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Sample records for non-rigid registration algorithm

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

    Science.gov (United States)

    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.

  2. Non-Rigid Image Registration Algorithm Based on B-Splines Approximation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Hongying; ZHANG Jiawan; SUN Jizhou; SUN Yigang

    2007-01-01

    An intensity-based non-rigid registration algorithm is discussed, which uses Gaussian smoothing to constrain the transformation to be smooth, and thus preserves the topology of images. In view of the insufficiency of the uniform Gaussian filtering of the deformation field, an automatic and accurate non-rigid image registration method based on B-splines approximation is proposed. The regularization strategy is adopted by using multi-level B-splines approximation to regularize the dis-placement fields in a coarse-to-fine manner. Moreover, it assigns the different weights to the estimated displacements according to their reliabilities. In this way, the level of regularity can be adapted locally. Experiments were performed on both synthetic and real medical images of brain, and the results show that the proposed method improves the registration accuracy and robustness.

  3. Infrared image non-rigid registration based on regional information entropy demons algorithm

    Science.gov (United States)

    Lu, Chaoliang; Ma, Lihua; Yu, Ming; Cui, Shumin; Wu, Qingrong

    2015-02-01

    Infrared imaging fault detection which is treated as an ideal, non-contact, non-destructive testing method is applied to the circuit board fault detection. Since Infrared images obtained by handheld infrared camera with wide-angle lens have both rigid and non-rigid deformations. To solve this problem, a new demons algorithm based on regional information entropy was proposed. The new method overcame the shortcomings of traditional demons algorithm that was sensitive to the intensity. First, the information entropy image was gotten by computing regional information entropy of the image. Then, the deformation between the two images was calculated that was the same as demons algorithm. Experimental results demonstrated that the proposed algorithm has better robustness in intensity inconsistent images registration compared with the traditional demons algorithm. Achieving accurate registration between intensity inconsistent infrared images provided strong support for the temperature contrast.

  4. Non-rigid image registration using bone growth model

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten; Gramkow, Claus; Kreiborg, Sven

    1997-01-01

    Non-rigid registration has traditionally used physical models like elasticity and fluids. These models are very seldom valid models of the difference between the registered images. This paper presents a non-rigid registration algorithm, which uses a model of bone growth as a model of the change b...

  5. Research on non rigid registration algorithm of DCE-MRI based on mutual information and optical flow

    Science.gov (United States)

    Yu, Shihua; Wang, Rui; Wang, Kaiyu; Xi, Mengmeng; Zheng, Jiashuo; Liu, Hui

    2015-07-01

    Image matching plays a very important role in the field of medical image, while the two image registration methods based on the mutual information and the optical flow are very effective. The experimental results show that the two methods have their prominent advantages. The method based on mutual information is good for the overall displacement, while the method based on optical flow is very sensitive to small deformation. In the breast DCE-MRI images studied in this paper, there is not only overall deformation caused by the patient, but also non rigid small deformation caused by respiratory deformation. In view of the above situation, the single-image registration algorithms cannot meet the actual needs of complex situations. After a comprehensive analysis to the advantages and disadvantages of these two methods, this paper proposes a registration algorithm of combining mutual information with optical flow field, and applies subtraction images of the reference image and the floating image as the main criterion to evaluate the registration effect, at the same time, applies the mutual information between image sequence values as auxiliary criterion. With the test of the example, this algorithm has obtained a better accuracy and reliability in breast DCE-MRI image sequences.

  6. Robust CPD Algorithm for Non-Rigid Point Set Registration Based on Structure Information.

    Science.gov (United States)

    Peng, Lei; Li, Guangyao; Xiao, Mang; Xie, Li

    2016-01-01

    Recently, the Coherent Point Drift (CPD) algorithm has become a very popular and efficient method for point set registration. However, this method does not take into consideration the neighborhood structure information of points to find the correspondence and requires a manual assignment of the outlier ratio. Therefore, CPD is not robust for large degrees of degradation. In this paper, an improved method is proposed to overcome the two limitations of CPD. A structure descriptor, such as shape context, is used to perform the auxiliary calculation of the correspondence, and the proportion of each GMM component is adjusted by the similarity. The outlier ratio is formulated in the EM framework so that it can be automatically calculated and optimized iteratively. The experimental results on both synthetic data and real data demonstrate that the proposed method described here is more robust to deformation, noise, occlusion, and outliers than CPD and other state-of-the-art algorithms.

  7. Non-rigid registration using higher-order mutual information

    Science.gov (United States)

    Rueckert, D.; Clarkson, M. J.; Hill, D. L. G.; Hawkes, D. J.

    2000-03-01

    Non-rigid registration of multi-modality images is an important tool for assessing temporal and structural changesbetween images. For rigid registration, voxel similarity measures like mutual information have been shown to alignimages from different modalities accurately and robustly. For non-rigid registration, mutual information can besensitive to local variations of intensity which in MR images may be caused by RF inhomogeneity. The reasonfor the sensitivity of mutual information towards intensity variations stems from the fact that mutual informationignores any spatial information. In this paper we propose an extension of the mutual information framework whichincorporates spatial information about higher-order image structure into the registration process and has the potentialto improve the accuracy and robustness of non-rigid registration in the presence of intensity variations. We haveapplied the non-rigid registration algorithm to a number of simulated MR brain images of a digital phantom whichhave been degraded by a simulated intensity shading and a known deformation. In addition, we have applied thealgorithm for the non-rigid registration of eight pre- and post-operative brain MR images which were acquired withan interventional MR scanner and therefore have substantial intensity shading due to RF field inhomogeneities. Inall cases the second-order estimate of mutual information leads to robust and accurate registration.

  8. Optimized imaging using non-rigid registration

    Energy Technology Data Exchange (ETDEWEB)

    Berkels, Benjamin, E-mail: berkels@aices.rwth-aachen.de [Interdisciplinary Mathematics Institute, 1523 Greene Street, University of South Carolina, Columbia, SC 29208 (United States); Binev, Peter, E-mail: binev@math.sc.edu [Interdisciplinary Mathematics Institute, 1523 Greene Street, University of South Carolina, Columbia, SC 29208 (United States); Department of Mathematics, 1523 Greene Street, University of South Carolina, Columbia, SC 29208 (United States); Blom, Douglas A., E-mail: doug.blom@sc.edu [NanoCenter, 1212 Greene Street, University of South Carolina, Columbia, SC 29208 (United States); Dahmen, Wolfgang, E-mail: dahmen@igpm.rwth-aachen.de [Interdisciplinary Mathematics Institute, 1523 Greene Street, University of South Carolina, Columbia, SC 29208 (United States); Institut für Geometrie und Praktische Mathematik, RWTH Aachen, Templergraben 55, 52056 Aachen (Germany); Sharpley, Robert C., E-mail: rcsharpley@gmail.com [Interdisciplinary Mathematics Institute, 1523 Greene Street, University of South Carolina, Columbia, SC 29208 (United States); Department of Mathematics, 1523 Greene Street, University of South Carolina, Columbia, SC 29208 (United States); Vogt, Thomas, E-mail: tvogt@mailbox.sc.edu [Interdisciplinary Mathematics Institute, 1523 Greene Street, University of South Carolina, Columbia, SC 29208 (United States); NanoCenter, 1212 Greene Street, University of South Carolina, Columbia, SC 29208 (United States); Department of Chemistry and Biochemistry, 631 Sumter Street, University of South Carolina, Columbia, SC 29208 (United States)

    2014-03-01

    The extraordinary improvements of modern imaging devices offer access to data with unprecedented information content. However, widely used image processing methodologies fall far short of exploiting the full breadth of information offered by numerous types of scanning probe, optical, and electron microscopies. In many applications, it is necessary to keep measurement intensities below a desired threshold. We propose a methodology for extracting an increased level of information by processing a series of data sets suffering, in particular, from high degree of spatial uncertainty caused by complex multiscale motion during the acquisition process. An important role is played by a non-rigid pixel-wise registration method that can cope with low signal-to-noise ratios. This is accompanied by formulating objective quality measures which replace human intervention and visual inspection in the processing chain. Scanning transmission electron microscopy of siliceous zeolite material exhibits the above-mentioned obstructions and therefore serves as orientation and a test of our procedures. - Highlights: • Developed a new process for extracting more information from a series of STEM images. • An objective non-rigid registration process copes with distortions. • Images of zeolite Y show retrieval of all information available from the data set. • Quantitative measures of registration quality were implemented. • Applicable to any serially acquired data, e.g. STM, AFM, STXM, etc.

  9. 融合SIFT的B样条红外图像非刚性配准%B-spline non-rigid registration algorithm for infrared image based on SIFT

    Institute of Scientific and Technical Information of China (English)

    卢朝梁; 马丽华; 陈豪; 张薇; 于敏; 崔树民

    2014-01-01

    手持式广角镜头红外热像仪所拍摄的不同时刻红外图像具有刚性形变和非刚性形变,传统图像配准算法很难同时矫正刚性形变与非刚性形变,针对该问题,提出一种融合SIFT的B样条配准算法。首先在待配准图像中建立控制网格,其次运用SIFT算法寻找待配准与基准图像间的匹配点对,剔除错误匹配点对并计算出待配准图像与基准图像间的刚性变换参数,接着对控制点进行刚性变换,最后以局部强度和为测度函数,运用B样条非刚性配准算法对广角镜头引起图像的非线性进行矫正。对比实验结果表明,本文算法具有很高配准精度,能够满足实际工程精度要求。%Infrared images obtained by handheld infrared camera with wide-angle lens have rigid and non-rigid deform-ations. Tradition image registration algorithm is difficult to correct the rigid and non-rigid deformations. To solve this problem,B-spline non-rigid registration algorithm based on SIFT is proposed. At first,the control mesh is created in the input image. Then,matching points between input image and template image are found by SIFT algorithm. The rigid transformation parameters are calculated after ignoring the incorrect matching points. Next,the control points are transformed by rigid transformation parameters. Finally,the sum of pattern intensity is used as measurement,and the nonlinear transformation of the image that is caused by wide-angle lens is corrected by B-spline non-rigid registration algorithm. The results of comparison show that the new method has better registration accuracy and it also can meet the requirements of practical engineering accuracy.

  10. Non-rigid registration by geometry-constrained diffusion

    DEFF Research Database (Denmark)

    Andresen, Per Rønsholt; Nielsen, Mads

    2001-01-01

    Assume that only partial knowledge about a non-rigid registration is given: certain points, curves, or surfaces in one 3D image are known to map to certain points, curves, or surfaces in another 3D image. In trying to identify the non-rigid registration field, we face a generalized aperture problem...

  11. Survey of Non-Rigid Registration Tools in Medicine.

    Science.gov (United States)

    Keszei, András P; Berkels, Benjamin; Deserno, Thomas M

    2017-02-01

    We catalogue available software solutions for non-rigid image registration to support scientists in selecting suitable tools for specific medical registration purposes. Registration tools were identified using non-systematic search in Pubmed, Web of Science, IEEE Xplore® Digital Library, Google Scholar, and through references in identified sources (n = 22). Exclusions are due to unavailability or inappropriateness. The remaining (n = 18) tools were classified by (i) access and technology, (ii) interfaces and application, (iii) living community, (iv) supported file formats, and (v) types of registration methodologies emphasizing the similarity measures implemented. Out of the 18 tools, (i) 12 are open source, 8 are released under a permissive free license, which imposes the least restrictions on the use and further development of the tool, 8 provide graphical processing unit (GPU) support; (ii) 7 are built on software platforms, 5 were developed for brain image registration; (iii) 6 are under active development but only 3 have had their last update in 2015 or 2016; (iv) 16 support the Analyze format, while 7 file formats can be read with only one of the tools; and (v) 6 provide multiple registration methods and 6 provide landmark-based registration methods. Based on open source, licensing, GPU support, active community, several file formats, algorithms, and similarity measures, the tools Elastics and Plastimatch are chosen for the platform ITK and without platform requirements, respectively. Researchers in medical image analysis already have a large choice of registration tools freely available. However, the most recently published algorithms may not be included in the tools, yet.

  12. Constrained non-rigid registration for whole body image registration: method and validation

    Science.gov (United States)

    Li, Xia; Yankeelov, Thomas E.; Peterson, Todd E.; Gore, John C.; Dawant, Benoit M.

    2007-03-01

    3D intra- and inter-subject registration of image volumes is important for tasks that include measurements and quantification of temporal/longitudinal changes, atlas-based segmentation, deriving population averages, or voxel and tensor-based morphometry. A number of methods have been proposed to tackle this problem but few of them have focused on the problem of registering whole body image volumes acquired either from humans or small animals. These image volumes typically contain a large number of articulated structures, which makes registration more difficult than the registration of head images, to which the vast majority of registration algorithms have been applied. To solve this problem, we have previously proposed an approach, which initializes an intensity-based non-rigid registration algorithm with a point based registration technique [1, 2]. In this paper, we introduce new constraints into our non-rigid registration algorithm to prevent the bones from being deformed inaccurately. Results we have obtained show that the new constrained algorithm leads to better registration results than the previous one.

  13. Non-rigid registration of medical images based on ordinal feature and manifold learning

    Science.gov (United States)

    Li, Qi; Liu, Jin; Zang, Bo

    2015-12-01

    With the rapid development of medical imaging technology, medical image research and application has become a research hotspot. This paper offers a solution to non-rigid registration of medical images based on ordinal feature (OF) and manifold learning. The structural features of medical images are extracted by combining ordinal features with local linear embedding (LLE) to improve the precision and speed of the registration algorithm. A physical model based on manifold learning and optimization search is constructed according to the complicated characteristics of non-rigid registration. The experimental results demonstrate the robustness and applicability of the proposed registration scheme.

  14. Robust non-rigid point set registration using student's-t mixture model.

    Directory of Open Access Journals (Sweden)

    Zhiyong Zhou

    Full Text Available The Student's-t mixture model, which is heavily tailed and more robust than the Gaussian mixture model, has recently received great attention on image processing. In this paper, we propose a robust non-rigid point set registration algorithm using the Student's-t mixture model. Specifically, first, we consider the alignment of two point sets as a probability density estimation problem and treat one point set as Student's-t mixture model centroids. Then, we fit the Student's-t mixture model centroids to the other point set which is treated as data. Finally, we get the closed-form solutions of registration parameters, leading to a computationally efficient registration algorithm. The proposed algorithm is especially effective for addressing the non-rigid point set registration problem when significant amounts of noise and outliers are present. Moreover, less registration parameters have to be set manually for our algorithm compared to the popular coherent points drift (CPD algorithm. We have compared our algorithm with other state-of-the-art registration algorithms on both 2D and 3D data with noise and outliers, where our non-rigid registration algorithm showed accurate results and outperformed the other algorithms.

  15. SIFT and shape information incorporated into fluid model for non-rigid registration of ultrasound images.

    Science.gov (United States)

    Lu, Xuesong; Zhang, Su; Yang, Wei; Chen, Yazhu

    2010-11-01

    Non-rigid registration of ultrasound images takes an important role in image-guided radiotherapy and surgery. Intensity-based method is popular in non-rigid registration, but it is sensitive to intensity variations and has problems with matching small structure features for the existence of speckles in ultrasound images. In this paper, we develop a new algorithm integrating the intensity and feature of ultrasound images. Both global shape information and local keypoint information extracted by scale invariant feature transform (SIFT) are incorporated into intensity similarity measure as the body force of viscous fluid model in a Bayesian framework. Experiments were performed on synthetic and clinical ultrasound images of breast and kidney. It is shown that shape and keypoint information significantly improves fluid model for non-rigid registration, especially for alignment of small structure features in accuracy.

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

    Science.gov (United States)

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

    2016-10-21

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

    Science.gov (United States)

    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).

  18. Detection and correction of inconsistency-based errors in non-rigid registration

    Science.gov (United States)

    Gass, Tobias; Szekely, Gabor; Goksel, Orcun

    2014-03-01

    In this paper we present a novel post-processing technique to detect and correct inconsistency-based errors in non-rigid registration. While deformable registration is ubiquitous in medical image computing, assessing its quality has yet been an open problem. We propose a method that predicts local registration errors of existing pairwise registrations between a set of images, while simultaneously estimating corrected registrations. In the solution the error is constrained to be small in areas of high post-registration image similarity, while local registrations are constrained to be consistent between direct and indirect registration paths. The latter is a critical property of an ideal registration process, and has been frequently used to asses the performance of registration algorithms. In our work, the consistency is used as a target criterion, for which we efficiently find a solution using a linear least-squares model on a coarse grid of registration control points. We show experimentally that the local errors estimated by our algorithm correlate strongly with true registration errors in experiments with known, dense ground-truth deformations. Additionally, the estimated corrected registrations consistently improve over the initial registrations in terms of average deformation error or TRE for different registration algorithms on both simulated and clinical data, independent of modality (MRI/CT), dimensionality (2D/3D) and employed primary registration method (demons/Markov-randomfield).

  19. Non-Rigid Medical Image Registration with Joint Histogram Estimation Based on Mutual Information

    Institute of Scientific and Technical Information of China (English)

    LU Xuesong; ZHANG Su; SU He; CHEN Yazhu

    2007-01-01

    A mutual information-based non-rigid medical image registration algorithm is presented. An approximate function of Harming windowed sinc is used as kernel function of partial volume (PV)interpolation to estimate the joint histogram, which is the key to calculating the mutual information. And a new method is proposed to compute the gradient of mutual information with respect to themodel parameters. The transformation of object is modeled by a free-form deformation (FFD) based on B-splines. The experiments on 3D synthetic and real image data show that the algorithm can con-verge at the global optimum and restrain the emergency of local extreme.

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

    Science.gov (United States)

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

    2014-11-01

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

  1. Non-rigid registration of 3D point clouds under isometric deformation

    Science.gov (United States)

    Ge, Xuming

    2016-11-01

    An algorithm for pairwise non-rigid registration of 3D point clouds is presented in the specific context of isometric deformations. The critical step is registration of point clouds at different epochs captured from an isometric deformation surface within overlapping regions. Based on characteristics invariant under isometric deformation, a variant of the four-point congruent sets algorithm is applied to generate correspondences between two deformed point clouds, and subsequently a RANSAC framework is used to complete cluster extraction in preparation for global optimal alignment. Examples are presented and the results compared with existing approaches to demonstrate the two main contributions of the technique: a success rate for generating true correspondences of 90% and a root mean square error after final registration of 2-3 mm.

  2. 3D non-rigid registration using surface and local salient features for transrectal ultrasound image-guided prostate biopsy

    Science.gov (United States)

    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.

  3. Mouse whole-body organ mapping by non-rigid registration approach

    Science.gov (United States)

    Xiao, Di; Zahra, David; Bourgeat, Pierrick; Berghofer, Paula; Acosta Tamayo, Oscar; Green, Heather; Gregoire, Marie Claude; Salvado, Olivier

    2011-03-01

    Automatic small animal whole-body organ registration is challenging because of subject's joint structure, posture and position difference and loss of reference features. In this paper, an improved 3D shape context based non-rigid registration method is applied for mouse whole-body skeleton registration and lung registration. A geodesic path based non-rigid registration method is proposed for mouse torso skin registration. Based on the above registration methods, a novel non-rigid registration framework is proposed for mouse whole-body organ mapping from an atlas to new scanned CT data. A preliminary experiment was performed to test the method on lung and skin registration. A whole-body organ mapping was performed on three target data and the selected organs were compared with the manual outlining results. The robust of the method has been demonstrated.

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

    Science.gov (United States)

    Yang, Xuan; Pei, Jihong; Shi, Jingli

    2014-01-01

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

  5. MUTUAL INFORMATION BASED 3D NON-RIGID REGISTRATION OF CT/MR ABDOMEN IMAGES

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A mutual information based 3D non-rigid registration approach was proposed for the registration of deformable CT/MR body abdomen images. The Parzen Windows Density Estimation (PWDE) method is adopted to calculate the mutual information between the two modals of CT and MRI abdomen images. By maximizing MI between the CT and MR volume images, the overlapping part of them reaches the biggest, which means that the two body images of CT and MR matches best to each other. Visible Human Project (VHP) Male abdomen CT and MRI Data are used as experimental data sets. The experimental results indicate that this approach of non-rigid 3D registration of CT/MR body abdominal images can be achieved effectively and automatically, without any prior processing procedures such as segmentation and feature extraction, but has a main drawback of very long computation time. Key words: medical image registration; multi-modality; mutual information; non-rigid; Parzen window density estimation

  6. Automatic mitral annulus tracking in volumetric ultrasound using non-rigid image registration.

    Science.gov (United States)

    De Veene, Henri; Bertrand, Philippe B; Popovic, Natasa; Vandervoort, Pieter M; Claus, Piet; De Beule, Matthieu; Heyde, Brecht

    2015-01-01

    Analysis of mitral annular dynamics plays an important role in the diagnosis and selection of optimal valve repair strategies, but remains cumbersome and time-consuming if performed manually. In this paper we propose non-rigid image registration to automatically track the annulus in 3D ultrasound images for both normal and pathological valves, and compare the performance against manual tracing. Relevant clinical properties such as annular area, circumference and excursion could be extracted reliably by the tracking algorithm. The root-mean-square error, calculated as the difference between the manually traced landmarks (18 in total) and the automatic tracking, was 1.96 ± 0.46 mm over 10 valves (5 healthy and 5 diseased) which is within the clinically acceptable error range.

  7. Level set motion assisted non-rigid 3D image registration

    Science.gov (United States)

    Yang, Deshan; Deasy, Joseph O.; Low, Daniel A.; El Naqa, Issam

    2007-03-01

    Medical imaging applications of rigid and non-rigid elastic deformable image registration are undergoing wide scale development. Our approach determines image deformation maps through a hierarchical process, from global to local scales. Vemuri (2000) reported a registration method, based on levelset evolution theory, to morph an image along the motion gradient until it deforms to the reference image. We have applied this level set motion method as basis to iteratively compute the incremental motion fields and then we approximated the field using a higher-level affine and non-rigid motion model. In such a way, we combine sequentially the global affine motion, local affine motion and local non-rigid motion. Our method is fully automated, computationally efficient, and is able to detect large deformations if used together with multi-grid approaches, potentially yielding greater registration accuracy.

  8. Non-rigid registration by geometry-constrained diffusion

    DEFF Research Database (Denmark)

    Andresen, Per Rønsholt; Nielsen, Mads

    1999-01-01

    are not given. We will advocate the viewpoint that the aperture and the 3D interpolation problem may be solved simultaneously by finding the simplest displacement field. This is obtained by a geometry-constrained diffusion which yields the simplest displacement field in a precise sense. The point registration...

  9. Efficient convex optimization approach to 3D non-rigid MR-TRUS registration.

    Science.gov (United States)

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

    2013-01-01

    In this study, we propose an efficient non-rigid MR-TRUS deformable registration method to improve the accuracy of targeting suspicious locations during a 3D ultrasound (US) guided prostate biopsy. The proposed deformable registration approach employs the multi-channel modality independent neighbourhood descriptor (MIND) as the local similarity feature across the two modalities of MR and TRUS, and a novel and efficient duality-based convex optimization based algorithmic scheme is introduced to extract the deformations which align the two MIND descriptors. The registration accuracy was evaluated using 10 patient images by measuring the TRE of manually identified corresponding intrinsic fiducials in the whole gland and peripheral zone, and performance metrics (DSC, MAD and MAXD) for the apex, mid-gland and base of the prostate were also calculated by comparing two manually segmented prostate surfaces in the registered 3D MR and TRUS images. Experimental results show that the proposed method yielded an overall mean TRE of 1.74 mm, which is favorably comparable to a clinical requirement for an error of less than 2.5 mm.

  10. Robust feature estimation by non-rigid hierarchical image registration and its application in disparity measurement

    Science.gov (United States)

    Badshah, Amir; Choudhry, Aadil Jaleel; Ullah, Shan

    2017-03-01

    Industries are moving towards automation in order to increase productivity and ensure quality. Variety of electronic and electromagnetic systems are being employed to assist human operator in fast and accurate quality inspection of products. Majority of these systems are equipped with cameras and rely on diverse image processing algorithms. Information is lost in 2D image, therefore acquiring accurate 3D data from 2D images is an open issue. FAST, SURF and SIFT are well-known spatial domain techniques for features extraction and henceforth image registration to find correspondence between images. The efficiency of these methods is measured in terms of the number of perfect matches found. A novel fast and robust technique for stereo-image processing is proposed. It is based on non-rigid registration using modified normalized phase correlation. The proposed method registers two images in hierarchical fashion using quad-tree structure. The registration process works through global to local level resulting in robust matches even in presence of blur and noise. The computed matches can further be utilized to determine disparity and depth for industrial product inspection. The same can be used in driver assistance systems. The preliminary tests on Middlebury dataset produced satisfactory results. The execution time for a 413 x 370 stereo-pair is 500ms approximately on a low cost DSP.

  11. Improving Feature-based Non-rigid Registration for Applications in Radiotherapy

    NARCIS (Netherlands)

    E.M. Vásquez Osorio (Eliana)

    2012-01-01

    textabstractThis thesis describes the improvements of a feature-based non-rigid registration method that were essential for its application in radiotherapy. In addition, this thesis presents three practical applications of the improved method: 1) quantification of anatomical changes in 3D for head a

  12. An information theoretic approach for non-rigid image registration using voxel class probabilities.

    Science.gov (United States)

    D'Agostino, Emiliano; Maes, Frederik; Vandermeulen, Dirk; Suetens, Paul

    2006-06-01

    We propose two information theoretic similarity measures that allow to incorporate tissue class information in non-rigid image registration. The first measure assumes that tissue class probabilities have been assigned to each of the images to be registered by prior segmentation of both of them. One image is then non-rigidly deformed to match the other such that the fuzzy overlap of corresponding voxel object labels becomes similar to the ideal case whereby the tissue probability maps of both images are identical. Image similarity is assessed during registration by the divergence between the ideal and actual joint class probability distributions of both images. A second registration measure is proposed that applies in case a segmentation is available for only one of the images, for instance an atlas image that is to be matched to a study image to guide the segmentation thereof. Intensities in one image are matched to the fuzzy class labels in the other image by minimizing the conditional entropy of the intensities in the first image given the class labels in the second image. We derive analytic expressions for the gradient of each measure with respect to individual voxel displacements to derive a force field that drives the registration process, which is regularized by a viscous fluid model. The performance of the class-based measures is evaluated in the context of non-rigid inter-subject registration and atlas-based segmentation of MR brain images and compared with maximization of mutual information using only intensity information. Our results demonstrate that incorporation of class information in the registration measure significantly improves the overlap between corresponding tissue classes after non-rigid matching. The methods proposed here open new perspectives for integrating segmentation and registration in a single process, whereby the output of one is used to guide the other.

  13. Multi-modal 2D-3D non-rigid registration

    Science.gov (United States)

    Prümmer, M.; Hornegger, J.; Pfister, M.; Dörfler, A.

    2006-03-01

    In this paper, we propose a multi-modal non-rigid 2D-3D registration technique. This method allows a non-rigid alignment of a patient pre-operatively computed tomography (CT) to few intra operatively acquired fluoroscopic X-ray images obtained with a C-arm system. This multi-modal approach is especially focused on the 3D alignment of high contrast reconstructed volumes with intra-interventional low contrast X-ray images in order to make use of up-to-date information for surgical guidance and other interventions. The key issue of non-rigid 2D-3D registration is how to define the distance measure between high contrast 3D data and low contrast 2D projections. In this work, we use algebraic reconstruction theory to handle this problem. We modify the Euler-Lagrange equation by introducing a new 3D force. This external force term is computed from the residual of the algebraic reconstruction procedures. In the multi-modal case we replace the residual between the digitally reconstructed radiographs (DRR) and observed X-ray images with a statistical based distance measure. We integrate the algebraic reconstruction technique into a variational registration framework, so that the 3D displacement field is driven to minimize the reconstruction distance between the volumetric data and its 2D projections using mutual information (MI). The benefits of this 2D-3D registration approach are its scalability in the number of used X-ray reference images and the proposed distance that can handle low contrast fluoroscopies as well. Experimental results are presented on both artificial phantom and 3D C-arm CT images.

  14. Hierarchical and successive approximate registration of the non-rigid medical image based on thin-plate splines

    Science.gov (United States)

    Hu, Jinyan; Li, Li; Yang, Yunfeng

    2017-06-01

    The hierarchical and successive approximate registration method of non-rigid medical image based on the thin-plate splines is proposed in the paper. There are two major novelties in the proposed method. First, the hierarchical registration based on Wavelet transform is used. The approximate image of Wavelet transform is selected as the registered object. Second, the successive approximation registration method is used to accomplish the non-rigid medical images registration, i.e. the local regions of the couple images are registered roughly based on the thin-plate splines, then, the current rough registration result is selected as the object to be registered in the following registration procedure. Experiments show that the proposed method is effective in the registration process of the non-rigid medical images.

  15. Non-rigid image registration under non-deterministic deformation bounds

    Science.gov (United States)

    Ge, Qian; Lokare, Namita; Lobaton, Edgar

    2015-01-01

    Image registration aims to identify the mapping between corresponding locations in an anatomic structure. Most traditional approaches solve this problem by minimizing some error metric. However, they do not quantify the uncertainty behind their estimates and the feasibility of other solutions. In this work, it is assumed that two images of the same anatomic structure are related via a Lipschitz non-rigid deformation (the registration map). An approach for identifying point correspondences with zero false-negative rate and high precision is introduced under this assumption. This methodology is then extended to registration of regions in an image which is posed as a graph matching problem with geometric constraints. The outcome of this approach is a homeomorphism with uncertainty bounds characterizing its accuracy over the entire image domain. The method is tested by applying deformation maps to the LPBA40 dataset.

  16. PROBABILISTIC NON-RIGID REGISTRATION OF PROSTATE IMAGES: MODELING AND QUANTIFYING UNCERTAINTY

    Science.gov (United States)

    Risholm, Petter; Fedorov, Andriy; Pursley, Jennifer; Tuncali, Kemal; Cormack, Robert; Wells, William M.

    2012-01-01

    Registration of pre- to intra-procedural prostate images needs to handle the large changes in position and shape of the prostate caused by varying rectal filling and patient positioning. We describe a probabilistic method for non-rigid registration of prostate images which can quantify the most probable deformation as well as the uncertainty of the estimated deformation. The method is based on a biomechanical Finite Element model which treats the prostate as an elastic material. We use a Markov Chain Monte Carlo sampler to draw deformation configurations from the posterior distribution. In practice, we simultaneously estimate the boundary conditions (surface displacements) and the internal deformations of our biomechanical model. The proposed method was validated on a clinical MRI dataset with registration results comparable to previously published methods, but with the added benefit of also providing uncertainty estimates which may be important to take into account during prostate biopsy and brachytherapy procedures. PMID:22288004

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

    Science.gov (United States)

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

    2011-03-01

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

  18. Contour propagation in MRI-guided radiotherapy treatment of cervical cancer: the accuracy of rigid, non-rigid and semi-automatic registrations

    Science.gov (United States)

    van der Put, R. W.; Kerkhof, E. M.; Raaymakers, B. W.; Jürgenliemk-Schulz, I. M.; Lagendijk, J. J. W.

    2009-12-01

    External beam radiation treatment for patients with cervical cancer is hindered by the relatively large motion of the target volume. A hybrid MRI-accelerator system makes it possible to acquire online MR images during treatment in order to correct for motion and deformation. To fully benefit from such a system, online delineation of the target volumes is necessary. The aim of this study is to investigate the accuracy of rigid, non-rigid and semi-automatic registrations of MR images for interfractional contour propagation in patients with cervical cancer. Registration using mutual information was performed on both bony anatomy and soft tissue. A B-spline transform was used for the non-rigid method. Semi-automatic registration was implemented with a point set registration algorithm on a small set of manual landmarks. Online registration was simulated by application of each method to four weekly MRI scans for each of 33 cervical cancer patients. Evaluation was performed by distance analysis with respect to manual delineations. The results show that soft-tissue registration significantly (P treatment of cervical cancer, online MRI imaging will allow target localization based on soft tissue visualization, which provides a significantly higher accuracy than localization based on bony anatomy. The use of limited user input to guide the registration increases overall accuracy. Additional non-rigid registration further reduces the propagation error and negates errors caused by small observer variations.

  19. Combination of automatic non-rigid and landmark based registration: the best of both worlds

    Science.gov (United States)

    Fischer, Bernd; Modersitzki, Jan

    2003-05-01

    Automatic, parameter-free, and non-rigid registration schemes are known to be valuable tools in various (medical) image processing applications. Typically, these approaches aim to match intensity patterns in each scan by minimizing an appropriate distance measure. The outcome of an automatic registration procedure in general matches the target image quite good on the average. However, it may be inaccurate for specific, important locations as for example anatomical landmarks. On the other hand, landmark based registration techniques are designed to accurately match user specified landmarks. A drawback of landmark based registration is that the intensities of the images are completely neglected. Consequently, the registration result away from the landmarks may be very poor. Here we propose a framework for novel registration techniques which are capable to combine automatic and landmark driven approaches in order to benefit from the advantages of both strategies. We also propose a general, mathematical treatment of this framework and a particular implementation. The procedure computes a displacement field which is guaranteed to produce a one-to-one match between given landmarks and at the smae time minimizes an intensity based measure for the remaining parts of the images. The properties of the new scheme are demonstrated for a variety of numerical example. It is worthwhile noticing, that we not only present a new approach. Instead, we propose a general framework for a variety of different approaches. The choice of the main building blocks, the distance measure and the smoothness constraint, is essentially free.

  20. Non-rigid contour-to-pixel registration of photographic and quantitative light-induced fluorescence imaging of decalcified teeth

    Science.gov (United States)

    Berkels, Benjamin; Deserno, Thomas; Ehrlich, Eva E.; Fritz, Ulrike B.; Sirazitdinova, Ekaterina; Tatano, Rosalia

    2016-03-01

    Quantitative light-induced fluorescence (QLF) is widely used to assess the damage of a tooth due to decalcification. In digital photographs, decalcification appears as white spot lesions, i.e. white spots on the tooth surface. We propose a novel multimodal registration approach for the matching of digital photographs and QLF images of decalcified teeth. The registration is based on the idea of contour-to-pixel matching. Here, the curve, which represents the shape of the tooth, is extracted from the QLF image using a contour segmentation by binarization and morphological processing. This curve is aligned to the photo with a non-rigid variational registration approach. Thus, the registration problem is formulated as minimization problem with an objective function that consists of a data term and a regularizer for the deformation. To construct the data term, the photo is pointwise classified into tooth and non-tooth regions. Then, the signed distance function of the tooth region allows to measure the mismatch between curve and photo. As regularizer a higher order, linear elastic prior is used. The resulting minimization problem is solved numerically using bilinear Finite Elements for the spatial discretization and the Gauss-Newton algorithm. The evaluation is based on 150 image pairs, where an average of 5 teeth have been captured from 32 subjects. All registrations have been confirmed correctly by a dental expert. The contour-to-pixel methods can directly be used in 3D for surface-to-voxel tasks.

  1. Non-rigid registration of breast surfaces using the laplace and diffusion equations

    Directory of Open Access Journals (Sweden)

    Ou Jao J

    2010-02-01

    Full Text Available Abstract A semi-automated, non-rigid breast surface registration method is presented that involves solving the Laplace or diffusion equations over undeformed and deformed breast surfaces. The resulting potential energy fields and isocontours are used to establish surface correspondence. This novel surface-based method, which does not require intensity images, anatomical landmarks, or fiducials, is compared to a gold standard of thin-plate spline (TPS interpolation. Realistic finite element simulations of breast compression and further testing against a tissue-mimicking phantom demonstrate that this method is capable of registering surfaces experiencing 6 - 36 mm compression to within a mean error of 0.5 - 5.7 mm.

  2. Bayesian Characterization of Uncertainty in Intra-Subject Non-Rigid Registration

    Science.gov (United States)

    Risholm, Petter; Janoos, Firdaus; Norton, Isaiah; Golby, Alex J.; Wells, William M.

    2013-01-01

    In settings where high-level inferences are made based on registered image data, the registration uncertainty can contain important information. In this article, we propose a Bayesian non-rigid registration framework where conventional dissimilarity and regularization energies can be included in the likelihood and the prior distribution on deformations respectively through the use of Boltzmann’s distribution. The posterior distribution is characterized using Markov Chain Monte Carlo (MCMC) methods with the effect of the Boltzmann temperature hyper-parameters marginalized under broad uninformative hyper-prior distributions. The MCMC chain permits estimation of the most likely deformation as well as the associated uncertainty. On synthetic examples, we demonstrate the ability of the method to identify the maximum a posteriori estimate and the associated posterior uncertainty, and demonstrate that the posterior distribution can be non-Gaussian. Additionally, results from registering clinical data acquired during neurosurgery for resection of brain tumor are provided; we compare the method to single transformation results from a deterministic optimizer and introduce methods that summarize the high-dimensional uncertainty. At the site of resection, the registration uncertainty increases and the marginal distribution on deformations is shown to be multi-modal. PMID:23602919

  3. Improving supervised classification accuracy using non-rigid multimodal image registration: detecting prostate cancer

    Science.gov (United States)

    Chappelow, Jonathan; Viswanath, Satish; Monaco, James; Rosen, Mark; Tomaszewski, John; Feldman, Michael; Madabhushi, Anant

    2008-03-01

    Computer-aided diagnosis (CAD) systems for the detection of cancer in medical images require precise labeling of training data. For magnetic resonance (MR) imaging (MRI) of the prostate, training labels define the spatial extent of prostate cancer (CaP); the most common source for these labels is expert segmentations. When ancillary data such as whole mount histology (WMH) sections, which provide the gold standard for cancer ground truth, are available, the manual labeling of CaP can be improved by referencing WMH. However, manual segmentation is error prone, time consuming and not reproducible. Therefore, we present the use of multimodal image registration to automatically and accurately transcribe CaP from histology onto MRI following alignment of the two modalities, in order to improve the quality of training data and hence classifier performance. We quantitatively demonstrate the superiority of this registration-based methodology by comparing its results to the manual CaP annotation of expert radiologists. Five supervised CAD classifiers were trained using the labels for CaP extent on MRI obtained by the expert and 4 different registration techniques. Two of the registration methods were affi;ne schemes; one based on maximization of mutual information (MI) and the other method that we previously developed, Combined Feature Ensemble Mutual Information (COFEMI), which incorporates high-order statistical features for robust multimodal registration. Two non-rigid schemes were obtained by succeeding the two affine registration methods with an elastic deformation step using thin-plate splines (TPS). In the absence of definitive ground truth for CaP extent on MRI, classifier accuracy was evaluated against 7 ground truth surrogates obtained by different combinations of the expert and registration segmentations. For 26 multimodal MRI-WMH image pairs, all four registration methods produced a higher area under the receiver operating characteristic curve compared to that

  4. GPU accelerated non-rigid registration for the evaluation of cardiac function.

    Science.gov (United States)

    Li, Bo; Young, Alistair A; Cowan, Brett R

    2008-01-01

    We present a method for the fast and efficient tracking of motion in cardiac magnetic resonance (CMR) cines. A GPU accelerated Levenberg-Marquardt non-linear least squares optimization procedure for finite element non-rigid registration was implemented on an NVIDIA graphics card using the OpenGL environment. Points were tracked from frame to frame using forward and backward incremental registration. The inner (endocardial) and outer (epicardial) boarders of the heart were tracked in six short axis cines with approximately 25 frames through the cardiac cycle in 36 patients with vascular disease. Contours placed by two independent expert observers using a semi-automatic ventricular analysis program (CIM version 4.6) were used as the gold standard. The method took 0.5 seconds per frame, and the maximum Hausdorff errors were less than 2 mm on average which was of the same order as the expert inter-observer error. In conclusion, GPU accelerated Levenberg-Marquardt non-linear optimization enables fast and accurate tracking of cardiac motion in CMR images.

  5. Non-rigid registration and KLT filter to improve SNR and CNR in GRE-EPI myocardial perfusion imaging.

    Science.gov (United States)

    Mihai, Georgeta; Ding, Yu; Xue, Hui; Chung, Yiu-Cho; Rajagopalan, Sanjay; Guehring, Jens; Simonetti, Orlando P

    2012-12-01

    The purpose of the study was to evaluate the effect of motion compensation by non-rigid registration combined with the Karhunen-Loeve Transform (KLT) filter on the signal to noise (SNR) and contrast-to-noise ratio (CNR) of hybrid gradient-echo echoplanar (GRE-EPI) first-pass myocardial perfusion imaging. Twenty one consecutive first-pass adenosine stress perfusion MR data sets interpreted positive for ischemia or infarction were processed by non-rigid Registration followed by KLT filtering. SNR and CNR were measured in abnormal and normal myocardium in unfiltered and KLT filtered images following non-rigid registration to compensate for respiratory and other motions. Image artifacts introduced by filtering in registered and nonregistered images were evaluated by two observers. There was a statistically significant increase in both SNR and CNR between normal and abnormal myocardium with KLT filtering (mean SNR increased by 62.18% ± 21.05% and mean CNR increased by 58.84% ± 18.06%; p = 0.01). Motion correction prior to KLT filtering reduced significantly the occurrence of filter induced artifacts (KLT only-artifacts in 42 out of 55 image series vs. registered plus KLT-artifacts in 3 out of 55 image series). In conclusion the combination of non- rigid registration and KLT filtering was shown to increase the SNR and CNR of GRE-EPI perfusion images. Subjective evaluation of image artifacts revealed that prior motion compensation significantly reduced the artifacts introduced by the KLT filtering process.

  6. Effects of reusing baseline volumes of interest by applying (non-rigid image registration on positron emission tomography response assessments.

    Directory of Open Access Journals (Sweden)

    Floris H P van Velden

    Full Text Available OBJECTIVES: Reusing baseline volumes of interest (VOI by applying non-rigid and to some extent (local rigid image registration showed good test-retest variability similar to delineating VOI on both scans individually. The aim of the present study was to compare response assessments and classifications based on various types of image registration with those based on (semi-automatic tumour delineation. METHODS: Baseline (n = 13, early (n = 12 and late (n = 9 response (after one and three cycles of treatment, respectively whole body [(18F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (PET/CT scans were acquired in subjects with advanced gastrointestinal malignancies. Lesions were identified for early and late response scans. VOI were drawn independently on all scans using an adaptive 50% threshold method (A50. In addition, various types of (non-rigid image registration were applied to PET and/or CT images, after which baseline VOI were projected onto response scans. Response was classified using PET Response Criteria in Solid Tumors for maximum standardized uptake value (SUV(max, average SUV (SUV(mean, peak SUV (SUV(peak, metabolically active tumour volume (MATV, total lesion glycolysis (TLG and the area under a cumulative SUV-volume histogram curve (AUC. RESULTS: Non-rigid PET-based registration and non-rigid CT-based registration followed by non-rigid PET-based registration (CTPET did not show differences in response classifications compared to A50 for SUV(max and SUV(peak, however, differences were observed for MATV, SUV(mean, TLG and AUC. For the latter, these registrations demonstrated a poorer performance for small lung lesions (<2.8 ml, whereas A50 showed a poorer performance when another area with high uptake was close to the target lesion. All methods were affected by lesions with very heterogeneous tracer uptake. CONCLUSIONS: Non-rigid PET- and CTPET-based image registrations may be used to classify response

  7. High-throughput mouse phenotyping using non-rigid registration and robust principal component analysis

    Science.gov (United States)

    Xie, Zhongliu; Kitamoto, Asanobu; Tamura, Masaru; Shiroishi, Toshihiko; Gillies, Duncan

    2016-03-01

    Intensive international efforts are underway towards phenotyping the mouse genome, by knocking out each of its ≍25,000 genes one-by-one for comparative study. With vast amounts of data to analyze, the traditional method using time-consuming histological examination is clearly impractical, leading to an overwhelming demand for some high-throughput phenotyping framework, especially with the employment of biomedical image informatics to efficiently identify phenotypes concerning morphological abnormality. Existing work has either excessively relied on volumetric analytics which is insensitive to phenotypes associated with no severe volume variations, or tailored for specific defects and thus fails to serve a general phenotyping purpose. Furthermore, the prevailing requirement of an atlas for image segmentation in contrast to its limited availability further complicates the issue in practice. In this paper we propose a high-throughput general-purpose phenotyping framework that is able to efficiently perform batch-wise anomaly detection without prior knowledge of the phenotype and the need for atlas-based segmentation. Anomaly detection is centered on the combined use of group-wise non-rigid image registration and robust principal component analysis (RPCA) for feature extraction and decomposition.

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

    Science.gov (United States)

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

    2016-03-01

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

  9. Topology preserving non-rigid image registration using time-varying elasticity model for MRI brain volumes.

    Science.gov (United States)

    Ahmad, Sahar; Khan, Muhammad Faisal

    2015-12-01

    In this paper, we present a new non-rigid image registration method that imposes a topology preservation constraint on the deformation. We propose to incorporate the time varying elasticity model into the deformable image matching procedure and constrain the Jacobian determinant of the transformation over the entire image domain. The motion of elastic bodies is governed by a hyperbolic partial differential equation, generally termed as elastodynamics wave equation, which we propose to use as a deformation model. We carried out clinical image registration experiments on 3D magnetic resonance brain scans from IBSR database. The results of the proposed registration approach in terms of Kappa index and relative overlap computed over the subcortical structures were compared against the existing topology preserving non-rigid image registration methods and non topology preserving variant of our proposed registration scheme. The Jacobian determinant maps obtained with our proposed registration method were qualitatively and quantitatively analyzed. The results demonstrated that the proposed scheme provides good registration accuracy with smooth transformations, thereby guaranteeing the preservation of topology.

  10. Estimation of myocardial strain from non-rigid registration and highly accelerated cine CMR.

    Science.gov (United States)

    Langton, Jonathan E N; Lam, Hoi-Ieng; Cowan, Brett R; Occleshaw, Christopher J; Gabriel, Ruvin; Lowe, Boris; Lydiard, Suzanne; Greiser, Andreas; Schmidt, Michaela; Young, Alistair A

    2017-01-01

    Sparsely sampled cardiac cine accelerated acquisitions show promise for faster evaluation of left-ventricular function. Myocardial strain estimation using image feature tracking methods is also becoming widespread. However, it is not known whether highly accelerated acquisitions also provide reliable feature tracking strain estimates. Twenty patients and twenty healthy volunteers were imaged with conventional 14-beat/slice cine acquisition (STD), 4× accelerated 4-beat/slice acquisition with iterative reconstruction (R4), and a 9.2× accelerated 2-beat/slice real-time acquisition with sparse sampling and iterative reconstruction (R9.2). Radial and circumferential strains were calculated using non-rigid registration in the mid-ventricle short-axis slice and inter-observer errors were evaluated. Consistency was assessed using intra-class correlation coefficients (ICC) and bias with Bland-Altman analysis. Peak circumferential strain magnitude was highly consistent between STD and R4 and R9.2 (ICC = 0.876 and 0.884, respectively). Average bias was -1.7 ± 2.0 %, p < 0.001, for R4 and -2.7 ± 1.9 %, p < 0.001 for R9.2. Peak radial strain was also highly consistent (ICC = 0.829 and 0.785, respectively), with average bias -11.2 ± 18.4 %, p < 0.001, for R4 and -15.0 ± 21.2 %, p < 0.001 for R9.2. STD circumferential strain could be predicted by linear regression from R9.2 with an R(2) of 0.82 and a root mean squared error of 1.8 %. Similarly, radial strain could be predicted with an R(2) of 0.67 and a root mean squared error of 21.3 %. Inter-observer errors were not significantly different between methods, except for peak circumferential strain R9.2 (1.1 ± 1.9 %) versus STD (0.3 ± 1.0 %), p = 0.011. Although small systematic differences were observed in strain, these were highly consistent with standard acquisitions, suggesting that accelerated myocardial strain is feasible and reliable in patients who

  11. A batch Algorithm for Implicit Non-Rigid Shape and Motion Recovery

    DEFF Research Database (Denmark)

    Bartoli, Adrien; Olsen, Søren Ingvor

    2005-01-01

    manner. There are several issues that have not been addressed yet, among which, choosing the rank automatically and dealing with erroneous point tracks and missing data. We introduce theoretical and practical contributions that address these issues. We propose an implicit imaging model for non......The recovery of 3D shape and camera motion for non-rigid scenes from single-camera video footage is a very important problem in computer vision. The low-rank shape model consists in regarding the deformations as linear combinations of basis shapes. Most algorithms for reconstructing the parameters...... of the subsequence, using a robust estimator incorporating a model selection criterion that detects erroneous image points. Preliminary experimental results on real and simulated data show that our algorithm deals with challenging video sequences....

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

    Science.gov (United States)

    Yu, Weimin; Zysset, Philippe; Zheng, Guoyan

    2015-03-01

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

  13. Non-rigid image registration to reduce beam-induced blurring of cryo-electron microscopy images

    Energy Technology Data Exchange (ETDEWEB)

    Karimi Nejadasl, Fatemeh; Karuppasamy, Manikandan [Leiden University Medical Center, PO Box 9600, 2300RC Leiden (Netherlands); Newman, Emily R.; McGeehan, John E. [University of Portsmouth, Portsmouth PO1 2DY (United Kingdom); Ravelli, Raimond B. G., E-mail: raimond.nl@gmail.com [Leiden University Medical Center, PO Box 9600, 2300RC Leiden (Netherlands)

    2013-01-01

    Cryo-electron microscopy images of vitrified large macromolecular complexes can become blurred due to beam-induced specimen alterations. Exposure series are examined, and rigid and non-rigid image registration schemes are applied to reduce such blurring. The typical dose used to record cryo-electron microscopy images from vitrified biological specimens is so high that radiation-induced structural alterations are bound to occur during data acquisition. Integration of all scattered electrons into one image can lead to significant blurring, particularly if the data are collected from an unsupported thin layer of ice suspended over the holes of a support film. Here, the dose has been fractioned and exposure series have been acquired in order to study beam-induced specimen movements under low dose conditions, prior to bubbling. Gold particles were added to the protein sample as fiducial markers. These were automatically localized and tracked throughout the exposure series and showed correlated motions within small patches, with larger amplitudes of motion vectors at the start of a series compared with the end of each series. A non-rigid scheme was used to register all images within each exposure series, using natural neighbor interpolation with the gold particles as anchor points. The procedure increases the contrast and resolution of the examined macromolecules.

  14. 3D prostate MR-TRUS non-rigid registration using dual optimization with volume-preserving constraint

    Science.gov (United States)

    Qiu, Wu; Yuan, Jing; Fenster, Aaron

    2016-03-01

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

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

    NARCIS (Netherlands)

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

    2016-01-01

    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,

  16. Validation of TMJ osteoarthritis synthetic defect database via non-rigid registration

    Science.gov (United States)

    Paniagua, Beatriz; Pera, Juliette; Budin, Francois; Gomes, Liliane; Styner, Martin; Lucia, Cevidanes; Nguyen, Tung

    2015-03-01

    Temporomandibular joint (TMJ) disorders are a group of conditions that cause pain and dysfunction in the jaw joint and the muscles controlling jaw movement. However, diagnosis and treatment of these conditions remain controversial. To date, there is no single sign, symptom, or test that can clearly diagnose early stages of osteoarthritis (OA). Instead, the diagnosis is based on a consideration of several factors, including radiological evaluation. The current radiological diagnosis scores of TMJ pathology are subject to misdiagnosis. We believe these scores are limited by the acquisition procedures, such as oblique cuts of the CT and head positioning errors, and can lead to incorrect diagnoses of flattening of the head of the condyle, formation of osteophytes, or condylar pitting. This study consists of creating and validating a methodological framework to simulate defects in CBCT scans of known location and size, in order to create synthetic TMJ OA database. User-generated defects were created using a non-rigid deformation protocol in CBCT. All segmentation evaluation, surface distances and linear distances from the user-generated to the simulated defects showed our methodological framework to be very precise and within a voxel (0.5 mm) of magnitude. A TMJ OA synthetic database will be created next, and evaluated by expert radiologists, and this will serve to evaluate how sensitive the current radiological diagnosis tools are.

  17. Non-rigid Registration for Large Sets of Microscopic Images on Graphics Processors.

    Science.gov (United States)

    Ruiz, Antonio; Ujaldon, Manuel; Cooper, Lee; Huang, Kun

    2009-04-01

    Microscopic imaging is an important tool for characterizing tissue morphology and pathology. 3D reconstruction and visualization of large sample tissue structure requires registration of large sets of high-resolution images. However, the scale of this problem presents a challenge for automatic registration methods. In this paper we present a novel method for efficient automatic registration using graphics processing units (GPUs) and parallel programming. Comparing a C++ CPU implementation with Compute Unified Device Architecture (CUDA) libraries and pthreads running on GPU we achieve a speed-up factor of up to 4.11× with a single GPU and 6.68× with a GPU pair. We present execution times for a benchmark composed of two sets of large-scale images: mouse placenta (16K × 16K pixels) and breast cancer tumors (23K × 62K pixels). It takes more than 12 hours for the genetic case in C++ to register a typical sample composed of 500 consecutive slides, which was reduced to less than 2 hours using two GPUs, in addition to a very promising scalability for extending those gains easily on a large number of GPUs in a distributed system.

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

    Science.gov (United States)

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

    2010-02-01

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

  19. Two Phase Non-Rigid Multi-Modal Image Registration Using Weber Local Descriptor-Based Similarity Metrics and Normalized Mutual Information

    Science.gov (United States)

    Yang, Feng; Ding, Mingyue; Zhang, Xuming; Wu, Yi; Hu, Jiani

    2013-01-01

    Non-rigid multi-modal image registration plays an important role in medical image processing and analysis. Existing image registration methods based on similarity metrics such as mutual information (MI) and sum of squared differences (SSD) cannot achieve either high registration accuracy or high registration efficiency. To address this problem, we propose a novel two phase non-rigid multi-modal image registration method by combining Weber local descriptor (WLD) based similarity metrics with the normalized mutual information (NMI) using the diffeomorphic free-form deformation (FFD) model. The first phase aims at recovering the large deformation component using the WLD based non-local SSD (wldNSSD) or weighted structural similarity (wldWSSIM). Based on the output of the former phase, the second phase is focused on getting accurate transformation parameters related to the small deformation using the NMI. Extensive experiments on T1, T2 and PD weighted MR images demonstrate that the proposed wldNSSD-NMI or wldWSSIM-NMI method outperforms the registration methods based on the NMI, the conditional mutual information (CMI), the SSD on entropy images (ESSD) and the ESSD-NMI in terms of registration accuracy and computation efficiency. PMID:23765270

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

    Directory of Open Access Journals (Sweden)

    Rexilius Jan

    2005-03-01

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

  1. A new technique for noise reduction at coronary CT angiography with multi-phase data-averaging and non-rigid image registration

    Energy Technology Data Exchange (ETDEWEB)

    Tatsugami, Fuminari; Higaki, Toru; Nakamura, Yuko; Yamagami, Takuji; Date, Shuji; Awai, Kazuo [Hiroshima University, Department of Diagnostic Radiology, Minami-ku, Hiroshima (Japan); Fujioka, Chikako; Kiguchi, Masao [Hiroshima University, Department of Radiology, Minami-ku, Hiroshima (Japan); Kihara, Yasuki [Hiroshima University, Department of Cardiovascular Medicine, Minami-ku, Hiroshima (Japan)

    2015-01-15

    To investigate the feasibility of a newly developed noise reduction technique at coronary CT angiography (CTA) that uses multi-phase data-averaging and non-rigid image registration. Sixty-five patients underwent coronary CTA with prospective ECG-triggering. The range of the phase window was set at 70-80 % of the R-R interval. First, three sets of consecutive volume data at 70 %, 75 % and 80 % of the R-R interval were prepared. Second, we applied non-rigid registration to align the 70 % and 80 % images to the 75 % image. Finally, we performed weighted averaging of the three images and generated a de-noised image. The image noise and contrast-to-noise ratio (CNR) in the proximal coronary arteries between the conventional 75 % and the de-noised images were compared. Two radiologists evaluated the image quality using a 5-point scale (1, poor; 5, excellent). On de-noised images, mean image noise was significantly lower than on conventional 75 % images (18.3 HU ± 2.6 vs. 23.0 HU ± 3.3, P < 0.01) and the CNR was significantly higher (P < 0.01). The mean image quality score for conventional 75 % and de-noised images was 3.9 and 4.4, respectively (P < 0.01). Our method reduces image noise and improves image quality at coronary CTA. (orig.)

