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Sample records for based multimodal registration

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

    PubMed

    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.

  2. Multimodal image registration based on binary gradient angle descriptor.

    PubMed

    Jiang, Dongsheng; Shi, Yonghong; Yao, Demin; Fan, Yifeng; Wang, Manning; Song, Zhijian

    2017-08-31

    Multimodal image registration plays an important role in image-guided interventions/therapy and atlas building, and it is still a challenging task due to the complex intensity variations in different modalities. The paper addresses the problem and proposes a simple, compact, fast and generally applicable modality-independent binary gradient angle descriptor (BGA) based on the rationale of gradient orientation alignment. The BGA can be easily calculated at each voxel by coding the quadrant in which a local gradient vector falls, and it has an extremely low computational complexity, requiring only three convolutions, two multiplication operations and two comparison operations. Meanwhile, the binarized encoding of the gradient orientation makes the BGA more resistant to image degradations compared with conventional gradient orientation methods. The BGA can extract similar feature descriptors for different modalities and enable the use of simple similarity measures, which makes it applicable within a wide range of optimization frameworks. The results for pairwise multimodal and monomodal registrations between various images (T1, T2, PD, T1c, Flair) consistently show that the BGA significantly outperforms localized mutual information. The experimental results also confirm that the BGA can be a reliable alternative to the sum of absolute difference in monomodal image registration. The BGA can also achieve an accuracy of [Formula: see text], similar to that of the SSC, for the deformable registration of inhale and exhale CT scans. Specifically, for the highly challenging deformable registration of preoperative MRI and 3D intraoperative ultrasound images, the BGA achieves a similar registration accuracy of [Formula: see text] compared with state-of-the-art approaches, with a computation time of 18.3 s per case. The BGA improves the registration performance in terms of both accuracy and time efficiency. With further acceleration, the framework has the potential for

  3. Multimodal registration of remotely sensed images based on Jeffrey's divergence

    NASA Astrophysics Data System (ADS)

    Xu, Xiaocong; Li, Xia; Liu, Xiaoping; Shen, Huanfeng; Shi, Qian

    2016-12-01

    Entropy-based measures (e.g., mutual information, also known as Kullback-Leiber divergence), which quantify the similarity between two signals, are widely used as similarity measures for image registration. Although they are proven superior to many classical statistical measures, entropy-based measures, such as mutual information, may fail to yield the optimum registration if the multimodal image pair has insufficient scene overlap region. To overcome this challenge, we proposed using the symmetric form of Kullback-Leiber divergence, namely Jeffrey's divergence, as the similarity measure in practical multimodal image registration tasks. Mathematical analysis was performed to investigate the causes accounting for the limitation of mutual information when dealing with insufficient scene overlap image pairs. Experimental registrations of SPOT image, Landsat TM image, ALOS PalSAR image, and DEM data were carried out to compare the performance of Jeffrey's divergence and mutual information. Results indicate that Jeffrey's divergence is capable of providing larger feasible search space, which is favorable for exploring optimum transformation parameters in a larger range. This superiority of Jeffrey's divergence was further confirmed by a series of paradigms. Thus, the proposed model is more applicable for registering image pairs that are greatly misaligned or have an insufficient scene overlap region.

  4. A hybrid multimodal non-rigid registration of MR images based on diffeomorphic demons.

    PubMed

    Lu, Huanxiang; Cattin, Philippe C; Reyes, Mauricio

    2010-01-01

    In this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.

  5. Manifold-based feature point matching for multi-modal image registration.

    PubMed

    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.

  6. Multi-modal image registration based on gradient orientations of minimal uncertainty.

    PubMed

    De Nigris, Dante; Collins, D Louis; Arbel, Tal

    2012-12-01

    In this paper, we propose a new multi-scale technique for multi-modal image registration based on the alignment of selected gradient orientations of reduced uncertainty. We show how the registration robustness and accuracy can be improved by restricting the evaluation of gradient orientation alignment to locations where the uncertainty of fixed image gradient orientations is minimal, which we formally demonstrate correspond to locations of high gradient magnitude. We also embed a computationally efficient technique for estimating the gradient orientations of the transformed moving image (rather than resampling pixel intensities and recomputing image gradients). We have applied our method to different rigid multi-modal registration contexts. Our approach outperforms mutual information and other competing metrics in the context of rigid multi-modal brain registration, where we show sub-millimeter accuracy with cases obtained from the retrospective image registration evaluation project. Furthermore, our approach shows significant improvements over standard methods in the highly challenging clinical context of image guided neurosurgery, where we demonstrate misregistration of less than 2 mm with relation to expert selected landmarks for the registration of pre-operative brain magnetic resonance images to intra-operative ultrasound images.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    PubMed

    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).

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  10. Automatic model-based semantic registration of multimodal MRI knee data.

    PubMed

    Xue, Ning; Doellinger, Michael; Fripp, Jurgen; Ho, Charles P; Surowiec, Rachel K; Schwarz, Raphael

    2015-03-01

    To propose a robust and automated model-based semantic registration for the multimodal alignment of the knee bone and cartilage from three-dimensional (3D) MR image data. The movement of the knee joint can be semantically interpreted as a combination of movements of each bone. A semantic registration of the knee joint was implemented by separately reconstructing the rigid movements of the three bones. The proposed method was validated by registering 3D morphological MR datasets of 25 subjects into the corresponding T2 map datasets, and was compared with rigid and elastic methods using two criteria: the spatial overlap of the manually segmented cartilage and the distance between the same landmarks in the reference and target datasets. The mean Dice Similarity Coefficient (DSC) of the overlapped cartilage segmentation was increased to 0.68 ± 0.1 (mean ± SD) and the landmark distance was reduced to 1.3 ± 0.3 mm after the proposed registration method. Both metrics were statistically superior to using rigid (DSC: 0.59 ± 0.12; landmark distance: 2.1 ± 0.4 mm) and elastic (DSC: 0.64 ± 0.11; landmark distance: 1.5 ± 0.5 mm) registrations. The proposed method is an efficient and robust approach for the automated registration between morphological knee datasets and T2 MRI relaxation maps. © 2014 Wiley Periodicals, Inc.

  11. Multimodality medical image registration and fusion techniques using mutual information and genetic algorithm-based approaches.

    PubMed

    Bhattacharya, Mahua; Das, Arpita

    2011-01-01

    Medical image fusion has been used to derive the useful complimentary information from multimodal images. The prior step of fusion is registration or proper alignment of test images for accurate extraction of detail information. For this purpose, the images to be fused are geometrically aligned using mutual information (MI) as similarity measuring metric followed by genetic algorithm to maximize MI. The proposed fusion strategy incorporating multi-resolution approach extracts more fine details from the test images and improves the quality of composite fused image. The proposed fusion approach is independent of any manual marking or knowledge of fiducial points and starts the procedure automatically. The performance of proposed genetic-based fusion methodology is compared with fuzzy clustering algorithm-based fusion approach, and the experimental results show that genetic-based fusion technique improves the quality of the fused image significantly over the fuzzy approaches.

  12. Laplacian eigenmaps for multimodal groupwise image registration

    NASA Astrophysics Data System (ADS)

    Polfliet, Mathias; Klein, Stefan; Niessen, Wiro J.; Vandemeulebroucke, Jef

    2017-02-01

    Multimodal groupwise registration has been of growing interest to the image processing community due to developments in scanner technologies (e.g. multiparametric MRI, DCE-CT or PET-MR) that increased both the number of modalities and number of images under consideration. In this work a novel methodology is presented for multimodal groupwise registration that is based on Laplacian eigenmaps, a nonlinear dimensionality reduction technique. Compared to recently proposed dissimilarity metrics based on principal component analysis, the proposed metric should enable a better capture of the intensity relationships between different images in the group. The metric is constructed to be the second smallest eigenvalue from the eigenvector problem defined in Laplacian eigenmaps. The method was validated in three distinct experiments: a non-linear synthetic registration experiment, the registration of quantitative MRI data of the carotid artery, and the registration of multimodal data of the brain (RIRE). The results show increased accuracy and robustness compared to other state-of-the-art groupwise registration methodologies.

  13. [Research on non-rigid registration of multi-modal medical image based on Demons algorithm].

    PubMed

    Hao, Peibo; Chen, Zhen; Jiang, Shaofeng; Wang, Yang

    2014-02-01

    Non-rigid medical image registration is a popular subject in the research areas of the medical image and has an important clinical value. In this paper we put forward an improved algorithm of Demons, together with the conservation of gray model and local structure tensor conservation model, to construct a new energy function processing multi-modal registration problem. We then applied the L-BFGS algorithm to optimize the energy function and solve complex three-dimensional data optimization problem. And finally we used the multi-scale hierarchical refinement ideas to solve large deformation registration. The experimental results showed that the proposed algorithm for large de formation and multi-modal three-dimensional medical image registration had good effects.

  14. Image registration techniques for multimodal sensors

    NASA Astrophysics Data System (ADS)

    Altinalev, Tevfik; Cetin, Enis A.; Yardimci, Yasemin C.

    2002-08-01

    Image registration refers to the problem of spatially aligning two or more images. A challenging problem in this area is the registration of images obtained by different types of sensors. In general such images have different gray level characteristics and commonly used techniques such as those based on area correlations cannot be applied directly. On the other hand, contours representing the region boundaries are preserved in most cases. Therefore, contour based registration techniques are applicable to multimodal sensors. In this paper, various registration techniques based on subband decomposition and projection along x and y directions are introduced. The effect of binarization is investigated. Unknown translation and scaling parameters are computed using cross-correlation methods over the projections. Performance of the algorithms is compared.

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

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

  16. Multi-modal image registration using structural features.

    PubMed

    Kasiri, Keyvan; Clausi, David A; Fieguth, Paul

    2014-01-01

    Multi-modal image registration has been a challenging task in medical images because of the complex intensity relationship between images to be aligned. Registration methods often rely on the statistical intensity relationship between the images which suffers from problems such as statistical insufficiency. The proposed registration method works based on extracting structural features by utilizing the complex phase and gradient-based information. By employing structural relationships between different modalities instead of complex similarity measures, the multi-modal registration problem is converted into a mono-modal one. Therefore, conventional mono-modal similarity measures can be utilized to evaluate the registration results. This new registration paradigm has been tested on magnetic resonance (MR) brain images of different modes. The method has been evaluated based on target registration error (TRE) to determine alignment accuracy. Quantitative results demonstrate that the proposed method is capable of achieving comparable registration accuracy compared to the conventional mutual information.

  17. Statistical power of intensity- and feature-based similarity measures for registration of multimodal remote sensing images

    NASA Astrophysics Data System (ADS)

    Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

    2016-10-01

    This paper investigates performance characteristics of similarity measures (SM) used in image registration domain to discriminate between aligned and not-aligned reference and template image (RI and TI) fragments. The study emphasizes registration of multimodal remote sensing images including optical-to-radar, optical-to-DEM, and radar-to- DEM scenarios. We compare well-known area-based SMs such as Mutual Information, Normalized Correlation Coefficient, Phase Correlation, and feature-based SM using SIFT and SIFT-OCT descriptors. In addition, a new SM called logLR based on log-likelihood ratio test and parametric modeling of a pair of RI and TI fragments by the Fractional Brownian Motion model is proposed. While this new measure is restricted to linear intensity change between RI and TI (assumption somewhat restrictive for multimodal registration), it takes explicitly into account noise properties of RI and TI and multivariate mutual distribution of RI and TI pixels. Unlike other SMs, distribution of logLR measure for the null hypothesis does not depend on registration scenario or fragments size and follows closely chi-squared distribution according to Wilks's theorem. We demonstrate that a SM utility for image registration purpose can be naturally represented in (True Positive Rate, Positive Likelihood Rate) coordinates. Experiments on real images show that overall the logLR SM outperforms the other SMs in terms of area under the ROC curve, denoted AUC. It also provides the highest Positive Likelihood Rate for True Positive Rate values below 0.4-0.6. But for certain registration problem types, logLR can be second or third best after MI or SIFT SMs.

  18. A new multi-modal similarity measure for fast gradient-based 2D-3D image registration.

    PubMed

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

    2009-01-01

    2D-3D image registration has been adopted in many clinical applications such as image-guided surgery and the kinematic analysis of bones in knee and ankle joints. In this paper we propose a new single-plane 2D-3D registration algorithm which requires far less iteration than previous techniques. The new algorithm includes a new multi-modal similarity measure and a novel technique for the analytic calculation of the required gradients. Our experimental results show that, when compared to existing gradient and non-gradient based techniques, the proposed algorithm has a wider range of initial poses for which registration can be achieved and requires significantly fewer iterations to converge to the true 3D position of the anatomical structure.

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

    PubMed Central

    2010-01-01

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

  20. [Multimodal medical image registration using cubic spline interpolation method].

    PubMed

    He, Yuanlie; Tian, Lianfang; Chen, Ping; Wang, Lifei; Ye, Guangchun; Mao, Zongyuan

    2007-12-01

    Based on the characteristic of the PET-CT multimodal image series, a novel image registration and fusion method is proposed, in which the cubic spline interpolation method is applied to realize the interpolation of PET-CT image series, then registration is carried out by using mutual information algorithm and finally the improved principal component analysis method is used for the fusion of PET-CT multimodal images to enhance the visual effect of PET image, thus satisfied registration and fusion results are obtained. The cubic spline interpolation method is used for reconstruction to restore the missed information between image slices, which can compensate for the shortage of previous registration methods, improve the accuracy of the registration, and make the fused multimodal images more similar to the real image. Finally, the cubic spline interpolation method has been successfully applied in developing 3D-CRT (3D Conformal Radiation Therapy) system.

  1. Automated skeleton based multi-modal deformable registration of head&neck datasets.

    PubMed

    Steger, Sebastian; Wesarg, Stefan

    2012-01-01

    This paper presents a novel skeleton based method for the registration of head&neck datasets. Unlike existing approaches it is fully automated, spatial relation of the bones is considered during their registration and only one of the images must be a CT scan. An articulated atlas is used to jointly obtain a segmentation of the skull, the mandible and the vertebrae C1-Th2 from the CT image. These bones are then successively rigidly registered with the moving image, beginning at the skull, resulting in a rigid transformation for each of the bones. Linear combinations of those transformations describe the deformation in the soft tissue. The weights for the transformations are given by the solution of the Laplace equation. Optionally, the skin surface can be incorporated. The approach is evaluated on 20 CT/MRI pairs of head&neck datasets acquired in clinical routine. Visual inspection shows that the segmentation of the bones was successful in all cases and their successive alignment was successful in 19 cases. Based on manual segmentations of lymph nodes in both modalities, the registration accuracy in the soft tissue was assessed. The mean target registration error of the lymph node centroids was 5.33 +/- 2.44 mm when the registration was solely based on the deformation of the skeleton and 5.00 +/- 2.38 mm when the skin surface was additionally considered. The method's capture range is sufficient to cope with strongly deformed images and it can be modified to support other parts of the body. The overall registration process typically takes less than 2 minutes.

  2. WE-D-9A-04: Improving Multi-Modality Image Registration Using Edge-Based Transformations

    SciTech Connect

    Wang, Y; Tyagi, N; Veeraraghavan, H; Deasy, J

    2014-06-15

    Purpose: Multi-modality deformable image registration (DIR) for head and neck (HN) radiotherapy is difficult, particularly when matching computed tomography (CT) scans with magnetic resonance imaging (MRI) scans. We hypothesized that the ‘shared information’ between images of different modalities was to be found in some form of edge-based transformation, and that novel edge-based DIR methods might outperform standard DIR methods. Methods: We propose a novel method that combines gray-scale edge-based morphology and mutual information (MI) in two stages. In the first step, we applied a modification of a previously published mathematical morphology method as an efficient gray scale edge estimator, with denoising function. The results were fed into a MI-based solver (plastimatch). The method was tested on 5 HN patients with pretreatment CT and MR datasets and associated follow-up weekly MR scans. The followup MRs showed significant regression in tumor and normal structure volumes as compared to the pretreatment MRs. The MR images used in this study were obtained using fast spin echo based T2w images with a 1 mm isotropic resolution and FOV matching the CT scan. Results: In all cases, the novel edge-based registration method provided better registration quality than MI-based DIR using the original CT and MRI images. For example, the mismatch in carotid arteries was reduced from 3–5 mm to within 2 mm. The novel edge-based method with different registration regulation parameters did not show any distorted deformations as compared to the non-realistic deformations resulting from MI on the original images. Processing time was 1.3 to 2 times shorter (edge vs. non-edge). In general, we observed quality improvement and significant calculation time reduction with the new method. Conclusion: Transforming images to an ‘edge-space,’ if designed appropriately, greatly increases the speed and accuracy of DIR.

  3. Post-operative assessment in Deep Brain Stimulation based on multimodal images: registration workflow and validation

    NASA Astrophysics Data System (ADS)

    Lalys, Florent; Haegelen, Claire; Abadie, Alexandre; Jannin, Pierre

    2009-02-01

    Object Movement disorders in Parkinson disease patients may require functional surgery, when medical therapy isn't effective. In Deep Brain Stimulation (DBS) electrodes are implanted within the brain to stimulate deep structures such as SubThalamic Nucleus (STN). This paper describes successive steps for constructing a digital Atlas gathering patient's location of electrodes and contacts for post operative assessment. Materials and Method 12 patients who had undergone bilateral STN DBS have participated to the study. Contacts on post-operative CT scans were automatically localized, based on black artefacts. For each patient, post operative CT images were rigidly registered to pre operative MR images. Then, pre operative MR images were registered to a MR template (super-resolution Collin27 average MRI template). This last registration was the combination of global affine, local affine and local non linear registrations, respectively. Four different studies were performed in order to validate the MR patient to template registration process, based on anatomical landmarks and clinical scores (i.e., Unified Parkinson's disease rating Scale). Visualisation software was developed for displaying into the template images the stimulated contacts represented as cylinders with a colour code related to the improvement of the UPDRS. Results The automatic contact localization algorithm was successful for all the patients. Validation studies for the registration process gave a placement error of 1.4 +/- 0.2 mm and coherence with UPDRS scores. Conclusion The developed visualization tool allows post-operative assessment for previous interventions. Correlation with additional clinical scores will certainly permit to learn more about DBS and to better understand clinical side-effects.

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

    PubMed Central

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

    2013-01-01

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

  5. Multi-modality image registration for effective thermographic fever screening

    NASA Astrophysics Data System (ADS)

    Dwith, C. Y. N.; Ghassemi, Pejhman; Pfefer, Joshua; Casamento, Jon; Wang, Quanzeng

    2017-02-01

    Fever screening based on infrared thermographs (IRTs) is a viable mass screening approach during infectious disease pandemics, such as Ebola and Severe Acute Respiratory Syndrome (SARS), for temperature monitoring in public places like hospitals and airports. IRTs have been found to be powerful, quick and non-invasive methods for detecting elevated temperatures. Moreover, regions medially adjacent to the inner canthi (called the canthi regions in this paper) are preferred sites for fever screening. Accurate localization of the canthi regions can be achieved through multi-modality registration of infrared (IR) and white-light images. Here we propose a registration method through a coarse-fine registration strategy using different registration models based on landmarks and edge detection on eye contours. We have evaluated the registration accuracy to be within +/- 2.7 mm, which enables accurate localization of the canthi regions.

  6. An innovative multimodal/multispectral image registration method for medical images based on the Expectation-Maximization algorithm.

    PubMed

    Arce-Santana, Edgar; Campos-Delgado, Daniel U; Mejia-Rodriguez, Aldo; Reducindo, Isnardo

    2015-01-01

    In this paper, we present a methodology for multimodal/ multispectral image registration of medical images. This approach is formulated by using the Expectation-Maximization (EM) methodology, such that we estimate the parameters of a geometric transformation that aligns multimodal/multispectral images. In this framework, the hidden random variables are associated to the intensity relations between the studied images, which allow to compare multispectral intensity values between images of different modalities. The methodology is basically composed by an iterative two-step procedure, where at each step, a new estimation of the joint conditional multispectral intensity distribution and the geometric transformation is computed. The proposed algorithm was tested with different kinds of medical images, and the obtained results show that the proposed methodology can be used to efficiently align multimodal/multispectral medical images.

  7. Sorted self-similarity for multi-modal image registration.

    PubMed

    Kasiri, Keyvan; Fieguth, Paul; Clausi, David A

    2016-08-01

    In medical image analysis, registration of multimodal images has been challenging due to the complex intensity relationship between images. Classical multi-modal registration approaches evaluate the degree of the alignment by measuring the statistical dependency of the intensity values between images to be aligned. Employing statistical similarity measures, such as mutual information, is not promising in those cases with complex and spatially dependent intensity relations. A new similarity measure is proposed based on the assessing the similarity of pixels within an image, based on the idea that similar structures in an image are more probable to undergo similar intensity transformations. The most significant pixel similarity values are considered to transmit the most significant self-similarity information. The proposed method is employed in a framework to register different modalities of real brain scans and the performance of the method is compared to the conventional multi-modal registration approach. Quantitative evaluation of the method demonstrates the better registration accuracy in both rigid and non-rigid deformations.

  8. Multi-Modal Robust Inverse-Consistent Linear Registration

    PubMed Central

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

    2016-01-01

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

  9. A new region descriptor for multi-modal medical image registration and region detection.

    PubMed

    Xiaonan Wan; Dongdong Yu; Feng Yang; Caiyun Yang; Chengcai Leng; Min Xu; Jie Tian

    2015-08-01

    Establishing accurate anatomical correspondences plays a critical role in multi-modal medical image registration and region detection. Although many features based registration methods have been proposed to detect these correspondences, they are mostly based on the point descriptor which leads to high memory cost and could not represent local region information. In this paper, we propose a new region descriptor which depicts the features in each region, instead of in each point, as a vector. First, feature attributes of each point are extracted by a Gabor filter bank combined with a gradient filter. Then, the region descriptor is defined as the covariance of feature attributes of each point inside the region, based on which a cost function is constructed for multi-modal image registration. Finally, our proposed region descriptor is applied to both multi-modal region detection and similarity metric measurement in multi-modal image registration. Experiments demonstrate the feasibility and effectiveness of our proposed region descriptor.

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

    PubMed

    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.

  11. Mono- and multimodal registration of optical breast images

    NASA Astrophysics Data System (ADS)

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

    2012-08-01

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

  12. Multi-modality image registration using the decomposition model

    NASA Astrophysics Data System (ADS)

    Ibrahim, Mazlinda; Chen, Ke

    2017-04-01

    In medical image analysis, image registration is one of the crucial steps required to facilitate automatic segmentation, treatment planning and other application involving imaging machines. Image registration, also known as image matching, aims to align two or more images so that information obtained can be compared and combined. Different imaging modalities and their characteristics make the task more challenging. We propose a decomposition model combining parametric and non-parametric deformation for multi-modality image registration. Numerical results show that the normalised gradient field perform better than the mutual information with the decomposition model.

  13. Multimodality image registration quality assurance for conformal three-dimensional treatment planning.

    PubMed

    Mutic, S; Dempsey, J F; Bosch, W R; Low, D A; Drzymala, R E; Chao, K S; Goddu, S M; Cutler, P D; Purdy, J A

    2001-09-01

    We present a quality assurance methodology to determine the accuracy of multimodality image registration and fusion for the purpose of conformal three-dimensional and intensity-modulated radiation therapy treatment planning. Registration and fusion accuracy between any combination of computed tomography (CT), magnetic resonance (MR), and positron emission computed tomography (PET) imaging studies can be evaluated. A commercial anthropomorphic head phantom filled with water and containing CT, MR, and PET visible targets was modified to evaluate the accuracy of multimodality image registration and fusion software. For MR and PET imaging, the water inside the phantom was doped with CuNO(3) and 18F-fluorodeoxyglucose (18F-FDG), respectively. Targets consisting of plastic spheres and pins were distributed throughout the cranium section of the phantom. Each target sphere had a conical-shaped bore with its apex at the center of the sphere. The pins had a conical extension or indentation at the free end. The contours of the spheres, sphere centers, and pin tips were used as anatomic landmark models for image registration, which was performed using affine coordinate-transformation tools provided in a commercial multimodality image registration/fusion software package. Four sets of phantom image studies were obtained: primary CT, secondary CT with different phantom immobilization, MR, and PET study. A novel CT, MR, and PET external fiducial marking system was also tested. The registration of CT/CT, CT/MR, and CT/PET images allowed correlation of anatomic landmarks to within 2 mm, verifying the accuracy of the registration software and spatial fidelity of the four multimodality image sets. This straightforward phantom-based quality assurance of the image registration and fusion process can be used in a routine clinical setting or for providing a working image set for development of the image registration and fusion process and new software.

