely sensed data for target location and identification, and super-resolution algorithms. Since human analysis is tedious and error prone for large data sets, we require an automatic, efficient, robust, and accurate method to register images. Wavelet transforms have proven useful for a variety of signal and image processing tasks. In our research, we present a fundamentally new wavelet-based registration algorithm utilizing redundant transforms and a masking process to suppress the adverse effects of noise and improve processing efficiency. The shift-invariant wavelet transform is applied in translation estimation and a new rotation-invariant polar wavelet transform is effectively utilized in rotation estimation. We demonstrate the robustness of these redundant wavelet transforms for the registration of two images (i.e., translating or rotating an input image to a reference image), but extensions to larger data sets are feasible. We compare the registration accuracy of our redundant wavelet transforms to the critically sampled discrete wavelet transform using the Daubechies wavelet to illustrate the power of our algorithm in the presence of significant additive white Gaussian noise and strongly translated or rotated images.

  2. A multi-scale registration of urban aerial image with airborne lidar data

    NASA Astrophysics Data System (ADS)

    Huang, Shuo; Chen, Siying; Zhang, Yinchao; Guo, Pan; Chen, He

    2015-11-01

    This paper presented a multi-scale progressive registration method of airborne LiDAR data with aerial image. The cores of the proposed method lie in the coarse registration with road networks and the fine registration method using regularized building corners. During the two-stage registration, the exterior orientation parameters (EOP) are continually refined. By validation of the actual flight data of Dunhuang, the experimental result shows that the proposed method can obtain accurate results with low-precision initial EOP, also improve the automatic degree of registration.

  3. Ricci Flow-based Spherical Parameterization and Surface Registration.

    PubMed

    Chen, X; He, H; Zou, G; Zhang, X; Gu, X; Hua, J

    2013-09-01

    This paper presents an improved Euclidean Ricci flow method for spherical parameterization. We subsequently invent a scale space processing built upon Ricci energy to extract robust surface features for accurate surface registration. Since our method is based on the proposed Euclidean Ricci flow, it inherits the properties of Ricci flow such as conformality, robustness and intrinsicalness, facilitating efficient and effective surface mapping. Compared with other surface registration methods using curvature or sulci pattern, our method demonstrates a significant improvement for surface registration. In addition, Ricci energy can capture local differences for surface analysis as shown in the experiments and applications. PMID:24019739

  4. Onboard Image Registration from Invariant Features

    NASA Technical Reports Server (NTRS)

    Wang, Yi; Ng, Justin; Garay, Michael J.; Burl, Michael C

    2008-01-01

    This paper describes a feature-based image registration technique that is potentially well-suited for onboard deployment. The overall goal is to provide a fast, robust method for dynamically combining observations from multiple platforms into sensors webs that respond quickly to short-lived events and provide rich observations of objects that evolve in space and time. The approach, which has enjoyed considerable success in mainstream computer vision applications, uses invariant SIFT descriptors extracted at image interest points together with the RANSAC algorithm to robustly estimate transformation parameters that relate one image to another. Experimental results for two satellite image registration tasks are presented: (1) automatic registration of images from the MODIS instrument on Terra to the MODIS instrument on Aqua and (2) automatic stabilization of a multi-day sequence of GOES-West images collected during the October 2007 Southern California wildfires.

  5. 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

  6. 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.

  7. Mono- and multimodal registration of optical breast images

    NASA Astrophysics Data System (ADS)

    Pearlman, Paul C.; Adams, Arthur; Elias, Sjoerd G.; Mali, Willem P. Th. M.; Viergever, Max A.; Pluim, Josien P. W.

    2012-08-01

    Optical breast imaging offers the possibility of noninvasive, low cost, and high sensitivity imaging of breast cancers. Poor spatial resolution and a lack of anatomical landmarks in optical images of the breast make interpretation difficult and motivate registration and fusion of these data with subsequent optical images and other breast imaging modalities. Methods used for registration and fusion of optical breast images are reviewed. Imaging concerns relevant to the registration problem are first highlighted, followed by a focus on both monomodal and multimodal registration of optical breast imaging. Where relevant, methods pertaining to other imaging modalities or imaged anatomies are presented. The multimodal registration discussion concerns digital x-ray mammography, ultrasound, magnetic resonance imaging, and positron emission tomography.

  8. SU-E-J-122: The CBCT Dose Calculation Using a Patient Specific CBCT Number to Mass Density Conversion Curve Based On a Novel Image Registration and Organ Mapping Method in Head-And-Neck Radiation Therapy

    SciTech Connect

    Zhou, J; Lasio, G; Chen, S; Zhang, B; Langen, K; Prado, K; D’Souza, W; Yi, B; Huang, J

    2015-06-15

    Purpose: To develop a CBCT HU correction method using a patient specific HU to mass density conversion curve based on a novel image registration and organ mapping method for head-and-neck radiation therapy. Methods: There are three steps to generate a patient specific CBCT HU to mass density conversion curve. First, we developed a novel robust image registration method based on sparseness analysis to register the planning CT (PCT) and the CBCT. Second, a novel organ mapping method was developed to transfer the organs at risk (OAR) contours from the PCT to the CBCT and corresponding mean HU values of each OAR were measured in both the PCT and CBCT volumes. Third, a set of PCT and CBCT HU to mass density conversion curves were created based on the mean HU values of OARs and the corresponding mass density of the OAR in the PCT. Then, we compared our proposed conversion curve with the traditional Catphan phantom based CBCT HU to mass density calibration curve. Both curves were input into the treatment planning system (TPS) for dose calculation. Last, the PTV and OAR doses, DVH and dose distributions of CBCT plans are compared to the original treatment plan. Results: One head-and-neck cases which contained a pair of PCT and CBCT was used. The dose differences between the PCT and CBCT plans using the proposed method are −1.33% for the mean PTV, 0.06% for PTV D95%, and −0.56% for the left neck. The dose differences between plans of PCT and CBCT corrected using the CATPhan based method are −4.39% for mean PTV, 4.07% for PTV D95%, and −2.01% for the left neck. Conclusion: The proposed CBCT HU correction method achieves better agreement with the original treatment plan compared to the traditional CATPhan based calibration method.

  9. Towards an intercomparison of automated registration algorithms for multiple source remote sensing data

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; Xia, Wei; Chettri, Samir; El-Ghazawi, Tarek; Kaymaz, Emre; Lerner, Bao-Ting; Mareboyana, Manohar; Netanyahu, Nathan; Pierce, John; Raghavan, Srini; Tilton, James C.; Campbell, William J.; Cromp, Robert F.

    1997-01-01

    The first step in the integration of multiple data is registration, either relative image-to-image registration or absolute geo-registration, to a map or a fixed coordinate system. As the need for automating registration techniques is recognized, we feel that there is a need to survey all the registration methods which may be applicable to Earth and space science problems and to evaluate their performances on a large variety of existing remote sensing data as well as on simulated data of soon-to-be-flown instruments. In this paper we will describe: 1) the operational toolbox which we are developing and which will consist in some of the most important registration techniques; and 2) the quantitative intercomparison of the different methods, which will allow a user to select the desired registration technique based on this evaluation and the visualization of the registration results.

  10. Automatic parameter selection for multimodal image registration.

    PubMed

    Hahn, Dieter A; Daum, Volker; Hornegger, Joachim

    2010-05-01

    Over the past ten years similarity measures based on intensity distributions have become state-of-the-art in automatic multimodal image registration. An implementation for clinical usage has to support a plurality of images. However, a generally applicable parameter configuration for the number and sizes of histogram bins, optimal Parzen-window kernel widths or background thresholds cannot be found. This explains why various research groups present partly contradictory empirical proposals for these parameters. This paper proposes a set of data-driven estimation schemes for a parameter-free implementation that eliminates major caveats of heuristic trial and error. We present the following novel approaches: a new coincidence weighting scheme to reduce the influence of background noise on the similarity measure in combination with Max-Lloyd requantization, and a tradeoff for the automatic estimation of the number of histogram bins. These methods have been integrated into a state-of-the-art rigid registration that is based on normalized mutual information and applied to CT-MR, PET-MR, and MR-MR image pairs of the RIRE 2.0 database. We compare combinations of the proposed techniques to a standard implementation using default parameters, which can be found in the literature, and to a manual registration by a medical expert. Additionally, we analyze the effects of various histogram sizes, sampling rates, and error thresholds for the number of histogram bins. The comparison of the parameter selection techniques yields 25 approaches in total, with 114 registrations each. The number of bins has no significant influence on the proposed implementation that performs better than both the manual and the standard method in terms of acceptance rates and target registration error (TRE). The overall mean TRE is 2.34 mm compared to 2.54 mm for the manual registration and 6.48 mm for a standard implementation. Our results show a significant TRE reduction for distortion

  11. Highly accurate fast lung CT registration

    NASA Astrophysics Data System (ADS)

    Rühaak, Jan; Heldmann, Stefan; Kipshagen, Till; Fischer, Bernd

    2013-03-01

    Lung registration in thoracic CT scans has received much attention in the medical imaging community. Possible applications range from follow-up analysis, motion correction for radiation therapy, monitoring of air flow and pulmonary function to lung elasticity analysis. In a clinical environment, runtime is always a critical issue, ruling out quite a few excellent registration approaches. In this paper, a highly efficient variational lung registration method based on minimizing the normalized gradient fields distance measure with curvature regularization is presented. The method ensures diffeomorphic deformations by an additional volume regularization. Supplemental user knowledge, like a segmentation of the lungs, may be incorporated as well. The accuracy of our method was evaluated on 40 test cases from clinical routine. In the EMPIRE10 lung registration challenge, our scheme ranks third, with respect to various validation criteria, out of 28 algorithms with an average landmark distance of 0.72 mm. The average runtime is about 1:50 min on a standard PC, making it by far the fastest approach of the top-ranking algorithms. Additionally, the ten publicly available DIR-Lab inhale-exhale scan pairs were registered to subvoxel accuracy at computation times of only 20 seconds. Our method thus combines very attractive runtimes with state-of-the-art accuracy in a unique way.

  12. 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.

  13. 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.

  14. 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).

  15. A surface-matching technique for robot-assisted registration.

    PubMed

    Glozman, D; Shoham, M; Fischer, A

    2001-01-01

    Successful implementation of robot-assisted surgery (RAS) requires coherent integration of spatial image data with sensing and actuating devices, each having its own coordinate system. Hence, accurate estimation of the geometric relationships between relevant reference frames, known as registration, is a crucial procedure in all RAS applications. The purpose of this paper is to present a new registration scheme, along with the results of an experimental evaluation of a robot-assisted registration method for RAS applications in orthopedics. The accuracy of the proposed registration is appropriate for specified orthopedic surgical applications such as Total Knee Replacement. The registration method is based on a surface-matching algorithm that does not require marker implants, thereby reducing surgical invasiveness. Points on the bone surface are sampled by the robot, which in turn directs the surgical tool. This technique eliminates additional coordinate transformations to an external device (such as a digitizer), resulting in increased surgical accuracy. The registration technique was tested on an RSPR six-degrees-of-freedom parallel robot specifically designed for medical applications. A six-axis force sensor attached to the robot's moving platform enables fast and accurate acquisition of positions and surface normal directions at sampled points. Sampling with a robot probe was shown to be accurate, fast, and easy to perform. The whole procedure takes about 2 min, with the robot performing most of the registration procedures, leaving the surgeon's hands free. Robotic registration was shown to provide a flawless link between preoperative planning and robotic assistance during surgery. PMID:11892002

  16. Color image registration based on quaternion Fourier transformation

    NASA Astrophysics Data System (ADS)

    Wang, Qiang; Wang, Zhengzhi

    2012-05-01

    The traditional Fourier Mellin transform is applied to quaternion algebra in order to investigate quaternion Fourier transformation properties useful for color image registration in frequency domain. Combining with the quaternion phase correlation, we propose a method for color image registration based on the quaternion Fourier transform. The registration method, which processes color image in a holistic manner, is convenient to realign color images differing in translation, rotation, and scaling. Experimental results on different types of color images indicate that the proposed method not only obtains high accuracy in similarity transform in the image plane but also is computationally efficient.

  17. Registration of structurally dissimilar images in MRI-based brachytherapy

    NASA Astrophysics Data System (ADS)

    Berendsen, F. F.; Kotte, A. N. T. J.; de Leeuw, A. A. C.; Jürgenliemk-Schulz, I. M.; Viergever, M. A.; Pluim, J. P. W.

    2014-08-01

    A serious challenge in image registration is the accurate alignment of two images in which a certain structure is present in only one of the two. Such topological changes are problematic for conventional non-rigid registration algorithms. We propose to incorporate in a conventional free-form registration framework a geometrical penalty term that minimizes the volume of the missing structure in one image. We demonstrate our method on cervical MR images for brachytherapy. The intrapatient registration problem involves one image in which a therapy applicator is present and one in which it is not. By including the penalty term, a substantial improvement in the surface distance to the gold standard anatomical position and the residual volume of the applicator void are obtained. Registration of neighboring structures, i.e. the rectum and the bladder is generally improved as well, albeit to a lesser degree.

  18. An automatic nonrigid registration for stained histological sections.

    PubMed

    Auer, Martin; Regitnig, Peter; Holzapfel, Gerhard A

    2005-04-01

    Automatic computer-based analyses of histological sections which are differently stained require that they are related to each other. Most registration methods are only able to perform rigid-body motion and are sensitive to noise and artifacts. Histological images, however, are accompanied by several artifacts and different contrasts, which require a nonrigid registration. In this paper, we present a hierarchical nonrigid registration algorithm able to align images, which contain minor image artifacts. The algorithm requires no a priori knowledge of the true image. The hierarchical design of the algorithm enhances robustness and accuracy, and saves computational costs. The proposed algorithm is decomposed into a fast, coarse, rigid registration step and a slower, but finer, nonrigid step. For the coarse registration, we use image pyramids, while for the second step, we combine a point-based registration with an elastic thin-plate spline interpolation. Accuracy tests, performed for 20 histological images obtained from human arteries, have shown that the error measure is acceptable, and that the image noise does not cause a problem. The associated convergence rate of the mean pixel displacement error during the rigid and nonrigid registrations is satisfying. The algorithm can be applied to various multicontrast elastic registration problems in medical imaging and may be extended to three dimensions. PMID:15825482

  19. Diffeomorphic Registration of Images with Variable Contrast Enhancement

    PubMed Central

    Janssens, Guillaume; Jacques, Laurent; Orban de Xivry, Jonathan; Geets, Xavier; Macq, Benoit

    2011-01-01

    Nonrigid image registration is widely used to estimate tissue deformations in highly deformable anatomies. Among the existing methods, nonparametric registration algorithms such as optical flow, or Demons, usually have the advantage of being fast and easy to use. Recently, a diffeomorphic version of the Demons algorithm was proposed. This provides the advantage of producing invertible displacement fields, which is a necessary condition for these to be physical. However, such methods are based on the matching of intensities and are not suitable for registering images with different contrast enhancement. In such cases, a registration method based on the local phase like the Morphons has to be used. In this paper, a diffeomorphic version of the Morphons registration method is proposed and compared to conventional Morphons, Demons, and diffeomorphic Demons. The method is validated in the context of radiotherapy for lung cancer patients on several 4D respiratory-correlated CT scans of the thorax with and without variable contrast enhancement. PMID:21197460

  20. Lung registration using airway tree morphometry

    NASA Astrophysics Data System (ADS)

    Tan, Jun; Zheng, Bin; Park, Sang; Pu, Jiantao; Wenzel, Sally E.; Leader, Joseph K.

    2011-03-01

    This paper describes a non-linear medical image registration algorithm that aligns lung CT images scanned at different respiratory phases. The method uses landmarks obtained from the airway tree to find the airway branch extension lines and where the lines intersect the lung surface. The branch extension and lung intersection voxels on the surface were the crucial landmarks that initialize the non-rigid registration process. The advantage of these landmarks is that they have high correspondence between the matching patterns in the template images and deformed images. This method was developed and tested on CT examinations from participants in an asthma study. The registration accuracy was evaluated by the average distance between the corresponding airway tree branch points in the pair of images. The mean value of the distance between landmarks in template images and deformed matching images for subjects 1 and 2 were 8.44 mm (+/-4.46 mm) and 4.33 mm (+/- 3.78 mm), respectively. The results show that the lung image registration technique developed in this study may prove useful in quantifying longitudinal changes, performing regional analysis, tracking lung tumors, and compensating for subject motion across CT images.

  1. 14 CFR 47.43 - Invalid registration.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Invalid registration. 47.43 Section 47.43... REGISTRATION Certificates of Aircraft Registration § 47.43 Invalid registration. Link to an amendment published... registration of an aircraft is invalid if, at the time it is made— (1) The aircraft is registered in a...

  2. 17 CFR 250.1 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 17 Commodity and Securities Exchanges 3 2011-04-01 2011-04-01 false Registration. 250.1 Section... AND REGULATIONS, PUBLIC UTILITY HOLDING COMPANY ACT OF 1935 Registration and General Exemptions § 250.1 Registration. (a) Notification of registration. Notifications of registration pursuant to...

  3. 17 CFR 250.1 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 17 Commodity and Securities Exchanges 3 2010-04-01 2010-04-01 false Registration. 250.1 Section... AND REGULATIONS, PUBLIC UTILITY HOLDING COMPANY ACT OF 1935 Registration and General Exemptions § 250.1 Registration. (a) Notification of registration. Notifications of registration pursuant to...

  4. 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).

  5. Combined Volumetric and Surface Registration

    PubMed Central

    Zöllei, Lilla; Fischl, Bruce

    2009-01-01

    In this paper, we propose a novel method for the registration of volumetric images of the brain that optimizes the alignment of both cortical and subcortical structures. In order to achieve this, relevant geometrical information is extracted from a surface-based morph and diffused into the volume using the Navier operator of elasticity, resulting in a volumetric warp that aligns cortical folding patterns. This warp field is then refined with an intensity driven optical flow procedure that registers noncortical regions, while preserving the cortical alignment. The result is a combined surface and volume morph (CVS) that accurately registers both cortical and subcortical regions, establishing a single coordinate system suitable for the entire brain. PMID:19273000

  6. Quantifying brain development in early childhood using segmentation and registration

    NASA Astrophysics Data System (ADS)

    Aljabar, P.; Bhatia, K. K.; Murgasova, M.; Hajnal, J. V.; Boardman, J. P.; Srinivasan, L.; Rutherford, M. A.; Dyet, L. E.; Edwards, A. D.; Rueckert, D.

    2007-03-01

    In this work we obtain estimates of tissue growth using longitudinal data comprising MR brain images of 25 preterm children scanned at one and two years. The growth estimates are obtained using segmentation and registration based methods. The segmentation approach used an expectation maximisation (EM) method to classify tissue types and the registration approach used tensor based morphometry (TBM) applied to a free form deformation (FFD) model. The two methods show very good agreement indicating that the registration and segmentation approaches can be used interchangeably. The advantage of the registration based method, however, is that it can provide more local estimates of tissue growth. This is the first longitudinal study of growth in early childhood, previous longitudinal studies have focused on later periods during childhood.

