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Sample records for 3d-2d registration methods

  1. 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).

  2. 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.

  3. 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.

  4. 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. PMID:27335531

  5. Automatic masking for robust 3D-2D image registration in image-guided spine surgery

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

    During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.

  6. 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

  7. 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

  8. 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes.

    PubMed

    Zhong, Zichun; Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun; Mao, Weihua

    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

  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

    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

  12. 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.

  13. 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.

  14. 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.

  15. 3D/2D model-to-image registration applied to TIPS surgery.

    PubMed

    Jomier, Julien; Bullitt, Elizabeth; Van Horn, Mark; Pathak, Chetna; Aylward, Stephen R

    2006-01-01

    We have developed a novel model-to-image registration technique which aligns a 3-dimensional model of vasculature with two semiorthogonal fluoroscopic projections. Our vascular registration method is used to intra-operatively initialize the alignment of a catheter and a preoperative vascular model in the context of image-guided TIPS (Transjugular, Intrahepatic, Portosystemic Shunt formation) surgery. Registration optimization is driven by the intensity information from the projection pairs at sample points along the centerlines of the model. Our algorithm shows speed, accuracy and consistency given clinical data.

  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. Intensity-based 3D/2D registration for percutaneous intervention of major aorto-pulmonary collateral arteries

    NASA Astrophysics Data System (ADS)

    Couet, Julien; Rivest-Henault, David; Miro, Joaquim; Lapierre, Chantal; Duong, Luc; Cheriet, Mohamed

    2012-02-01

    Percutaneous cardiac interventions rely mainly on the experience of the cardiologist to safely navigate inside soft tissues vessels under X-ray angiography guidance. Additional navigation guidance tool might contribute to improve reliability and safety of percutaneous procedures. This study focus on major aorta-pulmonary collateral arteries (MAPCAs) which are pediatric structures. We present a fully automatic intensity-based 3D/2D registration method that accurately maps pre-operatively acquired 3D tomographic vascular data of a newborn patient over intra-operatively acquired angiograms. The tomographic dataset 3D pose is evaluated by comparing the angiograms with simulated X-ray projections, computed from the pre-operative dataset with a proposed splatting-based projection technique. The rigid 3D pose is updated via a transformation matrix usually defined in respect of the C-Arm acquisition system reference frame, but it can also be defined in respect of the projection plane local reference frame. The optimization of the transformation is driven by two algorithms. First the hill climbing local search and secondly a proposed variant, the dense hill climbing. The latter makes the search space denser by considering the combinations of the registration parameters instead of neighboring solutions only. Although this study focused on the registration of pediatric structures, the same procedure could be applied for any cardiovascular structures involving CT-scan and X-ray angiography. Our preliminary results are promising that an accurate (3D TRE 0.265 +/- 0.647mm) and robust (99% success rate) bi-planes registration of the aorta and MAPCAs from a initial displacement up to 20mm and 20° can be obtained within a reasonable amount of time (13.7 seconds).

  18. 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

  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.

    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

  2. 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

  3. 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.

  4. Dynamic tracking of a deformable tissue based on 3D-2D MR-US image registration

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

    Real-time registration of pre-operative magnetic resonance (MR) or computed tomography (CT) images with intra-operative Ultrasound (US) images can be a valuable tool in image-guided therapies and interventions. This paper presents an automatic method for dynamically tracking the deformation of a soft tissue based on registering pre-operative three-dimensional (3D) MR images to intra-operative two-dimensional (2D) US images. The registration algorithm is based on concepts in state estimation where a dynamic finite element (FE)- based linear elastic deformation model correlates the imaging data in the spatial and temporal domains. A Kalman-like filtering process estimates the unknown deformation states of the soft tissue using the deformation model and a measure of error between the predicted and the observed intra-operative imaging data. The error is computed based on an intensity-based distance metric, namely, modality independent neighborhood descriptor (MIND), and no segmentation or feature extraction from images is required. The performance of the proposed method is evaluated by dynamically deforming 3D pre-operative MR images of a breast phantom tissue based on real-time 2D images obtained from an US probe. Experimental results on different registration scenarios showed that deformation tracking converges in a few iterations. The average target registration error on the plane of 2D US images for manually selected fiducial points was between 0.3 and 1.5 mm depending on the size of deformation.

  5. 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.

  6. 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

  7. 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

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

    PubMed

    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 run) the

  9. 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

  10. 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 runtime (29.3 s). The GO metric improved

  11. 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.

  12. 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.

  13. 3D/2D convertible projection-type integral imaging using concave half mirror array.

    PubMed

    Hong, Jisoo; Kim, Youngmin; Park, Soon-gi; Hong, Jong-Ho; Min, Sung-Wook; Lee, Sin-Doo; Lee, Byoungho

    2010-09-27

    We propose a new method for implementing 3D/2D convertible feature in the projection-type integral imaging by using concave half mirror array. The concave half mirror array has the partially reflective characteristic to the incident light. And the reflected term is modulated by the concave mirror array structure, while the transmitted term is unaffected. With such unique characteristic, 3D/2D conversion or even the simultaneous display of 3D and 2D images is also possible. The prototype was fabricated by the aluminum coating and the polydimethylsiloxane molding process. We could experimentally verify the 3D/2D conversion and the display of 3D image on 2D background with the fabricated prototype.

  14. 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.

  15. 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.

  16. 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.

  17. Combined experimental and theoretical probe of the lifetime of the 3 d 2D5 /2 state in 40Ca+

    NASA Astrophysics Data System (ADS)

    Guan, Hua; Shao, Hu; Qian, Yuan; Huang, Yao; Liu, Pei-Liang; Bian, Wu; Li, Cheng-Bin; Sahoo, B. K.; Gao, Ke-Lin

    2015-02-01

    In light of the diverse range of reported values for the lifetimes of metastable states of 40Ca+ , we have carried out afresh both measurements and theoretical investigation to confirm the lifetime of its 3 d 2D5 /2 state (τ3 d 5 /2) . A high-efficiency quantum state detection method by monitoring the quantum jumps of a laser-cooled single Ca+ ion in a miniature ring Paul trap was employed in the measurement. Also, sophisticated calculations were performed considering higher order nonlinear terms in the relativistic coupled-cluster (RCC) method with all possible single and double excitations, but accounting only for the important triple excitations from both the core and the valence orbitals. Systematic factors affecting measurement, such as collision with background gases, heating effects, the power of the 866-nm laser, and state detection errors were carefully analyzed. Our observational and theoretical values for τ3 d 5 /2 are 1174(10) ms and 1172(3) ms, respectively, which agree well with the experimental results reported by P. A. Barton et al. [Phys. Rev. A 62, 032503 (2000), 10.1103/PhysRevA.62.032503] and A. Kreuter et al. [Phys. Rev. A 71, 032504 (2005), 10.1103/PhysRevA.71.032504]. The present theoretical analysis demonstrates that the contributions from the core triples and Breit interaction are notable, as they improve the theoretical results obtained in the previous RCC calculations [B. K. Sahoo, Phys. Rev. A 74, 062504 (2006), 10.1103/PhysRevA.74.062504].

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. An automatic registration method based on runway detection

    NASA Astrophysics Data System (ADS)

    Zhang, Xiuqiong; Yu, Li; Huang, Guo

    2014-04-01

    Runway is seen distinctly that is a crucial condition in the process of approaching and landing. One of the enhanced vision methods is image fusion method between the infrared and visible images in EVS (Enhanced Vision System). The image registration plays a very important role in image fusion. So, an automatic image registration method is proposed based on the accurate runway detection. Firstly, runway is detected using DWT (discrete wavelets transform) from the infrared and visible images respectively. Then, a fitting triangle is constructed according to the edges of runway. The corresponding feature points extracted from the middle points of edges and the centroid of triangle are used to compute the transform parameters. The results of registration are more accurate and efficient than those of registration based on mutual information. This method is robust and has less computation which can be applied to real-time system.

  11. Automatic registration method for mobile LiDAR data

    NASA Astrophysics Data System (ADS)

    Wang, Ruisheng; Ferrie, Frank P.

    2015-01-01

    We present an automatic mutual information (MI) registration method for mobile LiDAR and panoramas collected from a driving vehicle. The suitability of MI for registration of aerial LiDAR and aerial oblique images has been demonstrated under an assumption that minimization of joint entropy (JE) is a sufficient approximation of maximization of MI. We show that this assumption is invalid for the ground-level data. The entropy of a LiDAR image cannot be regarded as approximately constant for small perturbations. Instead of minimizing the JE, we directly maximize MI to estimate corrections of camera poses. Our method automatically registers mobile LiDAR with spherical panoramas over an approximate 4-km drive, and is the first example we are aware of that tests MI registration in a large-scale context.

  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. A new patient registration method for intensive care department management.

    PubMed

    Van Aken, P; Bossaert, L; Gilot, C; Tielemans, L

    1987-01-01

    A new method to describe intensive care department performance is presented. The method is a complication of available administrative and medical data, completed with a severity of illness measure (Acute Physiology And Chronic Health Evaluation, APACHE) and the registration of nursing care intensity. The development of this latter patient stratification system (Intensive Care Activity Score, INCAS) is described. The performance of the method is demonstrated by a study of 200 consecutive admissions.

  14. 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.

  15. [A coarse-to-fine registration method for satellite infrared image and visual image].

    PubMed

    Hu, Yong-Li; Wang, Liang; Liu, Rong; Zhang, Li; Duan, Fu-Qing

    2013-11-01

    In the present paper, in order to resolve the registration of the multi-mode satellite images with different signal properties and features, a two-phase coarse-to-fine registration method is presented and is applied to the registration of satellite infrared images and visual images. In the coarse registration phase of this method, the edge of infrared and visual images is firstly detected. Then the Fourier-Mellin transform is adopted to process the edge images. Finally, the affine transformation parameters of the registration are computed rapidly by the transformation relation between the registering images in frequency domain. In the fine registration phase of the proposed method, the feature points of infrared and visual images are firstly detected by Harris operator. Then the matched feature points of infrared and visual images are determined by the cross-correlation similarity of their local neighborhoods. The fine registration is finally realized according to the spatial correspondent relation of the matched feature points in infrared and visual images. The proposed coarse-to-fine registration method derives both the advantages of two methods, the high efficiency of Fourier-Mellin transform based registration method and the accuracy of Harris operator based registration method, which is considered the novelty and merit of the proposed method. To evaluate the performance of the proposed registration method, the coarse-to-fine registration method is implemented on the infrared and visual images captured by the FY-2D meteorological satellite. The experimental results show that the presented registration method is robust and has acceptable registration accuracy.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. Complexity and accuracy of image registration methods in SPECT-guided radiation therapy

    NASA Astrophysics Data System (ADS)

    Yin, L. S.; Tang, L.; Hamarneh, G.; Gill, B.; Celler, A.; Shcherbinin, S.; Fua, T. F.; Thompson, A.; Liu, M.; Duzenli, C.; Sheehan, F.; Moiseenko, V.

    2010-01-01

    The use of functional imaging in radiotherapy treatment (RT) planning requires accurate co-registration of functional imaging scans to CT scans. We evaluated six methods of image registration for use in SPECT-guided radiotherapy treatment planning. Methods varied in complexity from 3D affine transform based on control points to diffeomorphic demons and level set non-rigid registration. Ten lung cancer patients underwent perfusion SPECT-scans prior to their radiotherapy. CT images from a hybrid SPECT/CT scanner were registered to a planning CT, and then the same transformation was applied to the SPECT images. According to registration evaluation measures computed based on the intensity difference between the registered CT images or based on target registration error, non-rigid registrations provided a higher degree of accuracy than rigid methods. However, due to the irregularities in some of the obtained deformation fields, warping the SPECT using these fields may result in unacceptable changes to the SPECT intensity distribution that would preclude use in RT planning. Moreover, the differences between intensity histograms in the original and registered SPECT image sets were the largest for diffeomorphic demons and level set methods. In conclusion, the use of intensity-based validation measures alone is not sufficient for SPECT/CT registration for RTTP. It was also found that the proper evaluation of image registration requires the use of several accuracy metrics.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. Registration method for infrared images under conditions of fixed-pattern noise

    NASA Astrophysics Data System (ADS)

    Zuo, Chao; Chen, Qian; Gu, Guohua; Sui, Xiubao

    2012-05-01

    This paper proposes a new registration method for infrared images under conditions of fixed-pattern noise (FPN). Conventional registration techniques are susceptible to FPN and it is therefore very desirable to have a registration algorithm that is tolerant to FPN. For this purpose, we utilize the difference of the cross-power spectrum of two discrete shifted images to suppress the noise power spectrum while the shifts information is well preserved. In particular, we show that the phase of the cross-power spectrum difference is a periodic two-dimensional binary stripe signal with the exact shifts determined to subpixel accuracy by the number of periods of the phase difference along each frequency axis. Robust estimates of shifts can be obtained by transforming its discontinuities to Hough domain. Experimental results show that the proposed method exhibits robust and accurate registration performance even for the noisy images that could not be handled by conventional registration algorithms. We have also incorporated this technique to a registration-based nonuniformity correction (NUC) framework, indicating that our registration technique is able to estimate motion parameters reliably, leading to satisfactory NUC result.

  8. Fully automatic hybrid registration method based on point feature detection without user intervention

    NASA Astrophysics Data System (ADS)

    Koo, Bang-Bon; Lee, Jong-Min; Kim, June-Sic; Kim, In-Young; Kwon, Jun-Soo; Kim, Sun I.

    2006-03-01

    In earlier work (KIM, J.S, MBEC, 2003), we demonstrated the registration method with a non-linear transformation using intensity similarity and feature similarity. Although the former approach showed good match in global shape of brain and feature-defined region, method contains user interventions for defining appropriate and sufficient number features. While manual delineating the region of interests for sufficient number of feature is a very time-consuming and can provide intra-, inter-rater variability, we proposed fully automatic hybrid registration via automatic feature defining method. Automatic feature definition was performed on the cortical surface from CLASP (KIM, J.S, Neuroimage, 2005) with using cortical surface matching algorithm (Robbins, S., MIA, 2004) and then applied to hybrid registration. The object of this work is to develop fully automated hybrid registration method which reveals enhanced performance in comparison to previous automated registration methods. In the result, our proposed scheme showed efficient performance from maintaining the strong points of hybrid registration without any user intervention.

  9. A hybrid registration-based method for whole-body micro-CT mice images.

    PubMed

    Qu, Xiaochao; Gao, Xueyuan; Xu, Xianhui; Zhu, Shouping; Liang, Jimin

    2016-07-01

    The widespread use of whole-body small animal in vivo imaging in preclinical research has proposed the new demands on imaging processing and analysis. Micro-CT provides detailed anatomical structural information for continuous detection and different individual comparison, but the body deformation happened during different data acquisition needs sophisticated registration. In this paper, we propose a hybrid method for registering micro-CT mice images, which combines the strengths of point-based and intensity-based registration methods. Point-based non-rigid method using thin-plate spline robust point matching algorithm is utilized to acquire a coarse registration. And then intensity-based non-rigid method using normalized mutual information, Halton sampling and adaptive stochastic gradient descent optimization is used to acquire precise registration. Two accuracy metrics, Dice coefficient and average surface distance are used to do the quantitative evaluation. With the intra- and intersubject micro-CT mice images registration assessment, the hybrid method has been proven capable of excellent performance on micro-CT mice images registration.

  10. 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.

  11. [Method of multi-resolution 3D image registration by mutual information].

    PubMed

    Ren, Haiping; Wu, Wenkai; Yang, Hu; Chen, Shengzu

    2002-12-01

    Maximization of mutual information is a powerful criterion for 3D medical image registration, allowing robust and fully accurate automated rigid registration of multi-modal images in a various applications. In this paper, a method based on normalized mutual information for 3D image registration was presented on the images of CT, MR and PET. Powell's direction set method and Brent's one-dimensional optimization algorithm were used as optimization strategy. A multi-resolution approach is applied to speedup the matching process. For PET images, pre-procession of segmentation was performed to reduce the background artefacts. According to the evaluation by the Vanderbilt University, Sub-voxel accuracy in multi-modality registration had been achieved with this algorithm. PMID:12561358

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. EVolution: an edge-based variational method for non-rigid multi-modal image registration

    NASA Astrophysics Data System (ADS)

    de Senneville, B. Denis; Zachiu, C.; Ries, M.; Moonen, C.

    2016-10-01

    Image registration is part of a large variety of medical applications including diagnosis, monitoring disease progression and/or treatment effectiveness and, more recently, therapy guidance. Such applications usually involve several imaging modalities such as ultrasound, computed tomography, positron emission tomography, x-ray or magnetic resonance imaging, either separately or combined. In the current work, we propose a non-rigid multi-modal registration method (namely EVolution: an edge-based variational method for non-rigid multi-modal image registration) that aims at maximizing edge alignment between the images being registered. The proposed algorithm requires only contrasts between physiological tissues, preferably present in both image modalities, and assumes deformable/elastic tissues. Given both is shown to be well suitable for non-rigid co-registration across different image types/contrasts (T1/T2) as well as different modalities (CT/MRI). This is achieved using a variational scheme that provides a fast algorithm with a low number of control parameters. Results obtained on an annotated CT data set were comparable to the ones provided by state-of-the-art multi-modal image registration algorithms, for all tested experimental conditions (image pre-filtering, image intensity variation, noise perturbation). Moreover, we demonstrate that, compared to existing approaches, our method possesses increased robustness to transient structures (i.e. that are only present in some of the images).

  17. 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.

  18. Semiautomatic Registration of Pre- and Postbrain Tumor Resection Laser Range Data: Method and Validation

    PubMed Central

    Ding, Siyi; Miga, Michael I.; Noble, Jack H.; Cao, Aize; Dumpuri, Prashanth; Thompson, Reid C.

    2009-01-01

    This paper presents a semiautomatic method for the registration of images acquired during surgery with a tracked laser range scanner (LRS). This method, which relies on the registration of vessels that can be visualized in the pre- and the postresection images, is a component of a larger system designed to compute brain shift that occurs during tumor resection cases. Because very large differences between pre- and postresection images are typically observed, the development of fully automatic methods to register these images is difficult. The method presented herein is semiautomatic and requires only the identification of a number of points along the length of the vessels. Vessel segments joining these points are then automatically identified using an optimal path finding algorithm that relies on intensity features extracted from the images. Once vessels are identified, they are registered using a robust point-based nonrigid registration algorithm. The transformation computed with the vessels is then applied to the entire image. This permits establishment of a complete correspondence between the pre- and post-3-D LRS data. Experiments show that the method is robust to operator errors in localizing homologous points and a quantitative evaluation performed on ten surgical cases shows submillimetric registration accuracy. PMID:19272895

  19. A comparison of rigid registration methods for prostate localization on CBCT and the dependence on rectum distension

    NASA Astrophysics Data System (ADS)

    Boydev, C.; Pasquier, D.; Derraz, F.; Peyrodie, L.; Taleb-Ahmed, A.; Thiran, J. P.

    2014-03-01

    We evaluated automatic three-dimensional intensity-based rigid registration (RR) methods for prostate localization on CBCT scans and studied the impact of rectum distension on registration quality. 106 CBCT scans of 9 prostate patients were used. Each one was registered to the planning computed tomography (CT) scan using different methods: (a) global registration, (b) pelvis bony structure registration, (c) bony registration refined by a local prostate registration using the CT clinical target volume (CTV) expanded with 1, 3, 5, 8, 10, 12, 15 or 20-mm margin. Automatic CBCT contours were generated after propagation of the manual CT contours. To evaluate results, a radiation oncologist was asked to manually delineate the CTV on the CBCT scans (gold standard). The Dice similarity coefficients between propagated and manual CBCT contours were calculated.

  20. 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.

  1. Registration of ultrasound echography for intraoperative use: a newly developed multiproperty method

    NASA Astrophysics Data System (ADS)

    Hata, Nobuhiko; Suzuki, Makoto; Dohi, Takeyoshi; Iseki, Hiroshi; Takakura, Kintomo; Hashimoto, Daijo

    1994-09-01

    Nowadays, several studies on 3D medical image registration are being investigated. The main purpose of these studies is to integrate complimentary information provided by different modalities. This paper describes a newly developed registration method of ultrasound echography to 3D medical image. The registration process consists of two stages. In the first stage, a registration process of the ultrasound echography to the pre- operative 3D images is performed using a position sensor. This is a rigid transformation, which can't provide a perfect match because the intra-operative organ is deformed or moved. The second step is a local matching process, where the current position of the ultrasound echography is approximated with a search-based surface matching algorithm. We used the 3D chamfer matching for this approximation. In this method, a goodness-of- match function, i.e., generalized distance, that rates the geometrical transformation is computed and minimized. In a preliminary experiment, the search-based matching process was examined. The algorithm and its accuracy were evaluated with an artificial transformed set of coordinates given as the initial guess. We also performed a clinical application and results confirmed the suitability of this method to clinical use.

  2. 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.

  3. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas.

    PubMed

    Chen, Zhenwei; Zhang, Lei; Zhang, Guo

    2016-09-17

    Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR) data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR) thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level.

  4. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas.

    PubMed

    Chen, Zhenwei; Zhang, Lei; Zhang, Guo

    2016-01-01

    Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR) data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR) thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level. PMID:27649207

  5. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas

    PubMed Central

    Chen, Zhenwei; Zhang, Lei; Zhang, Guo

    2016-01-01

    Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR) data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR) thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level. PMID:27649207

  6. 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.

  7. 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%.

  8. 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.

  9. 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.

  10. Automatic SAR and optical images registration method based on improved SIFT

    NASA Astrophysics Data System (ADS)

    Yue, Chunyu; Jiang, Wanshou

    2014-10-01

    An automatic SAR and optical images registration method based on improved SIFT is proposed in this paper, which is a two-step strategy, from rough to accuracy. The geometry relation of images is first constructed by the geographic information, and images are arranged based on the elevation datum plane to eliminate rotation and resolution differences. Then SIFT features extracted by the dominant direction improved SIFT from two images are matched by SSIM as similar measure according to structure information of the SIFT feature. As rotation difference is eliminated in images of flat area after rough registration, the number of correct matches and correct matching rate can be increased by altering the feature orientation assignment. And then, parallax and angle restrictions are introduced to improve the matching performance by clustering analysis in the angle and parallax domains. Mapping the original matches to the parallax feature space and rotation feature space in sequence, which are established by the custom defined parallax parameters and rotation parameters respectively. Cluster analysis is applied in the parallax feature space and rotation feature space, and the relationship between cluster parameters and matching result is analysed. Owing to the clustering feature, correct matches are retained. Finally, the perspective transform parameters for the registration are obtained by RANSAC algorithm with removing the false matches simultaneously. Experiments show that the algorithm proposed in this paper is effective in the registration of SAR and optical images with large differences.

  11. A deformable image registration method to handle distended rectums in prostate cancer radiotherapy

    SciTech Connect

    Gao Song; Zhang Lifei; Wang He; Crevoisier, Renaud de; Kuban, Deborah D.; Mohan, Radhe; Dong Lei

    2006-09-15

    In image-guided adaptive radiotherapy, it is important to have the capability to automatically and accurately delineate the rectal wall, which is a major dose-limiting organ in prostate cancer radiotherapy. As image registration is a process to find the spatial correspondence between two images, a major challenge in intensity-based deformable image registration is to deal with the situation where no correspondence exists for some objects between the two images to be registered. One example is the variation of rectal contents due to the presence and absence of bowel gas. The intensity-based deformable image registration methods alone cannot create the correct spatial transformation if there is no correspondence between the source and target images. In this study we implemented an automatic image intensity modification procedure to create artificial gas pockets in the planning computed tomography (CT) images. A diffusion-based deformable image registration algorithm was developed to use an adaptive smoothing algorithm to better handle large organ deformations. The process was tested in 15 prostate cancer cases and 30 daily CT images containing the largest distended rectums. The manually delineated rectums agreed well with the autodelineated rectums when using the image-intensity modification procedure.