  14. Groupwise registration of multimodal images by an efficient joint entropy minimization scheme.

    PubMed

    Spiclin, Ziga; Likar, Bostjan; Pernus, Franjo

    2012-05-01

    Groupwise registration is concerned with bringing a group of images into the best spatial alignment. If images in the group are from different modalities, then the intensity correspondences across the images can be modeled by the joint density function (JDF) of the cooccurring image intensities. We propose a so-called treecode registration method for groupwise alignment of multimodal images that uses a hierarchical intensity-space subdivision scheme through which an efficient yet sufficiently accurate estimation of the (high-dimensional) JDF based on the Parzen kernel method is computed. To simultaneously align a group of images, a gradient-based joint entropy minimization was employed that also uses the same hierarchical intensity-space subdivision scheme. If the Hilbert kernel is used for the JDF estimation, then the treecode method requires no data-dependent bandwidth selection and is thus fully automatic. The treecode method was compared with the ensemble clustering (EC) method on four different publicly available multimodal image data sets and on a synthetic monomodal image data set. The obtained results indicate that the treecode method has similar and, for two data sets, even superior performances compared to the EC method in terms of registration error and success rate. The obtained good registration performances can be mostly attributed to the sufficiently accurate estimation of the JDF, which is computed through the hierarchical intensity-space subdivision scheme, that captures all the important features needed to detect the correct intensity correspondences across a multimodal group of images undergoing registration.

  15. Automatic quantification of multi-modal rigid registration accuracy using feature detectors

    NASA Astrophysics Data System (ADS)

    Hauler, F.; Furtado, H.; Jurisic, M.; Polanec, S. H.; Spick, C.; Laprie, A.; Nestle, U.; Sabatini, U.; Birkfellner, W.

    2016-07-01

    In radiotherapy, the use of multi-modal images can improve tumor and target volume delineation. Images acquired at different times by different modalities need to be aligned into a single coordinate system by 3D/3D registration. State of the art methods for validation of registration are visual inspection by experts and fiducial-based evaluation. Visual inspection is a qualitative, subjective measure, while fiducial markers sometimes suffer from limited clinical acceptance. In this paper we present an automatic, non-invasive method for assessing the quality of intensity-based multi-modal rigid registration using feature detectors. After registration, interest points are identified on both image data sets using either speeded-up robust features or Harris feature detectors. The quality of the registration is defined by the mean Euclidean distance between matching interest point pairs. The method was evaluated on three multi-modal datasets: an ex vivo porcine skull (CT, CBCT, MR), seven in vivo brain cases (CT, MR) and 25 in vivo lung cases (CT, CBCT). Both a qualitative (visual inspection by radiation oncologist) and a quantitative (mean target registration error—mTRE—based on selected markers) method were employed. In the porcine skull dataset, the manual and Harris detectors give comparable results but both overestimated the gold standard mTRE based on fiducial markers. For instance, for CT-MR-T1 registration, the mTREman (based on manually annotated landmarks) was 2.2 mm whereas mTREHarris (based on landmarks found by the Harris detector) was 4.1 mm, and mTRESURF (based on landmarks found by the SURF detector) was 8 mm. In lung cases, the difference between mTREman and mTREHarris was less than 1 mm, while the difference between mTREman and mTRESURF was up to 3 mm. The Harris detector performed better than the SURF detector with a resulting estimated registration error close to the gold standard. Therefore the Harris detector was shown to be the more suitable

  16. Automatic quantification of multi-modal rigid registration accuracy using feature detectors.

    PubMed

    Hauler, F; Furtado, H; Jurisic, M; Polanec, S H; Spick, C; Laprie, A; Nestle, U; Sabatini, U; Birkfellner, W

    2016-07-21

    In radiotherapy, the use of multi-modal images can improve tumor and target volume delineation. Images acquired at different times by different modalities need to be aligned into a single coordinate system by 3D/3D registration. State of the art methods for validation of registration are visual inspection by experts and fiducial-based evaluation. Visual inspection is a qualitative, subjective measure, while fiducial markers sometimes suffer from limited clinical acceptance. In this paper we present an automatic, non-invasive method for assessing the quality of intensity-based multi-modal rigid registration using feature detectors. After registration, interest points are identified on both image data sets using either speeded-up robust features or Harris feature detectors. The quality of the registration is defined by the mean Euclidean distance between matching interest point pairs. The method was evaluated on three multi-modal datasets: an ex vivo porcine skull (CT, CBCT, MR), seven in vivo brain cases (CT, MR) and 25 in vivo lung cases (CT, CBCT). Both a qualitative (visual inspection by radiation oncologist) and a quantitative (mean target registration error-mTRE-based on selected markers) method were employed. In the porcine skull dataset, the manual and Harris detectors give comparable results but both overestimated the gold standard mTRE based on fiducial markers. For instance, for CT-MR-T1 registration, the mTREman (based on manually annotated landmarks) was 2.2 mm whereas mTREHarris (based on landmarks found by the Harris detector) was 4.1 mm, and mTRESURF (based on landmarks found by the SURF detector) was 8 mm. In lung cases, the difference between mTREman and mTREHarris was less than 1 mm, while the difference between mTREman and mTRESURF was up to 3 mm. The Harris detector performed better than the SURF detector with a resulting estimated registration error close to the gold standard. Therefore the Harris detector was shown to be the more suitable

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

    SciTech Connect

    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

  18. Multi-modality registration via multi-scale textural and spectral embedding representations

    NASA Astrophysics Data System (ADS)

    Li, Lin; Rusu, Mirabela; Viswanath, Satish; Penzias, Gregory; Pahwa, Shivani; Gollamudi, Jay; Madabhushi, Anant

    2016-03-01

    Intensity-based similarity measures assume that the original signal intensity of different modality images can provide statistically consistent information regarding the two modalities to be co-registered. In multi-modal registration problems, however, intensity-based similarity measures are often inadequate to identify an optimal transformation. Texture features can improve the performance of the multi-modal co-registration by providing more similar appearance representations of the two images to be co-registered, compared to the signal intensity representations. Furthermore, texture features extracted at different length scales (neighborhood sizes) can reveal similar underlying structural attributes between the images to be co-registered similarities that may not be discernible on the signal intensity representation alone. However one limitation of using texture features is that a number of them may be redundant and dependent and hence there is a need to identify non-redundant representations. Additionally it is not clear which features at which specific scales reveal similar attributes across the images to be co-registered. To address this problem, we introduced a novel approach for multimodal co-registration that employs new multi-scale image representations. Our approach comprises 4 distinct steps: (1) texure feature extraction at each length scale within both the target and template images, (2) independent component analysis (ICA) at each texture feature length scale, and (3) spectrally embedding (SE) the ICA components (ICs) obtained for the texture features at each length scale, and finally (4) identifying and combining the optimal length scales at which to perform the co-registration. To combine and co-register across different length scales, -mutual information (-MI) was applied in the high dimensional space of spectral embedding vectors to facilitate co-registration. To validate our multi-scale co-registration approach, we aligned 45 pairs of prostate

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

    NASA Astrophysics Data System (ADS)

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

    2008-03-01

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

  20. Fast and Robust Registration of Multimodal Remote Sensing Images via Dense Orientated Gradient Feature

    NASA Astrophysics Data System (ADS)

    Ye, Y.

    2017-09-01

    This paper presents a fast and robust method for the registration of multimodal remote sensing data (e.g., optical, LiDAR, SAR and map). The proposed method is based on the hypothesis that structural similarity between images is preserved across different modalities. In the definition of the proposed method, we first develop a pixel-wise feature descriptor named Dense Orientated Gradient Histogram (DOGH), which can be computed effectively at every pixel and is robust to non-linear intensity differences between images. Then a fast similarity metric based on DOGH is built in frequency domain using the Fast Fourier Transform (FFT) technique. Finally, a template matching scheme is applied to detect tie points between images. Experimental results on different types of multimodal remote sensing images show that the proposed similarity metric has the superior matching performance and computational efficiency than the state-of-the-art methods. Moreover, based on the proposed similarity metric, we also design a fast and robust automatic registration system for multimodal images. This system has been evaluated using a pair of very large SAR and optical images (more than 20000 × 20000 pixels). Experimental results show that our system outperforms the two popular commercial software systems (i.e. ENVI and ERDAS) in both registration accuracy and computational efficiency.

  1. Evaluation of registration strategies for multi-modality images of rat brain slices

    NASA Astrophysics Data System (ADS)

    Palm, Christoph; Vieten, Andrea; Salber, Dagmar; Pietrzyk, Uwe

    2009-05-01

    In neuroscience, small-animal studies frequently involve dealing with series of images from multiple modalities such as histology and autoradiography. The consistent and bias-free restacking of multi-modality image series is obligatory as a starting point for subsequent non-rigid registration procedures and for quantitative comparisons with positron emission tomography (PET) and other in vivo data. Up to now, consistency between 2D slices without cross validation using an inherent 3D modality is frequently presumed to be close to the true morphology due to the smooth appearance of the contours of anatomical structures. However, in multi-modality stacks consistency is difficult to assess. In this work, consistency is defined in terms of smoothness of neighboring slices within a single modality and between different modalities. Registration bias denotes the distortion of the registered stack in comparison to the true 3D morphology and shape. Based on these metrics, different restacking strategies of multi-modality rat brain slices are experimentally evaluated. Experiments based on MRI-simulated and real dual-tracer autoradiograms reveal a clear bias of the restacked volume despite quantitatively high consistency and qualitatively smooth brain structures. However, different registration strategies yield different inter-consistency metrics. If no genuine 3D modality is available, the use of the so-called SOP (slice-order preferred) or MOSOP (modality-and-slice-order preferred) strategy is recommended.

  2. Deformable image registration for multimodal lung-cancer staging

    NASA Astrophysics Data System (ADS)

    Cheirsilp, Ronnarit; Zang, Xiaonan; Bascom, Rebecca; Allen, Thomas W.; Mahraj, Rickhesvar P. M.; Higgins, William E.

    2016-03-01

    Positron emission tomography (PET) and X-ray computed tomography (CT) serve as major diagnostic imaging modalities in the lung-cancer staging process. Modern scanners provide co-registered whole-body PET/CT studies, collected while the patient breathes freely, and high-resolution chest CT scans, collected under a brief patient breath hold. Unfortunately, no method exists for registering a PET/CT study into the space of a high-resolution chest CT scan. If this could be done, vital diagnostic information offered by the PET/CT study could be brought seamlessly into the procedure plan used during live cancer-staging bronchoscopy. We propose a method for the deformable registration of whole-body PET/CT data into the space of a high-resolution chest CT study. We then demonstrate its potential for procedure planning and subsequent use in multimodal image-guided bronchoscopy.

  3. Multimodal image registration using floating regressors in the joint intensity scatter plot.

    PubMed

    Orchard, Jeff

    2008-08-01

    This paper presents a new approach for multimodal medical image registration and compares it to normalized mutual information (NMI) and the correlation ratio (CR). Like NMI and CR, the new method's measure of registration quality is based on the distribution of points in the joint intensity scatter plot (JISP); compact clusters indicate good registration. This method iteratively fits the JISP clusters with regressors (in the form of points and line segments), and uses those regressors to efficiently compute the next motion increment. The result is a striking, dynamic process in which the regressors float around the JISP, tracking groups of points as they contract into tight clusters. One of the method's strengths is that it is intuitive and customizable, offering a multitude of ways to incorporate prior knowledge to guide the registration process. Moreover, the method is adaptive, and can adjust itself to fit data that does not quite match the prior model. Finally, the method is efficiently expandable to higher-dimensional scatter plots, avoiding the "curse of dimensionality" inherent in histogram-based registration methods such as MI and NMI. In two sets of experiments, a simple implementation of the new registration framework is shown to be comparable to (if not superior to) state-of-the-art implementations of NMI and CR in both accuracy and convergence robustness.

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

    PubMed

    Mellado, Nicolas; Dellepiane, Matteo; Scopigno, Roberto

    2016-09-01

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

  5. Multi-modal registration for correlative microscopy using image analogies.

    PubMed

    Cao, Tian; Zach, Christopher; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc

    2014-08-01

    Correlative microscopy is a methodology combining the functionality of light microscopy with the high resolution of electron microscopy and other microscopy technologies for the same biological specimen. In this paper, we propose an image registration method for correlative microscopy, which is challenging due to the distinct appearance of biological structures when imaged with different modalities. Our method is based on image analogies and allows to transform images of a given modality into the appearance-space of another modality. Hence, the registration between two different types of microscopy images can be transformed to a mono-modality image registration. We use a sparse representation model to obtain image analogies. The method makes use of corresponding image training patches of two different imaging modalities to learn a dictionary capturing appearance relations. We test our approach on backscattered electron (BSE) scanning electron microscopy (SEM)/confocal and transmission electron microscopy (TEM)/confocal images. We perform rigid, affine, and deformable registration via B-splines and show improvements over direct registration using both mutual information and sum of squared differences similarity measures to account for differences in image appearance. Copyright © 2013 Elsevier B.V. All rights reserved.

  6. Multi-modal Registration for Correlative Microscopy using Image Analogies

    PubMed Central

    Cao, Tian; Zach, Christopher; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc

    2014-01-01

    Correlative microscopy is a methodology combining the functionality of light microscopy with the high resolution of electron microscopy and other microscopy technologies for the same biological specimen. In this paper, we propose an image registration method for correlative microscopy, which is challenging due to the distinct appearance of biological structures when imaged with different modalities. Our method is based on image analogies and allows to transform images of a given modality into the appearance-space of another modality. Hence, the registration between two different types of microscopy images can be transformed to a mono-modality image registration. We use a sparse representation model to obtain image analogies. The method makes use of corresponding image training patches of two different imaging modalities to learn a dictionary capturing appearance relations. We test our approach on backscattered electron (BSE) scanning electron microscopy (SEM)/confocal and transmission electron microscopy (TEM)/confocal images. We perform rigid, affine, and deformable registration via B-splines and show improvements over direct registration using both mutual information and sum of squared differences similarity measures to account for differences in image appearance. PMID:24387943

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

    PubMed

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

    2017-06-21

    To test and compare different registration approaches for performing whole-body diffusion-weighted (wbDWI) image station mosaicing, and its alignment to corresponding anatomical T1 whole-body image. Four different registration strategies aiming at mosaicing of diffusion-weighted image stations, and their alignment to the corresponding whole-body anatomical image, were proposed and evaluated. These included two-step approaches, where diffusion-weighted stations are first combined in a pairwise (Strategy 1) or groupwise (Strategy 2) manner and later non-rigidly aligned to the anatomical image; a direct pairwise mapping of DWI stations onto the anatomical image (Strategy 3); and simultaneous mosaicing of DWI and alignment to the anatomical image (Strategy 4). Additionally, different images driving the registration were investigated. Experiments were performed for 20 whole-body images of patients with bone metastases. Strategies 1 and 2 showed significant improvement in mosaicing accuracy with respect to the non-registered images (P < 0.006). Strategy 2 based on ADC images increased the alignment accuracy between DWI stations and the T1 whole-body image (P = 0.0009). A two-step registration strategy, relying on groupwise mosaicing of the ADC stations and subsequent registration to T1 , provided the best compromise between whole-body DWI image quality and multi-modal alignment. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  8. Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information.

    PubMed

    Maes, F; Vandermeulen, D; Suetens, P

    1999-12-01

    Maximization of mutual information of voxel intensities has been demonstrated to be a very powerful criterion for three-dimensional medical image registration, allowing robust and accurate fully automated affine registration of multimodal images in a variety of applications, without the need for segmentation or other preprocessing of the images. In this paper, we investigate the performance of various optimization methods and multiresolution strategies for maximization of mutual information, aiming at increasing registration speed when matching large high-resolution images. We show that mutual information is a continuous function of the affine registration parameters when appropriate interpolation is used and we derive analytic expressions of its derivatives that allow numerically exact evaluation of its gradient. Various multiresolution gradient- and non-gradient-based optimization strategies, such as Powell, simplex, steepest-descent, conjugate-gradient, quasi-Newton and Levenberg-Marquardt methods, are evaluated for registration of computed tomography (CT) and magnetic resonance images of the brain. Speed-ups of a factor of 3 on average compared to Powell's method at full resolution are achieved with similar precision and without a loss of robustness with the simplex, conjugate-gradient and Levenberg-Marquardt method using a two-level multiresolution scheme. Large data sets such as 256(2) x 128 MR and 512(2) x 48 CT images can be registered with subvoxel precision in <5 min CPU time on current workstations.

  9. Registration of multimodal brain images: some experimental results

    NASA Astrophysics Data System (ADS)

    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.

  10. Multimodal acquisition of articulatory data: Geometrical and temporal registration.

    PubMed

    Aron, Michaël; Berger, Marie-Odile; Kerrien, Erwan; Wrobel-Dautcourt, Brigitte; Potard, Blaise; Laprie, Yves

    2016-02-01

    Acquisition of dynamic articulatory data is of major importance for studying speech production. It turns out that one technique alone often is not enough to get a correct coverage of the whole vocal tract at a sufficient sampling rate. Ultrasound (US) imaging has been proposed as a good acquisition technique for the tongue surface because it offers a good temporal sampling, does not alter speech production, is cheap, and is widely available. However, it cannot be used alone and this paper describes a multimodal acquisition system which uses electromagnetography sensors to locate the US probe. The paper particularly focuses on the calibration of the US modality which is the key point of the system. This approach enables US data to be merged with other data. The use of the system is illustrated via an experiment consisting of measuring the minimal tongue to palate distance in order to evaluate and design Magnetic Resonance Imaging protocols well suited for the acquisition of three-dimensional images of the vocal tract. Compared to manual registration of acquisition modalities which is often used in acquisition of articulatory data, the approach presented relies on automatic techniques well founded from geometrical and mathematical points of view.

  11. A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration

    PubMed Central

    Chen, Jian; Tian, Jie; Lee, Noah; Zheng, Jian; Smith, R. Theodore; Laine, Andrew F.

    2011-01-01

    Detection of vascular bifurcations is a challenging task in multimodal retinal image registration. Existing algorithms based on bifurcations usually fail in correctly aligning poor quality retinal image pairs. To solve this problem, we propose a novel highly distinctive local feature descriptor named partial intensity invariant feature descriptor (PIIFD) and describe a robust automatic retinal image registration framework named Harris-PIIFD. PIIFD is invariant to image rotation, partially invariant to image intensity, affine transformation, and viewpoint/perspective change. Our Harris-PIIFD framework consists of four steps. First, corner points are used as control point candidates instead of bifurcations since corner points are sufficient and uniformly distributed across the image domain. Second, PIIFDs are extracted for all corner points, and a bilateral matching technique is applied to identify corresponding PIIFDs matches between image pairs. Third, incorrect matches are removed and inaccurate matches are refined. Finally, an adaptive transformation is used to register the image pairs. PIIFD is so distinctive that it can be correctly identified even in nonvascular areas. When tested on 168 pairs of multimodal retinal images, the Harris-PIIFD far outperforms existing algorithms in terms of robustness, accuracy, and computational efficiency. PMID:20176538

  12. Registration of Visible and Infrared Images Based on Gradient Information

    NASA Astrophysics Data System (ADS)

    Geng, Yingnan; Wang, Yanan

    2017-06-01

    Multi-modality image registration is very challenging due to disparate imaging theory of sensors. Extraction of similar features and evaluation of algorithms have been two key difficulties. In this paper, gradient of RGB vector space, as a similar image feature, is shown the viability of using for the registration of infrared and visible still stereo pairs. Based on adaptive support-window algorithm, a novel method, which formulates the registration problem as correspondences between gradients of RGB vector space and obtains the best matching by minimizing gradient difference in sliding correspondence support-windows, is proposed. Evaluation experiments demonstrate high rates of successful registration by yielding qualitative and quantitative results.

  13. Multimodal image registration for the identification of dominant intraprostatic lesion in high-precision radiotherapy treatments.

    PubMed

    Ciardo, Delia; Jereczek-Fossa, Barbara Alicja; Petralia, Giuseppe; Timon, Giorgia; Zerini, Dario; Cambria, Raffaella; Rondi, Elena; Cattani, Federica; Bazani, Alessia; Ricotti, Rosalinda; Garioni, Maria; Maestri, Davide; Marvaso, Giulia; Romanelli, Paola; Riboldi, Marco; Baroni, Guido; Orecchia, Roberto

    2017-08-22

    The integration of computed tomography (CT) and multiparametric magnetic resonance imaging (mpMRI) is a challenging task in high-precision radiotherapy for prostate cancer. A simple methodology for multimodal deformable image registration (DIR) of prostate cancer patients is presented. CT and mpMRI of ten patients were considered. Organs at risk and prostate were contoured on both scans. The dominant intraprostatic lesion was additionally delineated on magnetic resonance imaging. After a preliminary rigid image registration, the voxel intensity of all the segmented structures in both scans except the prostate was increased by a specific amount (a constant additional value, A), in order to enhance the contrast of the main organs influencing its position and shape. Seventy couples of scans were obtained by varying A from 0 to 800 and they were subsequently non-rigidly registered. Quantities derived from image analysis and contour statistics were considered for the tuning of the best performing A. A = 200 resulted the minimum enhancement value required to obtain statistically significant superior registration results. Mean centre of mass distance between corresponding structures decreases from 7.4 mm in rigid registration to 5.3 mm in DIR without enhancement (DIR-0) and to 2.7 mm in DIR with A = 200 (DIR-200). Mean contour distance was 2.5, 1.9 and 0.67 mm in rigid registration, DIR-0 and DIR-200, respectively. In DIR-200 mean contours overlap increases of +13% and +24% with respect to DIR-0 and rigid registration, respectively. Contour propagation according to the vector field resulting from DIR-200 allows the delineation of dominant intraprostatic lesion on CT scan and its use for high-precision radiotherapy treatment planning. Advances in knowledge: We investigated the application of a B-spline, mutual information-based multimodal DIR coupled with a simple, patient-unspecific but efficient contrast enhancement procedure in the pelvic body area, thus

  14. Multimodal registration of SD-OCT volumes and fundus photographs using histograms of oriented gradients

    PubMed Central

    Miri, Mohammad Saleh; Abràmoff, Michael D.; Kwon, Young H.; Garvin, Mona K.

    2016-01-01

    With availability of different retinal imaging modalities such as fundus photography and spectral domain optical coherence tomography (SD-OCT), having a robust and accurate registration scheme to enable utilization of this complementary information is beneficial. The few existing fundus-OCT registration approaches contain a vessel segmentation step, as the retinal blood vessels are the most dominant structures that are in common between the pair of images. However, errors in the vessel segmentation from either modality may cause corresponding errors in the registration. In this paper, we propose a feature-based registration method for registering fundus photographs and SD-OCT projection images that benefits from vasculature structural information without requiring blood vessel segmentation. In particular, after a preprocessing step, a set of control points (CPs) are identified by looking for the corners in the images. Next, each CP is represented by a feature vector which encodes the local structural information via computing the histograms of oriented gradients (HOG) from the neighborhood of each CP. The best matching CPs are identified by calculating the distance of their corresponding feature vectors. After removing the incorrect matches the best affine transform that registers fundus photographs to SD-OCT projection images is computed using the random sample consensus (RANSAC) method. The proposed method was tested on 44 pairs of fundus and SD-OCT projection images of glaucoma patients and the result showed that the proposed method successfully registers the multimodal images and produced a registration error of 25.34 ± 12.34 μm (0.84 ± 0.41 pixels). PMID:28018740

  15. Multi-Modality fiducial marker for validation of registration of medical images with histology

    NASA Astrophysics Data System (ADS)

    Shojaii, Rushin; Martel, Anne L.