  2. Non-rigid isometric ICP: A practical registration method for the analysis and compensation of form errors in production engineering

    KAUST Repository

    Sacharow, Alexei

    2011-12-01

    The unprecedented success of the iterative closest point (ICP) method for registration in geometry processing and related fields can be attributed to its efficiency, robustness, and wide spectrum of applications. Its use is however quite limited as soon as the objects to be registered arise from each other by a transformation significantly different from a Euclidean motion. We present a novel variant of ICP, tailored for the specific needs of production engineering, which registers a triangle mesh with a second surface model of arbitrary digital representation. Our method inherits most of ICP\\'s practical advantages but is capable of detecting medium-strength bendings i.e. isometric deformations. Initially, the algorithm assigns to all vertices in the source their closest point on the target mesh and then iteratively establishes isometry, a process which, very similar to ICP, requires intermediate re-projections. A NURBS-based technique for applying the resulting deformation to arbitrary instances of the source geometry, other than the very mesh used for correspondence estimation, is described before we present numerical results on synthetic and real data to underline the viability of our approach in comparison with others. © 2011 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    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.

  4. Measurement of Strain in Cardiac Myocytes at Micrometer Scale Based on Rapid Scanning Confocal Microscopy and Non-Rigid Image Registration.

    Science.gov (United States)

    Lichter, J; Li, Hui; Sachse, Frank B

    2016-10-01

    Measurement of cell shortening is an important technique for assessment of physiology and pathophysiology of cardiac myocytes. Many types of heart disease are associated with decreased myocyte shortening, which is commonly caused by structural and functional remodeling. Here, we present a new approach for local measurement of 2-dimensional strain within cells at high spatial resolution. The approach applies non-rigid image registration to quantify local displacements and Cauchy strain in images of cells undergoing contraction. We extensively evaluated the approach using synthetic cell images and image sequences from rapid scanning confocal microscopy of fluorescently labeled isolated myocytes from the left ventricle of normal and diseased canine heart. Application of the approach yielded a comprehensive description of cellular strain including novel measurements of transverse strain and spatial heterogeneity of strain. Quantitative comparison with manual measurements of strain in image sequences indicated reliability of the developed approach. We suggest that the developed approach provides researchers with a novel tool to investigate contractility of cardiac myocytes at subcellular scale. In contrast to previously introduced methods for measuring cell shorting, the developed approach provides comprehensive information on the spatio-temporal distribution of 2-dimensional strain at micrometer scale.

  5. Accuracy Validation for Medical Image Registration Algorithms: a Review

    Institute of Scientific and Technical Information of China (English)

    Zhe Liu; Xiang Deng; Guang-zhi Wang

    2012-01-01

    Accuracy validation is essential to clinical application of medical image registration techniques.Registration validation remains a challenging problem in practice mainly due to lack of 'ground truth'.In this paper,an overview of current validation methods for medical image registration is presented with detailed discussion of their benefits and drawbacks.Special focus is on non-rigid registration validation.Promising solution is also discussed.

  6. Objective evaluation of the correction by non-rigid registration of abdominal organ motion in low-dose 4D dynamic contrast-enhanced CT

    Science.gov (United States)

    Piper, Jim; Ikeda, Yoshihiro; Fujisawa, Yasuko; Ohno, Yoshiharu; Yoshikawa, Takeshi; O'Neil, Alison; Poole, Ian

    2012-03-01

    We objectively evaluate a straightforward registration method for correcting respiration-induced movement of abdominal organs in CT perfusion studies by measuring the distributions of alignment errors between corresponding landmark pairs. We introduce the concept and describe the advantages of using the surface-normal component of distance between pairs of corresponding landmarks selected so that their surface normal is in one of the three coordinate axis directions, and show that such landmarks can be precisely placed with respect to the surface normal. Using a large population of landmark pairs on a substantial quantity of 4D dynamic contrast-enhanced CT volume data, we quantify the average alignment errors of abdominal organs that remain uncorrected by registration.

  7. Mean Shift Registration Algorithm for Dissimilar Sensors

    Institute of Scientific and Technical Information of China (English)

    QI Yong-qing; JING Zhong-liang; HU Shi-qiang; ZHAO Hai-tao

    2009-01-01

    The mean shift registration (MSR) algorithm is proposed to accurately estimate the biases for multiple dissimilar sensors. The new algorithm is a batch optimization procedure. The maximum likelihood estimator is used to estimate the target states, and then the mean shift algorithm is implemented to estimate the sensor biases. Monte Carlo simulations show that the MSR algorithm has significant improvement in performance with reducing the standard deviation and mean of sensor biased estimation error compared with the maximum likelihood registration algorithm. The quantitative analysis and the qualitative analysis show that the MSR algorithm has less computation than the maximum likelihood registration method.

  8. Brownian Warps for Non-Rigid Registration

    DEFF Research Database (Denmark)

    Nielsen, Mads; Johansen, Peter; Jackson, Andrew D.;

    2008-01-01

    prior, we formulate a Partial Differential Equation for obtaining the maximally likely warp given matching constraints derived from the images. We solve for the free boundary conditions, and the bias toward smaller areas in the finite domain setting. Furthermore, we demonstrate the technique on 2D...

  9. Evaluation of Registration Methods on Thoracic CT

    DEFF Research Database (Denmark)

    Murphy, K.; van Ginneken, B.; Reinhardt, J.;

    2011-01-01

    EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intra-patient thoracic CT image pairs. Evaluation of non-rigid registration techniques is a non trivial task...

  10. A Robust and Accurate Two-Step Auto-Labeling Conditional Iterative Closest Points (TACICP Algorithm for Three-Dimensional Multi-Modal Carotid Image Registration.

    Directory of Open Access Journals (Sweden)

    Hengkai Guo

    Full Text Available Atherosclerosis is among the leading causes of death and disability. Combining information from multi-modal vascular images is an effective and efficient way to diagnose and monitor atherosclerosis, in which image registration is a key technique. In this paper a feature-based registration algorithm, Two-step Auto-labeling Conditional Iterative Closed Points (TACICP algorithm, is proposed to align three-dimensional carotid image datasets from ultrasound (US and magnetic resonance (MR. Based on 2D segmented contours, a coarse-to-fine strategy is employed with two steps: rigid initialization step and non-rigid refinement step. Conditional Iterative Closest Points (CICP algorithm is given in rigid initialization step to obtain the robust rigid transformation and label configurations. Then the labels and CICP algorithm with non-rigid thin-plate-spline (TPS transformation model is introduced to solve non-rigid carotid deformation between different body positions. The results demonstrate that proposed TACICP algorithm has achieved an average registration error of less than 0.2mm with no failure case, which is superior to the state-of-the-art feature-based methods.

  11. Collaborative Error Registration Algorithm for Radar System

    Institute of Scientific and Technical Information of China (English)

    WU Ze-min; REN Shu-jie; LIU Xi

    2009-01-01

    Affected by common target selection, target motion estimation and time alignment, the radar system error registration algorithm is greatly limited in application. By using communication and time synchronization function of a data link network, a collaborative algorithm is proposed, which makes use of a virtual coordinates constructed by airplane to get high precision measurement source and realize effective estimation of the system error. This algorithm is based on Kalman filter and does not require high capacities in memory and calculation. Simulated results show that the algorithm has better convergence performance and estimation precision, no constrain on sampling period and accords with transfer characteristic of data link and tactical internet perfectly.

  12. EVALUATION OF REGISTRATION, COMPRESSION AND CLASSIFICATION ALGORITHMS

    Science.gov (United States)

    Jayroe, R. R.

    1994-01-01

    Several types of algorithms are generally used to process digital imagery such as Landsat data. The most commonly used algorithms perform the task of registration, compression, and classification. Because there are different techniques available for performing registration, compression, and classification, imagery data users need a rationale for selecting a particular approach to meet their particular needs. This collection of registration, compression, and classification algorithms was developed so that different approaches could be evaluated and the best approach for a particular application determined. Routines are included for six registration algorithms, six compression algorithms, and two classification algorithms. The package also includes routines for evaluating the effects of processing on the image data. This collection of routines should be useful to anyone using or developing image processing software. Registration of image data involves the geometrical alteration of the imagery. Registration routines available in the evaluation package include image magnification, mapping functions, partitioning, map overlay, and data interpolation. The compression of image data involves reducing the volume of data needed for a given image. Compression routines available in the package include adaptive differential pulse code modulation, two-dimensional transforms, clustering, vector reduction, and picture segmentation. Classification of image data involves analyzing the uncompressed or compressed image data to produce inventories and maps of areas of similar spectral properties within a scene. The classification routines available include a sequential linear technique and a maximum likelihood technique. The choice of the appropriate evaluation criteria is quite important in evaluating the image processing functions. The user is therefore given a choice of evaluation criteria with which to investigate the available image processing functions. All of the available

  13. Algorithm for Fast Registration of Radar Images

    Directory of Open Access Journals (Sweden)

    Subrata Rakshit

    2002-07-01

    Full Text Available Radar imagery provides an all-weather and 24 h coverage, making it ideal for critical defence applications. In some applications, multiple images acquired of an area need to be registered for further processing. Such situations arise for battlefield surveillance based on satellite imagery. The registration has to be done between an earlier (reference image and a new (live image. For automated surveillance, registration is a prerequisite for change detection. Speed is essential due to large volumes of data involved and the need for quick responses. The registration transformation is quite simple, being mainly a global translation. (Scale and rotation corrections can be applied based on known camera parameters. The challenge lies in the fact that the radar images are not as feature-rich as optical images and the image content variation can be as high as 90 per cent. Even though the change on the ground may not be drastic, seasonal variations can significantly alter the radar signatures of ground, vegetation, and water bodies. This necessitates a novel approach different from the techniques developed for optical images. An algorithm has been developed that leads to fast registration of radar images, even in the presence of specular noise and significant scene content variation. The key features of this approach are adaptability to sensor/terrain types, ability to handle large content variations and false positive rejection. The present work shows that this algorithm allows for various cost-performance trade-offs, making it suitable for a wide variety of applications. The algorithm, in various cost-performance configurations, is tested on a set of ERS images. Results of such tests have been reported, indicating the performance of the algorithm for various cost-performance trade-offs.

  14. High performance deformable image registration algorithms for manycore processors

    CERN Document Server

    Shackleford, James; Sharp, Gregory

    2013-01-01

    High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. E

  15. Registering prostate external beam radiotherapy with a boost from high-dose-rate brachytherapy: a comparative evaluation of deformable registration algorithms.

    Science.gov (United States)

    Moulton, Calyn R; House, Michael J; Lye, Victoria; Tang, Colin I; Krawiec, Michele; Joseph, David J; Denham, James W; Ebert, Martin A

    2015-12-14

    Registering CTs for patients receiving external beam radiotherapy (EBRT) with a boost dose from high-dose-rate brachytherapy (HDR) can be challenging due to considerable image discrepancies (e.g. rectal fillings, HDR needles, HDR artefacts and HDR rectal packing materials). This study is the first to comparatively evaluate image processing and registration methods used to register the rectums in EBRT and HDR CTs of prostate cancer patients. The focus is on the rectum due to planned future analysis of rectal dose-volume response. For 64 patients, the EBRT CT was retrospectively registered to the HDR CT with rigid registration and non-rigid registration methods in VelocityAI. Image processing was undertaken on the HDR CT and the rigidly-registered EBRT CT to reduce the impact of discriminating features on alternative non-rigid registration methods applied in the software suite for Deformable Image Registration and Adaptive Radiotherapy Research (DIRART) using the Horn-Schunck optical flow and Demons algorithms. The propagated EBRT-rectum structures were compared with the HDR structure using the Dice similarity coefficient (DSC), Hausdorff distance (HD) and average surface distance (ASD). The image similarity was compared using mutual information (MI) and root mean squared error (MSE). The displacement vector field was assessed via the Jacobian determinant (JAC). The post-registration alignments of rectums for 21 patients were visually assessed. The greatest improvement in the median DSC relative to the rigid registration result was 35 % for the Horn-Schunck algorithm with image processing. This algorithm also provided the best ASD results. The VelocityAI algorithms provided superior HD, MI, MSE and JAC results. The visual assessment indicated that the rigid plus deformable multi-pass method within VelocityAI resulted in the best rectum alignment. The DSC, ASD and HD improved significantly relative to the rigid registration result if image processing was applied prior

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

    Science.gov (United States)

    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

  17. GPUs benchmarking in subpixel image registration algorithm

    Science.gov (United States)

    Sanz-Sabater, Martin; Picazo-Bueno, Jose Angel; Micó, Vicente; Ferrerira, Carlos; Granero, Luis; Garcia, Javier

    2015-05-01

    Image registration techniques are used among different scientific fields, like medical imaging or optical metrology. The straightest way to calculate shifting between two images is using the cross correlation, taking the highest value of this correlation image. Shifting resolution is given in whole pixels which cannot be enough for certain applications. Better results can be achieved interpolating both images, as much as the desired resolution we want to get, and applying the same technique described before, but the memory needed by the system is significantly higher. To avoid memory consuming we are implementing a subpixel shifting method based on FFT. With the original images, subpixel shifting can be achieved multiplying its discrete Fourier transform by a linear phase with different slopes. This method is high time consuming method because checking a concrete shifting means new calculations. The algorithm, highly parallelizable, is very suitable for high performance computing systems. GPU (Graphics Processing Unit) accelerated computing became very popular more than ten years ago because they have hundreds of computational cores in a reasonable cheap card. In our case, we are going to register the shifting between two images, doing the first approach by FFT based correlation, and later doing the subpixel approach using the technique described before. We consider it as `brute force' method. So we will present a benchmark of the algorithm consisting on a first approach (pixel resolution) and then do subpixel resolution approaching, decreasing the shifting step in every loop achieving a high resolution in few steps. This program will be executed in three different computers. At the end, we will present the results of the computation, with different kind of CPUs and GPUs, checking the accuracy of the method, and the time consumed in each computer, discussing the advantages, disadvantages of the use of GPUs.

  18. Learning-Based Tracking of Complex Non-Rigid Motion

    Institute of Scientific and Technical Information of China (English)

    Qiang Wang; Hai-Zhou Ai; Guang-You Xu

    2004-01-01

    This paper describes a novel method for tracking complex non-rigid motions by learning the intrinsic object structure.The approach builds on and extends the studies on non-linear dimensionality reduction for object representation,object dynamics modeling and particle filter style tracking.First,the dimensionality reduction and density estimation algorithm is derived for unsupervised learning of object intrinsic representation,and the obtained non-rigid part of object state reduces even to 2-3 dimensions.Secondly the dynamical model is derived and trained based on this intrinsic representation.Thirdly the learned intrinsic object structure is integrated into a particle filter style tracker.It is shown that this intrinsic object representation has some interesting properties and based on which the newly derived dynamical model makes particle filter style tracker more robust and reliable.Extensive experiments are done on the tracking of challenging non-rigid motions such as fish twisting with selfocclusion,large inter-frame lip motion and facial expressions with global head rotation.Quantitative results are given to make comparisons between the newly proposed tracker and the existing tracker.The proposed method also has the potential to solve other type of tracking problems.

  19. COMPARISON OF VOLUMETRIC REGISTRATION ALGORITHMS FOR TENSOR-BASED MORPHOMETRY

    Science.gov (United States)

    Villalon, Julio; Joshi, Anand A.; Toga, Arthur W.; Thompson, Paul M.

    2015-01-01

    Nonlinear registration of brain MRI scans is often used to quantify morphological differences associated with disease or genetic factors. Recently, surface-guided fully 3D volumetric registrations have been developed that combine intensity-guided volume registrations with cortical surface constraints. In this paper, we compare one such algorithm to two popular high-dimensional volumetric registration methods: large-deformation viscous fluid registration, formulated in a Riemannian framework, and the diffeomorphic “Demons” algorithm. We performed an objective morphometric comparison, by using a large MRI dataset from 340 young adult twin subjects to examine 3D patterns of correlations in anatomical volumes. Surface-constrained volume registration gave greater effect sizes for detecting morphometric associations near the cortex, while the other two approaches gave greater effects sizes subcortically. These findings suggest novel ways to combine the advantages of multiple methods in the future. PMID:26925198

  20. An Automatic Registration Algorithm for 3D Maxillofacial Model

    Science.gov (United States)

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

    2016-09-01

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

  1. Fast fluid registration of medical images

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten; Gramkow, Claus

    1996-01-01

    This paper offers a new fast algorithm for non-rigid viscous fluid registration of medical images that is at least an order of magnitude faster than the previous method by (Christensen et al., 1994). The core algorithm in the fluid registration method is based on a linear elastic deformation...... of the velocity field of the fluid. Using the linearity of this deformation we derive a convolution filter which we use in a scale-space framework. We also demonstrate that the `demon'-based registration method of (Thirion, 1996) can be seen as an approximation to the fluid registration method and point...

  2. Effect of registration on corpus callosum population differences found with DBM analysis

    Science.gov (United States)

    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. An improved SIFT algorithm based on KFDA in image registration

    Science.gov (United States)

    Chen, Peng; Yang, Lijuan; Huo, Jinfeng

    2016-03-01

    As a kind of stable feature matching algorithm, SIFT has been widely used in many fields. In order to further improve the robustness of the SIFT algorithm, an improved SIFT algorithm with Kernel Discriminant Analysis (KFDA-SIFT) is presented for image registration. The algorithm uses KFDA to SIFT descriptors for feature extraction matrix, and uses the new descriptors to conduct the feature matching, finally chooses RANSAC to deal with the matches for further purification. The experiments show that the presented algorithm is robust to image changes in scale, illumination, perspective, expression and tiny pose with higher matching accuracy.

  4. Automatic Image Registration Algorithm Based on Wavelet Transform

    Institute of Scientific and Technical Information of China (English)

    LIU Qiong; NI Guo-qiang

    2006-01-01

    An automatic image registration approach based on wavelet transform is proposed. This proposed method utilizes multiscale wavelet transform to extract feature points. A coarse-to-fine feature matching method is utilized in the feature matching phase. A two-way matching method based on cross-correlation to get candidate point pairs and a fine matching based on support strength combine to form the matching algorithm. At last, based on an affine transformation model, the parameters are iteratively refined by using the least-squares estimation approach. Experimental results have verified that the proposed algorithm can realize automatic registration of various kinds of images rapidly and effectively.

  5. 3D image registration using a fast noniterative algorithm.

    Science.gov (United States)

    Zhilkin, P; Alexander, M E

    2000-11-01

    This note describes the implementation of a three-dimensional (3D) registration algorithm, generalizing a previous 2D version [Alexander, Int J Imaging Systems and Technology 1999;10:242-57]. The algorithm solves an integrated form of linearized image matching equation over a set of 3D rectangular sub-volumes ('patches') in the image domain. This integrated form avoids numerical instabilities due to differentiation of a noisy image over a lattice, and in addition renders the algorithm robustness to noise. Registration is implemented by first convolving the unregistered images with a set of computationally fast [O(N)] filters, providing four bandpass images for each input image, and integrating the image matching equation over the given patch. Each filter and each patch together provide an independent set of constraints on the displacement field derived by solving a set of linear regression equations. Furthermore, the filters are implemented at a variety of spatial scales, enabling registration parameters at one scale to be used as an input approximation for deriving refined values of those parameters at a finer scale of resolution. This hierarchical procedure is necessary to avoid false matches occurring. Both downsampled and oversampled (undecimating) filtering is implemented. Although the former is computationally fast, it lacks the translation invariance of the latter. Oversampling is required for accurate interpolation that is used in intermediate stages of the algorithm to reconstruct the partially registered from the unregistered image. However, downsampling is useful, and computationally efficient, for preliminary stages of registration when large mismatches are present. The 3D registration algorithm was implemented using a 12-parameter affine model for the displacement: u(x) = Ax + b. Linear interpolation was used throughout. Accuracy and timing results for registering various multislice images, obtained by scanning a melon and human volunteers in various

  6. Evaluation of registration, compression and classification algorithms. Volume 1: Results

    Science.gov (United States)

    Jayroe, R.; Atkinson, R.; Callas, L.; Hodges, J.; Gaggini, B.; Peterson, J.

    1979-01-01

    The registration, compression, and classification algorithms were selected on the basis that such a group would include most of the different and commonly used approaches. The results of the investigation indicate clearcut, cost effective choices for registering, compressing, and classifying multispectral imagery.

  7. Manifold learning based registration algorithms applied to multimodal images.

    Science.gov (United States)

    Azampour, Mohammad Farid; Ghaffari, Aboozar; Hamidinekoo, Azam; Fatemizadeh, Emad

    2014-01-01

    Manifold learning algorithms are proposed to be used in image processing based on their ability in preserving data structures while reducing the dimension and the exposure of data structure in lower dimension. Multi-modal images have the same structure and can be registered together as monomodal images if only structural information is shown. As a result, manifold learning is able to transform multi-modal images to mono-modal ones and subsequently do the registration using mono-modal methods. Based on this application, in this paper novel similarity measures are proposed for multi-modal images in which Laplacian eigenmaps are employed as manifold learning algorithm and are tested against rigid registration of PET/MR images. Results show the feasibility of using manifold learning as a way of calculating the similarity between multimodal images.

  8. A modified iterative closest point algorithm for shape registration

    Science.gov (United States)

    Tihonkih, Dmitrii; Makovetskii, Artyom; Kuznetsov, Vladislav

    2016-09-01

    The iterative closest point (ICP) algorithm is one of the most popular approaches to shape registration. The algorithm starts with two point clouds and an initial guess for a relative rigid-body transformation between them. Then it iteratively refines the transformation by generating pairs of corresponding points in the clouds and by minimizing a chosen error metric. In this work, we focus on accuracy of the ICP algorithm. An important stage of the ICP algorithm is the searching of nearest neighbors. We propose to utilize for this purpose geometrically similar groups of points. Groups of points of the first cloud, that have no similar groups in the second cloud, are not considered in further error minimization. To minimize errors, the class of affine transformations is used. The transformations are not rigid in contrast to the classical approach. This approach allows us to get a precise solution for transformations such as rotation, translation vector and scaling. With the help of computer simulation, the proposed method is compared with common nearest neighbor search algorithms for shape registration.

  9. A hybrid genetic algorithm for multi-modal image registration

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    This paper describes a new method for three-dimensional medical image registration. In the interactive image-guided HIFU (High Intensity Focused Ultrasound) therapy system, a fast and precise localization of the tumor is very important. An automatic system is developed for registering pre-operative MR images with intra-operative ultrasound images based on the vessels visible in both of the modalities. When the MR and the ultrasound images are aligned, the centerline points of the vessels in the MR image will align with bright intensities in the ultrasound image. The method applies an optimization strategy combining the genetic algorithm with the conjugated gradients algorithm to minimize the objective function. It provides a feasible way of determining the global solution and makes the method robust to local maximum and insensitive to initial position. Two experiments were designed to evaluate the method, and the results show that our method has better registration accuracy and convergence rate than the other two classic algorithms.

  10. Fast registration algorithm using a variational principle for mutual information

    Science.gov (United States)

    Alexander, Murray E.; Summers, Randy

    2003-05-01

    A method is proposed for cross-modal image registration based on mutual information (MI) matching criteria. Both conventional and "normalized" MI are considered. MI may be expressed as a functional of a general image displacement field u. The variational principle for MI provides a field equation for u. The method employs a set of "registration points" consisting of a prescribed number of strongest edge points of the reference image, and minimizes an objective function D defined as the sum of the square residuals of the field equation for u at these points, where u is expressed as a sum over a set of basis functions (the affine model is presented here). D has a global minimum when the images are aligned, with a "basin of attraction" typically of width ~0.3 pixels. By pre-filtering with a low-pass filter, and using a multiresolution image pyramid, the basin may be significantly widened. The Levenberg-Marquardt algorithm is used to minimize D. Tests using randomly distributed misalignments of image pairs show that registration accuracy of 0.02 - 0.07 pixels is achieved, when using cubic B-splines for image representation, interpolation, and Parzen window estimation.

  11. Constrained branch-and-bound algorithm for image registration

    Institute of Scientific and Technical Information of China (English)

    JIN Jian-qiu; WANG Zhang-ye; PENG Qun-sheng

    2005-01-01

    In this paper, the authors propose a refined Branch-and-Bound algorithm for affine-transformation based image registration. Given two feature point-sets in two images respectively, the authors first extract a sequence of high-probability matched point-pairs by considering well-defined features. Each resultant point-pair can be regarded as a constraint in the search space of Branch-and-Bound algorithm guiding the search process. The authors carry out Branch-and-Bound search with the constraint of a pair-point selected by using Monte Carlo sampling according to the match measures of point-pairs. If such one cannot lead to correct result, additional candidate is chosen to start another search. High-probability matched point-pairs usually results in fewer loops and the search process is accelerated greatly. Experimental results verify the high efficiency and robustness of the author's approach.

  12. A Parallel Nonrigid Registration Algorithm Based on B-Spline for Medical Images

    Directory of Open Access Journals (Sweden)

    Xiaogang Du

    2016-01-01

    Full Text Available The nonrigid registration algorithm based on B-spline Free-Form Deformation (FFD plays a key role and is widely applied in medical image processing due to the good flexibility and robustness. However, it requires a tremendous amount of computing time to obtain more accurate registration results especially for a large amount of medical image data. To address the issue, a parallel nonrigid registration algorithm based on B-spline is proposed in this paper. First, the Logarithm Squared Difference (LSD is considered as the similarity metric in the B-spline registration algorithm to improve registration precision. After that, we create a parallel computing strategy and lookup tables (LUTs to reduce the complexity of the B-spline registration algorithm. As a result, the computing time of three time-consuming steps including B-splines interpolation, LSD computation, and the analytic gradient computation of LSD, is efficiently reduced, for the B-spline registration algorithm employs the Nonlinear Conjugate Gradient (NCG optimization method. Experimental results of registration quality and execution efficiency on the large amount of medical images show that our algorithm achieves a better registration accuracy in terms of the differences between the best deformation fields and ground truth and a speedup of 17 times over the single-threaded CPU implementation due to the powerful parallel computing ability of Graphics Processing Unit (GPU.

  13. Fast point cloud registration algorithm using multiscale angle features

    Science.gov (United States)

    Lu, Jun; Guo, Congling; Fang, Ying; Xia, Guihua; Wang, Wanjia; Elahi, Ahsan

    2017-05-01

    To fulfill the demands of rapid and real-time three-dimensional optical measurement, a fast point cloud registration algorithm using multiscale axis angle features is proposed. The key point is selected based on the mean value of scalar projections of the vectors from the estimated point to the points in the neighborhood on the normal of the estimated point. This method has a small amount of computation and good discriminating ability. A rotation invariant feature is proposed using the angle information calculated based on multiscale coordinate axis. The feature descriptor of a key point is computed using cosines of the angles between corresponding coordinate axes. Using this method, the surface information around key points is obtained sufficiently in three axes directions and it is easy to recognize. The similarity of descriptors is employed to quickly determine the initial correspondences. The rigid spatial distance invariance and clustering selection method are used to make the corresponding relationships more accurate and evenly distributed. Finally, the rotation matrix and translation vector are determined using the method of singular value decomposition. Experimental results show that the proposed algorithm has high precision, fast matching speed, and good antinoise capability.

  14. Registration algorithm for sensor alignment based on stochastic fuzzy neural network

    Institute of Scientific and Technical Information of China (English)

    Li Jiao; Jing Zhongliang; He Jiaona; Wang An

    2005-01-01

    Multiple sensor registration is an important link in multi-sensors data fusion. The existed algorithm is all based on the assumption that system errors come from a fixed deviation set. But there are many other factors, which can result system errors. So traditional registration algorithms have limitation. This paper presents a registration algorithm for sensor alignment based on stochastic fuzzy neural network (SNFF), and utilized fuzzy clustering algorithm obtaining the number of fuzzy rules. Finally, the simulative result illuminate that this way could gain a satisfing result.

  15. A New Extended Projection-Based Image Registration Algorithm

    Institute of Scientific and Technical Information of China (English)

    CHENHuafu; YAODezhong

    2005-01-01

    In the presence of fixed -pattern noise, the projection-based image registration technique is effective but its implementation is only confined to translation registration. Presented in this paper is an extended projectionbased image registration technique in which, by rearranging the projections of images, the image registration is implemented in two steps: rotation and translation, to accomplish two-dimensional (2-D) image registration. Thisapproach transforms the general 2-D optimization procedure into an 1-D projection optimization, thus considerably reducing the amount of computation. The validity ofthe new method is testified by simulation experiment.

  16. Medical Image Registration and Surgery Simulation

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten

    1996-01-01

    This thesis explores the application of physical models in medical image registration and surgery simulation. The continuum models of elasticity and viscous fluids are described in detail, and this knowledge is used as a basis for most of the methods described here. Real-time deformable models......, and the use of selective matrix vector multiplication. Fluid medical image registration A new and faster algorithm for non-rigid registration using viscous fluid models is presented. This algorithm replaces the core part of the original algorithm with multi-resolution convolution using a new filter, which...... for surgery simulation Real-time deformable models, using finite element models of linear elasticity, have been developed for surgery simulation. The time consumption of the finite element method is reduced dramaticly, by the use of condensation techniques, explicit inversion of the stiffness matrix...

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

    Science.gov (United States)

    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.

  18. List-mode-based reconstruction for respiratory motion correction in PET using non-rigid body transformations

    Energy Technology Data Exchange (ETDEWEB)

    Lamare, F [INSERM, U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), Brest, F-29200 (France); Carbayo, M J Ledesma [ETSI Telecomunicacion Universidad Politecnica de Madrid, Ciudad Universitaria s/n 28040, Madrid (Spain); Cresson, T [INSERM, U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), Brest, F-29200 (France); Kontaxakis, G [ETSI Telecomunicacion Universidad Politecnica de Madrid, Ciudad Universitaria s/n 28040, Madrid (Spain); Santos, A [ETSI Telecomunicacion Universidad Politecnica de Madrid, Ciudad Universitaria s/n 28040, Madrid (Spain); Rest, C Cheze Le [INSERM, U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), Brest, F-29200 (France); Reader, A J [School of Chemical Engineering and Analytical Science, University of Manchester, Manchester (United Kingdom); Visvikis, D [INSERM, U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), Brest, F-29200 (France)

    2007-09-07

    Respiratory motion in emission tomography leads to reduced image quality. Developed correction methodology has been concentrating on the use of respiratory synchronized acquisitions leading to gated frames. Such frames, however, are of low signal-to-noise ratio as a result of containing reduced statistics. In this work, we describe the implementation of an elastic transformation within a list-mode-based reconstruction for the correction of respiratory motion over the thorax, allowing the use of all data available throughout a respiratory motion average acquisition. The developed algorithm was evaluated using datasets of the NCAT phantom generated at different points throughout the respiratory cycle. List-mode-data-based PET-simulated frames were subsequently produced by combining the NCAT datasets with Monte Carlo simulation. A non-rigid registration algorithm based on B-spline basis functions was employed to derive transformation parameters accounting for the respiratory motion using the NCAT dynamic CT images. The displacement matrices derived were subsequently applied during the image reconstruction of the original emission list mode data. Two different implementations for the incorporation of the elastic transformations within the one-pass list mode EM (OPL-EM) algorithm were developed and evaluated. The corrected images were compared with those produced using an affine transformation of list mode data prior to reconstruction, as well as with uncorrected respiratory motion average images. Results demonstrate that although both correction techniques considered lead to significant improvements in accounting for respiratory motion artefacts in the lung fields, the elastic-transformation-based correction leads to a more uniform improvement across the lungs for different lesion sizes and locations.

  19. Non-rigid Reconstruction of Casting Process with Temperature Feature

    Science.gov (United States)

    Lin, Jinhua; Wang, Yanjie; Li, Xin; Wang, Ying; Wang, Lu

    2017-09-01

    Off-line reconstruction of rigid scene has made a great progress in the past decade. However, the on-line reconstruction of non-rigid scene is still a very challenging task. The casting process is a non-rigid reconstruction problem, it is a high-dynamic molding process lacking of geometric features. In order to reconstruct the casting process robustly, an on-line fusion strategy is proposed for dynamic reconstruction of casting process. Firstly, the geometric and flowing feature of casting are parameterized in manner of TSDF (truncated signed distance field) which is a volumetric block, parameterized casting guarantees real-time tracking and optimal deformation of casting process. Secondly, data structure of the volume grid is extended to have temperature value, the temperature interpolation function is build to generate the temperature of each voxel. This data structure allows for dynamic tracking of temperature of casting during deformation stages. Then, the sparse RGB features is extracted from casting scene to search correspondence between geometric representation and depth constraint. The extracted color data guarantees robust tracking of flowing motion of casting. Finally, the optimal deformation of the target space is transformed into a nonlinear regular variational optimization problem. This optimization step achieves smooth and optimal deformation of casting process. The experimental results show that the proposed method can reconstruct the casting process robustly and reduce drift in the process of non-rigid reconstruction of casting.

  20. Automated registration of freehand B-mode ultrasound and magnetic resonance imaging of the carotid arteries based on geometric features

    DEFF Research Database (Denmark)

    Carvalho, Diego D. B.; Arias Lorza, Andres Mauricio; Niessen, Wiro J.;

    2017-01-01

    An automated method for registering B-mode ultrasound (US) and magnetic resonance imaging (MRI) of the carotid arteries is proposed. The registration uses geometric features, namely, lumen centerlines and lumen segmentations, which are extracted fully automatically from the images after manual...... annotation of three seed points in US and MRI. The registration procedure starts with alignment of the lumen centerlines using a point-based registration algorithm. The resulting rigid transformation is used to initialize a rigid and subsequent non-rigid registration procedure that jointly aligns centerlines...

  1. Performance evaluation of grid-enabled registration algorithms using bronze-standards

    CERN Document Server

    Glatard, T; Montagnat, J

    2006-01-01

    Evaluating registration algorithms is difficult due to the lack of gold standard in most clinical procedures. The bronze standard is a real-data based statistical method providing an alternative registration reference through a computationally intensive image database registration procedure. We propose in this paper an efficient implementation of this method through a grid-interfaced workflow enactor enabling the concurrent processing of hundreds of image registrations in a couple of hours only. The performances of two different grid infrastructures were compared. We computed the accuracy of 4 different rigid registration algorithms on longitudinal MRI images of brain tumors. Results showed an average subvoxel accuracy of 0.4 mm and 0.15 degrees in rotation.

  2. MREG V1.1 : a multi-scale image registration algorithm for SAR applications.

    Energy Technology Data Exchange (ETDEWEB)

    Eichel, Paul H.

    2013-08-01

    MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962 leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.

  3. Full Non-Rigid Group and Symmetry of Dimethyltrichlorophosphorus

    Institute of Scientific and Technical Information of China (English)

    ASHRAFI; AliReza

    2005-01-01

    In this work, a simple method is described, by means of which it is possible to calculate character tables for the symmetry group of molecules consisting of a number of NH3 groups attached to a rigid framework. The full non-rigid group (f-NRG) of dimethyltrichlorophosphorus with the symmetry group D3h was studied. It has been proven that it is a group of order 216 with 27 conjugacy classes and its character table computed. Finally, the Permutation-lnversion group of this molecule was calculated.

  4. Non-Rigid Object Tracking by Anisotropic Kernel Mean Shift

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Mean shift, an iterative procedure that shifts each data point to the average of data points in its neighborhood, has been applied to object tracker. However, the traditional mean shift tracker by isotropic kernel often loses the object with the changing object structure in video sequences, especially when the object structure varies fast. This paper proposes a non-rigid object tracker by anisotropic kernel mean shift in which the shape, scale, and orientation of the kernels adapt to the changing object structure. The experimental results show that the new tracker is self-adaptive and approximately twice faster than the traditional tracker, which ensures the robustness and real time of tracking.

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

    Energy Technology Data Exchange (ETDEWEB)

    Han, T; Gifford, K [UT MD Anderson Cancer Center, Houston, TX (United States); Smith, B [MD Anderson Cancer Center, Houston, TX (United States); Salehpour, M [M.D. Anderson Cancer Center, Houston, TX (United States)

    2014-06-01

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

  6. Nonrigid registration algorithm for longitudinal breast MR images and the preliminary analysis of breast tumor response

    Science.gov (United States)

    Li, Xia; Dawant, Benoit M.; Welch, E. Brian; Chakravarthy, A. Bapsi; Freehardt, Darla; Mayer, Ingrid; Kelley, Mark; Meszoely, Ingrid; Gore, John C.; Yankeelov, Thomas E.

    2009-02-01

    Although useful for the detection of breast cancers, conventional imaging methods, including mammography and ultrasonography, do not provide adequate information regarding response to therapy. Dynamic contrast enhanced MRI (DCE-MRI) has emerged as a promising technique to provide relevant information on tumor status. Consequently, accurate longitudinal registration of breast MR images is critical for the comparison of changes induced by treatment at the voxel level. In this study, a nonrigid registration algorithm is proposed to allow for longitudinal registration of breast MR images obtained throughout the course of treatment. We accomplish this by modifying the adaptive bases algorithm (ABA) through adding a tumor volume preserving constraint in the cost function. The registration results demonstrate the proposed algorithm can successfully register the longitudinal breast MR images and permit analysis of the parameter maps. We also propose a novel validation method to evaluate the proposed registration algorithm quantitatively. These validations also demonstrate that the proposed algorithm constrains tumor deformation well and performs better than the unconstrained ABA algorithm.

  7. Sequential Non-Rigid Structure from Motion Using Physical Priors.

    Science.gov (United States)

    Agudo, Antonio; Moreno-Noguer, Francesc; Calvo, Begona; Montiel, Jose M Martinez

    2016-05-01

    We propose a new approach to simultaneously recover camera pose and 3D shape of non-rigid and potentially extensible surfaces from a monocular image sequence. For this purpose, we make use of the Extended Kalman Filter based Simultaneous Localization And Mapping (EKF-SLAM) formulation, a Bayesian optimization framework traditionally used in mobile robotics for estimating camera pose and reconstructing rigid scenarios. In order to extend the problem to a deformable domain we represent the object's surface mechanics by means of Navier's equations, which are solved using a Finite Element Method (FEM). With these main ingredients, we can further model the material's stretching, allowing us to go a step further than most of current techniques, typically constrained to surfaces undergoing isometric deformations. We extensively validate our approach in both real and synthetic experiments, and demonstrate its advantages with respect to competing methods. More specifically, we show that besides simultaneously retrieving camera pose and non-rigid shape, our approach is adequate for both isometric and extensible surfaces, does not require neither batch processing all the frames nor tracking points over the whole sequence and runs at several frames per second.

  8. GPU-accelerated Block Matching Algorithm for Deformable Registration of Lung CT Images.

    Science.gov (United States)

    Li, Min; Xiang, Zhikang; Xiao, Liang; Castillo, Edward; Castillo, Richard; Guerrero, Thomas

    2015-12-01

    Deformable registration (DR) is a key technology in the medical field. However, many of the existing DR methods are time-consuming and the registration accuracy needs to be improved, which prevents their clinical applications. In this study, we propose a parallel block matching algorithm for lung CT image registration, in which the sum of squared difference metric is modified as the cost function and the moving least squares approach is used to generate the full displacement field. The algorithm is implemented on Graphic Processing Unit (GPU) with the Compute Unified Device Architecture (CUDA). Results show that the proposed parallel block matching method achieves a fast runtime while maintaining an average registration error (standard deviation) of 1.08 (0.69) mm.

  9. A novel scheme for automatic nonrigid image registration using deformation invariant feature and geometric constraint

    Science.gov (United States)

    Deng, Zhipeng; Lei, Lin; Zhou, Shilin

    2015-10-01

    Automatic image registration is a vital yet challenging task, particularly for non-rigid deformation images which are more complicated and common in remote sensing images, such as distorted UAV (unmanned aerial vehicle) images or scanning imaging images caused by flutter. Traditional non-rigid image registration methods are based on the correctly matched corresponding landmarks, which usually needs artificial markers. It is a rather challenging task to locate the accurate position of the points and get accurate homonymy point sets. In this paper, we proposed an automatic non-rigid image registration algorithm which mainly consists of three steps: To begin with, we introduce an automatic feature point extraction method based on non-linear scale space and uniform distribution strategy to extract the points which are uniform distributed along the edge of the image. Next, we propose a hybrid point matching algorithm using DaLI (Deformation and Light Invariant) descriptor and local affine invariant geometric constraint based on triangulation which is constructed by K-nearest neighbor algorithm. Based on the accurate homonymy point sets, the two images are registrated by the model of TPS (Thin Plate Spline). Our method is demonstrated by three deliberately designed experiments. The first two experiments are designed to evaluate the distribution of point set and the correctly matching rate on synthetic data and real data respectively. The last experiment is designed on the non-rigid deformation remote sensing images and the three experimental results demonstrate the accuracy, robustness, and efficiency of the proposed algorithm compared with other traditional methods.

  10. Non-rigid Motion Correction in 3D Using Autofocusing with Localized Linear Translations

    Science.gov (United States)

    Cheng, Joseph Y.; Alley, Marcus T.; Cunningham, Charles H.; Vasanawala, Shreyas S.; Pauly, John M.; Lustig, Michael

    2012-01-01

    MR scans are sensitive to motion effects due to the scan duration. To properly suppress artifacts from non-rigid body motion, complex models with elements such as translation, rotation, shear, and scaling have been incorporated into the reconstruction pipeline. However, these techniques are computationally intensive and difficult to implement for online reconstruction. On a sufficiently small spatial scale, the different types of motion can be well-approximated as simple linear translations. This formulation allows for a practical autofocusing algorithm that locally minimizes a given motion metric – more specifically, the proposed localized gradient-entropy metric. To reduce the vast search space for an optimal solution, possible motion paths are limited to the motion measured from multi-channel navigator data. The novel navigation strategy is based on the so-called “Butterfly” navigators which are modifications to the spin-warp sequence that provide intrinsic translational motion information with negligible overhead. With a 32-channel abdominal coil, sufficient number of motion measurements were found to approximate possible linear motion paths for every image voxel. The correction scheme was applied to free-breathing abdominal patient studies. In these scans, a reduction in artifacts from complex, non-rigid motion was observed. PMID:22307933

  11. A Contour-Guided Deformable Image Registration Algorithm for Adaptive Radiotherapy

    CERN Document Server

    Gu, Xuejun; Wang, Jing; Yordy, John; Mell, Loren; Jia, Xun; Jiang, Steve B

    2013-01-01

    In adaptive radiotherapy, deformable image registration is often conducted between the planning CT and treatment CT (or cone beam CT) to generate a deformation vector field (DVF) for dose accumulation and contour propagation. The auto propagated contours on the treatment CT may contain relatively large errors, especially in low contrast regions. A clinician inspection and editing of the propagated contours are frequently needed. The edited contours are able to meet the clinical requirement for adaptive therapy; however, the DVF is still inaccurate and inconsistent with the edited contours. The purpose of this work is to develop a contour-guided deformable image registration (CG-DIR) algorithm to improve the accuracy and consistency of the DVF for adaptive radiotherapy. Incorporation of the edited contours into the registration algorithm is realized by regularizing the objective function of the original demons algorithm with a term of intensity matching between the delineated structures set pairs. The CG-DIR a...

  12. Medical image registration algorithms assesment Bronze Standard application enactment on grids using the MOTEUR workflow engine

    CERN Document Server

    Glatard, T; Pennec, X

    2006-01-01

    Medical image registration is pre-processing needed for many medical image analysis procedures. A very large number of registration algorithms are available today, but their performance is often not known and very difficult to assess due to the lack of gold standard. The Bronze Standard algorithm is a very data and compute intensive statistical approach for quantifying registration algorithms accuracy. In this paper, we describe the Bronze Standard application and we discuss the need for grids to tackle such computations on medical image databases. We demonstrate MOTEUR, a service-based workflow engine optimized for dealing with data intensive applications. MOTEUR eases the enactment of the Bronze Standard and similar applications on the EGEE production grid infrastructure. It is a generic workflow engine, based on current standards and freely available, that can be used to instrument legacy application code at low cost.

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

    Energy Technology Data Exchange (ETDEWEB)

    Inoue, Minoru; Yoshimura, Michio, E-mail: myossy@kuhp.kyoto-u.ac.jp; Sato, Sayaka; Nakamura, Mitsuhiro; Yamada, Masahiro; Hirata, Kimiko; Ogura, Masakazu; Hiraoka, Masahiro [Department of Radiation Oncology and Image-Applied Therapy, Kyoto University Graduate School of Medicine, Kyoto 606-8507 (Japan); Sasaki, Makoto; Fujimoto, Takahiro [Division of Clinical Radiology Service, Kyoto University Hospital, Kyoto 606-8507 (Japan)

    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.

  14. A Practical Approach Based on Analytic Deformable Algorithm for Scenic Image Registration.

    Directory of Open Access Journals (Sweden)

    Wei-Yen Hsu

    Full Text Available Image registration is to produce an entire scene by aligning all the acquired image sequences. A registration algorithm is necessary to tolerance as much as possible for intensity and geometric variation among images. However, captured image views of real scene usually produce unexpected distortions. They are generally derived from the optic characteristics of image sensors or caused by the specific scenes and objects.An analytic registration algorithm considering the deformation is proposed for scenic image applications in this study. After extracting important features by the wavelet-based edge correlation method, an analytic registration approach is then proposed to achieve deformable and accurate matching of point sets. Finally, the registration accuracy is further refined to obtain subpixel precision by a feature-based Levenberg-Marquardt (FLM method. It converges evidently faster than most other methods because of its feature-based characteristic.We validate the performance of proposed method by testing with synthetic and real image sequences acquired by a hand-held digital still camera (DSC and in comparison with an optical flow-based motion technique in terms of the squared sum of intensity differences (SSD and correlation coefficient (CC. The results indicate that the proposed method is satisfactory in the registration accuracy and quality of DSC images.

  15. Automatic multi-resolution image registration based on genetic algorithm and Hausdorff distance

    Institute of Scientific and Technical Information of China (English)

    Famao Ye; Lin Su; Shukai Li

    2006-01-01

    @@ Image registration is a crucial step in all image analysis tasks in which the final information is gained from the combination of various data sources, and it is difficult to automatically register due to the complexity of image. An approach based on genetic algorithm and Hausdorff distance to automatic image registration is presented. We use a multi-resolution edge tracker to find out the fine-quality edges and utilize the Hausdorff distance between the input image and the reference image as similarity measure. We use wavelet decomposition and genetic algorithm, which combine local search methods with global ones balancing exploration and exploitation, to speed up the search of the best transformation parameters.Experimental results show that the proposed approach is a promising method for registration of image.

  16. A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

    Directory of Open Access Journals (Sweden)

    W. Lu

    2017-09-01

    Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  17. a SAR Image Registration Method Based on Sift Algorithm

    Science.gov (United States)

    Lu, W.; Yue, X.; Zhao, Y.; Han, C.

    2017-09-01

    In order to improve the stability and rapidity of synthetic aperture radar (SAR) images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  18. Validation of experts versus atlas-based and automatic registration methods for subthalamic nucleus targeting on MRI

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez Castro, F.J.; Cuisenaire, O.; Thiran, J.P. [Ecole Polytechnique Federale de Lausanne (EPFL) (Switzerland). Signal Processing Inst.; Pollo, C. [Ecole Polytechnique Federale de Lausanne (EPFL) (Switzerland). Signal Processing Inst.; Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne (Switzerland). Dept. of Neurosurgery; Villemure, J.G. [Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne (Switzerland). Dept. of Neurosurgery

    2006-03-15

    Objects: In functional stereotactic neurosurgery, one of the cornerstones upon which the success and the operating time depends is an accurate targeting. The subthalamic nucleus (STN) is the usual target involved when applying deep brain stimulation for Parkinson's disease (PD). Unfortunately, STN is usually not clearly visible in common medical imaging modalities, which justifies the use of atlas-based segmentation techniques to infer the STN location. Materials and methods: Eight bilaterally implanted PD patients were included in this study. A three-dimensional T1-weighted sequence and inversion recovery T2-weighted coronal slices were acquired pre-operatively. We propose a methodology for the construction of a ground truth of the STN location and a scheme that allows both, to perform a comparison between different non-rigid registration algorithms and to evaluate their usability to locate the STN automatically. Results: The intra-expert variability in identifying the STN location is 1.06{+-}0.61 mm while the best non-rigid registration method gives an error of 1.80{+-}0.62 mm. On the other hand, statistical tests show that an affine registration with only 12 degrees of freedom is not enough for this application. Conclusions: Using our validation-evaluation scheme, we demonstrate that automatic STN localization is possible and accurate with non-rigid registration algorithms. (orig.)

  19. Algorithm for image registration and clutter and jitter noise reduction

    Energy Technology Data Exchange (ETDEWEB)

    Brower, K.L.

    1997-02-01

    This paper presents an analytical, computational method whereby two-dimensional images of an optical source represented in terms of a set of detector array signals can be registered with respect to a reference set of detector array signals. The detector image is recovered from the detector array signals and represented over a local region by a fourth order, two-dimensional taylor series. This local detector image can then be registered by a general linear transformation with respect to a reference detector image. The detector signal in the reference frame is reconstructed by integrating this detector image over the respective reference pixel. For cases in which the general linear transformation is uncertain by up to plus-or-minus two pixels, the general linear transformation can be determined by least squares fitting the detector image to the reference detector image. This registration process reduces clutter and jitter noise to a level comparable to the electronic noise level of the detector system. Test results with and without electronic noise using an analytical test function are presented.

  20. A Condition Number for Non-Rigid Shape Matching

    KAUST Repository

    Ovsjanikov, Maks

    2011-08-01

    © 2011 The Author(s). Despite the large amount of work devoted in recent years to the problem of non-rigid shape matching, practical methods that can successfully be used for arbitrary pairs of shapes remain elusive. In this paper, we study the hardness of the problem of shape matching, and introduce the notion of the shape condition number, which captures the intuition that some shapes are inherently more difficult to match against than others. In particular, we make a connection between the symmetry of a given shape and the stability of any method used to match it while optimizing a given distortion measure. We analyze two commonly used classes of methods in deformable shape matching, and show that the stability of both types of techniques can be captured by the appropriate notion of a condition number. We also provide a practical way to estimate the shape condition number and show how it can be used to guide the selection of landmark correspondences between shapes. Thus we shed some light on the reasons why general shape matching remains difficult and provide a way to detect and mitigate such difficulties in practice.

  1. a Novel Image Registration Algorithm for SAR and Optical Images Based on Virtual Points

    Science.gov (United States)

    Ai, C.; Feng, T.; Wang, J.; Zhang, S.

    2013-07-01

    Optical image is rich in spectral information, while SAR instrument can work in both day and night and obtain images through fog and clouds. Combination of these two types of complementary images shows the great advantages of better image interpretation. Image registration is an inevitable and critical problem for the applications of multi-source remote sensing images, such as image fusion, pattern recognition and change detection. However, the different characteristics between SAR and optical images, which are due to the difference in imaging mechanism and the speckle noises in SAR image, bring great challenges to the multi-source image registration. Therefore, a novel image registration algorithm based on the virtual points, derived from the corresponding region features, is proposed in this paper. Firstly, image classification methods are adopted to extract closed regions from SAR and optical images respectively. Secondly, corresponding region features are matched by constructing cost function with rotate invariant region descriptors such as area, perimeter, and the length of major and minor axes. Thirdly, virtual points derived from corresponding region features, such as the centroids, endpoints and cross points of major and minor axes, are used to calculate initial registration parameters. Finally, the parameters are corrected by an iterative calculation, which will be terminated when the overlap of corresponding region features reaches its maximum. In the experiment, WordView-2 and Radasat-2 with 0.5 m and 4.7 m spatial resolution respectively, obtained in August 2010 in Suzhou, are used to test the registration method. It is shown that the multi-source image registration algorithm presented above is effective, and the accuracy of registration is up to pixel level.

  2. Deformable mesh registration for the validation of automatic target localization algorithms

    Science.gov (United States)

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

    2013-01-01

    Purpose: To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation therapy. Methods: DMR was implemented in a hierarchical model, with rigid, affine, and B-spline transforms optimized in succession to register a pair of surface meshes. The gross tumor volumes (primary tumor and involved lymph nodes) were contoured by a physician on weekly CT scans in a cohort of lung cancer patients and converted to surface meshes. The meshes from weekly CT images were registered to the mesh from the planning CT, and the resulting registered meshes were compared with the delineated surfaces. Known deformations were also applied to the meshes, followed by mesh registration to recover the known deformation. Mesh registration accuracy was assessed at the mesh surface by computing the symmetric surface distance (SSD) between vertices of each registered mesh pair. Mesh registration quality in regions within 5 mm of the mesh surface was evaluated with respect to a high quality deformable image registration. Results: For 18 patients presenting with a total of 19 primary lung tumors and 24 lymph node targets, the SSD averaged 1.3 ± 0.5 and 0.8 ± 0.2 mm, respectively. Vertex registration errors (VRE) relative to the applied known deformation were 0.8 ± 0.7 and 0.2 ± 0.3 mm for the primary tumor and lymph nodes, respectively. Inside the mesh surface, corresponding average VRE ranged from 0.6 to 0.9 and 0.2 to 0.9 mm, respectively. Outside the mesh surface, average VRE ranged from 0.7 to 1.8 and 0.2 to 1.4 mm. The magnitude of errors generally increased with increasing distance away from the mesh. Conclusions: Provided that delineated surfaces are available, deformable mesh registration is an accurate and reliable method for obtaining a reference registration to validate automatic target registration algorithms for image-guided radiation therapy, specifically in regions on or near the target surfaces

  3. Implementation of Image Registration Algorithms for Real-time Target Tracking Through Video Sequences

    Directory of Open Access Journals (Sweden)

    Jharna Majumdar

    2002-07-01

    Full Text Available "Automatic detection and tracking of interesting targets from a sequence of images obtained from a reconnaissance platform is an interesting area of research for defence-related applications. Image registration is the basic step used in target tracking application. The paper briefly reviews some of the image registration algorithms, analyse their performance using a suitable image processing hardware, and selects the most suitable algorithm for a real-time target tracking application using cubic-spline model and spline model Kalman filter for the prediction of an occluded target. The algorithms developed are implemented in a ground-based image exploitation system (GIES developed at the Aeronautical Development Establishment for unmanned aerial vehicle application, and the results presented for the images obtained during actual flight trial.