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

    PubMed Central

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

    2015-01-01

    Purpose We propose two software tools for non-rigid registration of MRI and transrectal ultrasound (TRUS) images of the prostate. Our ultimate goal is to develop an open-source solution to support MRI–TRUS fusion image guidance of prostate interventions, such as targeted biopsy for prostate cancer detection and focal therapy. It is widely hypothesized that image registration is an essential component in such systems. Methods The two non-rigid registration methods are: (1) a deformable registration of the prostate segmentation distance maps with B-spline regularization and (2) a finite element-based deformable registration of the segmentation surfaces in the presence of partial data. We evaluate the methods retrospectively using clinical patient image data collected during standard clinical procedures. Computation time and Target Registration Error (TRE) calculated at the expert-identified anatomical landmarks were used as quantitative measures for the evaluation. Results The presented image registration tools were capable of completing deformable registration computation within 5 min. Average TRE was approximately 3 mm for both methods, which is comparable with the slice thickness in our MRI data. Both tools are available under nonrestrictive open-source license. Conclusions We release open-source tools that may be used for registration during MRI–TRUS-guided prostate interventions. Our tools implement novel registration approaches and produce acceptable registration results. We believe these tools will lower the barriers in development and deployment of interventional research solutions and facilitate comparison with similar tools. PMID:25847666

  8. Reflectance and fluorescence hyperspectral elastic image registration

    NASA Astrophysics Data System (ADS)

    Lange, Holger; Baker, Ross; Hakansson, Johan; Gustafsson, Ulf P.

    2004-05-01

    Science and Technology International (STI) presents a novel multi-modal elastic image registration approach for a new hyperspectral medical imaging modality. STI's HyperSpectral Diagnostic Imaging (HSDI) cervical instrument is used for the early detection of uterine cervical cancer. A Computer-Aided-Diagnostic (CAD) system is being developed to aid the physician with the diagnosis of pre-cancerous and cancerous tissue regions. The CAD system uses the fusion of multiple data sources to optimize its performance. The key enabling technology for the data fusion is image registration. The difficulty lies in the image registration of fluorescence and reflectance hyperspectral data due to the occurrence of soft tissue movement and the limited resemblance of these types of imagery. The presented approach is based on embedding a reflectance image in the fluorescence hyperspectral imagery. Having a reflectance image in both data sets resolves the resemblance problem and thereby enables the use of elastic image registration algorithms required to compensate for soft tissue movements. Several methods of embedding the reflectance image in the fluorescence hyperspectral imagery are described. Initial experiments with human subject data are presented where a reflectance image is embedded in the fluorescence hyperspectral imagery.

  9. Computer Assisted Operations: Registration Records, Schedules

    ERIC Educational Resources Information Center

    College and University, 1977

    1977-01-01

    Proceedings of AACRAO's 63rd annual meeting cover: computer networking in small colleges; continuous registration; computer logic; computerized academic record overview; on-line registration systems; and analysis of registration and records systems. (LBH)

  10. Coarse Point Cloud Registration by Egi Matching of Voxel Clusters

    NASA Astrophysics Data System (ADS)

    Wang, Jinhu; Lindenbergh, Roderik; Shen, Yueqian; Menenti, Massimo

    2016-06-01

    Laser scanning samples the surface geometry of objects efficiently and records versatile information as point clouds. However, often more scans are required to fully cover a scene. Therefore, a registration step is required that transforms the different scans into a common coordinate system. The registration of point clouds is usually conducted in two steps, i.e. coarse registration followed by fine registration. In this study an automatic marker-free coarse registration method for pair-wise scans is presented. First the two input point clouds are re-sampled as voxels and dimensionality features of the voxels are determined by principal component analysis (PCA). Then voxel cells with the same dimensionality are clustered. Next, the Extended Gaussian Image (EGI) descriptor of those voxel clusters are constructed using significant eigenvectors of each voxel in the cluster. Correspondences between clusters in source and target data are obtained according to the similarity between their EGI descriptors. The random sampling consensus (RANSAC) algorithm is employed to remove outlying correspondences until a coarse alignment is obtained. If necessary, a fine registration is performed in a final step. This new method is illustrated on scan data sampling two indoor scenarios. The results of the tests are evaluated by computing the point to point distance between the two input point clouds. The presented two tests resulted in mean distances of 7.6 mm and 9.5 mm respectively, which are adequate for fine registration.

  11. A Novel Technique for Prealignment in Multimodality Medical Image Registration

    PubMed Central

    Zhou, Wu; Zhang, Lijuan; Xie, Yaoqin; Liang, Changhong

    2014-01-01

    Image pair is often aligned initially based on a rigid or affine transformation before a deformable registration method is applied in medical image registration. Inappropriate initial registration may compromise the registration speed or impede the convergence of the optimization algorithm. In this work, a novel technique was proposed for prealignment in both monomodality and multimodality image registration based on statistical correlation of gradient information. A simple and robust algorithm was proposed to determine the rotational differences between two images based on orientation histogram matching accumulated from local orientation of each pixel without any feature extraction. Experimental results showed that it was effective to acquire the orientation angle between two unregistered images with advantages over the existed method based on edge-map in multimodalities. Applying the orientation detection into the registration of CT/MR, T1/T2 MRI, and monomadality images with respect to rigid and nonrigid deformation improved the chances of finding the global optimization of the registration and reduced the search space of optimization. PMID:25162024

  12. Promoting Competence Through Voter Registration.

    ERIC Educational Resources Information Center

    Hanrahan, Mary; And Others

    1986-01-01

    Describes a voter registration drive undertaken by a department of social work within a major medical teaching hospital. Provides highlights of the registration effort and several clinical vignettes that illustrate the meaning of the drive to psychiatric patients. Implications for social work and for the education of social work trainees are…

  13. Target error for image-to-physical space registration: preliminary clinical results using laser range scanning

    NASA Astrophysics Data System (ADS)

    Cao, Aize; Miga, Michael I.; Dumpuri, P.; Ding, S.; Dawant, B. M.; Thompson, R. C.

    2007-03-01

    In this paper, preliminary results from an image-to-physical space registration platform are presented. The current platform employs traditional and novel methods of registration which use a variety of data sources to include: traditional synthetic skin-fiducial point-based registration, surface registration based on facial contours, brain feature point-based registration, brain vessel-to-vessel registration, and a more comprehensive cortical surface registration method that utilizes both geometric and intensity information from both the image volume and physical patient. The intraoperative face and cortical surfaces were digitized using a laser range scanner (LRS) capable of producing highly resolved textured point clouds. In two in vivo cases, a series of registrations were performed using these techniques and compared within the context of a true target error. One of the advantages of using a textured point cloud data stream is that true targets among the physical cortical surface and the preoperative image volume can be identified and used to assess image-to-physical registration methods. The results suggest that iterative closest point (ICP) method for intraoperative face surface registration is equivalent to point-based registration (PBR) method of skin fiducial markers. With regard to the initial image and physical space registration, for patient 1, mean target registration error (TRE) were 3.1+/-0.4 mm and 3.6 +/-0.9 mm for face ICP and skin fiducial PBR, respectively. For patient 2, the mean TRE were 5.7 +/-1.3 mm, and 6.6 +/-0.9 mm for face ICP and skin fiducial PBR, respectively. With regard to intraoperative cortical surface registration, SurfaceMI outperformed feature based PBR and vessel ICP with 1.7+/-1.8 mm for patient 1. For patient 2, the best result was achieved by using vessel ICP with 1.9+/-0.5 mm.

  14. Automatic registration of satellite imagery

    NASA Technical Reports Server (NTRS)

    Fonseca, Leila M. G.; Costa, Max H. M.; Manjunath, B. S.; Kenney, C.

    1997-01-01

    Image registration is one of the basic image processing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-sensor/multi-spectral images has become an important issue. A wide range of registration techniques has been developed for many different types of applications and data. The objective of this paper is to present an automatic registration algorithm which uses a multiresolution analysis procedure based upon the wavelet transform. The procedure is completely automatic and relies on the grey level information content of the images and their local wavelet transform modulus maxima. The registration algorithm is very simple and easy to apply because it needs basically one parameter. We have obtained very encouraging results on test data sets from the TM and SPOT sensor images of forest, urban and agricultural areas.

  15. Homographic Patch Feature Transform: A Robustness Registration for Gastroscopic Surgery

    PubMed Central

    Wang, Bin; Liu, Jiquan; Duan, Huilong; Dai, Ning; Si, Jianmin

    2016-01-01

    Image registration is a key component of computer assistance in image guided surgery, and it is a challenging topic in endoscopic environments. In this study, we present a method for image registration named Homographic Patch Feature Transform (HPFT) to match gastroscopic images. HPFT can be used for tracking lesions and augmenting reality applications during gastroscopy. Furthermore, an overall evaluation scheme is proposed to validate the precision, robustness and uniformity of the registration results, which provides a standard for rejection of false matching pairs from corresponding results. Finally, HPFT is applied for processing in vivo gastroscopic data. The experimental results show that HPFT has stable performance in gastroscopic applications. PMID:27054567

  16. Serial Scanning and Registration of High Resolution Quantitative Computed Tomography Volume Scans for the Determination of Local Bone Density Changes

    NASA Technical Reports Server (NTRS)

    Whalen, Robert T.; Napel, Sandy; Yan, Chye H.

    1996-01-01

    Progress in development of the methods required to study bone remodeling as a function of time is reported. The following topics are presented: 'A New Methodology for Registration Accuracy Evaluation', 'Registration of Serial Skeletal Images for Accurately Measuring Changes in Bone Density', and 'Precise and Accurate Gold Standard for Multimodality and Serial Registration Method Evaluations.'

  17. INTER-GROUP IMAGE REGISTRATION BY HIERARCHICAL GRAPH SHRINKAGE

    PubMed Central

    Ying, Shihui; Wu, Guorong; Liao, Shu; Shen, Dinggang

    2013-01-01

    In this paper, we propose a novel inter-group image registration method to register different groups of images (e.g., young and elderly brains) simultaneously. Specifically, we use a hierarchical two-level graph to model the distribution of entire images on the manifold, with intra-graph representing the image distribution in each group and the inter-graph describing the relationship between two groups. Then the procedure of inter-group registration is formulated as a dynamic evolution of graph shrinkage. The advantage of our method is that the topology of entire image distribution is explored to guide the image registration. In this way, each image coordinates with its neighboring images on the manifold to deform towards the population center, by following the deformation pathway simultaneously optimized within the graph. Our proposed method has been also compared with other state-of-the-art inter-group registration methods, where our method achieves better registration results in terms of registration accuracy and robustness. PMID:24443692

  18. 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

  19. The Role of Registration in Accurate Surgical Guidance

    PubMed Central

    Fitzpatrick, J. Michael

    2016-01-01

    Registration is presented as the central issue of surgical guidance. The focus is on the accuracy of approaches employed today, all of which use pre-operative images to guide surgery on rigid anatomy. The three most well established approaches to guidance—the stereotactic frame, point fiducials, and surface matching—are examined in detail, along with two new approaches based on microstereotactic frames. It is shown that each method relies on the registration of points in the image to corresponding points in the operating room, and therefore that the error patterns associated with point registration are similar for all of them. Three types of registration error—fiducial localization error (FLE), fiducial registration error (FRE), and target registration error (TRE) are highlighted, as well as two additional guidance errors—target localization error, and total targeting error, the latter of which is the overall error of the guidance system. Statistical relationships between TRE and FLE, between FRE and FLE, and among TRE, TLE and TTE are given. Finally some myths concerning fiducial registration are highlighted. PMID:20718266

  20. Multi-modal robust inverse-consistent linear registration.

    PubMed

    Wachinger, Christian; Golland, Polina; Magnain, Caroline; Fischl, Bruce; Reuter, Martin

    2015-04-01

    Registration performance can significantly deteriorate when image regions do not comply with model assumptions. Robust estimation improves registration accuracy by reducing or ignoring the contribution of voxels with large intensity differences, but existing approaches are limited to monomodal registration. In this work, we propose a robust and inverse-consistent technique for cross-modal, affine image registration. The algorithm is derived from a contextual framework of image registration. The key idea is to use a modality invariant representation of images based on local entropy estimation, and to incorporate a heteroskedastic noise model. This noise model allows us to draw the analogy to iteratively reweighted least squares estimation and to leverage existing weighting functions to account for differences in local information content in multimodal registration. Furthermore, we use the nonparametric windows density estimator to reliably calculate entropy of small image patches. Finally, we derive the Gauss-Newton update and show that it is equivalent to the efficient second-order minimization for the fully symmetric registration approach. We illustrate excellent performance of the proposed methods on datasets containing outliers for alignment of brain tumor, full head, and histology images. PMID:25470798

  1. Three-dimensional warping registration of the pelvis and prostate

    NASA Astrophysics Data System (ADS)

    Fei, Baowei; Kemper, Corey; Wilson, David L.

    2002-05-01

    We are investigating interventional MRI guided radio- frequency (RF) thermal ablation for the minimally invasive treatment of prostate cancer. Among many potential applications of registration, we wish to compare registered MR images acquired before and immediately after RF ablation in order to determine whether a tumor is adequately treated. Warping registration is desired to correct for potential deformations of the pelvic region and movement of the prostate. We created a two-step, three-dimensional (3D) registration algorithm using mutual information and thin plate spline (TPS) warping for MR images. First, automatic rigid body registration was used to capture the global transformation. Second, local warping registration was applied. Interactively placed control points were automatically optimized by maximizing the mutual information of corresponding voxels in small volumes of interest and by using a 3D TPS to express the deformation throughout the image volume. Images were acquired from healthy volunteers in different conditions simulating potential applications. A variety of evaluation methods showed that warping consistently improved registration for volume pairs whenever patient position or condition was purposely changed between acquisitions. A TPS transformation based on 180 control points generated excellent warping throughout the pelvis following rigid body registration. The prostate centroid displacement for a typical volume pair was reduced from 3.4 mm to 0.6 mm when warping was added.

  2. 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.

  3. The role of registration in accurate surgical guidance.

    PubMed

    Fitzpatrick, J M

    2010-01-01

    Registration is presented as the central issue of surgical guidance. The focus is on the accuracy of approaches employed today, all of which use pre-operative images to guide surgery on rigid anatomy. The three most well-established approaches to guidance, namely the stereotactic frame, point fiducials, and surface matching, are examined in detail, together with two new approaches based on microstereotactic frames. It is shown that each method relies on the registration of points in the image to corresponding points in the operating room, and therefore that the error patterns associated with point registration are similar for all of them. Three types of registration error, namely fiducial localization error (FLE), fiducial registration error (FRE), and target registration error (TRE), are highlighted, as well as two additional guidance errors, namely target localization error and total targeting error, the latter of which is the overall error of the guidance system. Statistical relationships between TRE and FLE, between FRE and FLE, and between TRE, TLE, and TTE are given. Finally some myths concerning fiducial registration are highlighted. PMID:20718266

  4. Multi-Modal Robust Inverse-Consistent Linear Registration

    PubMed Central

    Wachinger, Christian; Golland, Polina; Magnain, Caroline; Fischl, Bruce; Reuter, Martin

    2016-01-01

    Registration performance can significantly deteriorate when image regions do not comply with model assumptions. Robust estimation improves registration accuracy by reducing or ignoring the contribution of voxels with large intensity differences, but existing approaches are limited to monomodal registration. In this work, we propose a robust and inverse-consistent technique for crossmodal, affine image registration. The algorithm is derived from a contextual framework of image registration. The key idea is to use a modality invariant representation of images based on local entropy estimation, and to incorporate a heteroskedastic noise model. This noise model allows us to draw the analogy to iteratively reweighted least squares estimation and to leverage existing weighting functions to account for differences in local information content in multimodal registration. Furthermore, we use the nonparametric windows density estimator to reliably calculate entropy of small image patches. Finally, we derive the Gauss–Newton update and show that it is equivalent to the efficient secondorder minimization for the fully symmetric registration approach. We illustrate excellent performance of the proposed methods on datasets containing outliers for alignment of brain tumor, full head, and histology images. PMID:25470798

  5. Shearlet Features for Registration of Remotely Sensed Multitemporal Images

    NASA Technical Reports Server (NTRS)

    Murphy, James M.; Le Moigne, Jacqueline

    2015-01-01

    We investigate the role of anisotropic feature extraction methods for automatic image registration of remotely sensed multitemporal images. Building on the classical use of wavelets in image registration, we develop an algorithm based on shearlets, a mathematical generalization of wavelets that offers increased directional sensitivity. Initial experimental results on LANDSAT images are presented, which indicate superior performance of the shearlet algorithm when compared to classical wavelet algorithms.

  6. 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

  7. Comparative Study of Two Automatic Registration Algorithms

    NASA Astrophysics Data System (ADS)

    Grant, D.; Bethel, J.; Crawford, M.

    2013-10-01

    The Iterative Closest Point (ICP) algorithm is prevalent for the automatic fine registration of overlapping pairs of terrestrial laser scanning (TLS) data. This method along with its vast number of variants, obtains the least squares parameters that are necessary to align the TLS data by minimizing some distance metric between the scans. The ICP algorithm uses a "model-data" concept in which the scans obtain differential treatment in the registration process depending on whether they were assigned to be the "model" or "data". For each of the "data" points, corresponding points from the "model" are sought. Another concept of "symmetric correspondence" was proposed in the Point-to-Plane (P2P) algorithm, where both scans are treated equally in the registration process. The P2P method establishes correspondences on both scans and minimizes the point-to-plane distances between the scans by simultaneously considering the stochastic properties of both scans. This paper studies both the ICP and P2P algorithms in terms of their consistency in registration parameters for pairs of TLS data. The question being investigated in this paper is, should scan A be registered to scan B, will the parameters be the same if scan B were registered to scan A? Experiments were conducted with eight pairs of real TLS data which were registered by the two algorithms in the forward (scan A to scan B) and backward (scan B to scan A) modes and the results were compared. The P2P algorithm was found to be more consistent than the ICP algorithm. The differences in registration accuracy between the forward and backward modes were negligible when using the P2P algorithm (mean difference of 0.03 mm). However, the ICP had a mean difference of 4.26 mm. Each scan was also transformed by the forward and backward parameters of the two algorithms and the misclosure computed. The mean misclosure for the P2P algorithm was 0.80 mm while that for the ICP algorithm was 5.39 mm. The conclusion from this study is

  8. Overlay improvement by exposure map based mask registration optimization

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  9. MR to CT registration of brains using image synthesis

    NASA Astrophysics Data System (ADS)

    Roy, Snehashis; Carass, Aaron; Jog, Amod; Prince, Jerry L.; Lee, Junghoon

    2014-03-01

    Computed tomography (CT) is the preferred imaging modality for patient dose calculation for radiation therapy. Magnetic resonance (MR) imaging (MRI) is used along with CT to identify brain structures due to its superior soft tissue contrast. Registration of MR and CT is necessary for accurate delineation of the tumor and other structures, and is critical in radiotherapy planning. Mutual information (MI) or its variants are typically used as a similarity metric to register MRI to CT. However, unlike CT, MRI intensity does not have an accepted calibrated intensity scale. Therefore, MI-based MR-CT registration may vary from scan to scan as MI depends on the joint histogram of the images. In this paper, we propose a fully automatic framework for MR-CT registration by synthesizing a synthetic CT image from MRI using a co-registered pair of MR and CT images as an atlas. Patches of the subject MRI are matched to the atlas and the synthetic CT patches are estimated in a probabilistic framework. The synthetic CT is registered to the original CT using a deformable registration and the computed deformation is applied to the MRI. In contrast to most existing methods, we do not need any manual intervention such as picking landmarks or regions of interests. The proposed method was validated on ten brain cancer patient cases, showing 25% improvement in MI and correlation between MR and CT images after registration compared to state-of-the-art registration methods.