    2010-03-01

    A multi-modality fiducial marker is presented in this work, which can be used for validating the correlation of histology images with medical images. This marker can also be used for landmark-based image registration. Seven different fiducial markers including a catheter, spaghetti, black spaghetti, cuttlefish ink, and liquid iron are implanted in a mouse specimen and then investigated based on visibility, localization, size, and stability. The black spaghetti and the mixture of cuttlefish ink and flour are shown to be the most suitable markers. Based on the size of the markers, black spaghetti is more suitable for big specimens and the mixture of the cuttlefish ink, flour, and water injected in a catheter is more suitable for small specimens such as mouse tumours. These markers are visible on medical images and also detectable on histology and optical images of the tissue blocks. The main component in these agents which enhances the contrast is iron.

  16. Multimodal Registration of White Matter Brain Data via Optimal Mass Transport.

    PubMed

    Rehman, Tauseefur; Haber, Eldad; Pohl, Kilian M; Haker, Steven; Halle, Mike; Talos, Florin; Wald, Lawrence L; Kikinis, Ron; Tannenbaum, Allen

    2008-09-01

    The elastic registration of medical scans from different acquisition sequences is becoming an important topic for many research labs that would like to continue the post-processing of medical scans acquired via the new generation of high-field-strength scanners. In this note, we present a parameter-free registration algorithm that is well suited for this scenario as it requires no tuning to specific acquisition sequences. The algorithm encompasses a new numerical scheme for computing elastic registration maps based on the minimizing flow approach to optimal mass transport. The approach utilizes all of the gray-scale data in both images, and the optimal mapping from image A to image B is the inverse of the optimal mapping from B to A. Further, no landmarks need to be specified, and the minimizer of the distance functional involved is unique. We apply the algorithm to register the white matter folds of two different scans and use the results to parcellate the cortex of the target image. To the best of our knowledge, this is the first time that the optimal mass transport function has been applied to register large 3D multimodal data sets.

  17. Multimodal Registration of White Matter Brain Data via Optimal Mass Transport

    PubMed Central

    Rehman, Tauseefur; Haber, Eldad; Pohl, Kilian M.; Haker, Steven; Halle, Mike; Talos, Florin; Wald, Lawrence L.; Kikinis, Ron; Tannenbaum, Allen

    2017-01-01

    The elastic registration of medical scans from different acquisition sequences is becoming an important topic for many research labs that would like to continue the post-processing of medical scans acquired via the new generation of high-field-strength scanners. In this note, we present a parameter-free registration algorithm that is well suited for this scenario as it requires no tuning to specific acquisition sequences. The algorithm encompasses a new numerical scheme for computing elastic registration maps based on the minimizing flow approach to optimal mass transport. The approach utilizes all of the gray-scale data in both images, and the optimal mapping from image A to image B is the inverse of the optimal mapping from B to A. Further, no landmarks need to be specified, and the minimizer of the distance functional involved is unique. We apply the algorithm to register the white matter folds of two different scans and use the results to parcellate the cortex of the target image. To the best of our knowledge, this is the first time that the optimal mass transport function has been applied to register large 3D multimodal data sets. PMID:28626844

  18. A software platform for visualization and multimodal registration of diffuse optical tomography and MRI of breast cancer

    NASA Astrophysics Data System (ADS)

    Azar, Fred S.; Hajjioui, Nassim; Khamene, Ali; Grady, Leo; Lee, Kijoon; Choe, Regine; Corlu, Alper; Konecky, Soren D.; Yodh, Arjun G.; Sauer, Frank

    2006-02-01

    We have developed a software platform for multimodal integration and visualization of diffuse optical tomography and magnetic resonance imaging. Novel registration and segmentation algorithms have been integrated into the platform. The multimodal registration technique enables the alignment of non-concurrently acquired MR and DOT breast data. The non-rigid registration algorithm uses two-dimensional signatures (2D digitally reconstructed radiographs) of the reference and moving volumes in order to register them. Multiple two-dimensional signatures can robustly represent the volume depending on the way signatures are generated. An easy way to conceptualize the idea is to understand the motion of an object by tracking three perpendicular shadows of the object. The breast MR image segmentation technique enables a priori structural information derived from MRI to be incorporated into the reconstruction of DOT data. The segmentation algorithm is based on "Random walkers". Both registration and segmentation algorithms were tested and have shown promising results. The average Target Registration Error (TRE) for phantom models simulating the large breast compression differences was always below 5%. Tests on patient datasets also showed satisfying visual results. Several tests were also conducted for segmentation assessment and results have shown high quality MR breast image segmentation.

  19. Registration and fusion of multimodal vascular images: a phantom study

    NASA Astrophysics Data System (ADS)

    Boussion, Nicolas; de Guise, Jacques A.; Soulez, Gilles; Daronat, Michel; Cloutier, Guy

    2003-05-01

    The aim of this work was to compare the geometric accuracy of X-ray angiography, MRI, X-ray computed tomography (XCT), and ultrasound imaging (B-mode and IVUS) for measuring the lumen diameters of blood vessels. An image fusion method also was developed to improve these measurements. The images were acquired from a realistic phantom mimicking normal vessels of known internal diameters. After acquisition, the multimodal images were coregistered, by manual alignment of fiducial markers and then by automatic maximization of mutual information. The fusion method was performed by means of a fuzzy logic modeling approach followed by a combination process based on possibilistic logic. The data showed (i) the good geometric accuracy of XCT compared to the other methods for all studied diameters; and (ii) the good results of fused images compared to single modalities alone. For XCT, the error varied from 1.1% to 9.7%, depending on the vessel diameter that ranged from 0.93 to 6.24 mm. MRI-IVUS fusion allowed variability of measurements to be reduced up to 78%. To conclude, this work underlined both the usefulness of the vascular phantom as a validation tool and the utility of image fusion in the vascular context. Future work will consist of studying pathological vessel shapes, image artifacts and partial volume effect correction.

  20. An extension of digital volume correlation for multimodality image registration

    NASA Astrophysics Data System (ADS)

    Tudisco, E.; Jailin, C.; Mendoza, A.; Tengattini, A.; Andò, E.; Hall, Stephen A.; Viggiani, Gioacchino; Hild, F.; Roux, S.

    2017-09-01

    The question of registering two images (or image volumes) acquired with different modalities, and thus exhibiting different contrast, at different positions is addressed based on an extension of global digital image (or volume) correlation. A specific comparison metric is introduced allowing the signature of the different phases to be related. A first solution consists of a Gaussian mixture to describe the joint distribution of gray levels, which not only provides a matching of both images, but also offers a natural segmentation indicator. A second ‘self-adapting’ solution does not include any postulated a priori model for the joint histogram and leads to a registration of the images based on their initial histograms. The algorithm is implemented with a pyramidal multiscale framework for the sake of robustness. The proposed multiscale technique is tested on two 3D images obtained from x-ray and neutron tomography respectively. The proposed approach brings the two images to coincidence with a sub-pixel accuracy and allows for a ‘natural’ segmentation of the different phases.

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

    PubMed

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-04-01

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

  3. Multimodal image registration of the scoliotic torso for surgical planning

    PubMed Central

    2013-01-01

    Background This paper presents a method that registers MRIs acquired in prone position, with surface topography (TP) and X-ray reconstructions acquired in standing position, in order to obtain a 3D representation of a human torso incorporating the external surface, bone structures, and soft tissues. Methods TP and X-ray data are registered using landmarks. Bone structures are used to register each MRI slice using an articulated model, and the soft tissue is confined to the volume delimited by the trunk and bone surfaces using a constrained thin-plate spline. Results The method is tested on 3 pre-surgical patients with scoliosis and shows a significant improvement, qualitatively and using the Dice similarity coefficient, in fitting the MRI into the standing patient model when compared to rigid and articulated model registration. The determinant of the Jacobian of the registration deformation shows higher variations in the deformation in areas closer to the surface of the torso. Conclusions The novel, resulting 3D full torso model can provide a more complete representation of patient geometry to be incorporated in surgical simulators under development that aim at predicting the effect of scoliosis surgery on the external appearance of the patient’s torso. PMID:23289431

  4. Fast and robust multimodal image registration using a local derivative pattern.

    PubMed

    Jiang, Dongsheng; Shi, Yonghong; Chen, Xinrong; Wang, Manning; Song, Zhijian

    2017-02-01

    Deformable multimodal image registration, which can benefit radiotherapy and image guided surgery by providing complementary information, remains a challenging task in the medical image analysis field due to the difficulty of defining a proper similarity measure. This article presents a novel, robust and fast binary descriptor, the discriminative local derivative pattern (dLDP), which is able to encode images of different modalities into similar image representations. dLDP calculates a binary string for each voxel according to the pattern of intensity derivatives in its neighborhood. The descriptor similarity is evaluated using the Hamming distance, which can be efficiently computed, instead of conventional L1 or L2 norms. For the first time, we validated the effectiveness and feasibility of the local derivative pattern for multimodal deformable image registration with several multi-modal registration applications. dLDP was compared with three state-of-the-art methods in artificial image and clinical settings. In the experiments of deformable registration between different magnetic resonance imaging (MRI) modalities from BrainWeb, between computed tomography and MRI images from patient data, and between MRI and ultrasound images from BITE database, we show our method outperforms localized mutual information and entropy images in terms of both accuracy and time efficiency. We have further validated dLDP for the deformable registration of preoperative MRI and three-dimensional intraoperative ultrasound images. Our results indicate that dLDP reduces the average mean target registration error from 4.12 mm to 2.30 mm. This accuracy is statistically equivalent to the accuracy of the state-of-the-art methods in the study; however, in terms of computational complexity, our method significantly outperforms other methods and is even comparable to the sum of the absolute difference. The results reveal that dLDP can achieve superior performance regarding both accuracy and

  5. New GPU optimizations for intensity-based registration

    NASA Astrophysics Data System (ADS)

    Yousfi, Razik; Bousquet, Guillaume; Chefd'hotel, Christophe

    2009-02-01

    The task of registering 3D medical images is very computationally expensive. With CPU-based implementations of registration algorithms it is typical to use various approximations, such as subsampling, to maintain reasonable computation times. This may however result in suboptimal alignments. With the constant increase of capabilities and performances of GPUs (Graphics Processing Unit), these highly vectorized processors have become a viable alternative to CPUs for image related computation tasks. This paper describes new strategies to implement on GPU the computation of image similarity metrics for intensity-based registration, using in particular the latest features of NVIDIA's GeForce 8 architecture and the Cg language. Our experimental results show that the computations are many times faster. In this paper, several GPU implementations of two image similarity criteria for both intramodal and multi-modal registration have been compared. In particular, we propose a new efficient and flexible solution based on the geometry shader.

  6. Multimode waveguide based directional coupler

    NASA Astrophysics Data System (ADS)

    Ahmed, Rajib; Rifat, Ahmmed A.; Sabouri, Aydin; Al-Qattan, Bader; Essa, Khamis; Butt, Haider

    2016-07-01

    The Silicon-on-Insulator (SOI) based platform overcomes limitations of the previous copper and fiber based technologies. Due to its high index difference, SOI waveguide (WG) and directional couplers (DC) are widely used for high speed optical networks and hybrid Electro-Optical inter-connections; TE00-TE01, TE00-TE00 and TM00-TM00 SOI direction couplers are designed with symmetrical and asymmetrical configurations to couple with TE00, TE01 and TM00 in a multi-mode semi-triangular ring-resonator configuration which will be applicable for multi-analyte sensing. Couplers are designed with effective index method and their structural parameters are optimized with consideration to coupler length, wavelength and polarization dependence. Lastly, performance of the couplers are analyzed in terms of cross-talk, mode overlap factor, coupling length and coupling efficiency.

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

    SciTech Connect

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

    2014-09-01

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

  8. Comparison of manual vs. automated multimodality (CT-MRI) image registration for brain tumors

    SciTech Connect

    Sarkar, Abhirup; Santiago, Roberto J.; Smith, Ryan; Kassaee, Alireza . E-mail: Kassaee@xrt.upenn.edu

    2005-03-31

    Computed tomgoraphy-magnetic resonance imaging (CT-MRI) registrations are routinely used for target-volume delineation of brain tumors. We clinically use 2 software packages based on manual operation and 1 automated package with 2 different algorithms: chamfer matching using bony structures, and mutual information using intensity patterns. In all registration algorithms, a minimum of 3 pairs of identical anatomical and preferably noncoplanar landmarks is used on each of the 2 image sets. In manual registration, the program registers these points and links the image sets using a 3-dimensional (3D) transformation. In automated registration, the 3 landmarks are used as an initial starting point and further processing is done to complete the registration. Using our registration packages, registration of CT and MRI was performed on 10 patients. We scored the results of each registration set based on the amount of time spent, the accuracy reported by the software, and a final evaluation. We evaluated each software program by measuring the residual error between 'matched' points on the right and left globes and the posterior fossa for fused image slices. In general, manual registration showed higher misalignment between corresponding points compared to automated registration using intensity matching. This error had no directional dependence and was, most of the time, larger for a larger structure in both registration techniques. Automated algorithm based on intensity matching also gave the best results in terms of registration accuracy, irrespective of whether or not the initial landmarks were chosen carefully, when compared to that done using bone matching algorithm. Intensity-matching algorithm required the least amount of user-time and provided better accuracy.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  10. Hierarchical Multi-modal Image Registration by Learning Common Feature Representations.

    PubMed

    Ge, Hongkun; Wu, Guorong; Wang, Li; Gao, Yaozong; Shen, Dinggang

    2015-10-05

    Mutual information (MI) has been widely used for registering images with different modalities. Since most inter-modality registration methods simply estimate deformations in a local scale, but optimizing MI from the entire image, the estimated deformations for certain structures could be dominated by the surrounding unrelated structures. Also, since there often exist multiple structures in each image, the intensity correlation between two images could be complex and highly nonlinear, which makes global MI unable to precisely guide local image deformation. To solve these issues, we propose a hierarchical inter-modality registration method by robust feature matching. Specifically, we first select a small set of key points at salient image locations to drive the entire image registration. Since the original image features computed from different modalities are often difficult for direct comparison, we propose to learn their common feature representations by projecting them from their native feature spaces to a common space, where the correlations between corresponding features are maximized. Due to the large heterogeneity between two high-dimension feature distributions, we employ Kernel CCA (Canonical Correlation Analysis) to reveal such non-linear feature mappings. Then, our registration method can take advantage of the learned common features to reliably establish correspondences for key points from different modality images by robust feature matching. As more and more key points take part in the registration, our hierarchical feature-based image registration method can efficiently estimate the deformation pathway between two inter-modality images in a global to local manner. We have applied our proposed registration method to prostate CT and MR images, as well as the infant MR brain images in the first year of life. Experimental results show that our method can achieve more accurate registration results, compared to other state-of-the-art image registration

  11. Hierarchical Multi-modal Image Registration by Learning Common Feature Representations

    PubMed Central

    Ge, Hongkun; Wu, Guorong; Wang, Li; Gao, Yaozong

    2016-01-01

    Mutual information (MI) has been widely used for registering images with different modalities. Since most inter-modality registration methods simply estimate deformations in a local scale, but optimizing MI from the entire image, the estimated deformations for certain structures could be dominated by the surrounding unrelated structures. Also, since there often exist multiple structures in each image, the intensity correlation between two images could be complex and highly nonlinear, which makes global MI unable to precisely guide local image deformation. To solve these issues, we propose a hierarchical inter-modality registration method by robust feature matching. Specifically, we first select a small set of key points at salient image locations to drive the entire image registration. Since the original image features computed from different modalities are often difficult for direct comparison, we propose to learn their common feature representations by projecting them from their native feature spaces to a common space, where the correlations between corresponding features are maximized. Due to the large heterogeneity between two high-dimension feature distributions, we employ Kernel CCA (Canonical Correlation Analysis) to reveal such non-linear feature mappings. Then, our registration method can take advantage of the learned common features to reliably establish correspondences for key points from different modality images by robust feature matching. As more and more key points take part in the registration, our hierarchical feature-based image registration method can efficiently estimate the deformation pathway between two inter-modality images in a global to local manner. We have applied our proposed registration method to prostate CT and MR images, as well as the infant MR brain images in the first year of life. Experimental results show that our method can achieve more accurate registration results, compared to other state-of-the-art image registration

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

    NASA Technical Reports Server (NTRS)

    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.

  13. Three-dimensional histopathology of lung cancer with multimodality image registration

    NASA Astrophysics Data System (ADS)

    de Ryk, Jessica; Weydert, Jamie; Christensen, Gary; Thiesse, Jacqueline; Namati, Eman; Reinhardt, Joseph; Hoffman, Eric; McLennan, Geoffrey

    2007-03-01

    Identifying the three-dimensional content of non-small cell lung cancer tumors is a vital step in the pursuit of understanding cancer growth, development and response to treatment. The majority of non-small cell lung cancer tumors are histologically heterogeneous, and consist of the malignant tumor cells, necrotic tumor cells, fibroblastic stromal tissue, and inflammation. Geometric and tissue density heterogeneity are utilized in computed tomography (CT) representations of lung tumors for distinguishing between malignant and benign nodules. However, the correlation between radiolographical heterogeneity and corresponding histological content has been limited. In this study, a multimodality dataset of human lung cancer is established, enabling the direct comparison between histologically identified tissue content and micro-CT representation. Registration of these two datasets is achieved through the incorporation of a large scale, serial microscopy dataset. This dataset serves as the basis for the rigid and non-rigid registrations required to align the radiological and histological data. The resulting comprehensive, three-dimensional dataset includes radio-density, color and cellular content of a given lung tumor. Using the registered datasets, neural network classification is applied to determine a statistical separation between cancerous and non-cancerous tumor regions in micro-CT.

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

    PubMed

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

    2016-07-01

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

  15. A rib-specific multimodal registration algorithm for fused unfolded rib visualization using PET/CT

    NASA Astrophysics Data System (ADS)

    Kaftan, Jens N.; Kopaczka, Marcin; Wimmer, Andreas; Platsch, Günther; Declerck, Jérôme

    2014-03-01

    Respiratory motion affects the alignment of PET and CT volumes from PET/CT examinations in a non-rigid manner. This becomes particularly apparent if reviewing fine anatomical structures such as ribs when assessing bone metastases, which frequently occur in many advanced cancers. To make this routine diagnostic task more efficient, a fused unfolded rib visualization for 18F-NaF PET/CT is presented. It allows to review the whole rib cage in a single image. This advanced visualization is enabled by a novel rib-specific registration algorithm that rigidly optimizes the local alignment of each individual rib in both modalities based on a matched filter response function. More specifically, rib centerlines are automatically extracted from CT and subsequently individually aligned to the corresponding bone-specific PET rib uptake pattern. The proposed method has been validated on 20 PET/CT scans acquired at different clinical sites. It has been demonstrated that the presented rib- specific registration method significantly improves the rib alignment without having to run complex deformable registration algorithms. At the same time, it guarantees that rib lesions are not further deformed, which may otherwise affect quantitative measurements such as SUVs. Considering clinically relevant distance thresholds, the centerline portion with good alignment compared to the ground truth improved from 60:6% to 86:7% after registration while approximately 98% can be still considered as acceptably aligned.

  16. A MULTICORE BASED PARALLEL IMAGE REGISTRATION METHOD

    PubMed Central

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

    2012-01-01

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

  17. Highly sensitive bending sensor based on multimode-multimode-coreoffset fiber structure

    NASA Astrophysics Data System (ADS)

    Qi, Yanhui; Ma, Lin; Sun, Jiang; Kang, Zexin; Bai, Yunlong; Jian, Shuisheng

    2015-12-01

    In this paper, we present a simple fiber optic bending sensor based on the multimode-multimode structure combining with the core-offset fiber structure. The multimode-multimode structure is composed of no core fiber (NCF) with hundreds of micrometers in length as a micro-lens for mode conversion, and single mode fiber (SMF) which can be seen as a section of special multimode fiber (MMF) when considered the cladding modes. The transmission spectrum in the experiment agrees well with the numerical model. The sensitivity of the structure can be achieved as high as 11.104 nm/m-1 in the measuring range. Meanwhile, the sensitivity of the neighboring resonance wavelength around 1546 nm exhibits approximately the same sensitivity which is 10.579 nm/m-1. Besides, the strain sensitivity is about -0.927 pm/με within the measuring strain range.

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

    PubMed Central

    Guo, Hengkai; Wang, Guijin; Huang, Lingyun; Hu, Yuxin; Yuan, Chun; Li, Rui; Zhao, Xihai

    2016-01-01

    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. PMID:26881433

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

    PubMed

    Guo, Hengkai; Wang, Guijin; Huang, Lingyun; Hu, Yuxin; Yuan, Chun; Li, Rui; Zhao, Xihai

    2016-01-01

    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.

  20. Registration of the Cone Beam CT and Blue-Ray Scanned Dental Model Based on the Improved ICP Algorithm

    PubMed Central

    Li, Zhenhua; Xu, Songsong; Guo, Xiaoyan

    2014-01-01

    Multimodality image registration and fusion has complementary significance for guiding dental implant surgery. As the needs of the different resolution image registration, we develop an improved Iterative Closest Point (ICP) algorithm that focuses on the registration of Cone Beam Computed Tomography (CT) image and high-resolution Blue-light scanner image. The proposed algorithm includes two major phases, coarse and precise registration. Firstly, for reducing the matching interference of human subjective factors, we extract feature points based on curvature characteristics and use the improved three point's translational transformation method to realize coarse registration. Then, the feature point set and reference point set, obtained by the initial registered transformation, are processed in the precise registration step. Even with the unsatisfactory initial values, this two steps registration method can guarantee the global convergence and the convergence precision. Experimental results demonstrate that the method has successfully realized the registration of the Cone Beam CT dental model and the blue-ray scanner model with higher accuracy. So the method could provide researching foundation for the relevant software development in terms of the registration of multi-modality medical data. PMID:24511309

  1. SAR image registration based on Susan algorithm

    NASA Astrophysics Data System (ADS)

    Wang, Chun-bo; Fu, Shao-hua; Wei, Zhong-yi

    2011-10-01

    Synthetic Aperture Radar (SAR) is an active remote sensing system which can be installed on aircraft, satellite and other carriers with the advantages of all day and night and all-weather ability. It is the important problem that how to deal with SAR and extract information reasonably and efficiently. Particularly SAR image geometric correction is the bottleneck to impede the application of SAR. In this paper we introduces image registration and the Susan algorithm knowledge firstly, then introduces the process of SAR image registration based on Susan algorithm and finally presents experimental results of SAR image registration. The Experiment shows that this method is effective and applicable, no matter from calculating the time or from the calculation accuracy.

  2. Biomechanical modeling constrained surface-based image registration for prostate MR guided TRUS biopsy.

    PubMed

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

    2015-05-01

    Adding magnetic resonance (MR)-derived information to standard transrectal ultrasound (TRUS) images for guiding prostate biopsy is of substantial clinical interest. A tumor visible on MR images can be projected on ultrasound (US) by using MR-US registration. A common approach is to use surface-based registration. The authors hypothesize that biomechanical modeling will better control deformation inside the prostate than a regular nonrigid surface-based registration method. The authors developed a novel method by extending a nonrigid surface-based registration algorithm with biomechanical finite element (FE) modeling to better predict internal deformations of the prostate. Data were collected from ten patients and the MR and TRUS images were rigidly registered to anatomically align prostate orientations. The prostate was manually segmented in both images and corresponding surface meshes were generated. Next, a tetrahedral volume mesh was generated from the MR image. Prostate deformations due to the TRUS probe were simulated using the surface displacements as the boundary condition. A three-dimensional thin-plate spline deformation field was calculated by registering the mesh vertices. The target registration errors (TREs) of 35 reference landmarks determined by surface and volume mesh registrations were compared. The median TRE of a surface-based registration with biomechanical regularization was 2.76 (0.81-7.96) mm. This was significantly different than the median TRE of 3.47 (1.05-7.80) mm for regular surface-based registration without biomechanical regularization. Biomechanical FE modeling has the potential to improve the accuracy of multimodal prostate registration when comparing it to a regular nonrigid surface-based registration algorithm and can help to improve the effectiveness of MR guided TRUS biopsy procedures.