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

    Science.gov (United States)

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

    2013-11-04

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

  5. Sensitivity study of voxel-based PET image comparison to image registration algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Yip, Stephen, E-mail: syip@lroc.harvard.edu; Chen, Aileen B.; Berbeco, Ross [Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 (United States); Aerts, Hugo J. W. L. [Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 and Department of Radiology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115 (United States)

    2014-11-01

    Purpose: Accurate deformable registration is essential for voxel-based comparison of sequential positron emission tomography (PET) images for proper adaptation of treatment plan and treatment response assessment. The comparison may be sensitive to the method of deformable registration as the optimal algorithm is unknown. This study investigated the impact of registration algorithm choice on therapy response evaluation. Methods: Sixteen patients with 20 lung tumors underwent a pre- and post-treatment computed tomography (CT) and 4D FDG-PET scans before and after chemoradiotherapy. All CT images were coregistered using a rigid and ten deformable registration algorithms. The resulting transformations were then applied to the respective PET images. Moreover, the tumor region defined by a physician on the registered PET images was classified into progressor, stable-disease, and responder subvolumes. Particularly, voxels with standardized uptake value (SUV) decreases >30% were classified as responder, while voxels with SUV increases >30% were progressor. All other voxels were considered stable-disease. The agreement of the subvolumes resulting from difference registration algorithms was assessed by Dice similarity index (DSI). Coefficient of variation (CV) was computed to assess variability of DSI between individual tumors. Root mean square difference (RMS{sub rigid}) of the rigidly registered CT images was used to measure the degree of tumor deformation. RMS{sub rigid} and DSI were correlated by Spearman correlation coefficient (R) to investigate the effect of tumor deformation on DSI. Results: Median DSI{sub rigid} was found to be 72%, 66%, and 80%, for progressor, stable-disease, and responder, respectively. Median DSI{sub deformable} was 63%–84%, 65%–81%, and 82%–89%. Variability of DSI was substantial and similar for both rigid and deformable algorithms with CV > 10% for all subvolumes. Tumor deformation had moderate to significant impact on DSI for progressor

  6. Fast pixel-wise adaptive visual tracking of non-rigid objects.

    Science.gov (United States)

    Duffner, Stefan; Garcia, Christophe

    2017-03-01

    In this paper, we present a new algorithm for realtime single-object tracking in videos in unconstrained environments. The algorithm comprises two different components that are trained "in one shot" at the first video frame: a detector that makes use of the generalised Hough transform with colour and gradient descriptors, and a probabilistic segmentation method based on global models for foreground and background colour distributions. Both components work at pixel level and are used for tracking in a combined way adapting each other in a cotraining manner. Moreover, we propose an adaptive shape model as well as a new probabilistic method for updating the scale of the tracker. Through effective model adaptation and segmentation, the algorithm is able to track objects that undergo rigid and non-rigid deformations and considerable shape and appearance variations. The proposed tracking method has been thoroughly evaluated on challenging benchmarks, and outperforms state-ofthe- art tracking methods designed for the same task. Finally, a very efficient implementation of the proposed models allows for extremely fast tracking.

  7. Validation of an accelerated 'demons' algorithm for deformable image registration in radiation therapy

    Science.gov (United States)

    Wang, He; Dong, Lei; O'Daniel, Jennifer; Mohan, Radhe; Garden, Adam S.; Kian Ang, K.; Kuban, Deborah A.; Bonnen, Mark; Chang, Joe Y.; Cheung, Rex

    2005-06-01

    A greyscale-based fully automatic deformable image registration algorithm, originally known as the 'demons' algorithm, was implemented for CT image-guided radiotherapy. We accelerated the algorithm by introducing an 'active force' along with an adaptive force strength adjustment during the iterative process. These improvements led to a 40% speed improvement over the original algorithm and a high tolerance of large organ deformations. We used three methods to evaluate the accuracy of the algorithm. First, we created a set of mathematical transformations for a series of patient's CT images. This provides a 'ground truth' solution for quantitatively validating the deformable image registration algorithm. Second, we used a physically deformable pelvic phantom, which can measure deformed objects under different conditions. The results of these two tests allowed us to quantify the accuracy of the deformable registration. Validation results showed that more than 96% of the voxels were within 2 mm of their intended shifts for a prostate and a head-and-neck patient case. The mean errors and standard deviations were 0.5 mm ± 1.5 mm and 0.2 mm ± 0.6 mm, respectively. Using the deformable pelvis phantom, the result showed a tracking accuracy of better than 1.5 mm for 23 seeds implanted in a phantom prostate that was deformed by inflation of a rectal balloon. Third, physician-drawn contours outlining the tumour volumes and certain anatomical structures in the original CT images were deformed along with the CT images acquired during subsequent treatments or during a different respiratory phase for a lung cancer case. Visual inspection of the positions and shapes of these deformed contours agreed well with human judgment. Together, these results suggest that the accelerated demons algorithm has significant potential for delineating and tracking doses in targets and critical structures during CT-guided radiotherapy.

  8. 改进的SIFT特征图像配准算法%Improved SIFT Feature Image Registration Algorithm

    Institute of Scientific and Technical Information of China (English)

    祁燕; 王琰; 王明宇

    2012-01-01

    在研究SIFT特征配准算法基础上,针对SIFT特征描述符的区域性特征,采用马氏距离对SIFT算法误匹配点进行剔除,以减少错误匹配,进而提高图像配准的正确率,并应用于纹理图像的配准.%It is aimed at districted feature of SIFT feature descriptor by studying the SIFT feature registration algorithm. In order to reduce the error registration, the Mahalanobis distance is used in SIFT algorithm. Part of the error registration points are eliminated by the improved algorithm. The precision of image registration is increased. And it is used in texture image registration.

  9. Enhancing the Multivariate Signal of 15O water PET Studies With a New Non-Linear Neuroanatomical Registration Algorithm

    DEFF Research Database (Denmark)

    Kjems, Ulrik; Storther, Stephen C.; Anderson, Jon

    1999-01-01

    This paper addresses the problem of neuro-anatomical registration across individuals for functional [15O]water PET activation studies. A new algorithm for 3D non-linear structural registration (warping) of MR scans is presented. The method performs a hierarchically scaled search for a displacement...

  10. Enhancing the Multivariate Signal of 15O water PET Studies With a New Non-Linear Neuroanatomical Registration Algorithm

    DEFF Research Database (Denmark)

    Kjems, Ulrik; Storther, Stephen C.; Anderson, Jon

    1999-01-01

    This paper addresses the problem of neuro-anatomical registration across individuals for functional [15O]water PET activation studies. A new algorithm for 3D non-linear structural registration (warping) of MR scans is presented. The method performs a hierarchically scaled search for a displacemen...

  11. Comparison of Two Deformable Registration Algorithms in the Presence of Radiologic Change Between Serial Lung CT Scans.

    Science.gov (United States)

    Cunliffe, Alexandra R; White, Bradley; Justusson, Julia; Straus, Christopher; Malik, Renuka; Al-Hallaq, Hania A; Armato, Samuel G

    2015-12-01

    We evaluated the image registration accuracy achieved using two deformable registration algorithms when radiation-induced normal tissue changes were present between serial computed tomography (CT) scans. Two thoracic CT scans were collected for each of 24 patients who underwent radiation therapy (RT) treatment for lung cancer, eight of whom experienced radiologically evident normal tissue damage between pre- and post-RT scan acquisition. For each patient, 100 landmark point pairs were manually placed in anatomically corresponding locations between each pre- and post-RT scan. Each post-RT scan was then registered to the pre-RT scan using (1) the Plastimatch demons algorithm and (2) the Fraunhofer MEVIS algorithm. The registration accuracy for each scan pair was evaluated by comparing the distance between landmark points that were manually placed in the post-RT scans and points that were automatically mapped from pre- to post-RT scans using the displacement vector fields output by the two registration algorithms. For both algorithms, the registration accuracy was significantly decreased when normal tissue damage was present in the post-RT scan. Using the Plastimatch algorithm, registration accuracy was 2.4 mm, on average, in the absence of radiation-induced damage and 4.6 mm, on average, in the presence of damage. When the Fraunhofer MEVIS algorithm was instead used, registration errors decreased to 1.3 mm, on average, in the absence of damage and 2.5 mm, on average, when damage was present. This work demonstrated that the presence of lung tissue changes introduced following RT treatment for lung cancer can significantly decrease the registration accuracy achieved using deformable registration.

  12. A block matching-based registration algorithm for localization of locally advanced lung tumors

    Science.gov (United States)

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

    2014-01-01

    Purpose: To implement and evaluate a block matching-based registration (BMR) algorithm for locally advanced lung tumor localization during image-guided radiotherapy. Methods: Small (1 cm3), nonoverlapping image subvolumes (“blocks”) were automatically identified on the planning image to cover the tumor surface using a measure of the local intensity gradient. Blocks were independently and automatically registered to the on-treatment image using a rigid transform. To improve speed and robustness, registrations were performed iteratively from coarse to fine image resolution. At each resolution, all block displacements having a near-maximum similarity score were stored. From this list, a single displacement vector for each block was iteratively selected which maximized the consistency of displacement vectors across immediately neighboring blocks. These selected displacements were regularized using a median filter before proceeding to registrations at finer image resolutions. After evaluating all image resolutions, the global rigid transform of the on-treatment image was computed using a Procrustes analysis, providing the couch shift for patient setup correction. This algorithm was evaluated for 18 locally advanced lung cancer patients, each with 4–7 weekly on-treatment computed tomography scans having physician-delineated gross tumor volumes. Volume overlap (VO) and border displacement errors (BDE) were calculated relative to the nominal physician-identified targets to establish residual error after registration. Results: Implementation of multiresolution registration improved block matching accuracy by 39% compared to registration using only the full resolution images. By also considering multiple potential displacements per block, initial errors were reduced by 65%. Using the final implementation of the BMR algorithm, VO was significantly improved from 77% ± 21% (range: 0%–100%) in the initial bony alignment to 91% ± 8% (range: 56%–100%; p < 0.001). Left

  13. Image registration algorithm using Mexican hat function-based operator and grouped feature matching strategy.

    Directory of Open Access Journals (Sweden)

    Feng Jin

    Full Text Available Feature detection and matching are crucial for robust and reliable image registration. Although many methods have been developed, they commonly focus on only one class of image features. The methods that combine two or more classes of features are still novel and significant. In this work, methods for feature detection and matching are proposed. A Mexican hat function-based operator is used for image feature detection, including the local area detection and the feature point detection. For the local area detection, we use the Mexican hat operator for image filtering, and then the zero-crossing points are extracted and merged into the area borders. For the feature point detection, the Mexican hat operator is performed in scale space to get the key points. After the feature detection, an image registration is achieved by using the two classes of image features. The feature points are grouped according to a standardized region that contains correspondence to the local area, precise registration is achieved eventually by the grouped points. An image transformation matrix is estimated by the feature points in a region and then the best one is chosen through competition of a set of the transformation matrices. This strategy has been named the Grouped Sample Consensus (GCS. The GCS has also ability for removing the outliers effectively. The experimental results show that the proposed algorithm has high registration accuracy and small computational volume.

  14. Myocardial strain assessment by cine cardiac magnetic resonance imaging using non-rigid registration.

    Science.gov (United States)

    Tsadok, Yossi; Friedman, Zvi; Haluska, Brian A; Hoffmann, Rainer; Adam, Dan

    2016-05-01

    To evaluate a novel post-processing method for assessment of longitudinal mid-myocardial strain in standard cine cardiac magnetic resonance (CMR) imaging sequences. Cine CMR imaging and tagged cardiac magnetic resonance imaging (TMRI) were performed in 15 patients with acute myocardial infarction (AMI) and 15 healthy volunteers served as control group. A second group of 37 post-AMI patients underwent both cine CMR and late gadolinium enhancement (LGE) CMR exams. Speckle tracking echocardiography (STE) was performed in 36 of these patients. Cine CMR, TMRI and STE were analyzed to obtain longitudinal strain. LGE-CMR datasets were analyzed to evaluate scar extent. Comparison of peak systolic strain (PSS) measured from CMR and TMRI yielded a strong correlation (r=0.86, pcine CMR data. The method was found to be highly correlated with strain measurements obtained by TMRI and STE. This tool allows accurate discrimination between different transmurality states of myocardial infarction. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. An Orthogonal Learning Differential Evolution Algorithm for Remote Sensing Image Registration

    Directory of Open Access Journals (Sweden)

    Wenping Ma

    2014-01-01

    Full Text Available We introduce an area-based method for remote sensing image registration. We use orthogonal learning differential evolution algorithm to optimize the similarity metric between the reference image and the target image. Many local and global methods have been used to achieve the optimal similarity metric in the last few years. Because remote sensing images are usually influenced by large distortions and high noise, local methods will fail in some cases. For this reason, global methods are often required. The orthogonal learning (OL strategy is efficient when searching in complex problem spaces. In addition, it can discover more useful information via orthogonal experimental design (OED. Differential evolution (DE is a heuristic algorithm. It has shown to be efficient in solving the remote sensing image registration problem. So orthogonal learning differential evolution algorithm (OLDE is efficient for many optimization problems. The OLDE method uses the OL strategy to guide the DE algorithm to discover more useful information. Experiments show that the OLDE method is more robust and efficient for registering remote sensing images.

  16. An efficient registration and fusion algorithm for large misalignment remote sensing images

    Science.gov (United States)

    Li, Lingling; Li, Cuihua; Zeng, Xiaoming; Li, Bao

    2007-11-01

    In this paper, an efficient technique to perform automatic registration and fusion for large misalignment remote sensing images is proposed. It complements SIFT features with Harris-affine features, and uses the ratio of the first and second nearest neighbor distance to setup the initial correspondences, then uses the affine invariant of Mahalanobis distance to remove the mismatched feature points. From this correspondence of the points, the affine matrix between two different images can be determined. All points in the sensed image are mapped to the reference using the estimated transformation matrix and the corresponding gray levels are assigned by re-sampling the image in the sensed image. Finally, we develop Burt's match and saliency metric and use neighborhood space frequency to fuse the registrated reference and sensed remote sensing images in NSCT domain. Experiments on remote sensing images with large misalignment demonstrate the superb performance of the algorithm.

  17. Efficient nonrigid registration using ranked order statistics

    DEFF Research Database (Denmark)

    Tennakoon, Ruwan B.; Bab-Hadiashar, Alireza; de Bruijne, Marleen

    2013-01-01

    Non-rigid image registration techniques are widely used in medical imaging applications. Due to high computational complexities of these techniques, finding appropriate registration method to both reduce the computation burden and increase the registration accuracy has become an intense area...... of research. In this paper we propose a fast and accurate non-rigid registration method for intra-modality volumetric images. Our approach exploits the information provided by an order statistics based segmentation method, to find the important regions for registration and use an appropriate sampling scheme...... to target those areas and reduce the registration computation time. A unique advantage of the proposed method is its ability to identify the point of diminishing returns and stop the registration process. Our experiments on registration of real lung CT images, with expert annotated landmarks, show...

  18. ANALYSIS OF TWO TRIANGLE-BASED MULTI-SURFACE REGISTRATION ALGORITHMS OF IRREGULAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    M. Al-Durgham

    2012-09-01

    Full Text Available The registration of multiple surface point clouds into a common reference frame is a well addressed topic, and the Iterative Closest Point (ICP is – perhaps – the most used method when registering laser scans due to their irregular nature. In this paper, we examine the proposed Iterative Closest Projected Point (ICPP algorithm for the simultaneous registration of multiple point clouds. First, a point to triangular patch (i.e. closest three points match is established by checking if the point falls within the triangular dipyramid, which has the three triangular patch points as a base and a user-chosen normal distance as the height to establish the two peaks. Then, the point is projected onto the patch surface, and its projection is then used as a match for the original point. It is also shown through empirical experimentation that the Delaunay triangles are not a requirement for establishing matches. In fact, Delaunay triangles in some scenarios may force blunders into the final solution, while using the closest three points leads to avoiding some undesired erroneous points. In addition, we review the algorithm by which the ICPP is inspired, namely, the Iterative Closest Patch (ICPatch; where conjugate point-patch pairs are extracted in the overlapping surface areas, and the transformation parameters between all neighbouring surfaces are estimated in a pairwise manner. Then, using the conjugate point-patch pairs, and applying the transformation parameters from the pairwise registration as initial approximations, the final surface transformation parameters are solved for simultaneously. Finally, we evaluate the assumptions made and examine the performance of the new algorithm against the ICPatch.

  19. A new approach to elastography using a modified demons registration algorithm

    Science.gov (United States)

    Sosa-Cabrera, Dario; Tristan-Vega, Antonio; Vegas-Sanchez-Ferrero, Gonzalo; Gonzalez-Fernandez, Javier; Gomez-Deniz, Luis; Alberla-Lopez, Carlos; Ruiz-Alzola, Juan

    2008-03-01

    Changes in tissue stiffness correlate with pathological phenomena that can aid the diagnosis of several diseases such as breast and prostate cancer. Ultrasound elastography measures the elastic properties of soft tissues using ultrasound signals. The standard way to estimate the displacement field from which researchers obtain the strain in elastography is the time-domain cross-correlation estimator (TDE). Optical flow (OF) methods have been also characterized and their use keeps increasing. We introduce in this paper the use of a Modified Demons Algorithm (MDA) to estimate the displacement field and we compare it with OF. A least-squares strain estimator (LSE) is applied to estimate the strain from the displacement. The input for the algorithm comes from the ultrasound scanner standard video output; therefore, its clinical implementation is immediate. To test the algorithm, a tissuemimicking phantom was modeled as a 10x10x5 cm region containing a centered 10mm cylindrical inclusion three times stiffer than the surrounding material, and its elastic behavior was simulated using COMSOL Multiphysics 3.2 software. Synthetic pre- and post-compression (1.25%) B-mode images were computer generated using FIELD II ultrasound simulator. Afterward, the algorithm was tested with a commercial CIRS breast elastography phantom, applying a 2% freehand compression. Axial displacement fields and strain figures are presented and in the case of the synthetic one compared to the ground truth given by the FE software. Although other researchers have used registration methods for elastography, as far as we know, they have not been used as stand alone but together with elastic modulus reconstruction or FE which iteratively varies material properties to improve registration.

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

    Science.gov (United States)

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

    2013-01-07

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

  1. SU-F-BRF-04: Evaluation of Five Commercially-Available Algorithms for Deformable Image Registration

    Energy Technology Data Exchange (ETDEWEB)

    Shah, A; Pukala, J; Staton, R; Meeks, S [UF Health Cancer Center at Orlando Health, Orlando, FL (United States); Johnson, P [University of Miami, Miami, FL (United States)

    2014-06-15

    Purpose: Deformable image registration (DIR) is increasingly being used in various clinical applications. Although there are several DIR packages all making successful attempts at modeling complex anatomical changes using even more complex mathematical approximations, they are all subject to various uncertainties. Many studies have attempted to quantify the spatial uncertainty with DIR. This is the first study to compare the uncertainty for interfraction DIR for 5 different commercially-available algorithms. The aim of this study was to benchmark the performance of the most commonlyused DIR algorithms offered through these 5 software packages: Eclipse, MIM, Pinnacle, RaySearch, and Velocity. Methods: A set of 10 virtual H'N phantoms [Pukala et al. MedPhys. 40(11) 2013] with known deformations were used to determine the spatial errors that might be seen when performing DIR. The “ground-truth” deformation vector field (DVF) was compared to the DVF output of the 5 commercially-available algorithms in order to evaluate spatial errors for six regions of interest (ROIs): brainstem, cord, mandible, left parotid, right parotid, and the external body contour. Results: We found that each software package had varying uncertainties with the various ROIs, but were generally all comparable to one another – with mean spatial errors for each algorithm below 3.5 mm for each ROI (averaged across all phantoms). We also found that no single algorithm was the clear winner over the other 4 algorithms. However, at times, we found huge maximum errors in our results (e.g. phantom #9 maximum errors: right parotid = 22.9 mm, external contour = 30.5mm) with the varying DIR algorithms. Conclusion: Although our evaluation was limited to H'N patients, we show that our methods are a single-assessment analysis tool that could be used by any physicist, within any type of facility, to compare their DIR software before initiating widespread use within their daily radiotherapy practice.

  2. Interactive Perception of Rigid and Non-Rigid Objects

    Directory of Open Access Journals (Sweden)

    Bryan Willimon

    2012-12-01

    Full Text Available This paper explores the concept of interactive perception, in which sensing guides manipulation, in the context of extracting and classifying unknown objects within a cluttered environment. In the proposed approach, a pile of objects lies on a flat background, and the goal of the robot is to isolate, interact with, and classify each object so that its properties can be obtained. The algorithm considers each object to be classified using color, shape, and flexibility. The approach works with a variety of objects relevant to service robot applications, including both rigid objects such as bottles, cans, and pliers as well as non‐rigid objects such as soft toy animals, socks, and shoes. Experiments on a number of different piles of objects demonstrate the ability of efficiently isolating and classifying each item through interaction.

  3. Kernel Bundle Diffeomorphic Image Registration Using Stationary Velocity Fields and Wendland Basis Functions.

    Science.gov (United States)

    Pai, Akshay; Sommer, Stefan; Sorensen, Lauge; Darkner, Sune; Sporring, Jon; Nielsen, Mads

    2016-06-01

    In this paper, we propose a multi-scale, multi-kernel shape, compactly supported kernel bundle framework for stationary velocity field-based image registration (Wendland kernel bundle stationary velocity field, wKB-SVF). We exploit the possibility of directly choosing kernels to construct a reproducing kernel Hilbert space (RKHS) instead of imposing it from a differential operator. The proposed framework allows us to minimize computational cost without sacrificing the theoretical foundations of SVF-based diffeomorphic registration. In order to recover deformations occurring at different scales, we use compactly supported Wendland kernels at multiple scales and orders to parameterize the velocity fields, and the framework allows simultaneous optimization over all scales. The performance of wKB-SVF is extensively compared to the 14 non-rigid registration algorithms presented in a recent comparison paper. On both MGH10 and CUMC12 datasets, the accuracy of wKB-SVF is improved when compared to other registration algorithms. In a disease-specific application for intra-subject registration, atrophy scores estimated using the proposed registration scheme separates the diagnostic groups of Alzheimer's and normal controls better than the state-of-the-art segmentation technique. Experimental results show that wKB-SVF is a robust, flexible registration framework that allows theoretically well-founded and computationally efficient multi-scale representation of deformations and is equally well-suited for both inter- and intra-subject image registration.

  4. Real-time Animation Technique for a Kind of Non-rigid Objects

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    A real-time animation technique for a kind of non-rigid objects, flexible and thin objects, is proposed, which can update with stability the state of n mass points of the mass-spring (MS) model with time complexity of O(n). The new implicit numerical integration technique of the authors, which is based on a simple approximation of the linear system, has great advantages over the existing implicit integration methods. Moreover, experiment shows that the new technique is highly efficient in animating a kind of non-rigid objects, and suitable for the draping module of the 3D garment CAD system.

  5. Analysis and optimization of assembly variations for non-rigid parts

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Traditional variation analysis methods are not applicable to non-rigid assemblies due to possible part deformation during the assembly process. This paper presents the use of finite element methods to simulate assembly deformation. The relationship between the parts' variation and the variation of the key points in final assembly for quality control is set up by calculating the spring back deformation after assembly. Moreover, the optimization method for non-rigid assembly variations based on finite element analysis is presented. The optimal objective is to reduce the manufacturing cost. The approach is implemented by using ANSYS and MATLAB. The test example shows that the proposed method is effective and applicable.

  6. Rapid and robust medical image elastic registration using mean shift algorithm

    Institute of Scientific and Technical Information of China (English)

    Xuan Yang; Jihong Pei

    2008-01-01

    In landmark-based image registration, estimating the landmark correspondence plays an important role. In this letter, a novel landmark correspondence estimation technique using mean shift algorithm is proposed. Image corner points are detected as landmarks and mean shift iterations are adopted to find the most probable corresponding point positions in two images. Mutual information between intensity of two local regions is computed to eliminate mis-matching points. Multi-level estimation (MLE) technique is proposed to improve the stability of corresponding estimation. Experiments show that the precision in location of correspondence landmarks is exact. The proposed technique is shown to be feasible and rapid in the experiments of various mono-modal medical images.

  7. Active zone impact on deformation state of non-rigid pavement

    Science.gov (United States)

    Mandula, Ján

    2014-06-01

    The paper deals with the design of non-rigid pavement, with emphasis on the effect of active zone on its deformation state. The concepts of determination of active zone are described. The results of numerical modelling of pavement laying on elastic subgrade are presented in the paper

  8. Active zone impact on deformation state of non-rigid pavement

    Directory of Open Access Journals (Sweden)

    Mandula Ján

    2014-06-01

    Full Text Available The paper deals with the design of non-rigid pavement, with emphasis on the effect of active zone on its deformation state. The concepts of determination of active zone are described. The results of numerical modelling of pavement laying on elastic subgrade are presented in the paper

  9. Surface registration algorithm by employing energy registration method and ICP algorithm%能量法与ICP算法相结合从粗到精的曲面配准技术

    Institute of Scientific and Technical Information of China (English)

    潘明存; 乔丽霞; 赵松潮

    2013-01-01

    In the registration of free-form surface which is represented by point cloud or triangular mesh, ICP algorithm is used widely, but in practical applications, the basic ICP algorithm has some defects. According to the inherent limitations of basic ICP matching algorithm, the registration algorithm based on two steps method was given. At first step, the energy registration method was employed to align the data in different coordinate system, and then ICP algorithm was employed to register the data precisely by using the result of energy as the initial value. The forming examples of the actual workpiece was used to verify that the property in global optimization of the registration algorithm based on two steps method is better than that of ICP algorithm.%在使用点云数据或三角网格数据表示的自由曲面的配准问题中,ICP算法使用相当广泛,但就实际应用来说,基本的ICP匹配算法存在一定的缺陷.针对基本ICP匹配算法存在的固有限制,本文采用先粗后精的匹配思路,即先用能量法进行数据间的粗略配准,以粗配准的结果做初始值,利用ICP算法进行数据间的精配准.并用实际工件的成形例子对配准算法进行验证,其全局优化性能优于ICP算法.

  10. Implementation of the Lucas-Kanade image registration algorithm on a GPU for 3D computational platform stabilisation

    CSIR Research Space (South Africa)

    Duvenhage, B

    2010-06-01

    Full Text Available . This paper presents the details of a real-time implementation of the Lucas- Kanade image registration algorithm on a Graphics Processing Unit (GPU) using the OpenGL Shading Language (GLSL). The implementation is driven by a real world requirement...

  11. Implementation and evaluation of various demons deformable image registration algorithms on GPU

    CERN Document Server

    Gu, Xuejun; Liang, Yun; Castillo, Richard; Yang, Deshan; Choi, Dongju; Castillo, Edward; Majumdar, Amitava; Guerrero, Thomas; Jiang, Steve B

    2009-01-01

    Online adaptive radiation therapy (ART) promises the ability to deliver an optimal treatment in response to daily patient anatomic variation. A major technical barrier for the clinical implementation of online ART is the requirement of rapid image segmentation. Deformable image registration (DIR) has been used as an automated segmentation method to transfer tumor/organ contours from the planning image to daily images. However, the current computational time of DIR is insufficient for online ART. In this work, this issue is addressed by using computer graphics processing units (GPUs). A grey-scale based DIR algorithm called demons and five of its variants were implemented on GPUs using the Compute Unified Device Architecture (CUDA) programming environment. The spatial accuracy of these algorithms was evaluated over five sets of pulmonary 4DCT images with an average size of 256x256x100 and more than 1,100 expert-determined landmark point pairs each. For all the testing scenarios presented in this paper, the GPU...

  12. A non-rigid point matching method with local topology preservation for accurate bladder dose summation in high dose rate cervical brachytherapy.

    Science.gov (United States)

    Chen, Haibin; Zhong, Zichun; Liao, Yuliang; Pompoš, Arnold; Hrycushko, Brian; Albuquerque, Kevin; Zhen, Xin; Zhou, Linghong; Gu, Xuejun

    2016-02-07

    GEC-ESTRO guidelines for high dose rate cervical brachytherapy advocate the reporting of the D2cc (the minimum dose received by the maximally exposed 2cc volume) to organs at risk. Due to large interfractional organ motion, reporting of accurate cumulative D2cc over a multifractional course is a non-trivial task requiring deformable image registration and deformable dose summation. To efficiently and accurately describe the point-to-point correspondence of the bladder wall over all treatment fractions while preserving local topologies, we propose a novel graphic processing unit (GPU)-based non-rigid point matching algorithm. This is achieved by introducing local anatomic information into the iterative update of correspondence matrix computation in the 'thin plate splines-robust point matching' (TPS-RPM) scheme. The performance of the GPU-based TPS-RPM with local topology preservation algorithm (TPS-RPM-LTP) was evaluated using four numerically simulated synthetic bladders having known deformations, a custom-made porcine bladder phantom embedded with twenty one fiducial markers, and 29 fractional computed tomography (CT) images from seven cervical cancer patients. Results show that TPS-RPM-LTP achieved excellent geometric accuracy with landmark residual distance error (RDE) of 0.7  ±  0.3 mm for the numerical synthetic data with different scales of bladder deformation and structure complexity, and 3.7  ±  1.8 mm and 1.6  ±  0.8 mm for the porcine bladder phantom with large and small deformation, respectively. The RDE accuracy of the urethral orifice landmarks in patient bladders was 3.7  ±  2.1 mm. When compared to the original TPS-RPM, the TPS-RPM-LTP improved landmark matching by reducing landmark RDE by 50  ±  19%, 37  ±  11% and 28  ±  11% for the synthetic, porcine phantom and the patient bladders, respectively. This was achieved with a computational time of less than 15 s in all cases

  13. The edge-driven dual-bootstrap iterative closest point algorithm for multimodal retinal image registration

    Science.gov (United States)

    Tsai, Chia-Ling; Li, Chun-Yi; Yang, Gehua

    2008-03-01

    Red-free (RF) fundus retinal images and fluorescein angiogram (FA) sequence are often captured from an eye for diagnosis and treatment of abnormalities of the retina. With the aid of multimodal image registration, physicians can combine information to make accurate surgical planning and quantitative judgment of the progression of a disease. The goal of our work is to jointly align the RF images with the FA sequence of the same eye in a common reference space. Our work is inspired by Generalized Dual-Bootstrap Iterative Closest Point (GDB-ICP), which is a fully-automatic, feature-based method using structural similarity. GDB-ICP rank-orders Lowe keypoint matches and refines the transformation computed from each keypoint match in succession. Albeit GDB-ICP has been shown robust to image pairs with illumination difference, the performance is not satisfactory for multimodal and some FA pairs which exhibit substantial non-linear illumination changes. Our algorithm, named Edge-Driven DBICP, modifies generation of keypoint matches for initialization by extracting the Lowe keypoints from the gradient magnitude image, and enriching the keypoint descriptor with global-shape context using the edge points. Our dataset consists of 61 randomly selected pathological sequences, each on average having two RF and 13 FA images. There are total of 4985 image pairs, out of which 1323 are multimodal pairs. Edge-Driven DBICP successfully registered 93% of all pairs, and 82% multimodal pairs, whereas GDB-ICP registered 80% and 40%, respectively. Regarding registration of the whole image sequence in a common reference space, Edge-Driven DBICP succeeded in 60 sequences, which is 26% improvement over GDB-ICP.

  14. A piecewise monotone subgradient algorithm for accurate L¹-TV based registration of physical slices with discontinuities in microscopy.

    Science.gov (United States)

    Michalek, Jan; Capek, Martin

    2013-05-01

    Image registration tasks are often formulated in terms of minimization of a functional consisting of a data fidelity term penalizing the mismatch between the reference and the target image, and a term enforcing smoothness of shift between neighboring pairs of pixels (a min-sum problem). Most methods for deformable image registration use some form of interpolation between matching control points. The interpolation makes it impossible to account for isolated discontinuities in the deformation field that may appear, e.g., when a physical slice of a microscopy specimen is ruptured by the cutting tool. For registration of neighboring physical slices of microscopy specimens with discontinuities, Janácek proposed an L¹-distance data fidelity term and a total variation (TV) smoothness term, and used a graph-cut (GC) based iterative steepest descent algorithm for minimization. The L¹-TV functional is nonconvex; hence a steepest descent algorithm is not guaranteed to converge to the global minimum. Schlesinger presented transformation of max-sum problems to minimization of a dual quantity called problem power, which is--contrary to the original max-sum functional--convex. Based on Schlesinger's solution to max-sum problems we developed an algorithm for L¹-TV minimization by iterative multi-label steepest descent minimization of the convex dual problem. For Schlesinger's subgradient algorithm we proposed a novel step control heuristics that considerably enhances both speed and accuracy compared with standard step size strategies for subgradient methods. It is shown experimentally that our subgradient scheme achieves consistently better image registration than GC in terms of lower values both of the composite L¹-TV functional, and of its components, i.e., the L¹ distance of the images and the transformation smoothness TV, and yields visually acceptable results even in cases where the GC based algorithm fails. The new algorithm allows easy parallelization and can thus be

  15. Hierarchical segmentation-assisted multimodal registration for MR brain images.

    Science.gov (United States)

    Lu, Huanxiang; Beisteiner, Roland; Nolte, Lutz-Peter; Reyes, Mauricio

    2013-04-01

    Information theory-based metric such as mutual information (MI) is widely used as similarity measurement for multimodal registration. Nevertheless, this metric may lead to matching ambiguity for non-rigid registration. Moreover, maximization of MI alone does not necessarily produce an optimal solution. In this paper, we propose a segmentation-assisted similarity metric based on point-wise mutual information (PMI). This similarity metric, termed SPMI, enhances the registration accuracy by considering tissue classification probabilities as prior information, which is generated from an expectation maximization (EM) algorithm. Diffeomorphic demons is then adopted as the registration model and is optimized in a hierarchical framework (H-SPMI) based on different levels of anatomical structure as prior knowledge. The proposed method is evaluated using Brainweb synthetic data and clinical fMRI images. Both qualitative and quantitative assessment were performed as well as a sensitivity analysis to the segmentation error. Compared to the pure intensity-based approaches which only maximize mutual information, we show that the proposed algorithm provides significantly better accuracy on both synthetic and clinical data.

  16. Q-Conjugacy character table for the non-rigid group of 2,3-dimethylbutane

    Directory of Open Access Journals (Sweden)

    MOHAMMAD REZA DARAFSHEH

    2009-01-01

    Full Text Available Maturated and unmaturated groups were introduced by the Japanese chemist Shinsaku Fujita, who used them in the markaracter table and the Q-conjugacy character table of a finite group. He then applied his results in this area of research to enumerate isomers of molecules. Using the non-rigid group theory, it was shown by the second author that the full non-rigid (f-NRG group of 2,3--dimethylbutane is isomorphic to the group (Z3×Z3×Z3×Z3:Z2 of order 162 with 54 conjugacy classes. Here (Z3×Z3×Z3×Z3:Z2 denotes the semi direct product of four copies of Z3 by Z2, where Zn is a cyclic group of order n. In this paper, it is shown with the GAP program that this group has 30 dominant classes (similarly, Q-conjugacy characters and that 24 of them are unmatured (similarly, Q-conjugacy characters such that they are the sum of two irreducible characters. Then, the Q-conjugacy character table of the unmatured full non-rigid group 2,3-dimethylbutane is derived.

  17. TU-AB-BRA-12: Impact of Image Registration Algorithms On the Prediction of Pathological Response with Radiomic Textures

    Energy Technology Data Exchange (ETDEWEB)

    Yip, S; Coroller, T; Niu, N; Mamon, H; Aerts, H; Berbeco, R [Brigham and Women’s Hospital, Boston, MA (United States)

    2015-06-15

    Purpose: Tumor regions-of-interest (ROI) can be propagated from the pre-onto the post-treatment PET/CT images using image registration of their CT counterparts, providing an automatic way to compute texture features on longitudinal scans. This exploratory study assessed the impact of image registration algorithms on textures to predict pathological response. Methods: Forty-six esophageal cancer patients (1 tumor/patient) underwent PET/CT scans before and after chemoradiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumor ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. One co-occurrence, two run-length and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs and texture quantification resulting from different algorithms were compared using overlap volume (OV) and coefficient of variation (CoV), respectively. Results: Tumor volumes were better captured by ROIs propagated by deformable rather than the rigid registration. The OV between rigidly and deformably propagated ROIs were 69%. The deformably propagated ROIs were found to be similar (OV∼80%) except for fast-demons (OV∼60%). Rigidly propagated ROIs with run-length matrix textures failed to significantly differentiate between responders and non-responders (AUC=0.65, p=0.07), while the differentiation was significant with other textures (AUC=0.69–0.72, p<0.03). Among the deformable algorithms, fast-demons was the least predictive (AUC=0.68–0.71, p<0.04). ROIs propagated by all other deformable algorithms with any texture significantly predicted pathologic responders (AUC=0.71–0.78, p<0.01) despite substantial variation in

  18. Deformable registration of multi-modal data including rigid structures

    Energy Technology Data Exchange (ETDEWEB)

    Huesman, Ronald H.; Klein, Gregory J.; Kimdon, Joey A.; Kuo, Chaincy; Majumdar, Sharmila

    2003-05-02

    Multi-modality imaging studies are becoming more widely utilized in the analysis of medical data. Anatomical data from CT and MRI are useful for analyzing or further processing functional data from techniques such as PET and SPECT. When data are not acquired simultaneously, even when these data are acquired on a dual-imaging device using the same bed, motion can occur that requires registration between the reconstructed image volumes. As the human torso can allow non-rigid motion, this type of motion should be estimated and corrected. We report a deformation registration technique that utilizes rigid registration for bony structures, while allowing elastic transformation of soft tissue to more accurately register the entire image volume. The technique is applied to the registration of CT and MR images of the lumbar spine. First a global rigid registration is performed to approximately align features. Bony structures are then segmented from the CT data using semi-automated process, and bounding boxes for each vertebra are established. Each CT subvolume is then individually registered to the MRI data using a piece-wise rigid registration algorithm and a mutual information image similarity measure. The resulting set of rigid transformations allows for accurate registration of the parts of the CT and MRI data representing the vertebrae, but not the adjacent soft tissue. To align the soft tissue, a smoothly-varying deformation is computed using a thin platespline(TPS) algorithm. The TPS technique requires a sparse set of landmarks that are to be brought into correspondence. These landmarks are automatically obtained from the segmented data using simple edge-detection techniques and random sampling from the edge candidates. A smoothness parameter is also included in the TPS formulation for characterization of the stiffness of the soft tissue. Estimation of an appropriate stiffness factor is obtained iteratively by using the mutual information cost function on the result

  19. Nonrigid registration of volumetric images using ranked order statistics

    DEFF Research Database (Denmark)

    Tennakoon, Ruwan; Bab-Hadiashar, Alireza; Cao, Zhenwei

    2014-01-01

    Non-rigid image registration techniques using intensity based similarity measures are widely used in medical imaging applications. Due to high computational complexities of these techniques, particularly for volumetric images, finding appropriate registration methods to both reduce the computation...... burden and increase the registration accuracy has become an intensive area of research. In this paper we propose a fast and accurate non-rigid registration method for intra-modality volumetric images. Our approach exploits the information provided by an order statistics based segmentation method, to find...... the important regions for registration and use an appropriate sampling scheme to target those areas and reduce the registration computation time. A unique advantage of the proposed method is its ability to identify the point of diminishing returns and stop the registration process. Our experiments...

  20. Automated analysis of small animal PET studies through deformable registration to an atlas

    Energy Technology Data Exchange (ETDEWEB)

    Gutierrez, Daniel F. [Geneva University Hospital, Division of Nuclear Medicine and Molecular Imaging, Geneva 4 (Switzerland); Zaidi, Habib [Geneva University Hospital, Division of Nuclear Medicine and Molecular Imaging, Geneva 4 (Switzerland); Geneva University, Geneva Neuroscience Center, Geneva (Switzerland); University of Groningen, Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen (Netherlands)

    2012-11-15

    This work aims to develop a methodology for automated atlas-guided analysis of small animal positron emission tomography (PET) data through deformable registration to an anatomical mouse model. A non-rigid registration technique is used to put into correspondence relevant anatomical regions of rodent CT images from combined PET/CT studies to corresponding CT images of the Digimouse anatomical mouse model. The latter provides a pre-segmented atlas consisting of 21 anatomical regions suitable for automated quantitative analysis. Image registration is performed using a package based on the Insight Toolkit allowing the implementation of various image registration algorithms. The optimal parameters obtained for deformable registration were applied to simulated and experimental mouse PET/CT studies. The accuracy of the image registration procedure was assessed by segmenting mouse CT images into seven regions: brain, lungs, heart, kidneys, bladder, skeleton and the rest of the body. This was accomplished prior to image registration using a semi-automated algorithm. Each mouse segmentation was transformed using the parameters obtained during CT to CT image registration. The resulting segmentation was compared with the original Digimouse atlas to quantify image registration accuracy using established metrics such as the Dice coefficient and Hausdorff distance. PET images were then transformed using the same technique and automated quantitative analysis of tracer uptake performed. The Dice coefficient and Hausdorff distance show fair to excellent agreement and a mean registration mismatch distance of about 6 mm. The results demonstrate good quantification accuracy in most of the regions, especially the brain, but not in the bladder, as expected. Normalized mean activity estimates were preserved between the reference and automated quantification techniques with relative errors below 10 % in most of the organs considered. The proposed automated quantification technique is

  1. Validation of deformable image registration algorithms on CT images of ex vivo porcine bladders with fiducial markers.

    Science.gov (United States)

    Wognum, S; Heethuis, S E; Rosario, T; Hoogeman, M S; Bel, A

    2014-07-01

    The spatial accuracy of deformable image registration (DIR) is important in the implementation of image guided adaptive radiotherapy techniques for cancer in the pelvic region. Validation of algorithms is best performed on phantoms with fiducial markers undergoing controlled large deformations. Excised porcine bladders, exhibiting similar filling and voiding behavior as human bladders, provide such an environment. The aim of this study was to determine the spatial accuracy of different DIR algorithms on CT images of ex vivo porcine bladders with radiopaque fiducial markers applied to the outer surface, for a range of bladder volumes, using various accuracy metrics. Five excised porcine bladders with a grid of 30-40 radiopaque fiducial markers attached to the outer wall were suspended inside a water-filled phantom. The bladder was filled with a controlled amount of water with added contrast medium for a range of filling volumes (100-400 ml in steps of 50 ml) using a luer lock syringe, and CT scans were acquired at each filling volume. DIR was performed for each data set, with the 100 ml bladder as the reference image. Six intensity-based algorithms (optical flow or demons-based) implemented in theMATLAB platform DIRART, a b-spline algorithm implemented in the commercial software package VelocityAI, and a structure-based algorithm (Symmetric Thin Plate Spline Robust Point Matching) were validated, using adequate parameter settings according to values previously published. The resulting deformation vector field from each registration was applied to the contoured bladder structures and to the marker coordinates for spatial error calculation. The quality of the algorithms was assessed by comparing the different error metrics across the different algorithms, and by comparing the effect of deformation magnitude (bladder volume difference) per algorithm, using the Independent Samples Kruskal-Wallis test. The authors found good structure accuracy without dependency on

  2. Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery.

    Science.gov (United States)

    Archip, Neculai; Clatz, Olivier; Whalen, Stephen; Kacher, Dan; Fedorov, Andriy; Kot, Andriy; Chrisochoides, Nikos; Jolesz, Ferenc; Golby, Alexandra; Black, Peter M; Warfield, Simon K

    2007-04-01

    The usefulness of neurosurgical navigation with current visualizations is seriously compromised by brain shift, which inevitably occurs during the course of the operation, significantly degrading the precise alignment between the pre-operative MR data and the intra-operative shape of the brain. Our objectives were (i) to evaluate the feasibility of non-rigid registration that compensates for the brain deformations within the time constraints imposed by neurosurgery, and (ii) to create augmented reality visualizations of critical structural and functional brain regions during neurosurgery using pre-operatively acquired fMRI and DT-MRI. Eleven consecutive patients with supratentorial gliomas were included in our study. All underwent surgery at our intra-operative MR imaging-guided therapy facility and have tumors in eloquent brain areas (e.g. precentral gyrus and cortico-spinal tract). Functional MRI and DT-MRI, together with MPRAGE and T2w structural MRI were acquired at 3 T prior to surgery. SPGR and T2w images were acquired with a 0.5 T magnet during each procedure. Quantitative assessment of the alignment accuracy was carried out and compared with current state-of-the-art systems based only on rigid registration. Alignment between pre-operative and intra-operative datasets was successfully carried out during surgery for all patients. Overall, the mean residual displacement remaining after non-rigid registration was 1.82 mm. There is a statistically significant improvement in alignment accuracy utilizing our non-rigid registration in comparison to the currently used technology (paugmented reality visualization to aid the surgeon.

  3. Non-rigid alignment of preoperative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery

    Science.gov (United States)

    Archip, Neculai; Clatz, Olivier; Whalen, Stephen; Kacher, Dan; Fedorov, Andriy; Kot, Andriy; Chrisochoides, Nikos; Jolesz, Ferenc; Golby, Alexandra; Black, Peter M.; Warfield, Simon K.

    2012-01-01

    Objective The usefulness of neurosurgical navigation with current visualizations is seriously compromised by brain shift, which inevitably occurs during the course of the operation, significantly degrading the precise alignment between the preoperative MR data and the intra-operative shape of the brain. Our objectives were (i) to evaluate the feasibility of non-rigid registration that compensates for the brain deformations within the time constraints imposed by neurosurgery, and (ii) create augmented reality visualizations of critical structural and functional brain regions during neurosurgery using pre-operatively acquired fMRI and DT-MRI. Materials and Methods Eleven consecutive patients with supratentorial gliomas were included in our study. All underwent surgery at our intra-operative MR imaging–guided therapy facility and have tumors in eloquent brain areas (e.g. precentral gyrus and cortico-spinal tract). Functional MRI and DT-MRI, together with MPRAGE and T2w structural MRI were acquired at 3T prior to surgery. SPGR and T2w images were acquired with a 0.5T magnet during each procedure. Quantitative assessment of the alignment accuracy was carried out and compared with current state-of the-art systems based only on rigid-registration. Results Alignment between preoperative and intra-operative datasets was successfully carried out during surgery for all patients. Overall, the mean residual displacement remaining after non-rigid registration was 1.82 mm. There is a statistically significant improvement in alignment accuracy utilizing our non-rigid registration in comparison to the currently used technology (paugmented reality visualization to aid the surgeon. PMID:17289403

  4. Flexible model and spectrum of non-rigid motion in LMF4 fluorides

    Science.gov (United States)

    Baranov, L. Ya.; Boldyrev, A. I.

    A flexible model is used to simulate the spectrum of the non-rigid motion in the LiBF4 molecule. It is shown that there are many states having energies below the barrier of rearrangement which can be regarded as anharmonic bending vibrations. A one-well representation of the potential energy surface appears to be a fairly good approximation for describing this part of the spectrum. The tunnelling splittings at these levels are extremely small. At energies above the barrier the level pattern changes radically and highly excited states should be regarded as intramolecular hindered rotation. Differences between the spectra of LMH4 hydrides and LMF4 fluorides are discussed.

  5. Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

    Science.gov (United States)

    Solarna, David; Moser, Gabriele; Le Moigne-Stewart, Jacqueline; Serpico, Sebastiano B.

    2017-01-01

    Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

  6. Experiences in determination of non-rigid body motion in industrial environment using low-cost photogrammetry

    Science.gov (United States)

    Rupnik, Ewelina; Jansa, Josef

    2013-04-01

    Central to our investigation is determination of dynamic behaviour of a highly reflective platform floating on water, as well as derivation of parameters defining instantaneous water state. The employed imaging setup consists of three off-the-shelf dSLR cameras capable of video recording at a 30Hz frame rate. In order to observe a change, the non-rigid and non-diffuse bodies impose the adoption of artificial targetting and custom measurement algorithms. Attention will be given to an in-house software tool implemented to carry out point measurement, correspondence search, tracking and outlier detection methods in the presence of specular reflections and a multimedia scene. A methodology for retrieval of wave parameters in regular wave conditions is also automatically handled by the software and will be discussed. In the context of performed measurements and achieved results, we will point out the extent to which consumer grade camera can fulfil automation and accuracy demands of industrial applications and the pitfalls entailed. Lastly, we will elaborate on visual representation of computed motion and deformations.

  7. Mass preserving image registration

    DEFF Research Database (Denmark)

    Gorbunova, Vladlena; Sporring, Jon; Lo, Pechin Chien Pau

    2010-01-01

    The paper presents results the mass preserving image registration method in the Evaluation of Methods for Pulmonary Image Registration 2010 (EMPIRE10) Challenge. The mass preserving image registration algorithm was applied to the 20 image pairs. Registration was evaluated using four different...

  8. Understanding geological processes: Visualization of rigid and non-rigid transformations

    Science.gov (United States)

    Shipley, T. F.; Atit, K.; Manduca, C. A.; Ormand, C. J.; Resnick, I.; Tikoff, B.

    2012-12-01

    Visualizations are used in the geological sciences to support reasoning about structures and events. Research in cognitive sciences offers insights into the range of skills of different users, and ultimately how visualizations might support different users. To understand the range of skills needed to reason about earth processes we have developed a program of research that is grounded in the geosciences' careful description of the spatial and spatiotemporal patterns associated with earth processes. In particular, we are pursuing a research program that identifies specific spatial skills and investigates whether and how they are related to each other. For this study, we focus on a specific question: Is there an important distinction in the geosciences between rigid and non-rigid deformation? To study a general spatial thinking skill we employed displays with non-geological objects that had been altered by rigid change (rotation), and two types of non-rigid change ("brittle" (or discontinuous) and "ductile" (or continuous) deformation). Disciplinary scientists (geosciences and chemistry faculty), and novices (non-science faculty and undergraduate psychology students) answered questions that required them to visualize the appearance of the object before the change. In one study, geologists and chemists were found to be superior to non-science faculty in reasoning about rigid rotations (e.g., what an object would look like from a different perspective). Geologists were superior to chemists in reasoning about brittle deformations (e.g., what an object looked like before it was broken - here the object was a word cut into many fragments displaced in different directions). This finding is consistent with two hypotheses: 1) Experts are good at visualizing the types of changes required for their domain; and 2) Visualization of rigid and non-rigid changes are not the same skill. An additional important finding is that there was a broad range of skill in both rigid and non-rigid

  9. Estimating the Video Registration Using Image Motions

    Directory of Open Access Journals (Sweden)

    N.Kannaiya Raja

    2012-07-01

    Full Text Available In this research, we consider the problems of registering multiple video sequences dynamic scenes which are not limited non rigid objects such as fireworks, blasting, high speed car moving taken from different vantage points. In this paper we propose a simple algorithm we can create different frames on particular videos moving for matching such complex scenes. Our algorithm does not require the cameras to be synchronized, and is not based on frame-by-frame or volume-by-volume registration. Instead, we model each video as the output of a linear dynamical system and transform the task of registering the video sequences to that of registering the parameters of the corresponding dynamical models. In this paper we use of a joint frame together to form distinct frame concurrently. The joint identification and the Jordan canonical form are not only applicable to the case of registering video sequences, but also to the entire genre of algorithms based on the dynamic texture model. We have also shown that out of all the possible choices for the method of identification and canonical form, the JID using JCF performs the best.

  10. Comparison of allocation algorithms for unambiguous registration of hits in presence of charge sharing in pixel detectors

    Science.gov (United States)

    Otfinowski, P.; Maj, P.; Deptuch, G.; Fahim, F.; Hoff, J.

    2017-01-01

    Charge sharing is the fractional collection of the charge cloud generated in a detector by two or more adjacent pixels. It may lead to excessive or inefficient registration of hits comparing to the number of impinging photons depending on how discrimination thresholds are set in typical photon counting pixel detector. The problems are particularly exposed for fine pixel sizes and/or for thick planar detectors. Presence of charge sharing is one of the limiting factors that discourages decreasing sizes of pixels in photon counting mode X-ray radiation imaging systems. Currently, a few different approaches tackling with the charge sharing problem exist (e.g. Medipix3RX, PIXIE, miniVIPIC or PIX45). The general idea is, first, to reconstruct the entire signal from adjacent pixels and, secondly, to allocate the hit to a single pixel. This paper focuses on the latter part of the process, i.e. on a comparison of how different hit allocation algorithms affect the spatial accuracy and false registration vs. missed hit probability. Different hit allocation algorithms were simulated, including standard photon counting (no full signal reconstruction) and the C8P1 algorithm. Also, a novel approach, based on a detection of patterns, with significantly limited analog signal processing, was proposed and characterized.

  11. Noise estimation in infrared image sequences: a tool for the quantitative evaluation of the effectiveness of registration algorithms.

    Science.gov (United States)

    Agostini, Valentina; Delsanto, Silvia; Knaflitz, Marco; Molinari, Filippo

    2008-07-01

    Dynamic infrared imaging has been proposed in literature as an adjunctive technique to mammography in breast cancer diagnosis. It is based on the acquisition of hundreds of consecutive thermal images with a frame rate ranging from 50 to 200 frames/s, followed by the harmonic analysis of temperature time series at each image pixel. However, the temperature fluctuation due to blood perfusion, which is the signal of interest, is small compared to the signal fluctuation due to subject movements. Hence, before extracting the time series describing temperature fluctuations, it is fundamental to realign the thermal images to attenuate motion artifacts. In this paper, we describe a method for the quantitative evaluation of any kind of feature-based registration algorithm on thermal image sequences, provided that an estimation of local velocities of reference points on the skin is available. As an example of evaluation of a registration algorithm, we report the evaluation of the SNR improvement obtained by applying a nonrigid piecewise linear algorithm.

  12. a Robust Registration Algorithm for Point Clouds from Uav Images for Change Detection

    Science.gov (United States)

    Al-Rawabdeh, A.; Al-Gurrani, H.; Al-Durgham, K.; Detchev, I.; He, F.; El-Sheimy, N.; Habib, A.

    2016-06-01

    Landslides are among the major threats to urban landscape and manmade infrastructure. They often cause economic losses, property damages, and loss of lives. Temporal monitoring data of landslides from different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces from two or more epochs is crucial for the proper analysis of landslide dynamics. The traditional methods for point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP) registration procedure to align any reconstructed surfaces from different epochs to a common reference frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy. For example, point clouds from different epochs might fit to local minima due to lack of geometrical variability within the data. Also, manual interaction is required to exclude any non-stable areas from the registration process. In this paper, a robust image-based registration method is introduced for the simultaneous evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs) of the camera and the Exterior Orientation Parameters (EOPs) of the involved images from all available observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense matching technique is implemented to generate dense 3D point clouds for each epoch using the images captured in a particular epoch separately. The normal distances between any two consecutive point clouds can then be readily computed, because the point clouds are already effectively co-registered. A low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV) was customised and used in this research for temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The customisation included adding a GPS logger and a Large-Field-Of-View (LFOV) action camera which facilitated capturing high-resolution geo-tagged images in two epochs

  13. IMAGE REGISTRATION OF HIGH-RESOLUTION UAV DATA: THE NEW HYPARE ALGORITHM

    OpenAIRE

    T. Bahr; Jin, X.; Lasica, R.; Giessel, D.

    2013-01-01

    Unmanned aerial vehicles play an important role in the present-day civilian and military intelligence. Equipped with a variety of sensors, such as SAR imaging modes, E/O- and IR sensor technology, they are due to their agility suitable for many applications. Hence, the necessity arises to use fusion technologies and to develop them continuously. Here an exact image-to-image registration is essential. It serves as the basis for important image processing operations such as georeferenc...

  14. A novel model-based evolutionary algorithm for multi-objective deformable image registration with content mismatch and large deformations: benchmarking efficiency and quality

    Science.gov (United States)

    Bouter, Anton; Alderliesten, Tanja; Bosman, Peter A. N.