  10. Skeleton Graph Matching vs. Maximum Weight Cliques aorta registration techniques.

    PubMed

    Czajkowska, Joanna; Feinen, C; Grzegorzek, M; Raspe, M; Wickenhöfer, R

    2015-12-01

    Vascular diseases are one of the most challenging health problems in developed countries. Past as well as ongoing research activities often focus on efficient, robust and fast aorta segmentation, and registration techniques. According to this needs our study targets an abdominal aorta registration method. The investigated algorithms make it possible to efficiently segment and register abdominal aorta in pre- and post-operative Computed Tomography (CT) data. In more detail, a registration technique using the Path Similarity Skeleton Graph Matching (PSSGM), as well as Maximum Weight Cliques (MWCs) are employed to realise the matching based on Computed Tomography data. The presented approaches make it possible to match characteristic voxels belonging to the aorta from different Computed Tomography (CT) series. It is particularly useful in the assessment of the abdominal aortic aneurysm treatment by visualising the correspondence between the pre- and post-operative CT data. The registration results have been tested on the database of 18 contrast-enhanced CT series, where the cross-registration analysis has been performed producing 153 matching examples. All the registration results achieved with our system have been verified by an expert. The carried out analysis has highlighted the advantage of the MWCs technique over the PSSGM method. The verification phase proves the efficiency of the MWCs approach and encourages to further develop this methods. PMID:26099640

  11. 7 CFR 800.34 - Registration fee.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 7 2010-01-01 2010-01-01 false Registration fee. 800.34 Section 800.34 Agriculture... ADMINISTRATION (FEDERAL GRAIN INSPECTION SERVICE), DEPARTMENT OF AGRICULTURE GENERAL REGULATIONS Registration § 800.34 Registration fee. An applicant shall submit the registration fee prescribed in § 800.71...

  12. 9 CFR 381.179 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 9 Animals and Animal Products 2 2011-01-01 2011-01-01 false Registration. 381.179 Section 381.179... CERTIFICATION POULTRY PRODUCTS INSPECTION REGULATIONS Records, Registration, and Reports § 381.179 Registration... effective date. All information submitted shall be current and correct. The registration form shall...

  13. 7 CFR 800.34 - Registration fee.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 7 Agriculture 7 2011-01-01 2011-01-01 false Registration fee. 800.34 Section 800.34 Agriculture... ADMINISTRATION (FEDERAL GRAIN INSPECTION SERVICE), DEPARTMENT OF AGRICULTURE GENERAL REGULATIONS Registration § 800.34 Registration fee. An applicant shall submit the registration fee prescribed in § 800.71...

  14. 44 CFR 206.112 - Registration period.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 44 Emergency Management and Assistance 1 2011-10-01 2011-10-01 false Registration period. 206.112... Households § 206.112 Registration period. (a) Initial period. The standard FEMA registration period is 60...) Extension of the registration period. The regional administrator or his/her designee may extend...

  15. 27 CFR 17.21 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2011-04-01 2011-04-01 false Registration. 17.21... PRODUCTS Registration § 17.21 Registration. Every person claiming drawback under this part must register annually as a nonbeverage domestic drawback claimant. Registration will be accomplished when the...

  16. 32 CFR 634.19 - Registration policy.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 4 2011-07-01 2011-07-01 false Registration policy. 634.19 Section 634.19... CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Motor Vehicle Registration § 634.19 Registration... registration of off-road vehicles and bicycles under a separate local system. (c) Commanders can grant...

  17. 27 CFR 17.21 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Registration. 17.21... PRODUCTS Registration § 17.21 Registration. Every person claiming drawback under this part must register annually as a nonbeverage domestic drawback claimant. Registration will be accomplished when the...

  18. 32 CFR 634.19 - Registration policy.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 4 2010-07-01 2010-07-01 true Registration policy. 634.19 Section 634.19... CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Motor Vehicle Registration § 634.19 Registration... registration of off-road vehicles and bicycles under a separate local system. (c) Commanders can grant...

  19. 28 CFR 5.200 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Registration. 5.200 Section 5.200 Judicial Administration DEPARTMENT OF JUSTICE ADMINISTRATION AND ENFORCEMENT OF FOREIGN AGENTS REGISTRATION ACT OF 1938, AS AMENDED § 5.200 Registration. (a) Registration under the Act is accomplished by...

  20. 28 CFR 5.200 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 28 Judicial Administration 1 2011-07-01 2011-07-01 false Registration. 5.200 Section 5.200 Judicial Administration DEPARTMENT OF JUSTICE ADMINISTRATION AND ENFORCEMENT OF FOREIGN AGENTS REGISTRATION ACT OF 1938, AS AMENDED § 5.200 Registration. (a) Registration under the Act is accomplished by...

  1. 9 CFR 381.179 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Registration. 381.179 Section 381.179... CERTIFICATION POULTRY PRODUCTS INSPECTION REGULATIONS Records, Registration, and Reports § 381.179 Registration... effective date. All information submitted shall be current and correct. The registration form shall...

  2. 40 CFR 79.13 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... OF FUELS AND FUEL ADDITIVES Fuel Registration Procedures § 79.13 Registration. (a) If the Administrator determines that a manufacturer has submitted an application for registration of a designated fuel... the fuel and notify the fuel manufacturer of such registration. (b) The Administrator shall maintain...

  3. 40 CFR 79.13 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... OF FUELS AND FUEL ADDITIVES Fuel Registration Procedures § 79.13 Registration. (a) If the Administrator determines that a manufacturer has submitted an application for registration of a designated fuel... the fuel and notify the fuel manufacturer of such registration. (b) The Administrator shall maintain...

  4. Sensor registration using airlanes: maximum likelihood solution

    NASA Astrophysics Data System (ADS)

    Ong, Hwa-Tung

    2004-01-01

    In this contribution, the maximum likelihood estimation of sensor registration parameters, such as range, azimuth and elevation biases in radar measurements, using airlane information is proposed and studied. The motivation for using airlane information for sensor registration is that it is freely available as a source of reference and it provides an alternative to conventional techniques that rely on synchronised and correctly associated measurements from two or more sensors. In the paper, the problem is first formulated in terms of a measurement model that is a nonlinear function of the unknown target state and sensor parameters, plus sensor noise. A probabilistic model of the target state is developed based on airlane information. The maximum likelihood and also maximum a posteriori solutions are given. The Cramer-Rao lower bound is derived and simulation results are presented for the case of estimating the biases in radar range, azimuth and elevation measurements. The accuracy of the proposed method is compared against the Cramer-Rao lower bound and that of an existing two-sensor alignment method. It is concluded that sensor registration using airlane information is a feasible alternative to existing techniques.

  5. Sensor registration using airlanes: maximum likelihood solution

    NASA Astrophysics Data System (ADS)

    Ong, Hwa-Tung

    2003-12-01

    In this contribution, the maximum likelihood estimation of sensor registration parameters, such as range, azimuth and elevation biases in radar measurements, using airlane information is proposed and studied. The motivation for using airlane information for sensor registration is that it is freely available as a source of reference and it provides an alternative to conventional techniques that rely on synchronised and correctly associated measurements from two or more sensors. In the paper, the problem is first formulated in terms of a measurement model that is a nonlinear function of the unknown target state and sensor parameters, plus sensor noise. A probabilistic model of the target state is developed based on airlane information. The maximum likelihood and also maximum a posteriori solutions are given. The Cramer-Rao lower bound is derived and simulation results are presented for the case of estimating the biases in radar range, azimuth and elevation measurements. The accuracy of the proposed method is compared against the Cramer-Rao lower bound and that of an existing two-sensor alignment method. It is concluded that sensor registration using airlane information is a feasible alternative to existing techniques.

  6. Hierarchical model-based interferometric synthetic aperture radar image registration

    NASA Astrophysics Data System (ADS)

    Wang, Yang; Huang, Haifeng; Dong, Zhen; Wu, Manqing

    2014-01-01

    With the rapid development of spaceborne interferometric synthetic aperture radar technology, classical image registration methods are incompetent for high-efficiency and high-accuracy masses of real data processing. Based on this fact, we propose a new method. This method consists of two steps: coarse registration that is realized by cross-correlation algorithm and fine registration that is realized by hierarchical model-based algorithm. Hierarchical model-based algorithm is a high-efficiency optimization algorithm. The key features of this algorithm are a global model that constrains the overall structure of the motion estimated, a local model that is used in the estimation process, and a coarse-to-fine refinement strategy. Experimental results from different kinds of simulated and real data have confirmed that the proposed method is very fast and has high accuracy. Comparing with a conventional cross-correlation method, the proposed method provides markedly improved performance.

  7. 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

  8. Visible and infrared image registration based on visual salient features

    NASA Astrophysics Data System (ADS)

    Wu, Feihong; Wang, Bingjian; Yi, Xiang; Li, Min; Hao, Jingya; Qin, Hanlin; Zhou, Huixin

    2015-09-01

    In order to improve the precision of visible and infrared (VIS/IR) image registration, an image registration method based on visual salient (VS) features is presented. First, a VS feature detector based on the modified visual attention model is presented to extract VS points. Because the iterative, within-feature competition method used in visual attention models is time consuming, an alternative fast visual salient (FVS) feature detector is proposed to make VS features more efficient. Then, a descriptor-rearranging (DR) strategy is adopted to describe feature points. This strategy combines information of both IR image and its negative image to overcome the contrast reverse problem between VIS and IR images, making it easier to find the corresponding points on VIS/IR images. Experiments show that both VS and FVS detectors have higher repeatability scores than scale invariant feature transform in the cases of blurring, brightness change, JPEG compression, noise, and viewpoint, except big scale change. The combination of VS detector and DR registration strategy can achieve precise image registration, but it is time-consuming. The combination of FVS detector and DR registration strategy can also reach a good registration of VIS/IR images but in a shorter time.

  9. 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.

  10. Registration algorithm of point clouds based on multiscale normal features

    NASA Astrophysics Data System (ADS)

    Lu, Jun; Peng, Zhongtao; Su, Hang; Xia, GuiHua

    2015-01-01

    The point cloud registration technology for obtaining a three-dimensional digital model is widely applied in many areas. To improve the accuracy and speed of point cloud registration, a registration method based on multiscale normal vectors is proposed. The proposed registration method mainly includes three parts: the selection of key points, the calculation of feature descriptors, and the determining and optimization of correspondences. First, key points are selected from the point cloud based on the changes of magnitude of multiscale curvatures obtained by using principal components analysis. Then the feature descriptor of each key point is proposed, which consists of 21 elements based on multiscale normal vectors and curvatures. The correspondences in a pair of two point clouds are determined according to the descriptor's similarity of key points in the source point cloud and target point cloud. Correspondences are optimized by using a random sampling consistency algorithm and clustering technology. Finally, singular value decomposition is applied to optimized correspondences so that the rigid transformation matrix between two point clouds is obtained. Experimental results show that the proposed point cloud registration algorithm has a faster calculation speed, higher registration accuracy, and better antinoise performance.

  11. Globally consistent registration of terrestrial laser scans via graph optimization

    NASA Astrophysics Data System (ADS)

    Theiler, Pascal Willy; Wegner, Jan Dirk; Schindler, Konrad

    2015-11-01

    In this paper we present a framework for the automatic registration of multiple terrestrial laser scans. The proposed method can handle arbitrary point clouds with reasonable pairwise overlap, without knowledge about their initial orientation and without the need for artificial markers or other specific objects. The framework is divided into a coarse and a fine registration part, which each start with pairwise registration and then enforce consistent global alignment across all scans. While we put forward a complete, functional registration system, the novel contribution of the paper lies in the coarse global alignment step. Merging multiple scans into a consistent network creates loops along which the relative transformations must add up. We pose the task of finding a global alignment as picking the best candidates from a set of putative pairwise registrations, such that they satisfy the loop constraints. This yields a discrete optimization problem that can be solved efficiently with modern combinatorial methods. Having found a coarse global alignment in this way, the framework proceeds by pairwise refinement with standard ICP, followed by global refinement to evenly spread the residual errors. The framework was tested on six challenging, real-world datasets. The discrete global alignment step effectively detects, removes and corrects failures of the pairwise registration procedure, finally producing a globally consistent coarse scan network which can be used as initial guess for the highly non-convex refinement. Our overall system reaches success rates close to 100% at acceptable runtimes < 1 h, even in challenging conditions such as scanning in the forest.

  12. [Registration of ethnicity allowed with conditions].

    PubMed

    Ploem, M C Corrette

    2009-01-01

    Registration of an individual's ethnicity is, in the light of the potential risks of stigmatization and discrimination, rightfully considered a sensitive issue. Traditionally, privacy legislation offers special legal protection in the collection, registration etc. of data relating to race and ethnic background. However, if it can be established that registration of ethnicity is necessary for providing good care, registration is lawful. However, registration for health research purposes requires the explicit consent of the persons involved. PMID:19785803

  13. 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

  14. Research on registration algorithm for check seal verification

    NASA Astrophysics Data System (ADS)

    Wang, Shuang; Liu, Tiegen

    2008-03-01

    Nowadays seals play an important role in China. With the development of social economy, the traditional method of manual check seal identification can't meet the need s of banking transactions badly. This paper focus on pre-processing and registration algorithm for check seal verification using theory of image processing and pattern recognition. First of all, analyze the complex characteristics of check seals. To eliminate the difference of producing conditions and the disturbance caused by background and writing in check image, many methods are used in the pre-processing of check seal verification, such as color components transformation, linearity transform to gray-scale image, medium value filter, Otsu, close calculations and labeling algorithm of mathematical morphology. After the processes above, the good binary seal image can be obtained. On the basis of traditional registration algorithm, a double-level registration method including rough and precise registration method is proposed. The deflection angle of precise registration method can be precise to 0.1°. This paper introduces the concepts of difference inside and difference outside and use the percent of difference inside and difference outside to judge whether the seal is real or fake. The experimental results of a mass of check seals are satisfied. It shows that the methods and algorithmic presented have good robustness to noise sealing conditions and satisfactory tolerance of difference within class.

  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. Mammogram CAD, hybrid registration and iconic analysis

    NASA Astrophysics Data System (ADS)

    Boucher, A.; Cloppet, F.; Vincent, N.

    2013-03-01

    This paper aims to develop a computer aided diagnosis (CAD) based on a two-step methodology to register and analyze pairs of temporal mammograms. The concept of "medical file", including all the previous medical information on a patient, enables joint analysis of different acquisitions taken at different times, and the detection of significant modifications. The developed registration method aims to superimpose at best the different anatomical structures of the breast. The registration is designed in order to get rid of deformation undergone by the acquisition process while preserving those due to breast changes indicative of malignancy. In order to reach this goal, a referent image is computed from control points based on anatomical features that are extracted automatically. Then the second image of the couple is realigned on the referent image, using a coarse-to-fine approach according to expert knowledge that allows both rigid and non-rigid transforms. The joint analysis detects the evolution between two images representing the same scene. In order to achieve this, it is important to know the registration error limits in order to adapt the observation scale. The approach used in this paper is based on an image sparse representation. Decomposed in regular patterns, the images are analyzed under a new angle. The evolution detection problem has many practical applications, especially in medical images. The CAD is evaluated using recall and precision of differences in mammograms.

  17. Automated landmark-guided deformable image registration.

    PubMed

    Kearney, Vasant; Chen, Susie; Gu, Xuejun; Chiu, Tsuicheng; Liu, Honghuan; Jiang, Lan; Wang, Jing; Yordy, John; Nedzi, Lucien; Mao, Weihua

    2015-01-01

    The purpose of this work is to develop an automated landmark-guided deformable image registration (LDIR) algorithm between the planning CT and daily cone-beam CT (CBCT) with low image quality. This method uses an automated landmark generation algorithm in conjunction with a local small volume gradient matching search engine to map corresponding landmarks between the CBCT and the planning CT. The landmarks act as stabilizing control points in the following Demons deformable image registration. LDIR is implemented on graphics processing units (GPUs) for parallel computation to achieve ultra fast calculation. The accuracy of the LDIR algorithm has been evaluated on a synthetic case in the presence of different noise levels and data of six head and neck cancer patients. The results indicate that LDIR performed better than rigid registration, Demons, and intensity corrected Demons for all similarity metrics used. In conclusion, LDIR achieves high accuracy in the presence of multimodality intensity mismatch and CBCT noise contamination, while simultaneously preserving high computational efficiency. PMID:25479095

  18. Automated landmark-guided deformable image registration

    NASA Astrophysics Data System (ADS)

    Kearney, Vasant; Chen, Susie; Gu, Xuejun; Chiu, Tsuicheng; Liu, Honghuan; Jiang, Lan; Wang, Jing; Yordy, John; Nedzi, Lucien; Mao, Weihua

    2015-01-01

    The purpose of this work is to develop an automated landmark-guided deformable image registration (LDIR) algorithm between the planning CT and daily cone-beam CT (CBCT) with low image quality. This method uses an automated landmark generation algorithm in conjunction with a local small volume gradient matching search engine to map corresponding landmarks between the CBCT and the planning CT. The landmarks act as stabilizing control points in the following Demons deformable image registration. LDIR is implemented on graphics processing units (GPUs) for parallel computation to achieve ultra fast calculation. The accuracy of the LDIR algorithm has been evaluated on a synthetic case in the presence of different noise levels and data of six head and neck cancer patients. The results indicate that LDIR performed better than rigid registration, Demons, and intensity corrected Demons for all similarity metrics used. In conclusion, LDIR achieves high accuracy in the presence of multimodality intensity mismatch and CBCT noise contamination, while simultaneously preserving high computational efficiency.

  19. Optimization strategies for ultrasound volume registration

    NASA Astrophysics Data System (ADS)

    Zeeshan Ijaz, Umer; Prager, Richard W.; Gee, Andrew H.; Treece, Graham M.

    2010-08-01

    This paper considers registration of 3D ultrasound volumes acquired in multiple views for display in a single image volume. One way to acquire 3D data is to use a mechanically swept 3D probe. However, the usefulness of these probes is restricted by their limited field of view. This problem can be overcome by attaching a six-degree-of-freedom (DOF) position sensor to the probe, and displaying the information from multiple sweeps in their proper positions. However, an external six-DOF position sensor can be an inconvenience in a clinical setting. The objective of this paper is to propose a hybrid strategy that replaces the sensor with a combination of three-DOF image registration and an unobtrusive inertial sensor for measuring orientation. We examine a range of optimization algorithms and similarity measures for registration and compare them in in vitro and in vivo experiments. We register based on multiple reslice images rather than a whole voxel array. In this paper, we use a large number of reslices for improved reliability at the expense of computational speed. We have found that the Levenberg-Marquardt method is very fast but is not guaranteed to give the correct solution all the time. We conclude that normalized mutual information used in the Nelder-Mead simplex algorithm is potentially suitable for the registration task with an average execution time of around 5 min, in the majority of cases, with two restarts in a C++ implementation on a 3.0 GHz Intel Core 2 Duo CPU machine.

  20. Iterative edge- and wavelet-based image registration of AVHRR and GOES satellite imagery

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; El-Saleous, Nazmi; Vermote, Eric

    1997-01-01

    Most automatic registration methods are either correlation-based, feature-based, or a combination of both. Examples of features which can be utilized for automatic image registration are edges, regions, corners, or wavelet-extracted features. In this paper, we describe two proposed approaches, based on edge or edge-like features, which are very appropriate to highlight regions of interest such as coastlines. The two iterative methods utilize the Normalized Cross-Correlation of edge and wavelet features and are applied to such problems as image-to-map registration, landmarking, and channel-to-channel co-registration, utilizing test data, AVHRR data, as well as GOES image data.

  1. Virtual-real spatial information visualization registration using affine representations

    NASA Astrophysics Data System (ADS)

    Wu, Xueling; Ren, Fu; Du, Qingyun

    2009-10-01

    Virtual-real registration in Outdoor Augmented Reality is committed to enhance user's spatial cognition by overlaying virtual geographical objects on real scene. According to analyze fiducial detection registration method in indoor AR, for the purpose of avoiding complex and tedious process of position tracking and camera calibration in traditional registration methods, it puts forward and practices a virtual-real spatial information visualization registration method using affine representations. Based on the observation from Koenderink and van Doorn, Ullman and Basri in 1991 which is given a set of four or more non-coplanar 3D points, the projection of all points in the set can be computed as a linear combination of the projection of just four of the points, it sets up global affine coordinate system in light of world coordinates, camera coordinates and virtual coordinates and extracts four feature points from scene image and calculates the global affine coordinates of key points of virtual objects. Then according to a linear homogeneous coordinates of the four feature point's projection, it calculates projection pixel coordinates of key points of virtual objects. In addition, it proposes an approach to obtain pixel relative depth for hidden surface removal. Finally, by a case study, it verifies the feasibility and efficiency of the registration methods. The method would not only explore a new research direction for Geographical Information Science, but also would provide location-based information and services for outdoor AR.

