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Sample records for marker-based registration algorithm

  1. 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.

  2. Fast and accurate marker-based projective registration method for uncalibrated transmission electron microscope tilt series.

    Science.gov (United States)

    Lee, Ho; Lee, Jeongjin; Shin, Yeong Gil; Lee, Rena; Xing, Lei

    2010-06-21

    This paper presents a fast and accurate marker-based automatic registration technique for aligning uncalibrated projections taken from a transmission electron microscope (TEM) with different tilt angles and orientations. Most of the existing TEM image alignment methods estimate the similarity between images using the projection model with least-squares metric and guess alignment parameters by computationally expensive nonlinear optimization schemes. Approaches based on the least-squares metric which is sensitive to outliers may cause misalignment since automatic tracking methods, though reliable, can produce a few incorrect trajectories due to a large number of marker points. To decrease the influence of outliers, we propose a robust similarity measure using the projection model with a Gaussian weighting function. This function is very effective in suppressing outliers that are far from correct trajectories and thus provides a more robust metric. In addition, we suggest a fast search strategy based on the non-gradient Powell's multidimensional optimization scheme to speed up optimization as only meaningful parameters are considered during iterative projection model estimation. Experimental results show that our method brings more accurate alignment with less computational cost compared to conventional automatic alignment methods.

  3. 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.

  4. Laser-induced damage tests based on a marker-based watershed algorithm with gray control

    Institute of Scientific and Technical Information of China (English)

    Yajing; Guo; Shunxing; Tang; Xiuqing; Jiang; Yujie; Peng; Baoqiang; Zhu; Zunqi; Lin

    2014-01-01

    An effective damage test method based on a marker-based watershed algorithm with gray control(MWGC) is proposed to study the properties of damage induced by near-field laser irradiation for large-aperture laser facilities.Damage tests were performed on fused silica samples and information on the size of damage sites was obtained by this new algorithm,which can effectively suppress the issue of over-segmentation of images resulting from non-uniform illumination in darkfield imaging.Experimental analysis and results show that the lateral damage growth on the exit surface is exponential,and the number of damage sites decreases sharply with damage site size in the damage site distribution statistics.The average damage growth coefficients fitted according to the experimental results for Corning-7980 and Heraeus-Suprasil312 samples at 351 nm are 1.10 ± 0.31 and 0.60 ± 0.09,respectively.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

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

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    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.

  18. A modified iterative closest point algorithm for shape registration

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    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.

  19. 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.

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

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    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.

  1. 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.

  2. [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.

  3. 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.

  4. 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.

  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. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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...

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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.

  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 displacement...

  11. 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...

  12. 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.

  13. 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

  14. 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.

  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. 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.

  18. 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.

  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. 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.

  3. 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.

  4. 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...

  5. 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...

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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

  16. 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...

  17. 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.

  18. 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...

  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. 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

  5. 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

  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.

    2015-03-01

    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

  7. 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.

  8. 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…

  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. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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 .

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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。

  8. 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.

  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. 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.

  11. 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.

  12. 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.

  13. 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....

  14. 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

  15. 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

  16. 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

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

    Science.gov (United States)

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

    2006-12-01

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

  18. 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

  19. 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.

  20. 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....

  1. Anatomy-based registration of CT-scan and intraoperative X-ray images for guiding a surgical robot.

    Science.gov (United States)

    Guéziec, A; Kazanzides, P; Williamson, B; Taylor, R H

    1998-10-01

    We describe new methods for rigid registration of a preoperative computed tomography (CT)-scan image to a set of intraoperative X-ray fluoroscopic images, for guiding a surgical robot to its trajectory planned from CT. Our goal is to perform the registration, i.e., compute a rotation and translation of one data set with respect to the other to within a prescribed accuracy, based upon bony anatomy only, without external fiducial markers. With respect to previous approaches, the following aspects are new: 1) we correct the geometric distortion in fluoroscopic images and calibrate them directly with respect to the robot by affixing to it a new calibration device designed as a radiolucent rod with embedded metallic markers, and by moving the device along two planes, while radiographs are being acquired at regular intervals; 2) the registration uses an algorithm for computing the best transformation between a set of lines in three space, the (intraoperative) X-ray paths, and a set of points on the surface of the bone (imaged preoperatively), in a statistically robust fashion, using the Cayley parameterization of a rotation; and 3) to find corresponding sets of points to the X-ray paths on the surfaces, our new approach consists of extracting the surface apparent contours for a given viewpoint, as a set of closed three-dimensional nonplanar curves, before registering the apparent contours to X-ray paths. Aside from algorithms, there are a number of major technical difficulties associated with engineering a clinically viable system using anatomy and image-based registration. To detect and solve them, we have so far conducted two experiments with the surgical robot in an operating room (OR), using CT and fluoroscopic image data of a cadaver bone, and attempting to faithfully simulate clinical conditions. Such experiments indicate that intraoperative X-ray-based registration is a promising alternative to marker-based registration for clinical use with our proposed method.

  2. 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...

  3. 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

  4. [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.

  5. 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.

  6. 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。

  7. 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.

  8. 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.

  9. 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.

  10. 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...

  11. The Application of Marker Based Segmentation for Surface Texture Characterization

    Directory of Open Access Journals (Sweden)

    Che Pin Nuraini binti

    2016-01-01

    Full Text Available Structured surfaces have been increasingly used in industry for a variety of applications, including improving the tribological properties of the surfaces. Surface metrology plays an important role in this discipline since with the help of surface metrology technology, surface texture can be measured, visualize and quantified. Traditional surface texture parameters, such as roughness and waviness, cannot be related to the function for structured surfaces due to the less statistical description and little information. Therefore, a new approaches based on characterizing the structured surface is introduces where this paper focus on type of edges grain surface. To identify features, it is a must to detect the location of the edges and segmented the features based on the detected edges. Hence characterization of surface texture segmentation based on the edges detection is developing using Marker Based segmentation and it is prove that this method is possible to be used in order to characterize the structured surface.

  12. Fiducial Marker Based on Projective Invariant for Augmented Reality

    Institute of Scientific and Technical Information of China (English)

    Yu Li; Yong-Tian Wang; Yue Liu

    2007-01-01

    Fiducial marker based Augmented Reality has many applications. So far the inner pattern of the fiducial marker is always used to encode the markers. Thus a large portion of the fiduciat marker image is used for encoding instead of providing corresponding feature points for pose accuracy. This paper presents a novel method which utilizes directly the projective invariant contained in the positional relation of the corresponding feature points to encode the marker. The proposed method does not require the region of pattern image for encoding any more and can provide more corresponding feature points so that higher pose accuracy can be achieved easily. Many related approaches suchas cumulative distribution function, reprojection verification and robust process are proposed to overcome the problem of sensibility of the projective invariant. Experimental results show that the proposed fiducial marker system is reliable and robust, and can provide higher pose accuracy than that achieved by existing fiducial marker systems.

  13. 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.

  14. 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.

  15. 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。

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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).

  1. 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...

  2. 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.

  3. 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.

  4. 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.

  5. Marker-based quantification of interfractional tumor position variation and the use of markers for setup verification in radiation therapy for esophageal cancer.

    Science.gov (United States)

    Jin, Peng; van der Horst, Astrid; de Jong, Rianne; van Hooft, Jeanin E; Kamphuis, Martijn; van Wieringen, Niek; Machiels, Melanie; Bel, Arjan; Hulshof, Maarten C C M; Alderliesten, Tanja

    2015-12-01

    The aim of this study was to quantify interfractional esophageal tumor position variation using markers and investigate the use of markers for setup verification. Sixty-five markers placed in the tumor volumes of 24 esophageal cancer patients were identified in computed tomography (CT) and follow-up cone-beam CT. For each patient we calculated pairwise distances between markers over time to evaluate geometric tumor volume variation. We then quantified marker displacements relative to bony anatomy and estimated the variation of systematic (Σ) and random errors (σ). During bony anatomy-based setup verification, we visually inspected whether the markers were inside the planning target volume (PTV) and attempted marker-based registration. Minor time trends with substantial fluctuations in pairwise distances implied tissue deformation. Overall, Σ(σ) in the left-right/cranial-caudal/anterior-posterior direction was 2.9(2.4)/4.1(2.4)/2.2(1.8) mm; for the proximal stomach, it was 5.4(4.3)/4.9(3.2)/1.9(2.4) mm. After bony anatomy-based setup correction, all markers were inside the PTV. However, due to large tissue deformation, marker-based registration was not feasible. Generally, the interfractional position variation of esophageal tumors is more pronounced in the cranial-caudal direction and in the proximal stomach. Currently, marker-based setup verification is not feasible for clinical routine use, but markers can facilitate the setup verification by inspecting whether the PTV covers the tumor volume adequately. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  6. 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...

  7. Marker-Based Human Motion Capture in Multiview Sequences

    Directory of Open Access Journals (Sweden)

    Canton-Ferrer Cristian

    2010-01-01

    Full Text Available This paper presents a low-cost real-time alternative to available commercial human motion capture systems. First, a set of distinguishable markers are placed on several human body landmarks, and the scene is captured by a number of calibrated and synchronized cameras. In order to establish a physical relation among markers, a human body model is defined. Markers are detected on all camera views and delivered as the input of an annealed particle filter scheme where every particle encodes an instance of the pose of the body model to be estimated. Likelihood between particles and input data is performed through the robust generalized symmetric epipolar distance and kinematic constrains are enforced in the propagation step towards avoiding impossible poses. Tests over the HumanEva annotated data set yield quantitative results showing the effectiveness of the proposed algorithm. Results over sequences involving fast and complex motions are also presented.

  8. 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.

  9. 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

  10. 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%.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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....

  19. 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....

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. 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.

  8. 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...

  9. 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.

  10. 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...

  11. 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.

  12. 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...

  13. 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...

  14. 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...

  15. 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

  16. A Real-Time Marker-Based Visual Sensor Based on a FPGA and a Soft Core Processor

    Directory of Open Access Journals (Sweden)

    Hilal Tayara

    2016-12-01

    Full Text Available This paper introduces a real-time marker-based visual sensor architecture for mobile robot localization and navigation. A hardware acceleration architecture for post video processing system was implemented on a field-programmable gate array (FPGA. The pose calculation algorithm was implemented in a System on Chip (SoC with an Altera Nios II soft-core processor. For every frame, single pass image segmentation and Feature Accelerated Segment Test (FAST corner detection were used for extracting the predefined markers with known geometries in FPGA. Coplanar PosIT algorithm was implemented on the Nios II soft-core processor supplied with floating point hardware for accelerating floating point operations. Trigonometric functions have been approximated using Taylor series and cubic approximation using Lagrange polynomials. Inverse square root method has been implemented for approximating square root computations. Real time results have been achieved and pixel streams have been processed on the fly without any need to buffer the input frame for further implementation.

  17. A Real-Time Marker-Based Visual Sensor Based on a FPGA and a Soft Core Processor.

    Science.gov (United States)

    Tayara, Hilal; Ham, Woonchul; Chong, Kil To

    2016-12-15

    This paper introduces a real-time marker-based visual sensor architecture for mobile robot localization and navigation. A hardware acceleration architecture for post video processing system was implemented on a field-programmable gate array (FPGA). The pose calculation algorithm was implemented in a System on Chip (SoC) with an Altera Nios II soft-core processor. For every frame, single pass image segmentation and Feature Accelerated Segment Test (FAST) corner detection were used for extracting the predefined markers with known geometries in FPGA. Coplanar PosIT algorithm was implemented on the Nios II soft-core processor supplied with floating point hardware for accelerating floating point operations. Trigonometric functions have been approximated using Taylor series and cubic approximation using Lagrange polynomials. Inverse square root method has been implemented for approximating square root computations. Real time results have been achieved and pixel streams have been processed on the fly without any need to buffer the input frame for further implementation.

  18. 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....

  19. Compatibility of pedigree-based and marker-based relationships for single-step genomic prediction

    DEFF Research Database (Denmark)

    Christensen, Ole Fredslund

    2012-01-01

    Single-step methods for genomic prediction have recently become popular because they are conceptually simple and in practice such a method can completely replace a pedigree-based method for routine genetic evaluation. An issue with single-step methods is compatibility between the marker-based rel......Single-step methods for genomic prediction have recently become popular because they are conceptually simple and in practice such a method can completely replace a pedigree-based method for routine genetic evaluation. An issue with single-step methods is compatibility between the marker......-based relationship matrix and the pedigree-based relationship matrix. The compatibility issue involves which allele frequencies to use in the marker-based relationship matrix, and also that adjustments of this matrix to the pedigree-based relationship matrix are needed. In addition, it has been overlooked...... in the base population. Here, two ideas are explored. The first idea is to instead adjust the pedigree-based relationship matrix to be compatible to the marker-based relationship matrix, whereas the second idea is to include the likelihood for the observed markers. A single-step method is used where...

  20. 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.

  1. 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.

  2. 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%.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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...

  9. 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

  10. 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.

  11. 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.

  12. 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).

  13. 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.

  14. 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.

  15. 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.

  16. Ultraspectral sounder data compression using a novel marker-based error-resilient arithmetic coder

    Science.gov (United States)

    Huang, Bormin; Sriraja, Y.; Wei, Shih-Chieh

    2006-08-01

    Entropy coding techniques aim to achieve the entropy of the source data by assigning variable-length codewords to symbols with the code lengths linked to the corresponding symbol probabilities. Entropy coders (e.g. Huffman coding, arithmetic coding), in one form or the other, are commonly used as the last stage in various compression schemes. While these variable-length coders provide better compression than fixed-length coders, they are vulnerable to transmission errors. Even a single bit error in the transmission process can cause havoc in the subsequent decoded stream. To cope with it, this research proposes a marker-based sentinel mechanism in entropy coding for error detection and recovery. We use arithmetic coding as an example to demonstrate this error-resilient technique for entropy coding. Experimental results on ultraspectral sounder data indicate that the marker-based error-resilient arithmetic coder provides remarkable robustness to correct transmission errors without significantly compromising the compression gains.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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...

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Dynamic stability margin using a marker based system and Tekscan: a comparison of four gait conditions.

    Science.gov (United States)

    Lugade, Vipul; Kaufman, Kenton

    2014-01-01

    Stability during gait is maintained through control of the center of mass (CoM) position and velocity in relation to the base of support (BoS). The dynamic stability margin, or the interaction of the extrapolated center of mass with the closest boundary of the BoS, can reveal possible control errors during gait. The purpose of this study was to investigate a marker based method for defining the BoS, and compare the dynamic stability margin throughout gait in comparison to a BoS defined from foot pressure sensors. The root mean squared difference between these two methodologies ranged from 0.9 cm to 3.5 cm, when walking under four conditions: plantigrade, equinus, everted, and inverted. As the stability margin approaches -35 cm prior to contralateral heel strike, there was approximately 90% agreement between the two systems at this time point. Underestimation of the marker based dynamic stability margin or overestimation of the pressure based dynamic stability margin was due to inaccuracies in defining the medial boundary of the BoS. Overall, care must be taken to ensure similar definitions of the BoS are utilized when comparing the dynamic stability margin between participants and gait conditions.

  5. 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...

  6. 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.

  7. 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...

  8. 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

  9. 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

  10. 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.

  11. Ghost marker detection and elimination in marker-based optical tracking systems for real-time tracking in stereotactic body radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Yan, Guanghua, E-mail: yan@ufl.edu; Li, Jonathan; Huang, Yin; Mittauer, Kathryn; Lu, Bo; Liu, Chihray [Department of Radiation Oncology, University of Florida, Gainesville, Florida 32610 (United States)

    2014-10-15

    Purpose: To propose a simple model to explain the origin of ghost markers in marker-based optical tracking systems (OTS) and to develop retrospective strategies to detect and eliminate ghost markers. Methods: In marker-based OTS, ghost markers are virtual markers created due to the cross-talk between the two camera sensors, which can lead to system execution failure or inaccuracy in patient tracking. As a result, the users have to limit the number of markers and avoid certain marker configurations to reduce the chances of ghost markers. In this work, the authors propose retrospective strategies to detect and eliminate ghost markers. The two camera sensors were treated as mathematical points in space. The authors identified the coplanar within limit (CWL) condition as the necessary condition for ghost marker occurrence. A simple ghost marker detection method was proposed based on the model. Ghost marker elimination was achieved through pattern matching: a ghost marker-free reference set was matched with the optical marker set observed by the OTS; unmatched optical markers were eliminated as either ghost markers or misplaced markers. The pattern matching problem was formulated as a constraint satisfaction problem (using pairwise distances as constraints) and solved with an iterative backtracking algorithm. Wildcard markers were introduced to address missing or misplaced markers. An experiment was designed to measure the sensor positions and the limit for the CWL condition. The ghost marker detection and elimination algorithms were verified with samples collected from a five-marker jig and a nine-marker anthropomorphic phantom, rotated with the treatment couch from −60° to +60°. The accuracy of the pattern matching algorithm was further validated with marker patterns from 40 patients who underwent stereotactic body radiotherapy (SBRT). For this purpose, a synthetic optical marker pattern was created for each patient by introducing ghost markers, marker position

  12. 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

  13. [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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  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. 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.