  3. Modeling and Performance Analysis of the Movement-Based Registration with Implicit Registration

    NASA Astrophysics Data System (ADS)

    Baek, Jang Hyun; Park, Jong Hun; Sicker, Douglas C.; Lee, Taehan

    This study examines movement-based registration (MBR). In MBR, a mobile station (MS) performs location registration whenever the number of entering cells reaches the specified movement threshold M. MBR is simple and its implementation is quite straightforward. However, it may result in more registrations than other similar schemes. We propose an improved MBR scheme, in which MBR combines with implicit registration (IR), to reduce registration cost. The performance of the proposed scheme is evaluated using a mathematical approach based on the 2-dimensional random walk mobility model in a hexagonal cell configuration. The numerical results for varying circumstances show that the proposed scheme performs better than conventional MBR.

  4. Phantom-based investigation of nonrigid registration constraints in mapping fMRI to anatomical MRI

    NASA Astrophysics Data System (ADS)

    Studholme, Colin; Constable, R. Todd; Duncan, James S.

    2000-06-01

    In previous work we have introduced an approach to improving the registration of EPI fMRI data with anatomical MRI by accounting for differences in magnetic field induced geometric distortion in the two types of MRI acquisition. In particular we began to explore the use of imaging physics based constraints in a non-rigid multi-modality registration algorithm. In this paper we present phantom based experimental work examining the behavior of different non-rigid registration constraints compared to a field map acquisition of the MRI distortion. This acquisition provides a pixel by pixel 'ground truth' estimate of the displacement field within the EPI data. In our registration based approach we employ a B-spline based estimate of the relative geometric distortion with a multi-grid optimization scheme. We maximize the normalized mutual information between the two types of MRI scans to estimate the B-Spline parameters. Using the field map estimates as a gold standard, registration estimates using no additional geometric constraints are compared to those using the spin echo based signal conservation. We also examine the use of logarithmic EPI values in the criteria to provide additional sensitivity in areas of low signal. Results indicate that registration of EPI to conventional MRI incorporating a spin echo distortion model can provide comparable estimates of geometric distortion to those from field mapping data without the need for significant additional acquisitions during each fMRI sequence.

  5. A Remote Registration Based on MIDAS

    NASA Astrophysics Data System (ADS)

    JIN, Xin

    2017-04-01

    We often need for software registration to protect the interests of the software developers. This article narrated one kind of software long-distance registration technology. The registration method is: place the registration information in a database table, after the procedure starts in check table registration information, if it has registered then the procedure may the normal operation; Otherwise, the customer must input the sequence number and registers through the network on the long-distance server. If it registers successfully, then records the registration information in the database table. This remote registration method can protect the rights of software developers.

  6. Canny edge-based deformable image registration

    NASA Astrophysics Data System (ADS)

    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.

  7. Biological fiducial point based registration for multiple brain tissues reconstructed from different imaging modalities

    NASA Astrophysics Data System (ADS)

    Wu, Huiqun; Zhou, Gangping; Geng, Xingyun; Zhang, Xiaofeng; Jiang, Kui; Tang, Lemin; Zhou, Guomin; Dong, Jiancheng

    2013-10-01

    With the development of computer aided navigation system, more and more tissues shall be reconstructed to provide more useful information for surgical pathway planning. In this study, we aimed to propose a registration framework for different reconstructed tissues from multi-modalities based on some fiducial points on lateral ventricles. A male patient with brain lesion was admitted and his brain scans were performed by different modalities. Then, the different brain tissues were segmented in different modality with relevant suitable algorithms. Marching cubes were calculated for three dimensional reconstructions, and then the rendered tissues were imported to a common coordinate system for registration. Four pairs of fiducial markers were selected to calculate the rotation and translation matrix using least-square measure method. The registration results were satisfied in a glioblastoma surgery planning as it provides the spatial relationship between tumors and surrounding fibers as well as vessels. Hence, our framework is of potential value for clinicians to plan surgery.

  8. Hierarchical patch-based co-registration of differently stained histopathology slides

    NASA Astrophysics Data System (ADS)

    Yigitsoy, Mehmet; Schmidt, Günter

    2017-03-01

    Over the past decades, digital pathology has emerged as an alternative way of looking at the tissue at subcellular level. It enables multiplexed analysis of different cell types at micron level. Information about cell types can be extracted by staining sections of a tissue block using different markers. However, robust fusion of structural and functional information from different stains is necessary for reproducible multiplexed analysis. Such a fusion can be obtained via image co-registration by establishing spatial correspondences between tissue sections. Spatial correspondences can then be used to transfer various statistics about cell types between sections. However, the multi-modal nature of images and sparse distribution of interesting cell types pose several challenges for the registration of differently stained tissue sections. In this work, we propose a co-registration framework that efficiently addresses such challenges. We present a hierarchical patch-based registration of intensity normalized tissue sections. Preliminary experiments demonstrate the potential of the proposed technique for the fusion of multi-modal information from differently stained digital histopathology sections.

  9. Multimodality registration of two-dimensional echocardiography and cardiac CT for mitral valve diagnosis and surgical planning.

    PubMed

    Khalil, Azira; Faisal, Amir; Ng, Siew-Cheok; Liew, Yih Miin; Lai, Khin Wee

    2017-07-01

    A registration method to fuse two-dimensional (2-D) echocardiography images with cardiac computed tomography (CT) volume is presented. The method consists of two major procedures: temporal and spatial registrations. In temporal registration, the echocardiography frames at similar cardiac phases as the CT volume were interpolated based on electrocardiogram signal information, and the noise of the echocardiography image was reduced using the speckle reducing anisotropic diffusion technique. For spatial registration, an intensity-based normalized mutual information method was applied with a pattern search optimization algorithm to produce an interpolated cardiac CT image. The proposed registration framework does not require optical tracking information. Dice coefficient and Hausdorff distance for the left atrium assessments were [Formula: see text] and [Formula: see text], respectively; for left ventricle, they were [Formula: see text] and [Formula: see text], respectively. There was no significant difference in the mitral valve annulus diameter measurement between the manually and automatically registered CT images. The transformation parameters showed small deviations ([Formula: see text] deviation in translation and [Formula: see text] for rotation) between manual and automatic registrations. The proposed method aids the physician in diagnosing mitral valve disease as well as provides surgical guidance during the treatment procedure.

  10. Broad-spectrum multi-modality image registration: from PET, CT, and MRI to autoradiography, microscopy, and beyond.

    PubMed

    Zanzonico, P B

    2006-01-01

    Image registration and fusion are increasingly important components of both clinical and small-animal imaging and have lead to the development of a variety of pertinent hardware and software tools, including multi-modality, e.g. PET-CT, devices. At the same time, advances in microscopic imaging, including phosphor-plate digital autoradiography and immunohistochemistry, now allow ultra-high (sub-100 microm)-resolution molecular characterization of tissue sections. To date, however, in vivo imaging of intact subjects and ex vivo imaging of harvested tissues sections have remained separate and distinct, making it difficult to reliably inter-compare the former and the latter. The Department of Medical Physics and the Radiation Biophysics Laboratory at Memorial Sloan-Kettering Cancer Center, under the direction of Dr. Clifton Ling, has now designed, fabricated, and tested a stereotactic imaging system for so-called "broad-spectrum" image registration, from coarser-resolution in vivo imaging modalities such as PET, CT, and MRI to ultra-high-resolution ex vivo imaging techniques such as histology, autoradiography, and immunohistochemistry.

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  12. Multimodal image registration of ex vivo 4 Tesla MRI with whole mount histology for prostate cancer detection

    NASA Astrophysics Data System (ADS)

    Chappelow, Jonathan; Madabhushi, Anant; Rosen, Mark; Tomaszeweski, John; Feldman, Michael

    2007-03-01

    In this paper we present novel methods for registration and subsequent evaluation of whole mount prostate histological sections to corresponding 4 Tesla ex vivo magnetic resonance imaging (MRI) slices to complement our existing computer-aided diagnosis (CAD) system for detection of prostatic adenocarcinoma from high resolution MRI. The CAD system is trained using voxels labeled as cancer on MRI by experts who visually aligned histology with MRI. To address voxel labeling errors on account of manual alignment and delineation, we have developed a registration method called combined feature ensemble mutual information (COFEMI) to automatically map spatial extent of prostate cancer from histology onto corresponding MRI for prostatectomy specimens. Our method improves over intensity-based similarity metrics (mutual information) by incorporating unique information from feature spaces that are relatively robust to intensity artifacts and which accentuate the structural details in the target and template images to be registered. Our registration algorithm accounts for linear gland deformations in the histological sections resulting from gland fixing and serial sectioning. Following automatic registration of MRI and histology, cancer extent from histological sections are mapped to the corresponding registered MRI slices. The manually delineated cancer areas on MRI obtained via manual alignment of histological sections and MRI are compared with corresponding cancer extent obtained via COFEMI by a novel registration evaluation technique based on use of non-linear dimensionality reduction (locally linear embedding (LLE)). The cancer map on MRI determined by COFEMI was found to be significantly more accurate compared to the manually determined cancer mask. The performance of COFEMI was also found to be superior compared to image intensity-based mutual information registration.

  13. Multiscale registration of medical images based on edge preserving scale space with application in image-guided radiation therapy

    NASA Astrophysics Data System (ADS)

    Li, Dengwang; Li, Hongsheng; Wan, Honglin; Chen, Jinhu; Gong, Guanzhong; Wang, Hongjun; Wang, Liming; Yin, Yong

    2012-08-01

    Mutual information (MI) is a well-accepted similarity measure for image registration in medical systems. However, MI-based registration faces the challenges of high computational complexity and a high likelihood of being trapped into local optima due to an absence of spatial information. In order to solve these problems, multi-scale frameworks can be used to accelerate registration and improve robustness. Traditional Gaussian pyramid representation is one such technique but it suffers from contour diffusion at coarse levels which may lead to unsatisfactory registration results. In this work, a new multi-scale registration framework called edge preserving multiscale registration (EPMR) was proposed based upon an edge preserving total variation L1 norm (TV-L1) scale space representation. TV-L1 scale space is constructed by selecting edges and contours of images according to their size rather than the intensity values of the image features. This ensures more meaningful spatial information with an EPMR framework for MI-based registration. Furthermore, we design an optimal estimation of the TV-L1 parameter in the EPMR framework by training and minimizing the transformation offset between the registered pairs for automated registration in medical systems. We validated our EPMR method on both simulated mono- and multi-modal medical datasets with ground truth and clinical studies from a combined positron emission tomography/computed tomography (PET/CT) scanner. We compared our registration framework with other traditional registration approaches. Our experimental results demonstrated that our method outperformed other methods in terms of the accuracy and robustness for medical images. EPMR can always achieve a small offset value, which is closer to the ground truth both for mono-modality and multi-modality, and the speed can be increased 5-8% for mono-modality and 10-14% for multi-modality registration under the same condition. Furthermore, clinical application by adaptive

  14. Reliability-Based Decision Fusion in Multimodal Biometric Verification Systems

    NASA Astrophysics Data System (ADS)

    Kryszczuk, Krzysztof; Richiardi, Jonas; Prodanov, Plamen; Drygajlo, Andrzej

    2007-12-01

    We present a methodology of reliability estimation in the multimodal biometric verification scenario. Reliability estimation has shown to be an efficient and accurate way of predicting and correcting erroneous classification decisions in both unimodal (speech, face, online signature) and multimodal (speech and face) systems. While the initial research results indicate the high potential of the proposed methodology, the performance of the reliability estimation in a multimodal setting has not been sufficiently studied or evaluated. In this paper, we demonstrate the advantages of using the unimodal reliability information in order to perform an efficient biometric fusion of two modalities. We further show the presented method to be superior to state-of-the-art multimodal decision-level fusion schemes. The experimental evaluation presented in this paper is based on the popular benchmarking bimodal BANCA database.

  15. A Framework for a WAP-Based Course Registration System

    ERIC Educational Resources Information Center

    AL-Bastaki, Yousif; Al-Ajeeli, Abid

    2005-01-01

    This paper describes a WAP-based course registration system designed and implemented to facilitating the process of students' registration at Bahrain University. The framework will support many opportunities for applying WAP based technology to many services such as wireless commerce, cashless payment... and location-based services. The paper…

  16. Efficient Variational Approach to Multimodal Registration of Anatomical and Functional Intra-Patient Tumorous Brain Data.

    PubMed

    Legaz-Aparicio, Alvar-Ginés; Verdú-Monedero, Rafael; Larrey-Ruiz, Jorge; Morales-Sánchez, Juan; López-Mir, Fernando; Naranjo, Valery; Bernabéu, Ángela

    2016-11-29

    This paper addresses the functional localization of intra-patient images of the brain. Functional images of the brain (fMRI and PET) provide information about brain function and metabolism whereas anatomical images (MRI and CT) supply the localization of structures with high spatial resolution. The goal is to find the geometric correspondence between functional and anatomical images in order to complement and fuse the information provided by each imaging modality. The proposed approach is based on a variational formulation of the image registration problem in the frequency domain. It has been implemented as a C/C[Formula: see text] library which is invoked from a GUI. This interface is routinely used in the clinical setting by physicians for research purposes (Inscanner, Alicante, Spain), and may be used as well for diagnosis and surgical planning. The registration of anatomic and functional intra-patient images of the brain makes it possible to obtain a geometric correspondence which allows for the localization of the functional processes that occur in the brain. Through 18 clinical experiments, it has been demonstrated how the proposed approach outperforms popular state-of-the-art registration methods in terms of efficiency, information theory-based measures (such as mutual information) and actual registration error (distance in space of corresponding landmarks).

  17. Groupwise Registration Based on Hierarchical Image Clustering and Atlas Synthesis

    PubMed Central

    Wang, Qian; Chen, Liya; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang

    2010-01-01

    Groupwise registration has recently been proposed for simultaneous and consistent registration of all images in a group. Since many deformation parameters need to be optimized for each image under registration, the number of images that can be effectively handled by conventional groupwise registration methods is limited. Moreover, the robustness of registration is at stake due to significant intersubject variability. To overcome these problems, we present a groupwise registration framework, which is based on a hierarchical image clustering and atlas synthesis strategy. The basic idea is to decompose a large-scale groupwise registration problem into a series of small-scale problems, each of which is relatively easy to solve using a general computer. In particular, we employ a method called affinity propagation, which is designed for fast and robust clustering, to hierarchically cluster images into a pyramid of classes. Intraclass registration is then performed to register all images within individual classes, resulting in a representative center image for each class. These center images of different classes are further registered, from the bottom to the top in the pyramid. Once the registration reaches the summit of the pyramid, a single center image, or an atlas, is synthesized. Utilizing this strategy, we can efficiently and effectively register a large image group, construct their atlas, and, at the same time, establish shape correspondences between each image and the atlas. We have evaluated our framework using real and simulated data, and the results indicate that our framework achieves better robustness and registration accuracy compared to conventional methods. PMID:20063349

  18. Multimodal target correction by local bone registration: a PET/CT evaluation.

    PubMed

    Oliveira-Santos, Thiago; Weitzel, Thilo; Klaeser, Bernd; Krause, Thomas; Nolte, Lutz-Peter; Weber, Stefan; Reyes, Mauricio

    2010-01-01

    PET/CT guidance for percutaneous interventions allows biopsy of suspicious metabolically active bone lesions even when no morphological correlation is delineable in the CT images. Clinical use of PET/CT guidance with conventional step-by-step technique is time consuming and complicated especially in cases in which the target lesion is not shown in the CT image. Our recently developed multimodal instrument guidance system (IGS) for PET/CT improved this situation. Nevertheless, bone biopsies even with IGS have a trade-off between precision and intervention duration which is proportional to patient and personnel exposure to radiation. As image acquisition and reconstruction of PET may take up to 10 minutes, preferably only one time consuming combined PET/CT acquisition should be needed during an intervention. In case of required additional control images in order to check for possible patient movements/deformations, or to verify the final needle position in the target, only fast CT acquisitions should be performed. However, for precise instrument guidance accounting for patient movement and/or deformation without having a control PET image, it is essential to be able to transfer the position of the target as identified in the original PET/CT to a changed situation as shown in the control CT.

  19. Intensity-Based Registration for Lung Motion Estimation

    NASA Astrophysics Data System (ADS)

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

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

  20. Magnetic field sensing based on magnetic-fluid-clad multimode-singlemode-multimode fiber structures.

    PubMed

    Tang, Jiali; Pu, Shengli; Dong, Shaohua; Luo, Longfeng

    2014-10-14

    Magnetic field sensing based on magnetic-fluid-clad multimode-singlemode- multimode fiber structures is proposed and experimentalized. The structures are fabricated out using fiber fusion splicing techniques. The sensing principle is based on the interference between the core mode and cladding modes. Two interference dips are observed in our spectral range. Experimental results indicate that the magnetic field sensing sensitivities of 215 pm/mT and 0.5742 dB/mT are obtained for interference dip around 1595 nm. For interference dip around 1565 nm, the sensitivities are 60.5 pm/mT and 0.4821 dB/mT. The response of temperature is also investigated. The temperature sensitivity for the dip around 1595 nm is obtained to be 9.93 pm/°C.

  1. Dual-core steered non-rigid registration for multi-modal images via bi-directional image synthesis.

    PubMed

    Cao, Xiaohuan; Yang, Jianhua; Gao, Yaozong; Guo, Yanrong; Wu, Guorong; Shen, Dinggang

    2017-10-01

    In prostate cancer radiotherapy, computed tomography (CT) is widely used for dose planning purposes. However, because CT has low soft tissue contrast, it makes manual contouring difficult for major pelvic organs. In contrast, magnetic resonance imaging (MRI) provides high soft tissue contrast, which makes it ideal for accurate manual contouring. Therefore, the contouring accuracy on CT can be significantly improved if the contours in MRI can be mapped to CT domain by registering MRI with CT of the same subject, which would eventually lead to high treatment efficacy. In this paper, we propose a bi-directional image synthesis based approach for MRI-to-CT pelvic image registration. First, we use patch-wise random forest with auto-context model to learn the appearance mapping from CT to MRI domain, and then vice versa. Consequently, we can synthesize a pseudo-MRI whose anatomical structures are exactly same with CT but with MRI-like appearance, and a pseudo-CT as well. Then, our MRI-to-CT registration can be steered in a dual manner, by simultaneously estimating two deformation pathways: 1) one from the pseudo-CT to the actual CT and 2) another from actual MRI to the pseudo-MRI. Next, a dual-core deformation fusion framework is developed to iteratively and effectively combine these two registration pathways by using complementary information from both modalities. Experiments on a dataset with real pelvic CT and MRI have shown improved registration performance of the proposed method by comparing it to the conventional registration methods, thus indicating its high potential of translation to the routine radiation therapy. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Edge-based correlation image registration for multispectral imaging

    DOEpatents

    Nandy, Prabal

    2009-11-17

    Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

  3. Towards a Noninvasive Intracranial Tumor Irradiation Using 3D Optical Imaging and Multimodal Data Registration

    PubMed Central

    Posada, R.; Daul, Ch.; Wolf, D.; Aletti, P.

    2007-01-01

    Conformal radiotherapy (CRT) results in high-precision tumor volume irradiation. In fractioned radiotherapy (FRT), lesions are irradiated in several sessions so that healthy neighbouring tissues are better preserved than when treatment is carried out in one fraction. In the case of intracranial tumors, classical methods of patient positioning in the irradiation machine coordinate system are invasive and only allow for CRT in one irradiation session. This contribution presents a noninvasive positioning method representing a first step towards the combination of CRT and FRT. The 3D data used for the positioning is point clouds spread over the patient's head (CT-data usually acquired during treatment) and points distributed over the patient's face which are acquired with a structured light sensor fixed in the therapy room. The geometrical transformation linking the coordinate systems of the diagnosis device (CT-modality) and the 3D sensor of the therapy room (visible light modality) is obtained by registering the surfaces represented by the two 3D point sets. The geometrical relationship between the coordinate systems of the 3D sensor and the irradiation machine is given by a calibration of the sensor position in the therapy room. The global transformation, computed with the two previous transformations, is sufficient to predict the tumor position in the irradiation machine coordinate system with only the corresponding position in the CT-coordinate system. Results obtained for a phantom show that the mean positioning error of tumors on the treatment machine isocentre is 0.4 mm. Tests performed with human data proved that the registration algorithm is accurate (0.1 mm mean distance between homologous points) and robust even for facial expression changes. PMID:18364992

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

    PubMed

    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

    2013-07-21

    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

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

    NASA Astrophysics Data System (ADS)

    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

  6. Deformable Image Registration for Cone-Beam CT Guided Transoral Robotic Base of Tongue Surgery

    PubMed Central

    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.

    2013-01-01

    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 CT (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 support

  7. Content-based TV sports video retrieval using multimodal analysis

    NASA Astrophysics Data System (ADS)

    Yu, Yiqing; Liu, Huayong; Wang, Hongbin; Zhou, Dongru

    2003-09-01

    In this paper, we propose content-based video retrieval, which is a kind of retrieval by its semantical contents. Because video data is composed of multimodal information streams such as video, auditory and textual streams, we describe a strategy of using multimodal analysis for automatic parsing sports video. The paper first defines the basic structure of sports video database system, and then introduces a new approach that integrates visual stream analysis, speech recognition, speech signal processing and text extraction to realize video retrieval. The experimental results for TV sports video of football games indicate that the multimodal analysis is effective for video retrieval by quickly browsing tree-like video clips or inputting keywords within predefined domain.

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

    PubMed

    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.

  9. Overlay improvement by exposure map based mask registration optimization

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  10. A new frame-based registration algorithm

    NASA Technical Reports Server (NTRS)

    Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Sumanaweera, T. S.; Yen, S. Y.; Napel, S.

    1998-01-01

    This paper presents a new algorithm for frame registration. Our algorithm requires only that the frame be comprised of straight rods, as opposed to the N structures or an accurate frame model required by existing algorithms. The algorithm utilizes the full 3D information in the frame as well as a least squares weighting scheme to achieve highly accurate registration. We use simulated CT data to assess the accuracy of our algorithm. We compare the performance of the proposed algorithm to two commonly used algorithms. Simulation results show that the proposed algorithm is comparable to the best existing techniques with knowledge of the exact mathematical frame model. For CT data corrupted with an unknown in-plane rotation or translation, the proposed technique is also comparable to the best existing techniques. However, in situations where there is a discrepancy of more than 2 mm (0.7% of the frame dimension) between the frame and the mathematical model, the proposed technique is significantly better (p < or = 0.05) than the existing techniques. The proposed algorithm can be applied to any existing frame without modification. It provides better registration accuracy and is robust against model mis-match. It allows greater flexibility on the frame structure. Lastly, it reduces the frame construction cost as adherence to a concise model is not required.

  11. A new frame-based registration algorithm

    NASA Technical Reports Server (NTRS)

    Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Sumanaweera, T. S.; Yen, S. Y.; Napel, S.

    1998-01-01

    This paper presents a new algorithm for frame registration. Our algorithm requires only that the frame be comprised of straight rods, as opposed to the N structures or an accurate frame model required by existing algorithms. The algorithm utilizes the full 3D information in the frame as well as a least squares weighting scheme to achieve highly accurate registration. We use simulated CT data to assess the accuracy of our algorithm. We compare the performance of the proposed algorithm to two commonly used algorithms. Simulation results show that the proposed algorithm is comparable to the best existing techniques with knowledge of the exact mathematical frame model. For CT data corrupted with an unknown in-plane rotation or translation, the proposed technique is also comparable to the best existing techniques. However, in situations where there is a discrepancy of more than 2 mm (0.7% of the frame dimension) between the frame and the mathematical model, the proposed technique is significantly better (p < or = 0.05) than the existing techniques. The proposed algorithm can be applied to any existing frame without modification. It provides better registration accuracy and is robust against model mis-match. It allows greater flexibility on the frame structure. Lastly, it reduces the frame construction cost as adherence to a concise model is not required.