  12. 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.

  13. A method for registration and model-based segmentation of Doppler ultrasound images

    NASA Astrophysics Data System (ADS)

    Kalinić, Hrvoje; Lončarić, Sven; Čikeš, Maja; Milicic, Davor; Čikeš, Ivo; Sutherland, George; Bijnens, Bart

    2009-02-01

    Morphological changes of Doppler ultrasound images are an important source of information for diagnosis of cardiovascular diseases. Quantification of these flow profiles requires segmentation of the ultrasound images. In this article, we propose a new model-based method for segmentation of (aortic outflow) velocity profiles. The method is based on a procedure for registration using a geometric transformation specifically designed for matching Doppler ultrasound profiles. After manual segmentation of a model image, the model image is temporarily registered to a new image using two manually defined points in time. Next, a non-rigid registration was carried out in the velocity direction. As a similarfity measure normalized mutual information is used, while optimization is performed by a genetic algorithm. The registration method is experimentally validated using an in-silico image phantom, and showed an accuracy of 5.4%. The model based on segmentation is evaluated in a seris of aortic outflow Doppler ultrasound images from 30 normal volunteers. Comparing the automated method to the manual delineation by an expert cardiologist the method proved accurate to 6.6%. The experimental results confirm the accuracy of the approach and shows that the method can be used for the segmentation of the clinically obtained aortic outflow velocity profiles.

  14. Atlas to patient registration with brain tumor based on a mesh-free method.

    PubMed

    Diaz, Idanis; Boulanger, Pierre

    2015-08-01

    Brain atlas to patient registration in the presence of tumors is a challenging task because its presence cause brain structure deformations and introduce large intensity variation between the affected areas. This large dissimilarity affects the results of traditional registration methods based on intensity or shape similarities. In order to overcome these problems, we propose a novel method that brings closer the atlas and the patient's image by simulating the mechanical behavior of brain deformation under a tumor pressure. The proposed method use a mesh-free total Lagrangian Explicit Dynamic algorithm for the simulation of atlas deformation and a data driven model of the tumor using multi-modal MRI segmentation. Experimental results look structurally very similar to the patient's image and outperform two of the top ranking algorithms.

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. A high accuracy multi-image registration method for tracking MRI-guided robots

    NASA Astrophysics Data System (ADS)

    Shang, Weijian; Fischer, Gregory S.

    2012-02-01

    Recent studies have demonstrated an increasing number of functional surgical robots and other devices operating in the Magnetic Resonance Imaging (MRI) environment. Calibration and tracking of the robotic device is essential during such MRI-guided procedures. A fiducial tracking module is placed on the base or the end effector of the robot to localize it within the scanner, and thus the patient coordinate system. The fiducial frame represents a Z shape and is made of seven tubes filled with high contrast fluid. The frame is highlighted in the MR images and is used in localization. Compared to the former single image registration method, multiple images are used in this algorithm to calculate the position and orientation of the frame, and thus the robot. By using multiple images together, measurement error is reduced and the rigid requirement of slow to acquire high quality of images is not required. Accuracy and performance were evaluated in experiments which were operated with a Philips 3T MRI scanner. Presented is an accuracy comparison of the new method with varied number of images, and a comparison to more traditional single image registration techniques.

  6. 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

  7. 2D/3D registration with the CMA-ES method

    NASA Astrophysics Data System (ADS)

    Gong, Ren Hui; Abolmaesumi, Purang

    2008-03-01

    In this paper, we propose a new method for 2D/3D registration and report its experimental results. The method employs the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm to search for an optimal transformation that aligns the 2D and 3D data. The similarity calculation is based on Digitally Reconstructed Radiographs (DRRs), which are dynamically generated from the 3D data using a hardware-accelerated technique - Adaptive Slice Geometry Texture Mapping (ASGTM). Three bone phantoms of different sizes and shapes were used to test our method: a long femur, a large pelvis, and a small scaphoid. A collection of experiments were performed to register CT to fluoroscope and DRRs of these phantoms using the proposed method and two prior work, i.e. our previously proposed Unscented Kalman Filter (UKF) based method and a commonly used simplex-based method. The experimental results showed that: 1) with slightly more computation overhead, the proposed method was significantly more robust to local minima than the simplex-based method; 2) while as robust as the UKF-based method in terms of capture range, the new method was not sensitive to the initial values of its exposed control parameters, and has also no special requirement about the cost function; 3) the proposed method was fast and consistently achieved the best accuracies in all compared methods.

  8. 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.

  9. 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

  10. 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.

  11. A fully automatic image-to-world registration method for image-guided procedure with intraoperative imaging updates

    NASA Astrophysics Data System (ADS)

    Li, Senhu; Sarment, David

    2016-03-01

    Image-guided procedure with intraoperative imaging updates has made a big impact on minimally invasive surgery. Compact and mobile CT imaging device combining with current commercial available image guided navigation system is a legitimate and cost-efficient solution for a typical operating room setup. However, the process of manual fiducial-based registration between image and physical spaces (image-to-world) is troublesome for surgeons during the procedure, which results in much procedure interruptions and is the main source of registration errors. In this study, we developed a novel method to eliminate the manual registration process. Instead of using probe to manually localize the fiducials during the surgery, a tracking plate with known fiducial positions relative to the reference coordinates is designed and fabricated through 3D printing technique. The workflow and feasibility of this method has been studied through a phantom experiment.

  12. 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.

  13. 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

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM ADMINISTRATION OF 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...

  1. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM ADMINISTRATION OF 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...

  2. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM ADMINISTRATION OF 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...

  3. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM ADMINISTRATION OF 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...

  4. Injury pattern in youth team handball: a comparison of two prospective registration methods.

    PubMed

    Olsen, O-E; Myklebust, G; Engebretsen, L; Bahr, R

    2006-12-01

    The purpose of this study was to examine the injury incidence and pattern of injuries in youth female and male team handball players using two different prospective registration methods; match reports (90 teams, 1080 players) and coach reports (34 teams, 428 players). A total of 118 injuries were recorded by the coach report, of which 93 (79%) were acute injuries (incidence training: 0.9+/-0.16 injuries/1000 player hours; matches: 9.9+/-1.26; rate ratio vs training: 10.8 [95% confidence interval (CI) 7.0-16.6]; P<0.0001) and 25 (21%) were overuse injuries. Knee (26%) and ankle (24%) injuries accounted for half of the acute injuries (training: 0.5+/-0.12 injuries/1000/h; matches: 4.4+/-0.84; rate ratio vs training: 8.0 (95% CI 4.5-14.5); P<0.0001). No gender difference was found in the injury rate (rate ratio female vs male: 1.3 (95% CI 0.8-2.1); P=0.40). Most of the injuries occurred in the attacking phase by back or wing players doing a plant-and-cut, landing or turning movement, and more than half in contact situations with the opponent. Similar results were observed for acute match injuries in the match report. These results indicate that the rate of injuries in youth team handball is as high as at the senior level, and prevention should focus on knee and ankle injuries. The coach report seems to be the best method to register injuries in youth team handball to provide a full spectrum of injuries according to their type, incidence and severity. PMID:17121645

  5. 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…

  6. Multifunction extension of simplex optimization method for mutual information-based registration of ultrasound volumes

    NASA Astrophysics Data System (ADS)

    Zagrodsky, Vladimir; Shekhar, Raj; Cornhill, J. Fredrick

    2001-07-01

    Mutual information has been demonstrated to be an accurate and reliable criterion function to perform registration of medical data. Due to speckle noise, ultrasound volumes do not provide a smooth mutual information function. Consequently the optimization technique used must be robust enough to avoid local maxima and converge on the desired global maximum eventually. While the well-known downhill simplex optimization uses a single criterion function, our extension to multi-function optimization uses three criterion functions, namely mutual information computed at three levels of intensity quantization and hence three degrees of noise suppression. Registration was performed with rigid as well as simple non-rigid transformation modes for real-time 3D ultrasound datasets of the left ventricle. Pairs of frames corresponding to the most stationary end- diastolic cardiac phase were chosen, and an initial misalignment was artificially introduced between them. The multi-function simplex optimization reduced the failure rate by a factor of two in comparison to the standard simplex optimization, while the average accuracy for the successful cases was unchanged. A more robust registration resulted form the parallel use of criterion functions. The additional computational cost was negligible, as each of the three implementations of the mutual information used the same joint histogram and required no extra spatial transformation.

  7. 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

  8. 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

  9. Articulated registration: elastic registration based on a wire-model

    NASA Astrophysics Data System (ADS)

    Martin-Fernandez, Miguel A.; Munyoz-Moreno, Emma; Martin-Fernandez, Marcos; Alberola-Lopez, Carlos

    2005-04-01

    In this paper we propose a new method of elastic registration of anatomical structures that bears an inner skeleton, such as the knee, hand or spine. Such a method has to deal with great degrees of variability, specially for the case of inter-subject registration; but even for the intra-subject case the degree of variability of images will be large since the structures we bear in mind are articulated. Rigid registration methods are clearly inappropriate for this problem, and well-known elastic methods do not usually incorporate the restriction of maintaining long skeletal structures straight. A new method is therefore needed to deal with such a situation; we call this new method "articulated registration". The inner bone skeleton is modeled with a wire model, where wires are drawn by connecting landmarks located in the main joints of the skeletal structure to be registered (long bones). The main feature of our registration method is that within the bone axis (specifically, where the wires are) an exact registration is guaranteed, while for the remaining image points an elastic registration is carried out based on a distance transform (with respect to the model wires); this causes the registration on long bones to be affine to all practical purposes, while the registration of soft tissue -- far from the bones -- is elastic. As a proof-of-concept of this method we describe the registration of hands on radiographs.

  10. 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

  11. 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.

  12. 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.

  13. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... registration card or other method of registration prescribed by the Director of Selective Service by a person... the records (master computer file) of the Selective Service System. Registration is completed when... Director include completing a Selective Service Registration Card at a classified Post Office,...

  14. 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

  15. 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

  16. 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 structures

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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.

  2. Optical design of wavelength selective CPVT system with 3D/2D hybrid concentration

    NASA Astrophysics Data System (ADS)

    Ahmad, N.; Ijiro, T.; Yamada, N.; Kawaguchi, T.; Maemura, T.; Ohashi, H.

    2012-10-01

    Optical design of a concentrating photovoltaic/thermal (CPVT) system is carried out. Using wavelength-selective optics, the system demonstrates 3-D concentration onto a solar cell and 2-D concentration onto a thermal receiver. Characteristics of the two types of concentrator systems are examined with ray-tracing analysis. The first system is a glazed mirror-based concentrator system mounted on a 2-axis pedestal tracker. The size of the secondary optical element is minimized to decrease the cost of the system, and it has a wavelength-selective function for performing 3-D concentration onto a solar cell and 2-D concentration onto a thermal receiver. The second system is a non-glazed beamdown concentrator system containing parabolic mirrors in the lower part. The beam-down selective mirror performs 3-D concentration onto a solar cell placed above the beam-down selective mirror, and 2-D concentration down to a thermal receiver placed at the bottom level. The system is mounted on a two-axis carousel tracker. A parametric study is performed for those systems with different geometrical 2-D/3-D concentration ratios. Wavelength-selective optics such as hot/cold mirrors and spectrum-splitting technologies are taken into account in the analysis. Results show reduced heat load on the solar cell and increased total system efficiency compared to a non-selective CPV system. Requirements for the wavelength-selective properties are elucidated. It is also shown that the hybrid concept with 2-D concentration onto a thermal receiver and 3-D concentration onto a solar cell has an advantageous geometry because of the high total system efficiency and compatibility with the piping arrangement of the thermal receiver.

  3. Delivery Path Length and Holding Tree Minimization Method of Securities Delivery among the Registration Agencies Connected as Non-Tree

    NASA Astrophysics Data System (ADS)

    Shimamura, Atsushi; Moritsu, Toshiyuki; Someya, Harushi

    To dematerialize the securities such as stocks or cooporate bonds, the securities were registered to account in the registration agencies which were connected as tree. This tree structure had the advantage in the management of the securities those were issued large amount and number of brands of securities were limited. But when the securities such as account receivables or advance notes are dematerialized, number of brands of the securities increases extremely. In this case, the management of securities with tree structure becomes very difficult because of the concentration of information to root of the tree. To resolve this problem, using the graph structure is assumed instead of the tree structure. When the securities are kept with tree structure, the delivery path of securities is unique, but when securities are kept with graph structure, path of delivery is not unique. In this report, we describe the requirement of the delivery path of securities, and we describe selecting method of the path.

  4. 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

  5. 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.

  6. 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

  7. A gaseous radiochemical method for registration of ionizing radiation and its possible applications in science and economy

    NASA Astrophysics Data System (ADS)

    Lebedev, S. G.; Akulinichev, S. V.; Iljinov, A. S.; Yants, V. E.

    2006-05-01

    This work presents a new possibility of registration of ionizing radiation by the flowing gaseous radiochemical method (FGRM). The specified method uses the property of some solid crystalline lattice materials for a free emission of radioactive isotopes of inert gas atoms formed as a result of nuclear reactions. Generated in an ampoule of the detector, the radioactive inert gases are transported by a gas-carrier into the proportional gas counter of the flowing type, where the decay rate of the radioactive gas species is measured. This quantity is unequivocally related to the flux of particles (neutrons, protons, light and heavy ions) at the location of the ampoule. The method was used to monitor the neutron flux of the pulsed neutron target “RADEX” driven by the linear proton accelerator of INR RAS. Further progress of the FGRM may give rise to possible applications in nuclear physics, astrophysics and medicine, in the nondestructive control of fissionable materials, diagnostics of thermonuclear plasma, monitoring of fluxes and measurement of spectra of bombarding particles.

  8. 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.

  9. 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.

  10. System and method for 3-D/3-D registration between non-contrast-enhanced CBCT and contrast-enhanced CT for abdominal aortic aneurysm stenting.

    PubMed

    Miao, Shun; Liao, Rui; Pfister, Marcus; Zhang, Li; Ordy, Vincent

    2013-01-01

    In this paper, we present an image guidance system for abdominal aortic aneurysm stenting, which brings pre-operative 3-D computed tomography (CT) into the operating room by registering it against intra-operative non-contrast-enhanced cone-beam CT (CBCT). Registration between CT and CBCT volumes is a challenging task due to two factors: the relatively low signal-to-noise ratio of the abdominal aorta in CBCT without contrast enhancement, and the drastically different field of view between the two image modalities. The proposed automatic registration method handles the first issue through a fast quasi-global search utilizing surrogate 2-D images, and solves the second problem by relying on neighboring dominant structures of the abdominal aorta (i.e. the spine) for initial coarse alignment, and using a confined and image-processed volume of interest around the abdominal aorta for fine registration. The proposed method is validated offline using 17 clinical datasets, and achieves 1.48 mm target registration error and 100% success rate in 2.83 s. The prototype system has been installed in hospitals for clinical trial and applied in around 30 clinical cases, with 100% success rate reported qualitatively. PMID:24505689

  11. 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.

  12. Registration and measurement of opening and closing jaw movements and rotational mandibular capacity by using the method of electronic axiography.

    PubMed

    Kraljević, Sonja; Pandurić, Josip; Badel, Tomislav; Dulcić, Niksa

    2003-01-01

    The aim of this study was to register and measure lower jaw movements, to analyse the measured length of opening and closing movements and to analyse the rotational mandibular capacity during the maximal opening of the mouth in the position of centric relation. Our objective was to determine the average values for each mandible and temporomandibular joint movement, as well as to determine the accuracy of electronic axiography, while diagnosing temporomandibular joint disorders. A statistical analysis was performed in order to evaluate whether significant differences between the length of the measured movements in asymptomatic and symptomatic subjects could be found. A symptomatic group consisted of 51 subjects with temporomandibular disorders. A control group consisted of 43 subjects without signs and symptoms of temporomandibular joint disorders. Each subject was registered by the GAMMA CADIAX system for registration of position and movement of the lower jaw, which consists of a conventional SAM axiograph, an electronic device for drawing curves by means of a computer. No significant differences were found between the groups of subjects for the measured variables. The results of the length of the mandibular and condyle movements, along with the rotational capacity of the mandible are important, in spite of unreliable indicators of temporomandibular joint function. Description analysis of a graphic recording of mandibular and TMJ movement remains an accurate evaluation method for the determination of TMJ dysfunction.

  13. An ellipse-fitting based method for efficient registration of breast masses on two mammographic views

    SciTech Connect

    Pu Jiantao; Zheng Bin; Leader, Joseph Ken; Gur, David

    2008-02-15

    When reading mammograms, radiologists routinely search for and compare suspicious breast lesions identified on two corresponding craniocaudal (CC) and mediolateral oblique (MLO) views. Automatically identifying and matching the same true-positive breast lesions depicted on two views is an important step for developing successful multiview based computer-aided detection (CAD) schemes. The authors developed a method to automatically register breast areas and detect matching strips of interest used to identify the matched mass regions depicted on CC and MLO views. The method uses an ellipse based model to fit the breast boundary contour (skin line) and set a local Cartesian coordinate system for each view. One intersection point between the major/minor axis and the fitted ellipse perimeter passed through breast boundary is selected as the origin and the majoraxis and the minoraxis of the ellipse are used as the two axis of the Cartesian coordinate system. When a mass is identified on one view, the scheme computes its position in the local coordinate system. Then, the distance is mapped onto the local coordinate of the other view. At the end of the mapped distance a registered centerline of the matching strip is created. The authors established an image database that includes 200 test examinations each depicting one verified mass visible on the two views. They tested whether the registered centerline identified on another view can be used to locate the matched mass region. The experiments show that the average distance between the mass region centers and the registered centerlines was {+-}8.3 mm and in 91% of testing cases the registered centerline actually passes through the matched mass regions. A matching strip width of 47 mm was required to achieve 100% sensitivity for the test database. The results demonstrate the feasibility of the proposed method to automatically identify masses depicted on CC and MLO views, which may improve future development of multiview

  14. An ellipse-fitting based method for efficient registration of breast masses on two mammographic views

    PubMed Central

    Pu, Jiantao; Zheng, Bin; Leader, Joseph Ken; Gur, David

    2008-01-01

    When reading mammograms, radiologists routinely search for and compare suspicious breast lesions identified on two corresponding craniocaudal (CC) and mediolateral oblique (MLO) views. Automatically identifying and matching the same true-positive breast lesions depicted on two views is an important step for developing successful multiview based computer-aided detection (CAD) schemes. The authors developed a method to automatically register breast areas and detect matching strips of interest used to identify the matched mass regions depicted on CC and MLO views. The method uses an ellipse based model to fit the breast boundary contour (skin line) and set a local Cartesian coordinate system for each view. One intersection point between the major/minor axis and the fitted ellipse perimeter passed through breast boundary is selected as the origin and the majoraxis and the minoraxis of the ellipse are used as the two axis of the Cartesian coordinate system. When a mass is identified on one view, the scheme computes its position in the local coordinate system. Then, the distance is mapped onto the local coordinate of the other view. At the end of the mapped distance a registered centerline of the matching strip is created. The authors established an image database that includes 200 test examinations each depicting one verified mass visible on the two views. They tested whether the registered centerline identified on another view can be used to locate the matched mass region. The experiments show that the average distance between the mass region centers and the registered centerlines was ±8.3 mm and in 91% of testing cases the registered centerline actually passes through the matched mass regions. A matching strip width of 47 mm was required to achieve 100% sensitivity for the test database. The results demonstrate the feasibility of the proposed method to automatically identify masses depicted on CC and MLO views, which may improve future development of multiview based

  15. Registration pollution of water by method of modulation intracavity laser spectroscopy

    NASA Astrophysics Data System (ADS)

    Bojko, Sergey; Gamalii, Vladimir F.

    1995-09-01

    In this work, the method of the modulation intracavity laser spectroscopy is shown to be candidate for investigation and quantitative analysis of organic pollutions in water. The test specimen is placed into the cavity of the multimode dye laser. When the Raman scattering line coincides with amplification spectrum of the active medium of the multimode laser the additional gain appears at the Stokes frequency. One can experimentally determine this gain and then determine concentration of pollution. Spectral width of the Raman lines are small (approximately 3 cm-1), therefore a number of organic pollutions may be observed simultaneously. We have investigated stimulated Raman scattering from molecules of peridin (C5H5N) in water. In our conditions concentration sensitivity was 7 IO-4M/1.

  16. 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.

  17. 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.

  18. 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...).

  19. 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.

  20. 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

  1. 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.

  2. Comparative study of application accuracy of two frameless neuronavigation systems: experimental error assessment quantifying registration methods and clinically influencing factors.

    PubMed

    Paraskevopoulos, Dimitrios; Unterberg, Andreas; Metzner, Roland; Dreyhaupt, Jens; Eggers, Georg; Wirtz, Christian Rainer

    2010-04-01

    This study aimed at comparing the accuracy of two commercial neuronavigation systems. Error assessment and quantification of clinical factors and surface registration, often resulting in decreased accuracy, were intended. Active (Stryker Navigation) and passive (VectorVision Sky, BrainLAB) neuronavigation systems were tested with an anthropomorphic phantom with a deformable layer, simulating skin and soft tissue. True coordinates measured by computer numerical control were compared with coordinates on image data and during navigation, to calculate software and system accuracy respectively. Comparison of image and navigation coordinates was used to evaluate navigation accuracy. Both systems achieved an overall accuracy of <1.5 mm. Stryker achieved better software accuracy, whereas BrainLAB better system and navigation accuracy. Factors with conspicuous influence (P<0.01) were imaging, instrument replacement, sterile cover drape and geometry of instruments. Precision data indicated by the systems did not reflect measured accuracy in general. Surface matching resulted in no improvement of accuracy, confirming former studies. Laser registration showed no differences compared to conventional pointers. Differences between the two systems were limited. Surface registration may improve inaccurate point-based registrations but does not in general affect overall accuracy. Accuracy feedback by the systems does not always match with true target accuracy and requires critical evaluation from the surgeon.

  3. 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

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

    PubMed Central

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

    2014-01-01

    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

  5. 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

  6. Virtual bite registration using intraoral digital scanning, CT and CBCT: In vitro evaluation of a new method and its implication for orthognathic surgery.

    PubMed

    Nilsson, Johanna; Richards, Robert Geoff; Thor, Andreas; Kamer, Lukas

    2016-09-01

    Three-dimensional (3D) computer-assisted planning requires detailed visualisation of the craniomaxillofacial region and interocclusal relationship. The aim of this study was to establish and evaluate a method to create a 3D model of the craniomaxillofacial region and to adopt intraoral digital scanning to place the lower jaw into a centric relation (CR) without the need of additional plaster casts and model surgery. A standard plastic skull modified by metallic dental wires and brackets was subjected to computed tomography (CT), cone beam computed tomography (CBCT), and intraoral digital scanning. We evaluated two different virtual bite registrations, a digital scan of the buccal dental surfaces and scanning of the wax bites to position the lower jaw into a CR, and assessed the accuracy of the integration of intraoral scanning to the CT/CBCT scans. The mean registration error of corresponding mesh points for the CT and intraoral scanned images was 0.15 ± 0.12 mm, while this error was 0.18 ± 0.13 mm for the CBCT and intraoral scanned images. The mean accuracy of the two virtual bite registrations ranged from 0.41 to 0.49 mm (buccal scan technique) and from 0.65 to 1.3 mm (virtualised wax bite technique). A method for virtual bite registration was developed. It has the potential to eliminate plaster casts and model surgery and may facilitate 3D computer-assisted planning of orthognathic surgery cases.

  7. Virtual bite registration using intraoral digital scanning, CT and CBCT: In vitro evaluation of a new method and its implication for orthognathic surgery.