    2017-02-01

    Taking a multi-objective optimization approach to deformable image registration has recently gained attention, because such an approach removes the requirement of manually tuning the weights of all the involved objectives. Especially for problems that require large complex deformations, this is a non-trivial task. From the resulting Pareto set of solutions one can then much more insightfully select a registration outcome that is most suitable for the problem at hand. To serve as an internal optimization engine, currently used multi-objective algorithms are competent, but rather inefficient. In this paper we largely improve upon this by introducing a multi-objective real-valued adaptation of the recently introduced Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) for discrete optimization. In this work, GOMEA is tailored specifically to the problem of deformable image registration to obtain substantially improved efficiency. This improvement is achieved by exploiting a key strength of GOMEA: iteratively improving small parts of solutions, allowing to faster exploit the impact of such updates on the objectives at hand through partial evaluations. We performed experiments on three registration problems. In particular, an artificial problem containing a disappearing structure, a pair of pre- and post-operative breast CT scans, and a pair of breast MRI scans acquired in prone and supine position were considered. Results show that compared to the previously used evolutionary algorithm, GOMEA obtains a speed-up of up to a factor of 1600 on the tested registration problems while achieving registration outcomes of similar quality.

  15. Air shower registration algorithm and mathematical processing of showers with radio signal at the Yakutsk array

    CERN Document Server

    Petrov, I; Petrov, Z

    2013-01-01

    The paper describes the techniques and method of registration of air shower radio emission at the Yakutsk array of extensive air showers at a frequency of 32 MHz. At this stage, emission registration involves two set of antennas, the distance between them is 500m. One set involves 8 antennas, second - 4 antennas. The antennas are perpendicularly crossed dipoles with radiation pattern North South,West East and raised 1.5 m above the ground. Each set of antennas connected to an industrial PC. The registration requires one of two triggers. First trigger are generated by scintillation detectors of Yakutsk array. Scintillation detectors cover area of 12 km^2 and registers air showers with energy more than 10^17 eV. The second trigger is generated by Small Cherenkov Array that covers area of 1 km^2 and registers air showers with energy 10^15 - 5*10^17 eV. Small Cherenkov Array is part of Yakutsk array and involve Cherenkov detectors located at a distance of 50, 100, 250 m. For further selection we are using an addi...

  16. Experiment and numerical simulation on the characteristics of fluid–structure interactions of non-rigid airships

    Directory of Open Access Journals (Sweden)

    Xiaocui Wu

    2015-11-01

    Full Text Available Fluid–structure interaction is an important issue for non-rigid airships with inflated envelopes. In this study, a wind tunnel test is conducted, and a loosely coupled procedure is correspondingly established for numerical simulation based on computational fluid dynamics and nonlinear finite element analysis methods. The typical results of the numerical simulation and wind tunnel experiment, including the overall lift and deformation, are in good agreement with each other. The results obtained indicate that the effect of fluid–structure interaction is noticeable and should be considered for non-rigid airships. Flow-induced deformation can further intensify the upward lift force and pitching moment, which can lead to a large deformation. Under a wind speed of 15 m/s, the lift force of the non-rigid model is increased to approximately 60% compared with that of the rigid model under a high angle of attack.

  17. Numerical calculation of the stress-strain state of non-rigid pavements, renovated by cold recycling technology

    Directory of Open Access Journals (Sweden)

    Світлана Михайлівна Талах

    2017-01-01

    Full Text Available The problem of improving the scientific basis to determine the stress-strain state of non-rigid pavements, renovated by cold recycling technology, is considered. The results of numerical calculation of stress-strain state of non-rigid pavements in the section of road Kyv-Kovel (297 + 700 km - 302 + 400 km are given using automated calculation software complex of thin-walled spatial structures (KARTPK. The real state of the road section through 8.5 years after the renovation is analyzed

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

    Science.gov (United States)

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

    2014-03-01

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

  19. Toward adaptive radiotherapy for head and neck patients: Uncertainties in dose warping due to the choice of deformable registration algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Veiga, Catarina, E-mail: catarina.veiga.11@ucl.ac.uk; Royle, Gary [Radiation Physics Group, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT (United Kingdom); Lourenço, Ana Mónica [Radiation Physics Group, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, United Kingdom and Acoustics and Ionizing Radiation Team, National Physical Laboratory, Teddington TW11 0LW (United Kingdom); Mouinuddin, Syed [Department of Radiotherapy, University College London Hospital, London NW1 2BU (United Kingdom); Herk, Marcel van [Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam 1066 CX (Netherlands); Modat, Marc; Ourselin, Sébastien; McClelland, Jamie R. [Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT (United Kingdom)

    2015-02-15

    Purpose: The aims of this work were to evaluate the performance of several deformable image registration (DIR) algorithms implemented in our in-house software (NiftyReg) and the uncertainties inherent to using different algorithms for dose warping. Methods: The authors describe a DIR based adaptive radiotherapy workflow, using CT and cone-beam CT (CBCT) imaging. The transformations that mapped the anatomy between the two time points were obtained using four different DIR approaches available in NiftyReg. These included a standard unidirectional algorithm and more sophisticated bidirectional ones that encourage or ensure inverse consistency. The forward (CT-to-CBCT) deformation vector fields (DVFs) were used to propagate the CT Hounsfield units and structures to the daily geometry for “dose of the day” calculations, while the backward (CBCT-to-CT) DVFs were used to remap the dose of the day onto the planning CT (pCT). Data from five head and neck patients were used to evaluate the performance of each implementation based on geometrical matching, physical properties of the DVFs, and similarity between warped dose distributions. Geometrical matching was verified in terms of dice similarity coefficient (DSC), distance transform, false positives, and false negatives. The physical properties of the DVFs were assessed calculating the harmonic energy, determinant of the Jacobian, and inverse consistency error of the transformations. Dose distributions were displayed on the pCT dose space and compared using dose difference (DD), distance to dose difference, and dose volume histograms. Results: All the DIR algorithms gave similar results in terms of geometrical matching, with an average DSC of 0.85 ± 0.08, but the underlying properties of the DVFs varied in terms of smoothness and inverse consistency. When comparing the doses warped by different algorithms, we found a root mean square DD of 1.9% ± 0.8% of the prescribed dose (pD) and that an average of 9% ± 4% of

  20. A ROBUST REGISTRATION ALGORITHM FOR POINT CLOUDS FROM UAV IMAGES FOR CHANGE DETECTION

    Directory of Open Access Journals (Sweden)

    A. Al-Rawabdeh

    2016-06-01

    Full Text Available Landslides are among the major threats to urban landscape and manmade infrastructure. They often cause economic losses, property damages, and loss of lives. Temporal monitoring data of landslides from different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces from two or more epochs is crucial for the proper analysis of landslide dynamics. The traditional methods for point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP registration procedure to align any reconstructed surfaces from different epochs to a common reference frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy. For example, point clouds from different epochs might fit to local minima due to lack of geometrical variability within the data. Also, manual interaction is required to exclude any non-stable areas from the registration process. In this paper, a robust image-based registration method is introduced for the simultaneous evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs of the camera and the Exterior Orientation Parameters (EOPs of the involved images from all available observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense matching technique is implemented to generate dense 3D point clouds for each epoch using the images captured in a particular epoch separately. The normal distances between any two consecutive point clouds can then be readily computed, because the point clouds are already effectively co-registered. A low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV was customised and used in this research for temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The customisation included adding a GPS logger and a Large-Field-Of-View (LFOV action camera which facilitated capturing high-resolution geo-tagged images

  1. Remote sensing image registration approach based on a retrofitted SIFT algorithm and Lissajous-curve trajectories.

    Science.gov (United States)

    Song, Zhi-li; Li, Sheng; George, Thomas F

    2010-01-18

    Through retrofitting the descriptor of a scale-invariant feature transform (SIFT) and developing a new similarity measure function based on trajectories generated from Lissajous curves, a new remote sensing image registration approach is constructed, which is more robust and accurate than prior approaches. In complex cases where the correct rate of feature matching is below 20%, the retrofitted SIFT descriptor improves the correct rate to nearly 100%. Mostly, the similarity measure function makes it possible to quantitatively analyze the temporary change of the same geographic position.

  2. An Efficient Exact Algorithm for the ’Least Squares Image Registration Problem

    Science.gov (United States)

    1989-05-01

    Zika -i TECHNICAL REPORT SOL ,J-5 May 1989 DTI.C , SELECTE ’" JUN 0 619891 F• • Department of Operations Research Stanford University Stanford, CA...the two-dimensional image registration problem. If X is a two-dimensional vector , then let x = zI + iz2 = [1xI4,9,. be the corresponding complex number...product. Therefore (x, y) = x c y for complex numbers, (z, y) = zry for real k-dimensional vectors , and if A and B are real n x k matrices, then let

  3. Poster — Thur Eve — 70: Automatic lung bronchial and vessel bifurcations detection algorithm for deformable image registration assessment

    Energy Technology Data Exchange (ETDEWEB)

    Labine, Alexandre; Carrier, Jean-François; Bedwani, Stéphane [Centre hospitalier de l' Université de Montréal (Canada); Chav, Ramnada; De Guise, Jacques [Laboratoire de recherche en imagerie et d' orthopédie-CRCHUM, École de technologie supérieure (Canada)

    2014-08-15

    Purpose: To investigate an automatic bronchial and vessel bifurcations detection algorithm for deformable image registration (DIR) assessment to improve lung cancer radiation treatment. Methods: 4DCT datasets were acquired and exported to Varian treatment planning system (TPS) EclipseTM for contouring. The lungs TPS contour was used as the prior shape for a segmentation algorithm based on hierarchical surface deformation that identifies the deformed lungs volumes of the 10 breathing phases. Hounsfield unit (HU) threshold filter was applied within the segmented lung volumes to identify blood vessels and airways. Segmented blood vessels and airways were skeletonised using a hierarchical curve-skeleton algorithm based on a generalized potential field approach. A graph representation of the computed skeleton was generated to assign one of three labels to each node: the termination node, the continuation node or the branching node. Results: 320 ± 51 bifurcations were detected in the right lung of a patient for the 10 breathing phases. The bifurcations were visually analyzed. 92 ± 10 bifurcations were found in the upper half of the lung and 228 ± 45 bifurcations were found in the lower half of the lung. Discrepancies between ten vessel trees were mainly ascribed to large deformation and in regions where the HU varies. Conclusions: We established an automatic method for DIR assessment using the morphological information of the patient anatomy. This approach allows a description of the lung's internal structure movement, which is needed to validate the DIR deformation fields for accurate 4D cancer treatment planning.

  4. THE PROGRAM OF NON-RIGID PAVEMENT COMPUTER-AIDED CALCULATION УКРРДО 15

    OpenAIRE

    MUSIIENKO I.

    2016-01-01

    A program for computer-aided calculation of non-rigid road coating UKRRDO 15 is considered in the given article. The program interface, a set of input data and the results of calculations are considered in detail. Calculations are performed for three strength criteria: permissible elastic deflection, shear strength of subsoil and monolithic layers resistance of tensile bending.

  5. THE PROGRAM OF NON-RIGID PAVEMENT COMPUTER-AIDED CALCULATION УКРРДО 15

    Directory of Open Access Journals (Sweden)

    I. Musiienko

    2016-06-01

    Full Text Available A program for computer-aided calculation of non-rigid road coating UKRRDO 15 is considered in the given article. The program interface, a set of input data and the results of calculations are considered in detail. Calculations are performed for three strength criteria: permissible elastic deflection, shear strength of subsoil and monolithic layers resistance of tensile bending.

  6. 3D–2D registration in mobile radiographs: algorithm development and preliminary clinical evaluation.

    Science.gov (United States)

    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

    2015-03-07

    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 the surgical product

  7. 3D-2D registration in mobile radiographs: algorithm development and preliminary clinical evaluation

    Science.gov (United States)

    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

  8. Research on UAV aerial image registration algorithm%无人机航拍图像配准算法研究

    Institute of Scientific and Technical Information of China (English)

    史俊莉

    2015-01-01

    针对无人机航拍图像对尺度变化不明显的问题,在经典SIFT特征匹配算法的基础上,提出了一种改进的CS-SIFT特征匹配算法.该算法通过建立S层金字塔,达到降低多尺度空间和减少特征点数量的目的.在特征向量的匹配中,利用准欧氏距离替代常用欧氏距离,并通过极限几何约束,消除部分错误配准点对,进一步提高特征匹配效率.Matlab仿真结果表明,改进后的算法具有较高的匹配精度和较少的匹配时间,适用于对实时性要求较高的无人机航拍系统.%Aiming at the problem that UAV aerial image was not obvious to scale change,an improved CS-SIFT feature matching algorithm was presented based on the classical feature matching algorithm of SIFT (scale invariant feature transform ).The algorithm established S-layer pyramid to reduce the multi-scale space and the number of feature points.In the matching feature vectors,quasi-Euclidean distance substitu-ted commonly used Euclidean distance and geometric constraints limitd by eliminating part of the registra-tion error points to further improve the efficiency of feature matching.The simulation results using Matlab language indicated that the improved algorithm had higher matching accuracy and needed less matching time and it was quite suitable for the UAV aerial system of high real-time demand.

  9. A Scheduling Algorithm for the Distributed Student Registration System in Transaction-Intensive Environment

    Science.gov (United States)

    Li, Wenhao

    2011-01-01

    Distributed workflow technology has been widely used in modern education and e-business systems. Distributed web applications have shown cross-domain and cooperative characteristics to meet the need of current distributed workflow applications. In this paper, the author proposes a dynamic and adaptive scheduling algorithm PCSA (Pre-Calculated…

  10. A Scheduling Algorithm for the Distributed Student Registration System in Transaction-Intensive Environment

    Science.gov (United States)

    Li, Wenhao

    2011-01-01

    Distributed workflow technology has been widely used in modern education and e-business systems. Distributed web applications have shown cross-domain and cooperative characteristics to meet the need of current distributed workflow applications. In this paper, the author proposes a dynamic and adaptive scheduling algorithm PCSA (Pre-Calculated…

  11. Robust Global Image Registration Based on a Hybrid Algorithm Combining Fourier and Spatial Domain Techniques

    Science.gov (United States)

    2012-09-01

    laboratory includes several visible PixeLINK CMOS machine vision cameras and an LWIR microbolometer camera. All results reported in this paper using...of nearly log-spaced positions, resulting in a 101 image sequence; the minimum and maximum calibrated shifts are 0.001 and 49.974 pixels...the four algorithms identified above, and the results are presented in Fig. 10 as a function of true ( calibrated ) shift. Results are shown on the

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

    Science.gov (United States)

    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. A semi-automated 2D/3D marker-based registration algorithm modelling prostate shrinkage during radiotherapy for prostate cancer.

    Science.gov (United States)

    Budiharto, Tom; Slagmolen, Pieter; Hermans, Jeroen; Maes, Frederik; Verstraete, Jan; Heuvel, Frank Van den; Depuydt, Tom; Oyen, Raymond; Haustermans, Karin

    2009-03-01

    Currently, most available patient alignment tools based on implanted markers use manual marker matching and rigid registration transformations to measure the needed translational shifts. To quantify the particular effect of prostate gland shrinkage, implanted gold markers were tracked during a course of radiotherapy including an isotropic scaling factor to model prostate shrinkage. Eight patients with prostate cancer had gold markers implanted transrectally and seven were treated with (neo) adjuvant androgen deprivation therapy. After patient alignment to skin tattoos, orthogonal electronic portal images (EPIs) were taken. A semi-automated 2D/3D marker-based registration was performed to calculate the necessary couch shifts. The registration consists of a rigid transformation combined with an isotropic scaling to model prostate shrinkage. The inclusion of an isotropic shrinkage model in the registration algorithm cancelled the corresponding increase in registration error. The mean scaling factor was 0.89+/-0.09. For all but two patients, a decrease of the isotropic scaling factor during treatment was observed. However, there was almost no difference in the translation offset between the manual matching of the EPIs to the digitally reconstructed radiographs and the semi-automated 2D/3D registration. A decrease in the intermarker distance was found correlating with prostate shrinkage rather than with random marker migration. Inclusion of shrinkage in the registration process reduces registration errors during a course of radiotherapy. Nevertheless, this did not lead to a clinically significant change in the proposed table translations when compared to translations obtained with manual marker matching without a scaling correction.

  14. 雷达组网的精确极大似然误差配准算法%An Exact Maximum Likelihood Error Registration Algorithm for Radar Network

    Institute of Scientific and Technical Information of China (English)

    丰昌政; 薛强

    2012-01-01

    针对最小二乘法和卡尔曼滤波方法在雷达网系统中的误差配准问题,提出一种雷达组网的精确极大似然误差配准算法.采用基于圆极投影的极大似然配准算法,利用各雷达站的几何关系,通过极大似然混合高斯-牛顿迭代方法估计出雷达网的系统误差,并进行仿真.仿真结果证明:该配准方法具有良好的一致性,可以用于多雷达组网的误差配准.%For the least square method and Caiman filter method in radar network system's error registration problems, put forward a kind of radar netting exact maximum likelihood error registration algorithm. Using maximum likelihood registration algorithm based on circular polar projection, according to the radar station geometric relationship, to estimate the error of radar network system by maximum likelihood mixed Gauss-Newton iterative method, and carried out a simulation. The simulation results show that the algorithm has good compatibility, can be used for multi radar netted registration.

  15. Calculation of the temperature of asphalt concrete at making the joints of multilane road pavement of non-rigid type

    OpenAIRE

    Giyasov Botir Iminzhonovich; Kupriyanov Roman Valer’evich; Andrianov Konstantin Anatol’evich; Zubkov Anatoliy Fedorovich

    2015-01-01

    The construction quality of road surface of non-rigid type essentially depend on providing the temperature regimes in the process of laying and packing of hot asphalt concrete mixtures. In order to provide the required characteristics of asphalt concrete due to the surface width it is necessary to provide the temperature regimes of hot asphalt concrete mixture in the zones of lane connection. The hot mixture is promptly cooling right after laying within several minutes, which results, accordi...

  16. Non-rigid, but not rigid, motion interferes with the processing of structural face information in developmental prosopagnosia.

    Science.gov (United States)

    Maguinness, Corrina; Newell, Fiona N

    2015-04-01

    There is growing evidence to suggest that facial motion is an important cue for face recognition. However, it is poorly understood whether motion is integrated with facial form information or whether it provides an independent cue to identity. To provide further insight into this issue, we compared the effect of motion on face perception in two developmental prosopagnosics and age-matched controls. Participants first learned faces presented dynamically (video), or in a sequence of static images, in which rigid (viewpoint) or non-rigid (expression) changes occurred. Immediately following learning, participants were required to match a static face image to the learned face. Test face images varied by viewpoint (Experiment 1) or expression (Experiment 2) and were learned or novel face images. We found similar performance across prosopagnosics and controls in matching facial identity across changes in viewpoint when the learned face was shown moving in a rigid manner. However, non-rigid motion interfered with face matching across changes in expression in both individuals with prosopagnosia compared to the performance of control participants. In contrast, non-rigid motion did not differentially affect the matching of facial expressions across changes in identity for either prosopagnosics (Experiment 3). Our results suggest that whilst the processing of rigid motion information of a face may be preserved in developmental prosopagnosia, non-rigid motion can specifically interfere with the representation of structural face information. Taken together, these results suggest that both form and motion cues are important in face perception and that these cues are likely integrated in the representation of facial identity.

  17. Voxel-based morphometric analysis in hypothyroidism using diffeomorphic anatomic registration via an exponentiated lie algebra algorithm approach.

    Science.gov (United States)

    Singh, S; Modi, S; Bagga, D; Kaur, P; Shankar, L R; Khushu, S

    2013-03-01

    The present study aimed to investigate whether brain morphological differences exist between adult hypothyroid subjects and age-matched controls using voxel-based morphometry (VBM) with diffeomorphic anatomic registration via an exponentiated lie algebra algorithm (DARTEL) approach. High-resolution structural magnetic resonance images were taken in ten healthy controls and ten hypothyroid subjects. The analysis was conducted using statistical parametric mapping. The VBM study revealed a reduction in grey matter volume in the left postcentral gyrus and cerebellum of hypothyroid subjects compared to controls. A significant reduction in white matter volume was also found in the cerebellum, right inferior and middle frontal gyrus, right precentral gyrus, right inferior occipital gyrus and right temporal gyrus of hypothyroid patients compared to healthy controls. Moreover, no meaningful cluster for greater grey or white matter volume was obtained in hypothyroid subjects compared to controls. Our study is the first VBM study of hypothyroidism in an adult population and suggests that, compared to controls, this disorder is associated with differences in brain morphology in areas corresponding to known functional deficits in attention, language, motor speed, visuospatial processing and memory in hypothyroidism. © 2012 British Society for Neuroendocrinology.

  18. A comparison of three Deformable Image Registration Algorithms in 4DCT using conventional contour based methods and voxel-by-voxel comparison methods.

    Directory of Open Access Journals (Sweden)

    Mirek eFatyga

    2015-02-01

    Full Text Available Background: Commonly used methods of assessing the accuracy of Deformable Image Registration (DIR rely on image segmentation or landmark selection. These methods are very labor intensive and thus limited to relatively small number of image pairs. The direct voxel-by-voxel comparison can be automated to examine fluctuations in DIR quality on a long series of image pairs.Methods: A voxel-by-voxel comparison of three DIR algorithms applied to lung patients is presented. Registrations are compared by comparing volume histograms formed both with individual DIR maps and with a voxel-by-voxel subtraction of the two maps. When two DIR maps agree one concludes that both maps are interchangeable in treatment planning applications, though one cannot conclude that either one agrees with the ground truth. If two DIR maps significantly disagree one concludes that at least one of the maps deviates from the ground truth. We use the method to compare three DIR algorithms applied to peak inhale-peak exhale registrations of 4DFBCT data obtained from thirteen patients. Results: All three algorithms appear to be nearly equivalent when compared using DICE similarity coefficients. A comparison based on Jacobian Volume Histograms shows that all three algorithms measure changes in total volume of the lungs with reasonable accuracy, but show large differences in the variance of Jacobian distribution on all contoured structures. Analysis of voxel-by-voxel subtraction of DIR maps shows that the three algorithms differ to a degree which is sufficient to create a potential for dosimetric discrepancy during dose accumulation.Conclusions: DIR algorithms can perform well in some clinical applications, while potentially fail in others. These algorithms are best treated as potentially useful approximations of tissue deformation that need to be separately validated for every intended clinical application.

  19. Physical Constraint Finite Element Model for Medical Image Registration.

    Directory of Open Access Journals (Sweden)

    Jingya Zhang

    Full Text Available Due to being derived from linear assumption, most elastic body based non-rigid image registration algorithms are facing challenges for soft tissues with complex nonlinear behavior and with large deformations. To take into account the geometric nonlinearity of soft tissues, we propose a registration algorithm on the basis of Newtonian differential equation. The material behavior of soft tissues is modeled as St. Venant-Kirchhoff elasticity, and the nonlinearity of the continuum represents the quadratic term of the deformation gradient under the Green- St.Venant strain. In our algorithm, the elastic force is formulated as the derivative of the deformation energy with respect to the nodal displacement vectors of the finite element; the external force is determined by the registration similarity gradient flow which drives the floating image deforming to the equilibrium condition. We compared our approach to three other models: 1 the conventional linear elastic finite element model (FEM; 2 the dynamic elastic FEM; 3 the robust block matching (RBM method. The registration accuracy was measured using three similarities: MSD (Mean Square Difference, NC (Normalized Correlation and NMI (Normalized Mutual Information, and was also measured using the mean and max distance between the ground seeds and corresponding ones after registration. We validated our method on 60 image pairs including 30 medical image pairs with artificial deformation and 30 clinical image pairs for both the chest chemotherapy treatment in different periods and brain MRI normalization. Our method achieved a distance error of 0.320±0.138 mm in x direction and 0.326±0.111 mm in y direction, MSD of 41.96±13.74, NC of 0.9958±0.0019, NMI of 1.2962±0.0114 for images with large artificial deformations; and average NC of 0.9622±0.008 and NMI of 1.2764±0.0089 for the real clinical cases. Student's t-test demonstrated that our model statistically outperformed the other methods in

  20. Multi-modal inter-subject registration of mouse brain images

    Science.gov (United States)

    Li, Xia; Yankeelov, Thomas E.; Rosen, Glenn; Gore, John C.; Dawant, Benoit M.

    2006-03-01

    The importance of small animal imaging in fundamental and clinical research is growing rapidly. These studies typically involve micro PET, micro MR, and micro CT images as well as optical or fluorescence images. Histological images are also often used to complement and/or validate the in vivo data. As is the case for human studies, automatic registration of these imaging modalities is a critical component of the overall analysis process, but, the small size of the animals and thus the limited spatial resolution of the in vivo images present specific challenges. In this paper, we propose a series of methods and techniques that permit the inter-subject registration of micro MR and histological images. We then compare results obtained by registering directly MR volumes to each other using a non-rigid registration algorithm we have developed at our institution with results obtained by registering first the MR volumes to their corresponding histological volume, which we reconstruct from 2D cross-sections, and then registering histological volumes to each other. We show that the second approach is preferable.

  1. AB initio calculations of the structure and stability of the non-rigid LiBF 4 molecule

    Science.gov (United States)

    Zakzhevzskii, V. G.; Boldyrev, A. I.; Charkin, O. P.

    1980-07-01

    Ab initio calculations of the potential energy surface, equilibrium geometry and energetic stability of the non-rigid LiBF4 molecule have been performed using the basis sets of Roos and Siegbahn, and Huzinaga and Dunning in a doublezeta contraction. The results are compared with similar ab initio data for LiBH 4, LiAlH 4, LiBeH -4, LiCH +4, Li 2 F 2, and LiBeF 3 ‡The geometry of the most disadvantageous configuration (m) was not optimized completely

  2. Application of harmony search quantum genetic algorithm in image registration%和声量子遗传算法在图像配准中的应用

    Institute of Scientific and Technical Information of China (English)

    张秀杰; 李士勇; 沈毅; 宋申民

    2012-01-01

    针对图像配准中的优化问题,利用量子遗传算法全局寻优能力强以及和声算法的微调特性,提出了一种新的和声量子遗传算法(harmony search quantum genetic algorithm,HSQGA).并将其应用到航拍图像配准当中.仿真结果证明了该算法比原有的和声算法和量子遗传算法在图像配准参数优化过程中具有更好的优化性能.此外,利用两个标准基本测试函数对新算法进行了测试,结果表明在一定的迭代次数内,该算法对一些复杂的优化问题也能精确寻优.%A new harmony search quantum genetic algorithm( HSQGA) is proposed for image registration, in which the harmony search (HS) method is merged together with the quantum genetic algorithm (QGA). The proposed algorithm is employed in parameter optimization of aerial image registration, and it can yield a superior optimization performance over the original HS method and basic QGA. The proposed algorithm is further tested on two common test functions, and simulation results illustrate that the proposed algorithm can find good solutions in the limited number of iteration.

  3. The interaction of luminance, velocity, and shape information in the perception of motion transparency, coherence, and non-rigid motion.

    Science.gov (United States)

    Jasinschi, R; Rosenfeld, A; Araújo, H J

    1993-01-01

    The perception of luminance transparency for superimposed patterns depends on how luminance, figural, and topological conditions are simultaneously satisfied. Motion transparency or coherence for two superimposed patterns, which correspond to the perception of both patterns moving across one another or to the perception of compound motion of the regions of pattern intersection, depends on the relation between the local velocity, luminance, and shape information. This study analyzes how luminance, shape, and local velocity interact in the perception of motion transparency and coherence. Psychophysical experiments done with sinusoidally modulated bar patterns are presented which show that the perception of motion transparency or coherence can be described as the result of the interaction of two integration modules: the velocity-luminance and the velocity-shape processes. The velocity-luminance process describes the integration of the local velocity with luminance information. When the luminance transparency rules are satisfied this process always generates the perception of motion transparency independently of the shape or contour information. On the other hand, when the luminance transparency rules are violated one can either perceive motion coherence or non-rigid motion; one perceives motion coherence when the patterns have small or zero amplitude, and non-rigid motion when the patterns have large amplitude. The velocity-shape process describes the integration of local velocity with shape information, and this depends on the relation between the error in the extraction of the local velocity and the magnitude of the contour amplitude. As a result of these experiments it is conjectured that the velocity-luminance and the velocity-shape processes do interact constructively or destructively. The constructive interaction occurs when the luminance transparency rules are satisfied. The destructive interaction occurs when the luminance transparency rules are violated, and

  4. ACCURATE REGISTRATION ALGORITHM FOR POINT CLOUD BASED ON PROPERTIES%基于特征的点云精确配准算法

    Institute of Scientific and Technical Information of China (English)

    许斌; 李忠科; 吕培军; 孙玉春; 王勇

    2013-01-01

    在散乱点云的配准过程中,由于不同次扫描得到的点云模型之间的重叠部分可能较小且点云具有丰富的几何细节,致使传统ICP(Iterative Closest Point)精确配准算法很难得到理想精度。针对这个问题以Chen和Medioni提出的点面距离误差测度函数为基础,结合基于特征的点云配准思想,设计了一种先建立拥有接近的主曲率的匹配点对集合,然后将二次拟合曲面间的平均距离作为误差测度进行迭代优化的精确配准算法。该算法在微小距离精确配准的应用环境下能提供相对于传统ICP算法更好的精度和更高的效率。%In process of scattered point cloud registration , since the overlapping portions of point cloud models derived from scanning in different times are always quite small , plus the point cloud has abundant geometric details , this makes the ideal accuracy becomes difficult to be gained by traditional ICP accurate registration algorithm .In light of this problem , we design an accurate registration algorithm , it is based on the metric function of point to surface distance error put forward by Chen and Medioni , and combining the property-based point cloud registration idea.First it establishes matching points set with closed main curvatures , and then it takes the average distance between quadric fitting surfaces as the error metric for iterative optimisation .In application environment of minute distance , this algorithm can provide better precision and higher efficiency than the traditional ICP algorithm .

  5. Continental deformation accommodated by non-rigid passive bookshelf faulting: An example from the Cenozoic tectonic development of northern Tibet

    Science.gov (United States)

    Zuza, Andrew V.; Yin, An

    2016-05-01

    Collision-induced continental deformation commonly involves complex interactions between strike-slip faulting and off-fault deformation, yet this relationship has rarely been quantified. In northern Tibet, Cenozoic deformation is expressed by the development of the > 1000-km-long east-striking left-slip Kunlun, Qinling, and Haiyuan faults. Each have a maximum slip in the central fault segment exceeding 10s to ~ 100 km but a much smaller slip magnitude (~rigid-body motion and flow-like distributed deformation end-member models for continental tectonics. Here we propose a non-rigid bookshelf-fault model for the Cenozoic tectonic development of northern Tibet. Our model, quantitatively relating discrete left-slip faulting to distributed off-fault deformation during regional clockwise rotation, explains several puzzling features, including the: (1) clockwise rotation of east-striking left-slip faults against the northeast-striking left-slip Altyn Tagh fault along the northwestern margin of the Tibetan Plateau, (2) alternating fault-parallel extension and shortening in the off-fault regions, and (3) eastward-tapering map-view geometries of the Qimen Tagh, Qaidam, and Qilian Shan thrust belts that link with the three major left-slip faults in northern Tibet. We refer to this specific non-rigid bookshelf-fault system as a passive bookshelf-fault system because the rotating bookshelf panels are detached from the rigid bounding domains. As a consequence, the wallrock of the strike-slip faults deforms to accommodate both the clockwise rotation of the left-slip faults and off-fault strain that arises at the fault ends. An important implication of our model is that the style and magnitude of Cenozoic deformation in northern Tibet vary considerably in the east-west direction. Thus, any single north-south cross section and its kinematic reconstruction through the region do not properly quantify the complex deformational processes of plateau formation.

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

    Science.gov (United States)

    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.

  7. SU-E-J-266: A Pitfall of a Deformable Image Registration in Lung Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Sugawara, Y [The National Center for Global Health and Medicine, Shinjuku, Tokyo (Japan); Tachibana, H [The National Cancer Center Hospital East, Kashiwa, Chiba (Japan); Moriya, S [Komazawa University, Setagaya, Tokyo (Japan); Sawant, A [UT Southwestern Medical Center, Dallas, TX (United States)

    2014-06-01

    Purpose: For four-dimensional (4D) planning and adaptive radiotherapy, deformable image registration (DIR) is needed and the accuracy is essential. We evaluated the accuracy of one free-downloadable DIR software library package (NiftyReg) and one commercial DIR software (MIM) in lung SBRT cancer patients. Methods: A rigid and non-rigid registrations were implemented to our in-house software. The non-rigid registration algorithm of the NiftyReg and MIM was based on the free-form deformation. The accuracy of the two software was evaluated when contoured structures to peak-inhale and peak-exhale 4DCT image data sets were measured using the dice similarity coefficient (DSC). The evaluation was performed in 20 lung SBRT patients. Results: In our visual evaluation, the eighteen cases show good agreement between the deformed structures for the peak-inhale phase and the peak-exhale phase structures (more than 0.8 DSC value). In the evaluation of the DSC in-house software, averaged DSC values of GTV and lung, heart, spinal cord, stomach and body were 0.862 and 0.979, 0.932, 0.974, 0.860, 0.998, respectively. As the Resultof the registration using the MIM program in the two cases which had less than 0.7 DSC value when analyzed using the in-house software, the DSC value were improved to 0.8. The CT images in a case with low DSC value shows the tumor was surrounded by the structure with the similar CT values, which were the chest wall or the diaphragm. Conclusion: Not only a free-downloadable DIR software but also a commercial software may provide unexpected results and there is a possibility that the results would make us misjudge the treatment planning. Therefore, we recommend that a commissioning test of any DIR software should be performed before clinical use and we should understand the characteristics of the software.

  8. 点云 FPFH 特征提取优化配准算法%The Registration Algorithm of Point Cloud Based on Optimal Extraction of FPFH Feature

    Institute of Scientific and Technical Information of China (English)

    陆军; 彭仲涛; 董东来; 宋景豪

    2014-01-01

    三维点云配准在机器人环境感知与建模、逆向工程等领域有着广泛的应用前景。针对获得的不同视角下点云数据的配准问题,设计一种 FPFH 特征提取优化配准方法。在提取关键点的基础上优化了FPFH 特征描述子计算过程中法向量计算,根据测量点及其邻域点估算每个关键点和它邻域点的曲面法矢,使用 SAC-IA 算法获得点云初始坐标变换矩阵,最后使用 ICP 算法精确配准。设计了三种配准方案,实验结果表明,只计算关键点及其周围一定范围内点法向量配准方法具有配准速度快、精度高的特点。%The three-dimensional point cloud registration has wide application prospect in fields of environmental perception and modeling of robot,reverse engineering,etc. An optimal feature extraction method of FPFH feature is designed to solve registration problem under different view of point cloud data. Based on the extracted key points,normal vector calculation used for getting FPFH feature descriptor is optimized. Based on the measurement point and its neighborhood points,the surface normal of each key points and its neighboring points are estimated. SAC-IA algorithm is used to obtain the initial point cloud coordinate transform matrix. Finally the ICP algorithm is used for precise registration. Three registration schemes are designed. The experimental results show that the scheme which only calculates normal of key points and their neighbors is faster and has high precision.

  9. A cross validation study of deep brain stimulation targeting: from experts to atlas-based, segmentation-based and automatic registration algorithms.

    Science.gov (United States)

    Castro, F Javier Sanchez; Pollo, Claudio; Meuli, Reto; Maeder, Philippe; Cuisenaire, Olivier; Cuadra, Meritxell Bach; Villemure, Jean-Guy; Thiran, Jean-Philippe

    2006-11-01

    Validation of image registration algorithms is a difficult task and open-ended problem, usually application-dependent. In this paper, we focus on deep brain stimulation (DBS) targeting for the treatment of movement disorders like Parkinson's disease and essential tremor. DBS involves implantation of an electrode deep inside the brain to electrically stimulate specific areas shutting down the disease's symptoms. The subthalamic nucleus (STN) has turned out to be the optimal target for this kind of surgery. Unfortunately, the STN is in general not clearly distinguishable in common medical imaging modalities. Usual techniques to infer its location are the use of anatomical atlases and visible surrounding landmarks. Surgeons have to adjust the electrode intraoperatively using electrophysiological recordings and macrostimulation tests. We constructed a ground truth derived from specific patients whose STNs are clearly visible on magnetic resonance (MR) T2-weighted images. A patient is chosen as atlas both for the right and left sides. Then, by registering each patient with the atlas using different methods, several estimations of the STN location are obtained. Two studies are driven using our proposed validation scheme. First, a comparison between different atlas-based and nonrigid registration algorithms with a evaluation of their performance and usability to locate the STN automatically. Second, a study of which visible surrounding structures influence the STN location. The two studies are cross validated between them and against expert's variability. Using this scheme, we evaluated the expert's ability against the estimation error provided by the tested algorithms and we demonstrated that automatic STN targeting is possible and as accurate as the expert-driven techniques currently used. We also show which structures have to be taken into account to accurately estimate the STN location.

  10. T-PHOT version 2.0: improved algorithms for background subtraction, local convolution, kernel registration, and new options

    CERN Document Server

    Merlin, E; Castellano, M; Ferguson, H C; Wang, T; Derriere, S; Dunlop, J S; Elbaz, D; Fontana, A

    2016-01-01

    We present the new release v2.0 of T-PHOT, a publicly available software package developed to perform PSF-matched, prior-based, multiwavelength deconfusion photometry of extragalactic fields. New features included in the code are presented and discussed: background estimation, fitting using position dependent kernels, flux prioring, diagnostical statistics on the residual image, exclusion of selected sources from the model and residual images, individual registration of fitted objects. These new options improve on the performance of the code, allowing for more accurate results and providing useful aids for diagnostics.

  11. T-PHOT version 2.0: Improved algorithms for background subtraction, local convolution, kernel registration, and new options

    Science.gov (United States)

    Merlin, E.; Bourne, N.; Castellano, M.; Ferguson, H. C.; Wang, T.; Derriere, S.; Dunlop, J. S.; Elbaz, D.; Fontana, A.

    2016-11-01

    Aims: We present the new release - version 2.0 - of t-phot, a publicly available software package developed to perform PSF-matched, prior-based, multiwavelength deconfusion photometry of extragalactic fields. Methods: New features included in the code are presented and discussed: background estimation, fitting using position dependent kernels, flux prioring, diagnostical statistics on the residual image, exclusion of selected sources from the model and residual images, and individual registration of fitted objects. Results: The new options improve on the performance of the code, allowing for more accurate results and providing useful aids for diagnostics.

  12. Automatic remote sensing image registration algorithm based on SIFT%基于SIFT的全自动遥感图像配准算法

    Institute of Scientific and Technical Information of China (English)

    余婷; 厉小润

    2013-01-01

    Aiming at the optical image affine transformation of the automatic registration, a coarse-to-fine remote sensing image automatic registration algorithm was proposed. Firstly, the input images were mapped for a local feature vector sets with translation, scaling and rotation invariant characteristic based on SIFT feature. According to the euclidean distance of the feature vector which is taken as the similarity decision measure, the initial matching feature points and the initial model parameter values of the transformation were determined. Secondly, making the mutual information as similarity measure, more established correspondence feature points were obtained based on the position control of the search strategy. Thirdly, the deeply optimized affine transformation model parameters were obtained by using the control points and the weighted least squares optimization algorithm together. In this way, a more sophisticated image registration was completed, and a root mean square error was used to evaluate the result of the registration. Finally joint histogram was taken as the registration precision evaluation standard to test registration effect. Experimental results demonstrate the effectiveness and accuracy of the proposed method.%针对仿射变换的光学图像自动配准精度不高的问题,提出了一种基于特征的由粗到细的遥感图像自动配准算法.首先采用SIFT特征进行了特征点的粗匹配,将输入图像映射为一个具有平移、缩放、旋转不变性的局部特征向量集,采用特征向量的欧氏距离作为相似性判定度量,通过两两比较找出匹配的若干对特征点对作为初始配准点对,以完成输入图像的粗匹配;其次,以互信息作为相似性测度,基于位置控制的搜索策略,确定了更多的特征点的对应关系;然后,利用控制点结合加权最小二乘优化仿射变换的模型参数,完成了图像间的精细配准;最后引入了联合直

  13. Diffusion Maps for Multimodal Registration

    Directory of Open Access Journals (Sweden)

    Gemma Piella

    2014-06-01

    Full Text Available Multimodal image registration is a difficult task, due to the significant intensity variations between the images. A common approach is to use sophisticated similarity measures, such as mutual information, that are robust to those intensity variations. However, these similarity measures are computationally expensive and, moreover, often fail to capture the geometry and the associated dynamics linked with the images. Another approach is the transformation of the images into a common space where modalities can be directly compared. Within this approach, we propose to register multimodal images by using diffusion maps to describe the geometric and spectral properties of the data. Through diffusion maps, the multimodal data is transformed into a new set of canonical coordinates that reflect its geometry uniformly across modalities, so that meaningful correspondences can be established between them. Images in this new representation can then be registered using a simple Euclidean distance as a similarity measure. Registration accuracy was evaluated on both real and simulated brain images with known ground-truth for both rigid and non-rigid registration. Results showed that the proposed approach achieved higher accuracy than the conventional approach using mutual information.

  14. Synthesis, modelling and NK1 antagonist evaluation of a non-rigid cyclopropane-containing analogue of CP-99,994.

    Science.gov (United States)

    Aitken, D J; Ongeri, S; Vallée-Goyet, D; Gramain, J C; Husson, H P

    2001-03-12

    A non-rigid cyclopropane-containing diamine analogue of CP-99,994 was synthesised and was found to have only moderate NK1 receptor binding affinity. Molecular dynamics calculations of the conformational space of the former compound gave good correlation between observed activity and a recently published pharmacophore model, lending predictive value to the latter.

  15. Calculation of the temperature of asphalt concrete at making the joints of multilane road pavement of non-rigid type

    Directory of Open Access Journals (Sweden)

    Giyasov Botir Iminzhonovich

    2015-03-01

    Full Text Available The construction quality of road surface of non-rigid type essentially depend on providing the temperature regimes in the process of laying and packing of hot asphalt concrete mixtures. In order to provide the required characteristics of asphalt concrete due to the surface width it is necessary to provide the temperature regimes of hot asphalt concrete mixture in the zones of lane connection. The hot mixture is promptly cooling right after laying within several minutes, which results, according to the construction technology and the specific conditions of work production, in temperature abuse of the mixture at joints of the lanes at packing. The authors present the analysis of the technology of arranging multilane road surface by one paver with the possibility of heating the surface lane edge with the temperature of the adjacent lane. The results of the studies of the production conditions effect on the temperature of edge heating of the previously laid lanes, and the time required to achieve the maximum heating temperature depending on the relative thickness of coating layers.

  16. Performance evaluation of an automatic anatomy segmentation algorithm on repeat or four-dimensional CT images using a deformable image registration method

    Science.gov (United States)

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

    2008-01-01

    Purpose Auto-propagation of anatomical region-of-interests (ROIs) from the planning CT to daily CT is an essential step in image-guided adaptive radiotherapy. The goal of this study was to quantitatively evaluate the performance of the algorithm in typical clinical applications. Method and Materials We previously adopted an image intensity-based deformable registration algorithm to find the correspondence between two images. In this study, the ROIs delineated on the planning CT image were mapped onto daily CT or four-dimentional (4D) CT images using the same transformation. Post-processing methods, such as boundary smoothing and modification, were used to enhance the robustness of the algorithm. Auto-propagated contours for eight head-and-neck patients with a total of 100 repeat CTs, one prostate patient with 24 repeat CTs, and nine lung cancer patients with a total of 90 4D-CT images were evaluated against physician-drawn contours and physician-modified deformed contours using the volume-overlap-index (VOI) and mean absolute surface-to-surface distance (ASSD). Results The deformed contours were reasonably well matched with daily anatomy on repeat CT images. The VOI and mean ASSD were 83% and 1.3 mm when compared to the independently drawn contours. A better agreement (greater than 97% and less than 0.4 mm) was achieved if the physician was only asked to correct the deformed contours. The algorithm was robust in the presence of random noise in the image. Conclusion The deformable algorithm may be an effective method to propagate the planning ROIs to subsequent CT images of changed anatomy, although a final review by physicians is highly recommended. PMID:18722272

  17. Registration Service

    CERN Multimedia

    GS Department

    2010-01-01

    Following a reorganization in Building 55, please note that the Registration Service is now organised as follows :  Ground floor: access cards (76903). 1st floor : registration of external firms’ personnel (76611 / 76622); car access stickers (76633); biometric registration (79710). Opening hours: 07-30 to 16-00 non-stop. GS-SEM Group General Infrastructure Services Department

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

    Science.gov (United States)

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

    2012-01-01

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

  19. Detailed analysis of the density change on chest CT of COPD using non-rigid registration of inspiration/expiration CT scans

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Eun Young [Chonbuk National University Medical School and Hospital, Research Institute of Clinical Medicine, Department of Radiology, Jeollabuk-do (Korea, Republic of); University of Ulsan College of Medicine, Asan Medical Center, Department of Radiology and Research Institute of Radiology, Seoul (Korea, Republic of); Seo, Joon Beom; Lee, Hyun Joo; Kim, Namkug; Lee, Eunsol; Lee, Sang Min; Oh, Sang Young [University of Ulsan College of Medicine, Asan Medical Center, Department of Radiology and Research Institute of Radiology, Seoul (Korea, Republic of); Hwang, Hye Jeon [Hallym University Sacred Heart Hospital, Department of Radiology, Hallym University College of Medicine, Gyeonggi-do (Korea, Republic of); Oh, Yeon-Mok; Lee, Sang-Do [University of Ulsan College of Medicine, Asan Medical Center, Department of Pulmonary and Critical Care Medicine, and Clinical Research Center for Chronic Obstructive Airway Diseases, Seoul (Korea, Republic of)

    2014-09-14

    One objective was to evaluate the air trapping index (ATI), measured by inspiration/expiration CT, in COPD patients and nonsmokers. Another objective was to assess the association between the pulmonary function test (PFT) and CT parameters such as ATI or other indices, separately in the whole lung, in emphysema, and in hyperinflated and normal lung areas. One hundred and thirty-eight COPD patients and 29 nonsmokers were included in our study. The ATI, the emphysema index (EI), the gas trapping index (Exp -856) and expiration/inspiration ratio of mean lung density (E/Iratio of MLD) were measured on CT. The values of the whole lung, of emphysema, and of hyperinflated and normal lung areas were compared and then correlated with various PFT parameters. Compared with nonsmokers, COPD patients showed a higher ATI in the whole lung and in each lung lesion (all P < 0.05). The ATI showed a higher correlation than EI with FEF{sub 25-75%}, RV and RV/TLC, and was comparable to Exp -856 and the E/I ratio of MLD. The ATI of emphysema and hyperinflated areas on CT showed better correlation than the normal lung area with PFT parameters. Detailed analysis of density change at inspiration and expiration CT of COPD can provide new insights into pulmonary functional impairment in each lung area. (orig.)

  20. Non-Rigid Registration with Simultaneously Matched Intensity and Shape%灰度与形状同步匹配的非刚性配准研究

    Institute of Scientific and Technical Information of China (English)

    林相波; 邱天爽; 阮素; Frédéric Nicolier

    2009-01-01

    基于灰度的非刚性配准算法一般假设参考图像和浮动图像对应结构之间的灰度保持一致,然而在基于图谱的图像配准应用中,这种假设往往不符合实际.本文在给出一种可以同时校正灰度和形状差异的弹性配准算法的同时,针对该算法不能校正局部微小形变的弱点,提出采用自由项变换的方法进行校正以提高配准精度.配准实验基于20个IBSR真实脑部MRI图像,结果表明配准后图像与参考图像间的互相关系数得到明显提高.实验证明,本文提出的方法不仅能够同时校正形状差异和灰度变化,而且具有较高的配准质量.

  1. Free Form Deformation-Based Image Registration Improves Accuracy of Traction Force Microscopy.

    Directory of Open Access Journals (Sweden)

    Alvaro Jorge-Peñas

    Full Text Available Traction Force Microscopy (TFM is a widespread method used to recover cellular tractions from the deformation that they cause in their surrounding substrate. Particle Image Velocimetry (PIV is commonly used to quantify the substrate's deformations, due to its simplicity and efficiency. However, PIV relies on a block-matching scheme that easily underestimates the deformations. This is especially relevant in the case of large, locally non-uniform deformations as those usually found in the vicinity of a cell's adhesions to the substrate. To overcome these limitations, we formulate the calculation of the deformation of the substrate in TFM as a non-rigid image registration process that warps the image of the unstressed material to match the image of the stressed one. In particular, we propose to use a B-spline -based Free Form Deformation (FFD algorithm that uses a connected deformable mesh to model a wide range of flexible deformations caused by cellular tractions. Our FFD approach is validated in 3D fields using synthetic (simulated data as well as with experimental data obtained using isolated endothelial cells lying on a deformable, polyacrylamide substrate. Our results show that FFD outperforms PIV providing a deformation field that allows a better recovery of the magnitude and orientation of tractions. Together, these results demonstrate the added value of the FFD algorithm for improving the accuracy of traction recovery.

  2. Free Form Deformation–Based Image Registration Improves Accuracy of Traction Force Microscopy

    Science.gov (United States)

    Jorge-Peñas, Alvaro; Izquierdo-Alvarez, Alicia; Aguilar-Cuenca, Rocio; Vicente-Manzanares, Miguel; Garcia-Aznar, José Manuel; Van Oosterwyck, Hans; de-Juan-Pardo, Elena M.; Ortiz-de-Solorzano, Carlos; Muñoz-Barrutia, Arrate

    2015-01-01

    Traction Force Microscopy (TFM) is a widespread method used to recover cellular tractions from the deformation that they cause in their surrounding substrate. Particle Image Velocimetry (PIV) is commonly used to quantify the substrate’s deformations, due to its simplicity and efficiency. However, PIV relies on a block-matching scheme that easily underestimates the deformations. This is especially relevant in the case of large, locally non-uniform deformations as those usually found in the vicinity of a cell’s adhesions to the substrate. To overcome these limitations, we formulate the calculation of the deformation of the substrate in TFM as a non-rigid image registration process that warps the image of the unstressed material to match the image of the stressed one. In particular, we propose to use a B-spline -based Free Form Deformation (FFD) algorithm that uses a connected deformable mesh to model a wide range of flexible deformations caused by cellular tractions. Our FFD approach is validated in 3D fields using synthetic (simulated) data as well as with experimental data obtained using isolated endothelial cells lying on a deformable, polyacrylamide substrate. Our results show that FFD outperforms PIV providing a deformation field that allows a better recovery of the magnitude and orientation of tractions. Together, these results demonstrate the added value of the FFD algorithm for improving the accuracy of traction recovery. PMID:26641883

  3. 3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

    Science.gov (United States)

    Mateo, Carlos M.; Gil, Pablo; Torres, Fernando

    2016-01-01

    Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments. PMID

  4. 3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

    Directory of Open Access Journals (Sweden)

    Carlos M. Mateo

    2016-05-01

    Full Text Available Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor

  5. 3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands.

    Science.gov (United States)

    Mateo, Carlos M; Gil, Pablo; Torres, Fernando

    2016-05-05

    Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object's surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand's fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

  6. Image Registration of Cochlear µCT Data Using Heat Distribution Similarity

    DEFF Research Database (Denmark)

    Kjer, Hans Martin; Vera, Sergio; Fagertun, Jens;

    2015-01-01

    Better understanding of the anatomical variability of the human cochlear is important for the design and function of Cochlear Implants. Good non-rigid alignment of high-resolution cochlear μCT data is a challenging task. In this paper we study the use of heat distribution similarity between sampl...... as an anatomical registration prior. We set-up and present our heat distribution model for the cochlea and utilize it in a typical cubic B-spline registration model. Evaluation and comparison is done against a corresponding normal registration of binary segmentations....

  7. 空间非合作目标的多视角点云配准算法研究%Research on registration algorithm of multiple-view point cloud for non-cooperative spacecraft

    Institute of Scientific and Technical Information of China (English)

    郭瑞科; 王立; 朱飞虎; 吴云

    2016-01-01

    为了提高相邻视角间稀疏扫描点云数据配准的速度和精度,实现多视角点云精确配准,提出一种基于KD-Tree点云均匀采样简化算法,并且对传统四点算法(4-Points Congruent Sets Algorithm,4PCS)中的阈值参数进行了统一,确定了各误差阈值参数和点云密度之间的关系,通过基于姿态校正的方法有效解决了对称视角点云引起的误配准问题.仿真结果表明,该方法能够快速、有效地实现卫星稀疏点云的配准.%The point cloud data registration is one of the key technical aspects of three-dimensional reconstruction for non-cooperative spacecraft.To solve the pair-wise registration issue of sparse point cloud, and align the multiple-view point cloud accurately, an optimization registration method was presented.A novel point cloud simplification algorithm using uniform sampling was proposed based on KD-Tree and the uniform relation of the threshold parameters in the 4PCS (4-Points Congruent Sets)algorithm was established via the density of the point cloud.By using the mis-registration correction method based on attitude,the mis-registration problem of the symmetry point cloud was solved. The results show that the proposed algorithm can effectively achieve good alignments of the sparse point cloud of the satellite,besides,the stability and the success rate of the algorithm is also improved.

  8. Fast CPD Building Point Cloud Registration Algorithm Based on ISS Feature Points%基于ISS特征点的快速CPD建筑物点云配准算法

    Institute of Scientific and Technical Information of China (English)

    刘伟权; 陈水利; 吴云东; 蔡国榕

    2016-01-01

    针对大规模建筑物点云数据采用CPD ( coherent point drift)算法进行配准时,计算复杂度增大的问题,提出了一种基于建筑物点云特征点简化数据的快速配准ISS⁃CPD算法。该配准算法采用ISS ( in⁃trinsic shape signature)算法求得建筑物点云的特征点,可减少建筑物点云的数据量规模,再对所提取的不同视角下建筑物点云的特征点用CPD算法进行配准。实验结果表明,改进的配准算法提高了建筑物点云的配准效率。%To counter the problem of the increasing computational complexity when using CPD ( Cohe⁃rent Point Drift) algorithm for registration to the large⁃scale building point cloud data, this paper proposes a fast registration algorithm based on feature points to simplify the building point cloud. This point cloud regis⁃tration algorithm is obtained by using the algorithm of ISS to extract building feature points to reduce the scale of building point cloud data, and use CPD algorithm to register the feature points of the multi⁃view building point cloud. The experimental results show that the improved registration algorithm is simple, effective, sta⁃ble and reliable, which can greatly improve the registration efficiency of the building point cloud using CPD algorithm.