  12. Automatic visible and infrared face registration based on silhouette matching and robust transformation estimation

    NASA Astrophysics Data System (ADS)

    Tian, Tian; Mei, Xiaoguang; Yu, Yang; Zhang, Can; Zhang, Xiaoye

    2015-03-01

    Registration of multi-sensor data (particularly visible color sensors and infrared sensors) is a prerequisite for multimodal image analysis such as image fusion. In this paper, we proposed an automatic registration technique for visible and infrared face images based on silhouette matching and robust transformation estimation. The key idea is to represent a (visible or infrared) face image by its silhouette which is extracted from the image's edge map and consists of a set of discrete points, and then align the two silhouette point sets by using their feature similarity and spatial geometrical information. More precisely, our algorithm first matches the silhouette point sets by their local shape features such as shape context, which creates a set of putative correspondences that may contaminated by outliers. Next, we estimate the accurate transformation from the putative correspondence set under a robust maximum likelihood framework combining with the EM algorithm, where the transformation between the image pair is modeled by a parametric model such as the rigid or affine transformation. The qualitative and quantitative comparisons on a publicly available database demonstrate that our method significantly outperforms other state-of-the-art visible/infrared face registration methods. As a result, our method will be beneficial for fusion-based face recognition.

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

    PubMed

    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.

  14. Event based self-supervised temporal integration for multimodal sensor data.

    PubMed

    Barakova, Emilia I; Lourens, Tino

    2005-06-01

    A method for synergistic integration of multimodal sensor data is proposed in this paper. This method is based on two aspects of the integration process: (1) achieving synergistic integration of two or more sensory modalities, and (2) fusing the various information streams at particular moments during processing. Inspired by psychophysical experiments, we propose a self-supervised learning method for achieving synergy with combined representations. Evidence from temporal registration and binding experiments indicates that different cues are processed individually at specific time intervals. Therefore, an event-based temporal co-occurrence principle is proposed for the integration process. This integration method was applied to a mobile robot exploring unfamiliar environments. Simulations showed that integration enhanced route recognition with many perceptual similarities; moreover, they indicate that a perceptual hierarchy of knowledge about instant movement contributes significantly to short-term navigation, but that visual perceptions have bigger impact over longer intervals.

  15. Registration-based interpolation applied to cardiac MRI

    NASA Astrophysics Data System (ADS)

    Ólafsdóttir, Hildur; Pedersen, Henrik; Hansen, Michael S.; Lyksborg, Mark; Hansen, Mads Fogtmann; Darkner, Sune; Larsen, Rasmus

    2010-03-01

    Various approaches have been proposed for segmentation of cardiac MRI. An accurate segmentation of the myocardium and ventricles is essential to determine parameters of interest for the function of the heart, such as the ejection fraction. One problem with MRI is the poor resolution in one dimension. A 3D registration algorithm will typically use a trilinear interpolation of intensities to determine the intensity of a deformed template image. Due to the poor resolution across slices, such linear approximation is highly inaccurate since the assumption of smooth underlying intensities is violated. Registration-based interpolation is based on 2D registrations between adjacent slices and is independent of segmentations. Hence, rather than assuming smoothness in intensity, the assumption is that the anatomy is consistent across slices. The basis for the proposed approach is the set of 2D registrations between each pair of slices, both ways. The intensity of a new slice is then weighted by (i) the deformation functions and (ii) the intensities in the warped images. Unlike the approach by Penney et al. 2004, this approach takes into account deformation both ways, which gives more robustness where correspondence between slices is poor. We demonstrate the approach on a toy example and on a set of cardiac CINE MRI. Qualitative inspection reveals that the proposed approach provides a more convincing transition between slices than images obtained by linear interpolation. A quantitative validation reveals significantly lower reconstruction errors than both linear and registration-based interpolation based on one-way registrations.

  16. Microscopic neural image registration based on the structure of mitochondria

    NASA Astrophysics Data System (ADS)

    Cao, Huiwen; Han, Hua; Rao, Qiang; Xiao, Chi; Chen, Xi

    2017-02-01

    Microscopic image registration is a key component of the neural structure reconstruction with serial sections of neural tissue. The goal of microscopic neural image registration is to recover the 3D continuity and geometrical properties of specimen. During image registration, various distortions need to be corrected, including image rotation, translation, tissue deformation et.al, which come from the procedure of sample cutting, staining and imaging. Furthermore, there is only certain similarity between adjacent sections, and the degree of similarity depends on local structure of the tissue and the thickness of the sections. These factors make the microscopic neural image registration a challenging problem. To tackle the difficulty of corresponding landmarks extraction, we introduce a novel image registration method for Scanning Electron Microscopy (SEM) images of serial neural tissue sections based on the structure of mitochondria. The ellipsoidal shape of mitochondria ensures that the same mitochondria has similar shape between adjacent sections, and its characteristic of broad distribution in the neural tissue guarantees that landmarks based on the mitochondria distributed widely in the image. The proposed image registration method contains three parts: landmarks extraction between adjacent sections, corresponding landmarks matching and image deformation based on the correspondences. We demonstrate the performance of our method with SEM images of drosophila brain.

  17. Research on image registration based on D-Nets

    NASA Astrophysics Data System (ADS)

    Wu, Cengceng; Liu, Zhaoguang; Cheng, Hongtan

    2017-06-01

    Image registration is the key technology of digital imaging applications, it is used widely. We researched the image registration techniques in this paper. Based on the basis of D-Nets image registration algorithms, we propose a new innovation. We turn first to process image, so we can get synthetic images of original images and enhanced images. Then we extract SIFT feature in the original image. Next, in order to reduce noise of the image, we use the Gauss filter to process the synthesized image. Then we do experiments with synthetic images in the process of image registration. In this process, we use the D-Nets algorithm to achieve. Compared to the existing method, it can greatly improve the accuracy and recall.

  18. Modification of species-based differential evolution for multimodal optimization

    NASA Astrophysics Data System (ADS)

    Idrus, Said Iskandar Al; Syahputra, Hermawan; Firdaus, Muliawan

    2015-12-01

    At this time optimization has an important role in various fields as well as between other operational research, industry, finance and management. Optimization problem is the problem of maximizing or minimizing a function of one variable or many variables, which include unimodal and multimodal functions. Differential Evolution (DE), is a random search technique using vectors as an alternative solution in the search for the optimum. To localize all local maximum and minimum on multimodal function, this function can be divided into several domain of fitness using niching method. Species-based niching method is one of method that build sub-populations or species in the domain functions. This paper describes the modification of species-based previously to reduce the computational complexity and run more efficiently. The results of the test functions show species-based modifications able to locate all the local optima in once run the program.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

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

    PubMed

    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

    2014-11-21

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  2. Smart automotive bumper based on a multimode optical fiber

    NASA Astrophysics Data System (ADS)

    Meyrueis, Patrick; Kress, Bernard; Fischer, Sylvain

    2007-09-01

    We are presenting a novel shock sensor device based on multimode optical fiber. This device is an elementary fiber sensor tailored for the transportation industry, and especially the automotive industry, allowing detection of shocks and the measurement of the deformation of surface external of the system. We also show how a plurality for such sensors can be combined in order to detect and characterize the shock in order to trigger an adapted response from the vehicle for added safety.

  3. Precise numerical modeling of next generation multimode fiber based links

    NASA Astrophysics Data System (ADS)

    Maksymiuk, L.; Stepniak, G.

    2015-12-01

    In order to numerically model modern multimode fiber based links we are required to take into account modal and chromatic dispersion, profile dispersion and spectral dependent coupling. In this paper we propose a complete numerical model which not only is precise but also versatile. Additionally to the detailed mathematical description of the model we provide also a bunch of numerical calculations performed with the use of the model.

  4. Multimodality Non-Rigid Image Registration for Planning, Targeting and Monitoring during CT-guided Percutaneous Liver Tumor Cryoablation

    PubMed Central

    Elhawary, Haytham; Oguro, Sota; Tuncali, Kemal; Morrison, Paul R.; Tatli, Servet; Shyn, Paul B.; Silverman, Stuart G.; Hata, Nobuhiko

    2010-01-01

    Rationale and Objectives To develop non-rigid image registration between pre-procedure contrast enhanced MR images and intra-procedure unenhanced CT images, to enhance tumor visualization and localization during CT-guided liver tumor cryoablation procedures. Materials and Methods After IRB approval, a non-rigid registration (NRR) technique was evaluated with different pre-processing steps and algorithm parameters and compared to a standard rigid registration (RR) approach. The Dice Similarity Coefficient (DSC), Target Registration Error (TRE), 95% Hausdorff distance (HD) and total registration time (minutes) were compared using a two-sided Student’s t-test. The entire registration method was then applied during five CT-guided liver cryoablation cases with the intra-procedural CT data transmitted directly from the CT scanner, with both accuracy and registration time evaluated. Results Selected optimal parameters for registration were section thickness of 5mm, cropping the field of view to 66% of its original size, manual segmentation of the liver, B-spline control grid of 5×5×5 and spatial sampling of 50,000 pixels. Mean 95% HD of 3.3mm (2.5x improvement compared to RR, p<0.05); mean DSC metric of 0.97 (13% increase); and mean TRE of 4.1mm (2.7x reduction) were measured. During the cryoablation procedure registration between the pre-procedure MR and the planning intra-procedure CT took a mean time of 10.6 minutes, the MR to targeting CT image took 4 minutes and MR to monitoring CT took 4.3 minutes. Mean registration accuracy was under 3.4mm. Conclusion Non-rigid registration allowed improved visualization of the tumor during interventional planning, targeting and evaluation of tumor coverage by the ice ball. Future work is focused on reducing segmentation time to make the method more clinically acceptable. PMID:20817574

  5. Automated Registration of Freehand B-Mode Ultrasound and Magnetic Resonance Imaging of the Carotid Arteries Based on Geometric Features.

    PubMed

    Carvalho, Diego D B; Arias Lorza, Andres Mauricio; Niessen, Wiro J; de Bruijne, Marleen; Klein, Stefan

    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 and segmentations by minimizing a weighted sum of the Euclidean distance between centerlines and the dissimilarity between segmentations. The method was evaluated in 28 carotid arteries from eight patients and six healthy volunteers. First, the automated US lumen segmentation method was validated and optimized in a cross-validation experiment. Next, the effect of the weighting parameter of the proposed registration dissimilarity metric and the control point spacing in the non-rigid registration was evaluated. Finally, the proposed registration method was evaluated in comparison to an existing intensity-and-point-based method, a registration using only the centerlines and a registration using manual US lumen segmentations. Registration accuracy was measured in terms of the mean surface distance between manual US segmentations and the registered MRI segmentations. The average mean surface distance was 0.78 ± 0.34 mm for all subjects, 0.65 ± 0.09 mm for healthy volunteers and 0.87 ± 0.42 mm for patients. The results for the complete set were significantly better (Wilcoxon test, p < 0.01) than the results for the intensity-and-point-based method and the centerline-based registration method. We conclude that the proposed method can robustly and accurately register US and MR images of the carotid artery, allowing multimodal analysis of the carotid plaque to improve

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

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

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

  7. SAR image registration based on SIFT and MSA

    NASA Astrophysics Data System (ADS)

    Yi, Zhaoxiang; Zhang, Xiongmei; Mu, Xiaodong; Wang, Kui; Song, Jianshe

    2014-02-01

    Referring to the problem of SAR image registration, an image registration method based on Scale Invariant Feature Transform (SIFT) and Multi-Scale Autoconvolution (MSA) is proposed. Based on the extraction of SIFT descriptors and the MSA affine invariant moments of the region around the keypoints, the feature fusion method based on canonical correlation analysis (CCA) is employed to fuse them together to be a new descriptor. After the control points are rough matched, the distance and gray correlation around the rough matched points are combined to build the similarity matrix and the singular value decomposition (SVD) method is employed to realize precise image registration. Finally, the affine transformation parameters are obtained and the images are registered. Experimental results show that the proposed method outperforms the SIFT method and achieves high accuracy in sub-pixel level.

  8. Automated retina identification based on multiscale elastic registration.

    PubMed

    Figueiredo, Isabel N; Moura, Susana; Neves, Júlio S; Pinto, Luís; Kumar, Sunil; Oliveira, Carlos M; Ramos, João D

    2016-12-01

    In this work we propose a novel method for identifying individuals based on retinal fundus image matching. The method is based on the image registration of retina blood vessels, since it is known that the retina vasculature of an individual is a signature, i.e., a distinctive pattern of the individual. The proposed image registration consists of a multiscale affine registration followed by a multiscale elastic registration. The major advantage of this particular two-step image registration procedure is that it is able to account for both rigid and non-rigid deformations either inherent to the retina tissues or as a result of the imaging process itself. Afterwards a decision identification measure, relying on a suitable normalized function, is defined to decide whether or not the pair of images belongs to the same individual. The method is tested on a data set of 21721 real pairs generated from a total of 946 retinal fundus images of 339 different individuals, consisting of patients followed in the context of different retinal diseases and also healthy patients. The evaluation of its performance reveals that it achieves a very low false rejection rate (FRR) at zero FAR (the false acceptance rate), equal to 0.084, as well as a low equal error rate (EER), equal to 0.053. Moreover, the tests performed by using only the multiscale affine registration, and discarding the multiscale elastic registration, clearly show the advantage of the proposed approach. The outcome of this study also indicates that the proposed method is reliable and competitive with other existing retinal identification methods, and forecasts its future appropriateness and applicability in real-life applications.

  9. Automatic image-to-world registration based on x-ray projections in cone-beam CT-guided interventions.

    PubMed

    Hamming, N M; Daly, M J; Irish, J C; Siewerdsen, J H

    2009-05-01

    Intraoperative imaging offers a means to account for morphological changes occurring during the procedure and resolve geometric uncertainties via integration with a surgical navigation system. Such integration requires registration of the image and world reference frames, conventionally a time consuming, error-prone manual process. This work presents a method of automatic image-to-world registration of intraoperative cone-beam computed tomography (CBCT) and an optical tracking system. Multimodality (MM) markers consisting of an infrared (IR) reflective sphere with a 2 mm tungsten sphere (BB) placed precisely at the center were designed to permit automatic detection in both the image and tracking (world) reference frames. Image localization is performed by intensity thresholding and pattern matching directly in 2D projections acquired in each CBCT scan, with 3D image coordinates computed using backprojection and accounting for C-arm geometric calibration. The IR tracking system localized MM markers in the world reference frame, and the image-to-world registration was computed by rigid point matching of image and tracker point sets. The accuracy and reproducibility of the automatic registration technique were compared to conventional (manual) registration using a variety of marker configurations suitable to neurosurgery (markers fixed to cranium) and head and neck surgery (markers suspended on a subcranial frame). The automatic technique exhibited subvoxel marker localization accuracy (< 0.8 mm) for all marker configurations. The fiducial registration error of the automatic technique was (0.35 +/-0.01) mm, compared to (0.64 +/- 0.07 mm) for the manual technique, indicating improved accuracy and reproducibility. The target registration error (TRE) averaged over all configurations was 1.14 mm for the automatic technique, compared to 1.29 mm for the manual in accuracy, although the difference was not statistically significant (p = 0.3). A statistically significant

  10. Landmark-based image registration using Gneiting's compactly supported functions

    NASA Astrophysics Data System (ADS)

    Cavoretto, Roberto; De Rossi, Alessandra

    2012-09-01

    In this paper we consider landmark-based image registration with compactly supported radial basis functions. Since using globally supported functions, as for example radial basis functions, a single landmark pair change may influence the whole registration result, in 2001 Fornefett et al. introduced the use of Wendland's compactly supported functions to define landmark-based image transformations [6]. Here we propose transformations defined by means of another family of compactly supported radial basis functions, known as Gneiting's functions [7, 5]. Firstly, we briefly review their definitions and properties. Secondly, numerical experiments are presented, where we compare Gneiting's functions with other interpolants.

  11. Reconstruction-based 3D/2D image registration.

    PubMed

    Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo

    2005-01-01

    In this paper we present a novel 3D/2D registration method, where first, a 3D image is reconstructed from a few 2D X-ray images and next, the preoperative 3D image is brought into the best possible spatial correspondence with the reconstructed image by optimizing a similarity measure. Because the quality of the reconstructed image is generally low, we introduce a novel asymmetric mutual information similarity measure, which is able to cope with low image quality as well as with different imaging modalities. The novel 3D/2D registration method has been evaluated using standardized evaluation methodology and publicly available 3D CT, 3DRX, and MR and 2D X-ray images of two spine phantoms, for which gold standard registrations were known. In terms of robustness, reliability and capture range the proposed method outperformed the gradient-based method and the method based on digitally reconstructed radiographs (DRRs).

  12. Biomechanical based image registration for head and neck radiation treatment

    NASA Astrophysics Data System (ADS)

    Al-Mayah, Adil; Moseley, Joanne; Hunter, Shannon; Velec, Mike; Chau, Lily; Breen, Stephen; Brock, Kristy

    2010-02-01

    Deformable image registration of four head and neck cancer patients was conducted using biomechanical based model. Patient specific 3D finite element models have been developed using CT and cone beam CT image data of the planning and a radiation treatment session. The model consists of seven vertebrae (C1 to C7), mandible, larynx, left and right parotid glands, tumor and body. Different combinations of boundary conditions are applied in the model in order to find the configuration with a minimum registration error. Each vertebra in the planning session is individually aligned with its correspondence in the treatment session. Rigid alignment is used for each individual vertebra and to the mandible since deformation is not expected in the bones. In addition, the effect of morphological differences in external body between the two image sessions is investigated. The accuracy of the registration is evaluated using the tumor, and left and right parotid glands by comparing the calculated Dice similarity index of these structures following deformation in relation to their true surface defined in the image of the second session. The registration improves when the vertebrae and mandible are aligned in the two sessions with the highest Dice index of 0.86+/-0.08, 0.84+/-0.11, and 0.89+/-0.04 for the tumor, left and right parotid glands, respectively. The accuracy of the center of mass location of tumor and parotid glands is also improved by deformable image registration where the error in the tumor and parotid glands decreases from 4.0+/-1.1, 3.4+/-1.5, and 3.8+/-0.9 mm using rigid registration to 2.3+/-1.0, 2.5+/-0.8 and 2.0+/-0.9 mm in the deformable image registration when alignment of vertebrae and mandible is conducted in addition to the surface projection of the body.

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

    PubMed

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

    2016-04-01

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

  14. Multimode model based defect characterization in composites

    NASA Astrophysics Data System (ADS)

    Roberts, R.; Holland, S.; Gregory, E.

    2016-02-01

    A newly-initiated research program for model-based defect characterization in CFRP composites is summarized. The work utilizes computational models of the interaction of NDE probing energy fields (ultrasound and thermography), to determine 1) the measured signal dependence on material and defect properties (forward problem), and 2) an assessment of performance-critical defect properties from analysis of measured NDE signals (inverse problem). Work is reported on model implementation for inspection of CFRP laminates containing delamination and porosity. Forward predictions of measurement response are presented, as well as examples of model-based inversion of measured data for the estimation of defect parameters.

  15. Accelerated Nonrigid Intensity-Based Image Registration Using Importance Sampling

    PubMed Central

    Bhagalia, Roshni; Fessler, Jeffrey A.; Kim, Boklye

    2015-01-01

    Nonrigid image registration methods using intensity-based similarity metrics are becoming increasingly common tools to estimate many types of deformations. Nonrigid warps can be very flexible with a large number of parameters and gradient optimization schemes are widely used to estimate them. However for large datasets, the computation of the gradient of the similarity metric with respect to these many parameters becomes very time consuming. Using a small random subset of image voxels to approximate the gradient can reduce computation time. This work focuses on the use of importance sampling to improve accuracy and reduce the variance of this gradient approximation. The proposed importance sampling framework is based on an edge-dependent adaptive sampling distribution designed for use with intensity-based registration algorithms. We compare the performance of registration based on stochastic approximations with and without importance sampling to that using deterministic gradient descent. Empirical results, on simulated MR brain data and real CT inhale-exhale lung data from 8 subjects, show that a combination of stochastic approximation methods and importance sampling improves the rate of convergence of the registration process while preserving accuracy. PMID:19211343

  16. Accelerated nonrigid intensity-based image registration using importance sampling.

    PubMed

    Bhagalia, Roshni; Fessler, Jeffrey A; Kim, Boklye

    2009-08-01

    Nonrigid image registration methods using intensity-based similarity metrics are becoming increasingly common tools to estimate many types of deformations. Nonrigid warps can be very flexible with a large number of parameters and gradient optimization schemes are widely used to estimate them. However, for large datasets, the computation of the gradient of the similarity metric with respect to these many parameters becomes very time consuming. Using a small random subset of image voxels to approximate the gradient can reduce computation time. This work focuses on the use of importance sampling to reduce the variance of this gradient approximation. The proposed importance sampling framework is based on an edge-dependent adaptive sampling distribution designed for use with intensity-based registration algorithms. We compare the performance of registration based on stochastic approximations with and without importance sampling to that using deterministic gradient descent. Empirical results, on simulated magnetic resonance brain data and real computed tomography inhale-exhale lung data from eight subjects, show that a combination of stochastic approximation methods and importance sampling accelerates the registration process while preserving accuracy.

  17. A novel automated method for doing registration and 3D reconstruction from multi-modal RGB/IR image sequences

    NASA Astrophysics Data System (ADS)

    Kirby, Richard; Whitaker, Ross

    2016-09-01

    In recent years, the use of multi-modal camera rigs consisting of an RGB sensor and an infrared (IR) sensor have become increasingly popular for use in surveillance and robotics applications. The advantages of using multi-modal camera rigs include improved foreground/background segmentation, wider range of lighting conditions under which the system works, and richer information (e.g. visible light and heat signature) for target identification. However, the traditional computer vision method of mapping pairs of images using pixel intensities or image features is often not possible with an RGB/IR image pair. We introduce a novel method to overcome the lack of common features in RGB/IR image pairs by using a variational methods optimization algorithm to map the optical flow fields computed from different wavelength images. This results in the alignment of the flow fields, which in turn produce correspondences similar to those found in a stereo RGB/RGB camera rig using pixel intensities or image features. In addition to aligning the different wavelength images, these correspondences are used to generate dense disparity and depth maps. We obtain accuracies similar to other multi-modal image alignment methodologies as long as the scene contains sufficient depth variations, although a direct comparison is not possible because of the lack of standard image sets from moving multi-modal camera rigs. We test our method on synthetic optical flow fields and on real image sequences that we created with a multi-modal binocular stereo RGB/IR camera rig. We determine our method's accuracy by comparing against a ground truth.

  18. Multimodal sensing-based camera applications

    NASA Astrophysics Data System (ADS)

    Bordallo López, Miguel; Hannuksela, Jari; Silvén, J. Olli; Vehviläinen, Markku

    2011-02-01

    The increased sensing and computing capabilities of mobile devices can provide for enhanced mobile user experience. Integrating the data from different sensors offers a way to improve application performance in camera-based applications. A key advantage of using cameras as an input modality is that it enables recognizing the context. Therefore, computer vision has been traditionally utilized in user interfaces to observe and automatically detect the user actions. The imaging applications can also make use of various sensors for improving the interactivity and the robustness of the system. In this context, two applications fusing the sensor data with the results obtained from video analysis have been implemented on a Nokia Nseries mobile device. The first solution is a real-time user interface that can be used for browsing large images. The solution enables the display to be controlled by the motion of the user's hand using the built-in sensors as complementary information. The second application is a real-time panorama builder that uses the device's accelerometers to improve the overall quality, providing also instructions during the capture. The experiments show that fusing the sensor data improves camera-based applications especially when the conditions are not optimal for approaches using camera data alone.