  20. 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…

  1. 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,...

  2. Compatibility of pedigree-based and marker-based relationship matrices for single-step genetic evaluation

    Directory of Open Access Journals (Sweden)

    Christensen Ole F

    2012-12-01

    Full Text Available Abstract Background Single-step methods provide a coherent and conceptually simple approach to incorporate genomic information into genetic evaluations. An issue with single-step methods is compatibility between the marker-based relationship matrix for genotyped animals and the pedigree-based relationship matrix. Therefore, it is necessary to adjust the marker-based relationship matrix to the pedigree-based relationship matrix. Moreover, with data from routine evaluations, this adjustment should in principle be based on both observed marker genotypes and observed phenotypes, but until now this has been overlooked. In this paper, I propose a new method to address this issue by 1 adjusting the pedigree-based relationship matrix to be compatible with the marker-based relationship matrix instead of the reverse and 2 extending the single-step genetic evaluation using a joint likelihood of observed phenotypes and observed marker genotypes. The performance of this method is then evaluated using two simulated datasets. Results The method derived here is a single-step method in which the marker-based relationship matrix is constructed assuming all allele frequencies equal to 0.5 and the pedigree-based relationship matrix is constructed using the unusual assumption that animals in the base population are related and inbred with a relationship coefficient γ and an inbreeding coefficient γ / 2. Taken together, this γ parameter and a parameter that scales the marker-based relationship matrix can handle the issue of compatibility between marker-based and pedigree-based relationship matrices. The full log-likelihood function used for parameter inference contains two terms. The first term is the REML-log-likelihood for the phenotypes conditional on the observed marker genotypes, whereas the second term is the log-likelihood for the observed marker genotypes. Analyses of the two simulated datasets with this new method showed that 1 the parameters involved

  3. Compatibility of pedigree-based and marker-based relationship matrices for single-step genetic evaluation.

    Science.gov (United States)

    Christensen, Ole F

    2012-12-03

    Single-step methods provide a coherent and conceptually simple approach to incorporate genomic information into genetic evaluations. An issue with single-step methods is compatibility between the marker-based relationship matrix for genotyped animals and the pedigree-based relationship matrix. Therefore, it is necessary to adjust the marker-based relationship matrix to the pedigree-based relationship matrix. Moreover, with data from routine evaluations, this adjustment should in principle be based on both observed marker genotypes and observed phenotypes, but until now this has been overlooked. In this paper, I propose a new method to address this issue by 1) adjusting the pedigree-based relationship matrix to be compatible with the marker-based relationship matrix instead of the reverse and 2) extending the single-step genetic evaluation using a joint likelihood of observed phenotypes and observed marker genotypes. The performance of this method is then evaluated using two simulated datasets. The method derived here is a single-step method in which the marker-based relationship matrix is constructed assuming all allele frequencies equal to 0.5 and the pedigree-based relationship matrix is constructed using the unusual assumption that animals in the base population are related and inbred with a relationship coefficient γ and an inbreeding coefficient γ / 2. Taken together, this γ parameter and a parameter that scales the marker-based relationship matrix can handle the issue of compatibility between marker-based and pedigree-based relationship matrices. The full log-likelihood function used for parameter inference contains two terms. The first term is the REML-log-likelihood for the phenotypes conditional on the observed marker genotypes, whereas the second term is the log-likelihood for the observed marker genotypes. Analyses of the two simulated datasets with this new method showed that 1) the parameters involved in adjusting marker-based and pedigree

  4. 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.

  5. 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)

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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.

  14. Comparison of markerless and marker-based motion capture technologies through simultaneous data collection during gait: proof of concept.

    Directory of Open Access Journals (Sweden)

    Elena Ceseracciu

    Full Text Available During the last decade markerless motion capture techniques have gained an increasing interest in the biomechanics community. In the clinical field, however, the application of markerless techniques is still debated. This is mainly due to a limited number of papers dedicated to the comparison with the state of the art of marker based motion capture, in term of repeatability of the three dimensional joints' kinematics. In the present work the application of markerless technique to data acquired with a marker-based system was investigated. All videos and external data were recorded with the same motion capture system and included the possibility to use markerless and marker-based methods simultaneously. Three dimensional markerless joint kinematics was estimated and compared with the one determined with traditional marker based systems, through the evaluation of root mean square distance between joint rotations. In order to compare the performance of markerless and marker-based systems in terms of clinically relevant joint angles estimation, the same anatomical frames of reference were defined for both systems. Differences in calibration and synchronization of the cameras were excluded by applying the same wand calibration and lens distortion correction to both techniques. Best results were achieved for knee flexion-extension angle, with an average root mean square distance of 11.75 deg, corresponding to 18.35% of the range of motion. Sagittal plane kinematics was estimated better than on the other planes also for hip and ankle (root mean square distance of 17.62 deg e.g. 44.66%, and 7.17 deg e.g. 33.12%, meanwhile estimates for hip joint were the most incorrect. This technique enables users of markerless technology to compare differences with marker-based in order to define the degree of applicability of markerless technique.

  15. 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...

  16. 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.

  17. 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.

  18. 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).

  19. 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....

  20. 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...

  1. 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.

  2. 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.

  3. 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

  4. 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...

  5. 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...

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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...

  11. Development of universal genetic markers based on single-copy orthologous (COSII) genes in Poaceae.

    Science.gov (United States)

    Liu, Hailan; Guo, Xiaoqin; Wu, Jiasheng; Chen, Guo-Bo; Ying, Yeqing

    2013-03-01

    KEY MESSAGE : We develop a set of universal genetic markers based on single-copy orthologous (COSII) genes in Poaceae. Being evolutionary conserved, single-copy orthologous (COSII) genes are particularly useful in comparative mapping and phylogenetic investigation among species. In this study, we identified 2,684 COSII genes based on five sequenced Poaceae genomes including rice, maize, sorghum, foxtail millet, and brachypodium, and then developed 1,072 COSII markers whose transferability and polymorphism among five bamboo species were further evaluated with 46 pairs of randomly selected primers. 91.3 % of the 46 primers obtained clear amplification in at least one bamboo species, and 65.2 % of them produced polymorphism in more than one species. We also used 42 of them to construct the phylogeny for the five bamboo species, and it might reflect more precise evolutionary relationship than the one based on the vegetative morphology. The results indicated a promising prospect of applying these markers to the investigation of genetic diversity and the classification of Poaceae. To ease and facilitate access of the information of common interest to readers, a web-based database of the COSII markers is provided ( http://www.sicau.edu.cn/web/yms/PCOSWeb/PCOS.html ).

  12. 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.

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. Compatibility of pedigree-based and marker-based relationship matrices for single-step genetic evaluation

    DEFF Research Database (Denmark)

    Christensen, Ole Fredslund

    2012-01-01

    Single-step methods for genomic prediction have recently become popular because they are conceptually simple and in practice such a method can completely replace a pedigree-based method for routine genetic evaluation. An issue with single-step methods is compatibility between the marker-based rel......Single-step methods for genomic prediction have recently become popular because they are conceptually simple and in practice such a method can completely replace a pedigree-based method for routine genetic evaluation. An issue with single-step methods is compatibility between the marker......-based relationship matrix and the pedigree-based relationship matrix. The compatibility issue involves which allele frequencies to use in the marker-based relationship matrix, and also that adjustments of this matrix to the pedigree-based relationship matrix are needed. In addition, it has been overlooked...... in the base population. Here, two ideas are explored. The first idea is to instead adjust the pedigree-based relationship matrix to be compatible to the marker-based relationship matrix, whereas the second idea is to include the likelihood for the observed markers. A single-step method is used where...

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  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. 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

  10. 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...

  11. 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...

  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. 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.

  3. 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

  4. 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.

  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. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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...

  14. 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...

  15. 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.

  16. 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

  17. Multivariate analysis for the estimation of target localization errors in fiducial marker-based radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Takamiya, Masanori [Department of Nuclear Engineering, Graduate School of Engineering, Kyoto University, Kyoto 606-8501, Japan and Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto 606-8507 (Japan); Nakamura, Mitsuhiro, E-mail: m-nkmr@kuhp.kyoto-u.ac.jp; Akimoto, Mami; Ueki, Nami; Yamada, Masahiro; Matsuo, Yukinori; Mizowaki, Takashi; Hiraoka, Masahiro [Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto 606-8507 (Japan); Tanabe, Hiroaki [Division of Radiation Oncology, Institute of Biomedical Research and Innovation, Kobe 650-0047 (Japan); Kokubo, Masaki [Division of Radiation Oncology, Institute of Biomedical Research and Innovation, Kobe 650-0047, Japan and Department of Radiation Oncology, Kobe City Medical Center General Hospital, Kobe 650-0047 (Japan); Itoh, Akio [Department of Nuclear Engineering, Graduate School of Engineering, Kyoto University, Kyoto 606-8501 (Japan)

    2016-04-15

    calculated from the MRA ({sup MRA}TLE) increased as |TMD| and |aRM| increased and adversely decreased with each increment of n. The median 3D {sup MRA}TLE was 2.0 mm (range, 0.6–4.3 mm) for n = 1, 1.8 mm (range, 0.4–4.0 mm) for n = 2, and 1.6 mm (range, 0.3–3.7 mm) for n = 3. Although statistical significance between n = 1 and n = 3 was observed in all directions, the absolute average difference and the standard deviation of the {sup MRA}TLE between n = 1 and n = 3 were 0.5 and 0.2 mm, respectively. Conclusions: A large |TMD| and |aRM| increased the differences in TLE between each n; however, the difference in 3D {sup MRA}TLEs was, at most, 0.6 mm. Thus, the authors conclude that it is acceptable to continue fiducial marker-based radiotherapy as long as |TMD| is maintained at ≤58.7 mm for a 3D |aRM|  ≥  10 mm.

  18. 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....

  19. 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)...

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. Hybrid Registration of Prostate and Seminal Vesicles for Image Guided Radiation Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Boer, Johan de; Herk, Marcel van; Pos, Floris J. [Department of Radiation Oncology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands); Sonke, Jan-Jakob, E-mail: j.sonke@nki.nl [Department of Radiation Oncology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands)

    2013-05-01

    Purpose: Fiducial markers are a good surrogate for the prostate but provide little information on the position and orientation of the seminal vesicles (SVs). Therefore, a more advanced localization method is warranted if the SVs are part of the target volume. The purpose of this study was to develop a hybrid registration technique for the localization of the prostate and SVs. Methods and Materials: Twenty prostate patients implanted with 2 or 3 elongated fiducial markers had cone beam computed tomography (CBCT) scans acquired at every fraction. The first step of the hybrid registration was to localize the prostate by CBCT-to-planning-CT alignment of the fiducial markers, allowing both translations and rotations. Using this marker registration as a starting point, the SVs were registered based on gray values, allowing only rotations around the lateral axis. We analyzed the differential rotation between the prostate and SVs and compared the required SV margins for 3 correction strategies. Results: The SV registration had a precision of 2.7° (1 standard deviation) and was successful for 96% of the scans. Mean (M), systematic (Σ), and random (σ) differences between the orientation of the prostate and SV were M = −0.4°, Σ = 7.2°, and σ = 6.4°. Daily marker-based corrections required an SV margin of 11.4 mm (translations only) and 11.6 mm (translations + rotations). Rotation corrections of the SVs reduced the required margin to 8.2 mm. Conclusions: We found substantial differences between the orientation of the prostate and SVs. The hybrid registration technique can accurately detect these rotations during treatment. Rotation correction of the SVs allows for margin reduction for the SVs.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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...

  14. Fluorescent marker-based and marker-free discrimination between healthy and cancerous human tissues using hyper-spectral imaging

    Science.gov (United States)

    Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

    2015-06-01

    Two problems are addressed in this paper (i) the fluorescent marker-based and the (ii) marker-free discrimination between healthy and cancerous human tissues. For both applications the performance of hyper-spectral methods are quantified. Fluorescent marker-based tissue classification uses a number of fluorescent markers to dye specific parts of a human cell. The challenge is that the emission spectra of the fluorescent dyes overlap considerably. They are, furthermore disturbed by the inherent auto-fluorescence of human tissue. This results in ambiguities and decreased image contrast causing difficulties for the treatment decision. The higher spectral resolution introduced by tunable-filter-based spectral imaging in combination with spectral unmixing techniques results in an improvement of the image contrast and therefore more reliable information for the physician to choose the treatment decision. Marker-free tissue classification is based solely on the subtle spectral features of human tissue without the use of artificial markers. The challenge in this case is that the spectral differences between healthy and cancerous tissues are subtle and embedded in intra- and inter-patient variations of these features. The contributions of this paper are (i) the evaluation of hyper-spectral imaging in combination with spectral unmixing techniques for fluorescence marker-based tissue classification, (ii) the evaluation of spectral imaging for marker-free intra surgery tissue classification. Within this paper, we consider real hyper-spectral fluorescence and endoscopy data sets to emphasize the practical capability of the proposed methods. It is shown that the combination of spectral imaging with multivariate statistical methods can improve the sensitivity and specificity of the detection and the staging of cancerous tissues compared to standard procedures.

  15. 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.

  16. 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.

  17. 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.

  18. 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).

  19. 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).

  20. Validating Dual Fluoroscopy System Capabilities for Determining In-Vivo Knee Joint Soft Tissue Deformation: A Strategy for Registration Error Management.

    Science.gov (United States)

    Sharma, Gulshan B; Kuntze, Gregor; Kukulski, Diane; Ronsky, Janet L

    2015-07-16

    Knee osteoarthritis (OA) causes structural and mechanical changes within tibiofemoral (TF) cartilage affecting tissue load deformation behavior. Quantifying in-vivo TF soft tissue deformations in healthy and early OA may provide a novel biomechanical marker, sensitive to alterations occurring prior to radiographic change. Dual Fluoroscopy (DF) allows accurate in-vivo TF soft tissue deformation assessment but requires validation. In-vivo healthy and early OA TF cartilage deforms 0.3-1.2mm during static standing full body-weight loading. Our aim was to establish minimum detectable displacement (MDD) for femoral translation in a DF system using a marker-based and markerless approach with variable image intensifier magnifications. An instrumented frame allowed controlled femur specimen translations. Bone positions were reconstructed from DF data using centroids of affixed steel beads (marker-based) and 2D-3D bone feature registration (markerless). Statistical analyses included independent samples t-tests and reliability analysis. Markerless measurements by three trained operators had large variations making it prudent to have an appropriate error management strategy when performing 2D-3D registration. Marker-based MDD improved with image resolution and was 0.05 mm at 3.2 LP/mm (LP: line pairs). Markerless MDD at 3.2 LP/mm was 0.08 mm. Average femur and tibia 2D-3D registrations yielded excellent reliability (84.4%). Therefore, DF images acquired at resolution greater than 3.2 LP/mm would be capable for determining accurate and reliable in-vivo healthy and early OA TF soft tissue deformation. This study provides a registration error management strategy for in-vivo TF soft tissue deformation assessment that could be applied for future clinical applications to establish non-invasive biomechanical markers for early OA diagnosis.