    PubMed

    Nilsson, Johanna; Richards, Robert Geoff; Thor, Andreas; Kamer, Lukas

    2016-09-01

    Three-dimensional (3D) computer-assisted planning requires detailed visualisation of the craniomaxillofacial region and interocclusal relationship. The aim of this study was to establish and evaluate a method to create a 3D model of the craniomaxillofacial region and to adopt intraoral digital scanning to place the lower jaw into a centric relation (CR) without the need of additional plaster casts and model surgery. A standard plastic skull modified by metallic dental wires and brackets was subjected to computed tomography (CT), cone beam computed tomography (CBCT), and intraoral digital scanning. We evaluated two different virtual bite registrations, a digital scan of the buccal dental surfaces and scanning of the wax bites to position the lower jaw into a CR, and assessed the accuracy of the integration of intraoral scanning to the CT/CBCT scans. The mean registration error of corresponding mesh points for the CT and intraoral scanned images was 0.15 ± 0.12 mm, while this error was 0.18 ± 0.13 mm for the CBCT and intraoral scanned images. The mean accuracy of the two virtual bite registrations ranged from 0.41 to 0.49 mm (buccal scan technique) and from 0.65 to 1.3 mm (virtualised wax bite technique). A method for virtual bite registration was developed. It has the potential to eliminate plaster casts and model surgery and may facilitate 3D computer-assisted planning of orthognathic surgery cases. PMID:27423538

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. Effect of registration on cyclical kinematic data.

    PubMed

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

    2010-08-26

    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 curve's 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 20s. 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.

  14. Diffusion tensor image registration using polynomial expansion

    NASA Astrophysics Data System (ADS)

    Wang, Yuanjun; Chen, Zengai; Nie, Shengdong; Westin, Carl-Fredrik

    2013-09-01

    In this paper, we present a deformable registration framework for the diffusion tensor image (DTI) using polynomial expansion. The use of polynomial expansion in image registration has previously been shown to be beneficial due to fast convergence and high accuracy. However, earlier work was developed only for 3D scalar medical image registration. In this work, it is shown how polynomial expansion can be applied to DTI registration. A new measurement is proposed for DTI registration evaluation, which seems to be robust and sensitive in evaluating the result of DTI registration. We present the algorithms for DTI registration using polynomial expansion by the fractional anisotropy image, and an explicit tensor reorientation strategy is inherent to the registration process. Analytic transforms with high accuracy are derived from polynomial expansion and used for transforming the tensor's orientation. Three measurements for DTI registration evaluation are presented and compared in experimental results. The experiments for algorithm validation are designed from simple affine deformation to nonlinear deformation cases, and the algorithms using polynomial expansion give a good performance in both cases. Inter-subject DTI registration results are presented showing the utility of the proposed method.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. Error correction in image registration using POCS

    NASA Astrophysics Data System (ADS)

    Duraisamy, Prakash; Alam, Mohammad S.; Jackson, Stephen C.

    2011-04-01

    Image registration plays a vital role in many real time imaging applications. Registering the images in a precise manner is a challenging problem. In this paper, we focus on improving image registration error computation using the projection onto convex sets (POCS) techniques which improves the sub-pixel accuracy in the images leading to better estimates for the registration error. This can be used in turn to improve the registration itself. The results obtained from the proposed technique match well with the ground truth which validates the accuracy of this technique. Furthermore, the proposed technique shows better performance compared to existing methods.

  3. The role of professional education in developing compassionate practitioners: a mixed methods study exploring the perceptions xof health professionals and pre-registration students.

    PubMed

    Bray, Lucy; O'Brien, Mary R; Kirton, Jennifer; Zubairu, Kate; Christiansen, Angela

    2014-03-01

    Compassionate practice is a public expectation and a core health professional value. However, in the face of growing public and professional unease about a perceived absence of compassion in health care it is essential that the role of education in developing compassionate practitioners is fully understood. The aim of this study was to explore qualified health professionals' and pre-registration students' understanding of compassion and the role of health professional education in promoting compassionate care. A sequential explanatory mixed methods study collected data using surveys and qualitative semi-structured interviews from qualified health professionals (n=155) and pre-registration students (n=197). Participants were from a range of health and social care disciplines and registered at a UK university. The findings indicate a high level of consensus in relation to participants' understanding of compassion in health care. Acting with warmth and empathy, providing individualised patient care and acting in a way you would like others to act towards you, were seen as the most common features of compassionate care. However, ambiguities and contradictions were evident when considering the role of health professional education in promoting compassionate practice. This study adds to the debate and current understanding of the role of education in fostering compassionate health care practice.

  4. Undergraduate Cross Registration.

    ERIC Educational Resources Information Center

    Grupe, Fritz H.

    This report discusses various aspects of undergraduate cross-registration procedures, including the dimensions, values, roles and functions, basic assumptions, and facilitating and encouragment of cross-registration. Dimensions of cross-registration encompass financial exchange, eligibility, program limitations, type of grade and credit; extent of…

  5. Radar image registration and rectification

    NASA Technical Reports Server (NTRS)

    Naraghi, M.; Stromberg, W. D.

    1983-01-01

    Two techniques for radar image registration and rectification are presented. In the registration method, a general 2-D polynomial transform is defined to accomplish the geometric mapping from one image into the other. The degree and coefficients of the polynomial are obtained using an a priori found tiepoint data set. In the second part of the paper, a rectification procedure is developed that models the distortion present in the radar image in terms of the radar sensor's platform parameters and the topographic variations of the imaged scene. This model, the ephemeris data and the digital topographic data are then used in rectifying the radar image. The two techniques are then used in registering and rectifying two examples of radar imagery. Each method is discussed as to its benefits, shortcomings and registration accuracy.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Automated Registration of MDIM with MOLA Tracks

    NASA Astrophysics Data System (ADS)

    Kim, J. R.; Muller, J.-P.; Morley, J. G.; Mitchell, K. L.

    2001-03-01

    We have developed a method for the automatic registration of MOLA tracks and optical images by means of a crater detection algorithm and a specialised matching function for the photogrammetric DEM creation with MOLA reference using stereo photogrammetric methods.

  12. 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.

  13. 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).

  14. Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations.

    PubMed

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

    2008-04-01

    In this article a comprehensive set of registration methods is utilized to provide image-to-physical space registration for image-guided neurosurgery in a clinical study. Central to all methods is the use of textured point clouds as provided by laser range scanning technology. The objective is to perform a systematic comparison of registration methods that include both extracranial (skin marker point-based registration (PBR), and face-based surface registration) and intracranial methods (feature PBR, cortical vessel-contour registration, a combined geometry/intensity surface registration method, and a constrained form of that method to improve robustness). The platform facilitates the selection of discrete soft-tissue landmarks that appear on the patient's intraoperative cortical surface and the preoperative gadolinium-enhanced magnetic resonance (MR) image volume, i.e., true corresponding novel targets. In an 11 patient study, data were taken to allow statistical comparison among registration methods within the context of registration error. The results indicate that intraoperative face-based surface registration is statistically equivalent to traditional skin marker registration. The four intracranial registration methods were investigated and the results demonstrated a target registration error of 1.6 +/- 0.5 mm, 1.7 +/- 0.5 mm, 3.9 +/- 3.4 mm, and 2.0 +/- 0.9 mm, for feature PBR, cortical vessel-contour registration, unconstrained geometric/intensity registration, and constrained geometric/intensity registration, respectively. When analyzing the results on a per case basis, the constrained geometric/intensity registration performed best, followed by feature PBR, and finally cortical vessel-contour registration. Interestingly, the best target registration errors are similar to targeting errors reported using bone-implanted markers within the context of rigid targets. The experience in this study as with others is that brain shift can compromise extracranial

  15. Tangent height registration method for the Version 1.4 data retrieval algorithm of the solar occultation sensor ILAS-II.

    PubMed

    Tanaka, Tomoaki; Nakajima, Hideaki; Sugita, Takafumi; Ejiri, Mitsumu K; Irie, Hitoshi; Saitoh, Naoko; Terao, Yukio; Kawasaki, Hiroyuki; Usami, Masatoshi; Yokota, Tatsuya; Kobayashi, Hirokazu; Sasano, Yasuhiro

    2007-10-10

    The Improved Limb Atmospheric Spectrometer-II (ILAS-II) is a satellite-borne solar occultation sensor onboard the Advanced Earth Observing Satellite-II (ADEOS-II). The ILAS-II succeeded the ILAS. The ILAS-II used four grating spectrometers to observe vertical profiles of gas volume mixing ratios of trace constituents and was also equipped with a Sun-edge sensor to determine tangent heights geometrically with high precision. The accuracy of gas volume mixing ratios depends on the accuracy of the tangent height determination. The combination method is a tangent height registration method that was developed to give appropriate tangent heights for the ILAS-II Version 1.4 data retrieval algorithm. This study describes the method used in the ILAS-II Version 1.4 retrieval algorithm to register tangent heights. The root-sum-square total random error is estimated to be 30 m, and the total systematic error is 180 m at an altitude of 30 km. The influence of the tangent height errors on the vertical profiles of gas volume mixing ratios in ILAS-II Version 1.4 is estimated by using the relative difference. The relative difference for each species is within 7% (20%) for an altitude shift of +/-100 m(+/-300 m).

  16. Tensor scale-based image registration

    NASA Astrophysics Data System (ADS)

    Saha, Punam K.; Zhang, Hui; Udupa, Jayaram K.; Gee, James C.

    2003-05-01

    Tangible solutions to image registration are paramount in longitudinal as well as multi-modal medical imaging studies. In this paper, we introduce tensor scale - a recently developed local morphometric parameter - in rigid image registration. A tensor scale-based registration method incorporates local structure size, orientation and anisotropy into the matching criterion, and therefore, allows efficient multi-modal image registration and holds potential to overcome the effects of intensity inhomogeneity in MRI. Two classes of two-dimensional image registration methods are proposed - (1) that computes angular shift between two images by correlating their tensor scale orientation histogram, and (2) that registers two images by maximizing the similarity of tensor scale features. Results of applications of the proposed methods on proton density and T2-weighted MR brain images of (1) the same slice of the same subject, and (2) different slices of the same subject are presented. The basic superiority of tensor scale-based registration over intensity-based registration is that it may allow the use of local Gestalts formed by the intensity patterns over the image instead of simply considering intensities as isolated events at the pixel level. This would be helpful in dealing with the effects of intensity inhomogeneity and noise in MRI.

  17. 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.

  18. 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.

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

    PubMed

    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.

  20. Impact of Policy Initiatives on Civil Registration System in Haryana

    PubMed Central

    Singh, Pravin Kumar; Kaur, Manmeet; Jaswal, Nidhi; Kumar, Rajesh

    2012-01-01

    Background: Despite the existence of Registration of Birth and Death Act (1969), Civil Registration System (CRS) in India registered only 68.3% of the births and 63.2% of the deaths. Hence, National Population Policy (2000) emphasized the need to improve registration of vital events. In 2005, Haryana initiated policy changes to enhance registration of vital events. We evaluated the impact of these policy changes on CRS in 2009. Materials and Methods: Records and reports of CRS were reviewed. On the basis of the birth and deaths reported by the Sample Registration System, the proportion of births and deaths registered by CRS were estimated using the projected population from 2001 Census. Results: Before 2005, Police Stations were the registration centers in rural Haryana. On 1st January 2005, the birth and death registration was made the responsibility of Primary Health Centers (PHCs). Medical Officers at PHCs were designated as Registrar and Pharmacists as Sub-Registrar of Births and Deaths. Auxiliary Nurse Midwife and Anganwadi Workers facilitated the registration. Till 2004, the registration of births was stagnant at the level of 70% for several years, which increased to 95% by 2009. Similarly registration of death events increased from 73.5% to 92.1%. Conclusion: Haryana state is still to achieve complete registration of births and deaths, but certainly shift of registration from police to health department has strengthened the CRS. PMID:22654286

  1. Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds.

    PubMed

    Bae, Kwang-Ho

    2009-01-01

    Using three dimensional point clouds from both simulated and real datasets from close and terrestrial laser scanners, the rotational and translational convergence regions of Geometric Primitive Iterative Closest Points (GP-ICP) are empirically evaluated. The results demonstrate the GP-ICP has a larger rotational convergence region than the existing methods, e.g., the Iterative Closest Point (ICP).

  2. 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

  3. 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

  4. 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.

  5. Automatic initialization for 3D bone registration

    NASA Astrophysics Data System (ADS)

    Foroughi, Pezhman; Taylor, Russell H.; Fichtinger, Gabor

    2008-03-01

    In image-guided bone surgery, sample points collected from the surface of the bone are registered to the preoperative CT model using well-known registration methods such as Iterative Closest Point (ICP). These techniques are generally very sensitive to the initial alignment of the datasets. Poor initialization significantly increases the chances of getting trapped local minima. In order to reduce the risk of local minima, the registration is manually initialized by locating the sample points close to the corresponding points on the CT model. In this paper, we present an automatic initialization method that aligns the sample points collected from the surface of pelvis with CT model of the pelvis. The main idea is to exploit a mean shape of pelvis created from a large number of CT scans as the prior knowledge to guide the initial alignment. The mean shape is constant for all registrations and facilitates the inclusion of application-specific information into the registration process. The CT model is first aligned with the mean shape using the bilateral symmetry of the pelvis and the similarity of multiple projections. The surface points collected using ultrasound are then aligned with the pelvis mean shape. This will, in turn, lead to initial alignment of the sample points with the CT model. The experiments using a dry pelvis and two cadavers show that the method can align the randomly dislocated datasets close enough for successful registration. The standard ICP has been used for final registration of datasets.

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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

  12. [Analysis and discussion on current condition of acupuncture clinical research registration].

    PubMed

    Xu, Ying; Chen, Bo; Guo, Yi

    2015-06-01

    To introduce the international registration condition of acupuncture clinical research. With the examples of World Health Organization International Clinical Trials Registry Platform and the U. S. National Institutes of Health Clinical Registration Platform, the registration method and current condition of acupuncture clinical trials in international clinical trials registration platform were analyzed. The results indicate that the number of acupuncture clinical trials registration is gradually increased and the registration number from China is on the rise as well. But most domestic acupuncture clinical researches haven't been registered arid the researchers' valuing degree for clinical trials registration and methodology research needs to be improved. PMID:26480568

  13. 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.

  14. 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.

  15. 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

  16. 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,...

  17. Deformable registration using scale space keypoints

    NASA Astrophysics Data System (ADS)

    Moradi, Mehdi; Abolmaesoumi, Purang; Mousavi, Parvin

    2006-03-01

    In this paper, we describe a new methodology for keypoint-based affine and deformable medical image registration. This fast and computationally efficient method is automatic and does not rely on segmentation of images. The keypoint pixels used in this technique are extreme points in the scale space and are characterized by descriptor vectors which summarize the intensity gradient profile of the surrounding pixels. For each of the keypoints in the scene image, a corresponding keypoint is identified in the model image using the feature space nearest neighbor criteria. For deformable registration, B-splines are used to extrapolate a regular deformation grid for all of the pixels in the scene image based on the relative displacement vectors of the corresponding pairs. This approach results in a fast and accurate registration in the brain MRI images (an average target registration error of less than 2mm was acquired). We have also studied the affine registration problem in the liver ultrasound and brain MRI images and have acquired acceptable registrations using a mean square solution for affine parameters based on only around 30 corresponding keypoint pairs.

  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. 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.

  20. 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.

  1. Curvelet-based registration of multi-component seismic waves

    NASA Astrophysics Data System (ADS)

    Wang, Hairong; Cheng, Yuanfeng; Ma, Jianwei

    2014-05-01

    Registration of the travel time of PP waves and PS waves on the same coordinate is critical for joint interpretation in multi-component seismic exploration. In this paper, we propose a new curvelet-based registration method to improve the precision of registration, especially for the data with heavy random noises. By making registration in curvelet multiscale spaces from coarser to finer scale, the proposed method is not sensitive to initial values of velocity ratio of PP waves and PS waves. Applications of the new method to real seismic dataset from Shengli Oilfield, China show good registered results in terms of both qualitative and quantitative analysis, in comparison with a traditional registration method and a wavelet-based method.

  2. 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…

  3. 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…

  4. DTI Image Registration under Probabilistic Fiber Bundles Tractography Learning

    PubMed Central

    Lei, Tao; Fan, Yangyu; Zhang, Xiuwei

    2016-01-01

    Diffusion Tensor Imaging (DTI) image registration is an essential step for diffusion tensor image analysis. Most of the fiber bundle based registration algorithms use deterministic fiber tracking technique to get the white matter fiber bundles, which will be affected by the noise and volume. In order to overcome the above problem, we proposed a Diffusion Tensor Imaging image registration method under probabilistic fiber bundles tractography learning. Probabilistic tractography technique can more reasonably trace to the structure of the nerve fibers. The residual error estimation step in active sample selection learning is improved by modifying the residual error model using finite sample set. The calculated deformation field is then registered on the DTI images. The results of our proposed registration method are compared with 6 state-of-the-art DTI image registration methods under visualization and 3 quantitative evaluation standards. The experimental results show that our proposed method has a good comprehensive performance. PMID:27774455

  5. 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.

  6. Data organization and storage model of the realty uniform registration system

    NASA Astrophysics Data System (ADS)

    Shen, Chenhua; Liu, Yu; Wu, Xiaobin

    2007-06-01

    Based on the Real Right Law, this article analyzes the entity objects of the realty uniform registration, and establishes the model of the logical relations among the entities, from which the dada relation model is proposed, and from which the data relation model of the realty uniform registration is proposed, and is compared with the current land registration data model and the real estate data model. It is proved that this uniform registration data model has not only maintained the close links with the land registration data model and the real estate registration data model, but also met the need of the uniform registration by comparing with the existing land registration data model and the real estate data model. In the end, this article discusses the method of data storage for the uniform registration of the land and the real estate to improve the efficiency of storage and access by adopting split technology to store the alteration data logically.

  7. 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

  8. Supporting registration decisions during 3D medical volume reconstructions

    NASA Astrophysics Data System (ADS)

    Bajcsy, Peter; Lee, Sang-Chul; Clutter, David

    2006-03-01

    We propose a methodology for making optimal registration decisions during 3D volume reconstruction in terms of (a) anticipated accuracy of aligned images, (b) uncertainty of obtained results during the registration process, (c) algorithmic repeatability of alignment procedure, and (d) computational requirements. We researched and developed a web-enabled, web services based, data-driven, registration decision support system. The registration decisions include (1) image spatial size (image sub-area or entire image), (2) transformation model (e.g., rigid, affine or elastic), (3) invariant registration feature (intensity, morphology or a sequential combination of the two), (4) automation level (manual, semi-automated, or fully-automated), (5) evaluations of registration results (multiple metrics and methods for establishing ground truth), and (6) assessment of resources (computational resources and human expertise, geographically local or distributed). Our goal is to provide mechanisms for evaluating the tradeoffs of each registration decision in terms of the aforementioned impacts. First, we present a medical registration methodology for making registration decisions that lead to registration results with well-understood accuracy, uncertainty, consistency and computational complexity characteristics. Second, we have built software tools that enable geographically distributed researchers to optimize their data-driven registration decisions by using web services and supercomputing resources. The support developed for registration decisions about 3D volume reconstruction is available to the general community with the access to the NCSA supercomputing resources. We illustrate performance by considering 3D volume reconstruction of blood vessels in histological sections of uveal melanoma from serial fluorescent labeled paraffin sections labeled with antibodies to CD34 and laminin. The specimens are studied by fluorescence confocal laser scanning microscopy (CLSM) images.

  9. 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.

  10. Large deformation diffeomorphic registration of diffusion-weighted imaging data

    PubMed Central

    Zhang, Pei; Niethammer, Marc; Shen, Dinggang; Yap, Pew-Thian

    2014-01-01

    Registration plays an important role in group analysis of diffusion-weighted imaging (DWI) data. It can be used to build a reference anatomy for investigating structural variation or tracking changes in white matter. Unlike traditional scalar image registration where spatial alignment is the only focus, registration of DWI data requires both spatial alignment of structures and reorientation of local signal profiles. As such, DWI registration is much more complex and challenging than scalar image registration. Although a variety of algorithms has been proposed to tackle the problem, most of them are restricted by the zdiffusion model used for registration, making it difficult to fit to the registered data a different model. In this paper we describe a method that allows any diffusion model to be fitted after registration for subsequent multifaceted analysis. This is achieved by directly aligning DWI data using a large deformation diffeomorphic registration framework. Our algorithm seeks the optimal coordinate mapping by simultaneously considering structural alignment, local signal profile reorientation, and deformation regularization. Our algorithm also incorporates a multi-kernel strategy to concurrently register anatomical structures at different scales. We demonstrate the efficacy of our approach using in vivo data and report detailed qualitative and quantitative results in comparison with several different registration strategies. PMID:25106710

  11. Registration of large data sets for multimodal inspection

    NASA Astrophysics Data System (ADS)

    Vedula, Venumadhav V. S.; Sheri, George

    2006-08-01

    Registration plays a key role in multimodal data fusion to extract synergistic information from multiple non-destructive evaluation (NDE) sources. One of the common techniques for registration of point datasets is the Iterative Closest Point (ICP) Algorithm. Generally, modern day NDE techniques generate large datasets and conventional ICP algorithm requires huge amount of time to register datasets to the desired accuracy. In this paper, we present algorithms to aid in the registration of large 3D NDE data sets in less time with the required accuracy. Various methods of coarse registration of data, partial registration and data reduction are used to realize this. These techniques have been used in registration and it is shown that registration can be accomplished to the desired accuracy with more than 90% reduction in time as compared to conventional ICP algorithm. Volumes of interest (VOI) can be defined on the data sets and merged together so that only the features of interest are used in the registration. The proposed algorithm also provides capability for eliminating noise in the data sets. Registration of Computed Tomography (CT) Image data, Coordinate Measuring Machine (CMM) Inspection data and CAD model has been discussed in the present work. The algorithm is generic in nature and can be applied to any other NDE inspection data.

  12. 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.

  13. 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.

  14. Registration of dynamic contrast-enhanced MRI using a progressive principal component registration (PPCR)

    NASA Astrophysics Data System (ADS)

    Melbourne, A.; Atkinson, D.; White, M. J.; Collins, D.; Leach, M.; Hawkes, D.

    2007-09-01

    Registration of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) of soft tissue is difficult. Conventional registration cost functions that depend on information content are compromised by the changing intensity profile, leading to misregistration. We present a new data-driven model of uptake patterns formed from a principal components analysis (PCA) of time-series data, avoiding the need for a physiological model. We term this process progressive principal component registration (PPCR). Registration is performed repeatedly to an artificial time series of target images generated using the principal components of the current best-registered time-series data. The aim is to produce a dataset that has had random motion artefacts removed but long-term contrast enhancement implicitly preserved. The procedure is tested on 22 DCE-MRI datasets of the liver. Preliminary assessment of the images is by expert observer comparison with registration to the first image in the sequence. The PPCR is preferred in all cases where a preference exists. The method requires neither segmentation nor a pharmacokinetic uptake model and can allow successful registration in the presence of contrast enhancement.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. REGISTRATION OF ORTHODONTIC DIGITAL MODELS

    PubMed Central

    Grauer, Dan; Cevidanes, Lucia H.; Tyndall, Donald; Styner, Martin A.; Flood, Patrick M.; Proffit, William R.

    2011-01-01

    Current methods to assess outcomes and change in orthodontics are comparison of photographs, cephalometric measurements and superimpositions, and comparisons/measurements on dental casts. Digital models are a relatively new records modality in orthodontics. They offer numerous advantages in terms of storage space, spatial registration and superimposition. The purpose of this chapter is to determine the reproducibility of: 1) establishing occlusion of independently scanned digital models; and 2) registering digital models obtained after treatment on their homologous digital model setups produced before treatment. Reliability of both procedures was assessed with two random samples of five patient’s models. In both experiments, three replicate positionings of the models per patient were created and variability in position was evaluated by the maximum surface difference between replicates, and the standard deviation of the surface distances between replicates respectively. Based on the data obtained, we concluded that it is reliable to register independently scanned models to a scanned surface of the models in occlusion. Surface-to-surface registration of final orthodontic digital models to planned setup models also is reproducible. PMID:26549917

  20. 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.