  2. Accelerating image registration of MRI by GPU-based parallel computation.

    PubMed

    Huang, Teng-Yi; Tang, Yu-Wei; Ju, Shiun-Ying

    2011-06-01

    Automatic image registration for MRI applications generally requires many iteration loops and is, therefore, a time-consuming task. This drawback prolongs data analysis and delays the workflow of clinical routines. Recent advances in the massively parallel computation of graphic processing units (GPUs) may be a solution to this problem. This study proposes a method to accelerate registration calculations, especially for the popular statistical parametric mapping (SPM) system. This study reimplemented the image registration of SPM system to achieve an approximately 14-fold increase in speed in registering single-modality intrasubject data sets. The proposed program is fully compatible with SPM, allowing the user to simply replace the original image registration library of SPM to gain the benefit of the computation power provided by commodity graphic processors. In conclusion, the GPU computation method is a practical way to accelerate automatic image registration. This technology promises a broader scope of application in the field of image registration. PMID:21531103

  3. Pydpiper: a flexible toolkit for constructing novel registration pipelines.

    PubMed

    Friedel, Miriam; van Eede, Matthijs C; Pipitone, Jon; Chakravarty, M Mallar; Lerch, Jason P

    2014-01-01

    Using neuroimaging technologies to elucidate the relationship between genotype and phenotype and brain and behavior will be a key contribution to biomedical research in the twenty-first century. Among the many methods for analyzing neuroimaging data, image registration deserves particular attention due to its wide range of applications. Finding strategies to register together many images and analyze the differences between them can be a challenge, particularly given that different experimental designs require different registration strategies. Moreover, writing software that can handle different types of image registration pipelines in a flexible, reusable and extensible way can be challenging. In response to this challenge, we have created Pydpiper, a neuroimaging registration toolkit written in Python. Pydpiper is an open-source, freely available software package that provides multiple modules for various image registration applications. Pydpiper offers five key innovations. Specifically: (1) a robust file handling class that allows access to outputs from all stages of registration at any point in the pipeline; (2) the ability of the framework to eliminate duplicate stages; (3) reusable, easy to subclass modules; (4) a development toolkit written for non-developers; (5) four complete applications that run complex image registration pipelines "out-of-the-box." In this paper, we will discuss both the general Pydpiper framework and the various ways in which component modules can be pieced together to easily create new registration pipelines. This will include a discussion of the core principles motivating code development and a comparison of Pydpiper with other available toolkits. We also provide a comprehensive, line-by-line example to orient users with limited programming knowledge and highlight some of the most useful features of Pydpiper. In addition, we will present the four current applications of the code. PMID:25126069

  4. Pydpiper: a flexible toolkit for constructing novel registration pipelines

    PubMed Central

    Friedel, Miriam; van Eede, Matthijs C.; Pipitone, Jon; Chakravarty, M. Mallar; Lerch, Jason P.

    2014-01-01

    Using neuroimaging technologies to elucidate the relationship between genotype and phenotype and brain and behavior will be a key contribution to biomedical research in the twenty-first century. Among the many methods for analyzing neuroimaging data, image registration deserves particular attention due to its wide range of applications. Finding strategies to register together many images and analyze the differences between them can be a challenge, particularly given that different experimental designs require different registration strategies. Moreover, writing software that can handle different types of image registration pipelines in a flexible, reusable and extensible way can be challenging. In response to this challenge, we have created Pydpiper, a neuroimaging registration toolkit written in Python. Pydpiper is an open-source, freely available software package that provides multiple modules for various image registration applications. Pydpiper offers five key innovations. Specifically: (1) a robust file handling class that allows access to outputs from all stages of registration at any point in the pipeline; (2) the ability of the framework to eliminate duplicate stages; (3) reusable, easy to subclass modules; (4) a development toolkit written for non-developers; (5) four complete applications that run complex image registration pipelines “out-of-the-box.” In this paper, we will discuss both the general Pydpiper framework and the various ways in which component modules can be pieced together to easily create new registration pipelines. This will include a discussion of the core principles motivating code development and a comparison of Pydpiper with other available toolkits. We also provide a comprehensive, line-by-line example to orient users with limited programming knowledge and highlight some of the most useful features of Pydpiper. In addition, we will present the four current applications of the code. PMID:25126069

  5. 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.

  6. Accuracy assessment of fluoroscopy-transesophageal echocardiography registration

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  7. Is Visual Registration Equivalent to Semiautomated Registration in Prostate Biopsy?

    PubMed Central

    Kwak, Jin Tae; Hong, Cheng William; Pinto, Peter A.; Williams, Molly; Xu, Sheng; Kruecker, Jochen; Yan, Pingkun; Turkbey, Baris; Choyke, Peter L.; Wood, Bradford J.

    2015-01-01

    In magnetic resonance iimaging- (MRI-) ultrasound (US) guided biopsy, suspicious lesions are identified on MRI, registered on US, and targeted during biopsy. The registration can be performed either by a human operator (visual registration) or by fusion software. Previous studies showed that software registration is fairly accurate in locating suspicious lesions and helps to improve the cancer detection rate. Here, the performance of visual registration was examined for ability to locate suspicious lesions defined on MRI. This study consists of 45 patients. Two operators with differing levels of experience (<1 and 18 years) performed visual registration. The overall spatial difference by the two operators in 72 measurements was 10.6 ± 6.0 mm. Each operator showed a spatial difference of 9.4 ± 5.1 mm (experienced; 39 lesions) and 12.1 ± 6.6 mm (inexperienced; 33 lesions), respectively. In a head-to-head comparison of the same 16 lesions from 12 patients, the spatial differences were 9.7 mm ± 4.9 mm (experienced) and 13.4 mm ± 7.4 mm (inexperienced). There were significant differences between the two operators (unpaired, P value = 0.042; paired, P value = 0.044). The substantial differences by the two operators suggest that visual registration could improperly and inaccurately target many tumors, thereby potentially leading to missed diagnosis or false characterization on pathology. PMID:25821799

  8. Evaluation of five non-rigid image registration algorithms using the NIREP framework

    NASA Astrophysics Data System (ADS)

    Wei, Ying; Christensen, Gary E.; Song, Joo Hyun; Rudrauf, David; Bruss, Joel; Kuhl, Jon G.; Grabowski, Thomas J.

    2010-03-01

    Evaluating non-rigid image registration algorithm performance is a difficult problem since there is rarely a "gold standard" (i.e., known) correspondence between two images. This paper reports the analysis and comparison of five non-rigid image registration algorithms using the Non-Rigid Image Registration Evaluation Project (NIREP) (www.nirep.org) framework. The NIREP framework evaluates registration performance using centralized databases of well-characterized images and standard evaluation statistics (methods) which are implemented in a software package. The performance of five non-rigid registration algorithms (Affine, AIR, Demons, SLE and SICLE) was evaluated using 22 images from two NIREP neuroanatomical evaluation databases. Six evaluation statistics (relative overlap, intensity variance, normalized ROI overlap, alignment of calcarine sulci, inverse consistency error and transitivity error) were used to evaluate and compare image registration performance. The results indicate that the Demons registration algorithm produced the best registration results with respect to the relative overlap statistic but produced nearly the worst registration results with respect to the inverse consistency statistic. The fact that one registration algorithm produced the best result for one criterion and nearly the worst for another illustrates the need to use multiple evaluation statistics to fully assess performance.

  9. Feasibility of Multimodal Deformable Registration for Head and Neck Tumor Treatment Planning

    SciTech Connect

    Fortunati, Valerio; Verhaart, René F.; Angeloni, Francesco; Lugt, Aad van der; Niessen, Wiro J.; Veenland, Jifke F.; Paulides, Margarethus M.; Walsum, Theo van

    2014-09-01

    Purpose: To investigate the feasibility of using deformable registration in clinical practice to fuse MR and CT images of the head and neck for treatment planning. Method and Materials: A state-of-the-art deformable registration algorithm was optimized, evaluated, and compared with rigid registration. The evaluation was based on manually annotated anatomic landmarks and regions of interest in both modalities. We also developed a multiparametric registration approach, which simultaneously aligns T1- and T2-weighted MR sequences to CT. This was evaluated and compared with single-parametric approaches. Results: Our results show that deformable registration yielded a better accuracy than rigid registration, without introducing unrealistic deformations. For deformable registration, an average landmark alignment of approximatively 1.7 mm was obtained. For all the regions of interest excluding the cerebellum and the parotids, deformable registration provided a median modified Hausdorff distance of approximatively 1 mm. Similar accuracies were obtained for the single-parameter and multiparameter approaches. Conclusions: This study demonstrates that deformable registration of head-and-neck CT and MR images is feasible, with overall a significanlty higher accuracy than for rigid registration.

  10. Can dental registrants use the Index of Orthodontic Treatment Need accurately? Part 1: Knowledge of IOTN among dental registrants.

    PubMed

    Jawad, Z; Bates, C; Hodge, T

    2016-05-27

    Aim To determine whether dental registrants can use the dental health component (DHC) and aesthetic component (AC) of the Index of Orthodontic Treatment Need (IOTN) 'accurately' to an acceptable level of agreement and diagnostic validity.Method Participants from six different registrant groups were asked to score the IOTN for 14 cases based on study models and photographs as well as completing a short questionnaire. Participants in the study were all recruited at study days and annual conferences. The main outcome measures include the different registrant groups IOTN scores compared to expert panel scores using kappa statistics. To assess for diagnostic validity, individual participants sensitivity and specificity scores were calculated.Result Overall, 229 registrants took part in the study. For the DHC the specialist orthodontist (SO), postgraduate orthodontic student (PGOS) and the qualified orthodontic therapist (QOT) groups achieved a mean kappa ≥0.60 indicating 'acceptable' agreement with the expert panel scores. The dental foundation trainee (DFT) and general dental practitioner (GDP) group achieved a mean kappa of 0.20 and 0.22 respectively indicating poor and fair agreement. The student orthodontic therapist (SOT) group achieved a mean kappa of 0.55 indicating moderate agreement. For the AC none of the registrant groups achieved an acceptable level of agreement with the mean kappa scores for the different groups ranging from kappa 0.13-0.21, indicating poor to fair agreement.Conclusion Overall agreement for the DHC was varied for the different registrant groups ranging from fair to substantial agreement. Registrants were better at applying the DHC compared to the AC with agreement ranging from poor to fair. More needs to done to help registrants use the IOTN more 'accurately'. PMID:27228933

  11. Nonrigid Medical Image Registration Based on Mesh Deformation Constraints

    PubMed Central

    Qiu, TianShuang; Guo, DongMei

    2013-01-01

    Regularizing the deformation field is an important aspect in nonrigid medical image registration. By covering the template image with a triangular mesh, this paper proposes a new regularization constraint in terms of connections between mesh vertices. The connection relationship is preserved by the spring analogy method. The method is evaluated by registering cerebral magnetic resonance imaging (MRI) image data obtained from different individuals. Experimental results show that the proposed method has good deformation ability and topology-preserving ability, providing a new way to the nonrigid medical image registration. PMID:23424604

  12. Automatic registration of serial mammary gland sections

    SciTech Connect

    Arganda-Carreras, Ignacio; Fernandez-Gonzalez, Rodrigo; Ortiz-de-Solorzano, Carlos

    2004-04-13

    We present two new methods for automatic registration of microscope images of consecutive tissue sections. They represent two possibilities for the first step in the 3-D reconstruction of histological structures from serially sectioned tissue blocks. The goal is to accurately align the sections in order to place every relevant shape contained in each image in front of its corresponding shape in the following section before detecting the structures of interest and rendering them in 3D. This is accomplished by finding the best rigid body transformation (translation and rotation) of the image being registered by maximizing a matching function based on the image content correlation. The first method makes use of the entire image information, whereas the second one uses only the information located at specific sites, as determined by the segmentation of the most relevant tissue structures. To reduce computing time, we use a multiresolution pyramidal approach that reaches the best registration transformation in increasing resolution steps. In each step, a subsampled version of the images is used. Both methods rely on a binary image which is a thresholded version of the Sobel gradients of the image (first method) or a set of boundaries manually or automatically obtained that define important histological structures of the sections. Then distance-transform of the binary image is computed. A proximity function is then calculated between the distance image of the image being registered and that of the reference image. The transformation providing a maximum of the proximity function is then used as the starting point of the following step. This is iterated until the registration error lies below a minimum value.

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

    SciTech Connect

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

    2009-10-15

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

  14. A Novel Ultrasound-Based Registration for Image-Guided Laparoscopic Liver Ablation.

    PubMed

    Fusaglia, Matteo; Tinguely, Pascale; Banz, Vanessa; Weber, Stefan; Lu, Huanxiang

    2016-08-01

    Background Patient-to-image registration is a core process of image-guided surgery (IGS) systems. We present a novel registration approach for application in laparoscopic liver surgery, which reconstructs in real time an intraoperative volume of the underlying intrahepatic vessels through an ultrasound (US) sweep process. Methods An existing IGS system for an open liver procedure was adapted, with suitable instrument tracking for laparoscopic equipment. Registration accuracy was evaluated on a realistic phantom by computing the target registration error (TRE) for 5 intrahepatic tumors. The registration work flow was evaluated by computing the time required for performing the registration. Additionally, a scheme for intraoperative accuracy assessment by visual overlay of the US image with preoperative image data was evaluated. Results The proposed registration method achieved an average TRE of 7.2 mm in the left lobe and 9.7 mm in the right lobe. The average time required for performing the registration was 12 minutes. A positive correlation was found between the intraoperative accuracy assessment and the obtained TREs. Conclusions The registration accuracy of the proposed method is adequate for laparoscopic intrahepatic tumor targeting. The presented approach is feasible and fast and may, therefore, not be disruptive to the current surgical work flow. PMID:26969718

  15. 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.

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

    SciTech Connect

    Kim, Youngjun; Li, Ruijiang; Na, Yong Hum; Xing, Lei; Lee, Rena

    2014-12-15

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

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

    SciTech Connect

    Inoue, Minoru; Yoshimura, Michio Sato, Sayaka; Nakamura, Mitsuhiro; Yamada, Masahiro; Hirata, Kimiko; Ogura, Masakazu; Hiraoka, Masahiro; Sasaki, Makoto; Fujimoto, Takahiro

    2015-04-15

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

  18. Nonrigid 2D registration of fluoroscopic coronary artery image sequence with layered motion

    NASA Astrophysics Data System (ADS)

    Park, Taewoo; Jung, Hoyup; Yun, Il Dong

    2016-03-01

    We present a new method for nonrigid registration of coronary artery models with layered motion information. 2D nonrigid registration method is proposed that brings layered motion information into correspondence with fluoroscopic angiograms. The registered model is overlaid on top of interventional angiograms to provide surgical assistance during image-guided chronic total occlusion procedures. The proposed methodology is divided into two parts: layered structures alignments and local nonrigid registration. In the first part, inpainting method is used to estimate a layered rigid transformation that aligns layered motion information. In the second part, a nonrigid registration method is implemented and used to compensate for any local shape discrepancy. Experimental evaluation conducted on a set of 7 fluoroscopic angiograms results in a reduced target registration error, which showed the effectiveness of the proposed method over single layered approach.

  19. Automatic deformable diffusion tensor registration for fiber population analysis.

    PubMed

    Irfanoglu, M O; Machiraju, R; Sammet, S; Pierpaoli, C; Knopp, M V

    2008-01-01

    In this work, we propose a novel method for deformable tensor-to-tensor registration of Diffusion Tensor Images. Our registration method models the distances in between the tensors with Geode-sic-Loxodromes and employs a version of Multi-Dimensional Scaling (MDS) algorithm to unfold the manifold described with this metric. Defining the same shape properties as tensors, the vector images obtained through MDS are fed into a multi-step vector-image registration scheme and the resulting deformation fields are used to reorient the tensor fields. Results on brain DTI indicate that the proposed method is very suitable for deformable fiber-to-fiber correspondence and DTI-atlas construction. PMID:18982704

  20. Automatic Deformable Diffusion Tensor Registration for Fiber Population Analysis

    PubMed Central

    Irfanoglu, M.O.; Machiraju, R.; Sammet, S.; Pierpaoli, C.; Knopp, M.V.

    2016-01-01

    In this work, we propose a novel method for deformable tensor–to–tensor registration of Diffusion Tensor Images. Our registration method models the distances in between the tensors with Geode-sic–Loxodromes and employs a version of Multi-Dimensional Scaling (MDS) algorithm to unfold the manifold described with this metric. Defining the same shape properties as tensors, the vector images obtained through MDS are fed into a multi–step vector–image registration scheme and the resulting deformation fields are used to reorient the tensor fields. Results on brain DTI indicate that the proposed method is very suitable for deformable fiber–to–fiber correspondence and DTI–atlas construction. PMID:18982704

  1. Vectorial total variation-based regularization for variational image registration.

    PubMed

    Chumchob, Noppadol

    2013-11-01

    To use interdependence between the primary components of the deformation field for smooth and non-smooth registration problems, the channel-by-channel total variation- or standard vectorial total variation (SVTV)-based regularization has been extended to a more flexible and efficient technique, allowing high quality regularization procedures. Based on this method, this paper proposes a fast nonlinear multigrid (NMG) method for solving the underlying Euler-Lagrange system of two coupled second-order nonlinear partial differential equations. Numerical experiments using both synthetic and realistic images not only confirm that the recommended VTV-based regularization yields better registration qualities for a wide range of applications than those of the SVTV-based regularization, but also that the proposed NMG method is fast, accurate, and reliable in delivering visually-pleasing registration results. PMID:23893729

  2. PCA-based groupwise image registration for quantitative MRI.

    PubMed

    Huizinga, W; Poot, D H J; Guyader, J-M; Klaassen, R; Coolen, B F; van Kranenburg, M; van Geuns, R J M; Uitterdijk, A; Polfliet, M; Vandemeulebroucke, J; Leemans, A; Niessen, W J; Klein, S

    2016-04-01

    Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or at multiple time points after injection of a contrast agent) and by fitting a qMRI signal model to the image intensities. Image registration is often necessary to compensate for misalignments due to subject motion and/or geometric distortions caused by the acquisition. However, large differences in image appearance make accurate image registration challenging. In this work, we propose a groupwise image registration method for compensating misalignment in qMRI. The groupwise formulation of the method eliminates the requirement of choosing a reference image, thus avoiding a registration bias. The method minimizes a cost function that is based on principal component analysis (PCA), exploiting the fact that intensity changes in qMRI can be described by a low-dimensional signal model, but not requiring knowledge on the specific acquisition model. The method was evaluated on 4D CT data of the lungs, and both real and synthetic images of five different qMRI applications: T1 mapping in a porcine heart, combined T1 and T2 mapping in carotid arteries, ADC mapping in the abdomen, diffusion tensor mapping in the brain, and dynamic contrast-enhanced mapping in the abdomen. Each application is based on a different acquisition model. The method is compared to a mutual information-based pairwise registration method and four other state-of-the-art groupwise registration methods. Registration accuracy is evaluated in terms of the precision of the estimated qMRI parameters, overlap of segmented structures, distance between corresponding landmarks, and smoothness of the deformation. In all qMRI applications the proposed method performed better than or equally well as

  3. Fundus image registration for vestibularis research

    NASA Astrophysics Data System (ADS)

    Ithapu, Vamsi K.; Fritsche, Armin; Oppelt, Ariane; Westhofen, Martin; Deserno, Thomas M.