  19. Multimodal Based Classification of Schizophrenia Patients

    PubMed Central

    Cetin, Mustafa S; Houck, Jon M.; Vergara, Victor M.; Miller, Robyn L.; Calhoun, Vince

    2016-01-01

    Schizophrenia is currently diagnosed by physicians through clinical assessment and their evaluation of patient’s self-reported experiences over the longitudinal course of the illness. There is great interest in identifying biologically based markers at the onset of illness, rather than relying on the evolution of symptoms across time. Functional network connectivity shows promise in providing individual subject predictive power. The majority of previous studies considered the analysis of functional connectivity during resting-state using only fMRI. However, exclusive reliance on fMRI to generate such networks, may limit inference on dysfunctional connectivity, which is hypothesized to underlie patient symptoms. In this work, we propose a framework for classification of schizophrenia patients and healthy control subjects based on using both fMRI and band limited envelope correlation metrics in MEG to interrogate functional network components in the resting state. Our results show that the combination of these two methods provide valuable information that captures fundamental characteristics of brain network connectivity in schizophrenia. Such information is useful for prediction of schizophrenia patients. Classification accuracy performance was improved significantly (up to ≈ 7%) relative to only the fMRI method and (up to ≈ 21%) relative to only the MEG method. PMID:26736831

  20. Intelligent Human Tracking Based on Multimodal Integration

    NASA Astrophysics Data System (ADS)

    Nakamura, Keisuke; Nakadai, Kazuhiro; Asano, Futoshi; Nakajima, Hirofumi; Ince, Gökhan

    Localization and tracking of humans are essential research topics in robotics. In particular, Sound Source Localization (SSL) has been of great interest. Despite the numerous reported methods, SSL in a real environment had mainly three issues; robustness against noise with high power, no framework for selective listening to sound sources, and tracking of inactive and/or noisy sound sources. For the first issue, we extended Multiple SIgnal Classification by incorporating Generalized Eigen Value Decomposition (GEVD-MUSIC) so that it can deal with high power noise and can select target sound sources. For the second issue, we proposed Sound Source Identification (SSI) based on hierarchical Gaussian mixture models and integrated it with GEVD-MUSIC to realize a function to listen to a specific sound source according to the sort of the sound source. For the third issue, auditory and visual human tracking were integrated using particle filtering. These three techniques are integrated into an intelligent human tracking system. Experimental results showed that integration of SSL and SSI successfully achieved human tracking only by audition, and the audio-visual integration showed considerable improvement in tracking by compensating the loss of auditory or visual information.

  1. Scene change detection based on multimodal integration

    NASA Astrophysics Data System (ADS)

    Zhu, Yingying; Zhou, Dongru

    2003-09-01

    Scene change detection is an essential step to automatic and content-based video indexing, retrieval and browsing. In this paper, a robust scene change detection and classification approach is presented, which analyzes audio, visual and textual sources and accounts for their inter-relations and coincidence to semantically identify and classify video scenes. Audio analysis focuses on the segmentation of audio stream into four types of semantic data such as silence, speech, music and environmental sound. Further processing on speech segments aims at locating speaker changes. Video analysis partitions visual stream into shots. Text analysis can provide a supplemental source of clues for scene classification and indexing information. We integrate the video and audio analysis results to identify video scenes and use the text information detected by the video OCR technology or derived from transcripts available to refine scene classification. Results from single source segmentation are in some cases suboptimal. By combining visual, aural features adn the accessorial text information, the scence extraction accuracy is enhanced, and more semantic segmentations are developed. Experimental results are proven to rather promising.

  2. Multimodal Feature-Based Surface Material Classification.

    PubMed

    Strese, Matti; Schuwerk, Clemens; Iepure, Albert; Steinbach, Eckehard

    2017-01-01

    When a tool is tapped on or dragged over an object surface, vibrations are induced in the tool, which can be captured using acceleration sensors. The tool-surface interaction additionally creates audible sound waves, which can be recorded using microphones. Features extracted from camera images provide additional information about the surfaces. We present an approach for tool-mediated surface classification that combines these signals and demonstrate that the proposed method is robust against variable scan-time parameters. We examine freehand recordings of 69 textured surfaces recorded by different users and propose a classification system that uses perception-related features, such as hardness, roughness, and friction; selected features adapted from speech recognition, such as modified cepstral coefficients applied to our acceleration signals; and surface texture-related image features. We focus on mitigating the effect of variable contact force and exploration velocity conditions on these features as a prerequisite for a robust machine-learning-based approach for surface classification. The proposed system works without explicit scan force and velocity measurements. Experimental results show that our proposed approach allows for successful classification of textured surfaces under variable freehand movement conditions, exerted by different human operators. The proposed subset of six features, selected from the described sound, image, friction force, and acceleration features, leads to a classification accuracy of 74 percent in our experiments when combined with a Naive Bayes classifier.

  3. Feature-based Alignment of Volumetric Multi-modal Images

    PubMed Central

    Toews, Matthew; Zöllei, Lilla; Wells, William M.

    2014-01-01

    This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

  4. Implicit function-based phantoms for evaluation of registration algorithms

    NASA Astrophysics Data System (ADS)

    Gopalakrishnan, Girish; Poston, Timothy; Nagaraj, Nithin; Mullick, Rakesh; Knoplioch, Jerome

    2005-04-01

    Medical image fusion is increasingly enhancing diagnostic accuracy by synergizing information from multiple images, obtained by the same modality at different times or from complementary modalities such as structural information from CT and functional from PET. An active, crucial research topic in fusion is validation of the registration (point-to-point correspondence) used. Phantoms and other simulated studies are useful in the absence of, or as a preliminary to, definitive clinical tests. Software phantoms in specific have the added advantage of robustness, repeatability and reproducibility. Our virtual-lung-phantom-based scheme can test the accuracy of any registration algorithm and is flexible enough for added levels of complexity (addition of blur/anti-alias, rotate/warp, and modality-associated noise) to help evaluate the robustness of an image registration/fusion methodology. Such a framework extends easily to different anatomies. The feature of adding software-based fiducials both within and outside simulated anatomies prove more beneficial when compared to experiments using data from external fiducials on a patient. It would help the diagnosing clinician make a prudent choice of registration algorithm.

  5. Reducing uncertainties in volumetric image based deformable organ registration.

    PubMed

    Liang, J; Yan, D

    2003-08-01

    Applying volumetric image feedback in radiotherapy requires image based deformable organ registration. The foundation of this registration is the ability of tracking subvolume displacement in organs of interest. Subvolume displacement can be calculated by applying biomechanics model and the finite element method to human organs manifested on the multiple volumetric images. The calculation accuracy, however, is highly dependent on the determination of the corresponding organ boundary points. Lacking sufficient information for such determination, uncertainties are inevitable-thus diminishing the registration accuracy. In this paper, a method of consuming energy minimization was developed to reduce these uncertainties. Starting from an initial selection of organ boundary point correspondence on volumetric image sets, the subvolume displacement and stress distribution of the whole organ are calculated and the consumed energy due to the subvolume displacements is computed accordingly. The corresponding positions of the initially selected boundary points are then iteratively optimized to minimize the consuming energy under geometry and stress constraints. In this study, a rectal wall delineated from patient CT image was artificially deformed using a computer simulation and utilized to test the optimization. Subvolume displacements calculated based on the optimized boundary point correspondence were compared to the true displacements, and the calculation accuracy was thereby evaluated. Results demonstrate that a significant improvement on the accuracy of the deformable organ registration can be achieved by applying the consuming energy minimization in the organ deformation calculation.

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

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

    NASA Astrophysics Data System (ADS)

    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).

  8. Intra-patient colon surface registration based on teniae; coli

    NASA Astrophysics Data System (ADS)

    Lamy, Julien; Summers, Ronald M.

    2007-03-01

    CT colonography, a prevalent tool to diagnose colon cancer in its early stages, is often limited by bad distention, or retained fluids, which will cause segments of the colon to be impossible to process by CAD tools. By scanning patients in both prone and supine positions, collapsed segments and retained fluids will not be in the same place in both images, increasing the length of the colon that can be processed correctly. In order to fully use these two scans, they must be registered, so that a lesion identified on one of them can be mapped to the other, thus increasing sensitivity and specificity of CAD tools. The surface of the colon is however large (more than half a million vertices on our images), and has no canonical shape, which makes atlases and other widely used registration algorithms non optimal. We present in this paper a fast method to register the colon surface between prone and supine scans using landmarks present on the colon, the teniae coli. Our method is composed of three steps. First, we register the body, based on manually placed landmarks. Then we register the three teniae; coli, and, from this registration, we compute a deformation field for each vertex of the colon surface. We tested our method on 5 cases, by measuring the RMS error after body registration, quantifying the intrisic movement of the colon, and after colon surface registration. The RMS error was reduced from 1.8 cm to 0.49 cm, a reduction of 71%.

  9. The neurocognitive bases of human multimodal food perception: consciousness.

    PubMed

    Verhagen, Justus V

    2007-02-01

    This review explores how we become aware of the (integrated) flavor of food. In recent years, progress has been made understanding the neural correlates of consciousness. Experimental and computational data have been largely based on the visual system. Contemporary neurobiological frameworks of consciousness are reviewed, concluding that neural reverberation among forward- and back-projecting neural ensembles across brain areas is a common theme. In an attempt to extrapolate these concepts to the oral-sensory and olfactory systems involved with multimodal flavor perception, the integration of the sensory information of which into a flavor gestalt has been reviewed elsewhere (Verhagen, J.V., Engelen, L., 2006. The neurocognitive bases of human multimodal food perception: Sensory integration. Neurosci. Biobehav. Rev. 30(5): 613_650), I reconceptualize the flavor-sensory system by integrating it into a larger neural system termed the Homeostatic Interoceptive System (HIS). This system consists of an oral (taste, oral touch, etc.) and non-oral part (non oral-thermosensation, pain, etc.) which are anatomically and functionally highly similar. Consistent with this new concept and with a large volume of experimental data, I propose that awareness of intraoral food is related to the concomitant reverberant self-sustained activation of a coalition of neuronal subsets in agranular insula and orbitofrontal cortex (affect, hedonics) and agranular insula and perirhinal cortex (food identity), as well as the amygdala (affect and identity) in humans. I further discuss the functional anatomy in relation essential nodes. These formulations are by necessity to some extent speculative.

  10. Multimodal biometrics system based on face profile and ear

    NASA Astrophysics Data System (ADS)

    Youssef, Iman S.; Abaza, Ayman A.; Rasmy, Mohamed E.; Badawi, Ahmed M.

    2014-05-01

    Face recognition from a side profile view, has recently received significant attention in the literature. Even though current face recognition systems have reached a certain level of maturity at angles up to 30 degrees, their success is still limited with side profile angles. This paper presents an efficient technique for the fusion of face profile and ear biometrics. We propose to use a Block-based Local Binary Pattern (LBP) to generate the features for recognition from face profile images and ear images. These feature distributions are then fused at the score level using simple mean rule. Experimental results show that the proposed multimodal system can achieve 97:98% recognition performance, compared to unimodal biometrics of face profile 96.76%, and unimodal biometrics of ear 96.95%, details in the Experimental Results Section. Comparisons with other multimodal systems used in the literature, like Principal Component Analysis (PCA), Full-space Linear Discriminant Analysis (FSLDA) and Kernel Fisher discriminant analysis (KFDA), are presented in the Experimental Results Section.

  11. Multi-mode reliability-based design of horizontal curves.

    PubMed

    Essa, Mohamed; Sayed, Tarek; Hussein, Mohamed

    2016-08-01

    Recently, reliability analysis has been advocated as an effective approach to account for uncertainty in the geometric design process and to evaluate the risk associated with a particular design. In this approach, a risk measure (e.g. probability of noncompliance) is calculated to represent the probability that a specific design would not meet standard requirements. The majority of previous applications of reliability analysis in geometric design focused on evaluating the probability of noncompliance for only one mode of noncompliance such as insufficient sight distance. However, in many design situations, more than one mode of noncompliance may be present (e.g. insufficient sight distance and vehicle skidding at horizontal curves). In these situations, utilizing a multi-mode reliability approach that considers more than one failure (noncompliance) mode is required. The main objective of this paper is to demonstrate the application of multi-mode (system) reliability analysis to the design of horizontal curves. The process is demonstrated by a case study of Sea-to-Sky Highway located between Vancouver and Whistler, in southern British Columbia, Canada. Two noncompliance modes were considered: insufficient sight distance and vehicle skidding. The results show the importance of accounting for several noncompliance modes in the reliability model. The system reliability concept could be used in future studies to calibrate the design of various design elements in order to achieve consistent safety levels based on all possible modes of noncompliance.

  12. Validation of a deformable image registration technique for cone beam CT-based dose verification

    SciTech Connect

    Moteabbed, M. Sharp, G. C.; Wang, Y.; Trofimov, A.; Efstathiou, J. A.; Lu, H.-M.

    2015-01-15

    Purpose: As radiation therapy evolves toward more adaptive techniques, image guidance plays an increasingly important role, not only in patient setup but also in monitoring the delivered dose and adapting the treatment to patient changes. This study aimed to validate a method for evaluation of delivered intensity modulated radiotherapy (IMRT) dose based on multimodal deformable image registration (DIR) for prostate treatments. Methods: A pelvic phantom was scanned with CT and cone-beam computed tomography (CBCT). Both images were digitally deformed using two realistic patient-based deformation fields. The original CT was then registered to the deformed CBCT resulting in a secondary deformed CT. The registration quality was assessed as the ability of the DIR method to recover the artificially induced deformations. The primary and secondary deformed CT images as well as vector fields were compared to evaluate the efficacy of the registration method and it’s suitability to be used for dose calculation. PLASTIMATCH, a free and open source software was used for deformable image registration. A B-spline algorithm with optimized parameters was used to achieve the best registration quality. Geometric image evaluation was performed through voxel-based Hounsfield unit (HU) and vector field comparison. For dosimetric evaluation, IMRT treatment plans were created and optimized on the original CT image and recomputed on the two warped images to be compared. The dose volume histograms were compared for the warped structures that were identical in both warped images. This procedure was repeated for the phantom with full, half full, and empty bladder. Results: The results indicated mean HU differences of up to 120 between registered and ground-truth deformed CT images. However, when the CBCT intensities were calibrated using a region of interest (ROI)-based calibration curve, these differences were reduced by up to 60%. Similarly, the mean differences in average vector field

  13. Validation of a deformable image registration technique for cone beam CT-based dose verification

    PubMed Central

    Moteabbed, M.; Sharp, G. C.; Wang, Y.; Trofimov, A.; Efstathiou, J. A.; Lu, H.-M.

    2015-01-01

    Purpose: As radiation therapy evolves toward more adaptive techniques, image guidance plays an increasingly important role, not only in patient setup but also in monitoring the delivered dose and adapting the treatment to patient changes. This study aimed to validate a method for evaluation of delivered intensity modulated radiotherapy (IMRT) dose based on multimodal deformable image registration (dir) for prostate treatments. Methods: A pelvic phantom was scanned with CT and cone-beam computed tomography (CBCT). Both images were digitally deformed using two realistic patient-based deformation fields. The original CT was then registered to the deformed CBCT resulting in a secondary deformed CT. The registration quality was assessed as the ability of the dir method to recover the artificially induced deformations. The primary and secondary deformed CT images as well as vector fields were compared to evaluate the efficacy of the registration method and it’s suitability to be used for dose calculation. plastimatch, a free and open source software was used for deformable image registration. A B-spline algorithm with optimized parameters was used to achieve the best registration quality. Geometric image evaluation was performed through voxel-based Hounsfield unit (HU) and vector field comparison. For dosimetric evaluation, IMRT treatment plans were created and optimized on the original CT image and recomputed on the two warped images to be compared. The dose volume histograms were compared for the warped structures that were identical in both warped images. This procedure was repeated for the phantom with full, half full, and empty bladder. Results: The results indicated mean HU differences of up to 120 between registered and ground-truth deformed CT images. However, when the CBCT intensities were calibrated using a region of interest (ROI)-based calibration curve, these differences were reduced by up to 60%. Similarly, the mean differences in average vector field

  14. Exploiting multimode waveguides for pure fibre-based imaging.

    PubMed

    Cižmár, Tomáš; Dholakia, Kishan

    2012-01-01

    There has been an immense drive in modern microscopy towards miniaturization and fibre-based technology. This has been necessitated by the need to access hostile or difficult environments in situ and in vivo. Strategies to date have included the use of specialist fibres and miniaturized scanning systems accompanied by ingenious microfabricated lenses. Here we present a novel approach for this field by utilizing disordered light within a standard multimode optical fibre for lensless microscopy and optical mode conversion. We demonstrate the modalities of bright- and dark-field imaging and scanning fluorescence microscopy at acquisition rates that allow observation of dynamic processes such as Brownian motion of mesoscopic particles. Furthermore, we show how such control can realize a new form of mode converter and generate various types of advanced light fields such as propagation-invariant beams and optical vortices. These may be useful for future fibre-based implementations of super-resolution or light-sheet microscopy.

  15. Multimodal recognition based on face and ear using local feature

    NASA Astrophysics Data System (ADS)

    Yang, Ruyin; Mu, Zhichun; Chen, Long; Fan, Tingyu

    2017-06-01

    The pose issue which may cause loss of useful information has always been a bottleneck in face and ear recognition. To address this problem, we propose a multimodal recognition approach based on face and ear using local feature, which is robust to large facial pose variations in the unconstrained scene. Deep learning method is used for facial pose estimation, and the method of a well-trained Faster R-CNN is used to detect and segment the region of face and ear. Then we propose a weighted region-based recognition method to deal with the local feature. The proposed method has achieved state-of-the-art recognition performance especially when the images are affected by pose variations and random occlusion in unconstrained scene.

  16. Validation of histology image registration

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  17. Feature quality-based multimodal unconstrained eye recognition

    NASA Astrophysics Data System (ADS)

    Zhou, Zhi; Du, Eliza Y.; Lin, Yong; Thomas, N. Luke; Belcher, Craig; Delp, Edward J.

    2013-05-01

    Iris recognition has been tested to the most accurate biometrics using high resolution near infrared images. However, it does not work well under visible wavelength illumination. Sclera recognition, however, has been shown to achieve reasonable recognition accuracy under visible wavelengths. Combining iris and sclera recognition together can achieve better recognition accuracy. However, image quality can significantly affect the recognition accuracy. Moreover, in unconstrained situations, the acquired eye images may not be frontally facing. In this research, we proposed a feature quality-based multimodal unconstrained eye recognition method that combine the respective strengths of iris recognition and sclera recognition for human identification and can work with frontal and off-angle eye images. The research results show that the proposed method is very promising.

  18. Optical mode switch based on multimode interference couplers

    NASA Astrophysics Data System (ADS)

    Xiao, Huifu; Deng, Lin; Zhao, Guolin; Liu, Zilong; Meng, Yinghao; Guo, Xiaonan; Liu, Guipeng; Liu, Su; Ding, Jianfeng; Tian, Yonghui

    2017-02-01

    In this paper, we propose an optical mode switch based on two cascaded multimode interference (MMI) couplers. After a fundamental mode divided into two equal-power fundamental modes in the first MMI coupler, the thermo-optic effect is employed to modulate the phase of the two fundamental modes before directed to the next MMI for the purpose of mode switching. By adjusting the electric signals applied to the modulation arms, the proposed device can implement mode switching in three states: (a) one first-order and two fundamental modes simultaneously output, (b) one first-order mode output, and (c) two fundamental modes output. As a result, the simulated excess losses are -0.29 dB, -0.10 dB, and -0.63 dB, respectively.

  19. Multimodal analgesia versus traditional opiate based analgesia after cardiac surgery, a randomized controlled trial

    PubMed Central

    2014-01-01

    Background To evaluate if an opiate sparing multimodal regimen of dexamethasone, gabapentin, ibuprofen and paracetamol had better analgesic effect, less side effects and was safe compared to a traditional morphine and paracetamol regimen after cardiac surgery. Methods Open-label, prospective randomized controlled trial. 180 patients undergoing cardiac procedures through median sternotomy, were included in the period march 2007- August 2009. 151 patients were available for analysis. Pain was assessed with the 11-numeric rating scale (11-NRS). Results Patients in the multimodal group demonstrated significantly lower average pain scores from the day of surgery throughout the third postoperative day. Extensive nausea and vomiting, was found in no patient in the multimodal group but in 13 patients in the morphine group, p < 0.001. Postoperative rise in individual creatinine levels demonstrated a non-significant rise in the multimodal group, 33.0±53.4 vs. 19.9±48.5, p = 0.133. Patients in the multimodal group suffered less major in-hospital events in crude numbers: myocardial infarction (MI) (1 vs. 2, p = 0.54), stroke (0 vs. 3, p = 0.075), dialysis (1 vs. 2, p = 0.54), and gastrointestinal (GI) bleeding (0 vs. 1, p = 0.31). 30-day mortality was 1 vs. 2, p = 0.54. Conclusions In patients undergoing cardiac surgery, a multimodal regimen offered significantly better analgesia than a traditional opiate regimen. Nausea and vomiting complaints were significantly reduced. No safety issues were observed with the multimodal regimen. Trial registration Clinicaltrials.gov identifier: NCT01966172 PMID:24650125

  20. Co-Registration of Bioluminescence Tomography, Computed Tomography, and Magnetic Resonance Imaging for Multimodal In Vivo Stem Cell Tracking

    PubMed Central

    Chehade, Moussa; Srivastava, Amit K.; Bulte, Jeff W.M.

    2016-01-01

    We present a practical approach for co-registration of bioluminescence tomography (BLT), computed tomography (CT), and magnetic resonance (MR) images. To this end, we developed a customized animal shuttle composed of non-fluorescent, MR-compatible Delrin plastic that fits a commercially available MR surface coil. Mouse embryonic stem cells (mESCs) were transfected with the luciferase gene and labeled with superparamagnetic iron oxide (SPIO) nanoparticles. Cells were stereotaxically implanted in mouse brain and imaged weekly for 4 weeks with BLI (IVIS Spectrum CT scanner) and MRI (11.7T horizontal bore scanner). Without the use of software co-registration, in vitro phantom studies yielded root-mean-square errors (RMSE) of 7.6×10−3, 0.93 mm, and 0.78 mm along the medial-lateral (ML), dorsal-ventral (DV), and anterior-posterior (AP) axes, respectively. Rotation errors were negligible. Software co-registration by translation along the DV and AP axes resulted in consistent agreement between the CT and MR images, without the need for rotation or warping. In vivo co-registered BLT/MRI mouse brain data sets demonstrated a single, diffuse region of BLI photon signal and MRI hypointensity. Over time, the transplanted cells formed tumors as validated by histopathology. Disagreement between BLT and MRI tumor location was greatest along the DV axis (1.4±0.2 mm) compared to the ML (0.5±0.3 mm) and AP axis (0.6 mm) due to the uncertainty of the depth of origin of the BLT signal. Combining the high spatial anatomical information of MRI with the cell viability/proliferation data from BLT should facilitate pre-clinical evaluation of novel therapeutic candidate stem cells. PMID:27478872

  1. An integrated GIS-based data model for multimodal urban public transportation analysis and management

    NASA Astrophysics Data System (ADS)

    Chen, Shaopei; Tan, Jianjun; Ray, C.; Claramunt, C.; Sun, Qinqin

    2008-10-01

    Diversity is one of the main characteristics of transportation data collected from multiple sources or formats, which can be extremely complex and disparate. Moreover, these multimodal transportation data are usually characterised by spatial and temporal properties. Multimodal transportation network data modelling involves both an engineering and research domain that has attracted the design of a number of spatio-temporal data models in the geographic information system (GIS). However, the application of these specific models to multimodal transportation network is still a challenging task. This research addresses this challenge from both integrated multimodal data organization and object-oriented modelling perspectives, that is, how a complex urban transportation network should be organized, represented and modeled appropriately when considering a multimodal point of view, and using object-oriented modelling method. We proposed an integrated GIS-based data model for multimodal urban transportation network that lays a foundation to enhance the multimodal transportation network analysis and management. This modelling method organizes and integrates multimodal transit network data, and supports multiple representations for spatio-temporal objects and relationship as both visual and graphic views. The data model is expressed by using a spatio-temporal object-oriented modelling method, i.e., the unified modelling language (UML) extended to spatial and temporal plug-in for visual languages (PVLs), which provides an essential support to the spatio-temporal data modelling for transportation GIS.