  1. 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

  2. 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.

  3. 76 FR 79173 - Registration Review; Pesticide Dockets Opened for Review and Comment, and Notice of Availability...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-21

    ...: Notice. SUMMARY: EPA has established registration review dockets for the pesticides listed in the table... reviews. Registration review is EPA's periodic review of pesticide registrations to ensure that each... interest provided in the table in Unit III.A., by one of the following methods: Federal eRulemaking...

  4. 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.

  5. A statistical framework for inter-group image registration.

    PubMed

    Liao, Shu; Wu, Guorong; Shen, Dinggang

    2012-10-01

    Groupwise image registration plays an important role in medical image analysis. The principle of groupwise image registration is to align a given set of images to a hidden template space in an iteratively manner without explicitly selecting any individual image as the template. Although many approaches have been proposed to address the groupwise image registration problem for registering a single group of images, few attentions and efforts have been paid to the registration problem between two or more different groups of images. In this paper, we propose a statistical framework to address the registration problems between two different image groups. The main contributions of this paper lie in the following aspects: (1) In this paper, we demonstrate that directly registering the group mean images estimated from two different image groups is not sufficient to establish the reliable transformation from one image group to the other image group. (2) A novel statistical framework is proposed to extract anatomical features from the white matter, gray matter and cerebrospinal fluid tissue maps of all aligned images as morphological signatures for each voxel. The extracted features provide much richer anatomical information than the voxel intensity of the group mean image, and can be integrated with the multi-channel Demons registration algorithm to perform the registration process. (3) The proposed method has been extensively evaluated on two publicly available brain MRI databases: the LONI LPBA40 and the IXI databases, and it is also compared with a conventional inter-group image registration approach which directly performs deformable registration between the group mean images of two image groups. Experimental results show that the proposed method consistently achieves higher registration accuracy than the method under comparison.

  6. Informing pre-registration nurse education: a proposal outline on the value, methods and ethical considerations of involving children in doctoral research.

    PubMed

    Clarke, Sonya

    2014-12-01

    As pre-registration nurse education programmes evolve within the United Kingdom, it is imperative to involve patient/client groups within the research process, as the outcome may invoke a change in the care delivery of the registered nurse (RN). This paper focuses upon children and how children might hypothetically contribute to informing a generic nursing programme in their capacity as a rights holder and expert in their own lives. Even though their contribution and value has been debated around their capacity as research advisor, research participant and co researcher, this paper explores how the child's view of their experience of hospital and of the good nurse could be best captured. Research is a powerful vehicle that can enable their voice to equally inform UK nurse educators and policy makers so that the child's health care needs are effectively met in hospital by RN's who complete a generic programme.

  7. 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.

  8. The adaptive FEM elastic model for medical image registration.

    PubMed

    Zhang, Jingya; Wang, Jiajun; Wang, Xiuying; Feng, Dagan

    2014-01-01

    This paper proposes an adaptive mesh refinement strategy for the finite element method (FEM) based elastic registration model. The signature matrix for mesh refinement takes into account the regional intensity variance and the local deformation displacement. The regional intensity variance reflects detailed information for improving registration accuracy and the deformation displacement fine-tunes the mesh refinement for a more efficient algorithm. The gradient flows of two different similarity metrics, the sum of the squared difference and the spatially encoded mutual information for the mono-modal and multi-modal registrations, are used to derive external forces to drive the model to the equilibrium state. We compared our approach to three other models: (1) the conventional multi-resolution FEM registration algorithm; (2) the FEM elastic method that uses variation information for mesh refinement; and (3) the robust block matching based registration. Comparisons among different methods in a dataset with 20 CT image pairs upon artificial deformation demonstrate that our registration method achieved significant improvement in accuracies. Experimental results in another dataset of 40 real medical image pairs for both mono-modal and multi-modal registrations also show that our model outperforms the other three models in its accuracy.

  9. 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

  10. 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).

  11. Robust Point Set Registration Using Gaussian Mixture Models.

    PubMed

    Jian, Bing; Vemuri, Baba C

    2011-08-01

    In this paper, we present a unified framework for the rigid and nonrigid point set registration problem in the presence of significant amounts of noise and outliers. The key idea of this registration framework is to represent the input point sets using Gaussian mixture models. Then, the problem of point set registration is reformulated as the problem of aligning two Gaussian mixtures such that a statistical discrepancy measure between the two corresponding mixtures is minimized. We show that the popular iterative closest point (ICP) method [1] and several existing point set registration methods [2], [3], [4], [5], [6], [7] in the field are closely related and can be reinterpreted meaningfully in our general framework. Our instantiation of this general framework is based on the the L2 distance between two Gaussian mixtures, which has the closed-form expression and in turn leads to a computationally efficient registration algorithm. The resulting registration algorithm exhibits inherent statistical robustness, has an intuitive interpretation, and is simple to implement. We also provide theoretical and experimental comparisons with other robust methods for point set registration. PMID:21173443

  12. 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.

  13. Rapid registration of multimodal images using a reduced number of voxels

    NASA Astrophysics Data System (ADS)

    Huang, Xishi; Hill, Nicholas A.; Ren, Jing; Peters, Terry M.

    2006-03-01

    Rapid registration of multimodal cardiac images can improve image-guided cardiac surgeries and cardiac disease diagnosis. While mutual information (MI) is arguably the most suitable registration technique, this method is too slow to converge for real time cardiac image registration; moreover, correct registration may not coincide with a global or even local maximum of MI. These limitations become quite evident when registering three-dimensional (3D) ultrasound (US) images and dynamic 3D magnetic resonance (MR) images of the beating heart. To overcome these issues, we present a registration method that uses a reduced number of voxels, while retaining adequate registration accuracy. Prior to registration we preprocess the images such that only the most representative anatomical features are depicted. By selecting samples from preprocessed images, our method dramatically speeds up the registration process, as well as ensuring correct registration. We validated this registration method for registering dynamic US and MR images of the beating heart of a volunteer. Experimental results on in vivo cardiac images demonstrate significant improvements in registration speed without compromising registration accuracy. A second validation study was performed registering US and computed tomography (CT) images of a rib cage phantom. Two similarity metrics, MI and normalized crosscorrelation (NCC) were used to register the image sets. Experimental results on the rib cage phantom indicate that our method can achieve adequate registration accuracy within 10% of the computation time of conventional registration methods. We believe this method has the potential to facilitate intra-operative image fusion for minimally invasive cardio-thoracic surgical navigation.

  14. 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.

  15. A new combined surface and volume registration

    NASA Astrophysics Data System (ADS)

    Lepore, Natasha; Joshi, Anand A.; Leahy, Richard M.; Brun, Caroline; Chou, Yi-Yu; Pennec, Xavier; Lee, Agatha D.; Barysheva, Marina; De Zubicaray, Greig I.; Wright, Margaret J.; McMahon, Katie L.; Toga, Arthur W.; Thompson, Paul M.

    2010-03-01

    3D registration of brain MRI data is vital for many medical imaging applications. However, purely intensitybased approaches for inter-subject matching of brain structure are generally inaccurate in cortical regions, due to the highly complex network of sulci and gyri, which vary widely across subjects. Here we combine a surfacebased cortical registration with a 3D fluid one for the first time, enabling precise matching of cortical folds, but allowing large deformations in the enclosed brain volume, which guarantee diffeomorphisms. This greatly improves the matching of anatomy in cortical areas. The cortices are segmented and registered with the software Freesurfer. The deformation field is initially extended to the full 3D brain volume using a 3D harmonic mapping that preserves the matching between cortical surfaces. Finally, these deformation fields are used to initialize a 3D Riemannian fluid registration algorithm, that improves the alignment of subcortical brain regions. We validate this method on an MRI dataset from 92 healthy adult twins. Results are compared to those based on volumetric registration without surface constraints; the resulting mean templates resolve consistent anatomical features both subcortically and at the cortex, suggesting that the approach is well-suited for cross-subject integration of functional and anatomic data.

  16. 22 CFR 122.3 - Registration fees.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... reviewed, adjudicated or issued a response. The additional fee will be determined by multiplying $250 times...) Lapse in registration. A registrant who fails to renew a registration and, after an intervening...

  17. 22 CFR 122.3 - Registration fees.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... reviewed, adjudicated or issued a response. The additional fee will be determined by multiplying $250 times...) Lapse in registration. A registrant who fails to renew a registration and, after an intervening...

  18. 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)

  19. 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

  20. 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.

  1. Automated image registration for FDOPA PET studies

    NASA Astrophysics Data System (ADS)

    Lin, Kang-Ping; Huang, Sung-Cheng; Yu, Dan-Chu; Melega, William; Barrio, Jorge R.; Phelps, Michael E.

    1996-12-01

    In this study, various image registration methods are investigated for their suitability for registration of L-6-[18F]-fluoro-DOPA (FDOPA) PET images. Five different optimization criteria including sum of absolute difference (SAD), mean square difference (MSD), cross-correlation coefficient (CC), standard deviation of pixel ratio (SDPR), and stochastic sign change (SSC) were implemented and Powell's algorithm was used to optimize the criteria. The optimization criteria were calculated either unidirectionally (i.e. only evaluating the criteria for comparing the resliced image 1 with the original image 2) or bidirectionally (i.e. averaging the criteria for comparing the resliced image 1 with the original image 2 and those for the sliced image 2 with the original image 1). Monkey FDOPA images taken at various known orientations were used to evaluate the accuracy of different methods. A set of human FDOPA dynamic images was used to investigate the ability of the methods for correcting subject movement. It was found that a large improvement in performance resulted when bidirectional rather than unidirectional criteria were used. Overall, the SAD, MSD and SDPR methods were found to be comparable in performance and were suitable for registering FDOPA images. The MSD method gave more adequate results for frame-to-frame image registration for correcting subject movement during a dynamic FDOPA study. The utility of the registration method is further demonstrated by registering FDOPA images in monkeys before and after amphetamine injection to reveal more clearly the changes in spatial distribution of FDOPA due to the drug intervention.

  2. 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.

  3. 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

  4. INTER-GROUP IMAGE REGISTRATION BY HIERARCHICAL GRAPH SHRINKAGE.

    PubMed

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

    2013-12-31

    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.

  5. 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

  6. 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

  7. 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.'

  8. 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.

  9. 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.

  10. 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

  11. Dimensional 3D-2D cross-over under magnetic field in Bi2Sr2-xLaxCuOy induced by La/Sr substitution

    NASA Astrophysics Data System (ADS)

    Murrills, C. D.; Li, Z. Z.; Raffy, H.

    2015-06-01

    The single CuO2 layer Bi2Sr2CuO6 (Bi-2201) is characterized by a low anisotropy under magnetic field. We show that this anisotropy increases exponentially from 4 to 400 with La/Sr substitution in Bi2Sr2-xLaxCu06 (Bi(La)-2201). We present a phase diagram showing the change in transport properties from 3D to 2D when the La concentration is increased, deduced from angular transport measurements in the mixed state of c-axis oriented epitaxial Bi(La)-2201 thin films with columnar pinning centers parallel to the c-axis. We attribute this anisotropy increase to the decrease of the distortion of CuO2 planes by La/Sr substitution.

  12. 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.

  13. An Iterative Image Registration Algorithm by Optimizing Similarity Measurement.

    PubMed

    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.

  14. Multi-atlas segmentation with particle-based group-wise image registration.

    PubMed

    Lee, Joohwi; Lyu, Ilwoo; Styner, Martin

    2014-03-21

    We propose a novel multi-atlas segmentation method that employs a group-wise image registration method for the brain segmentation on rodent magnetic resonance (MR) images. The core element of the proposed segmentation is the use of a particle-guided image registration method that extends the concept of particle correspondence into the volumetric image domain. The registration method performs a group-wise image registration that simultaneously registers a set of images toward the space defined by the average of particles. The particle-guided image registration method is robust with low signal-to-noise ratio images as well as differing sizes and shapes observed in the developing rodent brain. Also, the use of an implicit common reference frame can prevent potential bias induced by the use of a single template in the segmentation process. We show that the use of a particle guided-image registration method can be naturally extended to a novel multi-atlas segmentation method and improves the registration method to explicitly use the provided template labels as an additional constraint. In the experiment, we show that our segmentation algorithm provides more accuracy with multi-atlas label fusion and stability against pair-wise image registration. The comparison with previous group-wise registration method is provided as well.

  15. 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

  16. 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.

  17. 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.

  18. Validation of histology image registration

    NASA Astrophysics Data System (ADS)

    Shojaii, Rushin; Karavardanyan, Tigran; Yaffe, Martin; Martel, Anne L.

    2011-03-01

    The aim of this paper is to validate an image registration pipeline used for histology image alignment. In this work a set of histology images are registered to their correspondent optical blockface images to make a histology volume. Then multi-modality fiducial markers are used to validate the alignment of histology images. The fiducial markers are catheters perfused with a mixture of cuttlefish ink and flour. Based on our previous investigations this fiducial marker is visible in medical images, optical blockface images and it can also be localized in histology images. The properties of this fiducial marker make it suitable for validation of the registration techniques used for histology image alignment. This paper reports on the accuracy of a histology image registration approach by calculation of target registration error using these fiducial markers.

  19. 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

  20. 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.

  1. 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.

  2. 3D ultrasound to stereoscopic camera registration through an air-tissue boundary.

    PubMed

    Yip, Michael C; Adebar, Troy K; Rohling, Robert N; Salcudean, Septimiu E; Nguan, Christopher Y

    2010-01-01

    A novel registration method between 3D ultrasound and stereoscopic cameras is proposed based on tracking a registration tool featuring both ultrasound fiducials and optical markers. The registration tool is pressed against an air-tissue boundary where it can be seen both in ultrasound and in the camera view. By localizing the fiducials in the ultrasound volume, knowing the registration tool geometry, and tracking the tool with the cameras, a registration is found. This method eliminates the need for external tracking, requires minimal setup, and may be suitable for a range of minimally invasive surgeries. A study of the appearance of ultrasound fiducials on an air-tissue boundary is presented, and an initial assessment of the ability to localize the fiducials in ultrasound with sub-millimeter accuracy is provided. The overall accuracy of registration (1.69 +/- 0.60 mm) is a noticeable improvement over other reported methods and warrants patient studies.

  3. 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.

  4. Non-rigid image registration with SalphaS filters.

    PubMed

    Liao, Shu; Chung, Albert C S

    2008-01-01

    In this paper, based on the SalphaS distributions, we design SalphaS filters and use the filters as a new feature extraction method for non-rigid medical image registration. In brain MR images, the energy distributions of different frequency bands often exhibit heavy-tailed behavior. Such non-Gaussian behavior is essential for non-rigid image registration but cannot be satisfactorily modeled by the conventional Gabor filters. This leads to unsatisfactory modeling of voxels located at the salient regions of the images. To this end, we propose the SalphaS filters for modeling the heavy-tailed behavior of the energy distributions of brain MR images, and show that the Gabor filter is a special case of the SalphaS filter. The maximum response orientation selection criterion is defined for each frequency band to achieve rotation invariance. In our framework, if the brain MR images are already segmented, each voxel can be automatically assigned a weighting factor based on the Fisher's separation criterion and it is shown that the registration performance can be further improved. The proposed method has been compared with the free-form-deformation based method, Demons algorithm and a method using Gabor features by conducting non-rigid image registration experiments. It is observed that the proposed method achieves the best registration accuracy among all the compared methods in both the simulated and real datasets obtained from the BrainWeb and IBSR respectively.

  5. 21 CFR 1301.35 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 223) to an applicant if... Federal Register. (c) The Certificate of Registration (DEA Form 223) shall contain the name, address,...

  6. 21 CFR 1309.42 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ...; denial of registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 511) to..., shall hold a hearing on the application pursuant to § 1309.51. (b) The Certificate of Registration...

  7. 21 CFR 1309.42 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ...; denial of registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 511) to..., shall hold a hearing on the application pursuant to § 1309.51. (b) The Certificate of Registration...

  8. 21 CFR 1301.35 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 223) to an applicant if... Federal Register. (c) The Certificate of Registration (DEA Form 223) shall contain the name, address,...

  9. 21 CFR 1301.35 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 223) to an applicant if... Federal Register. (c) The Certificate of Registration (DEA Form 223) shall contain the name, address,...

  10. 21 CFR 1309.42 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ...; denial of registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 511) to..., shall hold a hearing on the application pursuant to § 1309.51. (b) The Certificate of Registration...

  11. 21 CFR 1301.35 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 223) to an applicant if... Federal Register. (c) The Certificate of Registration (DEA Form 223) shall contain the name, address,...

  12. 21 CFR 1301.35 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 223) to an applicant if... Federal Register. (c) The Certificate of Registration (DEA Form 223) shall contain the name, address,...

  13. 21 CFR 1309.42 - Certificate of registration; denial of registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ...; denial of registration. (a) The Administrator shall issue a Certificate of Registration (DEA Form 511) to..., shall hold a hearing on the application pursuant to § 1309.51. (b) The Certificate of Registration...

  14. 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.

  15. 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

  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. The Quality of Registration of Clinical Trials

    PubMed Central

    Viergever, Roderik F.; Ghersi, Davina

    2011-01-01

    Background Lack of transparency in clinical trial conduct, publication bias and selective reporting bias are still important problems in medical research. Through clinical trials registration, it should be possible to take steps towards resolving some of these problems. However, previous evaluations of registered records of clinical trials have shown that registered information is often incomplete and non-meaningful. If these studies are accurate, this negates the possible benefits of registration of clinical trials. Methods and Findings A 5% sample of records of clinical trials that were registered between 17 June 2008 and 17 June 2009 was taken from the International Clinical Trials Registry Platform (ICTRP) database and assessed for the presence of contact information, the presence of intervention specifics in drug trials and the quality of primary and secondary outcome reporting. 731 records were included. More than half of the records were registered after recruitment of the first participant. The name of a contact person was available in 94.4% of records from non-industry funded trials and 53.7% of records from industry funded trials. Either an email address or a phone number was present in 76.5% of non-industry funded trial records and in 56.5% of industry funded trial records. Although a drug name or company serial number was almost always provided, other drug intervention specifics were often omitted from registration. Of 3643 reported outcomes, 34.9% were specific measures with a meaningful time frame. Conclusions Clinical trials registration has the potential to contribute substantially to improving clinical trial transparency and reducing publication bias and selective reporting. These potential benefits are currently undermined by deficiencies in the provision of information in key areas of registered records. PMID:21383991

  18. Implicit reference-based group-wise image registration and its application to structural and functional MRI.

    PubMed

    Geng, Xiujuan; Christensen, Gary E; Gu, Hong; Ross, Thomas J; Yang, Yihong

    2009-10-01

    In this study, an implicit reference group-wise (IRG) registration with a small deformation, linear elastic model was used to jointly estimate correspondences between a set of MRI images. The performance of pair-wise and group-wise registration algorithms was evaluated for spatial normalization of structural and functional MRI data. Traditional spatial normalization is accomplished by group-to-reference (G2R) registration in which a group of images are registered pair-wise to a reference image. G2R registration is limited due to bias associated with selecting a reference image. In contrast, implicit reference group-wise (IRG) registration estimates correspondences between a group of images by jointly registering the images to an implicit reference corresponding to the group average. The implicit reference is estimated during IRG registration eliminating the bias associated with selecting a specific reference image. Registration performance was evaluated using segmented T1-weighted magnetic resonance images from the Nonrigid Image Registration Evaluation Project (NIREP), DTI and fMRI images. Implicit reference pair-wise (IRP) registration-a special case of IRG registration for two images-is shown to produce better relative overlap than IRG for pair-wise registration using the same small deformation, linear elastic registration model. However, IRP-G2R registration is shown to have significant transitivity error, i.e., significant inconsistencies between correspondences defined by different pair-wise transformations. In contrast, IRG registration produces consistent correspondence between images in a group at the cost of slightly reduced pair-wise RO accuracy compared to IRP-G2R. IRG spatial normalization of the fractional anisotropy (FA) maps of DTI is shown to have smaller FA variance compared with G2R methods using the same elastic registration model. Analyses of fMRI data sets with sensorimotor and visual tasks show that IRG registration, on average, increases the

  19. 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

  20. Early Birth Registration at a Center in Rural India

    PubMed Central

    Sachdeva, Sandeep; Nagar, Mukesh; Tyagi, Ajay; Sachdeva, Ruchi; Kumar, Vijay

    2013-01-01

    Background: Registration of birth is mandatory in India however due to various issues compliance for timely birth registration has been poor. Objective: The objective of this study was to determine time elapsed between birth and registration and describe the socio-demographic profile of registered births at a rural center. Materials and Methods: A cross-sectional descriptive study was undertaken and all births registered at a primary health center of a block during the period 2010 and 2011 were retrieved and data collection carried using structured proforma based on birth formats under civil registration system (CRS). House to house visit was undertaken to identify births without registration. Results: A total of 340 and 276 births were registered during 2010 and 2011 respectively. Time elapsed between birth and registration was computed to be lower, i.e., 9.38 days (±7.46) during 2011 in-comparison with 10.52 days (±8.73) in 2010. On a positive note, higher level of education and marriage of women beyond legal age of 18 years was noticed in 2011 in comparison with 2010. Overall, institutional birth stood at a very encouraging note (66.2%). All (100%) births during the study period were registered at this (rural) or higher center (urban) depending on the place of delivery. An omission/commission of birth format is highlighted that needs urgent attention of the authorities. Discussion: Majority (>92%) of birth registration occurred with-in the stipulated period of 21 days as prescribed under CRS and our study indicates early birth registration in a rural area of Haryana, India. PMID:24479089

  1. 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.

  2. 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.

  3. Mask registration and wafer overlay

    NASA Astrophysics Data System (ADS)

    Lee, Chulseung; Bang, Changjin; Kim, Myoungsoo; Kang, Hyosang; Lee, Dohwa; Jeong, Woonjae; Lim, Ok-Sung; Yoon, Seunghoon; Jung, Jaekang; Laske, Frank; Parisoli, Lidia; Roeth, Klaus-Dieter; Robinson, John C.; Jug, Sven; Izikson, Pavel; Dinu, Berta; Widmann, Amir; Choi, DongSub

    2010-03-01

    Overlay continues to be one of the key challenges for lithography in advanced semiconductor manufacturing. It becomes even more challenging due to the continued shrinking of the device node. Some low k1 techniques, such as Double Exposure and Double Patterning also add additional loss of the overlay margin due to the fact that the single layer pattern is created based on more than 1 exposure. Therefore, the overlay between 2 exposures requires very tight overlay specification. Mask registration is one of the major contributors to wafer overlay, especially field related overlay. We investigated mask registration and wafer overlay by co-analyzing the mask data and the wafer overlay data. To achieve the accurate cohesive results, we introduced the combined metrology mark which can be used for both mask registration measurement as well as for wafer overlay measurement. Coincidence of both metrology marks make it possible to subtract mask signature from wafer overlay without compromising the accuracy due to the physical distance between measurement marks, if we use 2 different marks for both metrologies. Therefore, it is possible to extract pure scanner related signatures, and to analyze the scanner related signatures in details to in order to enable root cause analysis and ultimately drive higher wafer yield. We determined the exact mask registration error in order to decompose wafer overlay into mask, scanner, process and metrology. We also studied the impact of pellicle mounting by comparison of mask registration measurement pre-pellicle mounting and post-pellicle mounting in this investigation.

  4. 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.

  5. [Research on non-rigid medical image registration algorithm based on SIFT feature extraction].

    PubMed

    Wang, Anna; Lu, Dan; Wang, Zhe; Fang, Zhizhen

    2010-08-01

    In allusion to non-rigid registration of medical images, the paper gives a practical feature points matching algorithm--the image registration algorithm based on the scale-invariant features transform (Scale Invariant Feature Transform, SIFT). The algorithm makes use of the image features of translation, rotation and affine transformation invariance in scale space to extract the image feature points. Bidirectional matching algorithm is chosen to establish the matching relations between the images, so the accuracy of image registrations is improved. On this basis, affine transform is chosen to complement the non-rigid registration, and normalized mutual information measure and PSO optimization algorithm are also chosen to optimize the registration process. The experimental results show that the method can achieve better registration results than the method based on mutual information.