    2010-03-01

    In research on vestibular nerve disorders, fundus images of both left and right eyes are acquired systematically to precisely assess the rotation of the eye ball that is induced by the rotation of entire head. The measurement is still carried out manually. Although various methods have been proposed for medical image registration, robust detection of rotation especially in images with varied quality in terms of illumination, aberrations, blur and noise still is challenging. This paper evaluates registration algorithms operating on different levels of semantics: (i) data-based using Fourier transform and log polar maps; (ii) point-based using scaled image feature transform (SIFT); (iii) edge-based using Canny edge maps; (iv) object-based using matched filters for vessel detection; (v) scene-based detecting papilla and macula automatically and (vi) manually by two independent medical experts. For evaluation, a database of 22 patients is used, where each of left and right eye images is captured in upright head position and in lateral tilt of +/-200. For 66 pairs of images (132 in total), the results are compared with ground truth, and the performance measures are tabulated. Best correctness of 89.3% were obtained using the pixel-based method and allowing 2.5° deviation from the manual measures. However, the evaluation shows that for applications in computer-aided diagnosis involving a large set of images with varied quality, like in vestibularis research, registration methods based on a single level of semantics are not sufficiently robust. A multi-level semantics approach will improve the results since failure occur on different images.

  4. Analytic differential approach for robust registration of rat brain histological images.

    PubMed

    Hsu, Wei-Yen

    2011-06-01

    Image registration is an important topic in medical image analysis. It is usually used to reconstruct 3D structure of tissues from a series of microscopic images. However, a variety of inherent factors may result in great differences between acquired slices during imaging even if they are adjacent. The common differences include the color difference and geometry discrepancy, which make the registration problem a difficult challenge. In this study, we propose a robust registration method to automatically reconstruct 3D volume data of the rat brain. It mainly consists of three procedures, including multiscale wavelet-based feature extraction, analytic robust point matching (ARPM), and registration refinement with feature-based modified Levenberg-Marquardt algorithm (FMLM). The product of gradient moduli in multi-scales is used to decide if extracted feature points are true according to the characteristic that features could exist in multiscale. The ARPM registration algorithm is proposed to speedily accomplish the registration of two point sets with different size by simultaneously evaluating the spatial correspondence and geometrical transformation. In addition, a FMLM method is also proposed to further refine registration results and achieve subpixel accuracy. The FMLM method converges much faster than most other methods due to its feature-based and nonlinear characteristic. The performance of proposed method is evaluated by comparing it with well-known thin-plate spline robust point matching (TPS-RPM) algorithm. The results indicate that ARPM-FMLM algorithm is a robust and fast method in image registration. PMID:20945464

  5. 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.

  6. A Local IDW Transformation Algorithm for Medical Image Registration

    NASA Astrophysics Data System (ADS)

    Cavoretto, Roberto; De Rossi, Alessandra

    2008-09-01

    In this paper we propose the use of a modified version of the Inverse Distance Weighted (IDW) method for landmark—based registration of medical images. More precisely, we consider radial basis functions (RBFs) as nodal functions in the modified IDW method, circumventing the drawback due to RBF global support.

  7. 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

  8. 75 FR 4383 - Pesticide Products: Registration Applications

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-01-27

    ... AGENCY Pesticide Products: Registration Applications AGENCY: Environmental Protection Agency (EPA). ACTION: Notice. SUMMARY: This notice announces receipt of applications to register pesticide products... comments by the comment period deadline identified. II. Registration Applications EPA received...

  9. Scope and applications of translation invariant wavelets to image registration

    NASA Technical Reports Server (NTRS)

    Chettri, Samir; LeMoigne, Jacqueline; Campbell, William

    1997-01-01

    The first part of this article introduces the notion of translation invariance in wavelets and discusses several wavelets that have this property. The second part discusses the possible applications of such wavelets to image registration. In the case of registration of affinely transformed images, we would conclude that the notion of translation invariance is not really necessary. What is needed is affine invariance and one way to do this is via the method of moment invariants. Wavelets or, in general, pyramid processing can then be combined with the method of moment invariants to reduce the computational load.

  10. Multimodal registration of retinal images using self organizing maps.

    PubMed

    Matsopoulos, George K; Asvestas, Pantelis A; Mouravliansky, Nikolaos A; Delibasis, Konstantinos K

    2004-12-01

    In this paper, an automatic method for registering multimodal retinal images is presented. The method consists of three steps: the vessel centerline detection and extraction of bifurcation points only in the reference image, the automatic correspondence of bifurcation points in the two images using a novel implementation of the self organizing maps and the extraction of the parameters of the affine transform using the previously obtained correspondences. The proposed registration algorithm was tested on 24 multimodal retinal pairs and the obtained results show an advantageous performance in terms of accuracy with respect to the manual registration. PMID:15575412

  11. Accurate and robust registration of high-speed railway viaduct point clouds using closing conditions and external geometric constraints

    NASA Astrophysics Data System (ADS)

    Ji, Zheng; Song, Mengxiao; Guan, Haiyan; Yu, Yongtao

    2015-08-01

    This paper proposes an automatic method for registering multiple laser scans without a control network. The proposed registration method first uses artificial targets to pair-wise register adjacent scans for initial transformation estimates; the proposed registration method then employs combined adjustments with closing conditions and external triangle constraints to globally register all scans along a long-range, high-speed railway corridor. The proposed registration method uses (1) closing conditions to eliminate registration errors that gradually accumulate as the length of a corridor (the number of scan stations) increases, and (2) external geometric constraints to ensure the shape correctness of an elongated high-speed railway. A 640-m high-speed railway viaduct with twenty-one piers is used to conduct experiments using our proposed registration method. A group of comparative experiments is undertaken to evaluate the robustness and efficiency of the proposed registration method to accurately register long-range corridors.

  12. 40 CFR 79.14 - Termination of registration of fuels.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... PROGRAMS (CONTINUED) REGISTRATION OF FUELS AND FUEL ADDITIVES Fuel Registration Procedures § 79.14 Termination of registration of fuels. Registration may be terminated by the Administrator if the...

  13. 40 CFR 79.14 - Termination of registration of fuels.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... PROGRAMS (CONTINUED) REGISTRATION OF FUELS AND FUEL ADDITIVES Fuel Registration Procedures § 79.14 Termination of registration of fuels. Registration may be terminated by the Administrator if the...

  14. Groupwise Image Registration Guided by a Dynamic Digraph of Images.

    PubMed

    Tang, Zhenyu; Fan, Yong

    2016-04-01

    For groupwise image registration, graph theoretic methods have been adopted for discovering the manifold of images to be registered so that accurate registration of images to a group center image can be achieved by aligning similar images that are linked by the shortest graph paths. However, the image similarity measures adopted to build a graph of images in the extant methods are essentially pairwise measures, not effective for capturing the groupwise similarity among multiple images. To overcome this problem, we present a groupwise image similarity measure that is built on sparse coding for characterizing image similarity among all input images and build a directed graph (digraph) of images so that similar images are connected by the shortest paths of the digraph. Following the shortest paths determined according to the digraph, images are registered to a group center image in an iterative manner by decomposing a large anatomical deformation field required to register an image to the group center image into a series of small ones between similar images. During the iterative image registration, the digraph of images evolves dynamically at each iteration step to pursue an accurate estimation of the image manifold. Moreover, an adaptive dictionary strategy is adopted in the groupwise image similarity measure to ensure fast convergence of the iterative registration procedure. The proposed method has been validated based on both simulated and real brain images, and experiment results have demonstrated that our method was more effective for learning the manifold of input images and achieved higher registration accuracy than state-of-the-art groupwise image registration methods. PMID:26585712

  15. 14 CFR 47.3 - Registration required.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Registration required. 47.3 Section 47.3... REGISTRATION General § 47.3 Registration required. (a) An aircraft may be registered under 49 U.S.C. 44103 only... person may operate an aircraft that is eligible for registration under 49 U.S.C. 44101-44104, unless...

  16. 14 CFR 47.3 - Registration required.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Registration required. 47.3 Section 47.3... REGISTRATION General § 47.3 Registration required. (a) An aircraft may be registered under 49 U.S.C. 44103 only... eligible for registration under 49 U.S.C. 44101-44104, unless the aircraft— (1) Has been registered by...

  17. Combined registration and motion correction of longitudinal retinal OCT data

    PubMed Central

    Lang, Andrew; Carass, Aaron; Al-Louzi, Omar; Bhargava, Pavan; Solomon, Sharon D.; Calabresi, Peter A.; Prince, Jerry L.

    2016-01-01

    Optical coherence tomography (OCT) has become an important modality for examination of the eye. To measure layer thicknesses in the retina, automated segmentation algorithms are often used, producing accurate and reliable measurements. However, subtle changes over time are difficult to detect since the magnitude of the change can be very small. Thus, tracking disease progression over short periods of time is difficult. Additionally, unstable eye position and motion alter the consistency of these measurements, even in healthy eyes. Thus, both registration and motion correction are important for processing longitudinal data of a specific patient. In this work, we propose a method to jointly do registration and motion correction. Given two scans of the same patient, we initially extract blood vessel points from a fundus projection image generated on the OCT data and estimate point correspondences. Due to saccadic eye movements during the scan, motion is often very abrupt, producing a sparse set of large displacements between successive B-scan images. Thus, we use lasso regression to estimate the movement of each image. By iterating between this regression and a rigid point-based registration, we are able to simultaneously align and correct the data. With longitudinal data from 39 healthy control subjects, our method improves the registration accuracy by 50% compared to simple alignment to the fovea and 22% when using point-based registration only. We also show improved consistency of repeated total retina thickness measurements. PMID:27231406

  18. The use of sampling for vital registration and vital statistics.

    PubMed

    HAUSER, P M

    1954-01-01

    In this paper, the author does not so much try to give a blueprint for the application of sampling methods to vital registration and vital statistics as to show the opportunities for their use and the advantages to be derived from them. In the less developed areas of the world, modern sampling methods make it possible to obtain very accurate national statistics in the early stages of the establishment of a vital registration and vital statistics system and will lead to its more orderly and efficient development. In areas where more or less complete registration exists, the use of sampling may result in a reduction of costs and an improvement in the quality and currency of the data obtained.The sample vital statistics system proposed by the author should comprise complete primary registration units or combinations of them, representative of the entire universe for which statistics are wanted. The selection of these, however, must be made at random; but, in order to avoid bias, the units should be taken with probabilities proportionate to their size.After discussing the ways of carrying out his proposal and the relation of a sample vital statistics system to health programmes, the author considers the use of the sample system as a supplement to a complete system and the advantages of sampling for quality control, checking the completeness of registration, preparing advance tabulations, and conducting supplemental surveys and research. PMID:13199663

  19. Combined registration and motion correction of longitudinal retinal OCT data

    NASA Astrophysics Data System (ADS)

    Lang, Andrew; Carass, Aaron; Al-Louzi, Omar; Bhargava, Pavan; Solomon, Sharon D.; Calabresi, Peter A.; Prince, Jerry L.

    2016-03-01

    Optical coherence tomography (OCT) has become an important modality for examination of the eye. To measure layer thicknesses in the retina, automated segmentation algorithms are often used, producing accurate and reliable measurements. However, subtle changes over time are difficult to detect since the magnitude of the change can be very small. Thus, tracking disease progression over short periods of time is difficult. Additionally, unstable eye position and motion alter the consistency of these measurements, even in healthy eyes. Thus, both registration and motion correction are important for processing longitudinal data of a specific patient. In this work, we propose a method to jointly do registration and motion correction. Given two scans of the same patient, we initially extract blood vessel points from a fundus projection image generated on the OCT data and estimate point correspondences. Due to saccadic eye movements during the scan, motion is often very abrupt, producing a sparse set of large displacements between successive B-scan images. Thus, we use lasso regression to estimate the movement of each image. By iterating between this regression and a rigid point-based registration, we are able to simultaneously align and correct the data. With longitudinal data from 39 healthy control subjects, our method improves the registration accuracy by 43% compared to simple alignment to the fovea and 8% when using point-based registration only. We also show improved consistency of repeated total retina thickness measurements.

  20. 21 CFR 1301.36 - Suspension or revocation of registration; suspension of registration pending final order...

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 21 Food and Drugs 9 2012-04-01 2012-04-01 false Suspension or revocation of registration; suspension of registration pending final order; extension of registration pending final order. 1301.36 Section 1301.36 Food and Drugs DRUG ENFORCEMENT ADMINISTRATION, DEPARTMENT OF JUSTICE REGISTRATION OF MANUFACTURERS, DISTRIBUTORS, AND DISPENSERS...

  1. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 21 Food and Drugs 7 2012-04-01 2012-04-01 false Notification of registrant; cosmetic product... OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.6 Notification of registrant; cosmetic product establishment registration number....

  2. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 7 2011-04-01 2010-04-01 true Notification of registrant; cosmetic product... OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.6 Notification of registrant; cosmetic product establishment registration number....

  3. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 21 Food and Drugs 7 2010-04-01 2010-04-01 false Notification of registrant; cosmetic product... OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.6 Notification of registrant; cosmetic product establishment registration number....

  4. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 21 Food and Drugs 7 2013-04-01 2013-04-01 false Notification of registrant; cosmetic product... OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.6 Notification of registrant; cosmetic product establishment registration number....

  5. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 21 Food and Drugs 7 2014-04-01 2014-04-01 false Notification of registrant; cosmetic product... OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.6 Notification of registrant; cosmetic product establishment registration number....

  6. 49 CFR 368.5 - Re-registration of certain carriers holding certificates of registration.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 49 Transportation 5 2011-10-01 2011-10-01 false Re-registration of certain carriers holding certificates of registration. 368.5 Section 368.5 Transportation Other Regulations Relating to Transportation... MUNICIPALITIES. § 368.5 Re-registration of certain carriers holding certificates of registration. (a) Each...

  7. 21 CFR 1301.13 - Application for registration; time for application; expiration date; registration for independent...

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ...; expiration date; registration for independent activities; application forms, fees, contents and signature... § 1301.13 Application for registration; time for application; expiration date; registration for... days before the expiration date of his/her registration, except that a bulk manufacturer of Schedule...

  8. 21 CFR 1301.13 - Application for registration; time for application; expiration date; registration for independent...

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ...; expiration date; registration for independent activities; application forms, fees, contents and signature... § 1301.13 Application for registration; time for application; expiration date; registration for... days before the expiration date of his/her registration, except that a bulk manufacturer of Schedule...

  9. 21 CFR 1301.13 - Application for registration; time for application; expiration date; registration for independent...

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ...; expiration date; registration for independent activities; application forms, fees, contents and signature... § 1301.13 Application for registration; time for application; expiration date; registration for... days before the expiration date of his/her registration, except that a bulk manufacturer of Schedule...

  10. USDA registration and rectification requirements

    NASA Technical Reports Server (NTRS)

    Allen, R.

    1982-01-01

    Some of the requirements of the United States Department of Agriculture for accuracy of aerospace acquired data, and specifically, requirements for registration and rectification of remotely sensed data are discussed. Particular attention is given to foreign and domestic crop estimation and forecasting, forestry information applications, and rangeland condition evaluations.

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

    PubMed

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

    2011-05-01

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

  12. Semi-automatic elastic registration on thyroid gland ultrasonic image

    NASA Astrophysics Data System (ADS)

    Xu, Xia; Zhong, Yue; Luo, Yan; Li, Deyu; Lin, Jiangli; Wang, Tianfu

    2007-12-01

    Knowledge of in vivo thyroid volume has both diagnostic and therapeutic importance and could lead to a more precise quantification of absolute activity contained in the thyroid gland. However, the shape of thyroid gland is irregular and difficult to calculate. For precise estimation of thyroid volume by ultrasound imaging, this paper presents a novel semiautomatic minutiae matching method in thyroid gland ultrasonic image by means of thin-plate spline model. Registration consists of four basic steps: feature detection, feature matching, mapping function design, and image transformation and resampling. Due to the connectivity of thyroid gland boundary, we choose active contour model as feature detector, and radials from centric points for feature matching. The proposed approach has been used in thyroid gland ultrasound images registration. Registration results of 18 healthy adults' thyroid gland ultrasound images show this method consumes less time and energy with good objectivity than algorithms selecting landmarks manually.

  13. Multi-Sensor Registration of Earth Remotely Sensed Imagery

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; Cole-Rhodes, Arlene; Eastman, Roger; Johnson, Kisha; Morisette, Jeffrey; Netanyahu, Nathan S.; Stone, Harold S.; Zavorin, Ilya; Zukor, Dorothy (Technical Monitor)

    2001-01-01

    Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30m), MODIS (500m), and SeaWIFS (1000m).

  14. 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.

  15. Landsat image registration - A study of system parameters

    NASA Technical Reports Server (NTRS)

    Wacker, A. G.; Juday, R. D.; Wolfe, R. H., Jr.

    1984-01-01

    Some applications of Landsat data, particularily agricultural and forestry applications, require the ability to geometrically superimpose or register data acquired at different times and possibly by different satellites. An experimental investigation relating to a registration processor used by the Johnson Space Center for this purpose is the subject of this paper. Correlation of small subareas of images is at the heart of this registration processor and the manner in which various system parameters affect the correlation process is the prime area of investigation. Parameters investigated include preprocessing methods, methods for detecting sucessful correlations, fitting a surface to the correlation patch, fraction of pixels designated as edge pixels in edge detection adn local versus global generation of edge images. A suboptimum search procedure is used to find a good parameter set for this registration processor.

  16. 18 CFR 390.1 - Electronic registration.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Electronic registration. 390.1 Section 390.1 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY PROCEDURAL RULES ELECTRONIC REGISTRATION § 390.1 Electronic registration. Any person...

  17. 18 CFR 390.1 - Electronic registration.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Electronic registration. 390.1 Section 390.1 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY PROCEDURAL RULES ELECTRONIC REGISTRATION § 390.1 Electronic registration. Any person...

  18. 18 CFR 390.1 - Electronic registration.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Electronic registration. 390.1 Section 390.1 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY PROCEDURAL RULES ELECTRONIC REGISTRATION § 390.1 Electronic registration. Any person...

  19. 18 CFR 390.1 - Electronic registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Electronic registration. 390.1 Section 390.1 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY PROCEDURAL RULES ELECTRONIC REGISTRATION § 390.1 Electronic registration. Any person...

  20. 18 CFR 390.1 - Electronic registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Electronic registration. 390.1 Section 390.1 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY PROCEDURAL RULES ELECTRONIC REGISTRATION § 390.1 Electronic registration. Any person...

  1. 27 CFR 447.31 - Registration requirement.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 3 2011-04-01 2010-04-01 true Registration requirement. 447.31 Section 447.31 Alcohol, Tobacco Products, and Firearms BUREAU OF ALCOHOL, TOBACCO, FIREARMS... IMPLEMENTS OF WAR Registration § 447.31 Registration requirement. Persons engaged in the business, in...

  2. 31 CFR 346.2 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 31 Money and Finance:Treasury 2 2011-07-01 2011-07-01 false Registration. 346.2 Section 346.2 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) FISCAL SERVICE... RETIREMENT BONDS § 346.2 Registration. (a) General. The registration of Individual Retirement Bonds...

  3. 22 CFR 122.3 - Registration fees.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Registration fees. 122.3 Section 122.3 Foreign Relations DEPARTMENT OF STATE INTERNATIONAL TRAFFIC IN ARMS REGULATIONS REGISTRATION OF MANUFACTURERS AND EXPORTERS § 122.3 Registration fees. (a) A person who is required to register must do so on an annual...

  4. 27 CFR 26.307 - Claimant registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2011-04-01 2011-04-01 false Claimant registration. 26... Drawback on Eligible Articles From the Virgin Islands § 26.307 Claimant registration. Any person filing... must register annually as a nonbeverage domestic drawback claimant. Registration will be...