  1. 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

  2. Error analysis of marker-based object localization using a single-plane XRII

    Energy Technology Data Exchange (ETDEWEB)

    Habets, Damiaan F.; Pollmann, Steven I.; Yuan, Xunhua; Peters, Terry M.; Holdsworth, David W. [Imaging Research Laboratories, Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, 100 Perth Drive, London, Ontario N6A 5K8 (Canada) and Department of Medical Biophysics, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario N6A 5C1 (Canada); Imaging Research Laboratories, Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, 100 Perth Drive, London, Ontario N6A 5K8 (Canada); Imaging Research Laboratories, Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, 100 Perth Drive, London, Ontario N6A 5K8 (Canada) and Department of Medical Imaging, Department of Medical Biophysics, and Department of Biomedical Engineering, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario N6A 5C1 (Canada); Imaging Research Laboratories, Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, 100 Perth Drive, London, Ontario N6A 5K8 (Canada) and Department of Surgery, and Department of Medical Biophysics, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario N6A 5C1 (Canada)

    2009-01-15

    The role of imaging and image guidance is increasing in surgery and therapy, including treatment planning and follow-up. Fluoroscopy is used for two-dimensional (2D) guidance or localization; however, many procedures would benefit from three-dimensional (3D) guidance or localization. Three-dimensional computed tomography (CT) using a C-arm mounted x-ray image intensifier (XRII) can provide high-quality 3D images; however, patient dose and the required acquisition time restrict the number of 3D images that can be obtained. C-arm based 3D CT is therefore limited in applications for x-ray based image guidance or dynamic evaluations. 2D-3D model-based registration, using a single-plane 2D digital radiographic system, does allow for rapid 3D localization. It is our goal to investigate - over a clinically practical range - the impact of x-ray exposure on the resulting range of 3D localization precision. In this paper it is assumed that the tracked instrument incorporates a rigidly attached 3D object with a known configuration of markers. A 2D image is obtained by a digital fluoroscopic x-ray system and corrected for XRII distortions ({+-}0.035 mm) and mechanical C-arm shift ({+-}0.080 mm). A least-square projection-Procrustes analysis is then used to calculate the 3D position using the measured 2D marker locations. The effect of x-ray exposure on the precision of 2D marker localization and on 3D object localization was investigated using numerical simulations and x-ray experiments. The results show a nearly linear relationship between 2D marker localization precision and the 3D localization precision. However, a significant amplification of error, nonuniformly distributed among the three major axes, occurs, and that is demonstrated. To obtain a 3D localization error of less than {+-}1.0 mm for an object with 20 mm marker spacing, the 2D localization precision must be better than {+-}0.07 mm. This requirement was met for all investigated nominal x-ray exposures at 28 cm

  3. Error analysis of marker-based object localization using a single-plane XRII.

    Science.gov (United States)

    Habets, Damiaan F; Pollmann, Steven I; Yuan, Xunhua; Peters, Terry M; Holdsworth, David W

    2009-01-01

    The role of imaging and image guidance is increasing in surgery and therapy, including treatment planning and follow-up. Fluoroscopy is used for two-dimensional (2D) guidance or localization; however, many procedures would benefit from three-dimensional (3D) guidance or localization. Three-dimensional computed tomography (CT) using a C-arm mounted x-ray image intensifier (XRII) can provide high-quality 3D images; however, patient dose and the required acquisition time restrict the number of 3D images that can be obtained. C-arm based 3D CT is therefore limited in applications for x-ray based image guidance or dynamic evaluations. 2D-3D model-based registration, using a single-plane 2D digital radiographic system, does allow for rapid 3D localization. It is our goal to investigate-over a clinically practical range-the impact of x-ray exposure on the resulting range of 3D localization precision. In this paper it is assumed that the tracked instrument incorporates a rigidly attached 3D object with a known configuration of markers. A 2D image is obtained by a digital fluoroscopic x-ray system and corrected for XRII distortions (+/- 0.035 mm) and mechanical C-arm shift (+/- 0.080 mm). A least-square projection-Procrustes analysis is then used to calculate the 3D position using the measured 2D marker locations. The effect of x-ray exposure on the precision of 2D marker localization and on 3D object localization was investigated using numerical simulations and x-ray experiments. The results show a nearly linear relationship between 2D marker localization precision and the 3D localization precision. However, a significant amplification of error, nonuniformly distributed among the three major axes, occurs, and that is demonstrated. To obtain a 3D localization error of less than +/- 1.0 mm for an object with 20 mm marker spacing, the 2D localization precision must be better than +/- 0.07 mm. This requirement was met for all investigated nominal x-ray exposures at 28 cm FOV

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. A Cross-Species Gene Expression Marker-Based Genetic Map and QTL Analysis in Bambara Groundnut

    Directory of Open Access Journals (Sweden)

    Hui Hui Chai

    2017-02-01

    Full Text Available Bambara groundnut (Vigna subterranea (L. Verdc. is an underutilised legume crop, which has long been recognised as a protein-rich and drought-tolerant crop, used extensively in Sub-Saharan Africa. The aim of the study was to identify quantitative trait loci (QTL involved in agronomic and drought-related traits using an expression marker-based genetic map based on major crop resources developed in soybean. The gene expression markers (GEMs were generated at the (unmasked probe-pair level after cross-hybridisation of bambara groundnut leaf RNA to the Affymetrix Soybean Genome GeneChip. A total of 753 markers grouped at an LOD (Logarithm of odds of three, with 527 markers mapped into linkage groups. From this initial map, a spaced expression marker-based genetic map consisting of 13 linkage groups containing 218 GEMs, spanning 982.7 cM (centimorgan of the bambara groundnut genome, was developed. Of the QTL detected, 46% were detected in both control and drought treatment populations, suggesting that they are the result of intrinsic trait differences between the parental lines used to construct the cross, with 31% detected in only one of the conditions. The present GEM map in bambara groundnut provides one technically feasible route for the translation of information and resources from major and model plant species to underutilised and resource-poor crops.

  14. 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

  15. Mixed Marker-Based/Marker-Less Visual Odometry System for Mobile Robots

    Directory of Open Access Journals (Sweden)

    Fabrizio Lamberti

    2013-05-01

    Full Text Available When moving in generic indoor environments, robotic platforms generally rely solely on information provided by onboard sensors to determine their position and orientation. However, the lack of absolute references often leads to the introduction of severe drifts in estimates computed, making autonomous operations really hard to accomplish. This paper proposes a solution to alleviate the impact of the above issues by combining two vision‐based pose estimation techniques working on relative and absolute coordinate systems, respectively. In particular, the unknown ground features in the images that are captured by the vertical camera of a mobile platform are processed by a vision‐based odometry algorithm, which is capable of estimating the relative frame‐to‐frame movements. Then, errors accumulated in the above step are corrected using artificial markers displaced at known positions in the environment. The markers are framed from time to time, which allows the robot to maintain the drifts bounded by additionally providing it with the navigation commands needed for autonomous flight. Accuracy and robustness of the designed technique are demonstrated using an off‐the‐shelf quadrotor via extensive experimental tests.

  16. Remote Marker-Based Tracking for UAV Landing Using Visible-Light Camera Sensor.

    Science.gov (United States)

    Nguyen, Phong Ha; Kim, Ki Wan; Lee, Young Won; Park, Kang Ryoung

    2017-08-30

    Unmanned aerial vehicles (UAVs), which are commonly known as drones, have proved to be useful not only on the battlefields where manned flight is considered too risky or difficult, but also in everyday life purposes such as surveillance, monitoring, rescue, unmanned cargo, aerial video, and photography. More advanced drones make use of global positioning system (GPS) receivers during the navigation and control loop which allows for smart GPS features of drone navigation. However, there are problems if the drones operate in heterogeneous areas with no GPS signal, so it is important to perform research into the development of UAVs with autonomous navigation and landing guidance using computer vision. In this research, we determined how to safely land a drone in the absence of GPS signals using our remote maker-based tracking algorithm based on the visible light camera sensor. The proposed method uses a unique marker designed as a tracking target during landing procedures. Experimental results show that our method significantly outperforms state-of-the-art object trackers in terms of both accuracy and processing time, and we perform test on an embedded system in various environments.

  17. 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.

  18. 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

  19. 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...

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. Augmented reality surgical navigation with ultrasound-assisted registration for pedicle screw placement: a pilot study.

    Science.gov (United States)

    Ma, Longfei; Zhao, Zhe; Chen, Fang; Zhang, Boyu; Fu, Ligong; Liao, Hongen

    2017-08-05

    We present a novel augmented reality (AR) surgical navigation system based on ultrasound-assisted registration for pedicle screw placement. This system provides the clinically desired targeting accuracy and reduces radiation exposure. Ultrasound (US) is used to perform registration between preoperative computed tomography (CT) images and patient, and the registration is performed by least-squares fitting of these two three-dimensional (3D) point sets of anatomical landmarks taken from US and CT images. An integral videography overlay device is calibrated to accurately display naked-eye 3D images for surgical navigation. We use a 3.0-mm Kirschner wire (K-wire) instead of a pedicle screw in this study, and the K-wire is calibrated to obtain its orientation and tip location. Based on the above registration and calibration, naked-eye 3D images of the planning path and the spine are superimposed onto patient in situ using our AR navigation system. Simultaneously, a 3D image of the K-wire is overlaid accurately on the real one to guide the insertion procedure. The targeting accuracy is evaluated postoperatively by performing a CT scan. An agar phantom experiment was performed. Eight K-wires were inserted successfully after US-assisted registration, and the mean targeting error and angle error were 3.35 mm and [Formula: see text], respectively. Furthermore, an additional sheep cadaver experiment was performed. Four K-wires were inserted successfully. The mean targeting error was 3.79 mm and the mean angle error was [Formula: see text], and US-assisted registration yielded better targeting results than skin markers-based registration (targeting errors: 2.41 vs. 5.18 mm, angle errors: [Formula: see text] vs. [Formula: see text]. Experimental outcomes demonstrate that the proposed navigation system has acceptable targeting accuracy. In particular, the proposed navigation method reduces repeated radiation exposure to the patient and surgeons. Therefore, it has promising

  5. 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

  6. 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.

  7. 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.

  8. 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...

  9. 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.

  10. 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....

  11. 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...

  12. 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.

  13. 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.

  14. 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%).

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Molecular marker-based prediction of hybrid performance in maize using unbalanced data from multiple experiments with factorial crosses.

    Science.gov (United States)

    Schrag, Tobias A; Möhring, Jens; Maurer, Hans Peter; Dhillon, Baldev S; Melchinger, Albrecht E; Piepho, Hans-Peter; Sørensen, Anker P; Frisch, Matthias

    2009-02-01

    In hybrid breeding, the prediction of hybrid performance (HP) is extremely important as it is difficult to evaluate inbred lines in numerous cross combinations. Recent developments such as doubled haploid production and molecular marker technologies have enhanced the prospects of marker-based HP prediction to accelerate the breeding process. Our objectives were to (1) predict HP using a combined analysis of hybrids and parental lines from a breeding program, (2) evaluate the use of molecular markers in addition to phenotypic and pedigree data, (3) evaluate the combination of line per se data with marker-based estimates, (4) study the effect of the number of tested parents, and (5) assess the advantage of haplotype blocks. An unbalanced dataset of 400 hybrids from 9 factorial crosses tested in different experiments and data of 79 inbred parents were subjected to combined analyses with a mixed linear model. Marker data of the inbreds were obtained with 20 AFLP primer-enzyme combinations. Cross-validation was used to assess the performance prediction of hybrids of which no or only one parental line was testcross evaluated. For HP prediction, the highest proportion of explained variance (R (2)), 46% for grain yield (GY) and 70% for grain dry matter content (GDMC), was obtained from line per se best linear unbiased prediction (BLUP) estimates plus marker effects associated with mid-parent heterosis (TEAM-LM). Our study demonstrated that HP was efficiently predicted using molecular markers even for GY when testcross data of both parents are not available. This can help in improving greatly the efficiency of commercial hybrid breeding programs.

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

    Science.gov (United States)

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

    2015-04-01

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

  3. A fast image registration approach of neural activities in light-sheet fluorescence microscopy images

    Science.gov (United States)

    Meng, Hui; Hui, Hui; Hu, Chaoen; Yang, Xin; Tian, Jie

    2017-03-01

    The ability of fast and single-neuron resolution imaging of neural activities enables light-sheet fluorescence microscopy (LSFM) as a powerful imaging technique in functional neural connection applications. The state-of-art LSFM imaging system can record the neuronal activities of entire brain for small animal, such as zebrafish or C. elegans at single-neuron resolution. However, the stimulated and spontaneous movements in animal brain result in inconsistent neuron positions during recording process. It is time consuming to register the acquired large-scale images with conventional method. In this work, we address the problem of fast registration of neural positions in stacks of LSFM images. This is necessary to register brain structures and activities. To achieve fast registration of neural activities, we present a rigid registration architecture by implementation of Graphics Processing Unit (GPU). In this approach, the image stacks were preprocessed on GPU by mean stretching to reduce the computation effort. The present image was registered to the previous image stack that considered as reference. A fast Fourier transform (FFT) algorithm was used for calculating the shift of the image stack. The calculations for image registration were performed in different threads while the preparation functionality was refactored and called only once by the master thread. We implemented our registration algorithm on NVIDIA Quadro K4200 GPU under Compute Unified Device Architecture (CUDA) programming environment. The experimental results showed that the registration computation can speed-up to 550ms for a full high-resolution brain image. Our approach also has potential to be used for other dynamic image registrations in biomedical applications.

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

    Science.gov (United States)

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

    2014-03-01

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

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

    Science.gov (United States)

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

    2012-03-01

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

  6. Image Registration and Optimization in the Virtual Slaughterhouse

    DEFF Research Database (Denmark)

    Vester-Christensen, Martin

    This thesis presents the development and application of algorithms for the analysis of pig carcasses. Focus is on the simulation and quality estimation of meat products produced in a Danish slaughterhouse. Computed Tomography scans of pig carcasses provide the data used in the application. Image...... analysis is applied in order to imitate some of the cutting processes found in a slaughterhouse but also to give a quantitative measure of the composition of each carcass. The basis of the algorithms is non-linear image registration. This method finds the anatomical correspondence between a reference...... carcass and a template carcass. By iteratively comparing the transformed template with the reference a resulting dense deformation field is found. Propagating a set of landmarks from the reference coordinate system onto the template enables the simulation of slaughtering processes. Non...

  7. 17 CFR 3.4 - Registration in one capacity not included in registration in any other capacity.

    Science.gov (United States)

    2010-04-01

    ... 17 Commodity and Securities Exchanges 1 2010-04-01 2010-04-01 false Registration in one capacity not included in registration in any other capacity. 3.4 Section 3.4 Commodity and Securities Exchanges COMMODITY FUTURES TRADING COMMISSION REGISTRATION Registration § 3.4 Registration in one capacity...

  8. An adaptive patient specific deformable registration for breast images of positron emission tomography and magnetic resonance imaging using finite element approach

    Science.gov (United States)

    Xue, Cheng; Tang, Fuk-Hay

    2014-03-01

    A patient specific registration model based on finite element method was investigated in this study. Image registration of Positron Emission Tomography (PET) and Magnetic Resonance imaging (MRI) has been studied a lot. Surface-based registration is extensively applied in medical imaging. We develop and evaluate a registration method combine surface-based registration with biomechanical modeling. .Four sample cases of patients with PET and MRI breast scans performed within 30 days were collected from hospital. K-means clustering algorithm was used to segment images into two parts, which is fat tissue and neoplasm [2]. Instead of placing extrinsic landmarks on patients' body which may be invasive, we proposed a new boundary condition to simulate breast deformation during two screening. Then a three dimensional model with meshes was built. Material properties were assigned to this model according to previous studies. The whole registration was based on a biomechanical finite element model, which could simulate deformation of breast under pressure.

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

    Science.gov (United States)

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

    2013-07-08

    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 on B-spline transformation was performed using optimized parameters of the elastix package based on the Insight Toolkit (ITK) framework. Twenty-eight (17 male and 11 female) clinical studies were used in this work. The registration was evaluated using anatomical landmarks and segmented organs. In addition to 16 anatomical landmarks, three key organs (brain, lungs, and kidneys) and the entire body volume were segmented for evaluation. Several parameters--such as the Euclidean distance between anatomical landmarks, target overlap, Dice and Jaccard coefficients, false positives and false negatives, volume similarity, distance error, and Hausdorff distance--were calculated to quantify the quality of the registration algorithm. Dice coefficients for the majority of patients (> 75%) were in the 0.8-1 range for the whole body, brain, and lungs, which satisfies the criteria to achieve excellent alignment. On the other hand, for kidneys, Dice coefficients for volumes of 25% of the patients meet excellent volume agreement requirement, while the majority of patients satisfy good agreement criteria (> 0.6). For all patients, the distance error was in 0-10 mm range for all segmented organs. In summary, we optimized and evaluated the accuracy of an MR to CT deformable registration algorithm. The registered images constitute a useful 3D whole-body MR-CT atlas suitable for the development and evaluation of novel MR-guided attenuation correction procedures on hybrid PET-MR systems.

  10. Explicit pattern matching assignment algorithm

    Science.gov (United States)

    Levedahl, Mark

    2002-08-01

    Sharing data between two tracking systems frequently involves use of an object map: the transmitting system sends a frame of data with multiple observations, and the receiving system uses an assignment algorithm to correlate the information with its local observation data base. The usual prescription for this problem is an optimal assignment algorithm (such as JVC or auction) using a cost matrix based upon chi-squared distances between the local and remote observation data. The optimal assignment algorithm does not actually perform pattern matching, so this approach is not robust to large registration errors between the two systems when there exist differences in the number of observations held by both systems. Performance of a new assignment algorithm that uses a cost function including terms for both registration errors and track to track random errors is presented: the cost function explicitly includes a bias between the two observation sets and thus provides a maximum likelihood solution to the assignment problem. In practice, this assignment approach provides near perfect assignment accuracy in cases where the bias errors exceed the dimension of the transmitted object map and there exist mismatches in the numbers of observations made by the two systems. This performance extends to many cases where the optimal assignment algorithm methodology produces errors nearly 100% of the time. The paper includes the theoretical foundation of the assignment problem solved and comparison of achieved accuracy with existing optimal assignment approaches.