  9. 基于Android平台的增强现实算法%Augmented Reality Registration Algorithm Based on Android System

    Institute of Scientific and Technical Information of China (English)

    阮文惠; 薛亚娣

    2015-01-01

    In order to obtain more ideal effect of the augmented reality, this paper puts forward an augmented reality algorithm based on Android platform. Firstly, the feature positions in the two image corner points are determined by using FAST algorithm, and SURF is used to generate feature descriptor, and then the fast approximate proximal point search algorithm is used to match, finally, implemented in the Android platform and the performance is test by simulation experiment. The simulation results show that, the proposed algorithm has the advantages of Android and can meet the augmented reality real-time requirements, but also has good robustness, overcomes the limitation of traditional augmented reality technology.%为了获得更加理想的增强现实效果,提出一种基于利用 Android 平台的增强现实算法。首先采用 FAST算法确定两幅图像中的特征角点,并采用SURF生成特征点描述符,然后采用快速近似邻近点搜索进行图像匹配,最后在Android平台上实现算法,并采用仿真实验测试算法的性能。仿真结果表明,本文算法结合Android的优点,可以较好的满足增强现实的实时性的要求,而且具有较好的鲁棒性,克服了传统增强现实技术的局限性。

  10. 一种基于改进SIFT的航拍图像自动配准算法%An automatic aerial image registration algorithm based on SIFT with improved features

    Institute of Scientific and Technical Information of China (English)

    董银文; 苑秉成; 石钊铭; 朱明磊

    2013-01-01

    针对传统SIFT算法匹配时间长、错匹配较多等问题,提出了一种基于改进SIFT特征的航拍图像自动配准算法.首先,通过特征点检测时设定检测极值点数目,按照DOG空间层次结构由粗到精来搜索特征点,并使用改进的SIFT特征描述符生成算法;其次,利用最近邻匹配准则进行初步匹配得到初始匹配点对,并采用双向匹配方法对匹配特征点对进行筛选;然后,基于马氏距离的特征点相似度量方法进行二次匹配,并使用RANSAC算法求取仿射变换模型;最后,通过双线性插值对变换后的图像进行重采样和插值.实验结果表明:该算法可以实现航拍图像之间的有效配准,在配准性能上优于传统SIFT算法.%To solve the problems of long registration time and many wrong registrations in using the traditional scale invariance feature transformation (SIFT) algorithm, an automatic aerial image registration algorithm is proposed based on the SIFT with improved features. Firstly, the feature point was searched according to a coarse-to-fine difference of Gauss (DOG) structure by setting a feature point number threshold, and the improved feature descriptors are used in the algorithm. Then the initial matching feature point pairs were obtained by use of the nearest neighborhood similarity measurement rule, and wrong registrations were removed by the lateral matching method. Mahalanobis distance was used to select right registrations in the second registration, and affine transformation was computed by Random Sample Consensus (RANSAC) algorithm. Finally, the transformed image was resampled and interpolated by means of bilinear interpolation. The experiments results show that the algorithm can achieve more accurate aerial image registration and is better than the traditional SIFT algorithm in performance.

  11. Deformable Registration of Digital Images

    Institute of Scientific and Technical Information of China (English)

    管伟光; 解林; 等

    1998-01-01

    is paper proposes a novel elastic model and presents a deformable registration method based on the model.The method registers images without the need to extract reatures from the images,and therefore works directly on grey-level images.A new similarity metric is given on which the formation of external forces is based.The registration method,taking the coarse-to-fine strategy,constructs external forces in larger scales for the first few iterations to rely more on global evidence,and ther in smaller scales for later iterations to allow local refinements.The stiffness of the elastic body decreases as the process proceeds.To make it widely applicable,the method is not restricted to any type of transformation.The variations between images are thought as general free-form deformations.Because the elastic model designed is linearized,it can be solved very efficiently with high accuracy.The method has been successfully tested on MRI images.It will certainly find other uses such as matching time-varying sequences of pictures for motion analysis,fitting templates into images for non-rigid object recognition,matching stereo images for shape recovery,etc.

  12. An Efficient Globally Optimal Algorithm for Asymmetric Point Matching.

    Science.gov (United States)

    Lian, Wei; Zhang, Lei; Yang, Ming-Hsuan

    2016-08-29

    Although the robust point matching algorithm has been demonstrated to be effective for non-rigid registration, there are several issues with the adopted deterministic annealing optimization technique. First, it is not globally optimal and regularization on the spatial transformation is needed for good matching results. Second, it tends to align the mass centers of two point sets. To address these issues, we propose a globally optimal algorithm for the robust point matching problem where each model point has a counterpart in scene set. By eliminating the transformation variables, we show that the original matching problem is reduced to a concave quadratic assignment problem where the objective function has a low rank Hessian matrix. This facilitates the use of large scale global optimization techniques. We propose a branch-and-bound algorithm based on rectangular subdivision where in each iteration, multiple rectangles are used to increase the chances of subdividing the one containing the global optimal solution. In addition, we present an efficient lower bounding scheme which has a linear assignment formulation and can be efficiently solved. Extensive experiments on synthetic and real datasets demonstrate the proposed algorithm performs favorably against the state-of-the-art methods in terms of robustness to outliers, matching accuracy, and run-time.

  13. 基于SIFT算法的InSAR影像配准方法试验研究%Research on the Co-registration Method of INSAR Based on the SIFT Algorithm

    Institute of Scientific and Technical Information of China (English)

    喻小东; 郭际明; 黄长军; 袁长征

    2013-01-01

    配准是合成孔径雷达干涉测量(InSAR)中极其关键的一个步骤.本文详细介绍了SIFT算法,并根据其特点将其应用于InSAR数据的配准过程中.实验结果表明:SIFT算法在InSAR配准中是一种简单、有效和可靠的配准方法.%Co-registration is an important processing in Synthetic aperture radar interferometry (INSAR). This paper describes the SIFT algorithm,and then applies this method to the registration of INSAR. Experiments show that the co-registration method of SIFT is effective and reliable than the regular method.

  14. Earth Science Imagery Registration

    Science.gov (United States)

    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.

  15. WE-AB-BRA-08: Results of a Multi-Institutional Study for the Evaluation of Deformable Image Registration Algorithms for Structure Delineation Via Computational Phantoms

    Energy Technology Data Exchange (ETDEWEB)

    Loi, G; Fusella, M [University Hospital “Maggiore della Carita”, Novara (Italy); Fiandra, C [University of Torino, Turin (Italy); Lanzi, E [G. Mazzini Hospital, Teramo (Italy); Rosica, A [Regina Elena National Cancer Institute, Rome (Italy); Strigari, L [Centro Oncologico Fiorentino, Florence (Italy); Orlandini, L [A.O. Ordine Mauriziano di Torino, Turin (Italy); Gino, E [Istituto Oncologico Veneto IOV, Padova (Italy); Roggio, A [Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola (Italy); Marcocci, F [ARNAS Civico - Di Cristina - Benfratelli, Palermo (Italy); Iacovello, G; Miceli, R [Tor Vergata University General Hospital, Rome (Italy)

    2015-06-15

    Purpose: To investigate the accuracy of various algorithms for deformable image registration (DIR), to propagate regions of interest (ROIs) in computational phantoms based on patient images using different commercial systems. This work is part of an Italian multi-institutional study to test on common datasets the accuracy, reproducibility and safety of DIR applications in Adaptive Radiotherapy. Methods: Eleven institutions with three available commercial solutions provided data to assess the agreement of DIR-propagated ROIs with automatically drown ROIs considered as ground-truth for the comparison. The DIR algorithms were tested on real patient data from three different anatomical districts: head and neck, thorax and pelvis. For every dataset two specific Deformation Vector Fields (DVFs) provided by ImSimQA software were applied to the reference data set. Three different commercial software were used in this study: RayStation, Velocity and Mirada. The DIR-mapped ROIs were then compared with the reference ROIs using the Jaccard Conformity Index (JCI). Results: More than 600 DIR-mapped ROIs were analyzed. Putting together all JCI data of all institutions for the first DVF, the mean JCI was 0.87 ± 0.7 (1 SD) while for the second DVF JCI was 0.8 ± 0.13 (1 SD). Several considerations on different structures are available from collected data: the standard deviation among different institutions on specific structure raise as the larger is the applied DVF. The higher value is 10% for bladder. Conclusion: Although the complexity of deformation of human body is very difficult to model, this work illustrates some clinical scenarios with well-known DVFs provided by specific software. CI parameter gives the inter-user variability and may put in evidence the need of improving the working protocol in order to reduce the inter-institution JCI variability.

  16. Solid Mesh Registration for Radiotherapy Treatment Planning

    DEFF Research Database (Denmark)

    Noe, Karsten Østergaard; Sørensen, Thomas Sangild

    2010-01-01

    We present an algorithm for solid organ registration of pre-segmented data represented as tetrahedral meshes. Registration of the organ surface is driven by force terms based on a distance field representation of the source and reference shapes. Registration of internal morphology is achieved usi...... to complete. The proposed method has many potential uses in image guided radiotherapy (IGRT) which relies on registration to account for organ deformation between treatment sessions....

  17. Spherical Demons: Fast Surface Registration

    Science.gov (United States)

    Yeo, B.T. Thomas; Sabuncu, Mert; Vercauteren, Tom; Ayache, Nicholas; Fischl, Bruce; Golland, Polina

    2009-01-01

    We present the fast Spherical Demons algorithm for registering two spherical images. By exploiting spherical vector spline interpolation theory, we show that a large class of regularizers for the modified demons objective function can be efficiently implemented on the sphere using convolution. Based on the one parameter subgroups of diffeomorphisms, the resulting registration is diffeomorphic and fast – registration of two cortical mesh models with more than 100k nodes takes less than 5 minutes, comparable to the fastest surface registration algorithms. Moreover, the accuracy of our method compares favorably to the popular FreeSurfer registration algorithm. We validate the technique in two different settings: (1) parcellation in a set of in-vivo cortical surfaces and (2) Brodmann area localization in ex-vivo cortical surfaces. PMID:18979813

  18. Higher Order Kernels and Locally Affine LDDMM Registration

    CERN Document Server

    Sommer, Stefan; Darkner, Sune; Pennec, Xavier

    2011-01-01

    To achieve sparse description that allows intuitive analysis, we aim to represent deformation with a basis containing interpretable elements, and we wish to use elements that have the description capacity to represent the deformation compactly. We accomplish this by introducing higher order kernels in the LDDMM registration framework. The kernels allow local description of affine transformations and subsequent compact description of non-translational movement and of the entire non-rigid deformation. This is obtained with a representation that contains directly interpretable information from both mathematical and modeling perspectives. We develop the mathematical construction behind the higher order kernels, we show the implications for sparse image registration and deformation description, and we provide examples of how the capacity of the kernels enables registration with a very low number of parameters. The capacity and interpretability of the kernels lead to natural modeling of articulated movement, and th...

  19. Image-based motion estimation for cardiac CT via image registration

    Science.gov (United States)

    Cammin, J.; Taguchi, K.

    2010-03-01

    Images reconstructed from tomographic projection data are subject to motion artifacts from organs that move during the duration of the scan. The effect can be reduced by taking the motion into account in the reconstruction algorithm if an estimate of the deformation exists. This paper presents the estimation of the three-dimensional cardiac motion by registering reconstructed images from cardiac quiet phases as a first step towards motion-compensated cardiac image reconstruction. The non-rigid deformations of the heart are parametrized on a coarse grid on the image volume and are interpolated with cubic b-splines. The optimization problem of finding b-spline coefficients that best describe the observed deformations is ill-posed due to the large number of parameters and the resulting motion vector field is sensitive to the choice of initial parameters. Particularly challenging is the task to capture the twisting motion of the heart. The motion vector field from a dynamic computer phantom of the human heart is used to initialize the transformation parameters for the optimization process with realistic starting values. The results are evaluated by comparing the registered images and the obtained motion vector field to the case when the registration is performed without using prior knowledge about the expected cardiac motion. We find that the registered images are similar for both approaches, but the motion vector field obtained from motion estimation initialized with the phantom describes the cardiac contraction and twisting motion more accurately.

  20. SU-E-J-94: Geometric and Dosimetric Evaluation of Deformation Image Registration Algorithms Using Virtual Phantoms Generated From Patients with Lung Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Z; Greskovich, J; Xia, P [The Cleveland Clinic, Cleveland, OH (United States); Bzdusek, K [Philips, Fitchburg, WI (United States)

    2015-06-15

    Purpose: To generate virtual phantoms with clinically relevant deformation and use them to objectively evaluate geometric and dosimetric uncertainties of deformable image registration (DIR) algorithms. Methods: Ten lung cancer patients undergoing adaptive 3DCRT planning were selected. For each patient, a pair of planning CT (pCT) and replanning CT (rCT) were used as the basis for virtual phantom generation. Manually adjusted meshes were created for selected ROIs (e.g. PTV, lungs, spinal cord, esophagus, and heart) on pCT and rCT. The mesh vertices were input into a thin-plate spline algorithm to generate a reference displacement vector field (DVF). The reference DVF was used to deform pCT to generate a simulated replanning CT (srCT) that was closely matched to rCT. Three DIR algorithms (Demons, B-Spline, and intensity-based) were applied to these ten virtual phantoms. The images, ROIs, and doses were mapped from pCT to srCT using the DVFs computed by these three DIRs and compared to those mapped using the reference DVF. Results: The average Dice coefficients for selected ROIs were from 0.85 to 0.96 for Demons, from 0.86 to 0.97 for intensity-based, and from 0.76 to 0.95 for B-Spline. The average Hausdorff distances for selected ROIs were from 2.2 to 5.4 mm for Demons, from 2.3 to 6.8 mm for intensity-based, and from 2.4 to 11.4 mm for B-Spline. The average absolute dose errors for selected ROIs were from 0.2 to 0.6 Gy for Demons, from 0.1 to 0.5 Gy for intensity-based, and from 0.5 to 1.5 Gy for B-Spline. Conclusion: Virtual phantoms were modeled after patients with lung cancer and were clinically relevant for adaptive radiotherapy treatment replanning. Virtual phantoms with known DVFs serve as references and can provide a fair comparison when evaluating different DIRs. Demons and intensity-based DIRs were shown to have smaller geometric and dosimetric uncertainties than B-Spline. Z Shen: None; K Bzdusek: an employee of Philips Healthcare; J Greskovich: None; P Xia

  1. SU-E-J-115: Correlation of Displacement Vector Fields Calculated by Deformable Image Registration Algorithms with Motion Parameters of CT Images with Well-Defined Targets and Controlled-Motion

    Energy Technology Data Exchange (ETDEWEB)

    Jaskowiak, J; Ahmad, S; Ali, I [University of Oklahoma Health Sciences Center, Oklahoma City, OK (United States); Alsbou, N [Ohio Northern University, Ada, OH (United States)

    2015-06-15

    Purpose: To investigate correlation of displacement vector fields (DVF) calculated by deformable image registration algorithms with motion parameters in helical axial and cone-beam CT images with motion artifacts. Methods: A mobile thorax phantom with well-known targets with different sizes that were made from water-equivalent material and inserted in foam to simulate lung lesions. The thorax phantom was imaged with helical, axial and cone-beam CT. The phantom was moved with a cyclic motion with different motion amplitudes and frequencies along the superior-inferior direction. Different deformable image registration algorithms including demons, fast demons, Horn-Shunck and iterative-optical-flow from the DIRART software were used to deform CT images for the phantom with different motion patterns. The CT images of the mobile phantom were deformed to CT images of the stationary phantom. Results: The values of displacement vectors calculated by deformable image registration algorithm correlated strongly with motion amplitude where large displacement vectors were calculated for CT images with large motion amplitudes. For example, the maximal displacement vectors were nearly equal to the motion amplitudes (5mm, 10mm or 20mm) at interfaces between the mobile targets lung tissue, while the minimal displacement vectors were nearly equal to negative the motion amplitudes. The maximal and minimal displacement vectors matched with edges of the blurred targets along the Z-axis (motion-direction), while DVF’s were small in the other directions. This indicates that the blurred edges by phantom motion were shifted largely to match with the actual target edge. These shifts were nearly equal to the motion amplitude. Conclusions: The DVF from deformable-image registration algorithms correlated well with motion amplitude of well-defined mobile targets. This can be used to extract motion parameters such as amplitude. However, as motion amplitudes increased, image artifacts increased

  2. The effect of rigid and non-rigid connections between implants and teeth on biological and technical complications: a systematic review and a meta-analysis.

    Science.gov (United States)

    Tsaousoglou, Phoebus; Michalakis, Konstantinos; Kang, Kiho; Weber, Hans-Peter; Sculean, Anton

    2017-07-01

    To assess survival, as well as technical and biological complication rates of partial fixed dental prostheses (FDPs) supported by implants and teeth. An electronic Medline search was conducted to identify articles, published in dental journals from January 1980 to August 2015, reporting on partial FDPs supported by implants and teeth. The search terms were categorized into four groups comprising the PICO question. Manual searches of published full-text articles and related reviews were also performed. The initial database search produced 3587 relevant titles. Three hundred and eighty-six articles were retrieved for abstract review, while 39 articles were selected for full-text review. A total of 10 studies were selected for inclusion. Overall survival rate for implants ranged between 90% and 100%, after follow-up periods with a mean range of 18-120 months. The survival of the abutment teeth was 94.1-100%, while the prostheses survival was 85-100% for the same time period. The most frequent complications were "periapical lesions" (11.53%). The most frequent technical complication was "porcelain occlusal fracture" (16.6%), followed by "screw loosening" (15%). According to the meta-analysis, no intrusion was noted on the rigid connection group, while five teeth (8.19%) were intruded in the non-rigid connection group [95% CI (0.013-0.151)]. The tooth-implant FDP seems to be a possible alternative to an implant-supported FDP. There is limited evidence that rigid connection between teeth and implants presents better results when compared with the non-rigid one. The major drawback of non-rigidly connected FDPs is tooth intrusion. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  3. SU-F-BRF-09: A Non-Rigid Point Matching Method for Accurate Bladder Dose Summation in Cervical Cancer HDR Brachytherapy

    Energy Technology Data Exchange (ETDEWEB)

    Chen, H; Zhen, X; Zhou, L [Southern Medical University, Guangzhou, Guangdong (China); Zhong, Z [The University of Texas at Dallas, Department of Computer Science, TX (United States); Pompos, A; Yan, H; Jiang, S; Gu, X [UT Southwestern Medical Center, Dallas, TX (United States)

    2014-06-15

    Purpose: To propose and validate a deformable point matching scheme for surface deformation to facilitate accurate bladder dose summation for fractionated HDR cervical cancer treatment. Method: A deformable point matching scheme based on the thin plate spline robust point matching (TPSRPM) algorithm is proposed for bladder surface registration. The surface of bladders segmented from fractional CT images is extracted and discretized with triangular surface mesh. Deformation between the two bladder surfaces are obtained by matching the two meshes' vertices via the TPS-RPM algorithm, and the deformation vector fields (DVFs) characteristic of this deformation is estimated by B-spline approximation. Numerically, the algorithm is quantitatively compared with the Demons algorithm using five clinical cervical cancer cases by several metrics: vertex-to-vertex distance (VVD), Hausdorff distance (HD), percent error (PE), and conformity index (CI). Experimentally, the algorithm is validated on a balloon phantom with 12 surface fiducial markers. The balloon is inflated with different amount of water, and the displacement of fiducial markers is benchmarked as ground truth to study TPS-RPM calculated DVFs' accuracy. Results: In numerical evaluation, the mean VVD is 3.7(±2.0) mm after Demons, and 1.3(±0.9) mm after TPS-RPM. The mean HD is 14.4 mm after Demons, and 5.3mm after TPS-RPM. The mean PE is 101.7% after Demons and decreases to 18.7% after TPS-RPM. The mean CI is 0.63 after Demons, and increases to 0.90 after TPS-RPM. In the phantom study, the mean Euclidean distance of the fiducials is 7.4±3.0mm and 4.2±1.8mm after Demons and TPS-RPM, respectively. Conclusions: The bladder wall deformation is more accurate using the feature-based TPS-RPM algorithm than the intensity-based Demons algorithm, indicating that TPS-RPM has the potential for accurate bladder dose deformation and dose summation for multi-fractional cervical HDR brachytherapy. This work is supported

  4. Free-form image registration of human cochlear μCT data using skeleton similarity as anatomical prior

    DEFF Research Database (Denmark)

    Kjer, Hans Martin; Fagertun, Jens; Vera, Sergio

    2016-01-01

    Better understanding of the anatomical variability of the human cochlear is important for the design and function of Cochlear Implants. Proper non-rigid alignment of high-resolution cochlear μCT data is a challenge for the typical cubic B-spline registration model. In this paper we study one way...... of incorporating skeleton-based similarity as an anatomical registration prior. We extract a centerline skeleton of the cochlear spiral, and generate corresponding parametric pseudo-landmarks between samples. These correspondences are included in the cost function of a typical cubic B-spline registration model...

  5. Distribution pattern of left-ventricular myocardial strain analyzed by a cine MRI based deformation registration algorithm in healthy Chinese volunteers

    Science.gov (United States)

    Liu, Hong; Yang, Dan; Wan, Ke; Luo, Yong; Sun, Jia-Yu; Zhang, Tian-Jing; Li, Wei-Hao; Greiser, Andreas; Jolly, Marie-Pierre; Zhang, Qing; Chen, Yu-Cheng

    2017-01-01

    The cine magnetic resonance imaging based technique feature tracking-cardiac magnetic resonance (FT-CMR) is emerging as a novel, simple and robust method to evaluate myocardial strain. We investigated the distribution characteristics of left-ventricular myocardial strain using a novel cine MRI based deformation registration algorithm (DRA) in a cohort of healthy Chinese subjects. A total of 130 healthy Chinese subjects were enrolled. Three components of orthogonal strain (radial, circumferential, longitudinal) of the left ventricle were analyzed using DRA on steady-state free precession cine sequence images. A distinct transmural circumferential strain gradient was observed in the left ventricle that showed universal increment from the epicardial to endocardial myocardial wall (epiwall: −15.4 ± 1.9%; midwall: −18.8 ± 2.0%; endowall: −22.3 ± 2.3%, P < 0.001). Longitudinal strain showed a similar trend from epicardial to endocardial layers (epiwall: −16.0 ± 2.9%; midwall: −15.6 ± 2.7%; endowall: −14.8 ± 2.4%, P < 0.001), but radial strain had a very heterogeneous distribution and variation. In the longitudinal direction from the base to the apex of the left ventricle, there was a trend of decreasing peak systolic longitudinal strain (basal: −23.3 ± 4.6%; mid: −13.7 ± 7.3%; apical: −13.2 ± 5.5%; P < 0.001). In conclusion, there are distinct distribution patterns of circumferential and longitudinal strain within the left ventricle in healthy Chinese subjects. These distribution patterns of strain may provide unique profiles for further study in different types of myocardial disease. PMID:28349989

  6. Distribution pattern of left-ventricular myocardial strain analyzed by a cine MRI based deformation registration algorithm in healthy Chinese volunteers.

    Science.gov (United States)

    Liu, Hong; Yang, Dan; Wan, Ke; Luo, Yong; Sun, Jia-Yu; Zhang, Tian-Jing; Li, Wei-Hao; Greiser, Andreas; Jolly, Marie-Pierre; Zhang, Qing; Chen, Yu-Cheng

    2017-03-28

    The cine magnetic resonance imaging based technique feature tracking-cardiac magnetic resonance (FT-CMR) is emerging as a novel, simple and robust method to evaluate myocardial strain. We investigated the distribution characteristics of left-ventricular myocardial strain using a novel cine MRI based deformation registration algorithm (DRA) in a cohort of healthy Chinese subjects. A total of 130 healthy Chinese subjects were enrolled. Three components of orthogonal strain (radial, circumferential, longitudinal) of the left ventricle were analyzed using DRA on steady-state free precession cine sequence images. A distinct transmural circumferential strain gradient was observed in the left ventricle that showed universal increment from the epicardial to endocardial myocardial wall (epiwall: -15.4 ± 1.9%; midwall: -18.8 ± 2.0%; endowall: -22.3 ± 2.3%, P < 0.001). Longitudinal strain showed a similar trend from epicardial to endocardial layers (epiwall: -16.0 ± 2.9%; midwall: -15.6 ± 2.7%; endowall: -14.8 ± 2.4%, P < 0.001), but radial strain had a very heterogeneous distribution and variation. In the longitudinal direction from the base to the apex of the left ventricle, there was a trend of decreasing peak systolic longitudinal strain (basal: -23.3 ± 4.6%; mid: -13.7 ± 7.3%; apical: -13.2 ± 5.5%; P < 0.001). In conclusion, there are distinct distribution patterns of circumferential and longitudinal strain within the left ventricle in healthy Chinese subjects. These distribution patterns of strain may provide unique profiles for further study in different types of myocardial disease.

  7. Locally orderless registration

    DEFF Research Database (Denmark)

    Darkner, Sune; Sporring, Jon

    2013-01-01

    This paper presents a unifying approach for calculating a wide range of popular, but seemingly very different, similarity measures. Our domain is the registration of n-dimensional images sampled on a regular grid, and our approach is well suited for gradient-based optimization algorithms. Our...... approach is based on local intensity histograms and built upon the technique of Locally Orderless Images. Histograms by Locally Orderless Images are well posed and offer explicit control over the 3 inherent and unavoidable scales: the spatial resolution, intensity levels, and spatial extent of local......, and we compare these variations both theoretically, and empirically. Finally, using our algorithm, we explain the empirically observed differences between two popular joint density estimation techniques used in registration: Parzen Windows and Generalized Partial Volume....

  8. Image registration

    CERN Document Server

    Goshtasby, A Ardeshir

    2012-01-01

    This book presents a thorough and detailed guide to image registration, outlining the principles and reviewing state-of-the-art tools and methods. The book begins by identifying the components of a general image registration system, and then describes the design of each component using various image analysis tools. The text reviews a vast array of tools and methods, not only describing the principles behind each tool and method, but also measuring and comparing their performances using synthetic and real data. Features: discusses similarity/dissimilarity measures, point detectors, feature extr

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

    Science.gov (United States)

    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.

  10. Ab initio effective rotational and rovibrational Hamiltonians for non-rigid systems via curvilinear second order vibrational M{\\o}ller-Plesset perturbation theory

    CERN Document Server

    Changala, P Bryan

    2016-01-01

    We present a perturbative method for ab initio calculations of rotational and rovibrational effective Hamiltonians of both rigid and non-rigid molecules. Our approach is based on a curvilinear implementation of second order vibrational M{\\o}ller-Plesset perturbation theory (VMP2) extended to include rotational effects via a second order contact transformation. Though more expensive, this approach is significantly more accurate than standard second order vibrational perturbation theory (VPT2) for systems that are poorly described to zeroth order by rectilinear normal mode harmonic oscillators. We apply this method and demonstrate its accuracy on two molecules: Si$_2$C, a quasilinear triatomic with significant bending anharmonicity, and CH$_3$NO$_2$, which contains a completely unhindered methyl rotor. In addition to these two examples, we discuss several key technical aspects of the method, including an efficient implementation of Eckart and quasi-Eckart frame embedding that does not rely on numerical finite d...

  11. 一种用于视频超分辨率重建的块匹配图像配准方法%A Block-matching Image Registration Algorithm for Video Super-resolution Reconstruction

    Institute of Scientific and Technical Information of China (English)

    孙琰玥; 何小海; 宋海英; 陈为龙

    2011-01-01

    图像配准是超分辨率重建中的一个关键问题,直接影响超分辨率重建图像的质量.本文在自适应十字搜索(Adaptive rood pattern search,ARPS)块匹配算法的基础上,根据小波域中各图像之间的相关性,提出一种分层块匹配算法-基于小波变换的改进的自适应十字模式搜索算法(Improved adaptive rood pattern search algorithm based on wavelet transform,W-IARPS),该方法在小波变换域完成匹配宏块的搜索,有效地减少了匹配点的搜索个数,且配准图像的峰值信噪比相比全搜索算法下降不到0.1dB,保持了较高的配准精度.最后采用凸集投影(Projections onto convex sets,POCS)算法对配准后的图像进行超分辨率重建,取得了较好的视觉效果.实验结果表明,该方法具有较高的配准精度和重建效果,算法稳健可靠.%Image registration is one of the key components in super-resolution reconstruction, and it directly affects the quality of the reconstructed image. On the basis of adaptive rood pattern search (ARPS) block-matching algorithm,and according to the correlation between various images in wavelet domain, an hierarchical block-matching algorithm - improved adaptive rood pattern search algorithm based on wavelet transform (W-IARPS) is proposed. Searching matched-macroblocks in wavelet domain can effectively reduce the number of search points, and the ratio of peak signal to noise of registered images decreases less than 0.1 dB compared to the exhaustive-search algorithm. It means that the high registration accuracy is guaranteed. Finally, the projections onto convex sets (POCS) method is used to reconstruct the super-resolution image from the registered images, and it can achieve better visual effects. The simulation results show that the algorithm has a high registration accuracy and reliable reconstruction results.

  12. Rapid Registration Algorithm of Large-Scale Images Based on Normalized Gradient Phase Correlation%基于归一化梯度相位相关的大尺度图像快速配准算法

    Institute of Scientific and Technical Information of China (English)

    陈怀玉; 杨旸

    2015-01-01

    To solve the real﹣time registration problem of large﹣scale images with rotations, scalings, translations simultaneously, an image registration algorithm based on normalized gradient phase correlation is proposed in this paper. The complicated multilayer computation, interpolation and iteration is avoided in this algorithm. Plural gradient images are disposed by normalized gradient phase correlation. Giving consideration to robustness and rapidity of parameters estimation at the same time, this algorithm can efficiently expand the estimation range of transformation parameters. By means of parameter﹣adjustable window function, it can suppress the influence of the edge effect of the different kinds of images. Experimental results illustrate the rapidity and effectiveness of the proposed algorithm.%针对具有旋转、缩放、平移的大尺度变换图像的实时配准问题,提出基于归一化梯度相位相关的图像配准算法。该算法避免复杂的多层插值计算和迭代处理过程,利用归一化梯度相位相关法处理复数梯度图像,能在兼顾参数估计的鲁棒性和快速性的同时,扩大图像变换参数的估计范围。并通过一种参数可调整的窗函数有效抑制不同种类图像的边缘效应的影响。实验证明该算法的快速性和有效性。

  13. Masked object registration in the Fourier domain.

    Science.gov (United States)

    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.

  14. Progressive refinement for robust image registration

    Institute of Scientific and Technical Information of China (English)

    Li Song; Yuanhua Zhou; Jun Zhou

    2005-01-01

    @@ A new image registration algorithm with robust cost function and progressive refinement estimation is developed on the basis of direct method (DM). The robustness lies in M-estimation to avert larger local noise and outliers.

  15. Research on Sonar Image Registration and Fusion Based on SURF Algorithm%基于SURF的声纳图像配准与融合方法研究

    Institute of Scientific and Technical Information of China (English)

    郭军

    2013-01-01

    针对侧扫声纳图像分辨率高测深精度低而多波束声纳图像分辨率低测深精度高的特点,提出了一种基于SUFR的声纳图像自动配准与融合方法.该算法检测同一区域内侧扫声纳图像和多波束图像的特征点,通过最近邻匹配获得匹配点后,计算图像间的变换矩阵,利用空间变换完成配准,采用加权融合法实现两者的融合.实验结果表明该算法具有很好的鲁棒性,配准精度达到像素级,可实现两者的高精度自动配准与融合,取得了理想的效果.%According to multi - beam sonar system, the high - resolution backscatter but poor horizontal position accuracy, and side -scan sonar system, the accurate bathymetry and horizontal position but low resolution, the study is concerned with an automatic registration and fusion method of sonar image based on SURF. To achieve the integration of multi - beam sonar system and side - scan sonar system with the weighted fusion method, it extracts feature points by using SURF, computes transformation matrix by using match points, and performs registration and fusion with a spatial transform. The results indicate that this method is robust and stable with registration accuracy up to pixel level realizing the quite precise automatic registration and fusion, and is more suitable for sonar image.

  16. Mass preserving image registration for lung CT

    DEFF Research Database (Denmark)

    Gorbunova, Vladlena; Sporring, Jon; Lo, Pechin Chien Pau

    2012-01-01

    This paper presents a mass preserving image registration algorithm for lung CT images. To account for the local change in lung tissue intensity during the breathing cycle, a tissue appearance model based on the principle of preservation of total lung mass is proposed. This model is incorporated...... into a standard image registration framework with a composition of a global affine and several free-form B-Spline transformations with increasing grid resolution. The proposed mass preserving registration method is compared to registration using the sum of squared intensity differences as a similarity function...... inhale phases of 4D-CT images. Registration errors, measured as the average distance between vessel tree centerlines in the matched images, are significantly lower for the proposed mass preserving image registration method in the second, third and fourth group, while there is no statistically significant...

  17. The relative weight of shape and non-rigid motion cues in object perception: a model of the parameters underlying dynamic object discrimination.

    Science.gov (United States)

    Vuong, Quoc C; Friedman, Alinda; Read, Jenny C A

    2012-03-16

    Shape and motion are two dominant cues for object recognition, but it can be difficult to investigate their relative quantitative contribution to the recognition process. In the present study, we combined shape and non-rigid motion morphing to investigate the relative contributions of both types of cues to the discrimination of dynamic objects. In Experiment 1, we validated a novel parameter-based motion morphing technique using a single-part three-dimensional object. We then combined shape morphing with the novel motion morphing technique to pairs of multipart objects to create a joint shape and motion similarity space. In Experiment 2, participants were shown pairs of morphed objects from this space and responded "same" on the basis of motion-only, shape-only, or both cues. Both cue types influenced judgments: When responding to only one cue, the other cue could be ignored, although shape cues were more difficult to ignore. When responding on the basis of both cues, there was an overall bias to weight shape cues more than motion cues. Overall, our results suggest that shape influences discrimination more than motion even when both cue types have been made quantitatively equivalent in terms of their individual discriminability.

  18. Combined use of a priori data for fast system self-calibration of a non-rigid multi-camera fringe projection system

    Science.gov (United States)

    Stavroulakis, Petros I.; Chen, Shuxiao; Sims-Waterhouse, Danny; Piano, Samanta; Southon, Nicholas; Bointon, Patrick; Leach, Richard

    2017-06-01

    In non-rigid fringe projection 3D measurement systems, where either the camera or projector setup can change significantly between measurements or the object needs to be tracked, self-calibration has to be carried out frequently to keep the measurements accurate1. In fringe projection systems, it is common to use methods developed initially for photogrammetry for the calibration of the camera(s) in the system in terms of extrinsic and intrinsic parameters. To calibrate the projector(s) an extra correspondence between a pre-calibrated camera and an image created by the projector is performed. These recalibration steps are usually time consuming and involve the measurement of calibrated patterns on planes, before the actual object can continue to be measured after a motion of a camera or projector has been introduced in the setup and hence do not facilitate fast 3D measurement of objects when frequent experimental setup changes are necessary. By employing and combining a priori information via inverse rendering, on-board sensors, deep learning and leveraging a graphics processor unit (GPU), we assess a fine camera pose estimation method which is based on optimising the rendering of a model of a scene and the object to match the view from the camera. We find that the success of this calibration pipeline can be greatly improved by using adequate a priori information from the aforementioned sources.

  19. Accelerating Neuroimage Registration through Parallel Computation of Similarity Metric.

    Directory of Open Access Journals (Sweden)

    Yun-Gang Luo

    Full Text Available Neuroimage registration is crucial for brain morphometric analysis and treatment efficacy evaluation. However, existing advanced registration algorithms such as FLIRT and ANTs are not efficient enough for clinical use. In this paper, a GPU implementation of FLIRT with the correlation ratio (CR as the similarity metric and a GPU accelerated correlation coefficient (CC calculation for the symmetric diffeomorphic registration of ANTs have been developed. The comparison with their corresponding original tools shows that our accelerated algorithms can greatly outperform the original algorithm in terms of computational efficiency. This paper demonstrates the great potential of applying these registration tools in clinical applications.

  20. Application of MD5 Encryption Algorithm in Registration and Login Verification Module%MD5加密算法在注册及登录验证模块中的应用

    Institute of Scientific and Technical Information of China (English)

    周小红; 周建伙

    2015-01-01

    With the development of Internet technology,information security is becoming more and more popular.This pa-per introduces the basic principle of the MD5 encryption algorithm.The application of MD5 encryption algorithm in the regis-tration and login verification module in the.NET environment through Visual C# is introduced in detail.The security of MD5 al-gorithm is analyzed.Final y,put forward and realize the improvement method.%随着互联网技术的发展,信息安全越来越受到人们的关注。介绍了MD5加密算法的基本原理,详细介绍如何在。 NET环境下通过Visual C#实现MD5加密算法在注册及登录验证模块中的应用。分析MD5算法的安全性,最后提出并实现自己的改进方法。

  1. Acute high-grade acromioclavicular joint injuries treatment: Arthroscopic non-rigid coracoclavicular fixation provides better quality of life outcomes than hook plate ORIF.

    Science.gov (United States)

    Natera-Cisneros, L; Sarasquete-Reiriz, J; Escolà-Benet, A; Rodriguez-Miralles, J

    2016-02-01

    Treatment of acute high-grade acromioclavicular joint (ACJ) injuries with metal hardware alters the biomechanics of the ACJ, implying a second surgery for hardware removal. The period during which the plate is present involves functional limitations, pain and a risk factor for the development of hardware-related-injuries. Arthroscopy-assisted procedures compared to open-metal hardware techniques offer: less morbidity, the possibility to treat associated lesions and no need for a second operation. The aim was to compare the Quality of life (QoL) of patients with acute high-grade ACJ injuries (Rockwood grade III-V), managed arthroscopically with a non-rigid coracoclavicular (CC) fixation versus the QoL of patients managed with a hook plate, 24 months or more after their shoulder injury. A retrospective revision of high-grade ACJ injuries managed in three institutions was performed. Patients treated by means of an arthroscopy-assisted CC fixation or by means of a hook plate were included. The inclusion period was between 2008 and 2012. The QoL was evaluated at the last follow-up visit by means of the SF36, the visual analog scale (VAS), the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire, the Constant score and the global satisfaction (scale from 0 to 10). The presence of scapular dyskinesis and remaining vertical instability were evaluated. Comparison between groups was performed. Thirty-one patients were included: 20 arthroscopy-group (ARTH group: 3 Rockwood III, 3 IV and 14 V) and 11 hook plate-group (HOOK group: 5 Rockwood III and 6 V). The mean age was 36 [25-52] year-old for the ARTH group and 41 [19-55] for the HOOK group (P=0.185). The mean results of the questionnaires were: (1) physical SF36 score (ARTH group 58.24±2.16 and HOOK group 53.70±4.33, P<0.001); (2) mental SF36 score (ARTH group 56.15±2.21 and HOOK group 53.06±6.10, P=0.049); (3) VAS (ARTH group 0.40±0.50 and HOOK group 1.45±1.51, P=0.007); (4) DASH (ARTH group 2.98±2.03 and

  2. Creation of 3D digital anthropomorphic phantoms which model actual patient non-rigid body motion as determined from MRI and position tracking studies of volunteers

    Science.gov (United States)

    Connolly, C. M.; Konik, A.; Dasari, P. K. R.; Segars, P.; Zheng, S.; Johnson, K. L.; Dey, J.; King, M. A.

    2011-03-01

    Patient motion can cause artifacts, which can lead to difficulty in interpretation. The purpose of this study is to create 3D digital anthropomorphic phantoms which model the location of the structures of the chest and upper abdomen of human volunteers undergoing a series of clinically relevant motions. The 3D anatomy is modeled using the XCAT phantom and based on MRI studies. The NURBS surfaces of the XCAT are interactively adapted to fit the MRI studies. A detailed XCAT phantom is first developed from an EKG triggered Navigator acquisition composed of sagittal slices with a 3 x 3 x 3 mm voxel dimension. Rigid body motion states are then acquired at breath-hold as sagittal slices partially covering the thorax, centered on the heart, with 9 mm gaps between them. For non-rigid body motion requiring greater sampling, modified Navigator sequences covering the entire thorax with 3 mm gaps between slices are obtained. The structures of the initial XCAT are then adapted to fit these different motion states. Simultaneous to MRI imaging the positions of multiple reflective markers on stretchy bands about the volunteer's chest and abdomen are optically tracked in 3D via stereo imaging. These phantoms with combined position tracking will be used to investigate both imaging-data-driven and motion-tracking strategies to estimate and correct for patient motion. Our initial application will be to cardiacperfusion SPECT imaging where the XCAT phantoms will be used to create patient activity and attenuation distributions for each volunteer with corresponding motion tracking data from the markers on the body-surface. Monte Carlo methods will then be used to simulate SPECT acquisitions, which will be used to evaluate various motion estimation and correction strategies.

  3. Unmanned Aerial Vehicle Serial Aerial Image Automatic Registration Based on Improved SIFT Algorithm%改进SIFT算法的小型无人机航拍图像自动配准

    Institute of Scientific and Technical Information of China (English)

    熊自明; 万刚; 闫鹤; 李明

    2012-01-01

    针对小型无人机航拍图像视点离散、视角变化有一定运动规律的特点,首先对航拍图像进行数据预处理,结合Harris特征点和SIFT特征向量的优势,提取Harris特征点、计算特征点的特征半径和SIFT特征向量,并利用PCA降低特征向量的维数;然后采用最邻近(NN)方法进行特征匹配,利用BBF算法搜索特征的最邻近以提高匹配速度;最后采用PROSAC算法提纯特征点匹配对并精确计算运动模型参数,实现了图像的自动配准.实验证明,该图像配准方法在准确性、效率方面较经典的SIFT算法有较大的提高.%Due to the disperse and regular of view points and the view angle of UAV Aerial Image, the image data was preconditioned at first, then the Harris feature points with SIFT feature vectors were combined, Harris feature points were extracted, the characteristics radius of feature points and SIFT feature vector was calculated, and PCA (Principal Component Analysis) was used to reduce the dimension of SIFT feature vectors. And then the most close method (NN) was used to feature matching, the BBF algorithm was applied to search the nearest neighbor feature for improving the matching speed. Finally, the PROSAC algorithm was used to purify initial feature point matching pairs, and motion model parameters were calculated, the image automatic registration was achieved. The results of experiment proved that such algorithm was more efficient and exact than the classic SIFT algorithm.

  4. Scaling registration of multiview range scans via motion averaging

    Science.gov (United States)

    Zhu, Jihua; Zhu, Li; Jiang, Zutao; Li, Zhongyu; Li, Chen; Zhang, Fan

    2016-07-01

    Three-dimensional modeling of scene or object requires registration of multiple range scans, which are obtained by range sensor from different viewpoints. An approach is proposed for scaling registration of multiview range scans via motion averaging. First, it presents a method to estimate overlap percentages of all scan pairs involved in multiview registration. Then, a variant of iterative closest point algorithm is presented to calculate relative motions (scaling transformations) for these scan pairs, which contain high overlap percentages. Subsequently, the proposed motion averaging algorithm can transform these relative motions into global motions of multiview registration. In addition, it also introduces the parallel computation to increase the efficiency of multiview registration. Furthermore, it presents the error criterion for accuracy evaluation of multiview registration result, which can make it easy to compare results of different multiview registration approaches. Experimental results carried out with public available datasets demonstrate its superiority over related approaches.

  5. Registration of planar bioluminescence to magnetic resonance and x-ray computed tomography images as a platform for the development of bioluminescence tomography reconstruction algorithms.

    Science.gov (United States)

    Beattie, Bradley J; Klose, Alexander D; Le, Carl H; Longo, Valerie A; Dobrenkov, Konstantine; Vider, Jelena; Koutcher, Jason A; Blasberg, Ronald G

    2009-01-01

    The procedures we propose make possible the mapping of two-dimensional (2-D) bioluminescence image (BLI) data onto a skin surface derived from a three-dimensional (3-D) anatomical modality [magnetic resonance (MR) or computed tomography (CT)] dataset. This mapping allows anatomical information to be incorporated into bioluminescence tomography (BLT) reconstruction procedures and, when applied using sources visible to both optical and anatomical modalities, can be used to evaluate the accuracy of those reconstructions. Our procedures, based on immobilization of the animal and a priori determined fixed projective transforms, should be more robust and accurate than previously described efforts, which rely on a poorly constrained retrospectively determined warping of the 3-D anatomical information. Experiments conducted to measure the accuracy of the proposed registration procedure found it to have a mean error of 0.36+/-0.23 mm. Additional experiments highlight some of the confounds that are often overlooked in the BLT reconstruction process, and for two of these confounds, simple corrections are proposed.

  6. A Multistage Approach for Image Registration.

    Science.gov (United States)

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

    2016-09-01

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

  7. 窗口自适应更新的柔性目标视频跟踪%Visual Tracking with Window Updating of Non-rigid Object

    Institute of Scientific and Technical Information of China (English)

    李翠君; 王成儒

    2012-01-01

    运动人体目标的跟踪一直是视频监控中研究的重点.本文主要侧重柔性目标变形的方面,以HSI颜色模型进行模板的学习,在当前帧中得到模板,并且统计每一帧图像的信息量,然后在一下帧中进行Kalman预测.将预测到的区域与模板比较判断之后再决定是否更新模板,减少了一定的计算量,为了约束窗口的变化,引入信息量的概念,信息量由HSI颜色空间的I的特征点计算得到.这样,一直更新模板和窗口直至准确有效地跟踪人体目标.实验表明,在人体发生较大形变的过程中,会持续的跟踪人体,不会发生跟踪丢失的问题.%The human tracking is the key in the video surveillance. This text focuses on non-rigid objects, learning based on the HSI color model template. Each pixel of the template is modeled using two components with H and S. Get template from the current frame, statistic the information of every frame, and predict in the next frame using Kalman filter. Decide whether to update the template after comparing the forecast region and the template, reducing the amount of calculation. And for restraining the tracking window, information which is calculated from the color I is introduced. After that, the template and the window will be updated. The experimental results show that the proposed method achieves continuously tracking, and resolve the problem with the object disappeared.

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

    Science.gov (United States)

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

    2016-06-01

    Image registration is a basic task in medical image processing applications like group analysis and atlas construction. Similarity measure is a critical ingredient of image registration. Intensity distortion of medical images is not considered in most previous similarity measures. Therefore, in the presence of bias field distortions, they do not generate an acceptable registration. In this paper, we propose a sparse based similarity measure for mono-modal images that considers non-stationary intensity and spatially-varying distortions. The main idea behind this measure is that the aligned image is constructed by an analysis dictionary trained using the image patches. For this purpose, we use "Analysis K-SVD" to train the dictionary and find the sparse coefficients. We utilize image patches to construct the analysis dictionary and then we employ the proposed sparse similarity measure to find a non-rigid transformation using free form deformation (FFD). Experimental results show that the proposed approach is able to robustly register 2D and 3D images in both simulated and real cases. The proposed method outperforms other state-of-the-art similarity measures and decreases the transformation error compared to the previous methods. Even in the presence of bias field distortion, the proposed method aligns images without any preprocessing.

  9. Myocardial deformation from tagged MRI in hypertrophic cardiomyopathy using an efficient registration strategy

    Science.gov (United States)

    Piella, G.; De Craene, M.; Oubel, E.; Larrabide, I.; Huguet, M.; Bijnens, B. H.; Frangi, A. F.

    2009-02-01

    This paper combines different parallelization strategies for speeding up motion and deformation computation by non-rigid registration of a sequence of images. The registration is performed in a two-level acceleration approach: (1) parallelization of each registration process using MPI and/or threads, and (2) distribution of the sequential registrations over a cluster. On a 24-node double quad-core Intel Xeon (2.66 GHz CPU, 16 GB RAM) cluster, the method is demonstrated to efficiently compute the deformation of a cardiac sequence reducing the computation time from more than 3 hours to a couple of minutes (for low downsampled images). It is shown that the distribution of the sequential registrations over the cluster together with the parallelization of each pairwise registration by multithreading lowers the computation time towards values compatible with clinical requirements (a few minutes per patient). The combination of MPI and multithreading is only advantageous for large input data sizes. Performances are assessed for the specific scenario of aligning cardiac sequences of taggedMagnetic Resonance (tMR) images, with the aim of comparing strain in healthy subjects and hypertrophic cardiomyopathy (HCM) patients. In particular, we compared the distribution of systolic strain in both populations. On average, HCM patients showed lower average values of strain with larger deviation due to the coexistence of regions with impaired deformation and regions with normal deformation.

  10. Multiple Kernel Point Set Registration.

    Science.gov (United States)

    Nguyen, Thanh Minh; Wu, Q M Jonathan

    2016-06-01

    The finite Gaussian mixture model with kernel correlation is a flexible tool that has recently received attention for point set registration. While there are many algorithms for point set registration presented in the literature, an important issue arising from these studies concerns the mapping of data with nonlinear relationships and the ability to select a suitable kernel. Kernel selection is crucial for effective point set registration. We focus here on multiple kernel point set registration. We make several contributions in this paper. First, each observation is modeled using the Student's t-distribution, which is heavily tailed and more robust than the Gaussian distribution. Second, by automatically adjusting the kernel weights, the proposed method allows us to prune the ineffective kernels. This makes the choice of kernels less crucial. After parameter learning, the kernel saliencies of the irrelevant kernels go to zero. Thus, the choice of kernels is less crucial and it is easy to include other kinds of kernels. Finally, we show empirically that our model outperforms state-of-the-art methods recently proposed in the literature.

  11. 一种DEM套合自动检查算法的设计与实现%The Design and Implementation of Auto- Checking Algorithm of DEM Registration

    Institute of Scientific and Technical Information of China (English)

    张新利

    2012-01-01

    检查DEM(Digital Elevation Model)与相应DLG(Digital Line graph)的等高线套合是否合理是DEM产品生产质量检查中的重要内容。本文从生产实际出发,针对DEM数据特点与现有DEM套合检查的缺点,提出了一种自动检查DEM套合检查算法,并基于C#.Net给予了实现。通过在国家基础测绘1:50 000测图项目中的实践应用,结果表明该算法检查结果正确、可靠、算法性能稳定,与人工方式相比,可以大大提高DEM套合检查的自动化程度和准确度,从而提高生产作业效率。%Checking if the matching of DEM (Digital Elevation Model) and the corresponding DLG (Digital Line Graph) contour is reasonable is important to check the contents of the DEM production quality inspection. From production reality, a new algorithm for auto - checking of DEM matching with DLG - contour is proposed according to DEM data characteristics and shortcomings of the exist- ing DEM matching check,, and given implementation based on C#.. Net.. Through the practical application of the national basic sur- veying and mapping in 1 : 50 000 mapping project, the results show that the algorithm is correct, reliable, and stable. Compared to the artificial checking, it can greatly promote the automation and accuracy of the DEM matching check to improve the efficiency of produc- tion operations.

  12. A GPU Based Improved Demons Algorithm for CT to CBCT Deformable Image Registration%GPU框架下基于改进Demons算法的CT-CBCT图像变形配准研究

    Institute of Scientific and Technical Information of China (English)

    王琳婧; 张书旭; 张海南; 沈国辉; 余辉; 彭莹莹

    2013-01-01

    Objective:To propose a GPU-based fast CT to Cone-beam CT (CBCT) deformable image registration (DIR)method for adaptive radiotherapy.Methods:Before calculating deformation moving vector field using origin demons,an intensity correction step is first performed in CBCT by matching the first and the second moments of the voxel intensities inside a patch around the voxel with those on the CT image.This improved demons algorithm is implanted on the GPU fiamework using CUDA language.Results:We use CT and CBCT images from five clinical head-and-neck cancer patients to evaluate our algorithm,and compare the DIR results with that of the classic demons algorithm.The results show that our method can register CT and CBCT images with high accuracy in about 80 seconds.Conclusions:We have proposed and evaluated an improved demons algorithm for CT-CBCT DIR based on the GPU framework,and this improved method is a promising tool for clinical adaptive radiotherapy.%目的:针对自适应放射治疗中的关键技术——CT和CBCT图像变形配准问题,提出一种基于图形处理器GPU的改进Demons配准算法.方法:通过匹配CT和CBCT图像相应体素局部邻域点集的k阶样本矩,计算CBCT图像每一个体素CT值的线性变换系数,并在每一次Demons迭代过程中,对原CBCT图像逐体素做CT值线性变换,最后利用Demons公式计算变形场.结果:5例临床头颈部肿瘤患者的CT和CBCT图像配准结果表明,改进后算法不受CT和CBCT图像CT值强度不一致的影响,能快速、精确的完成图像的变形配准.结论:基于GPU框架的改进Demons算法可以快速精确完成CT-CBCT图像变形配准,较好的满足了临床对于快速变形图像配准的要求.

  13. Non-Rigid Medical Image Registration Based on the Thin-Plate Spline%基于薄板样条的非刚体医学图像配准

    Institute of Scientific and Technical Information of China (English)

    方柏林; 唐慧慧

    2010-01-01

    非刚体图象配准是非线性的图像配准方法,它能够实现图像之间的配准,为提高医学图像配准精度,对于形变较大的多模图像的配准等都有着重要的作用.提出了一种基于薄板样条的3D/2D非刚体医学图象配准算法,算法首先提出一个混合能量公式,在配准的过程中,用薄板样条法实现全局配准,并通过仿真退火算法进行迭代,以缩小并确定变形的待配准区域.在局部的待配准区域,采用互信息的方法进行配准.解决了因特征点不足引起的不完整匹配问题,使得图像连续平滑,以得到较优的配准效果.

  14. Mutual Information Based Registration for 3D Non-Rigid Medical Images%基于互信息非刚性医学图像配准的方法

    Institute of Scientific and Technical Information of China (English)

    陈昱; 庄天戈

    1999-01-01

    提出了一种基于互信息的对非刚性三维医学图像进行弹性配准的方法.用2D联合直方图法计算两幅图像重叠部分的图像灰度之间的互信息,使之最大化,从而实现两图像之间的全局仿射配准.然后将两幅图像的重叠部分均分成互为重叠的体积子块,再最大化每对对应体积子块图像灰度之间的互信息,实现每对对应子决的局部刚体配准,并将每个子块的中心作为一一对应的控制点.利用这些均匀分布的控制点对结合薄平板样条插值法实现图像的全局非刚性弹性配准.实验结果表明,该算法可以有效地实现三维图像全局弹性配准,但计算时间较长.

  15. Quantitative assessment of global and regional air trappings using non-rigid registration and regional specific volume change of inspiratory/expiratory CT scans: Studies on healthy volunteers and asthmatics

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Eun Sol; Seo, Joon Beom; Lee, Hyun Joo; Chae, Eun Jin; Lee, Sang Min; Oh, Sang Young; Kim, Nam Kug [Dept. of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul (Korea, Republic of)

    2015-06-15

    The purpose of this study was to compare air trapping in healthy volunteers with asthmatics using pulmonary function test and quantitative data, such as specific volume change from paired inspiratory CT and registered expiratory CT. Sixteen healthy volunteers and 9 asthmatics underwent paired inspiratory/expiratory CT. DeltaSV, which represents the ratio of air fraction released after exhalation, was measured with paired inspiratory and anatomically registered expiratory CT scans. Air trapping indexes, DeltaSV0.4 and DeltaSV0.5, were defined as volume fraction of lung below 0.4 and 0.5 DeltaSV, respectively. To assess the gravity effect of air-trapping, DeltaSV values of anterior and posterior lung at three different levels were measured and DeltaSV ratio of anterior lung to posterior lung was calculated. Color-coded DeltaSV map of the whole lung was generated and visually assessed. Mean DeltaSV, DeltaSV0.4, and DeltaSV0.5 were compared between healthy volunteers and asthmatics. In asthmatics, correlation between air trapping indexes and clinical parameters were assessed. Mean DeltaSV, DeltaSV0.4, and DeltaSV0.5 in asthmatics were significantly higher than those in healthy volunteer group (all p < 0.05). DeltaSV values in posterior lung in asthmatics were significantly higher than those in healthy volunteer group (p = 0.049). In asthmatics, air trapping indexes, such as DeltaSV0.5 and DeltaSV0.4, showed negative strong correlation with FEF25-75, FEV1, and FEV1/FVC. DeltaSV map of asthmatics showed abnormal geographic pattern in 5 patients (55.6%) and disappearance of anterior-posterior gradient in 3 patients (33.3%). Quantitative assessment of DeltaSV (the ratio of air fraction released after exhalation) shows the difference in extent of air trapping between health volunteers and asthmatics.