  5. 8 CFR 244.17 - Annual registration.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 8 Aliens and Nationality 1 2011-01-01 2011-01-01 false Annual registration. 244.17 Section 244.17... FOR NATIONALS OF DESIGNATED STATES § 244.17 Annual registration. (a) Aliens granted Temporary... of residence. Such registration will apply to nationals of those foreign states designated...

  6. 27 CFR 19.50 - Dealer registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Dealer registration. 19.50... OF THE TREASURY LIQUORS DISTILLED SPIRITS PLANTS Dealer Registration and Recordkeeping § 19.50 Dealer registration. Every proprietor who sells or offers for sale any alcoholic product (distilled spirits, wines,...

  7. 9 CFR 320.5 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 9 Animals and Animal Products 2 2011-01-01 2011-01-01 false Registration. 320.5 Section 320.5... CERTIFICATION RECORDS, REGISTRATION, AND REPORTS § 320.5 Registration. (a) Except as provided in paragraph (c... therein upon said effective date. All information submitted shall be current and correct. The...

  8. 22 CFR 122.3 - Registration fees.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 22 Foreign Relations 1 2011-04-01 2011-04-01 false Registration fees. 122.3 Section 122.3 Foreign Relations DEPARTMENT OF STATE INTERNATIONAL TRAFFIC IN ARMS REGULATIONS REGISTRATION OF MANUFACTURERS AND EXPORTERS § 122.3 Registration fees. (a) A person who is required to register must do so on an annual...

  9. 27 CFR 24.52 - Dealer registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Dealer registration. 24.52... OF THE TREASURY LIQUORS WINE Administrative and Miscellaneous Provisions Dealer Registration and Recordkeeping § 24.52 Dealer registration. Every proprietor who sells or offers for sale any alcohol...

  10. 7 CFR 1219.102 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 10 2010-01-01 2010-01-01 false Registration. 1219.102 Section 1219.102 Agriculture..., AND INFORMATION Referendum Procedures § 1219.102 Registration. An eligible producer or importer of... referendum under § 1219.104(b). Registration information shall be confidential under § 1219.108....

  11. 7 CFR 1219.102 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 7 Agriculture 10 2011-01-01 2011-01-01 false Registration. 1219.102 Section 1219.102 Agriculture..., AND INFORMATION Referendum Procedures § 1219.102 Registration. An eligible producer or importer of... referendum under § 1219.104(b). Registration information shall be confidential under § 1219.108....

  12. 32 CFR 935.150 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Registration. 935.150 Section 935.150 National Defense Department of Defense (Continued) DEPARTMENT OF THE AIR FORCE TERRITORIAL AND INSULAR REGULATIONS WAKE ISLAND CODE Registration and Island Permits § 935.150 Registration. (a) Each person who...

  13. 32 CFR 935.150 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 6 2011-07-01 2011-07-01 false Registration. 935.150 Section 935.150 National Defense Department of Defense (Continued) DEPARTMENT OF THE AIR FORCE TERRITORIAL AND INSULAR REGULATIONS WAKE ISLAND CODE Registration and Island Permits § 935.150 Registration. (a) Each person who...

  14. 32 CFR 1615.3 - Registration procedures.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Registration procedures. 1615.3 Section 1615.3 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM ADMINISTRATION OF REGISTRATION § 1615.3 Registration procedures. Persons required by selective service law and the...

  15. 47 CFR 64.1195 - Registration requirement.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 3 2011-10-01 2011-10-01 false Registration requirement. 64.1195 Section 64....1195 Registration requirement. (a) Applicability. A telecommunications carrier that will provide interstate telecommunications service shall file the registration information described in paragraph (b)...

  16. 47 CFR 64.1195 - Registration requirement.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 3 2010-10-01 2010-10-01 false Registration requirement. 64.1195 Section 64....1195 Registration requirement. (a) Applicability. A telecommunications carrier that will provide interstate telecommunications service shall file the registration information described in paragraph (b)...

  17. 27 CFR 447.31 - Registration requirement.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 3 2010-04-01 2010-04-01 false Registration requirement. 447.31 Section 447.31 Alcohol, Tobacco Products, and Firearms BUREAU OF ALCOHOL, TOBACCO, FIREARMS... IMPLEMENTS OF WAR Registration § 447.31 Registration requirement. Persons engaged in the business, in...

  18. 31 CFR 341.2 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false Registration. 341.2 Section 341.2 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) FISCAL SERVICE... BONDS § 341.2 Registration. (a) General. The registration of Retirement Plan Bonds is limited to...

  19. 9 CFR 320.5 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Registration. 320.5 Section 320.5... CERTIFICATION RECORDS, REGISTRATION, AND REPORTS § 320.5 Registration. (a) Except as provided in paragraph (c... therein upon said effective date. All information submitted shall be current and correct. The...

  20. 31 CFR 341.2 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 31 Money and Finance:Treasury 2 2011-07-01 2011-07-01 false Registration. 341.2 Section 341.2 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) FISCAL SERVICE... BONDS § 341.2 Registration. (a) General. The registration of Retirement Plan Bonds is limited to...

  1. 8 CFR 1244.17 - Annual registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 8 Aliens and Nationality 1 2010-01-01 2010-01-01 false Annual registration. 1244.17 Section 1244... REGULATIONS TEMPORARY PROTECTED STATUS FOR NATIONALS OF DESIGNATED STATES § 1244.17 Annual registration. (a... jurisdiction over their place of residence. Such registration will apply to nationals of those foreign...

  2. 8 CFR 244.17 - Annual registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 8 Aliens and Nationality 1 2010-01-01 2010-01-01 false Annual registration. 244.17 Section 244.17... FOR NATIONALS OF DESIGNATED STATES § 244.17 Annual registration. (a) Aliens granted Temporary... of residence. Such registration will apply to nationals of those foreign states designated...

  3. 32 CFR 1615.3 - Registration procedures.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 6 2011-07-01 2011-07-01 false Registration procedures. 1615.3 Section 1615.3 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM ADMINISTRATION OF REGISTRATION § 1615.3 Registration procedures. Persons required by selective service law and the...

  4. 27 CFR 26.307 - Claimant registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Claimant registration. 26... Drawback on Eligible Articles From the Virgin Islands § 26.307 Claimant registration. Any person filing... must register annually as a nonbeverage domestic drawback claimant. Registration will be...

  5. 14 CFR 380.62 - Registration applications.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Registration applications. 380.62 Section... PROCEEDINGS) SPECIAL REGULATIONS PUBLIC CHARTERS Registration of Foreign Charter Operators § 380.62 Registration applications. (a) To be registered under this subpart, a foreign charter operator shall file...

  6. 27 CFR 26.171 - Claimant registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2011-04-01 2011-04-01 false Claimant registration. 26... Drawback on Eligible Articles From Puerto Rico § 26.171 Claimant registration. Any person filing claim for... as a nonbeverage domestic drawback claimant. Registration will be accomplished when the...

  7. 27 CFR 24.52 - Dealer registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2011-04-01 2011-04-01 false Dealer registration. 24.52... OF THE TREASURY LIQUORS WINE Administrative and Miscellaneous Provisions Dealer Registration and Recordkeeping § 24.52 Dealer registration. Every proprietor who sells or offers for sale any alcohol...

  8. 8 CFR 1244.17 - Annual registration.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 8 Aliens and Nationality 1 2011-01-01 2011-01-01 false Annual registration. 1244.17 Section 1244... REGULATIONS TEMPORARY PROTECTED STATUS FOR NATIONALS OF DESIGNATED STATES § 1244.17 Annual registration. (a... jurisdiction over their place of residence. Such registration will apply to nationals of those foreign...

  9. 25 CFR 81.11 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 25 Indians 1 2011-04-01 2011-04-01 false Registration. 81.11 Section 81.11 Indians BUREAU OF... STATUTE § 81.11 Registration. (a) Only registered voters will be entitled to vote, and all determinations... member not residing on the reservation shall be accompanied by a preaddressed registration form (BIA...

  10. 14 CFR 380.62 - Registration applications.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 4 2011-01-01 2011-01-01 false Registration applications. 380.62 Section... PROCEEDINGS) SPECIAL REGULATIONS PUBLIC CHARTERS Registration of Foreign Charter Operators § 380.62 Registration applications. (a) To be registered under this subpart, a foreign charter operator shall file...

  11. 27 CFR 26.171 - Claimant registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Claimant registration. 26... Drawback on Eligible Articles From Puerto Rico § 26.171 Claimant registration. Any person filing claim for... as a nonbeverage domestic drawback claimant. Registration will be accomplished when the...

  12. 31 CFR 346.2 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false Registration. 346.2 Section 346.2 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) FISCAL SERVICE... RETIREMENT BONDS § 346.2 Registration. (a) General. The registration of Individual Retirement Bonds...

  13. 25 CFR 81.11 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 25 Indians 1 2010-04-01 2010-04-01 false Registration. 81.11 Section 81.11 Indians BUREAU OF... STATUTE § 81.11 Registration. (a) Only registered voters will be entitled to vote, and all determinations... member not residing on the reservation shall be accompanied by a preaddressed registration form (BIA...

  14. 27 CFR 19.202 - Dealer registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2011-04-01 2011-04-01 false Dealer registration. 19..., DEPARTMENT OF THE TREASURY LIQUORS DISTILLED SPIRITS PLANTS Dealer Registration and Recordkeeping § 19.202 Dealer registration. Every proprietor that sells or offers for sale any alcoholic product...

  15. 14 CFR 47.3 - Registration required.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Registration required. 47.3 Section 47.3 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AIRCRAFT AIRCRAFT REGISTRATION General § 47.3 Registration required. (a) An aircraft may be registered under 49 U.S.C. 44103...

  16. 40 CFR 79.23 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... OF FUELS AND FUEL ADDITIVES Additive Registration Procedures § 79.23 Registration. (a) If the... additive which includes all of the information and assurances required by § 79.21 and has satisfactorily... the fuel additive and notify the fuel manufacturer of such registration. (b) The Administrator...

  17. 40 CFR 79.23 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... OF FUELS AND FUEL ADDITIVES Additive Registration Procedures § 79.23 Registration. (a) If the... additive which includes all of the information and assurances required by § 79.21 and has satisfactorily... the fuel additive and notify the fuel manufacturer of such registration. (b) The Administrator...

  18. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Registration number. 47.15 Section 47.15 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AIRCRAFT AIRCRAFT REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft...

  19. Rapid pedobarographic image registration based on contour curvature and optimization.

    PubMed

    Oliveira, Francisco P M; Tavares, João Manuel R S; Pataky, Todd C

    2009-11-13

    Image registration, the process of optimally aligning homologous structures in multiple images, has recently been demonstrated to support automated pixel-level analysis of pedobarographic images and, subsequently, to extract unique and biomechanically relevant information from plantar pressure data. Recent registration methods have focused on robustness, with slow but globally powerful algorithms. In this paper, we present an alternative registration approach that affords both speed and accuracy, with the goal of making pedobarographic image registration more practical for near-real-time laboratory and clinical applications. The current algorithm first extracts centroid-based curvature trajectories from pressure image contours, and then optimally matches these curvature profiles using optimization based on dynamic programming. Special cases of disconnected images (that occur in high-arched subjects, for example) are dealt with by introducing an artificial spatially linear bridge between adjacent image clusters. Two registration algorithms were developed: a 'geometric' algorithm, which exclusively matched geometry, and a 'hybrid' algorithm, which performed subsequent pseudo-optimization. After testing the two algorithms on 30 control image pairs considered in a previous study, we found that, when compared with previously published results, the hybrid algorithm improved overlap ratio (p=0.010), but both current algorithms had slightly higher mean-squared error, assumedly because they did not consider pixel intensity. Nonetheless, both algorithms greatly improved the computational efficiency (25+/-8 and 53+/-9 ms per image pair for geometric and hybrid registrations, respectively). These results imply that registration-based pixel-level pressure image analyses can, eventually, be implemented for practical clinical purposes. PMID:19647829

  20. 40 CFR 155.50 - Initiate a pesticide's registration review.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 25 2013-07-01 2013-07-01 false Initiate a pesticide's registration...) PESTICIDE PROGRAMS REGISTRATION STANDARDS AND REGISTRATION REVIEW Registration Review Procedures § 155.50 Initiate a pesticide's registration review. The Agency will initiate a pesticide's registration review...

  1. 40 CFR 155.50 - Initiate a pesticide's registration review.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 24 2011-07-01 2011-07-01 false Initiate a pesticide's registration...) PESTICIDE PROGRAMS REGISTRATION STANDARDS AND REGISTRATION REVIEW Registration Review Procedures § 155.50 Initiate a pesticide's registration review. The Agency will initiate a pesticide's registration review...

  2. 40 CFR 155.50 - Initiate a pesticide's registration review.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 25 2012-07-01 2012-07-01 false Initiate a pesticide's registration...) PESTICIDE PROGRAMS REGISTRATION STANDARDS AND REGISTRATION REVIEW Registration Review Procedures § 155.50 Initiate a pesticide's registration review. The Agency will initiate a pesticide's registration review...

  3. 40 CFR 155.50 - Initiate a pesticide's registration review.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 24 2014-07-01 2014-07-01 false Initiate a pesticide's registration...) PESTICIDE PROGRAMS REGISTRATION STANDARDS AND REGISTRATION REVIEW Registration Review Procedures § 155.50 Initiate a pesticide's registration review. The Agency will initiate a pesticide's registration review...

  4. 40 CFR 155.50 - Initiate a pesticide's registration review.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 23 2010-07-01 2010-07-01 false Initiate a pesticide's registration...) PESTICIDE PROGRAMS REGISTRATION STANDARDS AND REGISTRATION REVIEW Registration Review Procedures § 155.50 Initiate a pesticide's registration review. The Agency will initiate a pesticide's registration review...

  5. 40 CFR 152.135 - Transfer of registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 23 2010-07-01 2010-07-01 false Transfer of registration. 152.135... PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Obligations and Rights of Registrants § 152.135 Transfer of registration. (a) A registrant may transfer the registration of a product to another...

  6. 40 CFR 155.57 - Registration review decision.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 23 2010-07-01 2010-07-01 false Registration review decision. 155.57... REGISTRATION STANDARDS AND REGISTRATION REVIEW Registration Review Procedures § 155.57 Registration review decision. A registration review decision is the Agency's determination whether a pesticide meets, or...

  7. 21 CFR 1301.51 - Modification in registration.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 21 Food and Drugs 9 2012-04-01 2012-04-01 false Modification in registration. 1301.51 Section 1301.51 Food and Drugs DRUG ENFORCEMENT ADMINISTRATION, DEPARTMENT OF JUSTICE REGISTRATION OF... Registration § 1301.51 Modification in registration. Any registrant may apply to modify his/her registration...

  8. 75 FR 80494 - Busan 74 (HPMTS); and Nithiazine; Registration Review Proposed Decisions; Notice of Availability

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-22

    ... availability of EPA's proposed registration review decisions for the pesticides listed in the table in Unit II... periodic review of pesticide registrations to ensure that each pesticide continues to satisfy the statutory... pesticide of interest provided in the table in Unit II.A., by one of the following methods: Federal...

  9. 75 FR 22788 - Garlic Oil and Capsaicin; Registration Review Proposed Decisions; Notice of Availability

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-30

    ... proposed registration review decisions for the pesticides listed in the table in Unit II.A. and opens a public comment period on the proposed decisions. Registration review is EPA's periodic review of... table in Unit II.A., by one of the following methods: Federal eRulemaking Portal:...

  10. 77 FR 18810 - Registration Review; Pesticide Dockets Opened for Review and Comment and Other Docket Act

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-28

    ... for the pesticides listed in the table in Unit III.A. With this document, EPA is opening the public comment period for these registration reviews. Registration review is EPA's periodic review of pesticide... interest provided in the table in Unit III.A., by one of the following methods: Federal eRulemaking...

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

    SciTech Connect

    Barber, J; Sykes, J; Holloway, L; Thwaites, D

    2015-06-15

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

  12. A Framework for Brain Registration via Simultaneous Surface and Volume Flow

    PubMed Central

    Joshi, Anand; Leahy, Richard; Toga, Arthur; Shattuck, David

    2015-01-01

    Volumetric registration of brain MR images presents a challenging problem due to the wide variety of sulcal folding patterns. We present a novel volumetric registration method based on an intermediate parameter space in which the shape differences are normalized. First, we generate a 3D harmonic map of each brain volume to unit ball which is used as an intermediate space. Cortical surface features and volumetric intensity are then used to find a simultaneous surface and volume registration. We present a finite element method for the registration by using a tetrahedral volumetric mesh for registering the interior volumetric information and the corresponding triangulated mesh at the surface points. This framework aligns the convoluted sulcal folding patterns as well as the subcortical structures by allowing simultaneous flow of surface and volumes for registration. We describe the methodology and FEM implementation and then evaluate the method in terms of the overlap between segmented structures in coregistered brains. PMID:19694295

  13. Automated registration of diagnostic to prediagnostic x-ray mammograms: Evaluation and comparison to radiologists' accuracy

    SciTech Connect

    Pinto Pereira, Snehal M.; Hipwell, John H.; McCormack, Valerie A.; Tanner, Christine; Moss, Sue M.; Wilkinson, Louise S.; Khoo, Lisanne A. L.; Pagliari, Catriona; Skippage, Pippa L.; Kliger, Carole J.; Hawkes, David J.; Santos Silva, Isabel M. dos

    2010-09-15

    Purpose: To compare and evaluate intensity-based registration methods for computation of serial x-ray mammogram correspondence. Methods: X-ray mammograms were simulated from MRIs of 20 women using finite element methods for modeling breast compressions and employing a MRI/x-ray appearance change model. The parameter configurations of three registration methods, affine, fluid, and free-form deformation (FFD), were optimized for registering x-ray mammograms on these simulated images. Five mammography film readers independently identified landmarks (tumor, nipple, and usually two other normal features) on pairs of diagnostic and corresponding prediagnostic digitized images from 52 breast cancer cases. Landmarks were independently reidentified by each reader. Target registration errors were calculated to compare the three registration methods using the reader landmarks as a gold standard. Data were analyzed using multilevel methods. Results: Between-reader variability varied with landmark (p<0.01) and screen (p=0.03), with between-reader mean distance (mm) in point location on the diagnostic/prediagnostic images of 2.50 (95% CI 1.95, 3.15)/2.84 (2.24, 3.55) for nipples and 4.26 (3.43, 5.24)/4.76 (3.85, 5.84) for tumors. Registration accuracy was sensitive to the type of landmark and the amount of breast density. For dense breasts ({>=}40%), the affine and fluid methods outperformed FFD. For breasts with lower density, the affine registration surpassed both fluid and FFD. Mean accuracy (mm) of the affine registration varied between 3.16 (95% CI 2.56, 3.90) for nipple points in breasts with density 20%-39% and 5.73 (4.80, 6.84) for tumor points in breasts with density <20%. Conclusions: Affine registration accuracy was comparable to that between independent film readers. More advanced two-dimensional nonrigid registration algorithms were incapable of increasing the accuracy of image alignment when compared to affine registration.