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

    Science.gov (United States)

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

    2012-01-01

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

  12. Nonrigid registration of myocardial perfusion MRI

    DEFF Research Database (Denmark)

    Ólafsdóttir, Hildur

    2005-01-01

    This paper describes a fully automatic registration of 10 multi-slice myocardial perfusion magnetic resonance image sequences. The registration of these sequences is crucial for the clinical interpretation, which currently is subjected to manual labour. The approach used in this study is a nonrig...

  13. 76 FR 42684 - Statutory Invention Registration

    Science.gov (United States)

    2011-07-19

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

  14. 77 FR 73558 - Sex Offender Registration Amendments

    Science.gov (United States)

    2012-12-11

    ... COLUMBIA 28 CFR Part 811 RIN 3225-AA10 Sex Offender Registration Amendments AGENCY: Court Services and... verification of registration information for sex offenders. The proposed rule, if finalized, would permit CSOSA to verify addresses of sex offenders by conducting home visits on its own accord and with its...

  15. Registrering af praehabilitering inden planlagt operation

    DEFF Research Database (Denmark)

    Tønnesen, Hanne; Duus, Benn Rønnow

    2008-01-01

    for registration of prehabilitation prior to surgery. Using one specific code for prehabilitation at the surgical department and another for prehabilitation at other departments will enable correct registration. Thereby, it is possible to differentiate between ordinary waiting time before surgery and time...

  16. Sparse Online Low-Rank Projection and Outlier Rejection (SOLO) for 3-D Rigid-Body Motion Registration

    CERN Document Server

    Slaughter, Chris; Bagwell, Justin; Checkles, Costa; Sentis, Luis; Vishwanath, Sriram

    2011-01-01

    Motivated by an emerging theory of robust low-rank matrix representation, in this paper, we introduce a novel solution for online rigid-body motion registration. The goal is to develop algorithmic techniques that enable a robust, real-time motion registration solution suitable for low-cost, portable 3-D camera devices. Assuming 3-D image features are tracked via a standard tracker, the algorithm first utilizes Robust PCA to initialize a low-rank shape representation of the rigid body. Robust PCA finds the global optimal solution of the initialization, while its complexity is comparable to singular value decomposition. In the online update stage, we propose a more efficient algorithm for sparse subspace projection to sequentially project new feature observations onto the shape subspace. The lightweight update stage guarantees the real-time performance of the solution while maintaining good registration even when the image sequence is contaminated by noise, gross data corruption, outlying features, and missing ...

  17. Technical Note: DIRART- A software suite for deformable image registration and adaptive radiotherapy research

    Energy Technology Data Exchange (ETDEWEB)

    Yang Deshan; Brame, Scott; El Naqa, Issam; Aditya, Apte; Wu Yu; Murty Goddu, S.; Mutic, Sasa; Deasy, Joseph O.; Low, Daniel A. [Department of Radiation Oncology, School of Medicine, Washington University in Saint Louis, Missouri 63110 (United States)

    2011-01-15

    Purpose: Recent years have witnessed tremendous progress in image guide radiotherapy technology and a growing interest in the possibilities for adapting treatment planning and delivery over the course of treatment. One obstacle faced by the research community has been the lack of a comprehensive open-source software toolkit dedicated for adaptive radiotherapy (ART). To address this need, the authors have developed a software suite called the Deformable Image Registration and Adaptive Radiotherapy Toolkit (DIRART). Methods: DIRART is an open-source toolkit developed in MATLAB. It is designed in an object-oriented style with focus on user-friendliness, features, and flexibility. It contains four classes of DIR algorithms, including the newer inverse consistency algorithms to provide consistent displacement vector field in both directions. It also contains common ART functions, an integrated graphical user interface, a variety of visualization and image-processing features, dose metric analysis functions, and interface routines. These interface routines make DIRART a powerful complement to the Computational Environment for Radiotherapy Research (CERR) and popular image-processing toolkits such as ITK. Results: DIRART provides a set of image processing/registration algorithms and postprocessing functions to facilitate the development and testing of DIR algorithms. It also offers a good amount of options for DIR results visualization, evaluation, and validation. Conclusions: By exchanging data with treatment planning systems via DICOM-RT files and CERR, and by bringing image registration algorithms closer to radiotherapy applications, DIRART is potentially a convenient and flexible platform that may facilitate ART and DIR research.

  18. [Affine transformation-based automatic registration for peripheral digital subtraction angiography (DSA)].

    Science.gov (United States)

    Kong, Gang; Dai, Dao-Qing; Zou, Lu-Min

    2008-07-01

    In order to remove the artifacts of peripheral digital subtraction angiography (DSA), an affine transformation-based automatic image registration algorithm is introduced here. The whole process is described as follows: First, rectangle feature templates are constructed with their centers of the extracted Harris corners in the mask, and motion vectors of the central feature points are estimated using template matching technology with the similarity measure of maximum histogram energy. And then the optimal parameters of the affine transformation are calculated with the matrix singular value decomposition (SVD) method. Finally, bilinear intensity interpolation is taken to the mask according to the specific affine transformation. More than 30 peripheral DSA registrations are performed with the presented algorithm, and as the result, moving artifacts of the images are removed with sub-pixel precision, and the time consumption is less enough to satisfy the clinical requirements. Experimental results show the efficiency and robustness of the algorithm.

  19. Evaluation of various Deformable Image Registrations for Point and Volume Variations

    CERN Document Server

    Han, Su Chul; Park, Seungwoo; Lee, Soon Sung; Jung, Haijo; Kim, Mi-Sook; Yoo, Hyung Jun; Ji, Young Hoon; Yi, Chul Young; Kim, Kum Bae

    2015-01-01

    The accuracy of deformable image registration (DIR) has a significant dosimetric impact in radiation treatment planning. We evaluated accuracy of various DIR algorithms using variations of the deformation point and volume. The reference image (Iref) and volume (Vref) was first generated with virtual deformation QA software (ImSimQA, Oncology System Limited, UK). We deformed Iref with axial movement of deformation point and Vref depending on the types of deformation that are the deformation1 is to increase the Vref (relaxation) and the deformation 2 is to decrease . The deformed image (Idef) and volume (Vdef) acquired by ImSimQA software were inversely deformed to Iref and Vref using DIR algorithms. As a result, we acquired deformed image (Iid) from Idef and volume (Vid) from Vdef. The DIR algorithms were the Horn Schunk optical flow (HS), Iterative Optical Flow (IOF), Modified Demons (MD) and Fast Demons (FD) with the Deformable Image Registration and Adaptive Radiotherapy Toolkit (DIRART) of MATLAB. The imag...

  20. Registration Day-Camp 2016

    CERN Multimedia

    Nursery School

    2016-01-01

    Registration for the CERN SA Day-camp are open for children from 4 to 6 years old From March 14 to 25 for children already enrolled in CERN SA EVE and School From April 4 to 15 for the children of CERN members of the personnel (MP) From April 18 for other children 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.

  1. Nonrigid registration with tissue-dependent filtering of the deformation field

    Energy Technology Data Exchange (ETDEWEB)

    Staring, Marius; Klein, Stefan; Pluim, Josien P W [Image Sciences Institute, University Medical Center Utrecht, PO Box 85500, 3508 GA, Room Q0S.459, Utrecht (Netherlands)

    2007-12-07

    In present-day medical practice it is often necessary to nonrigidly align image data. Current registration algorithms do not generally take the characteristics of tissue into account. Consequently, rigid tissue, such as bone, can be deformed elastically, growth of tumours may be concealed, and contrast-enhanced structures may be reduced in volume. We propose a method to locally adapt the deformation field at structures that must be kept rigid, using a tissue-dependent filtering technique. This adaptive filtering of the deformation field results in locally linear transformations without scaling or shearing. The degree of filtering is related to tissue stiffness: more filtering is applied at stiff tissue locations, less at parts of the image containing nonrigid tissue. The tissue-dependent filter is incorporated in a commonly used registration algorithm, using mutual information as a similarity measure and cubic B-splines to model the deformation field. The new registration algorithm is compared with this popular method. Evaluation of the proposed tissue-dependent filtering is performed on 3D computed tomography (CT) data of the thorax and on 2D digital subtraction angiography (DSA) images. The results show that tissue-dependent filtering of the deformation field leads to improved registration results: tumour volumes and vessel widths are preserved rather than affected.

  2. Evaluating automatic registration of UAV imagery using multi-temporal ortho images

    Science.gov (United States)

    Saur, Günter; Krüger, Wolfgang

    2016-10-01

    Accurate geo-registration of acquired imagery is an important task when using unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. As an example, change detection needs accurately geo-registered images for selecting and comparing co-located images taken at different points in time. One challenge using small UAVs lies in the instable flight behavior and using low-weight cameras. Thus, there is a need to stabilize and register the UAV imagery by image processing methods since using only direct approaches based on positional information coming from a GPS and attitude and acceleration measured by an inertial measurement unit (IMU) are not accurate enough. In order to improve this direct geo-registration (or "pre-registration"), image matching techniques are applied to align the UAV imagery to geo-registered reference images. The main challenge consists in matching images taken from different sensors at different day time and seasons. In this paper, we present evaluation methods for measuring the performance of image registration algorithms w.r.t. multi-temporal input data. They are based on augmenting a set of aligned image pairs by synthetic pre-registrations to an evaluation data set including truth transformations. The evaluation characteristics are based on quantiles of transformation residuals at certain control points. For a test site, video frames of a UAV mission and several ortho images from a period of 12 years are collected and synthetic pre-registrations corresponding to real flight parameters and registration errors are computed. Two algorithms A1 and A2 based on extracting key-points with a floating point descriptor (A1) and a binary descriptor (A2) are applied to the evaluation data set. As evaluation result, the algorithm A1 turned out to perform better than A2. Using affine or Helmert transformation types, both algorithms perform better than in the projective case. Furthermore, the evaluation classifies the ortho images w

  3. In-vitro assessment of a registration protocol for image guided implant dentistry.

    Science.gov (United States)

    Birkfellner, W; Solar, P; Gahleitner, A; Huber, K; Kainberger, F; Kettenbach, J; Homolka, P; Diemling, M; Watzek, G; Bergmann, H

    2001-02-01

    In this study a computer aided navigation technique for accurate positioning of oral implants was assessed. An optical tracking system with specially designed tools for monitoring the position of surgical instruments relative to the patient was used to register 5 partially or completely edentulous jaw models. Besides the accuracy of the tracking system, the precision of localizing a specific position on 3-dimensional preoperative imagery is governed by the registration algorithm which conveys the coordinate system of the preoperative computed tomography (CT) scan to the actual patient position. Two different point-to-point registration algorithms were compared for their suitability for this application. The accuracy was determined separately for the localization error of the position measurement hardware (fiducial localization error-FLE) and the error as reported by the registration algorithm (fiducial registration error-FRE). The overall error of the navigation procedure was determined as the localization error of additional landmarks (steel spheres, 0.5 mm diameter) after registration (target registration error-TRE). Images of the jaw models were obtained using a high resolution CT scan (1.5 mm slice thickness, 1 mm table feed, incremental scanning, 120 kV, 150 mAs, 512 x 512 matrix, FOV 120 mm). The accuracy of the position measurement probes was 0.69 +/- 0.15 mm (FLE). Using 3 implanted fiducial markers, FRE was 0.71 +/- 0.12 mm on average and 1.00 +/- 0.13 mm maximum. TRE was found to be 1.23 +/- 0.28 mm average and 1.87 +/- 0.47 mm maximum. Increasing the number of fiducial markers to a total of 5 did not significantly improve precision. Furthermore it was found that a registration algorithm based on solving an eigenvalue problem is the superior approach for point-to-point matching in terms of mathematical stability. The experimental results indicate that positioning accuracy of oral implants may benefit from computer aided intraoperative navigation. The

  4. Landmark matching based automatic retinal image registration with linear programming and self-similarities.

    Science.gov (United States)

    Zheng, Yuanjie; Hunter, Allan A; Wu, Jue; Wang, Hongzhi; Gao, Jianbin; Maguire, Maureen G; Gee, James C

    2011-01-01

    In this paper, we address the problem of landmark matching based retinal image registration. Two major contributions render our registration algorithm distinguished from many previous methods. One is a novel landmark-matching formulation which enables not only a joint estimation of the correspondences and transformation model but also the optimization with linear programming. The other contribution lies in the introduction of a reinforced self-similarities descriptor in characterizing the local appearance of landmarks. Theoretical analysis and a series of preliminary experimental results show both the effectiveness of our optimization scheme and the high differentiating ability of our features.

  5. Spatially adaptive regularized iterative high-resolution image reconstruction algorithm

    Science.gov (United States)

    Lim, Won Bae; Park, Min K.; Kang, Moon Gi

    2000-12-01

    High resolution images are often required in applications such as remote sensing, frame freeze in video, military and medical imaging. Digital image sensor arrays, which are used for image acquisition in many imaging systems, are not dense enough to prevent aliasing, so the acquired images will be degraded by aliasing effects. To prevent aliasing without loss of resolution, a dense detector array is required. But it may be very costly or unavailable, thus, many imaging systems are designed to allow some level of aliasing during image acquisition. The purpose of our work is to reconstruct an unaliased high resolution image from the acquired aliased image sequence. In this paper, we propose a spatially adaptive regularized iterative high resolution image reconstruction algorithm for blurred, noisy and down-sampled image sequences. The proposed approach is based on a Constrained Least Squares (CLS) high resolution reconstruction algorithm, with spatially adaptive regularization operators and parameters. These regularization terms are shown to improve the reconstructed image quality by forcing smoothness, while preserving edges in the reconstructed high resolution image. Accurate sub-pixel motion registration is the key of the success of the high resolution image reconstruction algorithm. However, sub-pixel motion registration may have some level of registration error. Therefore, a reconstruction algorithm which is robust against the registration error is required. The registration algorithm uses a gradient based sub-pixel motion estimator which provides shift information for each of the recorded frames. The proposed algorithm is based on a technique of high resolution image reconstruction, and it solves spatially adaptive regularized constrained least square minimization functionals. In this paper, we show that the reconstruction algorithm gives dramatic improvements in the resolution of the reconstructed image and is effective in handling the aliased information. The

  6. A 4D biomechanical lung phantom for joint segmentation/registration evaluation

    Science.gov (United States)

    Markel, Daniel; Levesque, Ives; Larkin, Joe; Léger, Pierre; El Naqa, Issam

    2016-10-01

    At present, there exists few openly available methods for evaluation of simultaneous segmentation and registration algorithms. These methods allow for a combination of both techniques to track the tumor in complex settings such as adaptive radiotherapy. We have produced a quality assurance platform for evaluating this specific subset of algorithms using a preserved porcine lung in such that it is multi-modality compatible: positron emission tomography (PET), computer tomography (CT) and magnetic resonance imaging (MRI). A computer controlled respirator was constructed to pneumatically manipulate the lungs in order to replicate human breathing traces. A registration ground truth was provided using an in-house bifurcation tracking pipeline. Segmentation ground truth was provided by synthetic multi-compartment lesions to simulate biologically active tumor, background tissue and a necrotic core. The bifurcation tracking pipeline results were compared to digital deformations and used to evaluate three registration algorithms, Diffeomorphic demons, fast-symmetric forces demons and MiMVista’s deformable registration tool. Three segmentation algorithms the Chan Vese level sets method, a Hybrid technique and the multi-valued level sets algorithm. The respirator was able to replicate three seperate breathing traces with a mean accuracy of 2-2.2%. Bifurcation tracking error was found to be sub-voxel when using human CT data for displacements up to 6.5 cm and approximately 1.5 voxel widths for displacements up to 3.5 cm for the porcine lungs. For the fast-symmetric, diffeomorphic and MiMvista registration algorithms, mean geometric errors were found to be 0.430+/- 0.001 , 0.416+/- 0.001 and 0.605+/- 0.002 voxels widths respectively using the vector field differences and 0.4+/- 0.2 , 0.4+/- 0.2 and 0.6+/- 0.2 voxel widths using the bifurcation tracking pipeline. The proposed phantom was found sufficient for accurate evaluation of registration and segmentation algorithms

  7. 2D/3D registration for X-ray guided bronchoscopy using distance map classification.