  6. Simultaneous registration and segmentation of images in wavelet domain

    NASA Astrophysics Data System (ADS)

    Yoshida, Hiroyuki

    1999-10-01

    A novel method for simultaneous registration and segmentation is developed. The method is designed to register two similar images while a region with significant difference is adaptively segmented. This is achieved by minimization of a non-linear functional that models the statistical properties of the subtraction of the two images. Minimization is performed in the wavelet domain by a coarse- to-fine approach to yield a mapping that yields the registration and the boundary that yields the segmentation. The new method was applied to the registration of the left and the right lung regions in chest radiographs for extraction of lung nodules while the normal anatomic structures such as ribs are removed. A preliminary result shows that our method is very effective in reducing the number of false detections obtained with our computer-aided diagnosis scheme for detection of lung nodules in chest radiographs.

  7. 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'.

  8. 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.

  9. 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.

  10. Language proficiency and nursing registration.

    PubMed

    Müller, Amanda

    2016-02-01

    This discussion paper focuses on English proficiency standards for nursing registration in Australia, how Australia has dealt with the issue of language proficiency, and the factors which have led to the establishment of the current language standards. Also, this paper will provide a comparison of the two language tests that are currently accepted in Australia (OET and IELTS), including the appropriateness of these tests and the minimum standards used. The paper will also examine the use of educational background as an indicator of language proficiency. Finally, communication-based complaints in the post-registration environment will be explored, and some discussion will be provided about why pre-registration measures might have failed to prevent such problematic situations from occurring.

  11. Language proficiency and nursing registration.

    PubMed

    Müller, Amanda

    2016-02-01

    This discussion paper focuses on English proficiency standards for nursing registration in Australia, how Australia has dealt with the issue of language proficiency, and the factors which have led to the establishment of the current language standards. Also, this paper will provide a comparison of the two language tests that are currently accepted in Australia (OET and IELTS), including the appropriateness of these tests and the minimum standards used. The paper will also examine the use of educational background as an indicator of language proficiency. Finally, communication-based complaints in the post-registration environment will be explored, and some discussion will be provided about why pre-registration measures might have failed to prevent such problematic situations from occurring. PMID:25704372

  12. 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.

  13. Hierarchical and symmetric infant image registration by robust longitudinal-example-guided correspondence detection

    PubMed Central

    Wu, Yao; Wu, Guorong; Wang, Li; Munsell, Brent C.; Wang, Qian; Lin, Weili; Feng, Qianjin; Chen, Wufan; Shen, Dinggang

    2015-01-01

    Purpose: To investigate anatomical differences across individual subjects, or longitudinal changes in early brain development, it is important to perform accurate image registration. However, due to fast brain development and dynamic tissue appearance changes, it is very difficult to align infant brain images acquired from birth to 1-yr-old. Methods: To solve this challenging problem, a novel image registration method is proposed to align two infant brain images, regardless of age at acquisition. The main idea is to utilize the growth trajectories, or spatial-temporal correspondences, learned from a set of longitudinal training images, for guiding the registration of two different time-point images with different image appearances. Specifically, in the training stage, an intrinsic growth trajectory is first estimated for each training subject using the longitudinal images. To register two new infant images with potentially a large age gap, the corresponding images patches between each new image and its respective training images with similar age are identified. Finally, the registration between the two new images can be assisted by the learned growth trajectories from one time point to another time point that have been established in the training stage. To further improve registration accuracy, the proposed method is combined with a hierarchical and symmetric registration framework that can iteratively add new key points in both images to steer the estimation of the deformation between the two infant brain images under registration. Results: To evaluate image registration accuracy, the proposed method is used to align 24 infant subjects at five different time points (2-week-old, 3-month-old, 6-month-old, 9-month-old, and 12-month-old). Compared to the state-of-the-art methods, the proposed method demonstrated superior registration performance. Conclusions: The proposed method addresses the difficulties in the infant brain registration and produces better results

  14. 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

  15. 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.

  16. 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

  17. Subspace-Based Holistic Registration for Low-Resolution Facial Images

    NASA Astrophysics Data System (ADS)

    Boom, B. J.; Spreeuwers, L. J.; Veldhuis, R. N. J.

    2010-12-01

    Subspace-based holistic registration is introduced as an alternative to landmark-based face registration, which has a poor performance on low-resolution images, as obtained in camera surveillance applications. The proposed registration method finds the alignment by maximizing the similarity score between a probe and a gallery image. We use a novel probabilistic framework for both user-independent as well as user-specific face registration. The similarity is calculated using the probability that the face image is correctly aligned in a face subspace, but additionally we take the probability into account that the face is misaligned based on the residual error in the dimensions perpendicular to the face subspace. We perform extensive experiments on the FRGCv2 database to evaluate the impact that the face registration methods have on face recognition. Subspace-based holistic registration on low-resolution images can improve face recognition in comparison with landmark-based registration on high-resolution images. The performance of the tested face recognition methods after subspace-based holistic registration on a low-resolution version of the FRGC database is similar to that after manual registration.

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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.

  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. 32 CFR 1615.3 - Registration procedures.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 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 Proclamation... of Selective Service....

  5. 32 CFR 1615.3 - Registration procedures.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 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 Proclamation... of Selective Service....

  6. 32 CFR 1615.3 - Registration procedures.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 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 Proclamation... of Selective Service....

  7. 32 CFR 1615.3 - Registration procedures.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 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 Proclamation... of Selective Service....

  8. 32 CFR 1615.3 - Registration procedures.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 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 Proclamation... of Selective Service....

  9. Configurable automatic detection and registration of fiducial frames for device-to-image registration in MRI-guided prostate interventions.

    PubMed

    Tokuda, Junichi; Song, Sang-Eun; Tuncali, Kemal; Tempany, Clare; Hata, Nobuhiko

    2013-01-01

    We propose a novel automatic fiducial frame detection and registration method for device-to-image registration in MRI-guided prostate interventions. The proposed method does not require any manual selection of markers, and can be applied to a variety of fiducial frames, which consist of multiple cylindrical MR-visible markers placed in different orientations. The key idea is that automatic extraction of linear features using a line filter is more robust than that of bright spots by thresholding; by applying a line set registration algorithm to the detected markers, the frame can be registered to the MRI. The method was capable of registering the fiducial frame to the MRI with an accuracy of 1.00 +/- 0.73 mm and 1.41 +/- 1.06 degrees in a phantom study, and was sufficiently robust to detect the fiducial frame in 98% of images acquired in clinical cases despite the existence of anatomical structures in the field of view.

  10. 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

  11. 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.

  12. 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....

  13. 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....

  14. 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....

  15. 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....

  16. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

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

  17. 16 CFR 1130.8 - Requirements for Web site registration or alternative e-mail registration.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... alternative e-mail registration. 1130.8 Section 1130.8 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION... PRODUCTS § 1130.8 Requirements for Web site registration or alternative e-mail registration. (a) Link to... site registration page shall request only the consumer's name, address, telephone number,...

  18. 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...

  19. Cross Correlation versus Normalized Mutual Information on Image Registration

    NASA Technical Reports Server (NTRS)

    Tan, Bin; Tilton, James C.; Lin, Guoqing

    2016-01-01

    This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.

  20. 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.

  1. 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.

  2. 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.

  3. Agile multi-scale decompositions for automatic image registration

    NASA Astrophysics Data System (ADS)

    Murphy, James M.; Leija, Omar Navarro; Le Moigne, Jacqueline

    2016-05-01

    In recent works, the first and third authors developed an automatic image registration algorithm based on a multiscale hybrid image decomposition with anisotropic shearlets and isotropic wavelets. This prototype showed strong performance, improving robustness over registration with wavelets alone. However, this method imposed a strict hierarchy on the order in which shearlet and wavelet features were used in the registration process, and also involved an unintegrated mixture of MATLAB and C code. In this paper, we introduce a more agile model for generating features, in which a flexible and user-guided mix of shearlet and wavelet features are computed. Compared to the previous prototype, this method introduces a flexibility to the order in which shearlet and wavelet features are used in the registration process. Moreover, the present algorithm is now fully coded in C, making it more efficient and portable than the mixed MATLAB and C prototype. We demonstrate the versatility and computational efficiency of this approach by performing registration experiments with the fully-integrated C algorithm. In particular, meaningful timing studies can now be performed, to give a concrete analysis of the computational costs of the flexible feature extraction. Examples of synthetically warped and real multi-modal images are analyzed.

  4. 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.

  5. Gabor feature-based registration: accurate alignment without fiducial markers

    NASA Astrophysics Data System (ADS)

    Parra, Nestor A.; Parra, Carlos A.

    2007-03-01

    Accurate registration of diagnosis and treatment images is a critical factor for the success of radiotherapy. This study presents a feature-based image registration algorithm that uses a branch- and-bound method to search the space of possible transformations, as well as a Hausdorff distance metric to evaluate their quality. This distance is computed in the space of responses to a circular Gabor filter, in which, for each point of interest in both reference and subject images, a vector of complex responses to different Gabor kernels is computed. Each kernel is generated using different frequencies and variances of the Gabor function, which determines correspondent regions in the images to be registered, by virtue of its rotation invariance characteristics. Responses to circular Gabor filters have also been reported in literature as a successful tool for image classification; and in this particular application we utilize them for patient positioning in cranial radiotherapy. For test purposes, we use 2D portal images acquired with an electronic portal imaging device (EPID). Our method presents EPID-EPID registrations errors under 0.2 mm for translations and 0.05 deg for rotations (subpixel accuracy). We are using fiducial marker registration as the ground truth for comparisons. Registration times average 2.70 seconds based on 1400 feature points using a 1.4 GHz processor.

  6. 12 CFR 583.18 - Registrant.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY DEFINITIONS FOR REGULATIONS AFFECTING SAVINGS AND LOAN HOLDING COMPANIES § 583.18 Registrant. The term registrant means a savings and loan holding company filing a registration statement with the Office pursuant to § 584.1 of this chapter....

  7. 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...

  8. 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...

  9. 75 FR 47729 - National Voter Registration Act

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-08-09

    ... COMMISSION 11 CFR Part 9428 National Voter Registration Act AGENCY: Election Assistance Commission. ACTION... proposed changes to its regulations pertaining to the National Voter Registration Act of 1993 (NVRA... mail voter registration form and for submitting a biennial report to Congress on the impact of the...

  10. 32 CFR 1602.20 - Registrant.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Registrant. 1602.20 Section 1602.20 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM DEFINITIONS § 1602.20 Registrant. A registrant is a person registered under the Selective Service Law....

  11. 32 CFR 1602.20 - Registrant.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 6 2011-07-01 2011-07-01 false Registrant. 1602.20 Section 1602.20 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM DEFINITIONS § 1602.20 Registrant. A registrant is a person registered under the Selective Service Law....

  12. 32 CFR 1602.20 - Registrant.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 32 National Defense 6 2014-07-01 2014-07-01 false Registrant. 1602.20 Section 1602.20 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM DEFINITIONS § 1602.20 Registrant. A registrant is a person registered under the Selective Service Law....

  13. 32 CFR 1602.20 - Registrant.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 32 National Defense 6 2012-07-01 2012-07-01 false Registrant. 1602.20 Section 1602.20 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM DEFINITIONS § 1602.20 Registrant. A registrant is a person registered under the Selective Service Law....

  14. 32 CFR 1602.20 - Registrant.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 32 National Defense 6 2013-07-01 2013-07-01 false Registrant. 1602.20 Section 1602.20 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM DEFINITIONS § 1602.20 Registrant. A registrant is a person registered under the Selective Service Law....

  15. Clinical trial registration in oral health journals.

    PubMed

    Smaïl-Faugeron, V; Fron-Chabouis, H; Durieux, P

    2015-03-01

    Prospective registration of randomized controlled trials (RCTs) represents the best solution to reporting bias. The extent to which oral health journals have endorsed and complied with RCT registration is unknown. We identified journals publishing RCTs in dentistry, oral surgery, and medicine in the Journal Citation Reports. We classified journals into 3 groups: journals requiring or recommending trial registration, journals referring indirectly to registration, and journals providing no reference to registration. For the 5 journals with the highest 2012 impact factors in each group, we assessed whether RCTs with results published in 2013 had been registered. Of 78 journals examined, 32 (41%) required or recommended trial registration, 19 (24%) referred indirectly to registration, and 27 (35%) provided no reference to registration. We identified 317 RCTs with results published in the 15 selected journals in 2013. Overall, 73 (23%) were registered in a trial registry. Among those, 91% were registered retrospectively and 32% did not report trial registration in the published article. The proportion of trials registered was not significantly associated with editorial policies: 29% with results in journals that required or recommended registration, 15% in those that referred indirectly to registration, and 21% in those providing no reference to registration (P = 0.05). Less than one-quarter of RCTs with results published in a sample of oral health journals were registered with a public registry. Improvements are needed with respect to how journals inform and require their authors to register their trials.

  16. 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.

  17. 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.

  18. 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).

  19. 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.

  20. 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.

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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.

  8. 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)

  9. 78 FR 40820 - 60-Day Notice of Proposed Information Collection: Exchange Programs Alumni Web Site Registration

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-08

    ... Notice of Proposed Information Collection: Exchange Programs Alumni Web Site Registration ACTION: Notice.... ADDRESSES: You may submit comments by any of the following methods: Web: Persons with access to the Internet... of Information Collection: Exchange Programs Alumni Web site Registration OMB Control Number:...

  10. 75 FR 57945 - Atonik and Verbenone, Registration Review Proposed Decisions; Notice of Availability

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-23

    ... 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:...

  11. 76 FR 38166 - Registration Review; Pesticide Dockets Opened for Review and Comment and Other Docket Actions

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-29

    ... review dockets 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... interest provided in the table in Unit III.A., by one of the following methods: Federal eRulemaking...

  12. 76 FR 4690 - Menthol and Propetamphos; Registration Review Proposed Decisions; Notice of Availability

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-01-26

    ... 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:...

  13. 75 FR 16117 - Registration Review; Pesticide Dockets Opened for Review and Comment

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-31

    ... 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... pesticide of interest provided in the table in Unit III.A., by one of the following methods: Federal...

  14. 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...

  15. 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...

  16. 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:...

  17. 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.

  18. Novel registration technique to register neutral zone

    PubMed Central

    Agrawal, Kaushal Kishor; Singh, Saumyendra Vikram; Vero, Nugotsov; Alvi, Habib Ahmed; Chand, Pooran; Singh, Kamleshwar; Goel, Prachi

    2012-01-01

    Introduction The three dimensional volume of complete dentures optimally occupies an edentulous space that is substantial, in the light of the progressive changes that accompany edentulism and functional dynamics. The paper discusses current knowledge of neutral zone registration and presents a novel technique for this registration. Material and methods Fabricate maxillary and mandibular occlusal rims over conventional record bases using high fusing impression compound. Register the maxillary and mandibular neutral zone separately by swallowing method and after try in of complete denture; remove the wax apical to the tooth surfaces and recording will be completed with putty and light body impression material. Results Complete dentures are a biomechanical device that must be designed in harmony with normal neuromuscular function to get stability and proper function. Improper teeth positioning and polished surface contour will result in compromised stability of denture. Conclusions This article describes a preview of facio-lingual positioning of denture teeth along with a novel approach of recording the neutral zone with an elastomeric impression material. PMID:25737865

  19. Simultaneous registration of multiple images: similarity metrics and efficient optimization.

    PubMed

    Wachinger, Christian; Navab, Nassir

    2013-05-01

    We address the alignment of a group of images with simultaneous registration. Therefore, we provide further insights into a recently introduced framework for multivariate similarity measures, referred to as accumulated pair-wise estimates (APE), and derive efficient optimization methods for it. More specifically, we show a strict mathematical deduction of APE from a maximum-likelihood framework and establish a connection to the congealing framework. This is only possible after an extension of the congealing framework with neighborhood information. Moreover, we address the increased computational complexity of simultaneous registration by deriving efficient gradient-based optimization strategies for APE: Gauss-Newton and the efficient second-order minimization (ESM). We present next to SSD the usage of intrinsically nonsquared similarity measures in this least squares optimization framework. The fundamental assumption of ESM, the approximation of the perfectly aligned moving image through the fixed image, limits its application to monomodal registration. We therefore incorporate recently proposed structural representations of images which allow us to perform multimodal registration with ESM. Finally, we evaluate the performance of the optimization strategies with respect to the similarity measures, leading to very good results for ESM. The extension to multimodal registration is in this context very interesting because it offers further possibilities for evaluations, due to publicly available datasets with ground-truth alignment.

  20. 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.

  1. 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.

  2. Semi-automated registration of pre- and intra-operative liver CT for image-guided interventions

    NASA Astrophysics Data System (ADS)

    Gunay, Gokhan; Ha, Luu Manh; van Walsum, Theo; Klein, Stefan

    2016-03-01

    Percutaneous radio frequency ablation is a method for liver tumor treatment when conventional surgery is not an option. It is a minimally invasive treatment and may be performed under CT image guidance if the tumor does not give sufficient contrast on ultrasound images. For optimal guidance, registration of the pre-operative contrast-enhanced CT image to the intra-operative CT image is hypothesized to improve guidance. This is a highly challenging registration task due to large differences in pose and image quality. In this study, we introduce a semi-automated registration algorithm to address this problem. The method is based on a conventional nonrigid intensity-based registration framework, extended with a novel point-to-surface constraint. The point-to-surface constraint serves to improve the alignment of the liver boundary, while requiring minimal user interaction during the operation. The method assumes that a liver segmentation of the pre-operative CT is available. After an initial nonrigid registration without the point-to-surface constraint, the operator clicks a few points on the liver surface at those regions where the nonrigid registration seems inaccurate. In a subsequent registration step, these points on the intra-operative image are driven towards the liver surface on the preoperative image, using a penalty term added to the registration cost function. The method is evaluated on five clinical datasets and it is shown to improve registration compared with conventional rigid and nonrigid registrations in all cases.

  3. 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.

  4. 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.

  5. Continuous registration based on computed tomography for breathing motion compensation

    PubMed Central

    Zyłkowski, Jaroslaw; Wróblewski, Tadeusz

    2013-01-01

    Introduction Image guidance for intervention is applied for complex and difficult anatomical regions. Nowadays, it is typically used in neurosurgery, otolaryngology, orthopedics and dentistry. The application of the image-guided system for soft tissues is challenging due to various deformations caused by respiratory motion, tissue elasticity and peristalsis. Aim The main task for the presented approach is continuous registration of preoperative computed tomography (CT) and patient position in the operating room (OR) without touching the patient and compensation of breathing motion. This approach is being developed as a step to image-guided percutaneous liver RF tumor ablation. Material and methods Up to ten integrated radiological markers are placed on the patient's skin before CT scans. Then the anatomical model based on CT images is calculated. Point-to-point registration based on the Horn algorithm during a few breathing cycles is performed using a videometric tracking system. The transformation which corresponds to the minimum fiducial registration error (FRE) is found during the registration and it is treated as the initial transformation for calculating local deformation field of breathing motion compensation based on the spline approach. Results For manual registration of the abdominal phantom, the mean values of target registration error (TRE), fiducial localization error (FLE) and FRE are all below 4 mm for the rigid transformation and are below 1 mm for the affine transformation. For the patient's data they are all below 9 mm and 6 mm, respectively. For the automatic method, different marker configurations have been evaluated while dividing the respiratory cycle into inhale and exhale. Average median values for FRE, TRE rigid estimation and TRE based on spline deformation were 15.56 mm, 0.82 mm and 7.21 mm respectively. Conclusions In this application two registration methods of abdominal preoperative CT anatomical model and physical patient position in

  6. 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

  7. Automated segmentation and registration technique for HMPAO-SPECT imaging of Alzheimer's patients

    NASA Astrophysics Data System (ADS)

    Radau, Perry E.; Slomka, Piotr J.; Julin, Per; Svensson, Leif; Wahlund, Lars-Olof

    2000-06-01

    We present an operator-independent software technique for segmentation, realignment and analysis of brain perfusion images, with both voxel-wise and regional quantitation methods. Inter-subject registration with normalized mutual information was tested with simulated defects. Brain perfusion images (HMPAO-SPECT) from 56 subjects (21 AD; 35 controls) were retrospectively analyzed. Templates were created from the 3-D registration of the controls. Automatic segmentation was developed to remove extraneous activity that disrupts registration. Two new registration methods, robust least squares (RLS) and normalized mutual information (NMI) were implemented and compared with sum of absolute differences (CD). The automatic segmentation method caused a registration displacement of 0.4 +/- 0.3 pixels compared with manual segmentation. NMI registration proved to be less adversely effected by simulated defects than RLS or CD. The error in quantitating the patient-template parietal ratio due to mis- registration was 2.0% and 0.5% for 70% and 85% hypoperfusion defects, respectively. The registration processing time was 1.6 min (233 MHz Pentium). The most accurate discriminant utilized a logistic equation parameterized by mean counts of the parietal and temporal regions of the map, (91 +/- 8% Se, 97 +/- 5% Sp). BRASS is a fast, objective software package for single-step analysis of brain SPECT, suitable to aid diagnosis of AD.

  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. 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

  10. 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

  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.

  12. 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.

  13. 48 CFR 18.102 - Central contractor registration.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 48 Federal Acquisition Regulations System 1 2012-10-01 2012-10-01 false Central contractor registration. 18.102 Section 18.102 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION CONTRACTING METHODS AND CONTRACT TYPES EMERGENCY ACQUISITIONS Available Acquisition Flexibilities...

  14. 48 CFR 18.102 - Central contractor registration.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 48 Federal Acquisition Regulations System 1 2011-10-01 2011-10-01 false Central contractor registration. 18.102 Section 18.102 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION CONTRACTING METHODS AND CONTRACT TYPES EMERGENCY ACQUISITIONS Available Acquisition Flexibilities...

  15. 48 CFR 18.102 - Central contractor registration.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Central contractor registration. 18.102 Section 18.102 Federal Acquisition Regulations System FEDERAL ACQUISITION REGULATION CONTRACTING METHODS AND CONTRACT TYPES EMERGENCY ACQUISITIONS Available Acquisition Flexibilities...

  16. Finite-Dimensional Lie Algebras for Fast Diffeomorphic Image Registration.

    PubMed

    Zhang, Miaomiao; Fletcher, P Thomas

    2015-01-01

    This paper presents a fast geodesic shooting algorithm for diffeomorphic image registration. We first introduce a novel finite-dimensional Lie algebra structure on the space of bandlimited velocity fields. We then show that this space can effectively represent initial velocities for diffeomorphic image registration at much lower dimensions than typically used, with little to no loss in registration accuracy. We then leverage the fact that the geodesic evolution equations, as well as the adjoint Jacobi field equations needed for gradient descent methods, can be computed entirely in this finite-dimensional Lie algebra. The result is a geodesic shooting method for large deformation metric mapping (LDDMM) that is dramatically faster and less memory intensive than state-of-the-art methods. We demonstrate the effectiveness of our model to register 3D brain images and compare its registration accuracy, run-time, and memory consumption with leading LDDMM methods. We also show how our algorithm breaks through the prohibitive time and memory requirements of diffeomorphic atlas building.

  17. 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.

  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. PCA and level set based non-rigid image registration for MRI and Paxinos-Watson atlas of rat brain

    NASA Astrophysics Data System (ADS)

    Cai, Chao; Liu, Ailing; Ding, Mingyue; Zhou, Chengping

    2007-12-01

    Image registration provides the ability to geometrically align one dataset with another. It is a basic task in a great variety of biomedical imaging applications. This paper introduced a novel three-dimensional registration method for Magnetic Resonance Image (MRI) and Paxinos-Watson Atlas of rat brain. For the purpose of adapting to a large range and non-linear deformation between MRI and atlas in higher registration accuracy, based on the segmentation of rat brain, we chose the principle components analysis (PCA) automatically performing the linear registration, and then, a level set based nonlinear registration correcting some small distortions. We implemented this registration method in a rat brain 3D reconstruction and analysis system. Experiments have demonstrated that this method can be successfully applied to registering the low resolution and noise affection MRI with Paxinos-Watson Atlas of rat brain.