  2. Quantitative evaluation of registration methods for atlas-based diffuse optical tomography

    NASA Astrophysics Data System (ADS)

    Wu, Xue; Eggebrecht, Adam T.; Culver, Joseph P.; Zhan, Yuxuan; Basevi, Hector; Dehghani, Hamid

    2013-06-01

    In Diffuse Optical Tomography (DOT), an atlas-based model can be used as an alternative to a subject-specific anatomical model for recovery of brain activity. The main step of the generation of atlas-based subject model is the registration of atlas model to the subject head. The accuracy of the DOT then relies on the accuracy of registration method. In this work, 11 registration methods are quantitatively evaluated. The registration method with EEG 10/20 systems with 19 landmarks and non-iterative point to point algorithm provides approximately 1.4 mm surface error and is considered as the most efficient registration method.

  3. [A method for the medical image registration based on the statistics samples averaging distribution theory].

    PubMed

    Xu, Peng; Yao, Dezhong; Luo, Fen

    2005-08-01

    The registration method based on mutual information is currently a popular technique for the medical image registration, but the computation for the mutual information is complex and the registration speed is slow. In engineering process, a subsampling technique is taken to accelerate the registration speed at the cost of registration accuracy. In this paper a new method based on statistics sample theory is developed, which has both a higher speed and a higher accuracy as compared with the normal subsampling method, and the simulation results confirm the validity of the new method.

  4. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... Database within 60 days of notice from the Managing Director that the TRS User Registration Database is... the TRS User Registration Database shows a properly executed certification has not been filed. (vii... from the TRS Fund. (4) TRS User Registration Database information. Each VRS provider shall collect...

  5. Projection-slice theorem based 2D-3D registration

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

    In X-ray guided procedures, the surgeon or interventionalist is dependent on his or her knowledge of the patient's specific anatomy and the projection images acquired during the procedure by a rotational X-ray source. Unfortunately, these X-ray projections fail to give information on the patient's anatomy in the dimension along the projection axis. It would be very profitable to provide the surgeon or interventionalist with a 3D insight of the patient's anatomy that is directly linked to the X-ray images acquired during the procedure. In this paper we present a new robust 2D-3D registration method based on the Projection-Slice Theorem. This theorem gives us a relation between the pre-operative 3D data set and the interventional projection images. Registration is performed by minimizing a translation invariant similarity measure that is applied to the Fourier transforms of the images. The method was tested by performing multiple exhaustive searches on phantom data of the Circle of Willis and on a post-mortem human skull. Validation was performed visually by comparing the test projections to the ones that corresponded to the minimal value of the similarity measure. The Projection-Slice Theorem Based method was shown to be very effective and robust, and provides capture ranges up to 62 degrees. Experiments have shown that the method is capable of retrieving similar results when translations are applied to the projection images.

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

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  7. Automated registration of intraoperative CT image data for navigated skull base surgery.

    PubMed

    Eggers, G; Kress, B; Mühling, J

    2008-02-01

    With a new intraoperative computed tomography (CT) imaging system, patient-to-image registration without any invasive registration markers is possible. Furthermore, registration can be performed fully automatically. The accuracy of this method for skull base surgery was investigated in this study. We employed a phantom study design. A phantom skull was equipped with 33 target markers in the regions of the anterior and lateral skull base. CT image data were acquired with an intraoperative CT suite. Image data were transferred as DICOM data to the navigation system, and registration was performed automatically. For registration, the position of the patient and the position of the CT gantry were monitored in the imaging process, using the infrared camera of a navigation system. Using the pointing device of the navigation system, the target markers were identified. The accuracy was measured as the spatial difference of the target markers in image space and on the phantom. Accuracy was always sufficient for image-guided surgery of any region of the skull base, with an average target registration error of below 1.2 mm. In contrast to traditional non-invasive registration methods, there was no difference in registration accuracy between the anterior skull base and the lateral skull base. Fully automated registration based on a tracked CT gantry is a robust and accurate registration method for skull base surgery.

  8. Co-registration of multi-modality imaging allows for comprehensive analysis of tumor-induced bone disease

    PubMed Central

    Seeley, Erin H.; Wilson, Kevin J.; Yankeelov, Thomas E.; Johnson, Rachelle W.; Gore, John C.; Caprioli, Richard M.; Matrisian, Lynn M.; Sterling, Julie A.

    2014-01-01

    Bone metastases are a clinically significant problem that arises in approximately 70% of metastatic breast cancer patients. Once established in bone, tumor cells induce changes in the bone microenvironment that lead to bone destruction, pain, and significant morbidity. While much is known about the later stages of bone disease, less is known about the earlier stages or the changes in protein expression in the tumor micro-environment. Due to promising results of combining magnetic resonance imaging (MRI) and Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry (MALDI IMS) ion images in the brain, we developed methods for applying these modalities to models of tumor-induced bone disease in order to better understand the changes in protein expression that occur within the tumor-bone microenvironment. Specifically, we integrated three dimensional-volume reconstructions of spatially resolved MALDI IMS with high-resolution anatomical and diffusion weighted MRI data and histology in an intratibial model of breast tumor-induced bone disease. This approach enables us to analyze proteomic profiles from MALDI IMS data with corresponding in vivo imaging and ex vivo histology data. To the best of our knowledge, this is the first time these three modalities have been rigorously registered in the bone. The MALDI mass-to-charge ratio peaks indicate differential expression of calcyclin, ubiquitin, and other proteins within the tumor cells, while peaks corresponding to hemoglobin A and calgranulin A provided molecular information that aided in the identification of areas rich in red and white blood cells, respectively. This multimodality approach will allow us to comprehensively understand the bone-tumor microenvironment and thus may allow us to better develop and test approaches for inhibiting bone metastases. PMID:24487126

  9. Silicon CMOS-based vertical multimode interference optical taps

    NASA Astrophysics Data System (ADS)

    Stenger, Vincent E.; Beyette, Fred R., Jr.

    2001-12-01

    A compact, low loss, optical tap technology is critical for the incorporation of optical interconnects into mainstream CMOS processes. A recently introduced multimode interference effect based device has the potential for very high speed performance in a compact geometry and in a CMOS compatible process. For this work, 2-D and 3-D device simulations confirm a low excess optical loss on order of 0.1 dB, and a nominal 40% (2.2 dB) optical coupling into the CMOS circuitry over a wide range of guide to substrate distances. Simulated devices are on the order of 25micrometers in length and as narrow as 1 um. High temperature, hybrid polymer materials used for commercial CMOS inter-metal dielectric layers are targeted for tap fabrication and are incorporated into the models. Low cost, silicon CMOS based processing makes the new tap technology especially suitable for computer multi-chip module and board level interconnects, as well as for metro fiber to the home and desk telecommunications applications.

  10. A three-dimensional head-and-neck phantom for validation of multimodality deformable image registration for adaptive radiotherapy

    SciTech Connect

    Singhrao, Kamal; Kirby, Neil; Pouliot, Jean

    2014-12-15

    Purpose: To develop a three-dimensional (3D) deformable head-and-neck (H and N) phantom with realistic tissue contrast for both kilovoltage (kV) and megavoltage (MV) imaging modalities and use it to objectively evaluate deformable image registration (DIR) algorithms. Methods: The phantom represents H and N patient anatomy. It is constructed from thermoplastic, which becomes pliable in boiling water, and hardened epoxy resin. Using a system of additives, the Hounsfield unit (HU) values of these materials were tuned to mimic anatomy for both kV and MV imaging. The phantom opens along a sagittal midsection to reveal radiotransparent markers, which were used to characterize the phantom deformation. The deformed and undeformed phantoms were scanned with kV and MV imaging modalities. Additionally, a calibration curve was created to change the HUs of the MV scans to be similar to kV HUs, (MC). The extracted ground-truth deformation was then compared to the results of two commercially available DIR algorithms, from Velocity Medical Solutions and MIM software. Results: The phantom produced a 3D deformation, representing neck flexion, with a magnitude of up to 8 mm and was able to represent tissue HUs for both kV and MV imaging modalities. The two tested deformation algorithms yielded vastly different results. For kV–kV registration, MIM produced mean and maximum errors of 1.8 and 11.5 mm, respectively. These same numbers for Velocity were 2.4 and 7.1 mm, respectively. For MV–MV, kV–MV, and kV–MC Velocity produced similar mean and maximum error values. MIM, however, produced gross errors for all three of these scenarios, with maximum errors ranging from 33.4 to 41.6 mm. Conclusions: The application of DIR across different imaging modalities is particularly difficult, due to differences in tissue HUs and the presence of imaging artifacts. For this reason, DIR algorithms must be validated specifically for this purpose. The developed H and N phantom is an effective tool

  11. A three-dimensional head-and-neck phantom for validation of multimodality deformable image registration for adaptive radiotherapy.

    PubMed

    Singhrao, Kamal; Kirby, Neil; Pouliot, Jean

    2014-12-01

    To develop a three-dimensional (3D) deformable head-and-neck (H&N) phantom with realistic tissue contrast for both kilovoltage (kV) and megavoltage (MV) imaging modalities and use it to objectively evaluate deformable image registration (DIR) algorithms. The phantom represents H&N patient anatomy. It is constructed from thermoplastic, which becomes pliable in boiling water, and hardened epoxy resin. Using a system of additives, the Hounsfield unit (HU) values of these materials were tuned to mimic anatomy for both kV and MV imaging. The phantom opens along a sagittal midsection to reveal radiotransparent markers, which were used to characterize the phantom deformation. The deformed and undeformed phantoms were scanned with kV and MV imaging modalities. Additionally, a calibration curve was created to change the HUs of the MV scans to be similar to kV HUs, (MC). The extracted ground-truth deformation was then compared to the results of two commercially available DIR algorithms, from Velocity Medical Solutions and mim software. The phantom produced a 3D deformation, representing neck flexion, with a magnitude of up to 8 mm and was able to represent tissue HUs for both kV and MV imaging modalities. The two tested deformation algorithms yielded vastly different results. For kV-kV registration, mim produced mean and maximum errors of 1.8 and 11.5 mm, respectively. These same numbers for Velocity were 2.4 and 7.1 mm, respectively. For MV-MV, kV-MV, and kV-MC Velocity produced similar mean and maximum error values. mim, however, produced gross errors for all three of these scenarios, with maximum errors ranging from 33.4 to 41.6 mm. The application of DIR across different imaging modalities is particularly difficult, due to differences in tissue HUs and the presence of imaging artifacts. For this reason, DIR algorithms must be validated specifically for this purpose. The developed H&N phantom is an effective tool for this purpose.

  12. Multimode-oriented polynomial transformation-based defuzzification strategy and parameter learning procedure.

    PubMed

    Jiang, T; Li, Y

    1997-01-01

    In an earlier paper (1996), we proposed a set of generalized defuzzification strategies which can be characterized as single-mode-oriented strategies. A single-mode-oriented defuzzification strategy, although useful in many research projects and real world applications, cannot be applied to a multimode situation where two or more distinct possibility peaks exist in its membership function distribution. In this paper, for multimode-oriented generalized defuzzification applications, a multimode-oriented polynomial transformation based defuzzification strategy (M-PTD) is introduced. The new M-PTD strategy, which uses the Kalman filter in parameter learning procedure, offers a constraint-free and self-renewal defuzzification solution.

  13. The Intersection of Multimodality and Critical Perspective: Multimodality as Subversion

    ERIC Educational Resources Information Center

    Huang, Shin-ying

    2015-01-01

    This study explores the relevance of multimodality to critical media literacy. It is based on the understanding that communication is intrinsically multimodal and multimodal communication is inherently social and ideological. By analysing two English-language learners' multimodal ensembles, the study reports on how multimodality contributes to a…

  14. The Intersection of Multimodality and Critical Perspective: Multimodality as Subversion

    ERIC Educational Resources Information Center

    Huang, Shin-ying

    2015-01-01

    This study explores the relevance of multimodality to critical media literacy. It is based on the understanding that communication is intrinsically multimodal and multimodal communication is inherently social and ideological. By analysing two English-language learners' multimodal ensembles, the study reports on how multimodality contributes to a…

  15. Optimization Model for Web Based Multimodal Interactive Simulations.

    PubMed

    Halic, Tansel; Ahn, Woojin; De, Suvranu

    2015-07-15

    This paper presents a technique for optimizing the performance of web based multimodal interactive simulations. For such applications where visual quality and the performance of simulations directly influence user experience, overloading of hardware resources may result in unsatisfactory reduction in the quality of the simulation and user satisfaction. However, optimization of simulation performance on individual hardware platforms is not practical. Hence, we present a mixed integer programming model to optimize the performance of graphical rendering and simulation performance while satisfying application specific constraints. Our approach includes three distinct phases: identification, optimization and update. In the identification phase, the computing and rendering capabilities of the client device are evaluated using an exploratory proxy code. This data is utilized in conjunction with user specified design requirements in the optimization phase to ensure best possible computational resource allocation. The optimum solution is used for rendering (e.g. texture size, canvas resolution) and simulation parameters (e.g. simulation domain) in the update phase. Test results are presented on multiple hardware platforms with diverse computing and graphics capabilities to demonstrate the effectiveness of our approach.

  16. Multimodal computational microscopy based on transport of intensity equation

    NASA Astrophysics Data System (ADS)

    Li, Jiaji; Chen, Qian; Sun, Jiasong; Zhang, Jialin; Zuo, Chao

    2016-12-01

    Transport of intensity equation (TIE) is a powerful tool for phase retrieval and quantitative phase imaging, which requires intensity measurements only at axially closely spaced planes without a separate reference beam. It does not require coherent illumination and works well on conventional bright-field microscopes. The quantitative phase reconstructed by TIE gives valuable information that has been encoded in the complex wave field by passage through a sample of interest. Such information may provide tremendous flexibility to emulate various microscopy modalities computationally without requiring specialized hardware components. We develop a requisite theory to describe such a hybrid computational multimodal imaging system, which yields quantitative phase, Zernike phase contrast, differential interference contrast, and light field moment imaging, simultaneously. It makes the various observations for biomedical samples easy. Then we give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens-based TIE system, combined with the appropriate postprocessing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

  17. The neurocognitive bases of human multimodal food perception: consciousness

    PubMed Central

    Verhagen, Justus V.

    2007-01-01

    This review explores how we become aware of the (integrated) flavor of food. In recent years progress has been made understanding the neural correlates of consciousness. Experimental and computational data has been largely based on the visual system. Contemporary neurobiological frameworks of consciousness are reviewed, concluding that neural reverberation among forward- and back-projecting neural ensembles across brain areas is a common theme. In an attempt to extrapolate these concepts to the oral-sensory and olfactory systems involved with multimodal flavor perception, the integration of the sensory information of which into a flavor gestalt has been reviewed elsewhere (Verhagen and Engelen 2006), I reconceptualize the flavor-sensory system by integrating it into a larger neural system termed the Homeostatic Interoceptive System (HIS). This system consists of an oral (taste, oral touch, etc.) and non-oral part (non oral-thermosensation, pain, etc) which are anatomically and functionaly highly similar. Consistent with this new concept and with a large volume of experimental data, I propose that awareness of intraoral food is related to the concomitant reverberant self-sustained activation of a coalition of neuronal subsets in agranular insula and orbitorfrontal cortex (affect, hedonics) and agranular insula and perirhinal cortex (food identity), as well as the amygdala (affect and identity) in humans. I further discuss the functional anatomy in relation essential nodes. These formulations are by necessity to some extent speculative. PMID:17027988

  18. Optimization Model for Web Based Multimodal Interactive Simulations

    PubMed Central

    Halic, Tansel; Ahn, Woojin; De, Suvranu

    2015-01-01

    This paper presents a technique for optimizing the performance of web based multimodal interactive simulations. For such applications where visual quality and the performance of simulations directly influence user experience, overloading of hardware resources may result in unsatisfactory reduction in the quality of the simulation and user satisfaction. However, optimization of simulation performance on individual hardware platforms is not practical. Hence, we present a mixed integer programming model to optimize the performance of graphical rendering and simulation performance while satisfying application specific constraints. Our approach includes three distinct phases: identification, optimization and update. In the identification phase, the computing and rendering capabilities of the client device are evaluated using an exploratory proxy code. This data is utilized in conjunction with user specified design requirements in the optimization phase to ensure best possible computational resource allocation. The optimum solution is used for rendering (e.g. texture size, canvas resolution) and simulation parameters (e.g. simulation domain) in the update phase. Test results are presented on multiple hardware platforms with diverse computing and graphics capabilities to demonstrate the effectiveness of our approach. PMID:26085713

  19. Rolled fingerprint construction using MRF-based nonrigid image registration.

    PubMed

    Kwon, Dongjin; Yun, Il Dong; Lee, Sang Uk

    2010-12-01

    This paper proposes a new rolled fingerprint construction approach incorporating a state-of-the-art nonrigid image registration method based upon a Markov random field (MRF) energy model. The proposed method finds dense correspondences between images from a rolled fingerprint sequence and warps the entire fingerprint area to synthesize a rolled fingerprint. This method can generate conceptually more accurate rolled fingerprints by preserving the geometric properties of the finger surface as opposed to ink-based rolled impressions and other existing rolled fingerprint construction methods. To verify the accuracy of the proposed method, various comparative experiments were designed to reveal differences among the rolled construction methods. The results show that the proposed method is significantly superior in various aspects compared to previous approaches.

  20. Segmentation-Based Registration of Organs in Intraoperative Video Sequences

    SciTech Connect

    Goddard Jr, James Samuel; Gee, Timothy Felix; Wang, Hengliang; Gorbach, Alexander M

    2006-01-01

    Intraoperative optical imaging of exposed organs in visible, near-infrared, and infrared (IR) wavelengths in the body has the potential to be use-ful for real-time assessment of organ viability and image guidance during surgical intervention. However, the motion of the internal organs presents significant challenges for fast analysis of recorded 2D video sequences. The movement observed during surgery, due to respiration, cardiac motion, blood flow, and mechanical shift accompanying the surgical intervention, causes organ reflection in the image sequence, making optical measurements for further analysis challenging. Correcting alignment is difficult in that the motion is not uniform over the image. This paper describes a Canny edge-based method for segmentation of the specific organ or region under study, along with a moment-based registration method for the segmented region. Experimental results are provided for a set of intraoperative IR image sequences.

  1. Multi-modal Learning-based Pre-operative Targeting in Deep Brain Stimulation Procedures.

    PubMed

    Liu, Yuan; Dawant, Benoit M

    2016-02-01

    Deep brain stimulation, as a primary surgical treatment for various neurological disorders, involves implanting electrodes to stimulate target nuclei within millimeter accuracy. Accurate pre-operative target selection is challenging due to the poor contrast in its surrounding region in MR images. In this paper, we present a learning-based method to automatically and rapidly localize the target using multi-modal images. A learning-based technique is applied first to spatially normalize the images in a common coordinate space. Given a point in this space, we extract a heterogeneous set of features that capture spatial and intensity contextual patterns at different scales in each image modality. Regression forests are used to learn a displacement vector of this point to the target. The target is predicted as a weighted aggregation of votes from various test samples, leading to a robust and accurate solution. We conduct five-fold cross validation using 100 subjects and compare our method to three indirect targeting methods, a state-of-the-art statistical atlas-based approach, and two variations of our method that use only a single modality image. With an overall error of 2.63±1.37mm, our method improves upon the single modality-based variations and statistically significantly outperforms the indirect targeting ones. Our technique matches state-of-the-art registration methods but operates on completely different principles. Both techniques can be used in tandem in processing pipelines operating on large databases or in the clinical flow for automated error detection.

  2. Motion compensation by registration-based catheter tracking

    NASA Astrophysics Data System (ADS)

    Brost, Alexander; Wimmer, Andreas; Liao, Rui; Hornegger, Joachim; Strobel, Norbert

    2011-03-01

    The treatment of atrial fibrillation has gained increasing importance in the field of computer-aided interventions. State-of-the-art treatment involves the electrical isolation of the pulmonary veins attached to the left atrium under fluoroscopic X-ray image guidance. Due to the rather low soft-tissue contrast of X-ray fluoroscopy, the heart is difficult to see. To overcome this problem, overlay images from pre-operative 3-D volumetric data can be used to add anatomical detail. Unfortunately, these overlay images are static at the moment, i.e., they do not move with respiratory and cardiac motion. The lack of motion compensation may impair X-ray based catheter navigation, because the physician could potentially position catheters incorrectly. To improve overlay-based catheter navigation, we present a novel two stage approach for respiratory and cardiac motion compensation. First, a cascade of boosted classifiers is employed to segment a commonly used circumferential mapping catheter which is firmly fixed at the ostium of the pulmonary vein during ablation. Then, a 2-D/2-D model-based registration is applied to track the segmented mapping catheter. Our novel hybrid approach was evaluated on 10 clinical data sets consisting of 498 fluoroscopic monoplane frames. We obtained an average 2-D tracking error of 0.61 mm, with a minimum error of 0.26 mm and a maximum error of 1.62 mm. These results demonstrate that motion compensation using registration-based catheter tracking is both feasible and accurate. Using this approach, we can only estimate in-plane motion. Fortunately, compensating for this is often sufficient for EP procedures where the motion is governed by breathing.

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

    PubMed Central

    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

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

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

  5. Multimode fiber focusing lens based on plasmonic structures

    NASA Astrophysics Data System (ADS)

    Xu, Yihang; Lu, Yongjiao; Zhu, Zheng; Shi, Jinhui; Guan, Chunying; Yuan, Libo

    2016-10-01

    In the present work, a compact all-fiber plasmonic focusing beam generator with single and multiple spots is proposed and demonstrated in a conventional multimode fiber. Here, the focusing beam generator is composed of air slit arrays perforated through the gold films deposited on the end facet of a multimode fiber. The array of nanoscale slits with varying widths is used to modulate phase distribution of the focused light. An all-fiber focusing beam generator provides many advantages, such as self-alignment, high flexibility, lower insert loss, and easy portability, which is of importance to realize optical trapping, micromanipulation, beam shaping, and fiber integrated devices.

  6. Multiscale Combination of Physically-Based Registration and Deformation Modeling

    SciTech Connect

    Tsap, L.; Goldgof, D.B.; Sarkar, S.

    1999-11-08

    In this paper the authors present a novel multiscale approach to recovery of nonrigid motion from sequences of registered intensity and range images. The main idea of the approach is that a finite element (FEM) model can naturally handle both registration and deformation modeling using a single model-driving strategy. The method includes a multiscale iterative algorithm based on analysis of the undirected Hausdorff distance to recover correspondences. The method is evaluated with respect to speed, accuracy, and noise sensitivity. Advantages of the proposed approach are demonstrated using man-made elastic materials and human skin motion. Experiments with regular grid features are used for performance comparison with a conventional approach (separate snakes and FEM models). It is shown that the new method does not require a grid and can adapt the model to available object features.

  7. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...) Default provider registration. Every provider of VRS or IP Relay must, no later than December 31, 2008, provide users with the capability to register with that VRS or IP Relay provider as a “default provider.” Upon a user's registration, the VRS or IP Relay provider shall: (1) Either: (i) Facilitate the user's...

  8. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...) Default provider registration. Every provider of VRS or IP Relay must, no later than December 31, 2008, provide users with the capability to register with that VRS or IP Relay provider as a “default provider.” Upon a user's registration, the VRS or IP Relay provider shall: (1) Either: (i) Facilitate the user's...

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

    ERIC Educational Resources Information Center

    Freeman, Raoul J.