    Science.gov (United States)

    Xu, Di; Xu, Sheng; Herzka, Daniel A; Yung, Rex C; Bergtholdt, Martin; Gutierrez, Luis F; McVeigh, Elliot R

    2010-01-01

    In X-ray guided bronchoscopy of peripheral pulmonary lesions, airways and nodules are hardly visible in X-ray images. Transbronchial biopsy of peripheral lesions is often carried out blindly, resulting in degraded diagnostic yield. One solution of this problem is to superimpose the lesions and airways segmented from preoperative 3D CT images onto 2D X-ray images. A feature-based 2D/3D registration method is proposed for the image fusion between the datasets of the two imaging modalities. Two stereo X-ray images are used in the algorithm to improve the accuracy and robustness of the registration. The algorithm extracts the edge features of the bony structures from both CT and X-ray images. The edge points from the X-ray images are categorized into eight groups based on the orientation information of their image gradients. An orientation dependent Euclidean distance map is generated for each group of X-ray feature points. The distance map is then applied to the edge points of the projected CT images whose gradient orientations are compatible with the distance map. The CT and X-ray images are registered by matching the boundaries of the projected CT segmentations to the closest edges of the X-ray images after the orientation constraint is satisfied. Phantom and clinical studies were carried out to validate the algorithm's performance, showing a registration accuracy of 4.19(± 0.5) mm with 48.39(± 9.6) seconds registration time. The algorithm was also evaluated on clinical data, showing promising registration accuracy and robustness.

  8. An automated deformable image registration evaluation of confidence tool

    Science.gov (United States)

    Kirby, Neil; Chen, Josephine; Kim, Hojin; Morin, Olivier; Nie, Ke; Pouliot, Jean

    2016-04-01

    Deformable image registration (DIR) is a powerful tool for radiation oncology, but it can produce errors. Beyond this, DIR accuracy is not a fixed quantity and varies on a case-by-case basis. The purpose of this study is to explore the possibility of an automated program to create a patient- and voxel-specific evaluation of DIR accuracy. AUTODIRECT is a software tool that was developed to perform this evaluation for the application of a clinical DIR algorithm to a set of patient images. In brief, AUTODIRECT uses algorithms to generate deformations and applies them to these images (along with processing) to generate sets of test images, with known deformations that are similar to the actual ones and with realistic noise properties. The clinical DIR algorithm is applied to these test image sets (currently 4). From these tests, AUTODIRECT generates spatial and dose uncertainty estimates for each image voxel based on a Student’s t distribution. In this study, four commercially available DIR algorithms were used to deform a dose distribution associated with a virtual pelvic phantom image set, and AUTODIRECT was used to generate dose uncertainty estimates for each deformation. The virtual phantom image set has a known ground-truth deformation, so the true dose-warping errors of the DIR algorithms were also known. AUTODIRECT predicted error patterns that closely matched the actual error spatial distribution. On average AUTODIRECT overestimated the magnitude of the dose errors, but tuning the AUTODIRECT algorithms should improve agreement. This proof-of-principle test demonstrates the potential for the AUTODIRECT algorithm as an empirical method to predict DIR errors.

  9. 2007-2008 National Voter Registration Act of 1993 Survey

    Data.gov (United States)

    Election Assistance Commission — This dataset contains voter registration data for the 2008 election cycle. The dataset and corresponding report address the impact of the National Voter Registration...

  10. Algorithm design

    CERN Document Server

    Kleinberg, Jon

    2006-01-01

    Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.

  11. Genetic algorithms

    Science.gov (United States)

    Wang, Lui; Bayer, Steven E.

    1991-01-01

    Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.

  12. Tensor scale-based image registration

    Science.gov (United States)

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

    2003-05-01

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

  13. Cellular recurrent deep network for image registration

    Science.gov (United States)

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

    2015-09-01

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

  14. Video surveillance for sensor platforms algorithms and architectures

    CERN Document Server

    Al Najjar, Mayssaa; Bayoumi, Magdy

    2014-01-01

    This book introduces resource aware image decomposition, registration, fusion, object detection and tracking algorithms along with their applications in security, monitoring and integration in 3rd Generation Surveillance Systems.  All algorithms are evaluated through experimental and simulation results and a parallel and pipelined efficient architecture for implementing the algorithms is described. • Describes a new type of image processing algorithms that are suited for low power and low memory platforms such as wireless sensor networks or mobile devices; • Uses simulation and experimental results to evaluate algorithms presented; • Includes hardware architecture for critical components in the algorithms described.

  15. Calibration of the Multi-camera Registration System for Visual Navigation Benchmarking

    Directory of Open Access Journals (Sweden)

    Adam Schmidt

    2014-06-01

    Full Text Available This paper presents the complete calibration procedure of a multi-camera system for mobile robot motion registration. Optimization-based, purely visual methods for the estimation of the relative poses of the motion registration system cameras, as well as the relative poses of the cameras and markers placed on the mobile robot were proposed. The introduced methods were applied to the calibration of the system and the quality of the obtained results was evaluated. The obtained results compare favourably with the state of the art solutions, allowing the use of the considered motion registration system for the accurate reconstruction of the mobile robot trajectory and to register new datasets suitable for the benchmarking of indoor, visual-based navigation algorithms.

  16. Spatially adaptive log-euclidean polyaffine registration based on sparse matches.

    Science.gov (United States)

    Taquet, Maxime; Macq, Benoît; Warfield, Simon K

    2011-01-01

    Log-euclidean polyaffine transforms have recently been introduced to characterize the local affine behavior of the deformation in principal anatomical structures. The elegant mathematical framework makes them a powerful tool for image registration. However, their application is limited to large structures since they require the pre-definition of affine regions. This paper extends the polyaffine registration to adaptively fit a log-euclidean polyaffine transform that captures deformations at smaller scales. The approach is based on the sparse selection of matching points in the images and the formulation of the problem as an expectation maximization iterative closest point problem. The efficiency of the algorithm is shown through experiments on inter-subject registration of brain MRI between a healthy subject and patients with multiple sclerosis.

  17. Demons Registration of CT Volume and CBCT Projections for Adaptive Radiotherapy: Avoiding CBCT Reconstruction

    DEFF Research Database (Denmark)

    Bjerre, Troels; Aznar, M.; Munck af Rosenschöld, P.

    2012-01-01

    . CBCT scans, are typically reconstructed using the filtered back-projection algorithm, which introduces significant artefacts, causing deteriorated image quality and registration results. We study the feasibility of performing demons registration without tomographic reconstruction of the CBCT...... and registered image was 1.4·10-3 HU2. The mean absolute difference between the Jacobian determinant of the true and estimated deformation field was 4.0·10- 4. Time consumption was 11 min. using 8 2.3 GHz AMD Opteron cores. Conclusions: In this feasibility study, using a known deformation and synthetic noise......Purpose/Objective: In adaptive radiotherapy, the dose plan is adapted throughout the fractionation schedule to accommodate for anatomical changes. This can be achieved by deformable image registration of the planning PET-CT scan with segmented tumor and organs to daily cone beam CT (CBCT) scans...

  18. The registration of dual-modality ship target images based on edge extraction

    Science.gov (United States)

    Zhang, Weimin; Wang, Risheng; Zhou, Fugen

    2014-11-01

    In this paper, we study the problem of visible and IR(infrared) ship target image registration with scale changes. We mainly focus on the infrared and visible image feature extraction and matching method. A method based on Force Field Transformation is used to determine the ship target contour area. Canny edge detection method is applied to obtain the edge features. During the process of image registration, we take the cross-correlation as the similarity measure and propose an improved Powell algorithm based on multi-scale searching to optimize the registration parameters. Through the edge fusion results, we can see the corresponding edges are almost overlapped, indicating that the method could achieve satisfying results. Also the average error distance of match is less than one pixel.

  19. 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.

  20. Two-step image registration by artificial immune system and chamfer matching

    Institute of Scientific and Technical Information of China (English)

    Famao Ye; Shaoping Xu; Yuhong Xiong

    2008-01-01

    Image registration is the precondition and foundation in the fusion of multi-source image data. A two-step approach based on artificial immune system and chamfer matching to register images from different types of sensors is presented. In the first step, it extracts the large edges and takes chamfer distance between the input image and the reference image as similarity measure and uses artificial immune network algorithm to speed up the searching of the initial transformation parameters. In the second step, an area-based method is utilized to refine the initial transformation and enhance the registration accuracy. Experimental results show that the proposed approach is a promising method for registration of multi-sensor images.

  1. Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?

    Directory of Open Access Journals (Sweden)

    Andrew Zisserman

    2007-01-01

    Full Text Available In multiple-image super-resolution, a high-resolution image is estimated from a number of lower-resolution images. This usually involves computing the parameters of a generative imaging model (such as geometric and photometric registration, and blur and obtaining a MAP estimate by minimizing a cost function including an appropriate prior. Two alternative approaches are examined. First, both registrations and the super-resolution image are found simultaneously using a joint MAP optimization. Second, we perform Bayesian integration over the unknown image registration parameters, deriving a cost function whose only variables of interest are the pixel values of the super-resolution image. We also introduce a scheme to learn the parameters of the image prior as part of the super-resolution algorithm. We show examples on a number of real sequences including multiple stills, digital video, and DVDs of movies.

  2. Introduction to Remote Sensing Image Registration

    Science.gov (United States)

    Le Moigne, Jacqueline

    2017-01-01

    For many applications, accurate and fast image registration of large amounts of multi-source data is the first necessary step before subsequent processing and integration. Image registration is defined by several steps and each step can be approached by various methods which all present diverse advantages and drawbacks depending on the type of data, the type of applications, the a prior information known about the data and the type of accuracy that is required. This paper will first present a general overview of remote sensing image registration and then will go over a few specific methods and their applications

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

    Science.gov (United States)

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

    2013-07-01

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

  4. Registration of FA and T1-weighted MRI data of healthy human brain based on template matching and normalized cross-correlation.

    Science.gov (United States)

    Malinsky, Milos; Peter, Roman; Hodneland, Erlend; Lundervold, Astri J; Lundervold, Arvid; Jan, Jiri

    2013-08-01

    In this work, we propose a new approach for three-dimensional registration of MR fractional anisotropy images with T1-weighted anatomy images of human brain. From the clinical point of view, this accurate coregistration allows precise detection of nerve fibers that is essential in neuroscience. A template matching algorithm combined with normalized cross-correlation was used for this registration task. To show the suitability of the proposed method, it was compared with the normalized mutual information-based B-spline registration provided by the Elastix software library, considered a reference method. We also propose a general framework for the evaluation of robustness and reliability of both registration methods. Both registration methods were tested by four evaluation criteria on a dataset consisting of 74 healthy subjects. The template matching algorithm has shown more reliable results than the reference method in registration of the MR fractional anisotropy and T1 anatomy image data. Significant differences were observed in the regions splenium of corpus callosum and genu of corpus callosum, considered very important areas of brain connectivity. We demonstrate that, in this registration task, the currently used mutual information-based parametric registration can be replaced by more accurate local template matching utilizing the normalized cross-correlation similarity measure.

  5. Temporal-spatial reach parameters derived from inertial sensors: Comparison to 3D marker-based motion capture.

    Science.gov (United States)

    Cahill-Rowley, Katelyn; Rose, Jessica

    2017-02-08

    Reaching is a well-practiced functional task crucial to daily living activities, and temporal-spatial measures of reaching reflect function for both adult and pediatric populations with upper-extremity motor impairments. Inertial sensors offer a mobile and inexpensive tool for clinical assessment of movement. This research outlines a method for measuring temporal-spatial reach parameters using inertial sensors, and validates these measures with traditional marker-based motion capture. 140 reaches from 10 adults, and 30 reaches from nine children aged 18-20 months, were recorded and analyzed using both inertial-sensor and motion-capture methods. Inertial sensors contained three-axis accelerometers, gyroscopes, and magnetometers. Gravitational offset of accelerometer data was measured when the sensor was at rest, and removed using sensor orientation measured at rest and throughout the reach. Velocity was calculated by numeric integration of acceleration, using a null-velocity assumption at reach start. Sensor drift was neglected given the 1-2s required for a reach. Temporal-spatial reach parameters were calculated independently for each data acquisition method. Reach path length and distance, peak velocity magnitude and timing, and acceleration at contact demonstrated consistent agreement between sensor- and motion-capture-based methods, for both adult and toddler reaches, as evaluated by intraclass correlation coefficients from 0.61 to 1.00. Taken together with actual difference between method measures, results indicate that these functional reach parameters may be reliably measured with inertial sensors.

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

    Directory of Open Access Journals (Sweden)

    Martyna Poreba

    2015-01-01

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

  7. A robust linear feature-based procedure for automated registration of point clouds.

    Science.gov (United States)

    Poreba, Martyna; Goulette, François

    2015-01-14

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

  8. Orthogonal moments for determining correspondence between vessel bifurcations for retinal image registration.

    Science.gov (United States)

    Patankar, Sanika S; Kulkarni, Jayant V

    2015-05-01

    Retinal image registration is a necessary step in diagnosis and monitoring of Diabetes Retinopathy (DR), which is one of the leading causes of blindness. Long term diabetes affects the retinal blood vessels and capillaries eventually causing blindness. This progressive damage to retina and subsequent blindness can be prevented by periodic retinal screening. The extent of damage caused by DR can be assessed by comparing retinal images captured during periodic retinal screenings. During image acquisition at the time of periodic screenings translation, rotation and scale (TRS) are introduced in the retinal images. Therefore retinal image registration is an essential step in automated system for screening, diagnosis, treatment and evaluation of DR. This paper presents an algorithm for registration of retinal images using orthogonal moment invariants as features for determining the correspondence between the dominant points (vessel bifurcations) in the reference and test retinal images. As orthogonal moments are invariant to TRS; moment invariants features around a vessel bifurcation are unaltered due to TRS and can be used to determine the correspondence between reference and test retinal images. The vessel bifurcation points are located in segmented, thinned (mono pixel vessel width) retinal images and labeled in corresponding grayscale retinal images. The correspondence between vessel bifurcations in reference and test retinal image is established based on moment invariants features. Further the TRS in test retinal image with respect to reference retinal image is estimated using similarity transformation. The test retinal image is aligned with reference retinal image using the estimated registration parameters. The accuracy of registration is evaluated in terms of mean error and standard deviation of the labeled vessel bifurcation points in the aligned images. The experimentation is carried out on DRIVE database, STARE database, VARIA database and database provided

  9. Biomechanically constrained groupwise ultrasound to CT registration of the lumbar spine.

    Science.gov (United States)

    Gill, Sean; Abolmaesumi, Purang; Fichtinger, Gabor; Boisvert, Jonathan; Pichora, David; Borshneck, Dan; Mousavi, Parvin

    2012-04-01

    We present a groupwise US to CT registration algorithm for guiding percutaneous spinal interventions. In addition, we introduce a comprehensive validation scheme that accounts for changes in the curvature of the spine between preoperative and intraoperative imaging. In our registration methodology, each vertebra in CT is treated as a sub-volume and transformed individually. A biomechanical model is used to constrain the displacement of the vertebrae relative to one another. The sub-volumes are then reconstructed into a single volume. During each iteration of registration, an US image is simulated from the reconstructed CT volume and an intensity-based similarity metric is calculated with the real US image. Validation studies are performed on CT and US images from a sheep cadaver, five patient-based phantoms designed to preserve realistic curvatures of the spine and a sixth patient-based phantom where the curvature of the spine is changed between preoperative and intraoperative imaging. For datasets where the spine curve between two imaging modalities was artificially perturbed, the proposed methodology was able to register initial misalignments of up to 20mm with a success rate of 95%. For the phantom with a physical change in the curvature of the spine introduced between the US and CT datasets, the registration success rate was 98.5%. Finally, the registration success rate for the sheep cadaver with soft-tissue information was 87%. The results demonstrate that our algorithm allows for robust registration of US and CT datasets, regardless of a change in the patients pose between preoperative and intraoperative image acquisitions.

  10. Algorithmic cryptanalysis

    CERN Document Server

    Joux, Antoine

    2009-01-01

    Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic

  11. 76 FR 26291 - Pesticide Products; Registration Applications

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    2011-05-06

    ... Protection Agency, 1200 Pennsylvania Ave., NW., Washington, DC 20460-0001, and Biopesticides and Pollution... group; stonefruit group; strawberries; tree nut group. Contact: Daniel Peacock, Registration Division...: Pistachio. Contact: Shanaz Bacchus, Biopesticides and Pollution Prevention Division, (703) 308-8097,...