  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. 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.

  3. 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.

  4. Point Set Registration via Particle Filtering and Stochastic Dynamics

    PubMed Central

    Sandhu, Romeil; Dambreville, Samuel; Tannenbaum, Allen

    2013-01-01

    In this paper, we propose a particle filtering approach for the problem of registering two point sets that differ by a rigid body transformation. Typically, registration algorithms compute the transformation parameters by maximizing a metric given an estimate of the correspondence between points across the two sets of interest. This can be viewed as a posterior estimation problem, in which the corresponding distribution can naturally be estimated using a particle filter. In this work, we treat motion as a local variation in pose parameters obtained by running a few iterations of a certain local optimizer. Employing this idea, we introduce stochastic motion dynamics to widen the narrow band of convergence often found in local optimizer approaches for registration. Thus, the novelty of our method is threefold: First, we employ a particle filtering scheme to drive the point set registration process. Second, we present a local optimizer that is motivated by the correlation measure. Third, we increase the robustness of the registration performance by introducing a dynamic model of uncertainty for the transformation parameters. In contrast with other techniques, our approach requires no annealing schedule, which results in a reduction in computational complexity (with respect to particle size) as well as maintains the temporal coherency of the state (no loss of information). Also unlike some alternative approaches for point set registration, we make no geometric assumptions on the two data sets. Experimental results are provided that demonstrate the robustness of the algorithm to initialization, noise, missing structures, and/or differing point densities in each set, on several challenging 2D and 3D registration scenarios. PMID:20558877

  5. Quantitative validation of 3D image registration techniques

    NASA Astrophysics Data System (ADS)

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

    1995-05-01

    Multimodality images obtained from different medical imaging systems such as magnetic resonance (MR), computed tomography (CT), ultrasound (US), positron emission tomography (PET), single photon emission computed tomography (SPECT) provide largely complementary characteristic or diagnostic information. Therefore, it is an important research objective to `fuse' or combine this complementary data into a composite form which would provide synergistic information about the objects under examination. An important first step in the use of complementary fused images is 3D image registration, where multi-modality images are brought into spatial alignment so that the point-to-point correspondence between image data sets is known. Current research in the field of multimodality image registration has resulted in the development and implementation of several different registration algorithms, each with its own set of requirements and parameters. Our research has focused on the development of a general paradigm for measuring, evaluating and comparing the performance of different registration algorithms. Rather than evaluating the results of one algorithm under a specific set of conditions, we suggest a general approach to validation using simulation experiments, where the exact spatial relationship between data sets is known, along with phantom data, to characterize the behavior of an algorithm via a set of quantitative image measurements. This behavior may then be related to the algorithm's performance with real patient data, where the exact spatial relationship between multimodality images is unknown. Current results indicate that our approach is general enough to apply to several different registration algorithms. Our methods are useful for understanding the different sources of registration error and for comparing the results between different algorithms.

  6. [Progress of research in retinal image registration].

    PubMed

    Yu, Lun; Wei, Lifang; Pan, Lin

    2011-10-01

    The retinal image registration has important applications in the processes of auxiliary diagnosis and treatment for a variety of diseases. The retinal image registration can be used to measure the disease process and the therapeutic effect. A variety of retinal image registration techniques have been studied extensively in recent years. However, there are still many problems existing and there are numerous research possibilities. Based on extensive investigation of existing literatures, the present paper analyzes the feature of retinal image and current challenges of retinal image registration, and reviews the transformation models of the retinal image registration technology and the main research algorithms in current retinal image registration, and analyzes the advantages and disadvantages of various types of algorithms. Some research challenges and future developing trends are also discussed.

  7. 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

  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. 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

  10. Decoupled automated rotational and translational registration for functional MRI time series data: the DART registration algorithm.

    PubMed

    Maas, L C; Frederick, B D; Renshaw, P F

    1997-01-01

    A rapid, in-plane image registration algorithm that accurately estimates and corrects for rotational and translational motion is described. This automated, one-pass method achieves its computational efficiency by decoupling the estimation of rotation and translation, allowing the application of rapid cross-correlation and cross-spectrum techniques for the determination of displacement parameters. k-space regridding and modulation techniques are used for image correction as alternatives to linear interpolation. The performance of this method was analyzed with simulations and echo-planar image data from both phantoms and human subjects. The processing time for image registration on a Hewlett-Packard 735/125 is 7.5 s for a 128 x 128 pixel image and 1.7 s for a 64 x 64 pixel image. Imaging phantom data demonstrate the accuracy of the method (mean rotational error, -0.09 degrees; standard deviation = 0.17 degrees; range, -0.44 degrees to +0.31 degrees; mean translational error = -0.035 pixels; standard deviation = 0.054 pixels; range, -0.16 to +0.06 pixels). Registered human functional imaging data demonstrate a significant reduction in motion artifacts such as linear trends in pixel time series and activation artifacts due to stimulus-correlated motion. The advantages of this technique are its noniterative one-pass nature, the reduction in image degradation as compared to previous methods, and the speed of computation.

  11. 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

  12. 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.

  13. Automatic geometric rectification for patient registration in image-guided spinal surgery

    NASA Astrophysics Data System (ADS)

    Cai, Yunliang; Olson, Jonathan D.; Fan, Xiaoyao; Evans, Linton T.; Paulsen, Keith D.; Roberts, David W.; Mirza, Sohail K.; Lollis, S. Scott; Ji, Songbai

    2016-03-01

    Accurate and efficient patient registration is crucial for the success of image-guidance in open spinal surgery. Recently, we have established the feasibility of using intraoperative stereovision (iSV) to perform patient registration with respect to preoperative CT (pCT) in human subjects undergoing spinal surgery. Although a desired accuracy was achieved, the method required manual segmentation and placement of feature points on reconstructed iSV and pCT surfaces. In this study, we present an improved registration pipeline to eliminate these manual operations. Specifically, automatic geometric rectification was performed on spines extracted from pCT and iSV into pose-invariant shapes using a nonlinear principal component analysis (NLPCA). Rectified spines were obtained by projecting the reconstructed 3D surfaces into an anatomically determined orientation. Two-dimensional projection images were then created with image intensity values encoding feature "height" in the dorsal-ventral direction. Registration between the 2D depth maps yielded an initial point-wise correspondence between the 3D surfaces. A refined registration was achieved using an iterative closest point (ICP) algorithm. The technique was successfully applied to two explanted and one live porcine spines. The computational cost of the registration pipeline was less than 1 min, with an average target registration error (TRE) less than 2.2 mm in the laminae area. These results suggest the potential for the pose-invariant, rectification-based registration technique for clinical application in human subjects in the future.

  14. 37 CFR 2.173 - Amendment of registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... change in the mark: a new specimen showing the mark as used on or in connection with the goods or...) Registration must still contain registrable matter. The registration as amended must still contain registrable matter, and the mark as amended must be registrable as a whole. (d) Amendment may not materially...

  15. 27 CFR 31.111 - Date registration form is due.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2014-04-01 2014-04-01 false Date registration form is....111 Date registration form is due. (a) General. Dealers must register by filing the registration form... form was filed, no additional registration is required. If the registration form is received in...

  16. 14 CFR 47.61 - Dealer's Aircraft Registration Certificates.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Dealer's Aircraft Registration Certificates... TRANSPORTATION AIRCRAFT AIRCRAFT REGISTRATION Dealers' Aircraft Registration Certificate § 47.61 Dealer's Aircraft Registration Certificates. (a) The FAA issues a Dealer's Aircraft Registration Certificate,...

  17. 14 CFR 47.61 - Dealers' Aircraft Registration Certificates.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Dealers' Aircraft Registration Certificates... TRANSPORTATION AIRCRAFT AIRCRAFT REGISTRATION Dealers' Aircraft Registration Certificate § 47.61 Dealers' Aircraft Registration Certificates. (a) The FAA issues a Dealers' Aircraft Registration Certificate,...

  18. 14 CFR 47.61 - Dealer's Aircraft Registration Certificates.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Dealer's Aircraft Registration Certificates... TRANSPORTATION AIRCRAFT AIRCRAFT REGISTRATION Dealers' Aircraft Registration Certificate § 47.61 Dealer's Aircraft Registration Certificates. (a) The FAA issues a Dealer's Aircraft Registration Certificate,...

  19. Nonrigid Image Registration for Head and Neck Cancer Radiotherapy Treatment Planning With PET/CT

    SciTech Connect

    Ireland, Rob H. . E-mail: r.ireland@sheffield.ac.uk; Dyker, Karen E.; Barber, David C.; Wood, Steven M.; Hanney, Michael B.; Tindale, Wendy B.; Woodhouse, Neil; Hoggard, Nigel; Conway, John; Robinson, Martin H.

    2007-07-01

    Purpose: Head and neck radiotherapy planning with positron emission tomography/computed tomography (PET/CT) requires the images to be reliably registered with treatment planning CT. Acquiring PET/CT in treatment position is problematic, and in practice for some patients it may be beneficial to use diagnostic PET/CT for radiotherapy planning. Therefore, the aim of this study was first to quantify the image registration accuracy of PET/CT to radiotherapy CT and, second, to assess whether PET/CT acquired in diagnostic position can be registered to planning CT. Methods and Materials: Positron emission tomography/CT acquired in diagnostic and treatment position for five patients with head and neck cancer was registered to radiotherapy planning CT using both rigid and nonrigid image registration. The root mean squared error for each method was calculated from a set of anatomic landmarks marked by four independent observers. Results: Nonrigid and rigid registration errors for treatment position PET/CT to planning CT were 2.77 {+-} 0.80 mm and 4.96 {+-} 2.38 mm, respectively, p = 0.001. Applying the nonrigid registration to diagnostic position PET/CT produced a more accurate match to the planning CT than rigid registration of treatment position PET/CT (3.20 {+-} 1.22 mm and 4.96 {+-} 2.38 mm, respectively, p = 0.012). Conclusions: Nonrigid registration provides a more accurate registration of head and neck PET/CT to treatment planning CT than rigid registration. In addition, nonrigid registration of PET/CT acquired with patients in a standardized, diagnostic position can provide images registered to planning CT with greater accuracy than a rigid registration of PET/CT images acquired in treatment position. This may allow greater flexibility in the timing of PET/CT for head and neck cancer patients due to undergo radiotherapy.

  20. 21 CFR 1301.52 - Termination of registration; transfer of registration; distribution upon discontinuance of business.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 21 Food and Drugs 9 2010-04-01 2010-04-01 false Termination of registration; transfer of registration; distribution upon discontinuance of business. 1301.52 Section 1301.52 Food and Drugs DRUG... person seeking authority to transfer a registration shall submit a written request, providing...

  1. 16 CFR 1130.8 - Requirements for Web site registration or alternative e-mail registration.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... alternative e-mail registration. 1130.8 Section 1130.8 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION... PRODUCTS § 1130.8 Requirements for Web site registration or alternative e-mail registration. (a) Link to... a link to the manufacturer's home page, a field to confirm submission, and a prompt to indicate...

  2. 28 CFR 12.3 - Prior registration with the Foreign Agents Registration Unit.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Prior registration with the Foreign Agents Registration Unit. 12.3 Section 12.3 Judicial Administration DEPARTMENT OF JUSTICE REGISTRATION OF CERTAIN PERSONS HAVING KNOWLEDGE OF FOREIGN ESPIONAGE, COUNTERESPIONAGE, OR SABOTAGE MATTERS UNDER THE...

  3. 75 FR 37790 - Lauryl Sulfate Salts; Antimicrobial Registration Review Final Work Plan and Proposed Registration...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-30

    ... AGENCY Lauryl Sulfate Salts; Antimicrobial Registration Review Final Work Plan and Proposed Registration... decision for the pesticide lauryl sulfate salts, case number 4061 and opens a public comment period on the... availability of EPA's proposed registration review decision for the pesticide lauryl sulfate salts, case...

  4. 21 CFR 1301.52 - Termination of registration; transfer of registration; distribution upon discontinuance of business.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 9 2011-04-01 2011-04-01 false Termination of registration; transfer of registration; distribution upon discontinuance of business. 1301.52 Section 1301.52 Food and Drugs DRUG... OF CONTROLLED SUBSTANCES Modification, Transfer and Termination of Registration § 1301.52...

  5. 21 CFR 1301.52 - Termination of registration; transfer of registration; distribution upon discontinuance of business.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 21 Food and Drugs 9 2012-04-01 2012-04-01 false Termination of registration; transfer of registration; distribution upon discontinuance of business. 1301.52 Section 1301.52 Food and Drugs DRUG... OF CONTROLLED SUBSTANCES Modification, Transfer and Termination of Registration § 1301.52...

  6. 21 CFR 1301.52 - Termination of registration; transfer of registration; distribution upon discontinuance of business.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 21 Food and Drugs 9 2013-04-01 2013-04-01 false Termination of registration; transfer of registration; distribution upon discontinuance of business. 1301.52 Section 1301.52 Food and Drugs DRUG... OF CONTROLLED SUBSTANCES Modification, Transfer and Termination of Registration § 1301.52...

  7. 21 CFR 1301.52 - Termination of registration; transfer of registration; distribution upon discontinuance of business.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 21 Food and Drugs 9 2014-04-01 2014-04-01 false Termination of registration; transfer of registration; distribution upon discontinuance of business. 1301.52 Section 1301.52 Food and Drugs DRUG... OF CONTROLLED SUBSTANCES Modification, Transfer and Termination of Registration § 1301.52...

  8. MRI Signal Intensity Based B-Spline Nonrigid Registration for Pre- and Intraoperative Imaging During Prostate Brachytherapy

    PubMed Central

    Oguro, Sota; Tokuda, Junichi; Elhawary, Haytham; Haker, Steven; Kikinis, Ron; Tempany, Clare M.C.; Hata, Nobuhiko

    2009-01-01

    Purpose To apply an intensity-based nonrigid registration algorithm to MRI-guided prostate brachytherapy clinical data and to assess its accuracy. Materials and Methods A nonrigid registration of preoperative MRI to intraoperative MRI images was carried out in 16 cases using a Basis-Spline algorithm in a retrospective manner. The registration was assessed qualitatively by experts’ visual inspection and quantitatively by measuring the Dice similarity coefficient (DSC) for total gland (TG), central gland (CG), and peripheral zone (PZ), the mutual information (MI) metric, and the fiducial registration error (FRE) between corresponding anatomical landmarks for both the nonrigid and a rigid registration method. Results All 16 cases were successfully registered in less than 5 min. After the nonrigid registration, DSC values for TG, CG, PZ were 0.91, 0.89, 0.79, respectively, the MI metric was −0.19 ± 0.07 and FRE presented a value of 2.3 ± 1.8 mm. All the metrics were significantly better than in the case of rigid registration, as determined by one-sided t-tests. Conclusion The intensity-based nonrigid registration method using clinical data was demonstrated to be feasible and showed statistically improved metrics when compare to only rigid registration. The method is a valuable tool to integrate pre- and intraoperative images for brachytherapy. PMID:19856437

  9. 3D non-rigid registration using surface and local salient features for transrectal ultrasound image-guided prostate biopsy

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  10. Registration of ultrasound to CT angiography of kidneys: a porcine phantom study

    NASA Astrophysics Data System (ADS)

    Xiang, Jing; Gill, Sean; Nguan, Christopher; Abolmaesumi, Purang; Rohling, Robert N.

    2010-02-01

    3D ultrasound (US) to computed tomography (CT) registration is a topic of significant interest because it can potentially improve many minimally invasive procedures such as laparoscopic partial nephrectomy. Partial nephrectomy patients often receive preoperative CT angiography, which helps define the important structures of the kidney such as the vasculature. Intraoperatively, dynamic real-time imaging information can be captured using ultrasound and compared with the preoperative data. Providing accurate registration between the two modalities would enhance navigation and guidance for the surgeon. However, one of the major problems of developing and evaluating registration techniques is obtaining sufficiently accurate and realistic phantom data especially for soft tissue. We present a detailed procedure for constructing tissue phantoms using porcine kidneys, which incorporates contrast agent into the tissue such that the kidneys appear representative of in vivo human CT angiography. These phantoms are also imaged with US and resemble US images from human patients. We then perform registration on corresponding CT and US datasets using a simulation-based algorithm. The method simulates an US image from the CT, generating an intermediate modality that resembles ultrasound. This simulated US is then registered to the original US dataset. Embedded fiducial markers provide a gold standard for registration. Being able to test our registration method on realistic datasets facilitates the development of novel CT to US registration techniques such that we can generate an effective method for human studies.

  11. α-Information Based Registration of Dynamic Scans for Magnetic Resonance Cystography

    PubMed Central

    Han, Hao; Lin, Qin; Li, Lihong; Duan, Chaijie; Lu, Hongbing; Li, Haifang; Yan, Zengmin; Fitzgerald, John

    2015-01-01

    To continue our effort on developing magnetic resonance (MR) cystography, we introduce a novel non–rigid 3D registration method to compensate for bladder wall motion and deformation in dynamic MR scans, which are impaired by relatively low signal–to–noise ratio in each time frame. The registration method is developed on the similarity measure of α–information, which has the potential of achieving higher registration accuracy than the commonly-used mutual information (MI) measure for either mono-modality or multi-modality image registration. The α–information metric was also demonstrated to be superior to both the mean squares and the cross-correlation metrics in multi-modality scenarios. The proposed α–registration method was applied for bladder motion compensation via real patient studies, and its effect to the automatic and accurate segmentation of bladder wall was also evaluated. Compared with the prevailing MI-based image registration approach, the presented α–information based registration was more effective to capture the bladder wall motion and deformation, which ensured the success of the following bladder wall segmentation to achieve the goal of evaluating the entire bladder wall for detection and diagnosis of abnormality. PMID:26087506

  12. Ground registration of data from an airborne scatterometer

    NASA Technical Reports Server (NTRS)

    Richter, J. C.

    1981-01-01

    A portion of the data for the agricultural soil moisture experiment, conducted near Colby, Kansas, was collected from four scatterometers mounted on an aircraft. A method is outlined for locating the scatterometer footprints with respect to a ground-based coordinate system. The method requires the airplane's flight parameters along with aerial photography acquired simultaneously with the scatterometer data. Listings of the programs used in the registration process are included.

  13. Highly Accurate Inverse Consistent Registration: A Robust Approach

    PubMed Central

    Reuter, Martin; Rosas, H. Diana; Fischl, Bruce

    2010-01-01

    The registration of images is a task that is at the core of many applications in computer vision. In computational neuroimaging where the automated segmentation of brain structures is frequently used to quantify change, a highly accurate registration is necessary for motion correction of images taken in the same session, or across time in longitudinal studies where changes in the images can be expected. This paper, inspired by Nestares and Heeger (2000), presents a method based on robust statistics to register images in the presence of differences, such as jaw movement, differential MR distortions and true anatomical change. The approach we present guarantees inverse consistency (symmetry), can deal with different intensity scales and automatically estimates a sensitivity parameter to detect outlier regions in the images. The resulting registrations are highly accurate due to their ability to ignore outlier regions and show superior robustness with respect to noise, to intensity scaling and outliers when compared to state-of-the-art registration tools such as FLIRT (in FSL) or the coregistration tool in SPM. PMID:20637289

  14. Morphological Feature Extraction for Automatic Registration of Multispectral Images

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2007-01-01

    The task of image registration can be divided into two major components, i.e., the extraction of control points or features from images, and the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual extraction of control features can be subjective and extremely time consuming, and often results in few usable points. On the other hand, automated feature extraction allows using invariant target features such as edges, corners, and line intersections as relevant landmarks for registration purposes. In this paper, we present an extension of a recently developed morphological approach for automatic extraction of landmark chips and corresponding windows in a fully unsupervised manner for the registration of multispectral images. Once a set of chip-window pairs is obtained, a (hierarchical) robust feature matching procedure, based on a multiresolution overcomplete wavelet decomposition scheme, is used for registration purposes. The proposed method is validated on a pair of remotely sensed scenes acquired by the Advanced Land Imager (ALI) multispectral instrument and the Hyperion hyperspectral instrument aboard NASA's Earth Observing-1 satellite.

  15. Incorporating target registration error into robotic bone milling

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  16. 40 CFR 68.160 - Registration.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 16 2014-07-01 2014-07-01 false Registration. 68.160 Section 68.160 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CHEMICAL ACCIDENT PREVENTION PROVISIONS Risk Management Plan § 68.160 Registration. (a) The owner or operator...

  17. 77 FR 73558 - Sex Offender Registration Amendments

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-11

    ... SUPERVISION AGENCY FOR THE DISTRICT OF COLUMBIA 28 CFR Part 811 RIN 3225-AA10 Sex Offender Registration... requirements relating to periodic verification of registration information for sex offenders. The proposed rule, if finalized, would permit CSOSA to verify addresses of sex offenders by conducting home visits...

  18. 78 FR 23835 - Sex Offender Registration Amendments

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-23

    ... it can be found at 77 FR 73558. The proposed rule was published to allow CSOSA to better meet the... SUPERVISION AGENCY FOR THE DISTRICT OF COLUMBIA 28 CFR Part 811 RIN 3225-AA10 Sex Offender Registration... verification of registration information for sex offenders. Furthermore, the rule permits CSOSA to...

  19. 5 CFR 330.207 - Registration area.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 5 Administrative Personnel 1 2013-01-01 2013-01-01 false Registration area. 330.207 Section 330..., SELECTION, AND PLACEMENT (GENERAL) Reemployment Priority List (RPL) § 330.207 Registration area. (a) Except... commuting area in which the eligible was, or will be, separated. (b) If the agency has, or will have,...

  20. 5 CFR 330.207 - Registration area.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 5 Administrative Personnel 1 2012-01-01 2012-01-01 false Registration area. 330.207 Section 330..., SELECTION, AND PLACEMENT (GENERAL) Reemployment Priority List (RPL) § 330.207 Registration area. (a) Except... commuting area in which the eligible was, or will be, separated. (b) If the agency has, or will have,...

  1. 77 FR 16544 - Pesticide Product Registration Approvals

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-21

    ... of receipt published on April 14, 2010 (75 FR 19388; FRL- 8808-5). One comment was received during... AGENCY Pesticide Product Registration Approvals AGENCY: Environmental Protection Agency (EPA). ACTION... pesticide products and amended registrations for currently existing pesticide products. FOR...

  2. 9 CFR 2.30 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... and filing a properly executed form which will be furnished, upon request, by the AC Regional Director. The registration form shall be filed with the AC Regional Director for the State in which the research... filing of a new registration form which will be provided by the AC Regional Director. Except as...

  3. 19 CFR 360.102 - Online registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Online registration. 360.102 Section 360.102... ANALYSIS SYSTEM § 360.102 Online registration. (a) In general. (1) Any importer, importing company, customs.... boxes will not be accepted. A user identification number will be issued within two business...

  4. 78 FR 48667 - Revised Company Registration System

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-09

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF ENERGY Federal Energy Regulatory Commission Revised Company Registration System AGENCY: Federal Energy Regulatory... Registration System. The Commission issued a previous notice in the Federal Register, 78 FR 44559 (July...

  5. 31 CFR 316.4 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....4 Registration. Series E bonds were permitted to be registered as set forth in subpart B of 31 CFR... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false Registration. 316.4 Section 316.4 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) FISCAL...

  6. 40 CFR 80.1650 - Registration.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... the first date that such person will blend oxygenate into RBOB, whichever is earlier. (4) Any ethanol... advance of the first date that such person will produce or import ethanol denaturant, whichever is earlier... inaccurate. (h) Certified ethanol denaturant producer registration. (1) Registration shall be on forms...