  16. Research on Intensity and Shape Based Non-rigid Image Registration%基于灰度和形状的非刚性图像配准算法的研究

    Institute of Scientific and Technical Information of China (English)

    林相波; 邱天爽; RUAN Su; Frédéric Morain-Nicolier

    2009-01-01

    提出一种新的灰度和形状信息相结合的全自动同模态医学图像非刚性配准-分割算法,将欧氏距离表示的形状信息融入基于灰度的配准算法中,构造出新的代价函数.该算法在医学图像多目标分割的应用中,能够较好地完成灰度相近、边缘模糊、间距较小的不同结构的分割.对5组真实脑部MRI图像进行分割脑深层灰质结构的实验,结果表明,本算法优于基于灰度信息的图像配准算法.

  17. A method for extracting multi-organ from four-phase contrasted CT images based on CT value distribution estimation using EM-algorithm

    Science.gov (United States)

    Sakashita, Makiko; Kitasaka, Takayuki; Mori, Kensaku; Suenaga, Yasuhito; Nawano, Shigeru

    2007-03-01

    This paper presents a method for extracting multi-organs from four-phase contrasted CT images taken at different contrast timings (non-contrast, early, portal, and late phases). First, we apply a median filter to each CT image and align four-phase CT images by performing non-rigid volumetric image registration. Then, a three-dimensional joint histogram of CT values is computed from three-phase (early-, portal-, and late-) CT images. We assume that this histogram is a mixture of normal distributions corresponding to the liver, spleen, kidney, vein, artery, muscle, and bone regions. The EM algorithm is employed to estimate each normal distribution. Organ labels are assigned to each voxel using the mahalanobis distance measure. Connected component analysis is applied to correct the shape of each organ region. After that, the pancreas region is extracted from non-contrasted CT images in which other extracted organs and vessel regions are excluded. The EM algorithm is also employed for estimating the distribution of CT values inside the pancreas. We applied this method to seven cases of four-phase CT images. Extraction results show that the proposed method extracted multi-organs satisfactorily.

  18. Skull registration for prone patient position using tracked ultrasound

    Science.gov (United States)

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

    2017-03-01

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

  19. On the usefulness of gradient information in multi-objective deformable image registration using a B-spline-based dual-dynamic transformation model: comparison of three optimization algorithms

    NARCIS (Netherlands)

    Pirpinia, K.; Bosman, P.A.N.; Sonke, J.-J.; van Herk, M.; Alderliesten, T.

    2015-01-01

    The use of gradient information is well-known to be highly useful in single-objective optimization-based image registration methods. However, its usefulness has not yet been investigated for deformable image registration from a multi-objective optimization perspective. To this end, within a previous

  20. Robust linear registration of CT images using random regression forests

    Science.gov (United States)

    Konukoglu, Ender; Criminisi, Antonio; Pathak, Sayan; Robertson, Duncan; White, Steve; Haynor, David; Siddiqui, Khan

    2011-03-01

    Global linear registration is a necessary first step for many different tasks in medical image analysis. Comparing longitudinal studies1, cross-modality fusion2, and many other applications depend heavily on the success of the automatic registration. The robustness and efficiency of this step is crucial as it affects all subsequent operations. Most common techniques cast the linear registration problem as the minimization of a global energy function based on the image intensities. Although these algorithms have proved useful, their robustness in fully automated scenarios is still an open question. In fact, the optimization step often gets caught in local minima yielding unsatisfactory results. Recent algorithms constrain the space of registration parameters by exploiting implicit or explicit organ segmentations, thus increasing robustness4,5. In this work we propose a novel robust algorithm for automatic global linear image registration. Our method uses random regression forests to estimate posterior probability distributions for the locations of anatomical structures - represented as axis aligned bounding boxes6. These posterior distributions are later integrated in a global linear registration algorithm. The biggest advantage of our algorithm is that it does not require pre-defined segmentations or regions. Yet it yields robust registration results. We compare the robustness of our algorithm with that of the state of the art Elastix toolbox7. Validation is performed via 1464 pair-wise registrations in a database of very diverse 3D CT images. We show that our method decreases the "failure" rate of the global linear registration from 12.5% (Elastix) to only 1.9%.

  1. Evaluation of whole-body MR to CT deformable image registration

    NARCIS (Netherlands)

    Akbarzadeh, A.; Gutierrez, D.; Baskin, A.; Ay, M. R.; Ahmadian, A.; Alam, N. Riahi; Loevblad, K. O.; Zaidi, H.

    2013-01-01

    Multimodality image registration plays a crucial role in various clinical and research applications. The aim of this study is to present an optimized MR to CT whole-body deformable image registration algorithm and its validation using clinical studies. A 3D intermodality registration technique based

  2. Evaluation of Registration Methods on Thoracic CT : The EMPIRE10 Challenge

    NARCIS (Netherlands)

    Murphy, Keelin; van Ginneken, Bram; Reinhardt, Joseph M.; Kabus, Sven; Ding, Kai; Deng, Xiang; Cao, Kunlin; Du, Kaifang; Christensen, Gary E.; Garcia, Vincent; Vercauteren, Tom; Ayache, Nicholas; Commowick, Olivier; Malandain, Gregoire; Glocker, Ben; Paragios, Nikos; Navab, Nassir; Gorbunova, Vladlena; Sporring, Jon; de Bruijne, Marleen; Han, Xiao; Heinrich, Mattias P.; Schnabel, Julia A.; Jenkinson, Mark; Lorenz, Cristian; Modat, Marc; McClelland, Jamie R.; Ourselin, Sebastien; Muenzing, Sascha E. A.; Viergever, Max A.; De Nigris, Dante; Collins, D. Louis; Arbel, Tal; Peroni, Marta; Li, Rui; Sharp, Gregory C.; Schmidt-Richberg, Alexander; Ehrhardt, Jan; Werner, Rene; Smeets, Dirk; Loeckx, Dirk; Song, Gang; Tustison, Nicholas; Avants, Brian; Gee, James C.; Staring, Marius; Klein, Stefan; Stoel, Berend C.; Urschler, Martin; Werlberger, Manuel; Vandemeulebroucke, Jef; Rit, Simon; Sarrut, David; Pluim, Josien P. W.

    2011-01-01

    EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This

  3. 集成MSER和SIFT特征的遥感影像自动配准算法%Remote Sensing Image Automatic Registration Algorithm of Integrated MSER and SIFT Features

    Institute of Scientific and Technical Information of China (English)

    王晓华; 邓喀中; 杨化超

    2013-01-01

    针对倾斜的遥感影像配准困难问题,提出一种基于集成最大极值稳定区域(MSER)和尺度不变特征转换(SIFT)的互补不变特征的自动影像配准算法。该算法首先应用目前公认的具有最佳仿射不变性的MSER特征区域进行影像的粗匹配,初步校正影像的空间形变。然后在粗匹配基础上采用匹配能力较强的 SIFT 描述子与仿射不变矩描述子相结合,进行精匹配。通过以上两步匹配,可以提高遥感影像配准精度,尤其对倾斜影像效果更明显。最后采用倾斜的无人机(UAV)影像进行试验,并与SIFT配准算法比较。结果表明,本文算法在仿射不变性和匹配正确率方面均优于SIFT配准方法。%An image matching approach which integrates Maximally Stable Extremal Regions (MSER, Maximally Stable Extremal Regions) and Scale Invariant Feature Transformation (SIFT, Scale Invariant Feature Transformation) complementary invariant feature automatically is proposed for the tilt Remote Sensing image registration. Firstly, the images are coarsely matched by applying currently recognized as the best affine invariant MSER features, and the large deformation images are corrected initially. Then the images are fine matched by the matching ability of the SIFT descriptor joint the moments based on the coarse matching. The remote sensing image matching accuracy is improved through the above two steps, especially, the more pronounced effect on the large tilt images. Finally, the UAV(Unmanned Aerial Vehicle) image experiments show that this algorithm is more effective than SIFT algorithm in the affine invariant and matching the correct rate.

  4. 船舶交通服务系统雷达网误差配准算法%Registration Algorithm of VTS Radar Network System Based on Square-root Kalman Filter

    Institute of Scientific and Technical Information of China (English)

    肖进丽; 刘明俊; 刘克中

    2012-01-01

    在船舶交通服务系统(Vessel Traffic Services,VTS)利用多台雷达组成的雷达网中,如果雷达的系统误差未经配准就进行多雷达数据融合,则会使融合结果不可信而严重影响其航迹跟踪质量.平方根无味卡尔曼滤波 (Square-root Unscented Kalman Filter,SRUKF)是一种改进的无味卡尔曼滤波(Unscented Kalman Filter,UKF)算法,它借鉴了平方根卡尔曼滤波(Square-root Kalman Filter,SRKF)能克服滤波发散的思想来设计滤波器,不仅具备无味卡尔曼滤波的全部优点,而且克服了无味卡尔曼滤波由于滤波数值计算中舍入误差的积累而容易导致协方差矩阵失去非负定性的缺点,具有更好的数值稳定性.利用平方根无味卡尔曼滤波实现船舶交通服务系统中的雷达网系统误差配准,并通过Matlab仿真对该方法和无味卡尔曼滤波的滤波性能进行了比较,仿真结果验证了该方法的可行性和有效性.%In multi-radar network of VTS, to improve the reliability and quality of target tracking through multiple radar data fusion, it is necessary to register system errors of the radars. Since Square-root Unscented Kalman Filter ( SRUKF) , a modified filtering algorithm based on Unscented Kalman Filter (UKF) , has higher estimation precision and better filtering stability Compared with UKF, it is introduced for error registration of VTS radar networks. Matlab simulation results validated the algorithm.

  5. A registration method for 2D blade profile

    Science.gov (United States)

    Zhang, Bin; Fang, Jianguo; Liu, Pengfei

    2016-10-01

    Fast and accurate registration research has important theory significance and engineering application value in improving digital measurement accuracy and efficiency. Aiming at solving registration precision and registration speed problem, the extraction scheme of contour dominant point, correspondence establishment method and the objective function of registration are discussed in the paper. Compared with other extraction ones, the scheme can extract typical characters of the blade contour effectively. It is essential to sample measuring points which can represent the entire blade with sufficient confidence and accuracy. Unlike the registration method that only minimizes the one-way distance between the data points and the initial fitted curves, the weighted mutual (two-way) distances between the template profile curves and the data points as the objective function is considered in the paper. The registration algorithm based on iterative closest point algorithm is introduced in details. Using experimental method, the validation of proposed model registration algorithm is verified. Two experimental examples were used to demonstrate registration precision and effectiveness.

  6. Intensity-Based Registration for Lung Motion Estimation

    Science.gov (United States)

    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.

  7. Population based ranking of frameless CT-MRI registration methods

    Energy Technology Data Exchange (ETDEWEB)

    Opposits, Gabor; Kis, Sandor A.; Tron, Lajos; Emri, Miklos [Debrecen Univ. (Hungary). Dept. of Nuclear Medicine; Berenyi, Ervin [Debrecen Univ. (Hungary). Dept. of Biomedical Laboratory and Imaging Science; Takacs, Endre [Rotating Gamma Ltd., Debrecen (Hungary); Dobai, Jozsef G.; Bognar, Laszlo [Debrecen Univ., Medical Center (Hungary). Dept. of Neurosurgery; Szuecs, Bernadett [ScanoMed Ltd., Debrecen (Hungary)

    2015-07-01

    Clinical practice often requires simultaneous information obtained by two different imaging modalities. Registration algorithms are commonly used for this purpose. Automated procedures are very helpful in cases when the same kind of registration has to be performed on images of a high number of subjects. Radiotherapists would prefer to use the best automated method to assist therapy planning, however there are not accepted procedures for ranking the different registration algorithms. We were interested in developing a method to measure the population level performance of CT-MRI registration algorithms by a parameter of values in the [0,1] interval. Pairs of CT and MRI images were collected from 1051 subjects. Results of an automated registration were corrected manually until a radiologist and a neurosurgeon expert both accepted the result as good. This way 1051 registered MRI images were produced by the same pair of experts to be used as gold standards for the evaluation of the performance of other registration algorithms. Pearson correlation coefficient, mutual information, normalized mutual information, Kullback-Leibler divergence, L{sub 1} norm and square L{sub 2} norm (dis)similarity measures were tested for sensitivity to indicate the extent of (dis)similarity of a pair of individual mismatched images. The square Hellinger distance proved suitable to grade the performance of registration algorithms at population level providing the developers with a valuable tool to rank algorithms. The developed procedure provides an objective method to find the registration algorithm performing the best on the population level out of newly constructed or available preselected ones.

  8. Locally Orderless Registration Code

    DEFF Research Database (Denmark)

    2012-01-01

    This is code for the TPAMI paper "Locally Orderless Registration". The code requires intel threadding building blocks installed and is provided for 64 bit on mac, linux and windows.......This is code for the TPAMI paper "Locally Orderless Registration". The code requires intel threadding building blocks installed and is provided for 64 bit on mac, linux and windows....

  9. Locally orderless registration code

    DEFF Research Database (Denmark)

    2012-01-01

    This is code for the TPAMI paper "Locally Orderless Registration". The code requires intel threadding building blocks installed and is provided for 64 bit on mac, linux and windows.......This is code for the TPAMI paper "Locally Orderless Registration". The code requires intel threadding building blocks installed and is provided for 64 bit on mac, linux and windows....

  10. Phase Correlation Based Iris Image Registration Model

    Institute of Scientific and Technical Information of China (English)

    Jun-Zhou Huang; Tie-Niu Tan; Li Ma; Yun-Hong Wang

    2005-01-01

    Iris recognition is one of the most reliable personal identification methods. In iris recognition systems, image registration is an important component. Accurately registering iris images leads to higher recognition rate for an iris recognition system. This paper proposes a phase correlation based method for iris image registration with sub-pixel accuracy.Compared with existing methods, it is insensitive to image intensity and can compensate to a certain extent the non-linear iris deformation caused by pupil movement. Experimental results show that the proposed algorithm has an encouraging performance.

  11. 3D-2D registration for surgical guidance: effect of projection view angles on registration accuracy

    Science.gov (United States)

    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 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.

  12. Information from the Registration Service

    CERN Multimedia

    GS Department

    2011-01-01

    Please note that the Registration Service (Bldg 55-1st floor) will be exceptionally open during the annual end of year closure from 10:00 to 12:00 on the following days: 22, 23, 26, 27,28, 29 et 30 December 2011 and 2,3, et 4 January 2012. All the activities related to the Registration Service will be operational: registration for contractors’ personnel; registrations for professional visits; access cards; car stickers; biometric registration. The Registration Service

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

    Science.gov (United States)

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

    2014-01-01

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

  14. Simple shape space for 3D face registration

    Science.gov (United States)

    Košir, Andrej; Perkon, Igor; Bracun, Drago; Tasic, Jurij; Mozina, Janez

    2009-09-01

    Three dimensional (3D) face recognition is a topic getting increasing interest in biometric applications. In our research framework we developed a laser scanner that provides 3D cloud information and texture data. In a user scenario with cooperative subjects with indoor light conditions, we address three problems of 3D face biometrics: the face registration, the formulation of a shape space together with a special designed gradient algorithm and the impact of initial approximation to the convergence of a registration algorithm. By defining the face registration as a problem of aligning a 3D data cloud with a predefined reference template, we solve the registration problem with a second order gradient algorithm working on a shape space designed for reducing the computational complexity of the method.

  15. A Comparison of FFD-based Nonrigid Registration and AAMs Applied to Myocardial Perfusion MRI

    DEFF Research Database (Denmark)

    Ólafsdóttir, Hildur; Stegmann, Mikkel Bille; Ersbøll, Bjarne Kjær;

    2006-01-01

    Little work has been done on comparing the performance of statistical model-based approaches and nonrigid registration algorithms. This paper deals with the qualitative and quantitative comparison of active appearance models (AAMs) and a nonrigid registration algorithm based on free......-form deformations (FFDs). AAMs are known to be much faster than nonrigid registration algorithms. On the other hand nonrigid registration algorithms are independent of a training set as required to build an AAM. To obtain a further comparison of the two methods, they are both applied to automatically register multi......-slice myocardial perfusion images. The images are acquired by magnetic resonance imaging, from infarct patients. A registration of these sequences is crucial for clinical practice, which currently is subjected to manual labor. In the paper, the pros and cons of the two registration approaches are discussed...

  16. Coarse Fingerprint Registration Using Orientation Fields

    Directory of Open Access Journals (Sweden)

    Yager Neil

    2005-01-01

    Full Text Available The majority of traditional research into automated fingerprint identification has focused on algorithms using minutiae-based features. However, shortcomings of this approach are becoming apparent due to the difficulty of extracting minutiae points from noisy or low-quality images. Therefore, there has been increasing interest in algorithms based on nonminutiae features in recent years. One vital stage in most fingerprint verification systems is registration, which involves recovering the transformation parameters that align features from each fingerprint. This paper investigates the use of orientation fields for registration; an approach that has the potential to perform robustly for poor-quality images. Three diverse algorithms have been implemented for the task. The first algorithm is based on the generalized Hough transform, and it works by accumulating evidence for transformations in a discretized parameter space. The second algorithm is based on identifying distinctive local orientations, and using these as landmarks for alignment. The final algorithm follows the path of steepest descent in the parameter space to quickly find solutions that are locally optimal. The performance of these three algorithms is evaluated using an FVC2002 dataset.

  17. Mass preserving image registration for lung CT

    DEFF Research Database (Denmark)

    Gorbunova, Vladlena; Sporring, Jon; Lo, Pechin;

    2012-01-01

    on four groups of data: 44 pairs of longitudinal inspiratory chest CT scans with small difference in lung volume; 44 pairs of longitudinal inspiratory chest CT scans with large difference in lung volume; 16 pairs of expiratory and inspiratory CT scans; and 5 pairs of images extracted at end exhale and end...... inhale phases of 4D-CT images. Registration errors, measured as the average distance between vessel tree centerlines in the matched images, are significantly lower for the proposed mass preserving image registration method in the second, third and fourth group, while there is no statistically significant......This paper presents a mass preserving image registration algorithm for lung CT images. To account for the local change in lung tissue intensity during the breathing cycle, a tissue appearance model based on the principle of preservation of total lung mass is proposed. This model is incorporated...

  18. Onboard Image Registration from Invariant Features

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Nasehi Tehrani, J; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States); Guo, X [University of Texas at Dallas, Richardson, TX (United States); Yang, Y [The University of New Mexico, New Mexico, NM (United States)

    2014-06-01

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

  20. Joint CT/CBCT deformable registration and CBCT enhancement for cancer radiotherapy

    OpenAIRE

    Lou, Yifei; Niu, Tianye; Jia, Xun; Vela, Patricio A.; Zhu, Lei; Tannenbaum, Allen R.

    2013-01-01

    This paper details an algorithm to simultaneously perform registration of computed tomography (CT) and cone-beam computed (CBCT) images, and image enhancement of CBCT. The algorithm employs a viscous fluid model which naturally incorporates two components: a similarity measure for registration and an intensity correction term for image enhancement. Incorporating an intensity correction term improves the registration results. Furthermore, applying the image enhancement term to CBCT imagery lea...

  1. Canny edge-based deformable image registration

    Science.gov (United States)

    Kearney, Vasant; Huang, Yihui; Mao, Weihua; Yuan, Baohong; Tang, Liping

    2017-02-01

    This work focuses on developing a 2D Canny edge-based deformable image registration (Canny DIR) algorithm to register in vivo white light images taken at various time points. This method uses a sparse interpolation deformation algorithm to sparsely register regions of the image with strong edge information. A stability criterion is enforced which removes regions of edges that do not deform in a smooth uniform manner. Using a synthetic mouse surface ground truth model, the accuracy of the Canny DIR algorithm was evaluated under axial rotation in the presence of deformation. The accuracy was also tested using fluorescent dye injections, which were then used for gamma analysis to establish a second ground truth. The results indicate that the Canny DIR algorithm performs better than rigid registration, intensity corrected Demons, and distinctive features for all evaluation matrices and ground truth scenarios. In conclusion Canny DIR performs well in the presence of the unique lighting and shading variations associated with white-light-based image registration.

  2. Pesticide Registration Information System

    Data.gov (United States)

    U.S. Environmental Protection Agency — PRISM provides an integrated, web portal for all pesticide related data, communications, registrations and transactions for OPP and its stakeholders, partners and...

  3. Visitor Registration System

    Data.gov (United States)

    US Agency for International Development — Visitor Registration System (VRS) streamlines visitor check-in and check-out process for expediting visitors into USAID. The system captures visitor information...

  4. Antenna Structure Registrate

    Data.gov (United States)

    Department of Homeland Security — This file is an extract of the Antenna Structure Registrate (ASR). The ASR consists of antenna structures that are more than 60.96 meters (200 feet) in height or...

  5. Bayesian technique for image classifying registration.

    Science.gov (United States)

    Hachama, Mohamed; Desolneux, Agnès; Richard, Frédéric J P

    2012-09-01

    In this paper, we address a complex image registration issue arising while the dependencies between intensities of images to be registered are not spatially homogeneous. Such a situation is frequently encountered in medical imaging when a pathology present in one of the images modifies locally intensity dependencies observed on normal tissues. Usual image registration models, which are based on a single global intensity similarity criterion, fail to register such images, as they are blind to local deviations of intensity dependencies. Such a limitation is also encountered in contrast-enhanced images where there exist multiple pixel classes having different properties of contrast agent absorption. In this paper, we propose a new model in which the similarity criterion is adapted locally to images by classification of image intensity dependencies. Defined in a Bayesian framework, the similarity criterion is a mixture of probability distributions describing dependencies on two classes. The model also includes a class map which locates pixels of the two classes and weighs the two mixture components. The registration problem is formulated both as an energy minimization problem and as a maximum a posteriori estimation problem. It is solved using a gradient descent algorithm. In the problem formulation and resolution, the image deformation and the class map are estimated simultaneously, leading to an original combination of registration and classification that we call image classifying registration. Whenever sufficient information about class location is available in applications, the registration can also be performed on its own by fixing a given class map. Finally, we illustrate the interest of our model on two real applications from medical imaging: template-based segmentation of contrast-enhanced images and lesion detection in mammograms. We also conduct an evaluation of our model on simulated medical data and show its ability to take into account spatial variations

  6. Jacobians for Lebesgue registration for a range of similarity measures

    DEFF Research Database (Denmark)

    Sporring, Jon; Darkner, Sune

    In [Darkner and Sporring, 2011] was presented a framework based on locally orderless images and Lebesgue integration resulting in a fast algorithm for registration using normalized mutual information as dissimilarity measure. This report extends the algorithm to arbitrary complex similarity measu...... measures and supplies the full derivatives of a range of common dissimilarity measures as well as their obvious extensions....

  7. Semiautomated Multimodal Breast Image Registration

    Directory of Open Access Journals (Sweden)

    Charlotte Curtis

    2012-01-01

    However, due to the highly deformable nature of breast tissues, comparison of 3D and 2D modalities is a challenge. To enable this comparison, a registration technique was developed to map features from 2D mammograms to locations in the 3D image space. This technique was developed and tested using magnetic resonance (MR images as a reference 3D modality, as MR breast imaging is an established technique in clinical practice. The algorithm was validated using a numerical phantom then successfully tested on twenty-four image pairs. Dice's coefficient was used to measure the external goodness of fit, resulting in an excellent overall average of 0.94. Internal agreement was evaluated by examining internal features in consultation with a radiologist, and subjective assessment concludes that reasonable alignment was achieved.

  8. Block-to-Point Fine Registration in Terrestrial Laser Scanning

    Directory of Open Access Journals (Sweden)

    Jin Wang

    2013-12-01

    Full Text Available Fine registration of point clouds plays an important role in data analysis in Terrestrial Laser Scanning (TLS. This work proposes a block-to-point fine registration approach to correct the errors of point clouds from TLS and of geodetic networks observed using total stations. Based on a reference coordinate system, the block-to-point estimation is performed to obtain representative points. Then, fine registration with a six-parameter transformation is performed with the help of an Iterative Closest Point (ICP method. For comparisons, fine registration with a seven-parameter transformation is introduced by applying a Singular Value Decomposition (SVD algorithm. The proposed method not only corrects the registration errors between a geodetic network and the scans, but also considers the errors among the scans. The proposed method was tested on real TLS data of a dam surface, and the results showed that distance discrepancies of estimated representative points between scans were reduced by approximately 60%.

  9. DTI Image Registration under Probabilistic Fiber Bundles Tractography Learning

    Science.gov (United States)

    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.

  10. The Registration of Knee Joint Images with Preprocessing

    Directory of Open Access Journals (Sweden)

    Zhenyan Ji

    2011-06-01

    Full Text Available the registration of CT and MR images is important to analyze the effect of PCL and ACL deficiency on knee joint. Because CT and MR images have different limitations, we need register CT and MR images of knee joint and then build a model to do an analysis of the stress distribution on knee joint. In our project, we adopt image registration based on mutual information. In the knee joint images, the information about adipose, muscle and other soft tissue affects the registration accuracy. To eliminate the interference, we propose a combined preprocessing solution BEBDO, which consists of five steps, image blurring, image enhancement, image blurring, image edge detection and image outline preprocessing. We also designed the algorithm of image outline preprocessing. At the end of the paper, an experiment is done to compare the image registration results without the preprocessing and with the preprocessing. The results prove that the preprocessing can improve the image registration accuracy.

  11. General approach to error prediction in point registration

    Science.gov (United States)

    Danilchenko, Andrei; Fitzpatrick, J. Michael

    2010-02-01

    A method for the first-order analysis of the point registration problem is presented and validated. The method is a unified approach to the problem that allows for inhomogeneous and anisotropic fiducial localization error (FLE) and arbitrary weighting in the registration algorithm. Cross-covariance matrices are derived both for target registration error (TRE) and for weighted fiducial registration error (FRE). Furthermore, it is shown that for ideal weighting, in which the weighting matrix for each fiducial equals the inverse of the square root of the cross covariance of the two-space FLE for that fiducial, fluctuations of FRE and TRE are independent. These results are validated by comparison with previously published expressions for special cases and by simulation and shown to be correct. Furthermore, simulations for randomly generated fiducial positions and FLEs are presented that show that correlation is negligible (correlation coefficient FRE, are unreliable estimators of registration accuracy, i.e., TRE, and should be avoided.

  12. Automatic Registration of SAR Images with the Integrated Complementary Invariant Feature

    Directory of Open Access Journals (Sweden)

    Xiao-hua Wang

    2014-01-01

    Full Text Available The accurate Synthetic Aperture Radar (SAR image registration is important for exact analyses of mine deformation and ecological environment change. Currently, many image registration algorithms have been proposed, but these registration algorithms cannot be directly applied to SAR image, so an integrated registration approach is presented in this paper. Firstly, it is the coarse matching with Canny edge dividing regions; secondly, it is the fine matching by SIFT algorithm with improved Canny edge features; finally, obtain accurate registration SAR image. This approach has fewer computations than that simply using SIFT feature matching. Experimental analyses with SAR images of Yanzhou Mine demonstrate the efficiency and the accuracy of this approach for mine SAR image registration, which provides a simple and effective tool in SAR monitoring of mining deformation and ecological changes

  13. Automated landmark-guided deformable image registration

    Science.gov (United States)

    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.

  14. Evaluation of registration methods on thoracic CT

    DEFF Research Database (Denmark)

    Murphy, K.; van Ginneken, B.; Reinhardt, J.

    2011-01-01

    . This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which...... method and the evaluation is independent, using the same criteria for all participants. All results are published on the EMPIRE10 website (http://empire10.isi.uu.nl). The challenge remains ongoing and open to new participants. Full results from 24 algorithms have been published at the time of writing...

  15. Image registration and stitching algorithm of rice low-altitude remote sensing based on Harris corner self-adaptive detection%Harris角点自适应检测的水稻低空遥感图像配准与拼接算法

    Institute of Scientific and Technical Information of China (English)

    周志艳; 闫梦璐; 陈盛德; 兰玉彬; 罗锡文

    2015-01-01

    图像配准和拼接的自动化是微小型无人机能否被广泛应用于水稻长势低空遥感监测的关键技术之一.为了改进Harris 角点检测算法中阈值需要人为设定的局限,文章提出了基于 Harris 角点自适应检测的水稻低空遥感图像配准与拼接算法.该算法在 Harris 角点检测算法的基础上进行改进,采用基于图像像素灰度值标准差标准化的方法进行角点的自适应确定,并对角点进行特征描述,利用角点特征描述算子之间的欧式距离进行配准.为了验证算法的有效性并进行相关参数的优化,采用多旋翼无人直升机获取了水稻长势的低空遥感图像,并设计了重复率(衡量角点检测的稳定性)、辨识率(衡量角点描述算子的辨识度)、配准率(衡量图像的拼接精度)以及运行时间(衡量算法的运算速度)4个评价指标对配准与拼接的结果进行评判.随机选取获得的低空遥感图像分成 3 组进行测试,试验结果表明,平均配准率达到了98.95%,且各组图像之间的重复率与配准率差异不显著(显著性水平为0.05),说明改进后的算法稳定.设计了角点自适应检测算法阈值参数的优选试验,阈值参数为标准化处理后的图像像素灰度值标准差,方差分析结果表明,图像像素灰度标准差为1和2时配准率的差异不显著(显著性水平为0.05),但当图像像素灰度标准差为1时,图像配准与拼接平均运行时间是其为2时的2.5倍,因此,可设定图像像素灰度标准差为2作为本算法的较优参数.%Automation of images registration and stitching is one of the most important key technologies to the wide use of the low-altitude remote sensing by Micro-UAVs (unmanned aerial vehicles) in rice growing. In order to overcome the limitations, i.e. the thresholds need to be artificially determined for the traditional Harris corner detection algorithm, this paper proposed a self-adaptive algorithm for Harris

  16. Registration accuracy and quality of real-life images.

    Directory of Open Access Journals (Sweden)

    Wei-Yen Hsu

    Full Text Available BACKGROUND: A common registration problem for the application of consumer device is to align all the acquired image sequences into a complete scene. Image alignment requires a registration algorithm that will compensate as much as possible for geometric variability among images. However, images captured views from a real scene usually produce different distortions. Some are derived from the optic characteristics of image sensors, and others are caused by the specific scenes and objects. METHODOLOGY/PRINCIPAL FINDINGS: An image registration algorithm considering the perspective projection is proposed for the application of consumer devices in this study. It exploits a multiresolution wavelet-based method to extract significant features. An analytic differential approach is then proposed to achieve fast convergence of point matching. Finally, the registration accuracy is further refined to obtain subpixel precision by a feature-based modified Levenberg-Marquardt method. Due to its feature-based and nonlinear characteristic, it converges considerably faster than most other methods. In addition, vignette compensation and color difference adjustment are also performed to further improve the quality of registration results. CONCLUSIONS/SIGNIFICANCE: The performance of the proposed method is evaluated by testing the synthetic and real images acquired by a hand-held digital still camera and in comparison with two registration techniques in terms of the squared sum of intensity differences (SSD and correlation coefficient (CC. The results indicate that the proposed method is promising in registration accuracy and quality, which are statistically significantly better than other two approaches.

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

    Directory of Open Access Journals (Sweden)

    Wu Zhou

    2014-01-01

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

  18. Registration strategies for multi-modal whole-body MRI mosaicing.

    Science.gov (United States)

    Ceranka, Jakub; Polfliet, Mathias; Lecouvet, Frédéric; Michoux, Nicolas; de Mey, Johan; Vandemeulebroucke, Jef

    2017-06-21

    To test and compare different registration approaches for performing whole-body diffusion-weighted (wbDWI) image station mosaicing, and its alignment to corresponding anatomical T1 whole-body image. Four different registration strategies aiming at mosaicing of diffusion-weighted image stations, and their alignment to the corresponding whole-body anatomical image, were proposed and evaluated. These included two-step approaches, where diffusion-weighted stations are first combined in a pairwise (Strategy 1) or groupwise (Strategy 2) manner and later non-rigidly aligned to the anatomical image; a direct pairwise mapping of DWI stations onto the anatomical image (Strategy 3); and simultaneous mosaicing of DWI and alignment to the anatomical image (Strategy 4). Additionally, different images driving the registration were investigated. Experiments were performed for 20 whole-body images of patients with bone metastases. Strategies 1 and 2 showed significant improvement in mosaicing accuracy with respect to the non-registered images (P multi-modal alignment. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  19. Inter and intra-modal deformable registration: continuous deformations meet efficient optimal linear programming.

    Science.gov (United States)

    Glocker, Ben; Paragios, Nikos; Komodakis, Nikos; Tziritas, Georgios; Navab, Nassir

    2007-01-01

    In this paper we propose a novel non-rigid volume registration based on discrete labeling and linear programming. The proposed framework reformulates registration as a minimal path extraction in a weighted graph. The space of solutions is represented using a set of a labels which are assigned to predefined displacements. The graph topology corresponds to a superimposed regular grid onto the volume. Links between neighborhood control points introduce smoothness, while links between the graph nodes and the labels (end-nodes) measure the cost induced to the objective function through the selection of a particular deformation for a given control point once projected to the entire volume domain, Higher order polynomials are used to express the volume deformation from the ones of the control points. Efficient linear programming that can guarantee the optimal solution up to (a user-defined) bound is considered to recover the optimal registration parameters. Therefore, the method is gradient free, can encode various similarity metrics (simple changes on the graph construction), can guarantee a globally sub-optimal solution and is computational tractable. Experimental validation using simulated data with known deformation, as well as manually segmented data demonstrate the extreme potentials of our approach.

  20. Automatic registration of imaging mass spectrometry data to the Allen Brain Atlas transcriptome

    Science.gov (United States)

    Abdelmoula, Walid M.; Carreira, Ricardo J.; Shyti, Reinald; Balluff, Benjamin; Tolner, Else; van den Maagdenberg, Arn M. J. M.; Lelieveldt, B. P. F.; McDonnell, Liam; Dijkstra, Jouke

    2014-03-01

    Imaging Mass Spectrometry (IMS) is an emerging molecular imaging technology that provides spatially resolved information on biomolecular structures; each image pixel effectively represents a molecular mass spectrum. By combining the histological images and IMS-images, neuroanatomical structures can be distinguished based on their biomolecular features as opposed to morphological features. The combination of IMS data with spatially resolved gene expression maps of the mouse brain, as provided by the Allen Mouse Brain atlas, would enable comparative studies of spatial metabolic and gene expression patterns in life-sciences research and biomarker discovery. As such, it would be highly desirable to spatially register IMS slices to the Allen Brain Atlas (ABA). In this paper, we propose a multi-step automatic registration pipeline to register ABA histology to IMS- images. Key novelty of the method is the selection of the best reference section from the ABA, based on pre-processed histology sections. First, we extracted a hippocampus-specific geometrical feature from the given experimental histological section to initially localize it among the ABA sections. Then, feature-based linear registration is applied to the initially localized section and its two neighbors in the ABA to select the most similar reference section. A non-rigid registration yields a one-to-one mapping of the experimental IMS slice to the ABA. The pipeline was applied on 6 coronal sections from two mouse brains, showing high anatomical correspondence, demonstrating the feasibility of complementing biomolecule distributions from individual mice with the genome-wide ABA transcriptome.

  1. TIMER: tensor image morphing for elastic registration.

    Science.gov (United States)

    Yap, Pew-Thian; Wu, Guorong; Zhu, Hongtu; Lin, Weili; Shen, Dinggang

    2009-08-15

    We propose a novel diffusion tensor imaging (DTI) registration algorithm, called Tensor Image Morphing for Elastic Registration (TIMER), which leverages the hierarchical guidance of regional distributions and local boundaries, both extracted directly from the tensors. Currently available DTI registration methods generally extract tensor scalar features from each tensor to construct scalar maps. Subsequently, regional integration and other operations such as edge detection are performed to extract more features to guide the registration. However, there are two major limitations with these approaches. First, the computed regional features might not reflect the actual regional tensor distributions. Second, by the same token, gradient maps calculated from the tensor-derived scalar feature maps might not represent the actual tissue tensor boundaries. To overcome these limitations, we propose a new approach which extracts regional and edge information directly from a tensor neighborhood. Regional tensor distribution information, such as mean and variance, is computed in a multiscale fashion directly from the tensors by taking into account the voxel neighborhood of different sizes, and hence capturing tensor information at different scales, which in turn can be employed to hierarchically guide the registration. Such multiscale scheme can help alleviate the problem of local minimum and is also more robust to noise since one can better determine the statistical properties of each voxel by taking into account the properties of its surrounding. Also incorporated in our method is edge information extracted directly from the tensors, which is crucial to facilitate registration of tissue boundaries. Experiments involving real subjects, simulated subjects, fiber tracking, and atrophy detection indicate that TIMER performs better than the other methods (Yang et al., 2008; Zhang et al., 2006).

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

    Science.gov (United States)

    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.

  3. Vertebral surface registration using ridgelines/crestlines

    Science.gov (United States)

    Tan, Sovira; Yao, Jianhua; Yao, Lawrence; Summers, Ronald M.; Ward, Michael M.

    2008-03-01

    The Iterative Closest Point (ICP) algorithm is an efficient and popular technique for surface registration. It however suffers from the well-known problem of local minima that make the algorithm stop before it reaches the desired global solution. ICP can be improved by the use of landmarks or features. We recently developed a level set capable of evolving on the surface of an object represented by a triangular mesh. This level set permits the segmentation of portions of a surface based on curvature features. The boundary of a segmented portion forms a ridgeline/crestline. We show that the ridgelines/crestlines and corresponding enclosed surfaces extracted by the algorithm can substantially improve ICP registration. We compared the performance of an ICP algorithm in three setups: 1) ICP without landmarks. 2) ICP using ridgelines. 3) ICP using ridgelines and corresponding enclosed surfaces. Our material consists of vertebral body surfaces extracted for a study about the progression of Ankylosing Spondylitis. Same vertebrae scanned at intervals of one or two years were rigidly registered. Vertebral body rims and the end plate surfaces they enclose were used as landmarks. The performance measure was the mean error distance between the registered surfaces. From the one hundred registrations that we performed the average mean error was respectively 0.503mm, 0.335mm and 0.254mm for the three setups. Setup 3 almost halved the average error of setup 1. Moreover the error range is dramatically reduced from [0.0985, 2.19]mm to just [0.0865, 0.532]mm, making the algorithm very robust.

  4. Deformable image registration with geometric changes

    Institute of Scientific and Technical Information of China (English)

    Yu LIU; Bo ZHU

    2015-01-01

    Geometric changes present a number of difficulties in deformable image registration. In this paper, we propose a global deformation framework to model geometric changes whilst promoting a smooth transformation between source and target images. To achieve this, we have developed an innovative model which significantly reduces the side effects of geometric changes in image registration, and thus improves the registration accuracy. Our key contribution is the introduction of a sparsity-inducing norm, which is typically L1 norm regularization targeting regions where geometric changes occur. This preserves the smoothness of global transformation by eliminating local transformation under different conditions. Numerical solutions are discussed and analyzed to guarantee the stability and fast convergence of our algorithm. To demonstrate the effectiveness and utility of this method, we evaluate it on both synthetic data and real data from traumatic brain injury (TBI). We show that the transformation estimated from our model is able to reconstruct the target image with lower instances of error than a standard elastic registration model.

  5. Image registration using adaptive polar transform.

    Science.gov (United States)

    Matungka, Rittavee; Zheng, Yuan F; Ewing, Robert L

    2009-10-01

    Image registration is an essential step in many image processing applications that need visual information from multiple images for comparison, integration, or analysis. Recently, researchers have introduced image registration techniques using the log-polar transform (LPT) for its rotation and scale invariant properties. However, it suffers from nonuniform sampling which makes it not suitable for applications in which the registered images are altered or occluded. Inspired by LPT, this paper presents a new registration algorithm that addresses the problems of the conventional LPT while maintaining the robustness to scale and rotation. We introduce a novel adaptive polar transform (APT) technique that evenly and effectively samples the image in the Cartesian coordinates. Combining APT with an innovative projection transform along with a matching mechanism, the proposed method yields less computational load and more accurate registration than that of the conventional LPT. Translation between the registered images is recovered with the new search scheme using Gabor feature extraction to accelerate the localization procedure. Moreover an image comparison scheme is proposed for locating the area where the image pairs differ. Experiments on real images demonstrate the effectiveness and robustness of the proposed approach for registering images that are subjected to occlusion and alteration in addition to scale, rotation, and translation.

  6. Heuristic approach to image registration

    Science.gov (United States)

    Gertner, Izidor; Maslov, Igor V.

    2000-08-01

    Image registration, i.e. correct mapping of images obtained from different sensor readings onto common reference frame, is a critical part of multi-sensor ATR/AOR systems based on readings from different types of sensors. In order to fuse two different sensor readings of the same object, the readings have to be put into a common coordinate system. This task can be formulated as optimization problem in a space of all possible affine transformations of an image. In this paper, a combination of heuristic methods is explored to register gray- scale images. The modification of Genetic Algorithm is used as the first step in global search for optimal transformation. It covers the entire search space with (randomly or heuristically) scattered probe points and helps significantly reduce the search space to a subspace of potentially most successful transformations. Due to its discrete character, however, Genetic Algorithm in general can not converge while coming close to the optimum. Its termination point can be specified either as some predefined number of generations or as achievement of a certain acceptable convergence level. To refine the search, potential optimal subspaces are searched using more delicate and efficient for local search Taboo and Simulated Annealing methods.

  7. Evaluation of five image registration tools for abdominal CT: pitfalls and opportunities with soft anatomy

    Science.gov (United States)

    Lee, Christopher P.; Xu, Zhoubing; Burke, Ryan P.; Baucom, Rebeccah; Poulose, Benjamin K.; Abramson, Richard G.; Landman, Bennett A.

    2015-03-01

    Image registration has become an essential image processing technique to compare data across time and individuals. With the successes in volumetric brain registration, general-purpose software tools are beginning to be applied to abdominal computed tomography (CT) scans. Herein, we evaluate five current tools for registering clinically acquired abdominal CT scans. Twelve abdominal organs were labeled on a set of 20 atlases to enable assessment of correspondence. The 20 atlases were pairwise registered based on only intensity information with five registration tools (affine IRTK, FNIRT, Non-Rigid IRTK, NiftyReg, and ANTs). Following the brain literature, the Dice similarity coefficient (DSC), mean surface distance, and Hausdorff distance were calculated on the registered organs individually. However, interpretation was confounded due to a significant proportion of outliers. Examining the retrospectively selected top 1 and 5 atlases for each target revealed that there was a substantive performance difference between methods. To further our understanding, we constructed majority vote segmentation with the top 5 DSC values for each organ and target. The results illustrated a median improvement of 85% in DSC between the raw results and majority vote. These experiments show that some images may be well registered to some targets using the available software tools, but there is significant room for improvement and reveals the need for innovation and research in the field of registration in abdominal CTs. If image registration is to be used for local interpretation of abdominal CT, great care must be taken to account for outliers (e.g., atlas selection in statistical fusion).

  8. Influence of image registration on ADC images computed from free-breathing diffusion MRIs of the abdomen

    Science.gov (United States)

    Guyader, Jean-Marie; Bernardin, Livia; Douglas, Naomi H. M.; Poot, Dirk H. J.; Niessen, Wiro J.; Klein, Stefan

    2014-03-01

    The apparent diffusion coefficient (ADC) is an imaging biomarker providing quantitative information on the diffusion of water in biological tissues. This measurement could be of relevance in oncology drug development, but it suffers from a lack of reliability. ADC images are computed by applying a voxelwise exponential fitting to multiple diffusion-weighted MR images (DW-MRIs) acquired with different diffusion gradients. In the abdomen, respiratory motion induces misalignments in the datasets, creating visible artefacts and inducing errors in the ADC maps. We propose a multistep post-acquisition motion compensation pipeline based on 3D non-rigid registrations. It corrects for motion within each image and brings all DW-MRIs to a common image space. The method is evaluated on 10 datasets of free-breathing abdominal DW-MRIs acquired from healthy volunteers. Regions of interest (ROIs) are segmented in the right part of the abdomen and measurements are compared in the three following cases: no image processing, Gaussian blurring of the raw DW-MRIs and registration. Results show that both blurring and registration improve the visual quality of ADC images, but compared to blurring, registration yields visually sharper images. Measurement uncertainty is reduced both by registration and blurring. For homogeneous ROIs, blurring and registration result in similar median ADCs, which are lower than without processing. In a ROI at the interface between liver and kidney, registration and blurring yield different median ADCs, suggesting that uncorrected motion introduces a bias. Our work indicates that averaging procedures on the scanner should be avoided, as they remove the opportunity to perform motion correction.

  9. The hidden KPI registration accuracy.

    Science.gov (United States)

    Shorrosh, Paul

    2011-09-01

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

  10. Surface driven biomechanical breast image registration

    Science.gov (United States)

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

    2016-03-01

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

  11. Non-rigid precession of magnetic stars

    CERN Document Server

    Lander, S K

    2016-01-01

    Stars are, generically, rotating and magnetised objects with a misalignment between their magnetic and rotation axes. Since a magnetic field induces a permanent distortion to its host, it provides effective rigidity even to a fluid star, leading to bulk stellar motion which resembles free precession. This bulk motion is however accompanied by induced interior velocity and magnetic field perturbations, which are oscillatory on the precession timescale. Extending previous work, we show that these quantities are described by a set of second-order perturbation equations featuring cross-terms scaling with the product of the magnetic and centrifugal distortions to the star. For the case of a background toroidal field, we reduce these to a set of differential equations in radial functions, and find a method for their solution. The resulting magnetic-field and velocity perturbations show complex multipolar structure and are strongest towards the centre of the star.

  12. 3D Elastic Registration of Ultrasound Images Based on Skeleton Feature

    Institute of Scientific and Technical Information of China (English)

    LI Dan-dan; LIU Zhi-Yan; SHEN Yi

    2005-01-01

    In order to eliminate displacement and elastic deformation between images of adjacent frames in course of 3D ultrasonic image reconstruction, elastic registration based on skeleton feature was adopt in this paper. A new automatically skeleton tracking extract algorithm is presented, which can extract connected skeleton to express figure feature. Feature points of connected skeleton are extracted automatically by accounting topical curvature extreme points several times. Initial registration is processed according to barycenter of skeleton. Whereafter, elastic registration based on radial basis function are processed according to feature points of skeleton. Result of example demonstrate that according to traditional rigid registration, elastic registration based on skeleton feature retain natural difference in shape for organ's different part, and eliminate slight elastic deformation between frames caused by image obtained process simultaneously. This algorithm has a high practical value for image registration in course of 3D ultrasound image reconstruction.

  13. Parallel Processing and Bio-inspired Computing for Biomedical Image Registration

    Directory of Open Access Journals (Sweden)

    Silviu Ioan Bejinariu

    2014-07-01

    Full Text Available Image Registration (IR is an optimization problem computing optimal parameters of a geometric transform used to overlay one or more source images to a given model by maximizing a similarity measure. In this paper the use of bio-inspired optimization algorithms in image registration is analyzed. Results obtained by means of three different algorithms are compared: Bacterial Foraging Optimization Algorithm (BFOA, Genetic Algorithm (GA and Clonal Selection Algorithm (CSA. Depending on the images type, the registration may be: area based, which is slow but more precise, and features based, which is faster. In this paper a feature based approach based on the Scale Invariant Feature Transform (SIFT is proposed. Finally, results obtained using sequential and parallel implementations on multi-core systems for area based and features based image registration are compared.

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

    Science.gov (United States)

    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.

  15. Image registration with uncertainty analysis

    Science.gov (United States)

    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.

  16. The role of image registration in brain mapping.

    Science.gov (United States)

    Toga, A W; Thompson, P M

    2001-01-01

    Image registration is a key step in a great variety of biomedical imaging applications. It provides the ability to geometrically align one dataset with another, and is a prerequisite for all imaging applications that compare datasets across subjects, imaging modalities, or across time. Registration algorithms also enable the pooling and comparison of experimental findings across laboratories, the construction of population-based brain atlases, and the creation of systems to detect group patterns in structural and functional imaging data. We review the major types of registration approaches used in brain imaging today. We focus on their conceptual basis, the underlying mathematics, and their strengths and weaknesses in different contexts. We describe the major goals of registration, including data fusion, quantification of change, automated image segmentation and labeling, shape measurement, and pathology detection. We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical analysis. The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the anatomy or physiology of the brain.

  17. Automatic nonrigid registration of whole body CT mice images.

    Science.gov (United States)

    Li, Xia; Yankeelov, Thomas E; Peterson, Todd E; Gore, John C; Dawant, Benoit M

    2008-04-01

    Three-dimensional intra- and intersubject registration of image volumes is important for tasks that include quantification of temporal/longitudinal changes, atlas-based segmentation, computing population averages, or voxel and tensor-based morphometry. While a number of methods have been proposed to address this problem, few have focused on the problem of registering whole body image volumes acquired either from humans or small animals. These image volumes typically contain a large number of articulated structures, which makes registration more difficult than the registration of head images, to which the majority of registration algorithms have been applied. This article presents a new method for the automatic registration of whole body computed tomography (CT) volumes, which consists of two main steps. Skeletons are first brought into approximate correspondence with a robust point-based method. Transformations so obtained are refined with an intensity-based nonrigid registration algorithm that includes spatial adaptation of the transformation's stiffness. The approach has been applied to whole body CT images of mice, to CT images of the human upper torso, and to human head and neck CT images. To validate the authors method on soft tissue structures, which are difficult to see in CT images, the authors use coregistered magnetic resonance images. They demonstrate that the approach they propose can successfully register image volumes even when these volumes are very different in size and shape or if they have been acquired with the subjects in different positions.

  18. Stepper registration feedback control in 300-mm manufacturing

    Science.gov (United States)

    Fenner, Joel; Roberts, Joel G.; Carson, Steven L.

    2003-06-01

    Control of registration (overlay error between printed layers) is a key aspect of successfully manufacturing semiconductors. At Intel, registration control was formerly achieved through manual adjustments of the tool to account for the known effects of non-stationary drift. The objective of the stepper registration control (SRC) project was to create a robust algorithm and automated implementation to replace the manual adjustment process. This goal was accomplished at Intel by developing an automated product called SRC. At the heart of the SRC application is the SRC feedback algorithm. At the stepper, alignment settings are adjusted to correct for non-stationary drift. The SRC algorithm uses a weighted average of registration data from previous lots to determine the recommended alignment settings. The novel scheme weights prior lots using a combination of traditional EWMA based weighting and variance based weighting. After piloting and comparing the results against the manual algorithm, the SRC application has been shown to be at least as good as the manual algorithm. Thus the SRC application is being used by all 300mm Intel factories. Since HVM factories cannot resource the same level of frequent manual adjustments, the benefits of reduced rework rate and increased process capability is more pronounced in HVM.

  19. Registration Method for CT-MR Image Based on Mutual Information

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Medical image registration is important in many medical applications. Registration method based on maximization of mutual information of voxel intensities is one of the most popular methods for 3-D multi-modality medical image registration. Generally, the optimization process is easily trapped in local maximum, resulting in wrong registration results. In order to find the correct optimum, a new multi-resolution approach for brain image registration based on normalized mutual information is proposed. In this method, to eliminate the effect of local optima, multi-scale wavelet transformation is adopted to extract the image edge features. Then the feature images are registered,and the result at this level is taken as the initial estimate for the registration of the original images.Three-dimensional volumes are used to test the algorithm. Experimental results show that the registration strategy proposed is a robust and efficient method which can reach sub-voxel accuracy and improve the optimization speed.

  20. Registration of acute stroke

    DEFF Research Database (Denmark)

    Wildenschild, Cathrine; Mehnert, Frank; Thomsen, Reimar Wernich

    2013-01-01

    BACKGROUND: The validity of the registration of patients in stroke-specific registries has seldom been investigated, nor compared with administrative hospital discharge registries. The objective of this study was to examine the validity of the registration of patients in a stroke-specific registry...... (The Danish Stroke Registry [DSR]) and a hospital discharge registry (The Danish National Patient Registry [DNRP]). METHODS: Assuming that all patients with stroke were registered in either the DSR, DNRP or both, we first identified a sample of 75 patients registered with stroke in 2009; 25 patients...... in the DSR, 25 patients in the DNRP, and 25 patients registered in both data sources. Using the medical record as a gold standard, we then estimated the sensitivity and positive predictive value of a stroke diagnosis in the DSR and the DNRP. Secondly, we reviewed 160 medical records for all potential stroke...

  1. Deformable image registration in radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Seung Jong; Kim, Si Yong [Dept. of Radiation Oncology, Virginia Commonwealth University, Richmond (United States)

    2017-06-15

    The number of imaging data sets has significantly increased during radiation treatment after introducing a diverse range of advanced techniques into the field of radiation oncology. As a consequence, there have been many studies proposing meaningful applications of imaging data set use. These applications commonly require a method to align the data sets at a reference. Deformable image registration (DIR) is a process which satisfies this requirement by locally registering image data sets into a reference image set. DIR identifies the spatial correspondence in order to minimize the differences between two or among multiple sets of images. This article describes clinical applications, validation, and algorithms of DIR techniques. Applications of DIR in radiation treatment include dose accumulation, mathematical modeling, automatic segmentation, and functional imaging. Validation methods discussed are based on anatomical landmarks, physical phantoms, digital phantoms, and per application purpose. DIR algorithms are also briefly reviewed with respect to two algorithmic components: similarity index and deformation models.

  2. elastix: a toolbox for intensity-based medical image registration.

    Science.gov (United States)

    Klein, Stefan; Staring, Marius; Murphy, Keelin; Viergever, Max A; Pluim, Josien P W

    2010-01-01

    Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities (e.g., magnetic resonance and computed tomography), different time points (e.g., follow-up scans), and/or different subjects (in case of population studies). A large number of methods for image registration are described in the literature. Unfortunately, there is not one method that works for all applications. We have therefore developed elastix, a publicly available computer program for intensity-based medical image registration. The software consists of a collection of algorithms that are commonly used to solve medical image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. The command-line interface enables automated processing of large numbers of data sets, by means of scripting. The usage of elastix for comparing different registration methods is illustrated with three example experiments, in which individual components of the registration method are varied.

  3. Image Classifying Registration and Dynamic Region Merging

    Directory of Open Access Journals (Sweden)

    Himadri Nath Moulick

    2013-07-01

    Full Text Available In this paper, we address a complex image registration issue arising when the dependencies between intensities of images to be registered are not spatially homogeneous. Such a situation is frequentlyencountered in medical imaging when a pathology present in one of the images modifies locally intensity dependencies observed on normal tissues. Usual image registration models, which are based on a single global intensity similarity criterion, fail to register such images, as they are blind to local deviations of intensity dependencies. Such a limitation is also encountered in contrast enhanced images where there exist multiple pixel classes having different properties of contrast agent absorption. In this paper, we propose a new model in which the similarity criterion is adapted locally to images by classification of image intensity dependencies. Defined in a Bayesian framework, the similarity criterion is a mixture of probability distributions describing dependencies on two classes. The model also includes a class map which locates pixels of the two classes and weights the two mixture components. The registration problem is formulated both as an energy minimization problem and as a Maximum A Posteriori (MAP estimation problem. It is solved using a gradient descent algorithm. In the problem formulation and resolution, the image deformation and the class map are estimated at the same time, leading to an original combination of registration and classification that we call image classifying registration. Whenever sufficient information about class location is available in applications, the registration can also be performed on its own by fixing a given class map. Finally, we illustrate the interest of our model on two real applications from medical imaging: template-based segmentation of contrast-enhanced images and lesion detection in mammograms. We also conduct an evaluation of our model on simulated medical data and show its ability to take into

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

    Science.gov (United States)

    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.