  14. Surface-based registration of liver in ultrasound and CT

    NASA Astrophysics Data System (ADS)

    Dehghan, Ehsan; Lu, Kongkuo; Yan, Pingkun; Tahmasebi, Amir; Xu, Sheng; Wood, Bradford J.; Abi-Jaoudeh, Nadine; Venkatesan, Aradhana; Kruecker, Jochen

    2015-03-01

    Ultrasound imaging is an attractive modality for real-time image-guided interventions. Fusion of US imaging with a diagnostic imaging modality such as CT shows great potential in minimally invasive applications such as liver biopsy and ablation. However, significantly different representation of liver in US and CT turns this image fusion into a challenging task, in particular if some of the CT scans may be obtained without contrast agents. The liver surface, including the diaphragm immediately adjacent to it, typically appears as a hyper-echoic region in the ultrasound image if the proper imaging window and depth setting are used. The liver surface is also well visualized in both contrast and non-contrast CT scans, thus making the diaphragm or liver surface one of the few attractive common features for registration of US and non-contrast CT. We propose a fusion method based on point-to-volume registration of liver surface segmented in CT to a processed electromagnetically (EM) tracked US volume. In this approach, first, the US image is pre-processed in order to enhance the liver surface features. In addition, non-imaging information from the EM-tracking system is used to initialize and constrain the registration process. We tested our algorithm in comparison with a manually corrected vessel-based registration method using 8 pairs of tracked US and contrast CT volumes. The registration method was able to achieve an average deviation of 12.8mm from the ground truth measured as the root mean square Euclidean distance for control points distributed throughout the US volume. Our results show that if the US image acquisition is optimized for imaging of the diaphragm, high registration success rates are achievable.

  15. Spherical Demons: Fast Diffeomorphic Landmark-Free Surface Registration

    PubMed Central

    Yeo, B.T. Thomas; Sabuncu, Mert R.; Vercauteren, Tom; Ayache, Nicholas; Fischl, Bruce; Golland, Polina

    2010-01-01

    We present the Spherical Demons algorithm for registering two spherical images. By exploiting spherical vector spline interpolation theory, we show that a large class of regularizors for the modified Demons objective function can be efficiently approximated on the sphere using iterative smoothing. Based on one parameter subgroups of diffeomorphisms, the resulting registration is diffeomorphic and fast. The Spherical Demons algorithm can also be modified to register a given spherical image to a probabilistic atlas. We demonstrate two variants of the algorithm corresponding to warping the atlas or warping the subject. Registration of a cortical surface mesh to an atlas mesh, both with more than 160k nodes requires less than 5 minutes when warping the atlas and less than 3 minutes when warping the subject on a Xeon 3.2GHz single processor machine. This is comparable to the fastest non-diffeomorphic landmark-free surface registration algorithms. Furthermore, the accuracy of our method compares favorably to the popular FreeSurfer registration algorithm. We validate the technique in two different applications that use registration to transfer segmentation labels onto a new image: (1) parcellation of in-vivo cortical surfaces and (2) Brodmann area localization in ex-vivo cortical surfaces. PMID:19709963

  16. 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.

  17. Registration-tolerant extended visual cryptography

    NASA Astrophysics Data System (ADS)

    Nakajima, Mizuho; Yamaguchi, Yasushi

    2003-06-01

    Extended Visual Cryptography is a method which encodes a number of images so that when the images are superimposed, the hidden image appears without a trace of original images. The decryption is done directly by human eyes without cryptographic calculations. The proposing system takes three pictures as input and generates two images which correspond to two of the input pictures. The third picture is perceived by superimposing the two output images. Previous methods are based on halftoning and Boolean operations. Transparency values must be quantized before encryption, and a pixel is halftoned by a fixed numbers of completely transparent and opaque subpixels. Then a transparency of the superimposed pixel is controlled by changing the subpixel arrangements of the two output pixels. Since the subpixel arrangement is basically random, a tradeoff exists that to express the more graylevels, each subpixel must become the smaller, making it the more difficult to superimpose by hand. Our new approach tolerates registration error for the third image and eases the difficulty, by adopting concentric-circular subpixel arrangement and continuous grayscale subpixel values. The system becomes considerably robust to the registration error. Also, it achieves quality improvement for all three images, by explicitly dealing with continuous graylevels.

  18. Perfect Color Registration Realized.

    ERIC Educational Resources Information Center

    Lovedahl, Gerald G.

    1979-01-01

    Describes apparatus and procedures to design and construct a "printing box" as a graphic arts project to make color prints on T-shirts using photography, indirect and direct photo screen methods, and other types of stencils. Step-by-step photographs illustrate the process. (MF)

  19. Registration using natural features for augmented reality systems.

    PubMed

    Yuan, M L; Ong, S K; Nee, A Y C

    2006-01-01

    Registration is one of the most difficult problems in augmented reality (AR) systems. In this paper, a simple registration method using natural features based on the projective reconstruction technique is proposed. This method consists of two steps: embedding and rendering. Embedding involves specifying four points to build the world coordinate system on which a virtual object will be superimposed. In rendering, the Kanade-Lucas-Tomasi (KLT) feature tracker is used to track the natural feature correspondences in the live video. The natural features that have been tracked are used to estimate the corresponding projective matrix in the image sequence. Next, the projective reconstruction technique is used to transfer the four specified points to compute the registration matrix for augmentation. This paper also proposes a robust method for estimating the projective matrix, where the natural features that have been tracked are normalized (translation and scaling) and used as the input data. The estimated projective matrix will be used as an initial estimate for a nonlinear optimization method that minimizes the actual residual errors based on the Levenberg-Marquardt (LM) minimization method, thus making the results more robust and stable. The proposed registration method has three major advantages: 1) It is simple, as no predefined fiducials or markers are used for registration for either indoor and outdoor AR applications. 2) It is robust, because it remains effective as long as at least six natural features are tracked during the entire augmentation, and the existence of the corresponding projective matrices in the live video is guaranteed. Meanwhile, the robust method to estimate the projective matrix can obtain stable results even when there are some outliers during the tracking process. 3) Virtual objects can still be superimposed on the specified areas, even if some parts of the areas are occluded during the entire process. Some indoor and outdoor experiments have

  20. Towards local estimation of emphysema progression using image registration

    NASA Astrophysics Data System (ADS)

    Staring, M.; Bakker, M. E.; Shamonin, D. P.; Stolk, J.; Reiber, J. H. C.; Stoel, B. C.

    2009-02-01

    Progression measurement of emphysema is required to evaluate the health condition of a patient and the effect of drugs. To locally estimate progression we use image registration, which allows for volume correction using the determinant of the Jacobian of the transformation. We introduce an adaptation of the so-called sponge model that circumvents its constant-mass assumption. Preliminary results from CT scans of a lung phantom and from CT data sets of three patients suggest that image registration may be a suitable method to locally estimate emphysema progression.

  1. An Iterative Image Registration Algorithm by Optimizing Similarity Measurement

    PubMed Central

    Chu, Wei; Ma, Li; Song, John; Vorburger, Theodore

    2010-01-01

    A new registration algorithm based on Newton-Raphson iteration is proposed to align images with rigid body transformation. A set of transformation parameters consisting of translation in x and y and rotation angle around z is calculated by optimizing a specified similarity metric using the Newton-Raphson method. This algorithm has been tested by registering and correlating pairs of topography measurements of nominally identical NIST Standard Reference Material (SRM 2461) standard cartridge cases, and very good registration accuracy has been obtained. PMID:27134776

  2. Congestion estimation technique in the optical network unit registration process.

    PubMed

    Kim, Geunyong; Yoo, Hark; Lee, Dongsoo; Kim, Youngsun; Lim, Hyuk

    2016-07-01

    We present a congestion estimation technique (CET) to estimate the optical network unit (ONU) registration success ratio for the ONU registration process in passive optical networks. An optical line terminal (OLT) estimates the number of collided ONUs via the proposed scheme during the serial number state. The OLT can obtain congestion level among ONUs to be registered such that this information may be exploited to change the size of a quiet window to decrease the collision probability. We verified the efficiency of the proposed method through simulation and experimental results. PMID:27367066

  3. Registration and identification of pulse signal for medical diagnostics

    NASA Astrophysics Data System (ADS)

    Buldakova, Tatyana I.; Suyatinov, Sergey I.

    2002-07-01

    Registration and identification of pulse signal requires the development and the use of special diagnostic equipment and modern methods of processing of the registered data. There are recognized that photoelectric and piezoelectric gauges are the most perspective converters for measurement of pulse signal. In this paper the approach to registration of pulse curves on the basis of the optical gauge is developed. The problem of identification of pulse signal is considered as the problem of recognition of images. The system of identification of pulse waves is offered. It is functioning as a visual system of recognition of images of the man and is based on artificial neural networks.

  4. Bidirectional Elastic Image Registration Using B-Spline Affine Transformation

    PubMed Central

    Gu, Suicheng; Meng, Xin; Sciurba, Frank C.; Wang, Chen; Kaminski, Naftali; Pu, Jiantao

    2014-01-01

    A registration scheme termed as B-spline affine transformation (BSAT) is presented in this study to elastically align two images. We define an affine transformation instead of the traditional translation at each control point. Mathematically, BSAT is a generalized form of the affine transformation and the traditional B-Spline transformation (BST). In order to improve the performance of the iterative closest point (ICP) method in registering two homologous shapes but with large deformation, a bi-directional instead of the traditional unidirectional objective / cost function is proposed. In implementation, the objective function is formulated as a sparse linear equation problem, and a sub-division strategy is used to achieve a reasonable efficiency in registration. The performance of the developed scheme was assessed using both two-dimensional (2D) synthesized dataset and three-dimensional (3D) volumetric computed tomography (CT) data. Our experiments showed that the proposed B-spline affine model could obtain reasonable registration accuracy. PMID:24530210

  5. Bidirectional elastic image registration using B-spline affine transformation.

    PubMed

    Gu, Suicheng; Meng, Xin; Sciurba, Frank C; Ma, Hongxia; Leader, Joseph; Kaminski, Naftali; Gur, David; Pu, Jiantao

    2014-06-01

    A registration scheme termed as B-spline affine transformation (BSAT) is presented in this study to elastically align two images. We define an affine transformation instead of the traditional translation at each control point. Mathematically, BSAT is a generalized form of the affine transformation and the traditional B-spline transformation (BST). In order to improve the performance of the iterative closest point (ICP) method in registering two homologous shapes but with large deformation, a bidirectional instead of the traditional unidirectional objective/cost function is proposed. In implementation, the objective function is formulated as a sparse linear equation problem, and a sub-division strategy is used to achieve a reasonable efficiency in registration. The performance of the developed scheme was assessed using both two-dimensional (2D) synthesized dataset and three-dimensional (3D) volumetric computed tomography (CT) data. Our experiments showed that the proposed B-spline affine model could obtain reasonable registration accuracy. PMID:24530210

  6. DIFFEOMORPHIC POINT SET REGISTRATION USING NON-STATIONARY MIXTURE MODELS

    PubMed Central

    Wassermann, D.; Ross, J.; Washko, G.; Westin, C-F; Estépar, R. San José

    2013-01-01

    This paper investigates a diffeomorphic point-set registration based on non-stationary mixture models. The goal is to improve the non-linear registration of anatomical structures by representing each point as a general non-stationary kernel that provides information about the shape of that point. Our framework generalizes work done by others that use stationary models. We achieve this by integrating the shape at each point when calculating the point-set similarity and transforming it according to the calculated deformation. We also restrict the non-rigid transform to the space of symmetric diffeomorphisms. Our algorithm is validated in synthetic and human datasets in two different applications: fiber bundle and lung airways registration. Our results shows that non-stationary mixture models are superior to Gaussian mixture models and methods that do not take into account the shape of each point. PMID:24419463

  7. High-performance automatic image registration for remote sensing

    NASA Astrophysics Data System (ADS)

    Chalermwat, Prachya

    Image registration is one of the crucial steps in the analysis of remotely sensed data. A new acquired image must be transformed, using image registration techniques, to match the orientation and scale of previous related images. Image registration requires intensive computational effort not only because of its computational complexity, but also due to the continuous increase in image resolution and spectral bands. Thus, high-performance computing techniques for image registration are critically needed. Very few works have addressed image registration on contemporary high-performance computing systems. Furthermore, issues of load balancing, scalability, and formal analysis of algorithmic efficiency were seldom considered. This dissertation introduces high-performance automatic image registration (HAIR) algorithms. High performance is achieved by: (1) reduction in search data, (2) reduction in search space, and (3) parallel processing. Reduction in search data is achieved by performing registration using only subimages. A new metric called registrability is used to select those subimages such that accuracy is maintained. In addition, a histogram comparison is used to discard anomalous subimages, such as those with clouds. Further data reduction is obtained using an iterative refinement search (IRA), which exploits the wavelet multi-resolution representation. This technique starts searching images with lower resolution first, then refining the results using higher resolution images to use the least possible data points in the overall registration task. Reduction of search space is achieved through two methods. First, iterative refinement reduces dramatically the number of solutions examined. In addition, genetic algorithms were also used to further expedite the search. Parallel processing techniques have been utilized to provide coarse-grain load-balanced parallel algorithms based on iterative refinement as well as genetic algorithms. Two hybrid algorithms have been

  8. A first step toward uncovering the truth about weight tuning in deformable image registration

    NASA Astrophysics Data System (ADS)

    Pirpinia, Kleopatra; Bosman, Peter A. N.; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

    2016-03-01

    Deformable image registration is currently predominantly solved by optimizing a weighted linear combination of objectives. Successfully tuning the weights associated with these objectives is not trivial, leading to trial-and-error approaches. Such an approach assumes an intuitive interplay between weights, optimization objectives, and target registration errors. However, it is not known whether this always holds for existing registration methods. To investigate the interplay between weights, optimization objectives, and registration errors, we employ multi-objective optimization. Here, objectives of interest are optimized simultaneously, causing a set of multiple optimal solutions to exist, called the optimal Pareto front. Our medical application is in breast cancer and includes the challenging prone-supine registration problem. In total, we studied the interplay in three different ways. First, we ran many random linear combinations of objectives using the well-known registration software elastix. Second, since the optimization algorithms used in registration are typically of a local-search nature, final solutions may not always form a Pareto front. We therefore employed a multi-objective evolutionary algorithm that finds weights that correspond to registration outcomes that do form a Pareto front. Third, we examined how the interplay differs if a true multi-objective (i.e., weight-free) image registration method is used. Results indicate that a trial-and-error weight-adaptation approach can be successful for the easy prone to prone breast image registration case, due to the absence of many local optima. With increasing problem difficulty the use of more advanced approaches can be of value in finding and selecting the optimal registration outcomes.

  9. Selection of massive bone allografts using shape-matching 3-dimensional registration

    PubMed Central

    Docquier, Pierre-Louis; Cartiaux, Olivier; Cornu, Olivier; Delloye, Christian; Banse, Xavier

    2010-01-01

    Background and purpose Massive bone allografts are used when surgery causes large segmental defects. Shape-matching is the primary criterion for selection of an allograft. The current selection method, based on 2-dimensional template comparison, is inefficient for 3-dimensional complex bones. We have analyzed a 3-dimensional (3-D) registration method to match the anatomy of the allograft with that of the recipient. Methods 3-D CT-based registration was performed to match the shapes of both bones. We used the registration to align the allograft volume onto the recipient's bone. Hemipelvic allograft selection was tested in 10 virtual recipients with a panel of 10 potential allografts, including one from the recipient himself (trap graft). 4 observers were asked to visually inspect the superposition of allograft over the recipient, to classify the allografts into 4 categories according to the matching of anatomic zones, and to select the 3 best matching allografts. The results obtained using the registration method were compared with those from a previous study on the template method. Results Using the registration method, the observers systematically detected the trap graft. Selections of the 3 best matching allografts performed using registration and template methods were different. Selection of the 3 best matching allografts was improved by the registration method. Finally, reproducibility of the selection was improved when using the registration method. Interpretation 3-D CT registration provides more useful information than the template method but the final decision lies with the surgeon, who should select the optimal allograft according to his or her own preferences and the needs of the recipient. PMID:20175643

  10. Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning

    PubMed Central

    Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C.

    2015-01-01

    Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data,, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked auto-encoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework image registration experiments were conducted on 7.0-tesla brain MR images. In all experiments, the results showed the new image registration framework consistently demonstrated more accurate registration results when compared to state-of-the-art. PMID:26552069

  11. Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning.

    PubMed

    Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C; Shen, Dinggang

    2016-07-01

    Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked autoencoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework, image registration experiments were conducted on 7.0-T brain MR images. In all experiments, the results showed that the new image registration framework consistently demonstrated more accurate registration results when compared to state of the art. PMID:26552069

  12. Quantitative evaluation of image registration techniques in the case of retinal images

    NASA Astrophysics Data System (ADS)

    Gavet, Yann; Fernandes, Mathieu; Pinoli, Jean-Charles

    2012-04-01

    In human retina observation (with non mydriatic optical microscopes), an image registration process is often employed to enlarge the field of view. Analyzing all the images takes a lot of time. Numerous techniques have been proposed to perform the registration process. Its good evaluation is a difficult question that is then raising. This article presents the use of two quantitative criterions to evaluate and compare some classical feature-based image registration techniques. The images are first segmented and the resulting binary images are then registered. The good quality of the registration process is evaluated with a normalized criterion based on the ɛ dissimilarity criterion, and the figure of merit criterion (fom), for 25 pairs of images with a manual selection of control points. These criterions are normalized by the results of the affine method (considered as the most simple method). Then, for each pair, the influence of the number of points used to perform the registration is evaluated.

  13. Point-based registration under a similarity transform

    NASA Astrophysics Data System (ADS)

    West, Jay B.; Fitzpatrick, J. Michael; Batchelor, Philippe G.

    2001-07-01

    This paper investigates the problem of point-based registration under a similarity transformation. This is a transformation that consists of rotation, translation, and isotropic scaling. There are many applications for registration under a similarity transform. First, the medical applications that usually use rigid-body registration may in some cases be improved by using a scale factor to account for particular types of distortion (for example, drift in gradient strength in MR image volumes). Second, similarity transforms are often used in biometrics to analyze and compare different sets of data. It was shown by Gower in 1971 that the choice of scale factor is independent from the choice of rotation and translation. We use a well-known solution for the rotation and translation parts of the transformation, and concentrate on the problem of choosing the scale factor. We examine three different methods of scaling, one of which is a novel maximum likelihood approach. We derive the target registration error and show the bias for each method. We introduce two different models of fiducial localization error, and we show that for one error model, Gower's method of scaling to minimize the sum of squared distances between corresponding points is also the maximum likelihood solution. Under the other error model, however, maximum likelihood leads to a new method of scaling.

  14. Proceedings of the NASA Workshop on Registration and Rectification

    NASA Technical Reports Server (NTRS)

    Bryant, N. A. (Editor)

    1982-01-01

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

  15. 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

  16. Automatic registration of large-scale urban scene point clouds based on semantic feature points

    NASA Astrophysics Data System (ADS)

    Yang, Bisheng; Dong, Zhen; Liang, Fuxun; Liu, Yuan

    2016-03-01

    Point clouds collected by terrestrial laser scanning (TLS) from large-scale urban scenes contain a wide variety of objects (buildings, cars, pole-like objects, and others) with symmetric and incomplete structures, and relatively low-textured surfaces, all of which pose great challenges for automatic registration between scans. To address the challenges, this paper proposes a registration method to provide marker-free and multi-view registration based on the semantic feature points extracted. First, the method detects the semantic feature points within a detection scheme, which includes point cloud segmentation, vertical feature lines extraction and semantic information calculation and finally takes the intersections of these lines with the ground as the semantic feature points. Second, the proposed method matches the semantic feature points using geometrical constraints (3-point scheme) as well as semantic information (category and direction), resulting in exhaustive pairwise registration between scans. Finally, the proposed method implements multi-view registration by constructing a minimum spanning tree of the fully connected graph derived from exhaustive pairwise registration. Experiments have demonstrated that the proposed method performs well in various urban environments and indoor scenes with the accuracy at the centimeter level and improves the efficiency, robustness, and accuracy of registration in comparison with the feature plane-based methods.

  17. Validation of a Non-Rigid Registration Error Detection Algorithm Using Clinical MRI Brain Data

    PubMed Central

    Datteri, Ryan D.; Liu, Yuan; D’Haese, Pierre-François; Dawant, Benoit M.