  7. 18 CFR 390.1 - Electronic registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    .... 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 who... Commission's web site, in compliance with instructions located on the Web site, at...

  8. 18 CFR 390.1 - Electronic registration.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    .... 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 who... Commission's web site, in compliance with instructions located on the Web site, at...

  9. 18 CFR 390.1 - Electronic registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    .... 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 who... Commission's web site, in compliance with instructions located on the Web site, at...

  10. 76 FR 42684 - Statutory Invention Registration

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-19

    ... Patent and Trademark Office Statutory Invention Registration ACTION: Proposed collection; comment request... drawings be published as a statutory invention registration (SIR). A published SIR is not a patent. It has... obtaining patents on the inventions claimed in the applications. However, given that 37 CFR 1.211...

  11. 32 CFR 636.9 - Registration requirement.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 32 National Defense 4 2013-07-01 2013-07-01 false Registration requirement. 636.9 Section 636.9 National Defense Department of Defense (Continued) DEPARTMENT OF THE ARMY (CONTINUED) LAW ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION (SPECIFIC INSTALLATIONS) Fort Stewart, Georgia § 636.9 Registration requirement....

  12. 7 CFR 915.120 - Handler registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE AVOCADOS GROWN IN SOUTH FLORIDA Rules and Regulations § 915.120 Handler registration. (a) Each handler who desires to handle avocados... shall be by application for registration filed with the Avocado Administrative Committee on a...

  13. 9 CFR 2.30 - Registration.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 9 Animals and Animal Products 1 2014-01-01 2014-01-01 false Registration. 2.30 Section 2.30 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE ANIMAL WELFARE REGULATIONS Research Facilities § 2.30 Registration. (a) Requirements and procedures. (1)...

  14. 9 CFR 2.30 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Registration. 2.30 Section 2.30 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE ANIMAL WELFARE REGULATIONS Research Facilities § 2.30 Registration. (a) Requirements and procedures. (1)...

  15. 15 CFR 295.24 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Registration. 295.24 Section 295.24 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade NATIONAL INSTITUTE OF... Assistance to United States Industry-Led Joint Research and Development Ventures § 295.24 Registration....

  16. 19 CFR 360.102 - Online registration.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 19 Customs Duties 3 2012-04-01 2012-04-01 false Online registration. 360.102 Section 360.102 Customs Duties INTERNATIONAL TRADE ADMINISTRATION, DEPARTMENT OF COMMERCE STEEL IMPORT MONITORING AND ANALYSIS SYSTEM § 360.102 Online registration. (a) In general. (1) Any importer, importing company,...

  17. 19 CFR 360.102 - Online registration.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 19 Customs Duties 3 2013-04-01 2013-04-01 false Online registration. 360.102 Section 360.102 Customs Duties INTERNATIONAL TRADE ADMINISTRATION, DEPARTMENT OF COMMERCE STEEL IMPORT MONITORING AND ANALYSIS SYSTEM § 360.102 Online registration. (a) In general. (1) Any importer, importing company,...

  18. 19 CFR 360.102 - Online registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 19 Customs Duties 3 2011-04-01 2011-04-01 false Online registration. 360.102 Section 360.102 Customs Duties INTERNATIONAL TRADE ADMINISTRATION, DEPARTMENT OF COMMERCE STEEL IMPORT MONITORING AND ANALYSIS SYSTEM § 360.102 Online registration. (a) In general. (1) Any importer, importing company,...

  19. 19 CFR 360.102 - Online registration.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 19 Customs Duties 3 2014-04-01 2014-04-01 false Online registration. 360.102 Section 360.102 Customs Duties INTERNATIONAL TRADE ADMINISTRATION, DEPARTMENT OF COMMERCE STEEL IMPORT MONITORING AND ANALYSIS SYSTEM § 360.102 Online registration. (a) In general. (1) Any importer, importing company,...

  20. Shape-constrained multi-atlas based segmentation with multichannel registration

    NASA Astrophysics Data System (ADS)

    Hao, Yongfu; Jiang, Tianzi; Fan, Yong

    2012-02-01

    Multi-atlas based segmentation methods have recently attracted much attention in medical image segmentation. The multi-atlas based segmentation methods typically consist of three steps, including image registration, label propagation, and label fusion. Most of the recent studies devote to improving the label fusion step and adopt a typical image registration method for registering atlases to the target image. However, the existing registration methods may become unstable when poor image quality or high anatomical variance between registered image pairs involved. In this paper, we propose an iterative image segmentation and registration procedure to simultaneously improve the registration and segmentation performance in the multi-atlas based segmentation framework. Particularly, a two-channel registration method is adopted with one channel driven by appearance similarity between the atlas image and the target image and the other channel optimized by similarity between atlas label and the segmentation of the target image. The image segmentation is performed by fusing labels of multiple atlases. The validation of our method on hippocampus segmentation of 30 subjects containing MR images with both 1.5T and 3.0T field strength has demonstrated that our method can significantly improve the segmentation performance with different fusion strategies and obtain segmentation results with Dice overlap of 0.892+/-0.024 for 1.5T images and 0.902+/-0.022 for 3.0T images to manual segmentations.

  1. Image Registration for Stability Testing of MEMS

    NASA Technical Reports Server (NTRS)

    Memarsadeghi, Nargess; LeMoigne, Jacqueline; Blake, Peter N.; Morey, Peter A.; Landsman, Wayne B.; Chambers, Victor J.; Moseley, Samuel H.

    2011-01-01

    Image registration, or alignment of two or more images covering the same scenes or objects, is of great interest in many disciplines such as remote sensing, medical imaging. astronomy, and computer vision. In this paper, we introduce a new application of image registration algorithms. We demonstrate how through a wavelet based image registration algorithm, engineers can evaluate stability of Micro-Electro-Mechanical Systems (MEMS). In particular, we applied image registration algorithms to assess alignment stability of the MicroShutters Subsystem (MSS) of the Near Infrared Spectrograph (NIRSpec) instrument of the James Webb Space Telescope (JWST). This work introduces a new methodology for evaluating stability of MEMS devices to engineers as well as a new application of image registration algorithms to computer scientists.

  2. Adaptive registration of diffusion tensor images on lie groups

    NASA Astrophysics Data System (ADS)

    Liu, Wei; Chen, LeiTing; Cai, HongBin; Qiu, Hang; Fei, Nanxi

    2016-08-01

    With diffusion tensor imaging (DTI), more exquisite information on tissue microstructure is provided for medical image processing. In this paper, we present a locally adaptive topology preserving method for DTI registration on Lie groups. The method aims to obtain more plausible diffeomorphisms for spatial transformations via accurate approximation for the local tangent space on the Lie group manifold. In order to capture an exact geometric structure of the Lie group, the local linear approximation is efficiently optimized by using the adaptive selection of the local neighborhood sizes on the given set of data points. Furthermore, numerical comparative experiments are conducted on both synthetic data and real DTI data to demonstrate that the proposed method yields a higher degree of topology preservation on a dense deformation tensor field while improving the registration accuracy.

  3. Effect of geometrical distortion correction in MR on image registration accuracy

    NASA Astrophysics Data System (ADS)

    Maurer, Calvin R., Jr.; Aboutanos, Georges B.; Dawant, Benoit M.; Gadamsetty, Srikanth; Margolin, Richard A.; Maciunas, Robert J.; Fitzpatrick, J. Michael

    1994-05-01

    In this paper we investigate the effect of geometrical distortion correction in magnetic resonance (MR) images on the accuracy of the registration of x-ray computed tomography (CT) and MR head images for a fiducial marker (extrinsic point) method and a surface matching technique. We used CT and T2-weighted MR volume images acquired from seven patients who underwent craniotomies in a stereotactic neurosurgical clinical trial. Each patient had four external markers attached to transcutaneous post screwed into the outer table of the skull. We define registration error as the distance between corresponding marker positions after registration and transformation. The accuracy of the fiducial marker method was determined by using each combination of three markers to estimate the transformation and the remaining marker to calculate registration error. Surface-based registration was accomplished by fitting MR contours corresponding to the CSF-dura interface to CT contours derived from the inner surface of the skull. Correction of geometrical distortion in MR images significantly reduced the registration error of both point-based and surface-based registration.

  4. Tuning of a deformable image registration procedure for skin component mechanical properties assessment.

    PubMed

    Montin, E; Cutri, E; Spadola, G; Testori, A; Pennati, G; Mainardi, L

    2015-01-01

    Several studies report the mechanical properties of skin tissues but their values largely depend on the measurement method. Therefore, we investigated the feasibility of recognizing the cellular constituents mechanical properties of pigmented skin by Confocal Laser Scanner Microscopy (CLSM). With this purpose, an healthy volunteer was examined in three areas nearby a pigmented skin lesion in two configurations: deforming and non deforming the nevus. The tissue displacement of the nevus was then assessed by means of deformable registration of the images in these two configurations. There are several registration strategy able to overcome this task, among them, we proposed two methods with different deformation models: a Free Form Deformation (FFD) model based on b-spline and a second one based on Demons Registration Algorithm (DRA). These two strategies need the definition of several parameters in order to obtain optimal registration performances. Thus, we tuned these parameters by means of simulated data and evaluated their registration abilities on the real in vivo CLSM acquisitions in the two configurations. The results showed that the registration using DRA had a better performance in comparison to the FFD one, in particular in two out of the three areas the DRA performance was significantly better than the FFD one. The registration procedure highlighted deformation differences among the chosen areas. PMID:26737734

  5. Unsupervised Deep Feature Learning for Deformable Registration of MR Brain Images

    PubMed Central

    Wu, Guorong; Kim, Minjeong; Wang, Qian; Gao, Yaozong; Liao, Shu; Shen, Dinggang

    2014-01-01

    Establishing accurate anatomical correspondences is critical for medical image registration. Although many hand-engineered features have been proposed for correspondence detection in various registration applications, no features are general enough to work well for all image data. Although many learning-based methods have been developed to help selection of best features for guiding correspondence detection across subjects with large anatomical variations, they are often limited by requiring the known correspondences (often presumably estimated by certain registration methods) as the ground truth for training. To address this limitation, we propose using an unsupervised deep learning approach to directly learn the basis filters that can effectively represent all observed image patches. Then, the coefficients by these learnt basis filters in representing the particular image patch can be regarded as the morphological signature for correspondence detection during image registration. Specifically, a stacked two-layer convolutional network is constructed to seek for the hierarchical representations for each image patch, where the high-level features are inferred from the responses of the low-level network. By replacing the hand-engineered features with our learnt data-adaptive features for image registration, we achieve promising registration results, which demonstrates that a general approach can be built to improve image registration by using data-adaptive features through unsupervised deep learning. PMID:24579196

  6. Unsupervised deep feature learning for deformable registration of MR brain images.

    PubMed

    Wu, Guorong; Kim, Minjeong; Wang, Qian; Gao, Yaozong; Liao, Shu; Shen, Dinggang

    2013-01-01

    Establishing accurate anatomical correspondences is critical for medical image registration. Although many hand-engineered features have been proposed for correspondence detection in various registration applications, no features are general enough to work well for all image data. Although many learning-based methods have been developed to help selection of best features for guiding correspondence detection across subjects with large anatomical variations, they are often limited by requiring the known correspondences (often presumably estimated by certain registration methods) as the ground truth for training. To address this limitation, we propose using an unsupervised deep learning approach to directly learn the basis filters that can effectively represent all observed image patches. Then, the coefficients by these learnt basis filters in representing the particular image patch can be regarded as the morphological signature for correspondence detection during image registration. Specifically, a stacked two-layer convolutional network is constructed to seek for the hierarchical representations for each image patch, where the high-level features are inferred from the responses of the low-level network. By replacing the hand-engineered features with our learnt data-adaptive features for image registration, we achieve promising registration results, which demonstrates that a general approach can be built to improve image registration by using data-adaptive features through unsupervised deep learning. PMID:24579196

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

    SciTech Connect

    Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali; and others

    2011-04-15

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

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

    PubMed Central

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

    2016-01-01

    A crucial issue in deformable image registration is achieving a robust registration algorithm at a reasonable computational cost. Given the iterative nature of the optimization procedure an algorithm must automatically detect convergence, and stop the iterative process when most appropriate. This paper ranks the performances of three stopping criteria and six stopping value computation strategies for a Log-Domain Demons Deformable registration method simulating both a coarse and a fine registration. The analyzed stopping criteria are: (a) velocity field update magnitude, (b) mean squared error, and (c) harmonic energy. Each stopping condition is formulated so that the user defines a threshold ε, which quantifies the residual error that is acceptable for the particular problem and calculation strategy. In this work, we did not aim at assigning a value to ε, but to give insights in how to evaluate and to set the threshold on a given exit strategy in a very popular registration scheme. Experiments on phantom and patient data demonstrate that comparing the optimization metric minimum over the most recent three iterations with the minimum over the fourth to sixth most recent iterations can be an appropriate algorithm stopping strategy. The harmonic energy was found to provide best trade-off between robustness and speed of convergence for the analyzed registration method at coarse registration, but was outperformed by mean squared error when all the original pixel information is used. This suggests the need of developing mathematically sound new convergence criteria in which both image and vector field information could be used to detect the actual convergence, which could be especially useful when considering multi-resolution registrations. Further work should be also dedicated to study same strategies performances in other deformable registration methods and body districts. PMID:24000996

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

    PubMed

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

    2016-02-01

    A crucial issue in deformable image registration is achieving a robust registration algorithm at a reasonable computational cost. Given the iterative nature of the optimization procedure an algorithm must automatically detect convergence, and stop the iterative process when most appropriate. This paper ranks the performances of three stopping criteria and six stopping value computation strategies for a Log-Domain Demons Deformable registration method simulating both a coarse and a fine registration. The analyzed stopping criteria are: (a) velocity field update magnitude, (b) mean squared error, and (c) harmonic energy. Each stoping condition is formulated so that the user defines a threshold ∊, which quantifies the residual error that is acceptable for the particular problem and calculation strategy. In this work, we did not aim at assigning a value to e, but to give insights in how to evaluate and to set the threshold on a given exit strategy in a very popular registration scheme. Experiments on phantom and patient data demonstrate that comparing the optimization metric minimum over the most recent three iterations with the minimum over the fourth to sixth most recent iterations can be an appropriate algorithm stopping strategy. The harmonic energy was found to provide best trade-off between robustness and speed of convergence for the analyzed registration method at coarse registration, but was outperformed by mean squared error when all the original pixel information is used. This suggests the need of developing mathematically sound new convergence criteria in which both image and vector field information could be used to detect the actual convergence, which could be especially useful when considering multi-resolution registrations. Further work should be also dedicated to study same strategies performances in other deformable registration methods and body districts. PMID:24000996

  10. Automatic Mrf-Based Registration of High Resolution Satellite Video Data

    NASA Astrophysics Data System (ADS)

    Platias, C.; Vakalopoulou, M.; Karantzalos, K.

    2016-06-01

    In this paper we propose a deformable registration framework for high resolution satellite video data able to automatically and accurately co-register satellite video frames and/or register them to a reference map/image. The proposed approach performs non-rigid registration, formulates a Markov Random Fields (MRF) model, while efficient linear programming is employed for reaching the lowest potential of the cost function. The developed approach has been applied and validated on satellite video sequences from Skybox Imaging and compared with a rigid, descriptor-based registration method. Regarding the computational performance, both the MRF-based and the descriptor-based methods were quite efficient, with the first one converging in some minutes and the second in some seconds. Regarding the registration accuracy the proposed MRF-based method significantly outperformed the descriptor-based one in all the performing experiments.

  11. Sequential and Automatic Image-Sequence Registration of Road Areas Monitored from a Hovering Helicopter

    PubMed Central

    Nejadasl, Fatemeh Karimi.; Lindenbergh, Roderik.

    2014-01-01

    In this paper, we propose an automatic and sequential method for the registration of an image sequence of a road area without ignoring scene-induced motion. This method contributes to a larger work, aiming at vehicle tracking. A typical image sequence is recorded from a helicopter hovering above the freeway. The demand for automation is inevitable due to the large number of images and continuous changes in the traffic situation and weather conditions. A framework is designed and implemented for this purpose. The registration errors are removed in a sequential way based on two homography assumptions. First, an approximate registration is obtained, which is efficiently refined in a second step, using a restricted search area. The results of the stabilization framework are demonstrated on an image sequence consisting of 1500 images and show that our method allows a registration between arbitrary images in the sequence with a geometric error of zero in pixel accuracy. PMID:25198006

  12. A Markov Random Field Groupwise Registration Framework for Face Recognition.

    PubMed

    Liao, Shu; Shen, Dinggang; Chung, Albert C S

    2014-04-01

    In this paper, we propose a new framework for tackling face recognition problem. The face recognition problem is formulated as groupwise deformable image registration and feature matching problem. The main contributions of the proposed method lie in the following aspects: (1) Each pixel in a facial image is represented by an anatomical signature obtained from its corresponding most salient scale local region determined by the survival exponential entropy (SEE) information theoretic measure. (2) Based on the anatomical signature calculated from each pixel, a novel Markov random field based groupwise registration framework is proposed to formulate the face recognition problem as a feature guided deformable image registration problem. The similarity between different facial images are measured on the nonlinear Riemannian manifold based on the deformable transformations. (3) The proposed method does not suffer from the generalizability problem which exists commonly in learning based algorithms. The proposed method has been extensively evaluated on four publicly available databases: FERET, CAS-PEAL-R1, FRGC ver 2.0, and the LFW. It is also compared with several state-of-the-art face recognition approaches, and experimental results demonstrate that the proposed method consistently achieves the highest recognition rates among all the methods under comparison.

  13. A Markov Random Field Groupwise Registration Framework for Face Recognition

    PubMed Central

    Liao, Shu; Shen, Dinggang; Chung, Albert C.S.

    2014-01-01

    In this paper, we propose a new framework for tackling face recognition problem. The face recognition problem is formulated as groupwise deformable image registration and feature matching problem. The main contributions of the proposed method lie in the following aspects: (1) Each pixel in a facial image is represented by an anatomical signature obtained from its corresponding most salient scale local region determined by the survival exponential entropy (SEE) information theoretic measure. (2) Based on the anatomical signature calculated from each pixel, a novel Markov random field based groupwise registration framework is proposed to formulate the face recognition problem as a feature guided deformable image registration problem. The similarity between different facial images are measured on the nonlinear Riemannian manifold based on the deformable transformations. (3) The proposed method does not suffer from the generalizability problem which exists commonly in learning based algorithms. The proposed method has been extensively evaluated on four publicly available databases: FERET, CAS-PEAL-R1, FRGC ver 2.0, and the LFW. It is also compared with several state-of-the-art face recognition approaches, and experimental results demonstrate that the proposed method consistently achieves the highest recognition rates among all the methods under comparison. PMID:25506109

  14. A knowledge-driven quasi-global registration of thoracic-abdominal CT and CBCT for image-guided interventions

    NASA Astrophysics Data System (ADS)

    Zhang, Li; Chefd'hotel, Christophe; Ordy, Vincent; Zheng, Jie; Deng, Xiang; Odry, Benjamin

    2013-03-01

    In this work, we have developed a novel knowledge-driven quasi-global method for fast and robust registration of thoracic-abdominal CT and cone beam CT (CBCT) scans. While the use of CBCT in operating rooms has become a common practice, there is an increasing demand on the registration of CBCT with pre-operative scans, in many cases, CT scans. One of the major challenges of thoracic-abdominal CT/CBCT registration is from various fields of view (FOVs) of the two imaging modalities. The proposed approach utilizes a priori knowledge of anatomy to generate 2D anatomy targeted projection (ATP) images that surrogate the original volumes. The use of lower dimension surrogate images can significantly reduce the computation cost of similarity evaluation during optimization and make it practically feasible to perform global optimization based registration for image-guided interventional procedures. Another a priori knowledge about the local optima distribution on energy curves is further used to effectively select multi-starting points for registration optimization. 20 clinical data sets were used to validate the method and the target registration error (TRE) and maximum registration error (MRE) were calculated to compare the performance of the knowledge-driven quasi-global registration against a typical local-search based registration. The local search based registration failed on 60% cases, with an average TRE of 22.9mm and MRE of 28.1mm; the knowledge-driven quasi-global registration achieved satisfactory results for all the 20 data sets, with an average TRE of 3.5mm, and MRE of 2.6mm. The average computation time for the knowledge-driven quasi-global registration is 8.7 seconds.

  15. Pair-wise automatic registration of three-dimensional laser scanning data from historical building by created two-dimensional images

    NASA Astrophysics Data System (ADS)

    Altuntas, Cihan

    2014-05-01

    Registration of a point cloud is a great challenge in the process of laser scanning data. So far, many registration methods have been introduced by range data, integrated camera image, and a combination of them. Moreover, the automatic registration of three-dimensional point clouds is an important research topic in both geomatics and computer sciences. In this study, keypoint-based registration of point clouds was introduced. Intensity images were created from the laser scanning data, and then a pair-wise automatic registration was performed with the keypoints extracted from the intensity images by a scale invariant feature transform (SIFT) and affine SIFT (ASIFT). The results were compared with the iterative closest point, which has high accuracy and is the extensively adopted method for the pair-wise registration. Consequently, SIFT and ASIFT keypoints which were extracted from intensity images can be exploited to pair-wise automatic registration of the point clouds.

  16. Automated Image Registration Using Morphological Region of Interest Feature Extraction

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2005-01-01

    With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

  17. Localization of brachytherapy seeds in ultrasound by registration to fluoroscopy

    NASA Astrophysics Data System (ADS)

    Fallavollita, P.; KarimAghaloo, Z.; Burdette, E. C.; Song, D. Y.; Abolmaesumi, P.; Fichtinger, G.

    2010-02-01

    Motivation: In prostate brachytherapy, transrectal ultrasound (TRUS) is used to visualize the anatomy, while implanted seeds can be seen in C-arm fluoroscopy or CT. Intra-operative dosimetry optimization requires localization of the implants in TRUS relative to the anatomy. This could be achieved by registration of TRUS images and the implants reconstructed from fluoroscopy or CT. Methods: TRUS images are filtered, compounded, and registered on the reconstructed implants by using an intensity-based metric based on a 3D point-to-volume registration scheme. A phantom was implanted with 48 seeds, imaged with TRUS and CT/X-ray. Ground-truth registration was established between the two. Seeds were reconstructed from CT/X-ray. Seven TRUS filtering techniques and two image similarity metrics were analyzed as well. Results: For point-to-volume registration, noise reduction combined with beam profile filter and mean squares metrics yielded the best result: an average of 0.38 +/- 0.19 mm seed localization error relative to the ground-truth. In human patient data C-arm fluoroscopy images showed 81 radioactive seeds implanted inside the prostate. A qualitative analysis showed clinically correct agreement between the seeds visible in TRUS and reconstructed from intra-operative fluoroscopy imaging. The measured registration error compared to the manually selected seed locations by the clinician was 2.86 +/- 1.26 mm. Conclusion: Fully automated seed localization in TRUS performed excellently on ground-truth phantom, adequate in clinical data and was time efficient having an average runtime of 90 seconds.

  18. Auxiliary anatomical labels for joint segmentation and atlas registration

    NASA Astrophysics Data System (ADS)

    Gass, Tobias; Szekely, Gabor; Goksel, Orcun

    2014-03-01

    This paper studies improving joint segmentation and registration by introducing auxiliary labels for anatomy that has similar appearance to the target anatomy while not being part of that target. Such auxiliary labels help avoid false positive labelling of non-target anatomy by resolving ambiguity. A known registration of a segmented atlas can help identify where a target segmentation should lie. Conversely, segmentations of anatomy in two images can help them be better registered. Joint segmentation and registration is then a method that can leverage information from both registration and segmentation to help one another. It has received increasing attention recently in the literature. Often, merely a single organ of interest is labelled in the atlas. In the presense of other anatomical structures with similar appearance, this leads to ambiguity in intensity based segmentation; for example, when segmenting individual bones in CT images where other bones share the same intensity profile. To alleviate this problem, we introduce automatic generation of additional labels in atlas segmentations, by marking similar-appearance non-target anatomy with an auxiliary label. Information from the auxiliary-labeled atlas segmentation is then incorporated by using a novel coherence potential, which penalizes differences between the deformed atlas segmentation and the target segmentation estimate. We validated this on a joint segmentation-registration approach that iteratively alternates between registering an atlas and segmenting the target image to find a final anatomical segmentation. The results show that automatic auxiliary labelling outperforms the same approach using a single label atlasses, for both mandibular bone segmentation in 3D-CT and corpus callosum segmentation in 2D-MRI.