  5. Registration of Standardized Histological Images in Feature Space

    CERN Document Server

    Bagci, Ulas; 10.1117/12.770219

    2009-01-01

    In this paper, we propose three novel and important methods for the registration of histological images for 3D reconstruction. First, possible intensity variations and nonstandardness in images are corrected by an intensity standardization process which maps the image scale into a standard scale where the similar intensities correspond to similar tissues meaning. Second, 2D histological images are mapped into a feature space where continuous variables are used as high confidence image features for accurate registration. Third, we propose an automatic best reference slice selection algorithm that improves reconstruction quality based on both image entropy and mean square error of the registration process. We demonstrate that the choice of reference slice has a significant impact on registration error, standardization, feature space and entropy information. After 2D histological slices are registered through an affine transformation with respect to an automatically chosen reference, the 3D volume is reconstruct...

  6. Spatial Information Based Medical Image Registration using Mutual Information

    Directory of Open Access Journals (Sweden)

    Benzheng Wei

    2011-06-01

    Full Text Available Image registration is a valuable technique for medical diagnosis and treatment. Due to the inferiority of image registration using maximum mutual information, a new hybrid method of multimodality medical image registration based on mutual information of spatial information is proposed. The new measure that combines mutual information, spatial information and feature characteristics, is proposed. Edge points are used as features, obtained from a morphology gradient detector. Feature characteristics like location, edge strength and orientation are taken into account to compute a joint probability distribution of corresponding edge points in two images. Mutual information based on this function is minimized to find the best alignment parameters. Finally, the translation parameters are calculated by using a modified Particle Swarm Optimization (MPSO algorithm. The experimental results demonstrate the effectiveness of the proposed registration scheme.

  7. Atlas-Based Prostate Segmentation Using an Hybrid Registration

    CERN Document Server

    Martin, Sébastien; Troccaz, Jocelyne

    2008-01-01

    Purpose: This paper presents the preliminary results of a semi-automatic method for prostate segmentation of Magnetic Resonance Images (MRI) which aims to be incorporated in a navigation system for prostate brachytherapy. Methods: The method is based on the registration of an anatomical atlas computed from a population of 18 MRI exams onto a patient image. An hybrid registration framework which couples an intensity-based registration with a robust point-matching algorithm is used for both atlas building and atlas registration. Results: The method has been validated on the same dataset that the one used to construct the atlas using the "leave-one-out method". Results gives a mean error of 3.39 mm and a standard deviation of 1.95 mm with respect to expert segmentations. Conclusions: We think that this segmentation tool may be a very valuable help to the clinician for routine quantitative image exploitation.

  8. Agile multi-scale decompositions for automatic image registration

    Science.gov (United States)

    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.

  9. Non-rigid body static model based miniature robotic arm pose estimation%基于非刚体静力模型的微型机械臂姿态估计

    Institute of Scientific and Technical Information of China (English)

    雷洋; 田书林; 程玉华

    2012-01-01

    A model based estimation approach is proposed to determine the real-time kinematic pose of a miniature cable driven robotic arm with ten passive planar rotation joints. A non-rigid body static equilibrium model is constructed, and the ten planar degree of freedom ( DOF) variables are transformed to one translational variable and one tensile force variable. An linear variable differential transformer(LVDT) sensor and a load cell are used in this robotic arm to measure the planar kinematic pose of its end actuator. The accuracy and error of the measurement results are analyzed; the advantage and insufficiency of this measurement approach are stated; and the proposed method is compared with other potential measurement schemes.%提出了一种针对具有10个被动平面转动关节的微型化柔索驱动机械臂运动姿态的实时估计方法.通过建立该微型机械臂的非刚体静力模型,将10个平面自由度变量转化为1个位移变量和1个张力变量.用一个线型差动变压位移传感器(linear variable differential transformer,LVDT)和一个微型载荷传感器(load cell)测量该微型机械臂终端执行器的平面运动姿态.通过对测量结果的精度和误差进行分析,指出了该测量方法的优势与不足,并与其他几种可能的测量方法进行了比较和讨论.

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

    Science.gov (United States)

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

    2016-03-01

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

  11. Fast Registration Method for Point Clouds Using the Image Information

    Directory of Open Access Journals (Sweden)

    WANG Ruiyan

    2016-01-01

    Full Text Available On the existing laser scanners, there usually is a coaxial camera, which could capture images in the scanning site. For the laser scanners with a coaxial camera, we propose a fast registration method using the image information. Unlike the traditional registration methods that computing the rotation and translation simultaneously, our method calculates them individually. The rotation transformation between the point clouds is obtained by the knowledge of the vision geometry and the image information, while their translation is acquired by our improved ICP algorithm. In the improved ICP algorithm, only the translation vector is updated iteratively, whose input is the point clouds that removing the rotation transformation. Experimental results show that the rotation matrix obtained by the images has a high accuracy. In addition, compared with the traditional ICP algorithm, our algorithm converges faster and is easier to fall into the global optimum.

  12. Verification and Validation of a Fingerprint Image Registration Software

    Directory of Open Access Journals (Sweden)

    Liu Yan

    2006-01-01

    Full Text Available The need for reliable identification and authentication is driving the increased use of biometric devices and systems. Verification and validation techniques applicable to these systems are rather immature and ad hoc, yet the consequences of the wide deployment of biometric systems could be significant. In this paper we discuss an approach towards validation and reliability estimation of a fingerprint registration software. Our validation approach includes the following three steps: (a the validation of the source code with respect to the system requirements specification; (b the validation of the optimization algorithm, which is in the core of the registration system; and (c the automation of testing. Since the optimization algorithm is heuristic in nature, mathematical analysis and test results are used to estimate the reliability and perform failure analysis of the image registration module.

  13. Automatic Image Registration of Multi-Modal Remotely Sensed Data with Global Shearlet Features

    Science.gov (United States)

    Murphy, James M.; Le Moigne, Jacqueline; Harding, David J.

    2016-01-01

    Automatic image registration is the process of aligning two or more images of approximately the same scene with minimal human assistance. Wavelet-based automatic registration methods are standard, but sometimes are not robust to the choice of initial conditions. That is, if the images to be registered are too far apart relative to the initial guess of the algorithm, the registration algorithm does not converge or has poor accuracy, and is thus not robust. These problems occur because wavelet techniques primarily identify isotropic textural features and are less effective at identifying linear and curvilinear edge features. We integrate the recently developed mathematical construction of shearlets, which is more effective at identifying sparse anisotropic edges, with an existing automatic wavelet-based registration algorithm. Our shearlet features algorithm produces more distinct features than wavelet features algorithms; the separation of edges from textures is even stronger than with wavelets. Our algorithm computes shearlet and wavelet features for the images to be registered, then performs least squares minimization on these features to compute a registration transformation. Our algorithm is two-staged and multiresolution in nature. First, a cascade of shearlet features is used to provide a robust, though approximate, registration. This is then refined by registering with a cascade of wavelet features. Experiments across a variety of image classes show an improved robustness to initial conditions, when compared to wavelet features alone.

  14. A review of segmentation and deformable registration methods applied to adaptive cervical cancer radiation therapy treatment planning.

    Science.gov (United States)

    Ghose, Soumya; Holloway, Lois; Lim, Karen; Chan, Philip; Veera, Jacqueline; Vinod, Shalini K; Liney, Gary; Greer, Peter B; Dowling, Jason

    2015-06-01

    Manual contouring and registration for radiotherapy treatment planning and online adaptation for cervical cancer radiation therapy in computed tomography (CT) and magnetic resonance images (MRI) are often necessary. However manual intervention is time consuming and may suffer from inter or intra-rater variability. In recent years a number of computer-guided automatic or semi-automatic segmentation and registration methods have been proposed. Segmentation and registration in CT and MRI for this purpose is a challenging task due to soft tissue deformation, inter-patient shape and appearance variation and anatomical changes over the course of treatment. The objective of this work is to provide a state-of-the-art review of computer-aided methods developed for adaptive treatment planning and radiation therapy planning for cervical cancer radiation therapy. Segmentation and registration methods published with the goal of cervical cancer treatment planning and adaptation have been identified from the literature (PubMed and Google Scholar). A comprehensive description of each method is provided. Similarities and differences of these methods are highlighted and the strengths and weaknesses of these methods are discussed. A discussion about choice of an appropriate method for a given modality is provided. In the reviewed papers a Dice similarity coefficient of around 0.85 along with mean absolute surface distance of 2-4mm for the clinically treated volume were reported for transfer of contours from planning day to the treatment day. Most segmentation and non-rigid registration methods have been primarily designed for adaptive re-planning for the transfer of contours from planning day to the treatment day. The use of shape priors significantly improved segmentation and registration accuracy compared to other models. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. A combined alignment and registration scheme of psoriasis lesion |images

    DEFF Research Database (Denmark)

    Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær

    2003-01-01

    A two-stage registration scheme of psoriasis lesion patterns is proposed. In the first stage, global rotation and translation effects of assumed equally scaled psoriasis lesion patterns are removed. In the second stage, only local translation effects are removed. In both stages a novel algorithm...

  16. Automated registration of partially defective surfaces by local landmark identification.

    Science.gov (United States)

    Malthan, Dirk; Ehrlich, Günther; Stallkamp, Jan; Dammann, Florian; Schwaderer, Erwin; Maassen, Marcus M

    2003-01-01

    In computer- and robot-assisted surgery, the term "registration" refers to the definition of the geometrical relationship between the coordinate system of a surgical planning system and that of the patient. Within the context of the development of a navigation and control system for computer- and robot-assisted surgery of the lateral skull base, it was desirable to realize an algorithm for automated registration of partially defective surfaces that is reliable and suitable for use in clinical practice. A registration algorithm based on the use of local fingerprints for specific points on a surface (so-called "spin images") was developed. Anatomical patient landmarks were identified automatically and assigned to CT data, performing a cross-correlation analysis and an investigation of the geometrical consistency. The algorithm was evaluated within the development of the navigation and robotic control system in a laboratory setting. Under laboratory conditions it could be shown that partially defective surfaces (simulated by, for example, adding white noise, or reducing or smoothing the polygon data) were correctly recognized and thereby registered. In particular, the algorithm proved its excellence in interpreting partially modified topologies. The proposed procedure can be used to accomplish dynamic intra-operative registration of the skull bone by the generation of point relations to the CT images.

  17. A Comparison of FFD-based Nonrigid Registration and AAMs Applied to Myocardial Perfusion MRI

    DEFF Research Database (Denmark)

    Ólafsdóttir, Hildur; Stegmann, Mikkel Bille; Ersbøll, Bjarne Kjær

    2006-01-01

    Little work has been done on comparing the performance of statistical model-based approaches and nonrigid registration algorithms. This paper deals with the qualitative and quantitative comparison of active appearance models (AAMs) and a nonrigid registration algorithm based on free...... and qualitative and quantitative comparisons are provided. The quantitative comparison is obtained by an analysis of variance of landmark errors, i.e. point to point and point to curve errors. Even though the FFD-based approach does not include a training phase it gave similar accuracy as the AAMs in terms......-form deformations (FFDs). AAMs are known to be much faster than nonrigid registration algorithms. On the other hand nonrigid registration algorithms are independent of a training set as required to build an AAM. To obtain a further comparison of the two methods, they are both applied to automatically register multi...

  18. Hyperspectral Imaging for Cancer Surgical Margin Delineation: Registration of Hyperspectral and Histological Images.

    Science.gov (United States)

    Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

    2014-03-12

    The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection.

  19. Automatic Registration of Quad-Rotor UAV Imagery based on SIFT and TPS Algorithm%基于SIFT和TPS算法的四旋翼无人机图像自动配准

    Institute of Scientific and Technical Information of China (English)

    陈本清; 杨燕明; 郑凌虹; 文洪涛

    2013-01-01

    As an important complementarity of remote sensing technique,Unmanned Aerial Vehicle (UAV) is attractive to various applications such as target searching,island management,disaster monitoring and low-altitude photogrammetry.The quad-rotor UAV,Compared to fixed-wing UAV,has the advantages of Vertical-Taking-of-Landing (VTOL) and low-altitude flexible flight.However,the quad-rotor UAV has small-volume and lightweight and is more easily influenced by the wind,the acquired imagery maybe have bigger tile angle and more obvious geometry distortion will would result in more difficulty on the image feature matching and image mosaic.For this question,we apply the Scale Invariant Feature Transformation (SIFT) to image feature matching and Thin Plate Spline (TPS) transformation to automatic registration of the micro quad-rotor UAV imageries in this paper.The registration imagery based on TPS transformation is then compared to that based on the affine transformation and the polynomial transformation by evaluating the visual effect of the mosaic imagery and Root Mean Square (RMS) statistic,which shows that after precise SIFT feature matching,the registration RMS accuracy and the visual effect of mosaic imagery of TPS transformation are best,and satisfies the demand of rapid registration and mosaic of micro quad-rotor UVA imagery,since TPS transformation considered both rigid transformation and partial nonlinear distortion of the micro quad-rotor UAV imagery.%针对四旋翼无人机图像姿态倾角大、图像变形明显等特点,采用尺度不变特征变换(SIFT)算法和薄板样条模型(TPS)对四旋翼无人机图像进行特征点匹配和配准实验研究,从拼接图像的目视效果和配准均方差方面比较分析了TPS模型与常用的仿射变换及多项式变换模型的图像配准效果.结果表明:在SIFT算法精确的同名点匹配下,TPS变换模型能够兼顾四旋翼无人机图像的整体刚性变形及局部的非刚性变形,无论是目

  20. Registration Summer Camp 2016

    CERN Multimedia

    2016-01-01

    Reminder: registration for the CERN Staff Association Summer Camp is now open for children from 4 to 6 years old.   More information on the website: http://nurseryschool.web.cern.ch/. The summer camp is open to all children. The proposed cost is 480.-CHF/week, lunch included. The camp will be open weeks 27, 28, 29 and 30, from 8:30 a.m. to 5:30 p.m. For further questions, you are welcome to contact us by email at Summer.Camp@cern.ch. CERN Staff Association

  1. Image Segmentation, Registration, Compression, and Matching

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2012-06-01

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

  3. Automated image registration for FDOPA PET studies

    Science.gov (United States)

    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.

  4. Using image synthesis for multi-channel registration of different image modalities

    Science.gov (United States)

    Chen, Min; Jog, Amod; Carass, Aaron; Prince, Jerry L.

    2015-01-01

    This paper presents a multi-channel approach for performing registration between magnetic resonance (MR) images with different modalities. In general, a multi-channel registration cannot be used when the moving and target images do not have analogous modalities. In this work, we address this limitation by using a random forest regression technique to synthesize the missing modalities from the available ones. This allows a single channel registration between two different modalities to be converted into a multi-channel registration with two mono-modal channels. To validate our approach, two openly available registration algorithms and five cost functions were used to compare the label transfer accuracy of the registration with (and without) our multi-channel synthesis approach. Our results show that the proposed method produced statistically significant improvements in registration accuracy (at an α level of 0.001) for both algorithms and all cost functions when compared to a standard multi-modal registration using the same algorithms with mutual information. PMID:26246653

  5. Shrinking of the Cocos and Nazca Plates due to Horizontal Thermal Contraction and Implications for Plate Non-rigidity and the Non-closure of the Pacific-Cocos-Nazca Plate Motion Circuit

    Science.gov (United States)

    Gordon, R. G.; Kreemer, C.

    2015-12-01

    Plate rigidity is the central tenet of plate tectonics. Mounting evidence suggests, however, that significant intraplate deformation occurs in oceanic lithosphere due to horizontal thermal contraction, the rate of which decreases as ≈ 1/age [Kumar & Gordon 2009]. Support for this hypothesis comes from the azimuths of submarine transform faults, which are fit significantly better assuming shrinking plates than by assuming rigid plates [Mishra & Gordon 2015]. Previously we estimated the intraplate velocity field of the Pacific plate accounting for horizontal thermal contraction. The ≈2 mm/yr southeastward motion predicted for the northeastern part of the plate relative to the Pacific-Antarctic Rise may contribute to the non-closure of the Pacific-North America plate motion circuit. In a reference frame in which fix the oldest portion of the Pacific plate, some sites on the plate move up to ≈2 mm/yr [Kreemer & Gordon 2014]. Here we present intraplate velocity fields of the Cocos and Nazca plates and discuss their implications for the non-rigidity of plates and the non-closure of the Pacific-Cocos-Nazca plate circuit, which fails closure by a stunning 14 ±5 mm/yr [DeMets et al. 2010]. If we fix the oldest part of the Cocos plate, intraplate velocities of up to ≈2 mm/yr are estimated, with the fastest motion occurring at the northern end of the plate. If we fix the oldest part of the Nazca plate, displacement rates up to 2 mm/yr are estimated, with the fastest motion occurring in the northeasternmost portion of the plate. In the velocity fields for both plates, the lithosphere adjacent to transform faults along the East Pacific Rise tends to move to the south, which would skew the azimuths of the transform faults clockwise of the values expected for rigid plates, which is the same as the sense of misfit between observed azimuths of transform faults and the azimuths calculated from the MORVEL global set of relative angular velocities [DeMets et al. 2010]. Direct

  6. Structure Damage Analysis of Photoelectric Composite Cable under Impaction by Admiral Anchors on Non-Rigid Bottom%非刚性底质上海军锚对光电复合缆撞击损伤分析

    Institute of Scientific and Technical Information of China (English)

    王力平; 罗晓兰; 高强; 段梦兰; 徐健; 脱浩虎

    2016-01-01

    The ship’s anchor impact is easy to make submarine cable breakage and damage.It is very meaningful to carry out the research on the impact damage of submarine cable structure, which is very important for ensuring the safety of communication,power and production.Aiming at admiral anchor on the non-rigid bottom,a finite element model of drop anchor impacting photo-electric composite cable is created,and the plastic strain and sectional deformation of photoelectric composite cable are analyzed and calculated when admiral anchor dropped the cable.To find the strain and deformation trend of photoelectric composite cable structure of each layer are basic con-sistency,so the damage the internal structure from outer injury can be determined.Meanwhile,the comparative calculation and test results show that the light unit is more likely to suffer extrusion deformation than the electric unit.When the cross-sectional deformation of the photoelectric com-posite cable reaches 9%,the light unit of cable is damaged.%船锚撞击容易使海底电缆断裂、破损,为此,开展海底电缆结构的撞击损伤研究,对保障海底通讯通电生产安全具有非常重要的意义。针对非刚性底及质海军锚,建立落锚冲击光电复合缆的有限元计算模型,通过对落锚冲击时光电复合缆结构的等效塑性应变和截面变形量的计算分析,发现光电缆各层结构的应变和变形趋势基本一致,从而可以从外层铠装的损伤来判断内部结构的损伤情况。计算结果对比试验结果表明,光单元比电单元更容易遭受挤压变形,当光电缆的截面变形量达到9%,电缆中光单元受损。

  7. Registration and 3D visualization of large microscopy images

    Science.gov (United States)

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

    2006-03-01

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

  8. An ASIFT-Based Local Registration Method for Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Xiangjun Wang

    2015-05-01

    Full Text Available Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. It is highly desired to find a way to identify registration regions among input stereo image pairs with high accuracy, particularly in remote sensing applications in which ground control points (GCPs are not always available, such as in selecting a landing zone on an outer space planet. In this paper, a framework for localization in image registration is developed. It strengthened the local registration accuracy from two aspects: less reprojection error and better feature point distribution. Affine scale-invariant feature transform (ASIFT was used for acquiring feature points and correspondences on the input images. Then, a homography matrix was estimated as the transformation model by an improved random sample consensus (IM-RANSAC algorithm. In order to identify a registration region with a better spatial distribution of feature points, the Euclidean distance between the feature points is applied (named the S criterion. Finally, the parameters of the homography matrix were optimized by the Levenberg–Marquardt (LM algorithm with selective feature points from the chosen registration region. In the experiment section, the Chang’E-2 satellite remote sensing imagery was used for evaluating the performance of the proposed method. The experiment result demonstrates that the proposed method can automatically locate a specific region with high registration accuracy between input images by achieving lower root mean square error (RMSE and better distribution of feature points.

  9. Authentications of Myanmar National Registration Card

    Directory of Open Access Journals (Sweden)

    Myint Myint Sein

    2013-04-01

    Full Text Available The automatic identification system of Myanmar national registration card (NRC holder is presented in this paper. The proposed system can be handled the identification by the extracted low quality face image and fingerprint image from Myanmar NRC. Both of the facial recognition and fingerprint recognition system are developed for Myanmar citizenship confirmation. Age invariant face recognition algorithm is performed based on combination of DiaPCA (Diagonal principal Component Analysis and KNN (Kth nearest neighbor classifier approaches. An algorithm of the fingerprint recognition is proposed for recognition of the poor quality fingerprint image with fabric background.  Several experiments have been done for confirming the effectiveness of the proposed approach.

  10. Registration Delay and Student Performance

    Science.gov (United States)

    Siefken, Jason

    2017-01-01

    Tracking the difference between the time a first-year student is allowed to register for a course and the time he or she does register for a course (a student's registration delay), we notice a negative correlation between registration delay and final grade in a course. The difference between a student who registers within the first two minutes…

  11. 16 CFR 1130.8 - Requirements for Web site registration or alternative e-mail registration.

    Science.gov (United States)

    2010-01-01

    ... registration. (a) Link to registration page. The manufacturer's Web site, or other Web site established for the... web page that goes directly to “Product Registration.” (b) Purpose statement. The registration page... registration page. The Web site registration page shall request only the consumer's name, address,...

  12. Registration of multimodal brain images: some experimental results

    Science.gov (United States)

    Chen, Hua-mei; Varshney, Pramod K.

    2002-03-01

    Joint histogram of two images is required to uniquely determine the mutual information between the two images. It has been pointed out that, under certain conditions, existing joint histogram estimation algorithms like partial volume interpolation (PVI) and linear interpolation may result in different types of artifact patterns in the MI based registration function by introducing spurious maxima. As a result, the artifacts may hamper the global optimization process and limit registration accuracy. In this paper we present an extensive study of interpolation-induced artifacts using simulated brain images and show that similar artifact patterns also exist when other intensity interpolation algorithms like cubic convolution interpolation and cubic B-spline interpolation are used. A new joint histogram estimation scheme named generalized partial volume estimation (GPVE) is proposed to eliminate the artifacts. A kernel function is involved in the proposed scheme and when the 1st order B-spline is chosen as the kernel function, it is equivalent to the PVI. A clinical brain image database furnished by Vanderbilt University is used to compare the accuracy of our algorithm with that of PVI. Our experimental results show that the use of higher order kernels can effectively remove the artifacts and, in cases when MI based registration result suffers from the artifacts, registration accuracy can be improved significantly.

  13. Deformable image registration for image guided prostate radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Cassetta, Roberto; Riboldi, Marco; Baroni, Guido [DEIB, Politecnico di Milano, Milano (Italy); Leandro, Kleber; Novaes, Paulo Eduardo [Hospital Vitoria, Santos, SP (Brazil); Goncalves, Vinicius; Sakuraba, Roberto [Hospital Israelita Albert Einstein, Sao Paulo, SP (Brazil); Fattori, Giovanni [Paul Scherrer Institute, Center for Proton Therapy, Villigen (Switzerland)

    2016-07-01

    In this study, we present a CT to CBCT deformable registration method based on the ITK library. An algorithm was developed in order to explore the soft tissue information of the CT-CBCT images to perform deformable image registration (DIR), making efforts to overcome the poor signal-to-noise ratio and HU calibration issues that limits CBCT use for treatment planning purposes. Warped CT images and contours were generated and their impact in adaptive radiotherapy was evaluated by DVH analysis for photon and proton treatments. Considerable discrepancies, related to the treatment planning dose distribution, might be found due to changes in patient’s anatomy. (author)

  14. Coercive Region-level Registration for Multi-modal Images

    CERN Document Server

    Chen, Yu-Hui; Newstadt, Gregory; Simmons, Jeffrey; hero, Alfred

    2015-01-01

    We propose a coercive approach to simultaneously register and segment multi-modal images which share similar spatial structure. Registration is done at the region level to facilitate data fusion while avoiding the need for interpolation. The algorithm performs alternating minimization of an objective function informed by statistical models for pixel values in different modalities. Hypothesis tests are developed to determine whether to refine segmentations by splitting regions. We demonstrate that our approach has significantly better performance than the state-of-the-art registration and segmentation methods on microscopy images.

  15. TEMPORAL REGISTRATION OF PARTIAL DATA USING PARTICLE FILTERING.

    Science.gov (United States)

    Nir, Guy; Tannenbaum, Allen

    2011-01-01

    We propose a particle filtering framework for rigid registration of a model image to a time-series of partially observed images. The method incorporates a model-based segmentation technique in order to track the pose dynamics of an underlying observed object with time. An applicable algorithm is derived by employing the proposed framework for registration of a 3D model of an anatomical structure, which was segmented from preoperative images, to consecutive axial 2D slices of a magnetic resonance imaging (MRI) scan, which are acquired intraoperatively over time. The process is fast and robust with respect to image noise and clutter, variations of illumination, and different imaging modalities.

  16. Correcting image placement errors using registration control (RegC®) technology in the photomask periphery

    Science.gov (United States)

    Cohen, Avi; Lange, Falk; Ben-Zvi, Guy; Graitzer, Erez; Vladimir, Dmitriev

    2012-11-01

    The ITRS roadmap specifies wafer overlay control as one of the major tasks for the sub 40 nm nodes in addition to CD control and defect control. Wafer overlay is strongly dependent on mask image placement error (registration errors or Reg errors)1. The specifications for registration or mask placement accuracy are significantly tighter in some of the double patterning techniques (DPT). This puts a heavy challenge on mask manufacturers (mask shops) to comply with advanced node registration specifications. The conventional methods of feeding back the systematic registration error to the E-beam writer and re-writing the mask are becoming difficult, expensive and not sufficient for the advanced nodes especially for double pattering technologies. Six production masks were measured on a standard registration metrology tool and the registration errors were calculated and plotted. Specially developed algorithm along with the RegC Wizard (dedicated software) was used to compute a correction lateral strain field that would minimize the registration errors. This strain field was then implemented in the photomask bulk material using an ultra short pulse laser based system. Finally the post process registration error maps were measured and the resulting residual registration error field with and without scale and orthogonal errors removal was calculated. In this paper we present a robust process flow in the mask shop which leads up to 32% registration 3sigma improvement, bringing some out-of-spec masks into spec, utilizing the RegC® process in the photomask periphery while leaving the exposure field optically unaffected.

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

    Energy Technology Data Exchange (ETDEWEB)

    Fortunati, Valerio, E-mail: v.fortunati@erasmusmc.nl [Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC University Medical Center, Rotterdam (Netherlands); Verhaart, René F. [Hyperthermia Unit, Department of Radiation Oncology, Erasmus MC University Medical Center Cancer Institute, Rotterdam (Netherlands); Angeloni, Francesco [Istituto di Ricovero e Cura a Carattere Scientifico Foundation SDN for Research and High Education in Nuclear Diagnostics, Naples (Italy); Lugt, Aad van der [Department of Radiology, Erasmus MC University Medical Center, Rotterdam (Netherlands); Niessen, Wiro J. [Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC University Medical Center, Rotterdam (Netherlands); Faculty of Applied Sciences, Delft University of Technology, Delft (Netherlands); Veenland, Jifke F. [Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC University Medical Center, Rotterdam (Netherlands); Paulides, Margarethus M. [Hyperthermia Unit, Department of Radiation Oncology, Erasmus MC University Medical Center Cancer Institute, Rotterdam (Netherlands); Walsum, Theo van [Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC University Medical Center, Rotterdam (Netherlands)

    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.

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

    Science.gov (United States)

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

    Energy Technology Data Exchange (ETDEWEB)

    Presles, Benoît, E-mail: benoit.presles@creatis.insa-lyon.fr; Rit, Simon; Sarrut, David [Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1, Lyon F-69621, France and Léon Bérard Cancer Center, Université de Lyon, Lyon F-69373 (France); Fargier-Voiron, Marie; Liebgott, Hervé [Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1, Lyon F-69621 (France); Biston, Marie-Claude; Munoz, Alexandre; Pommier, Pascal [Léon Bérard Cancer Center, Université de Lyon, Lyon F-69373 (France); Lynch, Rod [The Andrew Love Cancer Centre, University Hospital Geelong, Geelong 3220 (Australia)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    Gong, Ren Hui; Güler, Özgür [The Sheikh Zayed Institute for Pediatric Surgical Innovation, Children' s National Medical Center, Washington, DC 20010 (United States); Kürklüoglu, Mustafa [Department of Cardiac Surgery, Children' s National Medical Center, Washington, DC 20010 (United States); Lovejoy, John [Department of Orthopaedic Surgery and Sports Medicine, Children' s National Medical Center, Washington, DC 20010 (United States); Yaniv, Ziv, E-mail: ZYaniv@childrensnational.org [The Sheikh Zayed Institute for Pediatric Surgical Innovation, Children' s National Medical Center, Washington, DC 20010 and Departments of Pediatrics and Radiology, George Washington University, Washington, DC 20037 (United States)

    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

  1. Fast local trust region technique for diffusion tensor registration using exact reorientation and regularization.

    Science.gov (United States)

    Li, Junning; Shi, Yonggang; Tran, Giang; Dinov, Ivo; Wang, Danny J J; Toga, Arthur

    2014-05-01

    Diffusion tensor imaging is widely used in brain connectivity research. As more and more studies recruit large numbers of subjects, it is important to design registration methods which are not only theoretically rigorous, but also computationally efficient. However, the requirement of reorienting diffusion tensors complicates and considerably slows down registration procedures, due to the correlated impacts of registration forces at adjacent voxel locations. Based on the diffeomorphic Demons algorithm (Vercauteren , 2009), we propose a fast local trust region algorithm for handling inseparable registration forces for quadratic energy functions. The method guarantees that, at any time and at any voxel location, the velocity is always within its local trust region. This local regularization allows efficient calculation of the transformation update with numeric integration instead of completely solving a large linear system at every iteration. It is able to incorporate exact reorientation and regularization into the velocity optimization, and preserve the linear complexity of the diffeomorphic Demons algorithm. In an experiment with 84 diffusion tensor images involving both pair-wise and group-wise registrations, the proposed algorithm achieves better registration in comparison with other methods solving large linear systems (Yeo , 2009). At the same time, this algorithm reduces the computation time and memory demand tenfold.

  2. Significantly reducing registration time in IGRT using graphics processing units

    DEFF Research Database (Denmark)

    Noe, Karsten Østergaard; Denis de Senneville, Baudouin; Tanderup, Kari

    2008-01-01

    Purpose/Objective For online IGRT, rapid image processing is needed. Fast parallel computations using graphics processing units (GPUs) have recently been made more accessible through general purpose programming interfaces. We present a GPU implementation of the Horn and Schunck method...... respiration phases in a free breathing volunteer and 41 anatomical landmark points in each image series. The registration method used is a multi-resolution GPU implementation of the 3D Horn and Schunck algorithm. It is based on the CUDA framework from Nvidia. Results On an Intel Core 2 CPU at 2.4GHz each...... registration took 30 minutes. On an Nvidia Geforce 8800GTX GPU in the same machine this registration took 37 seconds, making the GPU version 48.7 times faster. The nine image series of different respiration phases were registered to the same reference image (full inhale). Accuracy was evaluated on landmark...

  3. Hue-assisted automatic registration of color point clouds

    Directory of Open Access Journals (Sweden)

    Hao Men

    2014-10-01

    Full Text Available This paper describes a variant of the extended Gaussian image based registration algorithm for point clouds with surface color information. The method correlates the distributions of surface normals for rotational alignment and grid occupancy for translational alignment with hue filters applied during the construction of surface normal histograms and occupancy grids. In this method, the size of the point cloud is reduced with a hue-based down sampling that is independent of the point sample density or local geometry. Experimental results show that use of the hue filters increases the registration speed and improves the registration accuracy. Coarse rigid transformations determined in this step enable fine alignment with dense, unfiltered point clouds or using Iterative Common Point (ICP alignment techniques.

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

    Science.gov (United States)

    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.

  5. Uncertainty driven probabilistic voxel selection for image registration.

    Science.gov (United States)

    Oreshkin, Boris N; Arbel, Tal

    2013-10-01

    This paper presents a novel probabilistic voxel selection strategy for medical image registration in time-sensitive contexts, where the goal is aggressive voxel sampling (e.g., using less than 1% of the total number) while maintaining registration accuracy and low failure rate. We develop a Bayesian framework whereby, first, a voxel sampling probability field (VSPF) is built based on the uncertainty on the transformation parameters. We then describe a practical, multi-scale registration algorithm, where, at each optimization iteration, different voxel subsets are sampled based on the VSPF. The approach maximizes accuracy without committing to a particular fixed subset of voxels. The probabilistic sampling scheme developed is shown to manage the tradeoff between the robustness of traditional random voxel selection (by permitting more exploration) and the accuracy of fixed voxel selection (by permitting a greater proportion of informative voxels).

  6. Pro Forma Registration of Companies

    DEFF Research Database (Denmark)

    Werlauff, Erik

    2010-01-01

    The article analyses the view taken by Community law on companies' pro forma registration in another EU or EEA country. Community law recognises pro forma registration under company law, i.e. a brass plate is sufficient, whereas it does not recognise pro forma registration under tax law, i.......e. a brass plate is not sufficient. The article provides reasons for the differential treatment of the two contexts and clarifies the difference on the basis of the Hubbard criterion, in which it was ruled that the effectiveness of Community law cannot vary according to the various branches of national law....

  7. Registration of randomized clinical trials

    DEFF Research Database (Denmark)

    Østervig, R M; Sonne, A; Rasmussen, L S

    2015-01-01

    BACKGROUND: Registration of interventional studies is necessary according to the Declaration of Helsinki but implementation has been a challenge for many journals. Acta Anaesthesiologica Scandinavica (Acta) requires registration for studies conducted after January 1(st) 2010. We aimed to assess...... registered when it could be verified that patient enrolment was started after registration in a trial registry. RESULTS: We identified 200 RCTs. Dates for patient enrolment were not specified in 51 (25.5%). The proportion of correctly registered trials increased significantly from 17.1% (19/111) for trials...

  8. PARALLEL AND ADAPTIVE UNIFORM-DISTRIBUTED REGISTRATION METHOD FOR CHANG’E-1 LUNAR REMOTE SENSED IMAGERY

    Directory of Open Access Journals (Sweden)

    X. Ning

    2012-08-01

    To resolve the above-mentioned registration difficulties, a parallel and adaptive uniform-distributed registration method for CE-1 lunar remote sensed imagery is proposed in this paper. Based on 6 pairs of randomly selected images, both the standard SIFT algorithm and the parallel and adaptive uniform-distributed registration method were executed, the versatility and effectiveness were assessed. The experimental results indicate that: by applying the parallel and adaptive uniform-distributed registration method, the efficiency of CE-1 lunar remote sensed imagery registration were increased dramatically. Therefore, the proposed method in the paper could acquire uniform-distributed registration results more effectively, the registration difficulties including difficult to obtain results, time-consuming, non-uniform distribution could be successfully solved.

  9. Computer Registration Becoming Mandatory

    CERN Multimedia

    2003-01-01

    Following the decision by the CERN Management Board (see Weekly Bulletin 38/2003), registration of all computers connected to CERN's network will be enforced and only registered computers will be allowed network access. The implementation has started with the IT buildings, continues with building 40 and the Prevessin site (as of Tuesday 4th November 2003), and will cover the whole of CERN before the end of this year. We therefore recommend strongly that you register all your computers in CERN's network database (Ethernet and wire-less cards) as soon as possible without waiting for the access restriction to take force. This will allow you accessing the network without interruption and help IT service providers to contact you in case of problems (security problems, viruses, etc.) • Users WITH a CERN computing account register at: http://cern.ch/register/ (CERN Intranet page) • Visitors WITHOUT a CERN computing account (e.g. short term visitors) register at: http://cern.ch/registerVisitorComp...

  10. Computer Registration Becoming Mandatory

    CERN Multimedia

    2003-01-01

    Following the decision by the CERN Management Board (see Weekly Bulletin 38/2003), registration of all computers connected to CERN's network will be enforced and only registered computers will be allowed network access. The implementation has started with the IT buildings, continues with building 40 and the Prevessin site (as of Tuesday 4th November 2003), and will cover the whole of CERN before the end of this year. We therefore recommend strongly that you register all your computers in CERN's network database including all network access cards (Ethernet AND wireless) as soon as possible without waiting for the access restriction to take force. This will allow you accessing the network without interruption and help IT service providers to contact you in case of problems (e.g. security problems, viruses, etc.) Users WITH a CERN computing account register at: http://cern.ch/register/ (CERN Intranet page) Visitors WITHOUT a CERN computing account (e.g. short term visitors) register at: http://cern.ch/regis...

  11. Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information

    Directory of Open Access Journals (Sweden)

    Kunlin Cao

    2012-01-01

    Full Text Available Accurate pulmonary image registration is a challenging problem when the lungs have a deformation with large distance. In this work, we present a nonrigid volumetric registration algorithm to track lung motion between a pair of intrasubject CT images acquired at different inflation levels and introduce a new vesselness similarity cost that improves intensity-only registration. Volumetric CT datasets from six human subjects were used in this study. The performance of four intensity-only registration algorithms was compared with and without adding the vesselness similarity cost function. Matching accuracy was evaluated using landmarks, vessel tree, and fissure planes. The Jacobian determinant of the transformation was used to reveal the deformation pattern of local parenchymal tissue. The average matching error for intensity-only registration methods was on the order of 1 mm at landmarks and 1.5 mm on fissure planes. After adding the vesselness preserving cost function, the landmark and fissure positioning errors decreased approximately by 25% and 30%, respectively. The vesselness cost function effectively helped improve the registration accuracy in regions near thoracic cage and near the diaphragm for all the intensity-only registration algorithms tested and also helped produce more consistent and more reliable patterns of regional tissue deformation.

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

    Science.gov (United States)

    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.

  13. A first step toward uncovering the truth about weight tuning in deformable image registration

    Science.gov (United States)

    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.

  14. 基于SIFT特征的SAR图像配准方法在玉树地震中的应用%SAR Image Registration Based on SIFT Algorithm and its Application to the 2010 Yushu Earthquake

    Institute of Scientific and Technical Information of China (English)

    贺素歌; 董彦芳; 袁小祥

    2013-01-01

    An improved matching method based on Scale Invariant Features Transform (SIFT) algorithm is proposed in this paper. The Infinite Symmetric Exponential Filter (ISEF) algorithm is adopted to reduce speckle noise before computation of the scale space pyramid. SIFT algorithm is utilized to detect the feature points and skip the first scale-space octave to reduce processing time. And then false matches are deleted in the Euclidean space. Experiments show that the proposed method increases the number of the features and improves the robustness. The match accuracy could meet the requirement of sub-pixel matching and the processing time has been cut by 60%. Finally, earthquake change detection is implemented from ALOS PALSAR images, and the building damage information detected is consistent with the results from high spatial resolution aerial image.%本文针对SAR图像特点,提出了基于改进SIFT(尺度不变特征变换)算法的SAR图像配准方案:①对待配准图像进行ISEF(无限对称指数滤波器)滤波处理,降低图像的斑点噪声;②采用SIFT算法提取特征点,略过差分金字塔第一层的特征点检测,提高时间效率;③在欧氏空间内剔除误匹配点,提高配准精度.实验表明,本文提出的SAR图像配准方案检测到的匹配点对的数量和稳健性都有提高,精度能够满足亚像元级SAR图像的应用需求,且用时比传统SIFT方法减少60%以上.最后对精配准的SAR图像进行震害变化检测,得到的震害分布与高分辨率光学图像上判读的建筑物毁坏情况基本一致.

  15. Drug Establishments Current Registration Site

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Drug Establishments Current Registration Site (DECRS) is a database of current information submitted by drug firms to register establishments (facilities) which...

  16. A MNCIE method for registration of ultrasound images

    Institute of Scientific and Technical Information of China (English)

    JIN Jing; WANG Qiang; SHEN Yi

    2007-01-01

    A new approach to the problem of registration of ultrasound images is presented, using a concept of Nonlinear Correlation Information Entropy (NCIE) as the matching criterion. The proposed method applies NCIE to measure the correlation degree between the image intensities of corresponding voxel in the floating and reference images. Registration is achieved by adjustment of the relative position until NCIE between the images is maximized. However, unlike mutual information (MI), NCIE varies in the closed interval [0, 1 ], and around the extremum it varies sharply, which makes it possible that thresholds of NCIE can be used to boost the search for the registration transformation. Using this feature of NCIE, we combine the downhill simplex searching algorithm to register the ultrasound images. The simulations are conducted to testify the effectiveness and rapidity of the proposed registration method, in which the ultrasound floating images are aligned to the reference images with required registration accuracy. Moreover, the NCIE based method can overcome local minima problem by setting thresholds and can take care of the differences in contrast between the floating and reference images.

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

    Science.gov (United States)

    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.

  18. 44 CFR 206.112 - Registration period.

    Science.gov (United States)

    2010-10-01

    ... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Registration period. 206.112... Households § 206.112 Registration period. (a) Initial period. The standard FEMA registration period is 60...) Extension of the registration period. The regional administrator or his/her designee may extend the...

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

    Science.gov (United States)

    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.

  20. Breathing motion compensated registration of laparoscopic liver ultrasound to CT

    Science.gov (United States)

    Ramalhinho, João.; Robu, Maria; Thompson, Stephen; Edwards, Philip; Schneider, Crispin; Gurusamy, Kurinchy; Hawkes, David; Davidson, Brian; Barratt, Dean; Clarkson, Matthew J.

    2017-03-01

    Laparoscopic Ultrasound (LUS) is regularly used during laparoscopic liver resection to locate critical vascular structures. Many tumours are iso-echoic, and registration to pre-operative CT or MR has been proposed as a method of image guidance. However, factors such as abdominal insufflation, LUS probe compression and breathing motion cause deformation of the liver, making this task far from trivial. Fortunately, within a smaller local region of interest a rigid solution can suffice. Also, the respiratory cycle can be expected to be consistent. Therefore, in this paper we propose a feature-based local rigid registration method to align tracked LUS data with CT while compensating for breathing motion. The method employs the Levenberg-Marquardt Iterative Closest Point (LMICP) algorithm, registers both on liver surface and vessels and requires two LUS datasets, one for registration and another for breathing estimation. Breathing compensation is achieved by fitting a 1D breathing model to the vessel points. We evaluate the algorithm by measuring the Target Registration Error (TRE) of three manually selected landmarks of a single porcine subject. Breathing compensation improves accuracy in 77% of the measurements. In the best case, TRE values below 3mm are obtained. We conclude that our method can potentially correct for breathing motion without gated acquisition of LUS and be integrated in the surgical workflow with an appropriate segmentation.

  1. F-TIMER: fast tensor image morphing for elastic registration.

    Science.gov (United States)

    Yap, Pew-Thian; Wu, Guorong; Zhu, Hongtu; Lin, Weili; Shen, Dinggang

    2010-05-01

    We propose a novel diffusion tensor imaging (DTI) registration algorithm, called fast tensor image morphing for elastic registration (F-TIMER). F-TIMER leverages multiscale tensor regional distributions and local boundaries for hierarchically driving deformable matching of tensor image volumes. Registration is achieved by utilizing a set of automatically determined structural landmarks, via solving a soft correspondence problem. Based on the estimated correspondences, thin-plate splines are employed to generate a smooth, topology preserving, and dense transformation, and to avoid arbitrary mapping of nonlandmark voxels. To mitigate the problem of local minima, which is common in the estimation of high dimensional transformations, we employ a hierarchical strategy where a small subset of voxels with more distinctive attribute vectors are first deployed as landmarks to estimate a relatively robust low-degrees-of-freedom transformation. As the registration progresses, an increasing number of voxels are permitted to participate in refining the correspondence matching. A scheme as such allows less conservative progression of the correspondence matching towards the optimal solution, and hence results in a faster matching speed. Compared with its predecessor TIMER, which has been shown to outperform state-of-the-art algorithms, experimental results indicate that F-TIMER is capable of achieving comparable accuracy at only a fraction of the computation cost.

  2. Cross contrast multi-channel image registration using image synthesis for MR brain images.

    Science.gov (United States)

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

    2017-02-01

    Multi-modal deformable registration is important for many medical image analysis tasks such as atlas alignment, image fusion, and distortion correction. Whereas a conventional method would register images with different modalities using modality independent features or information theoretic metrics such as mutual information, this paper presents a new framework that addresses the problem using a two-channel registration algorithm capable of using mono-modal similarity measures such as sum of squared differences or cross-correlation. To make it possible to use these same-modality measures, image synthesis is used to create proxy images for the opposite modality as well as intensity-normalized images from each of the two available images. The new deformable registration framework was evaluated by performing intra-subject deformation recovery, intra-subject boundary alignment, and inter-subject label transfer experiments using multi-contrast magnetic resonance brain imaging data. Three different multi-channel registration algorithms were evaluated, revealing that the framework is robust to the multi-channel deformable registration algorithm that is used. With a single exception, all results demonstrated improvements when compared against single channel registrations using the same algorithm with mutual information.

  3. Corneal topography matching by iterative registration.

    Science.gov (United States)

    Wang, Junjie; Elsheikh, Ahmed; Davey, Pinakin G; Wang, Weizhuo; Bao, Fangjun; Mottershead, John E

    2014-11-01

    Videokeratography is used for the measurement of corneal topography in overlapping portions (or maps) which must later be joined together to form the overall topography of the cornea. The separate portions are measured from different viewpoints and therefore must be brought together by registration of measurement points in the regions of overlap. The central map is generally the most accurate, but all maps are measured with uncertainty that increases towards the periphery. It becomes the reference (or static) map, and the peripheral (or dynamic) maps must then be transformed by rotation and translation so that the overlapping portions are matched. The process known as registration, of determining the necessary transformation, is a well-understood procedure in image analysis and has been applied in several areas of science and engineering. In this article, direct search optimisation using the Nelder-Mead algorithm and several variants of the iterative closest/corresponding point routine are explained and applied to simulated and real clinical data. The measurement points on the static and dynamic maps are generally different so that it becomes necessary to interpolate, which is done using a truncated series of Zernike polynomials. The point-to-plane iterative closest/corresponding point variant has the advantage of releasing certain optimisation constraints that lead to persistent registration and alignment errors when other approaches are used. The point-to-plane iterative closest/corresponding point routine is found to be robust to measurement noise, insensitive to starting values of the transformation parameters and produces high-quality results when using real clinical data.

  4. A NEW IMAGE REGISTRATION METHOD FOR GREY IMAGES

    Institute of Scientific and Technical Information of China (English)

    Nie Xuan; Zhao Rongchun; Jiang Zetao

    2004-01-01

    The proposed algorithm relies on a group of new formulas for calculating tangent slope so as to address angle feature of edge curves of image. It can utilize tangent angle features to estimate automatically and fully the rotation parameters of geometric transform and enable rough matching of images with huge rotation difference. After angle compensation, it can search for matching point sets by correlation criterion, then calculate parameters of affine transform, enable higher-precision emendation of rotation and transferring. Finally, it fulfills precise matching for images with relax-tense iteration method. Compared with the registration approach based on wavelet direction-angle features, the matching algorithm with tangent feature of image edge is more robust and realizes precise registration of various images. Furthermore, it is also helpful in graphics matching.

  5. Registration of image feature points using differential evolution

    Institute of Scientific and Technical Information of China (English)

    ZHANG Hao; HUANG Zhan-hua; YU Dao-ying

    2005-01-01

    This paper introduces a robust global nonlinear optimizer-differential evolution(DE),which is a simple evolution algorithm to search for an optimal transformation that makes the best alignment of two sets of feature points.To map the problem of matching into the framework of DE,the objective function is proportional to the registration error which is measured by Hausdorff distance,while the parameters of transformation are encoded in floating-point as the functional variables.Three termination criteria are proposed for DE.A simulation of 2-dimensional point sets and a similarity transformation are presented to compare the robustness and convergence properties of DE with genetic algorithm's (GA).And the registration of an object and its contour model have been demonstrated by using of DE to natural images.

  6. A High-Precision Registration Technology Based on Bundle Adjustment in Structured Light Scanning System

    Directory of Open Access Journals (Sweden)

    Jianying Yuan

    2014-01-01

    Full Text Available The multiview 3D data registration precision will decrease with the increasing number of registrations when measuring a large scale object using structured light scanning. In this paper, we propose a high-precision registration method based on multiple view geometry theory in order to solve this problem. First, a multiview network is constructed during the scanning process. The bundle adjustment method from digital close range photogrammetry is used to optimize the multiview network to obtain high-precision global control points. After that, the 3D data under each local coordinate of each scan are registered with the global control points. The method overcomes the error accumulation in the traditional registration process and reduces the time consumption of the following 3D data global optimization. The multiview 3D scan registration precision and efficiency are increased. Experiments verify the effectiveness of the proposed algorithm.

  7. Automatic Registration and Error Detection of Multiple Slices Using Landmarks

    Directory of Open Access Journals (Sweden)

    Hans Frimmel

    2001-01-01

    Full Text Available Objectives. When analysing the 3D structure of tissue, serial sectioning and staining of the resulting slices is sometimes the preferred option. This leads to severe registration problems. In this paper, a method for automatic registration and error detection of slices using landmark needles has been developed. A cost function takes some parameters from the current state of the problem to be solved as input and gives a quality of the current solution as output. The cost function used in this paper, is based on a model of the slices and the landmark needles. The method has been used to register slices of prostates in order to create 3D computer models. Manual registration of the same prostates has been undertaken and compared with the results from the algorithm. Methods. Prostates from sixteen men who underwent radical prostatectomy were formalin fixed with landmark needles, sliced and the slices were computer reconstructed. The cost function takes rotation and translation for each prostate slice, as well as slope and offset for each landmark needle as input. The current quality of fit of the model, using the input parameters given, is returned. The function takes the built‐in instability of the model into account. The method uses a standard algorithm to optimize the prostate slice positions. To verify the result, s standard method in statistics was used. Results. The methods were evaluated for 16 prostates. When testing blindly, a physician could not determine whether the registration shown to him were created by the automated method described in this paper, or manually by an expert, except in one out of 16 cases. Visual inspection and analysis of the outlier confirmed that the input data had been deformed. The automatic detection of erroneous slices marked a few slices, including the outlier, as suspicious. Conclusions. The model based registration performs better than traditional simple slice‐wise registration. In the case of prostate

  8. Rotation and translation registration of bandlimited interferometric images using a chirp z-transform

    Science.gov (United States)

    Iacchetta, Alexander S.; Fienup, James R.; Leisawitz, David T.

    2016-07-01

    Image reconstruction algorithms for wide-field spatio-spectral interferometry require knowledge of registration parameters associated with low-resolution image measurements at various baseline orientations, such that the images can be registered to within the fine resolution of the final desired image. We have developed an image registration procedure that combines a nonlinear optimization algorithm with the sub-pixel precision of chirp z-transform resampling, particularly for rotation and translation, of bandlimited images with non-radially symmetric aberrations. We show the accuracy of this image registration technique on simulated images that have a complexity comparable to scenes observed experimentally with NASA's wide-field imaging interferometry testbed. Registration to within a tenth of a pixel for translation and within three arcminutes for rotation is demonstrated at the largest simulated noise levels.

  9. Efficient Hyperelastic Regularization for Registration

    DEFF Research Database (Denmark)

    Darkner, Sune; Hansen, Michael S; Larsen, Rasmus;

    2011-01-01

    For most image registration problems a smooth one-to-one mapping is desirable, a diffeomorphism. This can be obtained using priors such as volume preservation, certain kinds of elasticity or both. The key principle is to regularize the strain of the deformation which can be done through penalizat......For most image registration problems a smooth one-to-one mapping is desirable, a diffeomorphism. This can be obtained using priors such as volume preservation, certain kinds of elasticity or both. The key principle is to regularize the strain of the deformation which can be done through...... penalization of the eigen values of the stress tensor. We present a computational framework for regularization of image registration for isotropic hyper elasticity. We formulate an efficient and parallel scheme for computing the principal stain based for a given parameterization by decomposing the left Cauchy...... elastic priors such at the Saint Vernant Kirchoff model, the Ogden material model or Riemanian elasticity. We exemplify the approach through synthetic registration and special tests as well as registration of different modalities; 2D cardiac MRI and 3D surfaces of the human ear. The artificial examples...

  10. Handling topological changes during elastic registration : Application to augmented reality in laparoscopic surgery.

    Science.gov (United States)

    Paulus, Christoph J; Haouchine, Nazim; Kong, Seong-Ho; Soares, Renato Vianna; Cazier, David; Cotin, Stephane

    2017-03-01

    Locating the internal structures of an organ is a critical aspect of many surgical procedures. Minimally invasive surgery, associated with augmented reality techniques, offers the potential to visualize inner structures, allowing for improved analysis, depth perception or for supporting planning and decision systems. Most of the current methods dealing with rigid or non-rigid augmented reality make the assumption that the topology of the organ is not modified. As surgery relies essentially on cutting and dissection of anatomical structures, such methods are limited to the early stages of the surgery. We solve this shortcoming with the introduction of a method for physics-based elastic registration using a single view from a monocular camera. Singularities caused by topological changes are detected and propagated to the preoperative model. This significantly improves the coherence between the actual laparoscopic view and the model and provides added value in terms of navigation and decision-making, e.g., by overlaying the internal structures of an organ on the laparoscopic view. Our real-time augmentation method is assessed on several scenarios, using synthetic objects and real organs. In all cases, the impact of our approach is demonstrated, both qualitatively and quantitatively ( http://www.open-cas.org/?q=PaulusIJCARS16 ). The presented approach tackles the challenge of localizing internal structures throughout a complete surgical procedure, even after surgical cuts. This information is crucial for surgeons to improve the outcome for their surgical procedure and avoid complications.

  11. Real-time surface reconstruction from stereo endoscopic images for intraoperative registration

    Science.gov (United States)

    Röhl, S.; Bodenstedt, S.; Suwelack, S.; Kenngott, H.; Mueller-Stich, B. P.; Dillmann, R.; Speidel, S.

    2011-03-01

    Minimally invasive surgery is a medically complex discipline that can heavily benefit from computer assistance. One way to assist the surgeon is to blend in useful information about the intervention into the surgical view using Augmented Reality. This information can be obtained during preoperative planning and integrated into a patient-tailored model of the intervention. Due to soft tissue deformation, intraoperative sensor data such as endoscopic images has to be acquired and non-rigidly registered with the preoperative model to adapt it to local changes. Here, we focus on a procedure that reconstructs the organ surface from stereo endoscopic images with millimeter accuracy in real-time. It deals with stereo camera calibration, pixel-based correspondence analysis, 3D reconstruction and point cloud meshing. Accuracy, robustness and speed are evaluated with images from a test setting as well as intraoperative images. We also present a workflow where the reconstructed surface model is registered with a preoperative model using an optical tracking system. As preliminary result, we show an initial overlay between an intraoperative and a preoperative surface model that leads to a successful rigid registration between these two models.

  12. Accelerated Deformable Registration of Repetitive MRI during Radiotherapy in Cervical Cancer

    DEFF Research Database (Denmark)

    Noe, Karsten Østergaard; Tanderup, Kari; Kiritsis, Christian;

    2006-01-01

    Tumour regression and organ deformations during radiotherapy (RT) of cervical cancer represent major challenges regarding accurate conformation and calculation of dose when using image-guided adaptive radiotherapy. Deformable registration algorithms are able to handle organ deformations, which can...... be useful with advanced tools such as auto segmentation of organs and dynamic adaptation of radiotherapy. The aim of this study was to accelerate and validate deformable registration in MRI-based image-guided radiotherapy of cervical cancer.    ...