  12. 76 FR 38160 - Pesticide Products; Registration Applications

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    2011-06-29

    ... AGENCY Pesticide Products; Registration Applications AGENCY: Environmental Protection Agency (EPA). ACTION: Notice. SUMMARY: EPA has received applications to register pesticide products containing an... hereby providing notice of receipt and opportunity to comment on these applications. DATES: Comments must...

  13. 75 FR 3235 - Pesticide Products; Registration Applications

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  14. 75 FR 80490 - Pesticide Products; Registration Applications

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    ... AGENCY Pesticide Products; Registration Applications AGENCY: Environmental Protection Agency (EPA). ACTION: Notice. SUMMARY: EPA has received applications to register pesticide products containing active... providing notice of receipt and opportunity to comment on these applications. DATES: Comments must be...

  15. 76 FR 63298 - Pesticide Products; Registration Applications

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    2011-10-12

    ...] Pesticide Products; Registration Applications AGENCY: Environmental Protection Agency (EPA). ACTION: Notice. SUMMARY: EPA has received applications to register pesticide products containing active ingredients not... receipt and opportunity to comment on these applications. DATES: Comments must be received on or before...

  16. 75 FR 23759 - Pesticide Products; Registration Applications

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  18. 75 FR 24694 - Pesticide Products; Registration Applications

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    2010-05-05

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  19. 75 FR 8939 - Pesticide Products; Registration Applications

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  20. 75 FR 26754 - Pesticide Products; Registration Applications

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    2010-05-12

    ... Products; Registration Applications AGENCY: Environmental Protection Agency (EPA). ACTION: Notice. SUMMARY: EPA has received applications to register pesticide products containing active ingredients not... receipt and opportunity to comment on these applications. DATES: Comments must be received on or before...

  1. An active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on MRI: method and validation.

    Science.gov (United States)

    Duay, Valérie; Bresson, Xavier; Castro, Javier Sanchez; Pollo, Claudio; Cuadra, Meritxell Bach; Thiran, Jean-Philippe

    2008-01-01

    This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

  2. Quantification of tumor changes during neoadjuvant chemotherapy with longitudinal breast DCE-MRI registration

    Science.gov (United States)

    Wu, Jia; Ou, Yangming; Weinstein, Susan P.; Conant, Emily F.; Yu, Ning; Hoshmand, Vahid; Keller, Brad; Ashraf, Ahmed B.; Rosen, Mark; DeMichele, Angela; Davatzikos, Christos; Kontos, Despina

    2015-03-01

    Imaging plays a central role in the evaluation of breast tumor response to neoadjuvant chemotherapy. Image-based assessment of tumor change via deformable registration is a powerful, quantitative method potentially to explore novel information of tumor heterogeneity, structure, function, and treatment response. In this study, we continued a previous pilot study to further validate the feasibility of an open source deformable registration algorithm DRAMMS developed within our group as a means to analyze spatio-temporal tumor changes for a set of 14 patients with DCE-MR imaging. Two experienced breast imaging radiologists marked landmarks according to their anatomical meaning on image sets acquired before and during chemotherapy. Yet, chemotherapy remarkably changed the anatomical structure of both tumor and normal breast tissue, leading to significant discrepancies between both raters for landmarks in certain areas. Therefore, we proposed a novel method to grade the manually denoted landmarks into different challenge levels based on the inter-rater agreement, where a high level indicates significant discrepancies and considerable amounts of anatomical structure changes, which would indeed impose giant problem for the following registration algorithm. It is interesting to observe that DRAMMS performed in a similar manner as the human raters: landmark errors increased as inter-rater differences rose. Among all selected six deformable registration algorithms, DRAMMS achieves the highest overall accuracy, which is around 5.5 mm, while the average difference between human raters is 3 mm. Moreover, DRAMMS performed consistently well within both tumor and normal tissue regions. Lastly, we comprehensively tuned the fundamental parameters of DRAMMS to better understand DRAMMS to guide similar works in the future. Overall, we further validated that DRAMMS is a powerful registration tool to accurately quantify tumor changes and potentially predict early tumor response to

  3. VBM with viscous fluid registration of grey matter segments in SPM.

    Directory of Open Access Journals (Sweden)

    João M. S. Pereira

    2013-07-01

    Full Text Available Improved registration of grey matter segments in SPM has been achieved with the DARTEL algorithm. Previous work from our group suggested, however, that such improvements may not translate to studies of clinical groups. To address the registration issue in atrophic brains, this paper relaxed the condition of diffeomorphism, central to DARTEL, and made use of a viscous fluid registration model with limited regularisation constraints to register the modulated grey matter probability maps to an intra-population template. Quantitative analysis of the registration results after the additional viscous fluid step showed no worsening of co-localisation of fiducials compared to DARTEL or unified segmentation methods, and the resulting voxel based morphometry (VBM analyses were able to better identify atrophic regions and to produce results with fewer apparent false positives. DARTEL showed great sensitivity to atrophy, but the resulting VBM maps presented broad, amorphous regions of significance that are hard to interpret. We propose that the condition of diffeomorphism is not necessary for basic VBM studies in atrophic populations, but also that it has disadvantages that must be taken into consideration before a study. The presented viscous fluid registration method is proposed for VBM studies to enhance sensitivity and localizing power.

  4. VBM with viscous fluid registration of gray matter segments in SPM.

    Science.gov (United States)

    Pereira, Joao M S; Acosta-Cabronero, Julio; Pengas, George; Xiong, Li; Nestor, Peter J; Williams, Guy B

    2013-01-01

    Improved registration of gray matter segments in SPM has been achieved with the DARTEL algorithm. Previous work from our group suggested, however, that such improvements may not translate to studies of clinical groups. To address the registration issue in atrophic brains, this paper relaxed the condition of diffeomorphism, central to DARTEL, and made use of a viscous fluid registration model with limited regularization constraints to register the modulated gray matter probability maps to an intra-population template. Quantitative analysis of the registration results after the additional viscous fluid step showed no worsening of co-localization of fiducials compared to DARTEL or unified segmentation methods, and the resulting voxel based morphometry (VBM) analyses were able to better identify atrophic regions and to produce results with fewer apparent false positives. DARTEL showed great sensitivity to atrophy, but the resulting VBM maps presented broad, amorphous regions of significance that are hard to interpret. We propose that the condition of diffeomorphism is not necessary for basic VBM studies in atrophic populations, but also that it has disadvantages that must be taken into consideration before a study. The presented viscous fluid registration method is proposed for VBM studies to enhance sensitivity and localizing power.

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

    Science.gov (United States)

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

    2014-12-01

    Many applications in medical imaging include image registration for matching of images from the same or different modalities. In the case of full data sampling, the respective reconstructed images are usually of such a good image quality that standard deformable volume-to-volume (3D-3D) registration approaches can be applied. But research in temporal-correlated image reconstruction and dose reductions increases the number of cases where rawdata are available from only few projection angles. Here, deteriorated image quality leads to non-acceptable deformable volume-to-volume registration results. Therefore a registration approach is required that is robust against a decreasing number of projections defining the target position. We propose a deformable volume-to-rawdata (3D-2D) registration method that aims at finding a displacement vector field maximizing the alignment of a CT volume and the acquired rawdata based on the sum of squared differences in rawdata domain. The registration is constrained by a regularization term in accordance with a fluid-based diffusion. Both cost function components, the rawdata fidelity and the regularization term, are optimized in an alternating manner. The matching criterion is optimized by a conjugate gradient descent for nonlinear functions, while the regularization is realized by convolution of the vector fields with Gaussian kernels. We validate the proposed method and compare it to the demons algorithm, a well-known 3D-3D registration method. The comparison is done for a range of 4-60 target projections using datasets from low dose tomographic fluoroscopy as an application example. The results show a high correlation to the ground truth target position without introducing artifacts even in the case of very few projections. In particular the matching in the rawdata domain is improved compared to the 3D-3D registration for the investigated range. The proposed volume-to-rawdata registration increases the robustness regarding sparse

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

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Yuan-Jen [Department of Management Information Systems, Central Taiwan University of Science and Technology, No. 666, Buzih Rd., Beitun District, Taichung City, Taiwan (R.O.C.) (China); Institute of Biomedical Engineering and Materials Science, Central Taiwan University of Science and Technology, No. 666, Buzih Rd., Beitun District, Taichung City, Taiwan (R.O.C.) (China); Yao, Chun-Hsu [School of Chinese Medicine, China Medical University, Taichung, Taiwan (R.O.C.) (China); Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan (R.O.C.) (China); Department of Biomedical Informatics, Asia University, Taichung, Taiwan (R.O.C.) (China); Wu, Jay [Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan (R.O.C.) (China); Hsieh, Bor-Tsung [Department of Biomedical Imaging and Radiological Sciences, Central Taiwan University of Science and Technology, Taichung, Taiwan (R.O.C.) (China); Tsang, Yuk-Wah [Department of Radiation Oncology, Ditmanson Medical Foundation Chiayi Christian Hospital, Chiayi, Taiwan (R.O.C.) (China); Chen, Chin-Hsing [Department of Management Information Systems, Central Taiwan University of Science and Technology, No. 666, Buzih Rd., Beitun District, Taichung City, Taiwan (R.O.C.) (China)

    2015-06-01

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

  7. 76 FR 61563 - Voluntary Surrender of Certificate of Registration

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    ...: DEA is amending its regulations to clarify the registration status of a registrant who voluntarily... INFORMATION: Background Under current regulations, the DEA registration of any person terminates ``if and when... registration. DEA regulations, however, do not require further action by DEA's Administrator to terminate a DEA...

  8. 47 CFR 1.8001 - FCC Registration Number (FRN).

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    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false FCC Registration Number (FRN). 1.8001 Section 1.8001 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE FCC Registration Number § 1.8001 FCC Registration Number (FRN). (a) The FCC Registration Number (FRN) is a...

  9. 46 CFR 402.220 - Registration of pilots.

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    2010-10-01

    ... 46 Shipping 8 2010-10-01 2010-10-01 false Registration of pilots. 402.220 Section 402.220 Shipping... ORDERS Registration of Pilots § 402.220 Registration of pilots. (a) Each applicant pilot must complete the number of round trips specified in this section prior to registration as a U.S. registered pilot...

  10. A Frequency Domain Approach to Registration of Aliased Images with Application to Super-resolution

    Directory of Open Access Journals (Sweden)

    Vandewalle Patrick

    2006-01-01

    Full Text Available Super-resolution algorithms reconstruct a high-resolution image from a set of low-resolution images of a scene. Precise alignment of the input images is an essential part of such algorithms. If the low-resolution images are undersampled and have aliasing artifacts, the performance of standard registration algorithms decreases. We propose a frequency domain technique to precisely register a set of aliased images, based on their low-frequency, aliasing-free part. A high-resolution image is then reconstructed using cubic interpolation. Our algorithm is compared to other algorithms in simulations and practical experiments using real aliased images. Both show very good visual results and prove the attractivity of our approach in the case of aliased input images. A possible application is to digital cameras where a set of rapidly acquired images can be used to recover a higher-resolution final image.

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

    Science.gov (United States)

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

    2014-11-01

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

  12. RRS: Replica Registration Service for Data Grids

    Energy Technology Data Exchange (ETDEWEB)

    Shoshani, Arie; Sim, Alex; Stockinger, Kurt

    2005-07-15

    Over the last few years various scientific experiments and Grid projects have developed different catalogs for keeping track of their data files. Some projects use specialized file catalogs, others use distributed replica catalogs to reference files at different locations. Due to this diversity of catalogs, it is very hard to manage files across Grid projects, or to replace one catalog with another. In this paper we introduce a new Grid service called the Replica Registration Service (RRS). It can be thought of as an abstraction of the concepts for registering files and their replicas. In addition to traditional single file registration operations, the RRS supports collective file registration requests and keeps persistent registration queues. This approach is of particular importance for large-scale usage where thousands of files are copied and registered. Moreover, the RRS supports a set of error directives that are triggered in case of registration failures. Our goal is to provide a single uniform interface for various file catalogs to support the registration of files across multiple Grid projects, and to make Grid clients oblivious to the specific catalog used.

  13. Echocardiography to magnetic resonance image registration for use in image-guided cardiac catheterization procedures

    Energy Technology Data Exchange (ETDEWEB)

    Ma Yingliang; Penney, Graeme P; Razavi, Reza; Rhode, Kawal S [Division of Imaging Sciences, King' s College, London SE1 7EH (United Kingdom); Rinaldi, C Aldo; Cooklin, Mike [Department of Cardiology, Guy' s and St Thomas' NHS Foundation Trust, London, SE1 7EH (United Kingdom)], E-mail: y.ma@kcl.ac.uk

    2009-08-21

    We present a robust method to register three-dimensional echocardiography (echo) images to magnetic resonance images (MRI) based on anatomical features, which is designed to be used in the registration pipeline for overlaying MRI-derived roadmaps onto two-dimensional live x-ray images during cardiac catheterization procedures. The features used in image registration are the endocardial surface of the left ventricle and the centre line of the descending aorta. The MR-derived left ventricle surface is generated using a fully automated algorithm, and the echo-derived left ventricle surface is produced using a semi-automatic segmentation method provided by the QLab software (Philips Healthcare) that it is routinely used in clinical practice. We test our method on data from six volunteers and four patients. We validated registration accuracy using two methods: the first calculated a root mean square distance error using expert identified anatomical landmarks, and the second method used catheters as landmarks in two clinical electrophysiology procedures. Results show a mean error of 4.1 mm, which is acceptable for our clinical application, and no failed registrations were observed. In addition, our algorithm works on clinical data, is fast and only requires a small amount of manual input, and so it is applicable for use during cardiac catheterization procedures.

  14. Comparing nonrigid registration techniques for motion corrected MR prostate diffusion imaging

    Energy Technology Data Exchange (ETDEWEB)

    Buerger, C., E-mail: christian.buerger@philips.com; Sénégas, J.; Kabus, S.; Carolus, H.; Schulz, H.; Renisch, S. [Philips Research Hamburg, Hamburg 22335 (Germany); Agarwal, H. [Philips Research North America, Briarcliff Manor, New York 10510 and Molecular Imaging Program, NCI, National Institute of Health, Bethesda, Maryland 20892 (United States); Turkbey, B.; Choyke, P. L. [Molecular Imaging Program, NCI, National Institute of Health, Bethesda, Maryland 20892 (United States)

    2015-01-15

    Purpose: T{sub 2}-weighted magnetic resonance imaging (MRI) is commonly used for anatomical visualization in the pelvis area, such as the prostate, with high soft-tissue contrast. MRI can also provide functional information such as diffusion-weighted imaging (DWI) which depicts the molecular diffusion processes in biological tissues. The combination of anatomical and functional imaging techniques is widely used in oncology, e.g., for prostate cancer diagnosis and staging. However, acquisition-specific distortions as well as physiological motion lead to misalignments between T{sub 2} and DWI and consequently to a reduced diagnostic value. Image registration algorithms are commonly employed to correct for such misalignment. Methods: The authors compare the performance of five state-of-the-art nonrigid image registration techniques for accurate image fusion of DWI with T{sub 2}. Results: Image data of 20 prostate patients with cancerous lesions or cysts were acquired. All registration algorithms were validated using intensity-based as well as landmark-based techniques. Conclusions: The authors’ results show that the “fast elastic image registration” provides most accurate results with a target registration error of 1.07 ± 0.41 mm at minimum execution times of 11 ± 1 s.

  15. A transformation similarity constraint for groupwise nonlinear registration in longitudinal neuroimaging studies

    Science.gov (United States)

    Fleishman, Greg M.; Gutman, Boris A.; Fletcher, P. Thomas; Thompson, Paul

    2015-03-01

    Patients with Alzheimer's disease and other brain disorders often show a similar spatial distribution of volume change throughout the brain over time, but this information is not yet used in registration algorithms to refine the quantification of change. Here, we develop a mathematical basis to incorporate that prior information into a longitudinal structural neuroimaging study. We modify the canonical minimization problem for non-linear registration to include a term that couples a collection of registrations together to enforce group similarity. More specifically, throughout the computation we maintain a group-level representation of the transformations and constrain updates to individual transformations to be similar to this representation. The derivations necessary to produce the Euler-Lagrange equations for the coupling term are presented and a gradient descent algorithm based on the formulation was implemented. We demonstrate using 57 longitudinal image pairs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) that longitudinal registration with such a groupwise coupling prior is more robust to noise in estimating change, suggesting such change maps may have several important applications.

  16. Algorithmic mathematics

    CERN Document Server

    Hougardy, Stefan

    2016-01-01

    Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.

  17. Image navigation and registration for the geostationary lightning mapper (GLM)

    Science.gov (United States)

    van Bezooijen, Roel W. H.; Demroff, Howard; Burton, Gregory; Chu, Donald; Yang, Shu S.