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

    PubMed Central

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

    2016-01-01

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

  20. Efficient least squares multimodal registration with a globally exhaustive alignment search.

    PubMed

    Orchard, Jeff

    2007-10-01

    There are many image registration situations in which the initial misalignment of the two images is large. These registration problems, often involving comparison of the two images only within a region of interest (ROI), are difficult to solve. Most intensity-based registration methods perform local optimization of their cost function and often miss the global optimum when the initial misregistration is large. The registration of multimodal images makes the problem even more difficult since it limits the choice of available cost functions. We have developed an efficient method, capable of multimodal rigid-body registration within an ROI, that performs an exhaustive search over all integer translations, and a local search over rotations. The method uses the fast Fourier transform to efficiently compute the sum of squared differences cost function for all possible integer pixel shifts, and for each shift models the relationship between the intensities of the two images using linear regression. Test cases involving medical imaging, remote sensing and forensic science applications show that the method consistently brings the two images into close registration so that a local optimization method should have no trouble fine-tuning the solution.

  1. Development and evaluation of an articulated registration algorithm for human skeleton registration

    NASA Astrophysics Data System (ADS)

    Yip, Stephen; Perk, Timothy; Jeraj, Robert

    2014-03-01

    Accurate registration over multiple scans is necessary to assess treatment response of bone diseases (e.g. metastatic bone lesions). This study aimed to develop and evaluate an articulated registration algorithm for the whole-body skeleton registration in human patients. In articulated registration, whole-body skeletons are registered by auto-segmenting into individual bones using atlas-based segmentation, and then rigidly aligning them. Sixteen patients (weight = 80-117 kg, height = 168-191 cm) with advanced prostate cancer underwent the pre- and mid-treatment PET/CT scans over a course of cancer therapy. Skeletons were extracted from the CT images by thresholding (HU>150). Skeletons were registered using the articulated, rigid, and deformable registration algorithms to account for position and postural variability between scans. The inter-observers agreement in the atlas creation, the agreement between the manually and atlas-based segmented bones, and the registration performances of all three registration algorithms were all assessed using the Dice similarity index—DSIobserved, DSIatlas, and DSIregister. Hausdorff distance (dHausdorff) of the registered skeletons was also used for registration evaluation. Nearly negligible inter-observers variability was found in the bone atlases creation as the DSIobserver was 96 ± 2%. Atlas-based and manual segmented bones were in excellent agreement with DSIatlas of 90 ± 3%. Articulated (DSIregsiter = 75 ± 2%, dHausdorff = 0.37 ± 0.08 cm) and deformable registration algorithms (DSIregister = 77 ± 3%, dHausdorff = 0.34 ± 0.08 cm) considerably outperformed the rigid registration algorithm (DSIregsiter = 59 ± 9%, dHausdorff = 0.69 ± 0.20 cm) in the skeleton registration as the rigid registration algorithm failed to capture the skeleton flexibility in the joints. Despite superior skeleton registration performance, deformable registration algorithm failed to preserve the local rigidity of bones as over 60% of the

  2. Development and evaluation of an articulated registration algorithm for human skeleton registration.

    PubMed

    Yip, Stephen; Perk, Timothy; Jeraj, Robert

    2014-03-21

    Accurate registration over multiple scans is necessary to assess treatment response of bone diseases (e.g. metastatic bone lesions). This study aimed to develop and evaluate an articulated registration algorithm for the whole-body skeleton registration in human patients. In articulated registration, whole-body skeletons are registered by auto-segmenting into individual bones using atlas-based segmentation, and then rigidly aligning them. Sixteen patients (weight = 80-117 kg, height = 168-191 cm) with advanced prostate cancer underwent the pre- and mid-treatment PET/CT scans over a course of cancer therapy. Skeletons were extracted from the CT images by thresholding (HU>150). Skeletons were registered using the articulated, rigid, and deformable registration algorithms to account for position and postural variability between scans. The inter-observers agreement in the atlas creation, the agreement between the manually and atlas-based segmented bones, and the registration performances of all three registration algorithms were all assessed using the Dice similarity index-DSIobserved, DSIatlas, and DSIregister. Hausdorff distance (dHausdorff) of the registered skeletons was also used for registration evaluation. Nearly negligible inter-observers variability was found in the bone atlases creation as the DSIobserver was 96 ± 2%. Atlas-based and manual segmented bones were in excellent agreement with DSIatlas of 90 ± 3%. Articulated (DSIregsiter = 75 ± 2%, dHausdorff = 0.37 ± 0.08 cm) and deformable registration algorithms (DSIregister = 77 ± 3%, dHausdorff = 0.34 ± 0.08 cm) considerably outperformed the rigid registration algorithm (DSIregsiter = 59 ± 9%, dHausdorff = 0.69 ± 0.20 cm) in the skeleton registration as the rigid registration algorithm failed to capture the skeleton flexibility in the joints. Despite superior skeleton registration performance, deformable registration algorithm failed to preserve the local rigidity of bones as over 60% of the skeletons

  3. Automatic registration between reference and on-board digital tomosynthesis images for positioning verification

    SciTech Connect

    Ren Lei; Godfrey, Devon J.; Yan, Hui; Wu, Q. Jackie; Yin, Fang-Fang

    2008-02-15

    The authors developed a hybrid multiresolution rigid-body registration technique to automatically register reference digital tomosynthesis (DTS) images with on-board DTS images to guide patient positioning in radiation therapy. This hybrid registration technique uses a faster but less accurate static method to achieve an initial registration, followed by a slower but more accurate adaptive method to fine tune the registration. A multiresolution scheme is employed in the registration to further improve the registration accuracy, robustness, and efficiency. Normalized mutual information is selected as the criterion for the similarity measure and the downhill simplex method is used as the search engine. This technique was tested using image data both from an anthropomorphic chest phantom and from eight head-and-neck cancer patients. The effects of the scan angle and the region-of-interest (ROI) size on the registration accuracy and robustness were investigated. The necessity of using the adaptive registration method in the hybrid technique was validated by comparing the results of the static method and the hybrid method. With a 44 deg. scan angle and a large ROI covering the entire DTS volume, the average of the registration capture ranges in single-axis simulations was between -31 and +34 deg. for rotations and between -89 and +78 mm for translations in the phantom study, and between -38 and +38 deg. for rotations and between -58 and +65 mm for translations in the patient study. Decreasing the DTS scan angle from 44 deg. to 22 deg. mainly degraded the registration accuracy and robustness for the out-of-plane rotations. Decreasing the ROI size from the entire DTS volume to the volume surrounding the spinal cord reduced the capture ranges to between -23 and +18 deg. for rotations and between -33 and +43 mm for translations in the phantom study, and between -18 and +25 deg. for rotations and between -35 and +39 mm for translations in the patient study. Results also

  4. The use of ink jets in ultrasound registrations.

    PubMed

    Johansson, T; Nilsson, J; Almquist, L O; Holmer, N G

    1991-01-01

    The continuous ink jet method developed by Professor Hellmuth Hertz, Lund Institute of Technology, Sweden, is today used in printers that print digitally stored high-quality images rapidly and at low cost. The development started in the late 1950s when there was a need for a direct registration method for ultrasound echocardiograms. The development steps are described from the early ultrasound registrations to the true halftone printing of digital images today. Images from ultrasonic color Doppler examinations have been printed by an ink jet printer at our laboratory. The color capabilities of the printer are further illustrated by the printing of pseudo-colored gray-scale images and an image where color is used to highlight differences between two gray-scale images. The results show that the printer based on continuous ink jets is an interesting alternative to the existing hard-copy devices for medical images.

  5. Masked object registration in the Fourier domain.

    PubMed

    Padfield, Dirk

    2012-05-01

    Registration is one of the most common tasks of image analysis and computer vision applications. The requirements of most registration algorithms include large capture range and fast computation so that the algorithms are robust to different scenarios and can be computed in a reasonable amount of time. For these purposes, registration in the Fourier domain using normalized cross-correlation is well suited and has been extensively studied in the literature. Another common requirement is masking, which is necessary for applications where certain regions of the image that would adversely affect the registration result should be ignored. To address these requirements, we have derived a mathematical model that describes an exact form for embedding the masking step fully into the Fourier domain so that all steps of translation registration can be computed efficiently using Fast Fourier Transforms. We provide algorithms and implementation details that demonstrate the correctness of our derivations. We also demonstrate how this masked FFT registration approach can be applied to improve the Fourier-Mellin algorithm that calculates translation, rotation, and scale in the Fourier domain. We demonstrate the computational efficiency, advantages, and correctness of our algorithm on a number of images from real-world applications. Our framework enables fast, global, parameter-free registration of images with masked regions.

  6. Cellular recurrent deep network for image registration

    NASA Astrophysics Data System (ADS)

    Alam, M.; Vidyaratne, L.; Iftekharuddin, Khan M.

    2015-09-01

    Image registration using Artificial Neural Network (ANN) remains a challenging learning task. Registration can be posed as a two-step problem: parameter estimation and actual alignment/transformation using the estimated parameters. To date ANN based image registration techniques only perform the parameter estimation, while affine equations are used to perform the actual transformation. In this paper, we propose a novel deep ANN based image rigid registration that combines parameter estimation and transformation as a simultaneous learning task. Our previous work shows that a complex universal approximator known as Cellular Simultaneous Recurrent Network (CSRN) can successfully approximate affine transformations with known transformation parameters. This study introduces a deep ANN that combines a feed forward network with a CSRN to perform full rigid registration. Layer wise training is used to pre-train feed forward network for parameter estimation and followed by a CSRN for image transformation respectively. The deep network is then fine-tuned to perform the final registration task. Our result shows that the proposed deep ANN architecture achieves comparable registration accuracy to that of image affine transformation using CSRN with known parameters. We also demonstrate the efficacy of our novel deep architecture by a performance comparison with a deep clustered MLP.

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

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

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

  8. Convex hull matching and hierarchical decomposition for multimodality medical image registration.

    PubMed

    Yang, Jian; Fan, Jingfan; Fu, Tianyu; Ai, Danni; Zhu, Jianjun; Li, Qin; Wang, Yongtian

    2015-01-01

    This study proposes a novel hierarchical pyramid strategy for 3D registration of multimodality medical images. The surfaces of the source and target volume data are first extracted, and the surface point clouds are then aligned roughly using convex hull matching. The convex hull matching registration procedure could align images with large-scale transformations. The original images are divided into blocks and the corresponding blocks in the two images are registered by affine and non-rigid registration procedures. The sub-blocks are iteratively smoothed by the Gaussian kernel with different sizes during the registration procedure. The registration result of the large kernel is taken as the input of the small kernel registration. The fine registration of the two volume data sets is achieved by iteratively increasing the number of blocks, in which increase in similarity measure is taken as a criterion for acceptation of each iteration level. Results demonstrate the effectiveness and robustness of the proposed method in registering the multiple modalities of medical images.

  9. An efficient and robust algorithm for parallel groupwise registration of bone surfaces.

    PubMed

    van de Giessen, Martijn; Vos, Frans M; Grimbergen, Cornelis A; van Vliet, Lucas J; Streekstra, Geert J

    2012-01-01

    In this paper a novel groupwise registration algorithm is proposed for the unbiased registration of a large number of densely sampled point clouds. The method fits an evolving mean shape to each of the example point clouds thereby minimizing the total deformation. The registration algorithm alternates between a computationally expensive, but parallelizable, deformation step of the mean shape to each example shape and a very inexpensive step updating the mean shape. The algorithm is evaluated by comparing it to a state of the art registration algorithm. Bone surfaces of wrists, segmented from CT data with a voxel size of 0.3 x 0.3 x 0.3 mm3, serve as an example test set. The negligible bias and registration error of about 0.12 mm for the proposed algorithm are similar to those in. However, current point cloud registration algorithms usually have computational and memory costs that increase quadratically with the number of point clouds, whereas the proposed algorithm has linearly increasing costs, allowing the registration of a much larger number of shapes: 48 versus 8, on the hardware used.

  10. Deep Adaptive Log-Demons: Diffeomorphic Image Registration with Very Large Deformations.

    PubMed

    Zhao, Liya; Jia, Kebin

    2015-01-01

    This paper proposes a new framework for capturing large and complex deformation in image registration. Traditionally, this challenging problem relies firstly on a preregistration, usually an affine matrix containing rotation, scale, and translation and afterwards on a nonrigid transformation. According to preregistration, the directly calculated affine matrix, which is obtained by limited pixel information, may misregistrate when large biases exist, thus misleading following registration subversively. To address this problem, for two-dimensional (2D) images, the two-layer deep adaptive registration framework proposed in this paper firstly accurately classifies the rotation parameter through multilayer convolutional neural networks (CNNs) and then identifies scale and translation parameters separately. For three-dimensional (3D) images, affine matrix is located through feature correspondences by a triplanar 2D CNNs. Then deformation removal is done iteratively through preregistration and demons registration. By comparison with the state-of-the-art registration framework, our method gains more accurate registration results on both synthetic and real datasets. Besides, principal component analysis (PCA) is combined with correlation like Pearson and Spearman to form new similarity standards in 2D and 3D registration. Experiment results also show faster convergence speed. PMID:26120356

  11. Deep Adaptive Log-Demons: Diffeomorphic Image Registration with Very Large Deformations

    PubMed Central

    Zhao, Liya; Jia, Kebin

    2015-01-01

    This paper proposes a new framework for capturing large and complex deformation in image registration. Traditionally, this challenging problem relies firstly on a preregistration, usually an affine matrix containing rotation, scale, and translation and afterwards on a nonrigid transformation. According to preregistration, the directly calculated affine matrix, which is obtained by limited pixel information, may misregistrate when large biases exist, thus misleading following registration subversively. To address this problem, for two-dimensional (2D) images, the two-layer deep adaptive registration framework proposed in this paper firstly accurately classifies the rotation parameter through multilayer convolutional neural networks (CNNs) and then identifies scale and translation parameters separately. For three-dimensional (3D) images, affine matrix is located through feature correspondences by a triplanar 2D CNNs. Then deformation removal is done iteratively through preregistration and demons registration. By comparison with the state-of-the-art registration framework, our method gains more accurate registration results on both synthetic and real datasets. Besides, principal component analysis (PCA) is combined with correlation like Pearson and Spearman to form new similarity standards in 2D and 3D registration. Experiment results also show faster convergence speed. PMID:26120356

  12. Robust Matching of Wavelet Features for Sub-Pixel Registration of Landsat Data

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; Netanyahu, Nathan S.; Masek, Jeffrey G.; Mount, David M.; Goward, Samuel; Zukor, Dorothy (Technical Monitor)

    2001-01-01

    For many Earth and Space Science applications, automatic geo-registration at sub-pixel accuracy has become a necessity. In this work, we are focusing on building an operational system, which will provide a sub-pixel accuracy registration of Landsat-5 and Landsat-7 data. The input to our registration method consists of scenes that have been geometrically and radiometrically corrected. Such pre-processed scenes are then geo-registered relative to a database of Landsat chips. The method assumes a transformation composed of a rotation and a translation, and utilizes rotation- and translation-invariant wavelets to extract image features that are matched using statistically robust feature matching and a generalized Hausdorff distance metric. The registration process is described and results on four Landsat input scenes of the Washington, D.C. area are presented.

  13. Registration and Analysis of White Matter Group Differences with a Multi-Fiber Model

    PubMed Central

    Taquet, Maxime; Scherrer, Benoît; Commowick, Olivier; Peters, Jurriaan; Sahin, Mustafa; Macq, Benoît; Warfield, Simon K.

    2013-01-01

    Diffusion magnetic resonance imaging has been used extensively to probe the white matter in vivo. Typically, the raw diffusion images are used to reconstruct a diffusion tensor image (DTI). The in-capacity of DTI to represent crossing fibers leaded to the development of more sophisticated diffusion models. Among them, multi-fiber models represent each fiber bundle independently, allowing the direct extraction of diffusion features for population analysis. However, no method exists to properly register multi-fiber models, seriously limiting their use in group comparisons. This paper presents a registration and atlas construction method for multi-fiber models. The validity of the registration is demonstrated on a dataset of 45 subjects, including both healthy and unhealthy subjects. Morphometry analysis and tract-based statistics are then carried out, proving that multi-fiber models registration is better at detecting white matter local differences than single tensor registration. PMID:23286145

  14. A comparative approach of four different image registration techniques for quantitative assessment of coronary artery calcium lesions using intravascular ultrasound.

    PubMed

    Araki, Tadashi; Ikeda, Nobutaka; Dey, Nilanjan; Chakraborty, Sayan; Saba, Luca; Kumar, Dinesh; Godia, Elisa Cuadrado; Jiang, Xiaoyi; Gupta, Ajay; Radeva, Petia; Laird, John R; Nicolaides, Andrew; Suri, Jasjit S

    2015-02-01

    In IVUS imaging, constant linear velocity and a constant angular velocity of 1800 rev/min causes displacement of the calcium in subsequent image frames. To overcome this error in intravascular ultrasound video, IVUS image frames must be registered prior to the lesion quantification. This paper presents a comprehensive comparison of four registration methods, namely: Rigid, Affine, B-Splines and Demons on five set of calcium lesion quantification parameters namely: (i) the mean lesion area, (ii) mean lesion arc, (iii) mean lesion span, (iv) mean lesion length, and (v) mean lesion distance from catheter. Using our IRB approved data of 100 patient volumes, our results shows that all four registrations showed a decrease in five calcium lesion parameters as follows: for Rigid registration, the values were: 4.92%, 5.84%, 5.89%, 5.27%, and 4.57%, respectively, for Affine registration the values were: 6.06%, 6.51%, 7.28%, 6.50%, and 5.94%, respectively, for B-Splines registration the values were: 7.35%, 8.03%, 9.54%, 8.18%, and 7.62%, respectively, and for Demons registration the five parameters were 7.32%, 8.02%, 10.11%, 7.94%, and 8.92% respectively. The relative overlap of identified lesions decreased by 5.91% in case of Rigid registration, 6.23% in case of Affine registration, 4.48% for Demons registration, whereas it increased by 3.05% in case of B-Splines registration. Rigid and Affine transformation-based registration took only 0.1936 and 0.2893 s per frame, respectively. Demons and B-Splines framework took only 0.5705 and 0.9405 s per frame, respectively, which were significantly slower than Rigid and Affine transformation based image registration. PMID:25523233

  15. Registration verification of SEA/AR fields. [Oregon, Texas, Montana, Nebraska, Washington, Colorado, Kansas, Oklahoma, and North Dakota

    NASA Technical Reports Server (NTRS)

    Austin, W. W.; Lautenschlager, L. (Principal Investigator)

    1981-01-01

    A method of field registration verification for 20 SEA/AR sites for the 1979 crop year is evaluated. Field delineations for the sites were entered into the data base, and their registration verified using single channel gray scale computer printout maps of LANDSAT data taken over the site.

  16. Interferometric SAR to EO image registration problem

    NASA Astrophysics Data System (ADS)

    Rogers, George W.; Mansfield, Arthur W.; Rais, Houra

    2000-08-01

    Historically, SAR to EO registration accuracy has been at the multiple pixel level compared to sub-pixel EO to EO registration accuracies. This is due to a variety of factors including the different scattering characteristics of the ground for EO and SAR, SAR speckle, and terrain induced geometric distortion. One approach to improving the SAR to EO registration accuracy is to utilize the full information from multiple SAR surveys using interferometric techniques. In this paper we will examine this problem in detail with an example using ERS SAR imagery. Estimates of the resulting accuracy based on ERS are included.

  17. Quantitative assessment of mis-registration issues of diffusion tensor imaging (DTI)

    NASA Astrophysics Data System (ADS)

    Li, Yue; Jiang, Hangyi; Mori, Susumu

    2012-02-01

    Image distortions caused by eddy current and patient motion have been two major sources of the mis-registration issues in diffusion tensor imaging (DTI). Numerous registration methods have been proposed to correct them. However, quality control of DTI remains an important issue, because we rarely report how much mis-registration existed and how well they were corrected. In this paper, we propose a method for quantitative reporting of DTI data quality. This registration method minimizes a cost function based on mean square tensor fitting errors. Registration with twelve-parameter full affine transformation is used. From the registration result, distortion and motion parameters are estimated. Because the translation parameters involve both eddy-current-induced image translation and the patient motion, by analyzing the transformation model, we separate them by removing the contributions that are linearly correlated with diffusion gradients. We define the metrics measuring the amounts of distortion, rotation, translation. We tested our method on a database with 64 subjects and found the statistics of each of metrics. Finally we demonstrate that how these statistics can be used for assessing the data quality quantitatively in several examples.

  18. Finite Element Surface Registration Incorporating Curvature, Volume Preservation, and Statistical Model Information

    PubMed Central

    Lüthi, Marcel; Vetter, Thomas

    2013-01-01

    We present a novel method for nonrigid registration of 3D surfaces and images. The method can be used to register surfaces by means of their distance images, or to register medical images directly. It is formulated as a minimization problem of a sum of several terms representing the desired properties of a registration result: smoothness, volume preservation, matching of the surface, its curvature, and possible other feature images, as well as consistency with previous registration results of similar objects, represented by a statistical deformation model. While most of these concepts are already known, we present a coherent continuous formulation of these constraints, including the statistical deformation model. This continuous formulation renders the registration method independent of its discretization. The finite element discretization we present is, while independent of the registration functional, the second main contribution of this paper. The local discontinuous Galerkin method has not previously been used in image registration, and it provides an efficient and general framework to discretize each of the terms of our functional. Computational efficiency and modest memory consumption are achieved thanks to parallelization and locally adaptive mesh refinement. This allows for the first time the use of otherwise prohibitively large 3D statistical deformation models. PMID:24187581

  19. Finite element surface registration incorporating curvature, volume preservation, and statistical model information.

    PubMed

    Albrecht, Thomas; Dedner, Andreas; Lüthi, Marcel; Vetter, Thomas

    2013-01-01

    We present a novel method for nonrigid registration of 3D surfaces and images. The method can be used to register surfaces by means of their distance images, or to register medical images directly. It is formulated as a minimization problem of a sum of several terms representing the desired properties of a registration result: smoothness, volume preservation, matching of the surface, its curvature, and possible other feature images, as well as consistency with previous registration results of similar objects, represented by a statistical deformation model. While most of these concepts are already known, we present a coherent continuous formulation of these constraints, including the statistical deformation model. This continuous formulation renders the registration method independent of its discretization. The finite element discretization we present is, while independent of the registration functional, the second main contribution of this paper. The local discontinuous Galerkin method has not previously been used in image registration, and it provides an efficient and general framework to discretize each of the terms of our functional. Computational efficiency and modest memory consumption are achieved thanks to parallelization and locally adaptive mesh refinement. This allows for the first time the use of otherwise prohibitively large 3D statistical deformation models.

  20. Medical image registration using sparse coding of image patches.

    PubMed

    Afzali, Maryam; Ghaffari, Aboozar; Fatemizadeh, Emad; Soltanian-Zadeh, Hamid

    2016-06-01

    Image registration is a basic task in medical image processing applications like group analysis and atlas construction. Similarity measure is a critical ingredient of image registration. Intensity distortion of medical images is not considered in most previous similarity measures. Therefore, in the presence of bias field distortions, they do not generate an acceptable registration. In this paper, we propose a sparse based similarity measure for mono-modal images that consider