  13. 3D-2D ultrasound feature-based registration for navigated prostate biopsy: A feasibility study

    OpenAIRE

    Selmi, Sonia,; Promayon, Emmanuel; Troccaz, Jocelyne

    2016-01-01

    International audience; The aim of this paper is to describe a 3D-2D ultrasound feature-based registration method for navigated prostate biopsy and its first results obtained on patient data. A system combining a low-cost tracking system and a 3D-2D registration algorithm was designed. The proposed 3D-2D registration method combines geometric and image-based distances. After extracting features from ultrasound images, 3D and 2D features within a defined distance are matched using an intensity...

  14. 3D-2D ultrasound feature-based registration for navigated prostate biopsy: a feasibility study.

    Science.gov (United States)

    Selmi, Sonia Y; Promayon, Emmanuel; Troccaz, Jocelyne

    2016-08-01

    The aim of this paper is to describe a 3D-2D ultrasound feature-based registration method for navigated prostate biopsy and its first results obtained on patient data. A system combining a low-cost tracking system and a 3D-2D registration algorithm was designed. The proposed 3D-2D registration method combines geometric and image-based distances. After extracting features from ultrasound images, 3D and 2D features within a defined distance are matched using an intensity-based function. The results are encouraging and show acceptable errors with simulated transforms applied on ultrasound volumes from real patients.

  15. Automatic scan registration using 3D linear and planar features

    Science.gov (United States)

    Yao, Jian; Ruggeri, Mauro R.; Taddei, Pierluigi; Sequeira, Vítor

    2010-09-01

    We present a common framework for accurate and automatic registration of two geometrically complex 3D range scans by using linear or planar features. The linear features of a range scan are extracted with an efficient split-and-merge line-fitting algorithm, which refines 2D edges extracted from the associated reflectance image considering the corresponding 3D depth information. The planar features are extracted employing a robust planar segmentation method, which partitions a range image into a set of planar patches. We propose an efficient probability-based RANSAC algorithm to automatically register two overlapping range scans. Our algorithm searches for matching pairs of linear (planar) features in the two range scans leading to good alignments. Line orientation (plane normal) angles and line (plane) distances formed by pairs of linear (planar) features are invariant with respect to the rigid transformation and are utilized to find candidate matches. To efficiently seek for candidate pairs and groups of matched features we build a fast search codebook. Given two sets of matched features, the rigid transformation between two scans is computed by using iterative linear optimization algorithms. The efficiency and accuracy of our registration algorithm were evaluated on several challenging range data sets.

  16. SPHERE: SPherical Harmonic Elastic REgistration of HARDI data.

    Science.gov (United States)

    Yap, Pew-Thian; Chen, Yasheng; An, Hongyu; Yang, Yang; Gilmore, John H; Lin, Weili; Shen, Dinggang

    2011-03-15

    In contrast to the more common Diffusion Tensor Imaging (DTI), High Angular Resolution Diffusion Imaging (HARDI) allows superior delineation of angular microstructures of brain white matter, and makes possible multiple-fiber modeling of each voxel for better characterization of brain connectivity. However, the complex orientation information afforded by HARDI makes registration of HARDI images more complicated than scalar images. In particular, the question of how much orientation information is needed for satisfactory alignment has not been sufficiently addressed. Low order orientation representation is generally more robust than high order representation, although the latter provides more information for correct alignment of fiber pathways. However, high order representation, when naïvely utilized, might not necessarily be conducive to improving registration accuracy since similar structures with significant orientation differences prior to proper alignment might be mistakenly taken as non-matching structures. We present in this paper a HARDI registration algorithm, called SPherical Harmonic Elastic REgistration (SPHERE), which in a principled means hierarchically extracts orientation information from HARDI data for structural alignment. The image volumes are first registered using robust, relatively direction invariant features derived from the Orientation Distribution Function (ODF), and the alignment is then further refined using spherical harmonic (SH) representation with gradually increasing orders. This progression from non-directional, single-directional to multi-directional representation provides a systematic means of extracting directional information given by diffusion-weighted imaging. Coupled with a template-subject-consistent soft-correspondence-matching scheme, this approach allows robust and accurate alignment of HARDI data. Experimental results show marked increase in accuracy over a state-of-the-art DTI registration algorithm. Copyright © 2010

  17. Radar image registration and rectification

    Science.gov (United States)

    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.

  18. Efficient Hyperelastic Regularization for Registration

    DEFF Research Database (Denmark)

    Darkner, Sune; Hansen, Michael Sass; Larsen, Rasmus;

    2011-01-01

    For most image registration problems a smooth one-to-one mapping is desirable, a diffeomorphism. This can be obtained using priors such as volume preservation, certain kinds of elasticity or both. The key principle is to regularize the strain of the deformation which can be done through penalizat......For most image registration problems a smooth one-to-one mapping is desirable, a diffeomorphism. This can be obtained using priors such as volume preservation, certain kinds of elasticity or both. The key principle is to regularize the strain of the deformation which can be done through...... penalization of the eigen values of the stress tensor. We present a computational framework for regularization of image registration for isotropic hyper elasticity. We formulate an efficient and parallel scheme for computing the principal stain based for a given parameterization by decomposing the left Cauchy...

  19. Language proficiency and nursing registration.

    Science.gov (United States)

    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.

  20. Surface-based registration of liver in ultrasound and CT

    Science.gov (United States)

    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.

  1. Global Registration of Kinect Point Clouds using Augmented Extended Information Filter and Multiple Features

    Science.gov (United States)

    Kang, Z.; Chang, M.

    2016-10-01

    Because the Infra-Red (IR) Kinect sensor only provides accurate depths up to 5 m for a limited field of view (60°), the problem of registration error accumulation becomes inevitable in indoor mapping. Therefore, in this paper, a global registration method is proposed based on augmented extended Information Filter (AEIF). The point cloud registration is regarded as a stochastic system so that AEIF is used to produces the accurate estimates of rigid transformation parameters through eliminating the error accumulation suffered by the pair-wise registration. Moreover, because the indoor scene normally contains planar primitives, they can be employed to control the registration of multiple scans. Therefore, the planar primitives are first fitted based on optimized BaySAC algorithm and simplification algorithm preserving the feature points. Besides the constraint of corresponding points, we then derive the plane normal vector constraint as an additional observation model of AEIF to optimize the registration parameters between each pair of adjacent scans. The proposed approach is tested on point clouds acquired by a Kinect camera from an indoor environment. The experimental results show that our proposed algorithm is proven to be capable of improving the accuracy of multiple scans aligning by 90%.

  2. Numerical methods for image registration

    CERN Document Server

    Modersitzki, Jan

    2003-01-01

    Based on the author's lecture notes and research, this well-illustrated and comprehensive text is one of the first to provide an introduction to image registration with particular emphasis on numerical methods in medical imaging. Ideal for researchers in industry and academia, it is also a suitable study guide for graduate mathematicians, computer scientists, engineers, medical physicists, and radiologists.Image registration is utilised whenever information obtained from different viewpoints needs to be combined or compared and unwanted distortion needs to be eliminated. For example, CCTV imag

  3. Manifold-based feature point matching for multi-modal image registration.

    Science.gov (United States)

    Hu, Liang; Wang, Manning; Song, Zhijian

    2013-03-01

    Images captured using different modalities usually have significant variations in their intensities, which makes it difficult to reveal their internal structural similarities and achieve accurate registration. Most conventional feature-based image registration techniques are fast and efficient, but they cannot be used directly for the registration of multi-modal images because of these intensity variations. This paper introduces the theory of manifold learning to transform the original images into mono-modal modalities, which is a feature-based method that is applicable to multi-modal image registration. Subsequently, scale-invariant feature transform is used to detect highly distinctive local descriptors and matches between corresponding images, and a point-based registration is executed. The algorithm was tested with T1- and T2-weighted magnetic resonance (MR) images obtained from BrainWeb. Both qualitative and quantitative evaluations of the method were performed and the results compared with those produced previously. The experiments showed that feature point matching after manifold learning achieved more accurate results than did the similarity measure for multi-modal image registration. This study provides a new manifold-based feature point matching method for multi-modal medical image registration, especially for MR images. The proposed method performs better than do conventional intensity-based techniques in terms of its registration accuracy and is suitable for clinical procedures. Copyright © 2012 John Wiley & Sons, Ltd.

  4. Duality based optical flow algorithms with applications

    DEFF Research Database (Denmark)

    Rakêt, Lars Lau

    We consider the popular TV-L1 optical flow formulation, and the so-called duality based algorithm for minimizing the TV-L1 energy. The original formulation is extended to allow for vector valued images, and minimization results are given. In addition we consider different definitions of total...... variation regularization, and related formulations of the optical flow problem that may be used with a duality based algorithm. We present a highly optimized algorithmic setup to estimate optical flows, and give five novel applications. The first application is registration of medical images, where X......-ray images of different hands, taken using different imaging devices are registered using a TV-L1 optical flow algorithm. We propose to regularize the input images, using sparsity enhancing regularization of the image gradient to improve registration results. The second application is registration of 2D...

  5. Duality based optical flow algorithms with applications

    DEFF Research Database (Denmark)

    Rakêt, Lars Lau

    We consider the popular TV-L1 optical flow formulation, and the so-called duality based algorithm for minimizing the TV-L1 energy. The original formulation is extended to allow for vector valued images, and minimization results are given. In addition we consider different definitions of total...... variation regularization, and related formulations of the optical flow problem that may be used with a duality based algorithm. We present a highly optimized algorithmic setup to estimate optical flows, and give five novel applications. The first application is registration of medical images, where X......-ray images of different hands, taken using different imaging devices are registered using a TV-L1 optical flow algorithm. We propose to regularize the input images, using sparsity enhancing regularization of the image gradient to improve registration results. The second application is registration of 2D...

  6. The Pose Estimation of Mobile Robot Based on Improved Point Cloud Registration

    Directory of Open Access Journals (Sweden)

    Yanzi Miao

    2016-03-01

    Full Text Available Due to GPS restrictions, an inertial sensor is usually used to estimate the location of indoor mobile robots. However, it is difficult to achieve high-accuracy localization and control by inertial sensors alone. In this paper, a new method is proposed to estimate an indoor mobile robot pose with six degrees of freedom based on an improved 3D-Normal Distributions Transform algorithm (3D-NDT. First, point cloud data are captured by a Kinect sensor and segmented according to the distance to the robot. After the segmentation, the input point cloud data are processed by the Approximate Voxel Grid Filter algorithm in different sized voxel grids. Second, the initial registration and precise registration are performed respectively according to the distance to the sensor. The most distant point cloud data use the 3D-Normal Distributions Transform algorithm (3D-NDT with large-sized voxel grids for initial registration, based on the transformation matrix from the odometry method. The closest point cloud data use the 3D-NDT algorithm with small-sized voxel grids for precise registration. After the registrations above, a final transformation matrix is obtained and coordinated. Based on this transformation matrix, the pose estimation problem of the indoor mobile robot is solved. Test results show that this method can obtain accurate robot pose estimation and has better robustness.

  7. USDA registration and rectification requirements

    Science.gov (United States)

    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.

  8. ACIR: automatic cochlea image registration

    Science.gov (United States)

    Al-Dhamari, Ibraheem; Bauer, Sabine; Paulus, Dietrich; Lissek, Friedrich; Jacob, Roland

    2017-02-01

    Efficient Cochlear Implant (CI) surgery requires prior knowledge of the cochlea's size and its characteristics. This information helps to select suitable implants for different patients. To get these measurements, a segmentation method of cochlea medical images is needed. An important pre-processing step for good cochlea segmentation involves efficient image registration. The cochlea's small size and complex structure, in addition to the different resolutions and head positions during imaging, reveals a big challenge for the automated registration of the different image modalities. In this paper, an Automatic Cochlea Image Registration (ACIR) method for multi- modal human cochlea images is proposed. This method is based on using small areas that have clear structures from both input images instead of registering the complete image. It uses the Adaptive Stochastic Gradient Descent Optimizer (ASGD) and Mattes's Mutual Information metric (MMI) to estimate 3D rigid transform parameters. The use of state of the art medical image registration optimizers published over the last two years are studied and compared quantitatively using the standard Dice Similarity Coefficient (DSC). ACIR requires only 4.86 seconds on average to align cochlea images automatically and to put all the modalities in the same spatial locations without human interference. The source code is based on the tool elastix and is provided for free as a 3D Slicer plugin. Another contribution of this work is a proposed public cochlea standard dataset which can be downloaded for free from a public XNAT server.

  9. What drives Users' Website Registration?

    NARCIS (Netherlands)

    T. Li (Ting); P.A. Pavlou (Paul)

    2013-01-01

    textabstractUser registration is an important prerequisite for the success of many websites by enabling users to gain access to domain information and personalized content. It is not always desirable for users, however, because they need to disclose personal information. This paper examines what dri

  10. Multibeam 3D Underwater SLAM with Probabilistic Registration

    Directory of Open Access Journals (Sweden)

    Albert Palomer

    2016-04-01

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

  11. Multibeam 3D Underwater SLAM with Probabilistic Registration.

    Science.gov (United States)

    Palomer, Albert; Ridao, Pere; Ribas, David

    2016-04-20

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

  12. 75 FR 4383 - Pesticide Products: Registration Applications

    Science.gov (United States)

    2010-01-27

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

  13. Accelerated gradient-based free form deformable registration for online adaptive radiotherapy

    Science.gov (United States)

    Yu, Gang; Liang, Yueqiang; Yang, Guanyu; Shu, Huazhong; Li, Baosheng; Yin, Yong; Li, Dengwang

    2015-04-01

    The registration of planning fan-beam computed tomography (FBCT) and daily cone-beam CT (CBCT) is a crucial step in adaptive radiation therapy. The current intensity-based registration algorithms, such as Demons, may fail when they are used to register FBCT and CBCT, because the CT numbers in CBCT cannot exactly correspond to the electron densities. In this paper, we investigated the effects of CBCT intensity inaccuracy on the registration accuracy and developed an accurate gradient-based free form deformation algorithm (GFFD). GFFD distinguishes itself from other free form deformable registration algorithms by (a) measuring the similarity using the 3D gradient vector fields to avoid the effect of inconsistent intensities between the two modalities; (b) accommodating image sampling anisotropy using the local polynomial approximation-intersection of confidence intervals (LPA-ICI) algorithm to ensure a smooth and continuous displacement field; and (c) introducing a ‘bi-directional’ force along with an adaptive force strength adjustment to accelerate the convergence process. It is expected that such a strategy can decrease the effect of the inconsistent intensities between the two modalities, thus improving the registration accuracy and robustness. Moreover, for clinical application, the algorithm was implemented by graphics processing units (GPU) through OpenCL framework. The registration time of the GFFD algorithm for each set of CT data ranges from 8 to 13 s. The applications of on-line adaptive image-guided radiation therapy, including auto-propagation of contours, aperture-optimization and dose volume histogram (DVH) in the course of radiation therapy were also studied by in-house-developed software.

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

    Energy Technology Data Exchange (ETDEWEB)

    Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali [Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205 (United States); 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

  15. 21 CFR 710.6 - Notification of registrant; cosmetic product establishment registration number.

    Science.gov (United States)

    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....

  16. 9 CFR 2.30 - Registration.

    Science.gov (United States)

    2010-01-01

    ... sign the registration form. (2) In any situation in which a school or department of a university or... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Registration. 2.30 Section 2.30... WELFARE REGULATIONS Research Facilities § 2.30 Registration. (a) Requirements and procedures. (1)...

  17. Clinical trial registration in oral health journals.

    Science.gov (United States)

    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.

  18. Fast Rotation Search with Stereographic Projections for 3D Registration.

    Science.gov (United States)

    Parra Bustos, Alvaro; Chin, Tat-Jun; Eriksson, Anders; Li, Hongdong; Suter, David

    2016-11-01

    Registering two 3D point clouds involves estimating the rigid transform that brings the two point clouds into alignment. Recently there has been a surge of interest in using branch-and-bound (BnB) optimisation for point cloud registration. While BnB guarantees globally optimal solutions, it is usually too slow to be practical. A fundamental source of difficulty lies in the search for the rotational parameters. In this work, first by assuming that the translation is known, we focus on constructing a fast rotation search algorithm. With respect to an inherently robust geometric matching criterion, we propose a novel bounding function for BnB that is provably tighter than previously proposed bounds. Further, we also propose a fast algorithm to evaluate our bounding function. Our idea is based on using stereographic projections to precompute and index all possible point matches in spatial R-trees for rapid evaluations. The result is a fast and globally optimal rotation search algorithm. To conduct full 3D registration, we co-optimise the translation by embedding our rotation search kernel in a nested BnB algorithm. Since the inner rotation search is very efficient, the overall 6DOF optimisation is speeded up significantly without losing global optimality. On various challenging point clouds, including those taken out of lab settings, our approach demonstrates superior efficiency.

  19. Improving JWST Coronagraphic Performance with Accurate Image Registration

    Science.gov (United States)

    Van Gorkom, Kyle; Pueyo, Laurent; Lajoie, Charles-Philippe; JWST Coronagraphs Working Group

    2016-06-01

    The coronagraphs on the James Webb Space Telescope (JWST) will enable high-contrast observations of faint objects at small separations from bright hosts, such as circumstellar disks, exoplanets, and quasar disks. Despite attenuation by the coronagraphic mask, bright speckles in the host’s point spread function (PSF) remain, effectively washing out the signal from the faint companion. Suppression of these bright speckles is typically accomplished by repeating the observation with a star that lacks a faint companion, creating a reference PSF that can be subtracted from the science image to reveal any faint objects. Before this reference PSF can be subtracted, however, the science and reference images must be aligned precisely, typically to 1/20 of a pixel. Here, we present several such algorithms for performing image registration on JWST coronagraphic images. Using both simulated and pre-flight test data (taken in cryovacuum), we assess (1) the accuracy of each algorithm at recovering misaligned scenes and (2) the impact of image registration on achievable contrast. Proper image registration, combined with post-processing techniques such as KLIP or LOCI, will greatly improve the performance of the JWST coronagraphs.

  20. On-line range images registration with GPGPU

    Science.gov (United States)

    Będkowski, J.; Naruniec, J.

    2013-03-01

    This paper concerns implementation of algorithms in the two important aspects of modern 3D data processing: data registration and segmentation. Solution proposed for the first topic is based on the 3D space decomposition, while the latter on image processing and local neighbourhood search. Data processing is implemented by using NVIDIA compute unified device architecture (NIVIDIA CUDA) parallel computation. The result of the segmentation is a coloured map where different colours correspond to different objects, such as walls, floor and stairs. The research is related to the problem of collecting 3D data with a RGB-D camera mounted on a rotated head, to be used in mobile robot applications. Performance of the data registration algorithm is aimed for on-line processing. The iterative closest point (ICP) approach is chosen as a registration method. Computations are based on the parallel fast nearest neighbour search. This procedure decomposes 3D space into cubic buckets and, therefore, the time of the matching is deterministic. First technique of the data segmentation uses accele-rometers integrated with a RGB-D sensor to obtain rotation compensation and image processing method for defining pre-requisites of the known categories. The second technique uses the adapted nearest neighbour search procedure for obtaining normal vectors for each range point.

  1. Tomographic patient registration and conformal avoidance tomotherapy

    Science.gov (United States)

    Aldridge, Jennifer Stacy

    Development of tomotherapy has led to the emergence of several processes, providing the basis for many unique investigative opportunities. These processes include setup verification, tomographic verification, megavoltage dose reconstruction, and conformal avoidance tomotherapy. Setup verification and conformal avoidance tomotherapy, in particular, are two closely intertwined matters. In order to avoid critical structures located within or adjacent to indistinct tumor regions, accurate patient positioning from fraction to fraction must be ensured. With tomographic patient registration, a higher level of assurance is offered than with traditional positioning methods. Translational and rotational offsets are calculated directly from projection data using cross- correlation or fast Fourier transforms. Experiments assessing the algorithm's ability to calculate individual offsets were conducted using the University of Wisconsin's Tomotherapy Benchtop. These experiments indicate statistical errors within +/-1 mm for offsets up to approximately 20 mm, with maximum offset errors of about +/-2 mm for displacements up to 35 mm. The angular offset component is within +/-2°. To evaluate the registration process as a whole, experimental results from a few multi-parameter examples are also analyzed. With the development of tomographic patient registration in projection space, efforts to promote further sparing of critical structures are justified. Conformal avoidance tomotherapy has as its objective to treat an indistinct tumor region while conformally avoiding any normal critical structures in that region. To demonstrate the advantages of conformal avoidance tomotherapy, conventional and tomotherapy treatments are contrasted for both nasopharyngeal and breast carcinoma cases. For initial research efforts, computed tomography data sets of a human male and female were obtained via the ``Visible Human Project''. Since these data sets are on the order of hundreds of megabytes, both

  2. 基于射线轮廓点匹配的生猪红外与可见光图像自动配准%Automatic registration of IR and optical pig images based on contour match of radial line feature points

    Institute of Scientific and Technical Information of China (English)

    刘波; 朱伟兴; 纪滨; 马长华

    2013-01-01

      为研究生猪多源图像特征提取方法及生猪体表温度与生猪异常的关系特征,该文提出一种基于射线轮廓特征点匹配的红外与可见光图像自动配准方法。采用红外热像仪,同时采集相同猪舍场景的可见光图像和红外热图像,以红外热图像中生猪区域质心为中心间隔均匀角度构建辅助射线,提取射线与边缘轮廓交点构建匹配特征点集,通过计算不同尺度变换因子下特征点集间的加权部分 Hausdorff 距离作为测度,引入 RPROP 算法进行迭代加速,实现了可见光图像和红外热图像的快速自动配准。试验中,应用该文算法对50对红外和光学图像进行了测试,所提出自动配准方法配准成功率达到94%,平均配准误差小于1像素,试验结果表明自动配准效果达到或超过手动配准的效果,为进一步研究生猪多源图像异常特征提取奠定基础。%In the research of pigs health monitoring, pig contour segmentation and feature extraction using optical images are difficult because of pig manure and illumination in the rough environment of pig house. To improve the effect of pig contour segmentation and feature extraction, fusion of infrared thermal image and optical image with an IR thermal imager is suggested. Moreover, it may provide the helpful data source about pigs for the research of the relationship between abnormalities and the temperature of body surface. Evidently, automatic registration of IR and optical images is a crucial step towards constructing fusion. As to this kind of non-rigid multi-sensor images registration, apart from some similarity in overall structure, there is almost no commonality in some popular feature spaces between the pair of images, and it shows that feature-based approaches, such as scale invariant feature transformation (SIFT) may be unsuitable for this type of image registration. In this paper, an auto registration method of IR and

  3. Entropy-Based Block Processing for Satellite Image Registration

    Directory of Open Access Journals (Sweden)

    Ikhyun Lee

    2012-11-01

    Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.

  4. Registration of multitemporal aerial optical images using line features

    Science.gov (United States)

    Zhao, Chenyang; Goshtasby, A. Ardeshir

    2016-07-01

    Registration of multitemporal images is generally considered difficult because scene changes can occur between the times the images are obtained. Since the changes are mostly radiometric in nature, features are needed that are insensitive to radiometric differences between the images. Lines are geometric features that represent straight edges of rigid man-made structures. Because such structures rarely change over time, lines represent stable geometric features that can be used to register multitemporal remote sensing images. An algorithm to establish correspondence between lines in two images of a planar scene is introduced and formulas to relate the parameters of a homography transformation to the parameters of corresponding lines in images are derived. Results of the proposed image registration on various multitemporal images are presented and discussed.

  5. EEG-MRI co-registration and sensor labeling using a 3D laser scanner.

    Science.gov (United States)

    Koessler, L; Cecchin, T; Caspary, O; Benhadid, A; Vespignani, H; Maillard, L

    2011-03-01

    This paper deals with the co-registration of an MRI scan with EEG sensors. We set out to evaluate the effectiveness of a 3D handheld laser scanner, a device that is not widely used for co-registration, applying a semi-automatic procedure that also labels EEG sensors. The scanner acquired the sensors' positions and the face shape, and the scalp mesh was obtained from the MRI scan. A pre-alignment step, using the position of three fiducial landmarks, provided an initial value for co-registration, and the sensors were automatically labeled. Co-registration was then performed using an iterative closest point algorithm applied to the face shape. The procedure was conducted on five subjects with two scans of EEG sensors and one MRI scan each. The mean time for the digitization of the 64 sensors and three landmarks was 53 s. The average scanning time for the face shape was 2 min 6 s for an average number of 5,263 points. The mean residual error of the sensors co-registration was 2.11 mm. These results suggest that the laser scanner associated with an efficient co-registration and sensor labeling algorithm is sufficiently accurate, fast and user-friendly for longitudinal and retrospective brain sources imaging studies.

  6. FULLY AUTOMATIC IMAGE-BASED REGISTRATION OF UNORGANIZED TLS DATA

    Directory of Open Access Journals (Sweden)

    M. Weinmann

    2012-09-01

    Full Text Available The estimation of the transformation parameters between different point clouds is still a crucial task as it is usually followed by scene reconstruction, object detection or object recognition. Therefore, the estimates should be as accurate as possible. Recent developments show that it is feasible to utilize both the measured range information and the reflectance information sampled as image, as 2D imagery provides additional information. In this paper, an image-based registration approach for TLS data is presented which consists of two major steps. In the first step, the order of the scans is calculated by checking the similarity of the respective reflectance images via the total number of SIFT correspondences between them. Subsequently, in the second step, for each SIFT correspondence the respective SIFT features are filtered with respect to their reliability concerning the range information and projected to 3D space. Combining the 3D points with 2D observations on a virtual plane yields 3D-to-2D correspondences from which the coarse transformation parameters can be estimated via a RANSAC-based registration scheme including the EPnP algorithm. After this coarse registration, the 3D points are again checked for consistency by using constraints based on the 3D distance, and, finally, the remaining 3D points are used for an ICP-based fine registration. Thus, the proposed methodology provides a fast, reliable, accurate and fully automatic image-based approach for the registration of unorganized point clouds without the need of a priori information about the order of the scans, the presence of regular surfaces or human interaction.

  7. Improving multispectral satellite image compression using onboard subpixel registration

    Science.gov (United States)

    Albinet, Mathieu; Camarero, Roberto; Isnard, Maxime; Poulet, Christophe; Perret, Jokin

    2013-09-01

    Future CNES earth observation missions will have to deal with an ever increasing telemetry data rate due to improvements in resolution and addition of spectral bands. Current CNES image compressors implement a discrete wavelet transform (DWT) followed by a bit plane encoding (BPE) but only on a mono spectral basis and do not profit from the multispectral redundancy of the observed scenes. Recent CNES studies have proven a substantial gain on the achievable compression ratio, +20% to +40% on selected scenarios, by implementing a multispectral compression scheme based on a Karhunen Loeve transform (KLT) followed by the classical DWT+BPE. But such results can be achieved only on perfectly registered bands; a default of registration as low as 0.5 pixel ruins all the benefits of multispectral compression. In this work, we first study the possibility to implement a multi-bands subpixel onboard registration based on registration grids generated on-the-fly by the satellite attitude control system and simplified resampling and interpolation techniques. Indeed bands registration is usually performed on ground using sophisticated techniques too computationally intensive for onboard use. This fully quantized algorithm is tuned to meet acceptable registration performances within stringent image quality criteria, with the objective of onboard real-time processing. In a second part, we describe a FPGA implementation developed to evaluate the design complexity and, by extrapolation, the data rate achievable on a spacequalified ASIC. Finally, we present the impact of this approach on the processing chain not only onboard but also on ground and the impacts on the design of the instrument.

  8. Summer Camp July 2017 - Registration

    CERN Multimedia

    EVE et École

    2017-01-01

    The CERN Staff Association’s Summer Camp will be open for children from 4 to 6 years old during four weeks, from 3 to 28 July. Registration is offered on a weekly basis for 450 CHF, lunch included. This year, the various activities will revolve around the theme of the Four Elements. Registration opened on 20 March 2017 for children currently attending the EVE and School of the Association. It will be open from 3 April for children of CERN Members of Personnel, and starting from 24 April for all other children. The general conditions are available on the website of the EVE and School of CERN Staff Association: http://nurseryschool.web.cern.ch. For further questions, please contact us by email at Summer.Camp@cern.ch.

  9. Groupwise registration of aerial images

    OpenAIRE

    Arandjelovic, Ognjen; Pham, Duc-Son; Venkatesh, Svetha

    2015-01-01

    This paper addresses the task of time separated aerial image registration. The ability to solve this problem accurately and reliably is important for a variety of subsequent image understanding applications. The principal challenge lies in the extent and nature of transient appearance variation that a land area can undergo, such as that caused by the change in illumination conditions, seasonal variations, or the occlusion by non-persistent objects (people, cars). Our work introduces several n...

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

    Energy Technology Data Exchange (ETDEWEB)

    Chen Xin [ADSIP Research Centre, University of Central Lancashire, Preston (United Kingdom); Varley, Martin R [ADSIP Research Centre, University of Central Lancashire, Preston (United Kingdom); Shark, Lik-Kwan [ADSIP Research Centre, University of Central Lancashire, Preston (United Kingdom); Shentall, Glyn S [Rosemere Cancer Centre, Royal Preston Hospital, Preston (United Kingdom); Kirby, Mike C [Satellite Centres, Christie Hospital NHS Foundation Trust, Manchester (United Kingdom)

    2008-02-21

    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 deg, {+-} 0.29 deg. 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.

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

    Science.gov (United States)

    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.

  12. Automatic Marker-free Longitudinal Infrared Image Registration by Shape Context Based Matching and Competitive Winner-guided Optimal Corresponding

    Science.gov (United States)

    Lee, Chia-Yen; Wang, Hao-Jen; Lai, Jhih-Hao; Chang, Yeun-Chung; Huang, Chiun-Sheng

    2017-02-01

    Long-term comparisons of infrared image can facilitate the assessment of breast cancer tissue growth and early tumor detection, in which longitudinal infrared image registration is a necessary step. However, it is hard to keep markers attached on a body surface for weeks, and rather difficult to detect anatomic fiducial markers and match them in the infrared image during registration process. The proposed study, automatic longitudinal infrared registration algorithm, develops an automatic vascular intersection detection method and establishes feature descriptors by shape context to achieve robust matching, as well as to obtain control points for the deformation model. In addition, competitive winner-guided mechanism is developed for optimal corresponding. The proposed algorithm is evaluated in two ways. Results show that the algorithm can quickly lead to accurate image registration and that the effectiveness is superior to manual registration with a mean error being 0.91 pixels. These findings demonstrate that the proposed registration algorithm is reasonably accurate and provide a novel method of extracting a greater amount of useful data from infrared images.

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

    Science.gov (United States)

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

    2016-07-01

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

  14. An Advanced Rotation Invariant Descriptor for SAR Image Registration

    Directory of Open Access Journals (Sweden)

    Yuming Xiang

    2017-07-01

    Full Text Available The Scale-Invariant Feature Transform (SIFT algorithm and its many variants have been widely used in Synthetic Aperture Radar (SAR image registration. The SIFT-like algorithms maintain rotation invariance by assigning a dominant orientation for each keypoint, while the calculation of dominant orientation is not robust due to the effect of speckle noise in SAR imagery. In this paper, we propose an advanced local descriptor for SAR image registration to achieve rotation invariance without assigning a dominant orientation. Based on the improved intensity orders, we first divide a circular neighborhood into several sub-regions. Second, rotation-invariant ratio orientation histograms of each sub-region are proposed by accumulating the ratio values of different directions in a rotation-invariant coordinate system. The proposed descriptor is composed of the concatenation of the histograms of each sub-region. In order to increase the distinctiveness of the proposed descriptor, multiple image neighborhoods are aggregated. Experimental results on several satellite SAR images have shown an improvement in the matching performance over other state-of-the-art algorithms.

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

    Science.gov (United States)

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

    2016-02-15

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

  16. A Finger Vein Recognition Method Using Improved Oriented Filter and Elastic Registration

    Directory of Open Access Journals (Sweden)

    Ma Hui

    2013-07-01

    Full Text Available In order to reduce the influence of relative position deviation and angle deviation between minutia point sets caused by external factors when finger vein images are obtained, a finger vein recognition method using elastic registration is presented. The proposed algorithm is based on an improved neighborhood direction template and oriented filter template which facilitates the enhancement of the finger vein image while taking full account of image orientation. Elastic registration is then applied to matching of feature points within the predefined angle and radius. Applying the idea of elastic registration to existing finger vein recognition method removes the need for perfect matching between corresponding feature points and has shown to be an effective method for dealing with the problem of nonlinear distortion of images. Experimental results show that this algorithm not only overcomes the limitations of traditional point matching method, but also effectively improves the recognition performance of the system.

  17. Historical Image Registration and Land-Use Land-Cover Change Analysis

    Directory of Open Access Journals (Sweden)

    Fang-Ju Jao

    2014-12-01

    Full Text Available Historical aerial images are important to retain past ground surface information. The land-use land-cover change in the past can be identified using historical aerial images. Automatic historical image registration and stitching is essential because the historical image pose information was usually lost. In this study, the Scale Invariant Feature Transform (SIFT algorithm was used for feature extraction. Subsequently, the present study used the automatic affine transformation algorithm for historical image registration, based on SIFT features and control points. This study automatically determined image affine parameters and simultaneously transformed from an image coordinate system to a ground coordinate system. After historical aerial image registration, the land-use land-cover change was analyzed between two different years (1947 and 1975 at the Tseng Wen River estuary. Results show that sandbars and water zones were transformed into a large number of fish ponds between 1947 and 1975.

  18. Adaptive robust image registration approach based on adequately sampling polar transform and weighted angular projection function

    Science.gov (United States)

    Wei, Zhao; Tao, Feng; Jun, Wang

    2013-10-01

    An efficient, robust, and accurate approach is developed for image registration, which is especially suitable for large-scale change and arbitrary rotation. It is named the adequately sampling polar transform and weighted angular projection function (ASPT-WAPF). The proposed ASPT model overcomes the oversampling problem of conventional log-polar transform. Additionally, the WAPF presented as the feature descriptor is robust to the alteration in the fovea area of an image, and reduces the computational cost of the following registration process. The experimental results show two major advantages of the proposed method. First, it can register images with high accuracy even when the scale factor is up to 10 and the rotation angle is arbitrary. However, the maximum scaling estimated by the state-of-the-art algorithms is 6. Second, our algorithm is more robust to the size of the sampling region while not decreasing the accuracy of the registration.

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

    Directory of Open Access Journals (Sweden)

    Jianda Han

    2016-02-01

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

  20. On Statistical Analysis of Neuroimages with Imperfect Registration

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2017-02-01

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

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

    Science.gov (United States)

    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 viscoelastic diffeomorphic map between preoperative MR and intraoperative CT

  3. Historical Image Registration and Land-Use Land-Cover Change Analysis

    OpenAIRE

    Fang-Ju Jao; Hone-Jay Chu; Yi-Hsing Tseng

    2014-01-01

    Historical aerial images are important to retain past ground surface information. The land-use land-cover change in the past can be identified using historical aerial images. Automatic historical image registration and stitching is essential because the historical image pose information was usually lost. In this study, the Scale Invariant Feature Transform (SIFT) algorithm was used for feature extraction. Subsequently, the present study used the automatic affine transformation algorithm for h...

  4. Three-dimensional quantitative coronary angiography and the registration with intravascular ultrasound and optical coherence tomography

    NARCIS (Netherlands)

    Tu, Shengxian

    2012-01-01

    This thesis proposes several new algorithms including X-ray angiographic image enhancement, three-dimensional (3D) angiographic reconstruction, angiographic overlap prediction, and the co-registration of X-ray angiography with intracoronary imaging devices, such as intravascular ultrasound (IVUS) an

  5. Multimodal registration of the face for computer-aided maxillofacial surgery

    CERN Document Server

    Leloup, T; Payan, Y; Leloup, Thierry; Chabanas, Matthieu; Payan, Yohan

    2006-01-01

    This paper introduces a multimodal elastic registration algorithm applied to match a generic Finite Element model of the face to several patients morphologies. The method is automatic and appears to be accurate and robust. The computing time is compatible with clinical practice constraints.

  6. Effect of deformable registration on the dose calculated in radiation therapy planning CT scans of lung cancer patients

    Energy Technology Data Exchange (ETDEWEB)

    Cunliffe, Alexandra R.; Armato, Samuel G.; White, Bradley; Justusson, Julia [Department of Radiology, The University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637 (United States); Contee, Clay; Malik, Renuka; Al-Hallaq, Hania A., E-mail: hal-hallaq@radonc.uchicago.edu [Department of Radiation and Cellular Oncology, The University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637 (United States)

    2015-01-15

    Purpose: To characterize the effects of deformable image registration of serial computed tomography (CT) scans on the radiation dose calculated from a treatment planning scan. Methods: Eighteen patients who received curative doses (≥60 Gy, 2 Gy/fraction) of photon radiation therapy for lung cancer treatment were retrospectively identified. For each patient, a diagnostic-quality pretherapy (4–75 days) CT scan and a treatment planning scan with an associated dose map were collected. To establish correspondence between scan pairs, a researcher manually identified anatomically corresponding landmark point pairs between the two scans. Pretherapy scans then were coregistered with planning scans (and associated dose maps) using the demons deformable registration algorithm and two variants of the Fraunhofer MEVIS algorithm (“Fast” and “EMPIRE10”). Landmark points in each pretherapy scan were automatically mapped to the planning scan using the displacement vector field output from each of the three algorithms. The Euclidean distance between manually and automatically mapped landmark points (d{sub E}) and the absolute difference in planned dose (|ΔD|) were calculated. Using regression modeling, |ΔD| was modeled as a function of d{sub E}, dose (D), dose standard deviation (SD{sub dose}) in an eight-pixel neighborhood, and the registration algorithm used. Results: Over 1400 landmark point pairs were identified, with 58–93 (median: 84) points identified per patient. Average |ΔD| across patients was 3.5 Gy (range: 0.9–10.6 Gy). Registration accuracy was highest using the Fraunhofer MEVIS EMPIRE10 algorithm, with an average d{sub E} across patients of 5.2 mm (compared with >7 mm for the other two algorithms). Consequently, average |ΔD| was also lowest using the Fraunhofer MEVIS EMPIRE10 algorithm. |ΔD| increased significantly as a function of d{sub E} (0.42 Gy/mm), D (0.05 Gy/Gy), SD{sub dose} (1.4 Gy/Gy), and the algorithm used (≤1 Gy). Conclusions: An

  7. Hand-eye calibration with a new linear decomposition algorithm

    Institute of Scientific and Technical Information of China (English)

    Rong-hua LIANG; Jian-fei MAO

    2008-01-01

    To solve the homogeneous transformation equation of the form AX=XB in hand-eye calibration, where X represents an unknown transformation from the camera to the robot hand, and A and B denote the known movement transformations associated with the robot hand and the camera, respectively, this paper introduces a new linear decomposition algorithm which consists of singular value decomposition followed by the estimation of the optimal rotation matrix and the least squares equation to solve the rotation matrix of X. Without the requirements of traditional methods that A and B be rigid transformations with the same rotation angle, it enables the extension to non-rigid transformations for.4 and B. The details of our method are given, together with a short discussion of experimental results, showing that more precision and robustness can be achieved.

  8. Registration Day-Camp 2016

    CERN Multimedia

    Nursery School

    2016-01-01

    Reminder Registration for the CERN Staff Association Day-camp are open for children from 4 to 6 years old More information on the website: http://nurseryschool.web.cern.ch/. The day-camp is open to all children. An inscription per week is proposed, cost 480.-CHF/week, lunch included The camp will be open weeks 27, 28, 29 and 30, from 8:30 am to 5:30 pm. For further questions, thanks you for contacting us by email at Summer.Camp@cern.ch.

  9. Control over structure-specific flexibility improves anatomical accuracy for point-based deformable registration in bladder cancer radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Wognum, S.; Chai, X.; Hulshof, M. C. C. M.; Bel, A. [Department of Radiotherapy, Academic Medical Center, Meiberdreef 9, 1105 AZ Amsterdam (Netherlands); Bondar, L.; Zolnay, A. G.; Hoogeman, M. S. [Department of Radiation Oncology, Daniel den Hoed Cancer Center, Erasmus Medical Center, Groene Hilledijk 301, 3075 EA Rotterdam (Netherlands)

    2013-02-15

    Purpose: Future developments in image guided adaptive radiotherapy (IGART) for bladder cancer require accurate deformable image registration techniques for the precise assessment of tumor and bladder motion and deformation that occur as a result of large bladder volume changes during the course of radiotherapy treatment. The aim was to employ an extended version of a point-based deformable registration algorithm that allows control over tissue-specific flexibility in combination with the authors' unique patient dataset, in order to overcome two major challenges of bladder cancer registration, i.e., the difficulty in accounting for the difference in flexibility between the bladder wall and tumor and the lack of visible anatomical landmarks for validation. Methods: The registration algorithm used in the current study is an extension of the symmetric-thin plate splines-robust point matching (S-TPS-RPM) algorithm, a symmetric feature-based registration method. The S-TPS-RPM algorithm has been previously extended to allow control over the degree of flexibility of different structures via a weight parameter. The extended weighted S-TPS-RPM algorithm was tested and validated on CT data (planning- and four to five repeat-CTs) of five urinary bladder cancer patients who received lipiodol injections before radiotherapy. The performance of the weighted S-TPS-RPM method, applied to bladder and tumor structures simultaneously, was compared with a previous version of the S-TPS-RPM algorithm applied to bladder wall structure alone and with a simultaneous nonweighted S-TPS-RPM registration of the bladder and tumor structures. Performance was assessed in terms of anatomical and geometric accuracy. The anatomical accuracy was calculated as the residual distance error (RDE) of the lipiodol markers and the geometric accuracy was determined by the surface distance, surface coverage, and inverse consistency errors. Optimal parameter values for the flexibility and bladder weight

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

    Science.gov (United States)

    Molina, Edgardo; Zhu, Zhigang

    2014-05-01

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

  11. Automatic Image Registration Technique of Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    M. Wahed

    2013-03-01

    Full Text Available Image registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources. Automatic registration of remote-sensing images is a difficult task as it must deal with the intensity changes and variation of scale, rotation and illumination of the images. This paper proposes image registration technique of multi-view, multi- temporal and multi-spectral remote sensing images. Firstly, a preprocessing step is performed by applying median filtering to enhance the images. Secondly, the Steerable Pyramid Transform is adopted to produce multi-resolution levels of reference and sensed images; then, the Scale Invariant Feature Transform (SIFT is utilized for extracting feature points that can deal with the large variations of scale, rotation and illumination between images .Thirdly, matching the features points by using the Euclidian distance ratio; then removing the false matching pairs using the RANdom SAmple Consensus (RANSAC algorithm. Finally, the mapping function is obtained by the affine transformation. Quantitative comparisons of our technique with the related techniques show a significant improvement in the presence of large scale, rotation changes, and the intensity changes. The effectiveness of the proposed technique is demonstrated by the experimental results.

  12. Bidirectional scale-invariant feature transform feature matching algorithms based on priority k-d tree search

    National Research Council Canada - National Science Library

    Liu, XiangShao; Zhou, Shangbo; Li, Hua; Li, Kun

    2016-01-01

    In this article, a bidirectional feature matching algorithm and two extended algorithms based on the priority k-d tree search are presented for the image registration using scale-invariant feature transform features...

  13. 75 FR 37790 - Lauryl Sulfate Salts; Antimicrobial Registration Review Final Work Plan and Proposed Registration...

    Science.gov (United States)

    2010-06-30

    ... AGENCY Lauryl Sulfate Salts; Antimicrobial Registration Review Final Work Plan and Proposed Registration.... SUMMARY: This notice announces the availability of EPA's final work plan and proposed registration review... with the posting of a summary document, containing a preliminary work plan, for public comment....

  14. 14 CFR 47.16 - Temporary registration numbers.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Temporary registration numbers. 47.16... AIRCRAFT REGISTRATION General § 47.16 Temporary registration numbers. (a) Temporary registration numbers... for as many temporary registration numbers as are necessary for his business. The application must...

  15. The role of regularization in deformable image registration for head and neck adaptive radiotherapy.

    Science.gov (United States)

    Ciardo, D; Peroni, M; Riboldi, M; Alterio, D; Baroni, G; Orecchia, R

    2013-08-01

    Deformable image registration provides a robust mathematical framework to quantify morphological changes that occur along the course of external beam radiotherapy treatments. As clinical reliability of deformable image registration is not always guaranteed, algorithm regularization is commonly introduced to prevent sharp discontinuities in the quantified deformation and achieve anatomically consistent results. In this work we analyzed the influence of regularization on two different registration methods, i.e. B-Splines and Log Domain Diffeomorphic Demons, implemented in an open-source platform. We retrospectively analyzed the simulation computed tomography (CTsim) and the corresponding re-planning computed tomography (CTrepl) scans in 30 head and neck cancer patients. First, we investigated the influence of regularization levels on hounsfield units (HU) information in 10 test patients for each considered method. Then, we compared the registration results of the open-source implementation at selected best performing regularization levels with a clinical commercial software on the remaining 20 patients in terms of mean volume overlap, surface and center of mass distances between manual outlines and propagated structures. The regularized B-Splines method was not statistically different from the commercial software. The tuning of the regularization parameters allowed open-source algorithms to achieve better results in deformable image registration for head and neck patients, with the additional benefit of a framework where regularization can be tuned on a patient specific basis.

  16. Patient-specific biomechanical model as whole-body CT image registration tool.

    Science.gov (United States)

    Li, Mao; Miller, Karol; Joldes, Grand Roman; Doyle, Barry; Garlapati, Revanth Reddy; Kikinis, Ron; Wittek, Adam

    2015-05-01

    Whole-body computed tomography (CT) image registration is important for cancer diagnosis, therapy planning and treatment. Such registration requires accounting for large differences between source and target images caused by deformations of soft organs/tissues and articulated motion of skeletal structures. The registration algorithms relying solely on image processing methods exhibit deficiencies in accounting for such deformations and motion. We propose to predict the deformations and movements of body organs/tissues and skeletal structures for whole-body CT image registration using patient-specific non-linear biomechanical modelling. Unlike the conventional biomechanical modelling, our approach for building the biomechanical models does not require time-consuming segmentation of CT scans to divide the whole body into non-overlapping constituents with different material properties. Instead, a Fuzzy C-Means (FCM) algorithm is used for tissue classification to assign the constitutive properties automatically at integration points of the computation grid. We use only very simple segmentation of the spine when determining vertebrae displacements to define loading for biomechanical models. We demonstrate the feasibility and accuracy of our approach on CT images of seven patients suffering from cancer and aortic disease. The results confirm that accurate whole-body CT image registration can be achieved using a patient-specific non-linear biomechanical model constructed without time-consuming segmentation of the whole-body images.

  17. A two-step framework for the registration of HE stained and FTIR images

    Science.gov (United States)

    Peñaranda, Francisco; Naranjo, Valery; Verdú, Rafaél.; Lloyd, Gavin R.; Nallala, Jayakrupakar; Stone, Nick

    2016-03-01

    FTIR spectroscopy is an emerging technology with high potential for cancer diagnosis but with particular physical phenomena that require special processing. Little work has been done in the field with the aim of registering hyperspectral Fourier-Transform Infrared (FTIR) spectroscopic images and Hematoxilin and Eosin (HE) stained histological images of contiguous slices of tissue. This registration is necessary to transfer the location of relevant structures that the pathologist may identify in the gold standard HE images. A two-step registration framework is presented where a representative gray image extracted from the FTIR hypercube is used as an input. This representative image, which must have a spatial contrast as similar as possible to a gray image obtained from the HE image, is calculated through the spectrum variation in the fingerprint region. In the first step of the registration algorithm a similarity transformation is estimated from interest points, which are automatically detected by the popular SURF algorithm. In the second stage, a variational registration framework defined in the frequency domain compensates for local anatomical variations between both images. After a proper tuning of some parameters the proposed registration framework works in an automated way. The method was tested on 7 samples of colon tissue in different stages of cancer. Very promising qualitative and quantitative results were obtained (a mean correlation ratio of 92.16% with a standard deviation of 3.10%).

  18. Efficient acceleration of mutual information computation for nonrigid registration using CUDA.

    Science.gov (United States)

    Ikeda, Kei; Ino, Fumihiko; Hagihara, Kenichi

    2014-05-01

    In this paper, we propose an efficient acceleration method for the nonrigid registration of multimodal images that uses a graphics processing unit. The key contribution of our method is efficient utilization of on-chip memory for both normalized mutual information (NMI) computation and hierarchical B-spline deformation, which compose a well-known registration algorithm. We implement this registration algorithm as a compute unified device architecture program with an efficient parallel scheme and several optimization techniques such as hierarchical data organization, data reuse, and multiresolution representation. We experimentally evaluate our method with four clinical datasets consisting of up to 512 × 512 × 296 voxels. We find that exploitation of on-chip memory achieves a 12-fold increase in speed over an off-chip memory version and, therefore, it increases the efficiency of parallel execution from 4% to 46%. We also find that our method running on a GeForce GTX 580 card is approximately 14 times faster than a fully optimized CPU-based implementation running on four cores. Some multimodal registration results are also provided to understand the limitation of our method. We believe that our highly efficient method, which completes an alignment task within a few tens of seconds, will be useful to realize rapid nonrigid registration.

  19. An accelerated image matching technique for UAV orthoimage registration

    Science.gov (United States)

    Tsai, Chung-Hsien; Lin, Yu-Ching

    2017-06-01

    Using an Unmanned Aerial Vehicle (UAV) drone with an attached non-metric camera has become a popular low-cost approach for collecting geospatial data. A well-georeferenced orthoimage is a fundamental product for geomatics professionals. To achieve high positioning accuracy of orthoimages, precise sensor position and orientation data, or a number of ground control points (GCPs), are often required. Alternatively, image registration is a solution for improving the accuracy of a UAV orthoimage, as long as a historical reference image is available. This study proposes a registration scheme, including an Accelerated Binary Robust Invariant Scalable Keypoints (ABRISK) algorithm and spatial analysis of corresponding control points for image registration. To determine a match between two input images, feature descriptors from one image are compared with those from another image. A ;Sorting Ring; is used to filter out uncorrected feature pairs as early as possible in the stage of matching feature points, to speed up the matching process. The results demonstrate that the proposed ABRISK approach outperforms the vector-based Scale Invariant Feature Transform (SIFT) approach where radiometric variations exist. ABRISK is 19.2 times and 312 times faster than SIFT for image sizes of 1000 × 1000 pixels and 4000 × 4000 pixels, respectively. ABRISK is 4.7 times faster than Binary Robust Invariant Scalable Keypoints (BRISK). Furthermore, the positional accuracy of the UAV orthoimage after applying the proposed image registration scheme is improved by an average of root mean square error (RMSE) of 2.58 m for six test orthoimages whose spatial resolutions vary from 6.7 cm to 10.7 cm.

  20. Advanced methods for image registration applied to JET videos

    Energy Technology Data Exchange (ETDEWEB)

    Craciunescu, Teddy, E-mail: teddy.craciunescu@jet.uk [EURATOM-MEdC Association, NILPRP, Bucharest (Romania); Murari, Andrea [Consorzio RFX, Associazione EURATOM-ENEA per la Fusione, Padova (Italy); Gelfusa, Michela [Associazione EURATOM-ENEA – University of Rome “Tor Vergata”, Roma (Italy); Tiseanu, Ion; Zoita, Vasile [EURATOM-MEdC Association, NILPRP, Bucharest (Romania); Arnoux, Gilles [EURATOM/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon (United Kingdom)

    2015-10-15

    Graphical abstract: - Highlights: • Development of an image registration method for JET IR and fast visible cameras. • Method based on SIFT descriptors and coherent point drift points set registration technique. • Method able to deal with extremely noisy images and very low luminosity images. • Computation time compatible with the inter-shot analysis. - Abstract: The last years have witnessed a significant increase in the use of digital cameras on JET. They are routinely applied for imaging in the IR and visible spectral regions. One of the main technical difficulties in interpreting the data of camera based diagnostics is the presence of movements of the field of view. Small movements occur due to machine shaking during normal pulses while large ones may arise during disruptions. Some cameras show a correlation of image movement with change of magnetic field strength. For deriving unaltered information from the videos and for allowing correct interpretation an image registration method, based on highly distinctive scale invariant feature transform (SIFT) descriptors and on the coherent point drift (CPD) points set registration technique, has been developed. The algorithm incorporates a complex procedure for rejecting outliers. The method has been applied for vibrations correction to videos collected by the JET wide angle infrared camera and for the correction of spurious rotations in the case of the JET fast visible camera (which is equipped with an image intensifier). The method has proved to be able to deal with the images provided by this camera frequently characterized by low contrast and a high level of blurring and noise.

  1. Direct Image-To Registration Using Mobile Sensor Data

    Science.gov (United States)

    Kehl, C.; Buckley, S. J.; Gawthorpe, R. L.; Viola, I.; Howell, J. A.

    2016-06-01

    Adding supplementary texture and 2D image-based annotations to 3D surface models is a useful next step for domain specialists to make use of photorealistic products of laser scanning and photogrammetry. This requires a registration between the new camera imagery and the model geometry to be solved, which can be a time-consuming task without appropriate automation. The increasing availability of photorealistic models, coupled with the proliferation of mobile devices, gives users the possibility to complement their models in real time. Modern mobile devices deliver digital photographs of increasing quality, as well as on-board sensor data, which can be used as input for practical and automatic camera registration procedures. Their familiar user interface also improves manual registration procedures. This paper introduces a fully automatic pose estimation method using the on-board sensor data for initial exterior orientation, and feature matching between an acquired photograph and a synthesised rendering of the orientated 3D scene as input for fine alignment. The paper also introduces a user-friendly manual camera registration- and pose estimation interface for mobile devices, based on existing surface geometry and numerical optimisation methods. The article further assesses the automatic algorithm's accuracy compared to traditional methods, and the impact of computational- and environmental parameters. Experiments using urban and geological case studies show a significant sensitivity of the automatic procedure to the quality of the initial mobile sensor values. Changing natural lighting conditions remain a challenge for automatic pose estimation techniques, although progress is presented here. Finally, the automatically-registered mobile images are used as the basis for adding user annotations to the input textured model.

  2. Slice-to-volume registration and its potential application to interventional MRI-guided radio-frequency thermal ablation of prostate cancer.

    Science.gov (United States)

    Fei, Baowei; Duerk, Jeffrey L; Boll, Daniel T; Lewin, Jonathan S; Wilson, David L

    2003-04-01

    In this study, we registered live-time interventional magnetic resonance imaging (iMRI) slices with a previously obtained high-resolution MRI volume that in turn can be registered with a variety of functional images, e.g., PET, SPECT, for tumor targeting. We created and evaluated a slice-to-volume (SV) registration algorithm with special features for its potential use in iMRI-guided radio-frequency (RF) thermal ablation of prostate cancer. The algorithm features included a multiresolution approach, two similarity measures, and automatic restarting to avoid local minima. Imaging experiments were performed on volunteers using a conventional 1.5-T MR scanner and a clinical 0.2-T C-arm iMRI system under realistic conditions. Both high-resolution MR volumes and actual iMRI image slices were acquired from the same volunteers. Actual and simulated iMRI images were used to test the dependence of SV registration on image noise, receive coil inhomogeneity, and RF needle artifacts. To quantitatively assess registration, we calculated the mean voxel displacement over a volume of interest between SV registration and volume-to-volume registration, which was previously shown to be quite accurate. More than 800 registration experiments were performed. For transverse image slices covering the prostate, the SV registration algorithm was 100% successful with an error of bladder filling. These preliminary experiments indicate that MR SV registration is sufficiently accurate to aid image-guided therapy.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)