    2014-01-01

    Identification of error in non-rigid registration is a critical problem in the medical image processing community. We recently proposed an algorithm that we call “Assessing Quality Using Image Registration Circuits” (AQUIRC) to identify non-rigid registration errors and have tested its performance using simulated cases. In this article, we extend our previous work to assess AQUIRC’s ability to detect local non-rigid registration errors and validate it quantitatively at specific clinical landmarks, namely the Anterior Commissure (AC) and the Posterior Commissure (PC). To test our approach on a representative range of error we utilize 5 different registration methods and use 100 target images and 9 atlas images. Our results show that AQUIRC’s measure of registration quality correlates with the true target registration error (TRE) at these selected landmarks with an R2 = 0.542. To compare our method to a more conventional approach, we compute Local Normalized Correlation Coefficient (LNCC) and show that AQUIRC performs similarly. However, a multi-linear regression performed with both AQUIRC’s measure and LNCC shows a higher correlation with TRE than correlations obtained with either measure alone, thus showing the complementarity of these quality measures. We conclude the article by showing that the AQUIRC algorithm can be used to reduce registration errors for all five algorithms. PMID:25095252

  18. Hierarchical Unbiased Graph Shrinkage (HUGS): A Novel Groupwise Registration for Large Data Set

    PubMed Central

    Ying, Shihui; Wu, Guorong; Wang, Qian; Shen, Dinggang

    2014-01-01

    Normalizing all images in a large data set into a common space is a key step in many clinical and research studies, e.g., for brain development, maturation, and aging. Recently, groupwise registration has been developed for simultaneous alignment of all images without selecting a particular image as template, thus potentially avoiding bias in the registration. However, most conventional groupwise registration methods do not explore the data distribution during the image registration. Thus, their performance could be affected by large inter-subject variations in the data set under registration. To solve this potential issue, we propose to use a graph to model the distribution of all image data sitting on the image manifold, with each node representing an image and each edge representing the geodesic pathway between two nodes (or images). Then, the procedure of warping all images to their population center turns to the dynamic shrinking of the graph nodes along their graph edges until all graph nodes become close to each other. Thus, the topology of image distribution on the image manifold is always preserved during the groupwise registration. More importantly, by modeling the distribution of all images via a graph, we can potentially reduce registration error since every time each image is warped only according to its nearby images with similar structures in the graph. We have evaluated our proposed groupwise registration method on both infant and adult data sets, by also comparing with the conventional group-mean based registration and the ABSORB methods. All experimental results show that our proposed method can achieve better performance in terms of registration accuracy and robustness. PMID:24055505

  19. S-HAMMER: Hierarchical Attribute-Guided, Symmetric Diffeomorphic Registration for MR Brain Images

    PubMed Central

    Wu, Guorong; Kim, Minjeong; Wang, Qian; Shen, Dinggang

    2013-01-01

    Deformable registration has been widely used in neuroscience studies for spatial normalization of brain images onto the standard space. Because of possible large anatomical differences across different individual brains, registration performance could be limited when trying to estimate a single directed deformation pathway, i.e., either from template to subject or from subject to template. Symmetric image registration, however, offers an effective way to simultaneously deform template and subject images toward each other until they meet at the middle point. Although some intensity-based registration algorithms have nicely incorporated this concept of symmetric deformation, the pointwise intensity matching between two images may not necessarily imply the matching of correct anatomical correspondences. Based on HAMMER registration algorithm (Shen and Davatzikos, [2002]: IEEE Trans Med Imaging 21:1421–1439), we integrate the strategies of hierarchical attribute matching and symmetric diffeomorphic deformation to build a new symmetric-diffeomorphic HAMMER registration algorithm, called as S-HAMMER. The performance of S-HAMMER has been extensively compared with 14 state-of-the-art nonrigid registration algorithms evaluated in (Klein et al., [2009]: NeuroImage 46:786–802) by using real brain images in LPBA40, IBSR18, CUMC12, and MGH10 datasets. In addition, the registration performance of S-HAMMER, by comparison with other methods, is also demonstrated on both elderly MR brain images (>70 years old) and the simulated brain images with ground-truth deformation fields. In all experiments, our proposed method achieves the best registration performance over all other registration methods, indicating the high applicability of our method in future neuroscience and clinical applications. PMID:23283836

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  2. Robust Adaptive Principal Component Analysis Based on Intergraph Matrix for Medical Image Registration

    PubMed Central

    Xiao, Jinjun; Li, Min; Zhang, Haipeng

    2015-01-01

    This paper proposes a novel robust adaptive principal component analysis (RAPCA) method based on intergraph matrix for image registration in order to improve robustness and real-time performance. The contributions can be divided into three parts. Firstly, a novel RAPCA method is developed to capture the common structure patterns based on intergraph matrix of the objects. Secondly, the robust similarity measure is proposed based on adaptive principal component. Finally, the robust registration algorithm is derived based on the RAPCA. The experimental results show that the proposed method is very effective in capturing the common structure patterns for image registration on real-world images. PMID:25960739

  3. Effect of registration on corpus callosum population differences found with DBM analysis

    NASA Astrophysics Data System (ADS)

    Han, Zhaoying; Thornton-Wells, Tricia A.; Gore, John C.; Dawant, Benoit M.

    2011-03-01

    Deformation Based Morphometry (DBM) is a relatively new method used for characterizing anatomical differences among populations. DBM is based on the analysis of the deformation fields generated by non-rigid registration algorithms, which warp the individual volumes to one standard coordinate system. Although several studies have compared non-rigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithm on population differences that may be uncovered through DBM. In this study, we compared DBM results obtained with five well established non-rigid registration algorithms on the corpus callosum (CC) in thirteen subjects with Williams Syndrome (WS) and thirteen Normal Control (NC) subjects. The five non-rigid registration algorithms include: (1) The Adaptive Basis Algorithm (ABA); (2) Image Registration Toolkit (IRTK); (3) FSL Nonlinear Image Registration Tool (FSL); (4) Automatic Registration Tools (ART); and (5) the normalization algorithm available in SPM8. For each algorithm, the 3D deformation fields from all subjects to the atlas were obtained and used to calculate the Jacobian determinant (JAC) at each voxel in the mid-sagittal slice of the CC. The mean JAC maps for each group were compared quantitatively across different nonrigid registration algorithms. An ANOVA test performed on the means of the JAC over the Genu and the Splenium ROIs shows the JAC differences between nonrigid registration algorithms are statistically significant over the Genu for both groups and over the Splenium for the NC group. These results suggest that it is important to consider the effect of registration when using DBM to compute morphological differences in populations.

  4. A contour-based approach to multisensor image registration.

    PubMed

    Li, H; Manjunath, B S; Mitra, S K

    1995-01-01

    Image registration is concerned with the establishment of correspondence between images of the same scene. One challenging problem in this area is the registration of multispectral/multisensor images. In general, such images have different gray level characteristics, and simple techniques such as those based on area correlations cannot be applied directly. On the other hand, contours representing region boundaries are preserved in most cases. The authors present two contour-based methods which use region boundaries and other strong edges as matching primitives. The first contour matching algorithm is based on the chain-code correlation and other shape similarity criteria such as invariant moments. Closed contours and the salient segments along the open contours are matched separately. This method works well for image pairs in which the contour information is well preserved, such as the optical images from Landsat and Spot satellites. For the registration of the optical images with synthetic aperture radar (SAR) images, the authors propose an elastic contour matching scheme based on the active contour model. Using the contours from the optical image as the initial condition, accurate contour locations in the SAR image are obtained by applying the active contour model. Both contour matching methods are automatic and computationally quite efficient. Experimental results with various kinds of image data have verified the robustness of the algorithms, which have outperformed manual registration in terms of root mean square error at the control points. PMID:18289982

  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. Approximate registration of point clouds with large scale differences

    NASA Astrophysics Data System (ADS)

    Novak, D.; Schindler, K.

    2013-10-01

    3D reconstruction of objects is a basic task in many fields, including surveying, engineering, entertainment and cultural heritage. The task is nowadays often accomplished with a laser scanner, which produces dense point clouds, but lacks accurate colour information, and lacks per-point accuracy measures. An obvious solution is to combine laser scanning with photogrammetric recording. In that context, the problem arises to register the two datasets, which feature large scale, translation and rotation differences. The absence of approximate registration parameters (3D translation, 3D rotation and scale) precludes the use of fine-registration methods such as ICP. Here, we present a method to register realistic photogrammetric and laser point clouds in a fully automated fashion. The proposed method decomposes the registration into a sequence of simpler steps: first, two rotation angles are determined by finding dominant surface normal directions, then the remaining parameters are found with RANSAC followed by ICP and scale refinement. These two steps are carried out at low resolution, before computing a precise final registration at higher resolution.

  7. A tool for intraoperative visualization of registration results

    NASA Astrophysics Data System (ADS)

    King, Franklin; Lasso, Andras; Pinter, Csaba; Fichtinger, Gabor

    2014-03-01

    PURPOSE: Validation of image registration algorithms is frequently accomplished by the visual inspection of the resulting linear or deformable transformation due to the lack of ground truth information. Visualization of transformations produced by image registration algorithms during image-guided interventions allows for a clinician to evaluate the accuracy of the result transformation. Software packages that perform the visualization of transformations exist, but are not part of a clinically usable software application. We present a tool that visualizes both linear and deformable transformations and is integrated in an open-source software application framework suited for intraoperative use and general evaluation of registration algorithms. METHODS: A choice of six different modes are available for visualization of a transform. Glyph visualization mode uses oriented and scaled glyphs, such as arrows, to represent the displacement field in 3D whereas glyph slice visualization mode creates arrows that can be seen as a 2D vector field. Grid visualization mode creates deformed grids shown in 3D whereas grid slice visualization mode creates a series of 2D grids. Block visualization mode creates a deformed bounding box of the warped volume. Finally, contour visualization mode creates isosurfaces and isolines that visualize the magnitude of displacement across a volume. The application 3D Slicer was chosen as the platform for the transform visualizer tool. 3D Slicer is a comprehensive open-source application framework developed for medical image computing and used for intra-operative registration. RESULTS: The transform visualizer tool fulfilled the requirements for quick evaluation of intraoperative image registrations. Visualizations were generated in 3D Slicer with little computation time on realistic datasets. It is freely available as an extension for 3D Slicer. CONCLUSION: A tool for the visualization of displacement fields was created and integrated into 3D Slicer

  8. Hierarchical Multi-modal Image Registration by Learning Common Feature Representations

    PubMed Central

    Ge, Hongkun; Wu, Guorong; Wang, Li; Gao, Yaozong

    2016-01-01

    Mutual information (MI) has been widely used for registering images with different modalities. Since most inter-modality registration methods simply estimate deformations in a local scale, but optimizing MI from the entire image, the estimated deformations for certain structures could be dominated by the surrounding unrelated structures. Also, since there often exist multiple structures in each image, the intensity correlation between two images could be complex and highly nonlinear, which makes global MI unable to precisely guide local image deformation. To solve these issues, we propose a hierarchical inter-modality registration method by robust feature matching. Specifically, we first select a small set of key points at salient image locations to drive the entire image registration. Since the original image features computed from different modalities are often difficult for direct comparison, we propose to learn their common feature representations by projecting them from their native feature spaces to a common space, where the correlations between corresponding features are maximized. Due to the large heterogeneity between two high-dimension feature distributions, we employ Kernel CCA (Canonical Correlation Analysis) to reveal such non-linear feature mappings. Then, our registration method can take advantage of the learned common features to reliably establish correspondences for key points from different modality images by robust feature matching. As more and more key points take part in the registration, our hierarchical feature-based image registration method can efficiently estimate the deformation pathway between two inter-modality images in a global to local manner. We have applied our proposed registration method to prostate CT and MR images, as well as the infant MR brain images in the first year of life. Experimental results show that our method can achieve more accurate registration results, compared to other state-of-the-art image registration

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

    SciTech Connect

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

    2012-01-15

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

  10. 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

  11. A Log-Euclidean polyaffine registration for articulated structures in medical images.

    PubMed

    Martín-Fernández, Miguel Angel; Martín-Fernández, Marcos; Alberola-López, Carlos

    2009-01-01

    In this paper we generalize the Log-Euclidean polyaffine registration framework of Arsigny et al. to deal with articulated structures. This framework has very useful properties as it guarantees the invertibility of smooth geometric transformations. In articulated registration a skeleton model is defined for rigid structures such as bones. The final transformation is affine for the bones and elastic for other tissues in the image. We extend the Arsigny el al.'s method to deal with locally-affine registration of pairs of wires. This enables the possibility of using this registration framework to deal with articulated structures. In this context, the design of the weighting functions, which merge the affine transformations defined for each pair of wires, has a great impact not only on the final result of the registration algorithm, but also on the invertibility of the global elastic transformation. Several experiments, using both synthetic images and hand radiographs, are also presented. PMID:20425983

  12. Nonlinear spatial warping for between-subjects pedobarographic image registration.

    PubMed

    Pataky, T C; Keijsers, N L W; Goulermas, J Y; Crompton, R H

    2009-04-01

    Foot size and shape vary between individuals and the foot adopts arbitrary stance phase postures, so traditional pedobarographic analyses regionalize foot pressure images to afford homologous data comparison. An alternative approach that does not require explicit anatomical labelling and that is used widely in other functional imaging domains is to register images such that homologous structures optimally overlap and then to compare images directly at the pixel level. Image registration represents the preprocessing cornerstone of such pixel-level techniques, so its performance warrants independent attention. The purpose of this study was to evaluate the performance of four between-subjects warping registration algorithms including: Principal Axes (PA), four-parameter Optimal Scaling (OS4), eight-parameter Optimal Projective (OP8), and locally affine Nonlinear (NL). Fifteen subjects performed 10 trials of self-paced walking, and their peak pressure images were registered within-subjects using an optimal rigid body transformation. The resulting mean images were then registered between-subjects using all four methods in all 210 (15x14) subject combinations. All registration methods improved alignment, and each method performed qualitatively well for certain image pairs. However, only the NL consistently performed satisfactorily because of disproportionate anatomical variation in toe lengths and rearfoot/forefoot width, for example. Using three independent image (dis)similarity metrics, MANOVA confirmed that the NL method yielded superior registration performance (p<0.001). These data demonstrate that nonlinear spatial warping is necessary for robust between-subject pedobarographic image registration and, by extension, robust homologous data comparison at the pixel level. PMID:19112023

  13. Multiscale registration of planning CT and daily cone beam CT images for adaptive radiation therapy

    SciTech Connect

    Paquin, Dana; Levy, Doron; Xing Lei

    2009-01-15

    Adaptive radiation therapy (ART) is the incorporation of daily images in the radiotherapy treatment process so that the treatment plan can be evaluated and modified to maximize the amount of radiation dose to the tumor while minimizing the amount of radiation delivered to healthy tissue. Registration of planning images with daily images is thus an important component of ART. In this article, the authors report their research on multiscale registration of planning computed tomography (CT) images with daily cone beam CT (CBCT) images. The multiscale algorithm is based on the hierarchical multiscale image decomposition of E. Tadmor, S. Nezzar, and L. Vese [Multiscale Model. Simul. 2(4), pp. 554-579 (2004)]. Registration is achieved by decomposing the images to be registered into a series of scales using the (BV, L{sup 2}) decomposition and initially registering the coarsest scales of the image using a landmark-based registration algorithm. The resulting transformation is then used as a starting point to deformably register the next coarse scales with one another. This procedure is iterated at each stage using the transformation computed by the previous scale registration as the starting point for the current registration. The authors present the results of studies of rectum, head-neck, and prostate CT-CBCT registration, and validate their registration method quantitatively using synthetic results in which the exact transformations our known, and qualitatively using clinical deformations in which the exact results are not known.

  14. Single- and multimodal subvoxel registration of dissimilar medical images using robust similarity measures

    NASA Astrophysics Data System (ADS)

    Nikou, Christophoros; Heitz, Fabrice; Armspach, Jean-Paul; Namer, Izzie-Jacques

    1998-06-01

    Although a large variety of image registration methods have been described in the literature, only a few approaches have attempted to address the rigid registration of medical images showing gross dissimilarities (due for instance to lesion evolution). In the present paper, we develop driven registration algorithms, relying on robust pixel similarity metrics, that enable an accurate (subvoxel) rigid registration of dissimilar single or multimodal 2D/3D images. In the proposed approach, gross dissimilarities are handled by considering similarity measures related to robust M-estimators. A `soft redescending' estimator (the Geman- McClure p-function) has been adopted to reject gross image dissimilarities during the registration. The registration parameters are estimated using a top down stochastic multigrid relaxation algorithm. Thanks to the stochastic multigrid strategy, the registration is not affected by local minima in the objective function and a manual initialization near the optimal solution is not necessary. The proposed robust similarity metrics compare favorably to the most popular standard similarity metrics, on patient image pairs showing gross dissimilarities. Two case studies are considered: the registration of MR/MR and MR/SPECT image volumes of patients suffering from multiple sclerosis and epilepsy.

  15. IR and visual image registration based on mutual information and PSO-Powell algorithm

    NASA Astrophysics Data System (ADS)

    Zhuang, Youwen; Gao, Kun; Miu, Xianghu

    2014-11-01

    Infrared and visual image registration has a wide application in the fields of remote sensing and military. Mutual information (MI) has proved effective and successful in infrared and visual image registration process. To find the most appropriate registration parameters, optimal algorithms, such as Particle Swarm Optimization (PSO) algorithm or Powell search method, are often used. The PSO algorithm has strong global search ability and search speed is fast at the beginning, while the weakness is low search performance in late search stage. In image registration process, it often takes a lot of time to do useless search and solution's precision is low. Powell search method has strong local search ability. However, the search performance and time is more sensitive to initial values. In image registration, it is often obstructed by local maximum and gets wrong results. In this paper, a novel hybrid algorithm, which combined PSO algorithm and Powell search method, is proposed. It combines both advantages that avoiding obstruction caused by local maximum and having higher precision. Firstly, using PSO algorithm gets a registration parameter which is close to global minimum. Based on the result in last stage, the Powell search method is used to find more precision registration parameter. The experimental result shows that the algorithm can effectively correct the scale, rotation and translation additional optimal algorithm. It can be a good solution to register infrared difference of two images and has a greater performance on time and precision than traditional and visible images.

  16. Analysis of deformable image registration accuracy using computational modeling.

    PubMed

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

    2010-03-01

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

  17. Analysis of deformable image registration accuracy using computational modeling

    SciTech Connect

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

    2010-03-15

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

  18. Rethinking image registration on customizable hardware

    NASA Astrophysics Data System (ADS)

    Bowman, David; Tahtali, Murat; Lambert, Andrew

    2010-08-01

    Image registration is one of the most important tasks in image processing and is frequently one of the most computationally intensive. In cases where there is a high likelihood of finding the exact template in the search image, correlation-based methods predominate. Presumably this is because the computational complexity of a correlation operation can be reduced substantially by transforming the task into the frequency domain. Alternative methods such as minimum Sum of Squared Differences (minSSD) are not so tractable and are normally disfavored. This bias is justified when dealing with conventional computer processors since the operations must be conducted in an essentially sequential manner however we demonstrate it is normally unjustified when the processing is undertaken on customizable hardware such as FPGAs where tasks can be temporally and/or spatially parallelized. This is because the gate-based logic of an FPGA is better suited to the tasks of minSSD i.e. signed-addition hardware can be very cheaply implemented in FPGA fabric, and square operations are easily implemented via a look-up table. In contrast, correlationbased methods require extensive use of multiplier hardware which cannot be so cheaply implemented in the device. Even with modern DSP-oriented FPGAs which contain many "hard" multipliers we experience at least an order of magnitude increase in the number of minSSD hardware modules we can implement compared to cross-correlation modules. We demonstrate successful use and comparison of techniques within an FPGA for registration and correction of turbulence degraded images.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Rönnholm, P.; Haggrén, H.

    2012-07-01

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