    2016-10-01

    The Geostationary Lightning Mappers (GLM) for the Geostationary Operational Environmental Satellite (GOES) GOES-R series will, for the first time, provide hemispherical lightning information 24 hours a day from longitudes of 75 and 137 degrees west. The first GLM of a series of four is planned for launch in November, 2016. Observation of lightning patterns by GLM holds promise to improve tornado warning lead times to greater than 20 minutes while halving the present false alarm rates. In addition, GLM will improve airline traffic flow management, and provide climatology data allowing us to understand the Earth's evolving climate. The paper describes the method used for translating the pixel position of a lightning event to its corresponding geodetic longitude and latitude, using the J2000 attitude of the GLM mount frame reported by the spacecraft, the position of the spacecraft, and the alignment of the GLM coordinate frame relative to its mount frame. Because the latter alignment will experience seasonal variation, this alignment is determined daily using GLM background images collected over the previous 7 days. The process involves identification of coastlines in the background images and determination of the alignment change necessary to match the detected coastline with the coastline predicted using the GSHHS database. Registration is achieved using a variation of the Lucas-Kanade algorithm where we added a dither and average technique to improve performance significantly. An innovative water mask technique was conceived to enable self-contained detection of clear coastline sections usable for registration. Extensive simulations using accurate visible images from GOES13 and GOES15 have been used to demonstrate the performance of the coastline registration method, the results of which are presented in the paper.

  18. A hybrid biomechanical intensity based deformable image registration of lung 4DCT

    Science.gov (United States)

    Samavati, Navid; Velec, Michael; Brock, Kristy

    2015-04-01

    Deformable image registration (DIR) has been extensively studied over the past two decades due to its essential role in many image-guided interventions (IGI). IGI demands a highly accurate registration that maintains its accuracy across the entire region of interest. This work evaluates the improvement in accuracy and consistency by refining the results of Morfeus, a biomechanical model-based DIR algorithm. A hybrid DIR algorithm is proposed based on, a biomechanical model-based DIR algorithm and a refinement step based on a B-spline intensity-based algorithm. Inhale and exhale reconstructions of four-dimensional computed tomography (4DCT) lung images from 31 patients were initially registered using the biomechanical DIR by modeling contact surface between the lungs and the chest cavity. The resulting deformations were then refined using the intensity-based algorithm to reduce any residual uncertainties. Important parameters in the intensity-based algorithm, including grid spacing, number of pyramids, and regularization coefficient, were optimized on 10 randomly-chosen patients (out of 31). Target registration error (TRE) was calculated by measuring the Euclidean distance of common anatomical points on both images after registration. For each patient a minimum of 30 points/lung were used. Grid spacing of 8 mm, 5 levels of grid pyramids, and regularization coefficient of 3.0 were found to provide optimal results on 10 randomly chosen patients. Overall the entire patient population (n = 31), the hybrid method resulted in mean ± SD (90th%) TRE of 1.5 ± 1.4 (2.9) mm compared to 3.1 ± 1.9 (5.6) using biomechanical DIR and 2.6 ± 2.5 (6.1) using intensity-based DIR alone. The proposed hybrid biomechanical modeling intensity based algorithm is a promising DIR technique which could be used in various IGI procedures. The current investigation shows the efficacy of this approach for the registration of 4DCT images of the lungs with average accuracy of 1.5 mm.

  19. Central research registration at Technical University of Denmark (DTU)

    DEFF Research Database (Denmark)

    Sand, Ane Ahrenkiel

    Some five years ago, DTU switched from decentralized research registration, where researchers entered their publications into the DTU research repository themselves to centralized research registration, whereby library staff upload academic publications to the repository on behalf...... of the researchers. The implementation of the centralization process was accompanied by, and depended on, the establishment of a research registration team at the DTU Library. This session shares DTU’s five years of experience with centralized research registration, including: the implementation process, the setting...... up the registration team, the configuration of the repository platform (Pure), the registration workflow and last but not least the results since DTU switched to centralized research registration....

  20. Global registration of subway tunnel point clouds using an augmented extended Kalman filter and central-axis constraint.

    Science.gov (United States)

    Kang, Zhizhong; Chen, Jinlei; Wang, Baoqian

    2015-01-01

    Because tunnels generally have tubular shapes, the distribution of tie points between adjacent scans is usually limited to a narrow region, which makes the problem of registration error accumulation inevitable. In this paper, a global registration method is proposed based on an augmented extended Kalman filter and a central-axis constraint. The point cloud registration is regarded as a stochastic system, and the global registration is considered to be a process that recursively estimates the rigid transformation parameters between each pair of adjacent scans. Therefore, the augmented extended Kalman filter (AEKF) is used to accurately estimate the rigid transformation parameters by eliminating the error accumulation caused by the pair-wise registration. Moreover, because the scanning range of a terrestrial laser scanner can reach hundreds of meters, a single scan can cover a tunnel segment with a length of more than one hundred meters, which means that the central axis extracted from the scan can be employed to control the registration of multiple scans. Therefore, the central axis of the subway tunnel is first determined through the 2D projection of the tunnel point cloud and curve fitting using the RANSAC (RANdom SAmple Consensus) algorithm. Because the extraction of the central axis by quadratic curve fitting may suffer from noise in the tunnel points and from variations in the tunnel, we present a global extraction algorithm that is based on segment-wise quadratic curve fitting. We then derive the central-axis constraint as an additional observation model of AEKF to optimize the registration parameters between each pair of adjacent scans. The proposed approach is tested on terrestrial point clouds that were acquired in a subway tunnel. The results show that the proposed algorithm is capable of improving the accuracy of aligning multiple scans by 48%.

  1. A survey of medical image registration - under review.

    Science.gov (United States)

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

    2016-10-01

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

  2. Quantum Algorithms

    Science.gov (United States)

    Abrams, D.; Williams, C.

    1999-01-01

    This thesis describes several new quantum algorithms. These include a polynomial time algorithm that uses a quantum fast Fourier transform to find eigenvalues and eigenvectors of a Hamiltonian operator, and that can be applied in cases for which all know classical algorithms require exponential time.

  3. Total algorithms

    NARCIS (Netherlands)

    Tel, G.

    1993-01-01

    We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of distri

  4. A novel point cloud registration using 2D image features

    Science.gov (United States)

    Lin, Chien-Chou; Tai, Yen-Chou; Lee, Jhong-Jin; Chen, Yong-Sheng

    2017-01-01

    Since a 3D scanner only captures a scene of a 3D object at a time, a 3D registration for multi-scene is the key issue of 3D modeling. This paper presents a novel and an efficient 3D registration method based on 2D local feature matching. The proposed method transforms the point clouds into 2D bearing angle images and then uses the 2D feature based matching method, SURF, to find matching pixel pairs between two images. The corresponding points of 3D point clouds can be obtained by those pixel pairs. Since the corresponding pairs are sorted by their distance between matching features, only the top half of the corresponding pairs are used to find the optimal rotation matrix by the least squares approximation. In this paper, the optimal rotation matrix is derived by orthogonal Procrustes method (SVD-based approach). Therefore, the 3D model of an object can be reconstructed by aligning those point clouds with the optimal transformation matrix. Experimental results show that the accuracy of the proposed method is close to the ICP, but the computation cost is reduced significantly. The performance is six times faster than the generalized-ICP algorithm. Furthermore, while the ICP requires high alignment similarity of two scenes, the proposed method is robust to a larger difference of viewing angle.

  5. Volume-Preserving Mapping and Registration for Collective Data Visualization.

    Science.gov (United States)

    Hu, Jiaxi; Zou, Guangyu Jeff; Hua, Jing

    2014-12-01

    In order to visualize and analyze complex collective data, complicated geometric structure of each data is desired to be mapped onto a canonical domain to enable map-based visual exploration. This paper proposes a novel volume-preserving mapping and registration method which facilitates effective collective data visualization. Given two 3-manifolds with the same topology, there exists a mapping between them to preserve each local volume element. Starting from an initial mapping, a volume restoring diffeomorphic flow is constructed as a compressible flow based on the volume forms at the manifold. Such a flow yields equality of each local volume element between the original manifold and the target at its final state. Furthermore, the salient features can be used to register the manifold to a reference template by an incompressible flow guided by a divergence-free vector field within the manifold. The process can retain the equality of local volume elements while registering the manifold to a template at the same time. An efficient and practical algorithm is also presented to generate a volume-preserving mapping and a salient feature registration on discrete 3D volumes which are represented with tetrahedral meshes embedded in 3D space. This method can be applied to comparative analysis and visualization of volumetric medical imaging data across subjects. We demonstrate an example application in multimodal neuroimaging data analysis and collective data visualization.

  6. Robust image registration using adaptive coherent point drift method

    Science.gov (United States)

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

    2016-04-01

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

  7. Distance-Dependent Multimodal Image Registration for Agriculture Tasks

    Directory of Open Access Journals (Sweden)

    Ron Berenstein

    2015-08-01

    Full Text Available Image registration is the process of aligning two or more images of the same scene taken at different times; from different viewpoints; and/or by different sensors. This research focuses on developing a practical method for automatic image registration for agricultural systems that use multimodal sensory systems and operate in natural environments. While not limited to any particular modalities; here we focus on systems with visual and thermal sensory inputs. Our approach is based on pre-calibrating a distance-dependent transformation matrix (DDTM between the sensors; and representing it in a compact way by regressing the distance-dependent coefficients as distance-dependent functions. The DDTM is measured by calculating a projective transformation matrix for varying distances between the sensors and possible targets. To do so we designed a unique experimental setup including unique Artificial Control Points (ACPs and their detection algorithms for the two sensors. We demonstrate the utility of our approach using different experiments and evaluation criteria.

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

    Science.gov (United States)

    Diaz, Idanis; Boulanger, Pierre

    2015-08-01

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

  9. Central Research Registration at Technical University of Denmark (DTU)

    DEFF Research Database (Denmark)

    Sand, Ane Ahrenkiel

    of the researchers. The implementation of the centralization process was accompanied by, and depended on, the establishment of a research registration team at the DTU Library. This session shares DTU’s five years of experience with centralized research registration, including: the implementation process, the setting...... up the registration team, the configuration of the repository platform (Pure), the registration workflow and last but not least the results since DTU switched to centralized research registration....

  10. Efficient 3D rigid-body registration of micro-MR and micro-CT trabecular bone images

    Science.gov (United States)

    Rajapakse, C. S.; Magland, J.; Wehrli, S. L.; Zhang, X. H.; Liu, X. S.; Guo, X. E.; Wehrli, F. W.

    2008-03-01

    Registration of 3D images acquired from different imaging modalities such as micro-magnetic resonance imaging (µMRI) and micro-computed tomography (µCT) are of interest in a number of medical imaging applications. Most general-purpose multimodality registration algorithms tend to be computationally intensive and do not take advantage of the shape of the imaging volume. Multimodality trabecular bone (TB) images of cylindrical cores, for example, tend to be misaligned along and around the axial direction more than that around other directions. Additionally, TB images acquired by µMRI can differ substantially from those acquired by µCT due to apparent trabecular thickening from magnetic susceptibility boundary effects and non-linear intensity correspondence. However, they share very similar contrast characteristics since the images essentially represent a binary tomographic system. The directional misalignment and the fundamental similarities of the two types of images can be exploited to achieve fast 3D registration. Here we present an intensity cross-correlation based 3D registration algorithm for registering 3D specimen images from cylindrical cores of cadaveric TB acquired by µMRI and µCT in the context of finite-element modeling to assess the bone's mechanical constants. The algorithm achieves the desired registration by first coarsely approximating the three translational and three rotational parameters required to align the µMR images to the µCT scan coordinate frame and fine-tuning the parameters in the neighborhood of the approximate solution. The algorithm described here is suitable for 3D rigid-body image registration applications where through-plane rotations are known to be relatively small. The accuracy of the technique is constrained by the image resolution and in-plane angular increments used.

  11. 一种新的扫描点云自动配准方法%A New Automatic Registration Method of Scanning Point Cloud

    Institute of Scientific and Technical Information of China (English)

    钱鹏鹏; 郑德华

    2013-01-01

      点云数据配准是三维激光数据处理的关键问题,结合曲率进行配准是点云配准非常有效的一种方式。为了提高配准的速度和精度,针对点云曲率和RANSAC算法的特点和应用,分析了两种方法之间的优缺点。研究了一种结合曲率的RANSAC点云配准算法,并利用改进的ICP算法对点云进行精确配准。结果表明:基于曲率的RANSAC算法能够显著提高初始配准的速度和精度,同时改进的ICP算法比原有ICP算法提高了二次配准的速度和精度。%The point cloud data registration is the key issue of 3-d laser data processing .The point cloud registration combined with curvature distribution is a very effective away .In order to improve the registration speed and precision ,in view of the characters and application of point cloud curvature and RANSAC algorithm ,the advantages and disadvantages of the two methods are analyzed here .Then ,a RANSAC point cloud registration algorithm combined with curvature is studied ,and the improved ICP algorithm is used for point cloud registration .The results show that :the RANSAC algo-rithm based on curvature can significantly improve the initial registration speed and precision ,at the same time ,the im-proved ICP algorithm can significanlly improve the secondary registration speed and precision compared with the original ICP algorithm .

  12. 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.

  13. The Experimental Research on the Frameless Registration of DSA/CT Images

    Institute of Scientific and Technical Information of China (English)

    HUANG Yong-feng; LI Wen; ZENG Pei-feng; ZHAO Jun

    2006-01-01

    DSA images show vessels with clarity and CT images show bones distinctly. In this paper, we present an experimental research on the frameless registration of DSA/CT images based on localization algorithm. With four external markers, the vessels and bones in human brain can be integrated. The mean accuracy of simulated experiment is about 2.0 mm. The experiment proved that the 3D images composed cerebral anatomy and vasculature could help neurosurgeons perform accurate diagnosis and make right operation planning.

  14. Reliability of registrations : a feasibility study into registration of occupational and educational titles in hospitals

    NARCIS (Netherlands)

    Popping, R

    Some results of an investigation are presented in which answers on some basic variables (occupation and education) are registered in several ways. The variables were measured in a setting in which the registration was to occur as fast as possible. All registrations went by using a computer. The

  15. Reliability of registrations : a feasibility study into registration of occupational and educational titles in hospitals

    NARCIS (Netherlands)

    Popping, R

    1997-01-01

    Some results of an investigation are presented in which answers on some basic variables (occupation and education) are registered in several ways. The variables were measured in a setting in which the registration was to occur as fast as possible. All registrations went by using a computer. The regi

  16. COMPACT SUPPORT THIN PLATE SPLINE ALGORITHM

    Institute of Scientific and Technical Information of China (English)

    Li Jing; Yang Xuan; Yu Jianping

    2007-01-01

    Common tools based on landmarks in medical image elastic registration are Thin Plate Spline (TPS) and Compact Support Radial Basis Function (CSRBF). TPS forces the corresponding landmarks to exactly match each other and minimizes the bending energy of the whole image. However,in real application, such scheme would deform the image globally when deformation is only local.CSRBF needs manually determine the support size, although its deformation is limited local. Therefore,to limit the effect of the deformation, new Compact Support Thin Plate Spline algorithm (CSTPS) is approached, analyzed and applied. Such new approach gains optimal mutual information, which shows its registration result satisfactory. The experiments also show it can apply in both local and global elastic registration.

  17. Dynamic lung modeling and tumor tracking using deformable image registration and geometric smoothing.

    Science.gov (United States)

    Zhang, Yongjie; Jing, Yiming; Liang, Xinghua; Xu, Guoliang; Dong, Lei

    2012-09-01

    A greyscale-based fully automatic deformable image registration algorithm, based on an optical flow method together with geometric smoothing, is developed for dynamic lung modeling and tumor tracking. In our computational processing pipeline, the input data is a set of 4D CT images with 10 phases. The triangle mesh of the lung model is directly extracted from the more stable exhale phase (Phase 5). In addition, we represent the lung surface model in 3D volumetric format by applying a signed distance function and then generate tetrahedral meshes. Our registration algorithm works for both triangle and tetrahedral meshes. In CT images, the intensity value reflects the local tissue density. For each grid point, we calculate the displacement from the static image (phase 5) to match with the moving image (other phases) by using merely intensity values of the CT images. The optical flow computation is followed by a regularization of the deformation field using geometric smoothing. Lung volume change and the maximum lung tissue movement are used to evaluate the accuracy of the application. Our testing results suggest that the application of deformable registration algorithm is an effective way for delineating and tracking tumor motion in image-guided radiotherapy.

  18. Registration Based Retrieval using Texture Measures

    Directory of Open Access Journals (Sweden)

    Swarnambiga AYYACHAMY

    2015-09-01

    Full Text Available The aim of the study presented in this manuscript was to develop and analyze registration based retrieval of medical image using texture measures. Three main methods are implemented in this work. The first method includes Affine transformation, Demons and Affine with B-spline. The second method implemented is medical image retrieval system using content based medical image retrieval. GLCM, LBP and GLCM with LBP are used for texture based retrieval. Shape based retrieval is processed using canny edge with the Otsu method. From registration based retrieval, Affine with B-Spline performs well and produces best result by increasing the retrieval rate and the next better performances are given by Demons and Affine registration. The results showed that the best results for registration based retrieval are given by Affine with B-Spline registration based retrieval using GLCM+LBP with (100/50. Based on more relevant retrieved images, Brain (100/50 and Knee (100/50 observed to have more relevant retrieved images.

  19. Socioeconomic determinants of birth registration in Ghana.

    Science.gov (United States)

    Amo-Adjei, Joshua; Annim, Samuel Kobina

    2015-06-15

    Identity registration is not only a matter of human rights but it also serves as an important instrument for planning about health, education and overall development. This paper examines the chances of a child born in Ghana between 2001 and 2006 obtaining legal status of identity. Data for this paper were extracted from the 2006 Ghana Multiple Indicator Cluster Survey (MICS). We used discrete choice modelling in estimating the likelihood of child registration in Ghana. Mother's education and household wealth are identified to be positively associated with the likelihood of a child being registered. In the context of structural factors, being a resident in the Eastern region of Ghana and rural areas were found to be risk factors for children not being registered. Besides, children who were resident in households where the head is affiliated to Traditional Religion were found to be at significant risk of being unregistered. Overall, our findings give an impression of birth registration being a privilege for children whose parents are educated, wealthy and resident in urban communities. Policies meant to increase uptake have to be broad-based, targeting the less privileged particularly with practical interventions such as transport vouchers to registration centres. This may help appropriate meaning to international protocols on birth registration as a human right issue to which Ghana affirms.

  20. Registration of renal SPECT and 2.5D US images.

    Science.gov (United States)

    Galdames, Francisco J; Perez, Claudio A; Estévez, Pablo A; Held, Claudio M; Jaillet, Fabrice; Lobo, Gabriel; Donoso, Gilda; Coll, Claudia

    2011-06-01

    Image registration is the process of transforming different image data sets of an object into the same coordinate system. This is a relevant task in the field of medical imaging; one of its objectives is to combine information from different imaging modalities. The main goal of this study is the registration of renal SPECT (Single Photon Emission Computerized Tomography) images and a sparse set of ultrasound slices (2.5D US), combining functional and anatomical information. Registration is performed after kidney segmentation in both image types. The SPECT segmentation is achieved using a deformable model based on a simplex mesh. The 2.5D US image segmentation is carried out in each of the 2D slices employing a deformable contour and Gabor filters to capture multi-scale image features. Moreover, a renal medulla detection method was developed to improve the US segmentation. A nonlinear optimization algorithm is used for the registration. In this process, movements caused by patient breathing during US image acquisition are also corrected. Only a few reports describe registration between SPECT images and a sparse set of US slices of the kidney, and they usually employ an optical localizer, unlike our method, that performs movement correction using information only from the SPECT and US images. Moreover, it does not require simultaneous acquisition of both image types. The registration method and both segmentations were evaluated separately. The SPECT segmentation was evaluated qualitatively by medical experts, obtaining a score of 5 over a scale from 1 to 5, where 5 represents a perfect segmentation. The 2.5D US segmentation was evaluated quantitatively, by comparing our method with an expert manual segmentation, and obtaining an average error of 3.3mm. The registration was evaluated quantitatively and qualitatively. Quantitatively the distance between the manual segmentation of the US images and the model extracted from the SPECT image was measured, obtaining an

  1. 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.

  2. ALGORITHM OF PRETREATMENT ON AUTOMOBILE BODY POINT CLOUD

    Institute of Scientific and Technical Information of China (English)

    GAO Feng; ZHOU Yu; DU Farong; QU Weiwei; XIONG Yonghua

    2007-01-01

    As point cloud of one whole vehicle body has the traits of large geometric dimension, huge data and rigorous reverse precision, one pretreatment algorithm on automobile body point cloud is put forward. The basic idea of the registration algorithm based on the skeleton points is to construct the skeleton points of the whole vehicle model and the mark points of the separate point cloud, to search the mapped relationship between skeleton points and mark points using congruence triangle method and to match the whole vehicle point cloud using the improved iterative closed point (ICP) algorithm. The data reduction algorithm, based on average square root of distance, condenses data by three steps, Computing datasets' average square root of distance in sampling cube grid, sorting order according to the value computed from the first step, choosing sampling percentage. The accuracy of the two algorithms above is proved by a registration and reduction example of whole vehicle point cloud of a certain light truck.

  3. Registration of a needle-positioning robot to high-resolution 3D ultrasound and computed tomography for image-guided interventions in small animals

    Science.gov (United States)

    Waspe, Adam C.; Lacefield, James C.; Holdsworth, David W.; Fenster, Aaron

    2008-03-01

    Preclinical research often requires the delivery of biological substances to specific locations in small animals. Guiding a needle to targets in small animals with an error animal imaging systems. Both techniques involve moving the needle to predetermined robot coordinates and determining corresponding needle locations in image coordinates. Registration accuracy will therefore be affected by the robot positioning error and is assessed by measuring the target registration error (TRE). A point-based registration between robot and micro-ultrasound coordinates was accomplished by attaching a fiducial phantom onto the needle. A TRE of 145 μm was achieved when moving the needle to a set of robot coordinates and registering the coordinates to needle tip locations determined from ultrasound fiducial measurements. Registration between robot and micro-CT coordinates was accomplished by injecting barium sulfate into tracks created when the robot withdraws the needle from a phantom. Points along cross-sectional slices of the segmented needle tracks were determined using an intensity-weighted centroiding algorithm. A minimum distance TRE of 194 +/- 18 μm was achieved by registering centroid points to robot trajectories using the iterative closest point (ICP) algorithm. Simulations, incorporating both robot and ultrasound fiducial localization errors, verify that robot error is a significant component of the experimental registration. Simulations of micro-CT to robot ICP registration similarly agree with the experimental results. Both registration techniques produce a TRE < 200 μm, meeting design specification.

  4. Construction of an SSR and RAD-Marker Based Molecular Linkage Map of Vigna vexillata (L.) A. Rich.

    Science.gov (United States)

    Marubodee, Rusama; Ogiso-Tanaka, Eri; Isemura, Takehisa; Chankaew, Sompong; Kaga, Akito; Naito, Ken; Ehara, Hiroshi; Tomooka, Norihiko

    2015-01-01

    Vigna vexillata (L.) A. Rich. (tuber cowpea) is an underutilized crop for consuming its tuber and mature seeds. Wild form of V. vexillata is a pan-tropical perennial herbaceous plant which has been used by local people as a food. Wild V. vexillata has also been considered as useful gene(s) source for V. unguiculata (cowpea), since it was reported to have various resistance gene(s) for insects and diseases of cowpea. To exploit the potential of V. vexillata, an SSR-based linkage map of V. vexillata was developed. A total of 874 SSR markers successfully amplified single DNA fragment in V. vexillata among 1,336 SSR markers developed from Vigna angularis (azuki bean), V. unguiculata and Phaseolus vulgaris (common bean). An F2 population of 300 plants derived from a cross between salt resistant (V1) and susceptible (V5) accessions was used for mapping. A genetic linkage map was constructed using 82 polymorphic SSR markers loci, which could be assigned to 11 linkage groups spanning 511.5 cM in length with a mean distance of 7.2 cM between adjacent markers. To develop higher density molecular linkage map and to confirm SSR markers position in a linkage map, RAD markers were developed and a combined SSR and RAD markers linkage map of V. vexillata was constructed. A total of 559 (84 SSR and 475 RAD) markers loci could be assigned to 11 linkage groups spanning 973.9 cM in length with a mean distance of 1.8 cM between adjacent markers. Linkage and genetic position of all SSR markers in an SSR linkage map were confirmed. When an SSR genetic linkage map of V. vexillata was compared with those of V. radiata and V. unguiculata, it was suggested that the structure of V. vexillata chromosome was considerably differentiated. This map is the first SSR and RAD marker-based V. vexillata linkage map which can be used for the mapping of useful traits.

  5. Study of ExacTrac X-ray 6D IGRT setup uncertainty for marker-based prostate IMRT treatment.

    Science.gov (United States)

    Shi, Chengyu; Tazi, Adam; Fang, Deborah Xiangdong; Iannuzzi, Christopher

    2012-05-10

    Novalis Tx ExacTrac X-ray system has the 6D adjustment ability for patient setup. Limited studies exist about the setup uncertainty with ExacTrac X-ray system for IMRT prostate treatment with fiducial markers implanted. The purpose of this study is to investigate the marker-based prostate IMRT treatment setup uncertainty using ExacTrac 6D IGRT ability for patient setup. Forty-three patients with prostate cancers and markers implanted have been treated on the Novalis Tx machine. The ExacTrac X-ray system has been used for the patient pretreatment setup and intratreatment verification. In total, the shifts data for 1261 fractions and 3504 correction times (the numbers of X-ray images were taken from tube 1 and tube 2) have been analyzed. The setup uncertainty has been separated into uncertainties in 6D. Marker matching uncertainty was also analyzed. Correction frequency probability density function was plotted, and the radiation dose for imaging was calculated. The minimum, average, and maximum translation shifts were: -5.12 ± 3.89 mm, 0.20 ± 2.21 mm, and 6.07 ± 4.44 mm, respectively, in the lateral direction; -6.80 ± 3.21 mm, -1.09 ± 2.21 mm, and 3.12 ± 2.62 mm, respectively, in the longitudinal direction; and -7.33 ± 3.46 mm, -0.93 ± 2.70 mm, and 5.93 ± 4.85mm, respectively, in the vertical direction. The minimum, average, and maximum rotation shifts were: -1.23° ± 1.95°, 0.25° ± 1.30°, and 2.38° ± 2.91°, respectively, along lateral direction; -0.67° ± 0.91°, 0.10° ± 0.61°, and 1.51° ± 2.04°, respectively, along longitudinal direction; and -0.75° ± 1.01°, 0.02° ± 0.50°, and 0.82° ± 1.13°, respectively, along vertical direction. On average, each patient had three correction times during one fraction treatment. The radiation dose is about 3 mSv per fraction. With the ExacTrac 6D X-ray system, the prostate IMRT treatment with marker implanted can achieve less than 2 mm setup uncertainty in translations, and less than 0.25° in

  6. Construction of an SSR and RAD-Marker Based Molecular Linkage Map of Vigna vexillata (L. A. Rich.

    Directory of Open Access Journals (Sweden)

    Rusama Marubodee

    Full Text Available Vigna vexillata (L. A. Rich. (tuber cowpea is an underutilized crop for consuming its tuber and mature seeds. Wild form of V. vexillata is a pan-tropical perennial herbaceous plant which has been used by local people as a food. Wild V. vexillata has also been considered as useful gene(s source for V. unguiculata (cowpea, since it was reported to have various resistance gene(s for insects and diseases of cowpea. To exploit the potential of V. vexillata, an SSR-based linkage map of V. vexillata was developed. A total of 874 SSR markers successfully amplified single DNA fragment in V. vexillata among 1,336 SSR markers developed from Vigna angularis (azuki bean, V. unguiculata and Phaseolus vulgaris (common bean. An F2 population of 300 plants derived from a cross between salt resistant (V1 and susceptible (V5 accessions was used for mapping. A genetic linkage map was constructed using 82 polymorphic SSR markers loci, which could be assigned to 11 linkage groups spanning 511.5 cM in length with a mean distance of 7.2 cM between adjacent markers. To develop higher density molecular linkage map and to confirm SSR markers position in a linkage map, RAD markers were developed and a combined SSR and RAD markers linkage map of V. vexillata was constructed. A total of 559 (84 SSR and 475 RAD markers loci could be assigned to 11 linkage groups spanning 973.9 cM in length with a mean distance of 1.8 cM between adjacent markers. Linkage and genetic position of all SSR markers in an SSR linkage map were confirmed. When an SSR genetic linkage map of V. vexillata was compared with those of V. radiata and V. unguiculata, it was suggested that the structure of V. vexillata chromosome was considerably differentiated. This map is the first SSR and RAD marker-based V. vexillata linkage map which can be used for the mapping of useful traits.

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

    Science.gov (United States)

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

    2016-06-01

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

  8. Surface fluid registration of conformal representation: application to detect disease burden and genetic influence on hippocampus.

    Science.gov (United States)

    Shi, Jie; Thompson, Paul M; Gutman, Boris; Wang, Yalin

    2013-09-01

    In this paper, we develop a new automated surface registration system based on surface conformal parameterization by holomorphic 1-forms, inverse consistent surface fluid registration, and multivariate tensor-based morphometry (mTBM). First, we conformally map a surface onto a planar rectangle space with holomorphic 1-forms. Second, we compute surface conformal representation by combining its local conformal factor and mean curvature and linearly scale the dynamic range of the conformal representation to form the feature image of the surface. Third, we align the feature image with a chosen template image via the fluid image registration algorithm, which has been extended into the curvilinear coordinates to adjust for the distortion introduced by surface parameterization. The inverse consistent image registration algorithm is also incorporated in the system to jointly estimate the forward and inverse transformations between the study and template images. This alignment induces a corresponding deformation on the surface. We tested the system on Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset to study AD symptoms on hippocampus. In our system, by modeling a hippocampus as a 3D parametric surface, we nonlinearly registered each surface with a selected template surface. Then we used mTBM to analyze the morphometry difference between diagnostic groups. Experimental results show that the new system has better performance than two publicly available subcortical surface registration tools: FIRST and SPHARM. We also analyzed the genetic influence of the Apolipoprotein E[element of]4 allele (ApoE4), which is considered as the most prevalent risk factor for AD. Our work successfully detected statistically significant difference between ApoE4 carriers and non-carriers in both patients of mild cognitive impairment (MCI) and healthy control subjects. The results show evidence that the ApoE genotype may be associated with accelerated brain atrophy so that our

  9. Legislation for trial registration and data transparency

    Directory of Open Access Journals (Sweden)

    Wu Tai-Xiang

    2010-05-01

    Full Text Available Abstract Public confidence in clinical trials has been eroded by data suppression, misrepresentation and manipulation. Although various attempts have been made to achieve universal trial registration- e.g., Declaration of Helsinki, WHO clinical Trial Registry Platform (WHO ICTRP, the International Committee of Medical Journal Editors requirement- they have not succeeded, probably because they lack the enough power of enforcement. Legislation appears to be the most efficient and effective means to ensure that all researchers register their trials and disseminate their data accurately and in a timely manner. We propose that a global network be established. This could be accomplished in two steps. The first step is to legislate about trial registration and data transparency, such as USA's FDAAA Act 2007; and the second step to establish a global network to ensure uniform, international consistency in policy and enforcement of trial registration and data transparency.

  10. Fractional Regularization Term for Variational Image Registration

    Directory of Open Access Journals (Sweden)

    Rafael Verdú-Monedero

    2009-01-01

    Full Text Available Image registration is a widely used task of image analysis with applications in many fields. Its classical formulation and current improvements are given in the spatial domain. In this paper a regularization term based on fractional order derivatives is formulated. This term is defined and implemented in the frequency domain by translating the energy functional into the frequency domain and obtaining the Euler-Lagrange equations which minimize it. The new regularization term leads to a simple formulation and design, being applicable to higher dimensions by using the corresponding multidimensional Fourier transform. The proposed regularization term allows for a real gradual transition from a diffusion registration to a curvature registration which is best suited to some applications and it is not possible in the spatial domain. Results with 3D actual images show the validity of this approach.

  11. Legislation for trial registration and data transparency.

    Science.gov (United States)

    Bian, Zhao-Xiang; Wu, Tai-Xiang

    2010-05-26

    Public confidence in clinical trials has been eroded by data suppression, misrepresentation and manipulation. Although various attempts have been made to achieve universal trial registration- e.g., Declaration of Helsinki, WHO clinical Trial Registry Platform (WHO ICTRP), the International Committee of Medical Journal Editors requirement- they have not succeeded, probably because they lack the enough power of enforcement.Legislation appears to be the most efficient and effective means to ensure that all researchers register their trials and disseminate their data accurately and in a timely manner. We propose that a global network be established. This could be accomplished in two steps. The first step is to legislate about trial registration and data transparency, such as USA's FDAAA Act 2007; and the second step to establish a global network to ensure uniform, international consistency in policy and enforcement of trial registration and data transparency.

  12. Mass Preserving Registration for lung CT