    1983-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

  11. Navigation accuracy after automatic- and hybrid-surface registration in sinus and skull base surgery.

    PubMed

    Grauvogel, Tanja Daniela; Engelskirchen, Paul; Semper-Hogg, Wiebke; Grauvogel, Juergen; Laszig, Roland

    2017-01-01

    Computer-aided-surgery in ENT surgery is mainly used for sinus surgery but navigation accuracy still reaches its limits for skull base procedures. Knowledge of navigation accuracy in distinct anatomical regions is therefore mandatory. This study examined whether navigation accuracy can be improved in specific anatomical localizations by using hybrid registration technique. Experimental phantom study. Operating room. The gold standard of screw registration was compared with automatic LED-mask-registration alone, and in combination with additional surface matching. 3D-printer-based skull models with individual fabricated silicone skin were used for the experiments. Overall navigation accuracy considering 26 target fiducials distributed over each skull was measured as well as the accuracy on selected anatomic localizations. Overall navigation accuracy was <1.0 mm in all cases, showing the significantly lowest values after screw registration (0.66 ± 0.08 mm), followed by hybrid registration (0.83± 0.08 mm), and sole mask registration (0.92 ± 0.13 mm).On selected anatomic localizations screw registration was significantly superior on the sphenoid sinus and on the internal auditory canal. However, mask registration showed significantly better accuracy results on the midface. Navigation accuracy on skull base localizations could be significantly improved by the combination of mask registration and additional surface matching. Overall navigation accuracy gives no sufficient information regarding navigation accuracy in a distinct anatomic area. The non-invasive LED-mask-registration proved to be an alternative in clinical routine showing best accuracy results on the midface. For challenging skull base procedures a hybrid registration technique is recommendable which improves navigation accuracy significantly in this operating field. Invasive registration procedures are reserved for selected challenging skull base operations where the required high precision warrants the

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

    NASA Astrophysics Data System (ADS)

    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.

  13. Multi-modality sparse representation-based classification for Alzheimer's disease and mild cognitive impairment.

    PubMed

    Xu, Lele; Wu, Xia; Chen, Kewei; Yao, Li

    2015-11-01

    The discrimination of Alzheimer's disease (AD) and its prodromal stage known as mild cognitive impairment (MCI) from normal control (NC) is important for patients' timely treatment. The simultaneous use of multi-modality data has been demonstrated to be helpful for more accurate identification. The current study focused on extending a multi-modality algorithm and evaluating the method by identifying AD/MCI. In this study, sparse representation-based classification (SRC), a well-developed method in pattern recognition and machine learning, was extended to a multi-modality classification framework named as weighted multi-modality SRC (wmSRC). Data including three modalities of volumetric magnetic resonance imaging (MRI), fluorodeoxyglucose (FDG) positron emission tomography (PET) and florbetapir PET from the Alzheimer's disease Neuroimaging Initiative database were adopted for AD/MCI classification (113 AD patients, 110 MCI patients and 117 NC subjects). Adopting wmSRC, the classification accuracy achieved 94.8% for AD vs. NC, 74.5% for MCI vs. NC, and 77.8% for progressive MCI vs. stable MCI, superior to or comparable with the results of some other state-of-the-art models in recent multi-modality researches. The wmSRC method is a promising tool for classification with multi-modality data. It could be effective for identifying diseases from NC with neuroimaging data, which could be helpful for the timely diagnosis and treatment of diseases. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  14. Elastic registration based on particle filter in radiotherapy images with brain deformations.

    PubMed

    Mejia-Rodriguez, A R; Arce-Santana, E R; Scalco, E; Tresoldi, D; Mendez, M O; Bianchi, A M; Cattaneo, G M; Rizzo, G

    2011-01-01

    This paper presents the evaluation of the accuracy of an elastic registration algorithm, based on the particle filter and an optical flow process. The algorithm is applied in brain CT and MRI simulated image datasets, and MRI images from a real clinical radiotherapy case. To validate registration accuracy, standard indices for registration accuracy assessment were calculated: the dice similarity coefficient (DICE), the average symmetric distance (ASD) and the maximal distance between pixels (Dmax). The results showed that this registration process has good accuracy, both qualitatively and quantitatively, suggesting that this method may be considered as a good new option for radiotherapy applications like patient's follow up treatment.

  15. Automatic parameter selection for feature-based multi-sensor image registration

    NASA Astrophysics Data System (ADS)

    DelMarco, Stephen; Tom, Victor; Webb, Helen; Chao, Alan

    2006-05-01

    Accurate image registration is critical for applications such as precision targeting, geo-location, change-detection, surveillance, and remote sensing. However, the increasing volume of image data is exceeding the current capacity of human analysts to perform manual registration. This image data glut necessitates the development of automated approaches to image registration, including algorithm parameter value selection. Proper parameter value selection is crucial to the success of registration techniques. The appropriate algorithm parameters can be highly scene and sensor dependent. Therefore, robust algorithm parameter value selection approaches are a critical component of an end-to-end image registration algorithm. In previous work, we developed a general framework for multisensor image registration which includes feature-based registration approaches. In this work we examine the problem of automated parameter selection. We apply the automated parameter selection approach of Yitzhaky and Peli to select parameters for feature-based registration of multisensor image data. The approach consists of generating multiple feature-detected images by sweeping over parameter combinations and using these images to generate estimated ground truth. The feature-detected images are compared to the estimated ground truth images to generate ROC points associated with each parameter combination. We develop a strategy for selecting the optimal parameter set by choosing the parameter combination corresponding to the optimal ROC point. We present numerical results showing the effectiveness of the approach using registration of collected SAR data to reference EO data.

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

    PubMed

    Du, Xiaogang; Dang, Jianwu; Wang, Yangping; Wang, Song; Lei, Tao

    2016-01-01

    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).

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

    PubMed Central

    Wang, Yangping; Wang, Song

    2016-01-01

    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). PMID:28053653

  18. Palmprint and Face Multi-Modal Biometric Recognition Based on SDA-GSVD and Its Kernelization

    PubMed Central

    Jing, Xiao-Yuan; Li, Sheng; Li, Wen-Qian; Yao, Yong-Fang; Lan, Chao; Lu, Jia-Sen; Yang, Jing-Yu

    2012-01-01

    When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person's overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person's different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance. PMID:22778600

  19. Neural Network-Based Multimode Fiber-Optic Information Transmission

    NASA Astrophysics Data System (ADS)

    Marusarz, Ronald K.; Sayeh, Mohammad R.

    2001-01-01

    A new technique for transmitting information through multimode fiber-optic cables is presented. This technique sends parallel channels through the fiber-optic cable, thereby greatly improving the data transmission rate compared with that of the current technology, which uses serial data transmission through single-mode fiber. An artificial neural network is employed to decipher the transmitted information from the received speckle pattern. Several different preprocessing algorithms are developed, tested, and evaluated. These algorithms employ average region intensity, distributed individual pixel intensity, and maximum mean-square-difference optimal group selection methods. The effect of modal dispersion on the data rate is analyzed. An increased data transmission rate by a factor of 37 over that of single-mode fibers is realized. When implementing our technique, we can increase the channel capacity of a typical multimode fiber by a factor of 6.

  20. Outcome of transarterial chemoembolization-based multi-modal treatment in patients with unresectable hepatocellular carcinoma.

    PubMed

    Song, Do Seon; Nam, Soon Woo; Bae, Si Hyun; Kim, Jin Dong; Jang, Jeong Won; Song, Myeong Jun; Lee, Sung Won; Kim, Hee Yeon; Lee, Young Joon; Chun, Ho Jong; You, Young Kyoung; Choi, Jong Young; Yoon, Seung Kew

    2015-02-28

    To investigate the efficacy and safety of transarterial chemoembolization (TACE)-based multimodal treatment in patients with large hepatocellular carcinoma (HCC). A total of 146 consecutive patients were included in the analysis, and their medical records and radiological data were reviewed retrospectively. In total, 119 patients received TACE-based multi-modal treatments, and the remaining 27 received conservative management. Overall survival (P<0.001) and objective tumor response (P=0.003) were significantly better in the treatment group than in the conservative group. After subgroup analysis, survival benefits were observed not only in the multi-modal treatment group compared with the TACE-only group (P=0.002) but also in the surgical treatment group compared with the loco-regional treatment-only group (P<0.001). Multivariate analysis identified tumor stage (P<0.001) and tumor type (P=0.009) as two independent pre-treatment factors for survival. After adjusting for significant pre-treatment prognostic factors, objective response (P<0.001), surgical treatment (P=0.009), and multi-modal treatment (P=0.002) were identified as independent post-treatment prognostic factors. TACE-based multi-modal treatments were safe and more beneficial than conservative management. Salvage surgery after successful downstaging resulted in long-term survival in patients with large, unresectable HCC.

  1. A line segment based registration method for Terrestrial Laser Scanning point cloud data

    NASA Astrophysics Data System (ADS)

    Cheng, Jun; Cheng, Ming; Lin, Yangbin; Wang, Cheng

    2016-03-01

    This paper proposed a 3d line segment based registration method for terrestrial laser scanning (TLS) data. The 3D line segment is adopted to describe the point cloud data and reduce geometric complexity. After that, we introduce a framework for registration. We demonstrate the accuracy of our method for rigid transformations in the presence of terrestrial laser scanning point cloud.

  2. Advancements in LiDAR-based registration of FIA field plots

    Treesearch

    Demetrios. Gatziolis

    2012-01-01

    Meaningful integration of National Forest Inventory field plot information with spectral imagery acquired from satellite or airborne platforms requires precise plot registration. Global positioning system-based plot registration procedures, such as the one employed by the Forest Inventory and Analysis (FIA) Program, yield plot coordinates that, although adequate for...

  3. SU-E-T-237: Deformable Image Registration and Deformed Dose Composite for Volumetric Evaluation of Multimodal Gynecological Cancer Treatments

    SciTech Connect

    Albani, D; Sherertz, T; Ellis, R; Podder, T; Cantley, J; Herrmann, K

    2015-06-15

    Purpose: Radiotherapy plans for patients with cervical cancer treated with EBRT followed by HDR brachytherapy are optimized by constraining dose to organs at risk (OARs). Risk of treatment related toxicities is estimated based on the dose received to the hottest 2cc (D2cc) of the bladder, bowel, rectum, and sigmoid. To account for intrafractional variation in OAR volume and positioning, a dose deformation method is proposed for more accurate evaluation of dose distribution for these patients. Methods: Radiotherapy plans from five patients who received 50.4Gy pelvic EBRT followed by 30Gy in five fractions of HDR brachytherapy, using split-ring and tandem applicators, were retrospectively evaluated using MIM Software version 6.0. Dose accumulation workflows were used for initial deformation of EBRT and HDR planning CTs onto a common HDR planning CT. The Reg Refine tool was applied with user-specified local alignments to refine the deformation. Doses from the deformed images were transferred to the common planning CT. Deformed doses were scaled to the EQD2, following the linear-quadratic BED model (considered α/β ratio for tumor as 10, and 3 for rest of the tissues), and then combined to create the dose composite. MIM composite doses were compared to the clinically-reported plan assessments based upon the American Brachytherapy Society (ABS) guidelines for cervical HDR brachytherapy treatment. Results: Bladder D2cc exhibited significant reduction (−11.4%±3.85%, p< 0.02) when evaluated using MIM deformable dose composition. Differences observed for bowel, rectum, and sigmoid D2cc were not significant (−0.58±7.37%, −4.13%±13.7%, and 8.58%±4.71%, respectively and p>0.05 for all) relative to the calculated values used clinically. Conclusion: Application of deformable dose composite techniques may lead to more accurate total dose reporting and can allow for elevated dose to target structures with the assurance of not exceeding dose to OARs. Further study into

  4. A CNN based Hybrid approach towards automatic image registration

    NASA Astrophysics Data System (ADS)

    Arun, Pattathal V.; Katiyar, Sunil K.

    2013-06-01

    Image registration is a key component of various image processing operations which involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however inability to properly model object shape as well as contextual information had limited the attainable accuracy. In this paper, we propose a framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as Vector Machines, Cellular Neural Network (CNN), SIFT, coreset, and Cellular Automata. CNN has found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using corset optimization The salient features of this work are cellular neural network approach based SIFT feature point optimisation, adaptive resampling and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. System has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. Methodology also illustrated to be effective in providing intelligent interpretation and adaptive resampling. Rejestracja obrazu jest kluczowym składnikiem różnych operacji jego przetwarzania. W ostatnich latach do automatycznej rejestracji obrazu wykorzystuje się metody sztucznej inteligencji, których największą wadą, obniżającą dokładność uzyskanych wyników jest brak możliwości dobrego wymodelowania kształtu i informacji kontekstowych. W niniejszej pracy zaproponowano zasady dokładnego modelowania kształtu oraz adaptacyjnego resamplingu z wykorzystaniem zaawansowanych technik, takich jak Vector Machines (VM), komórkowa sieć neuronowa (CNN), przesiewanie (SIFT), Coreset i

  5. Partially overlapped range images registration based on Fringe pattern profilometry

    NASA Astrophysics Data System (ADS)

    He, Xiaochen; Xi, Jiangtao; Yu, Yanguang

    2011-11-01

    Registration of two three-dimensional (3-D) point sets is a fundamental problem of 3-D shape measurement and modeling pipeline. This paper investigates the automatic pair-wise method to register partially overlapped range images generated by self-developed fringe pattern profilometry (FPP) system. The method is based on the classic iterative closest point (ICP) algorithm but combined with several extensions to adapt to the experimental data. Firstly, the distance function for correspondence finding is modified to be the weighted linear combination of positions and Euclidean invariant features for improving the probability of convergence. In addition, outliers can be discarded through robust statistics and adaptive thresholding of weighted distances between corresponding point pairs. Both artificial and real data are used to test the proposed method. In the ideal noise-free conditions, the experimental results illustrate that it converges to the global minima. The experimental results also show that the proposed method increases the possibility of global convergence when deal with partially overlapped range images.

  6. Digital image registration method based upon binary boundary maps

    NASA Technical Reports Server (NTRS)

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

    1974-01-01

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

  7. A vascular image registration method based on network structure and circuit simulation.

    PubMed

    Chen, Li; Lian, Yuxi; Guo, Yi; Wang, Yuanyuan; Hatsukami, Thomas S; Pimentel, Kristi; Balu, Niranjan; Yuan, Chun

    2017-05-02

    Image registration is an important research topic in the field of image processing. Applying image registration to vascular image allows multiple images to be strengthened and fused, which has practical value in disease detection, clinical assisted therapy, etc. However, it is hard to register vascular structures with high noise and large difference in an efficient and effective method. Different from common image registration methods based on area or features, which were sensitive to distortion and uncertainty in vascular structure, we proposed a novel registration method based on network structure and circuit simulation. Vessel images were transformed to graph networks and segmented to branches to reduce the calculation complexity. Weighted graph networks were then converted to circuits, in which node voltages of the circuit reflecting the vessel structures were used for node registration. The experiments in the two-dimensional and three-dimensional simulation and clinical image sets showed the success of our proposed method in registration. The proposed vascular image registration method based on network structure and circuit simulation is stable, fault tolerant and efficient, which is a useful complement to the current mainstream image registration methods.

  8. Fast time-of-flight camera based surface registration for radiotherapy patient positioning

    SciTech Connect

    Placht, Simon; Stancanello, Joseph; Schaller, Christian; Balda, Michael; Angelopoulou, Elli

    2012-01-15

    Purpose: This work introduces a rigid registration framework for patient positioning in radiotherapy, based on real-time surface acquisition by a time-of-flight (ToF) camera. Dynamic properties of the system are also investigated for future gating/tracking strategies. Methods: A novel preregistration algorithm, based on translation and rotation-invariant features representing surface structures, was developed. Using these features, corresponding three-dimensional points were computed in order to determine initial registration parameters. These parameters became a robust input to an accelerated version of the iterative closest point (ICP) algorithm for the fine-tuning of the registration result. Distance calibration and Kalman filtering were used to compensate for ToF-camera dependent noise. Additionally, the advantage of using the feature based preregistration over an ''ICP only'' strategy was evaluated, as well as the robustness of the rigid-transformation-based method to deformation. Results: The proposed surface registration method was validated using phantom data. A mean target registration error (TRE) for translations and rotations of 1.62 {+-} 1.08 mm and 0.07 deg. {+-} 0.05 deg., respectively, was achieved. There was a temporal delay of about 65 ms in the registration output, which can be seen as negligible considering the dynamics of biological systems. Feature based preregistration allowed for accurate and robust registrations even at very large initial displacements. Deformations affected the accuracy of the results, necessitating particular care in cases of deformed surfaces. Conclusions: The proposed solution is able to solve surface registration problems with an accuracy suitable for radiotherapy cases where external surfaces offer primary or complementary information to patient positioning. The system shows promising dynamic properties for its use in gating/tracking applications. The overall system is competitive with commonly-used surface

  9. Polymer optical fiber for large strain measurement based on multimode interference.

    PubMed

    Huang, Jie; Lan, Xinwei; Wang, Hanzheng; Yuan, Lei; Wei, Tao; Gao, Zhan; Xiao, Hai

    2012-10-15

    This Letter reports a polymer optical fiber (POF) based large strain sensor based on the multimode interference (MMI) theory for the application of structural health monitoring. A section of POFs is sandwiched between two silica single mode fibers to construct a single-mode-multimode-single-mode structure that produces a MMI spectrum. The strain sensing mechanism of the device was investigated and experimentally verified. A large dynamic range of 2×10(4) με (2%) and a detection limit of 33 µε have been demonstrated.

  10. Ray-tracing based registration for HRCT images of the lungs.

    PubMed

    Busayara, Sata; Zrimec, Tatjana

    2006-01-01

    Image registration is a fundamental problem in medical imaging. It is especially challenging in lung images compared, for example, with the brain. The challenges include large anatomical variations of human lung and a lack of fixed landmarks inside the lung. This paper presents a new method for lung HRCT image registration. It employs a landmark-based global transformation and a novel ray-tracing-based lung surface registration. The proposed surface registration method has two desirable properties: 1) it is fully reversible, and 2) it ensures that the registered lung will be inside the target lung. We evaluated the registration performance by applying it to lung regions mapping. Tested on 46 scans, the registered regions were 89% accurate compared with the ground-truth.

  11. Free-form deformation based non-rigid registration on breast cancer MR imaging

    NASA Astrophysics Data System (ADS)

    Zhang, Liangbin; Suo, Shiteng; Lu, Xuesong; Li, Yuehua; Chen, Li; Zhang, Su

    2013-07-01

    High-Intensity Focused Ultrasound treatment combined with magnetic resonance technology (MRI-guided HIFU, MRgHIFU) can protect the thermal ablation without harming the surrounding tissue by using MRI for target positioning, where image registration plays an important role in the implementation of precise treatment. In this paper, we apply three-dimension free-form deformation non-rigid registration on treatment plan amendments and tracking of breast cancer. Free-form deformation based and demons based non-rigid registration are respectively employed on breast cancer MR imaging required at different times before and after for comparison. The results of the experiments show that the registration performed on the breast tumor image data with slight and larger deformation is effective, and the mutual information of the ROI increased from 1.49 before registration to 1.53.

  12. Handheld laser scanner automatic registration based on random coding

    NASA Astrophysics Data System (ADS)

    He, Lei; Yu, Chun-ping; Wang, Li

    2011-06-01

    Current research on Laser Scanner often focuses mainly on the static measurement. Little use has been made of dynamic measurement, that are appropriate for more problems and situations. In particular, traditional Laser Scanner must Keep stable to scan and measure coordinate transformation parameters between different station. In order to make the scanning measurement intelligently and rapidly, in this paper ,we developed a new registration algorithm for handleheld laser scanner based on the positon of target, which realize the dynamic measurement of handheld laser scanner without any more complex work. the double camera on laser scanner can take photograph of the artificial target points to get the three-dimensional coordinates, this points is designed by random coding. And then, a set of matched points is found from control points to realize the orientation of scanner by the least-square common points transformation. After that the double camera can directly measure the laser point cloud in the surface of object and get the point cloud data in an unified coordinate system. There are three major contributions in the paper. Firstly, a laser scanner based on binocular vision is designed with double camera and one laser head. By those, the real-time orientation of laser scanner is realized and the efficiency is improved. Secondly, the coding marker is introduced to solve the data matching, a random coding method is proposed. Compared with other coding methods,the marker with this method is simple to match and can avoid the shading for the object. Finally, a recognition method of coding maker is proposed, with the use of the distance recognition, it is more efficient. The method present here can be used widely in any measurement from small to huge obiect, such as vehicle, airplane which strengthen its intelligence and efficiency. The results of experiments and theory analzing demonstrate that proposed method could realize the dynamic measurement of handheld laser

  13. 3D-2D ultrasound feature-based registration for navigated prostate biopsy: a feasibility study.

    PubMed

    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.

  14. Fabrication of polymer-based multimode interference optical splitters by UV-based soft imprint lithography

    NASA Astrophysics Data System (ADS)

    Liang, Yuxin; Han, Xiuyou; Luo, Yuqing; Gu, Yiying; Wu, Zhenlin; Zhao, Mingshan

    2016-10-01

    A polymer-based multimode interference (MMI) optical splitter chip has been fabricated through UV-based soft imprint lithography (Soft UV-NIL) technique. Propagation loss and bending loss are considered during the chip design in order to decrease the insertion loss. UV curable fluorinated acrylate resin is used due to its low material absorbing loss. 1×4 cascaded MMI splitter is fabricated and measured at 1550 nm optical wavelength and an average 12.38 dB insertion loss is obtained together with an 1.23 dB uniformity.

  15. Medical image registration using machine learning-based interest point detector

    NASA Astrophysics Data System (ADS)

    Sergeev, Sergey; Zhao, Yang; Linguraru, Marius George; Okada, Kazunori

    2012-02-01

    This paper presents a feature-based image registration framework which exploits a novel machine learning (ML)-based interest point detection (IPD) algorithm for feature selection and correspondence detection. We use a feed-forward neural network (NN) with back-propagation as our base ML detector. Literature on ML-based IPD is scarce and to our best knowledge no previous research has addressed feature selection strategy for IPD purpose with cross-validation (CV) detectability measure. Our target application is the registration of clinical abdominal CT scans with abnormal anatomies. We evaluated the correspondence detection performance of the proposed ML-based detector against two well-known IPD algorithms: SIFT and SURF. The proposed method is capable of performing affine rigid registrations of 2D and 3D CT images, demonstrating more than two times better accuracy in correspondence detection than SIFT and SURF. The registration accuracy has been validated manually using identified landmark points. Our experimental results shows an improvement in 3D image registration quality of 18.92% compared with affine transformation image registration method from standard ITK affine registration toolkit.

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

    SciTech Connect

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

    2015-04-15

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

  17. Comprehensive Context Recognizer Based on Multimodal Sensors in a Smartphone

    PubMed Central

    Han, Manhyung; Vinh, La The; Lee, Young-Koo; Lee, Sungyoung

    2012-01-01

    Recent developments in smartphones have increased the processing capabilities and equipped these devices with a number of built-in multimodal sensors, including accelerometers, gyroscopes, GPS interfaces, Wi-Fi access, and proximity sensors. Despite the fact that numerous studies have investigated the development of user-context aware applications using smartphones, these applications are currently only able to recognize simple contexts using a single type of sensor. Therefore, in this work, we introduce a comprehensive approach for context aware applications that utilizes the multimodal sensors in smartphones. The proposed system is not only able to recognize different kinds of contexts with high accuracy, but it is also able to optimize the power consumption since power-hungry sensors can be activated or deactivated at appropriate times. Additionally, the system is able to recognize activities wherever the smartphone is on a human's body, even when the user is using the phone to make a phone call, manipulate applications, play games, or listen to music. Furthermore, we also present a novel feature selection algorithm for the accelerometer classification module. The proposed feature selection algorithm helps select good features and eliminates bad features, thereby improving the overall accuracy of the accelerometer classifier. Experimental results show that the proposed system can classify eight activities with an accuracy of 92.43%.

  18. Multi-parameter optical fiber sensor based on enhanced multimode interference

    NASA Astrophysics Data System (ADS)

    Luo, Yiyang; Xia, Li; Yu, Can; Li, Wei; Sun, Qizhen; Wang, Yuanwu; Liu, Deming

    2015-06-01

    In this paper, a multi-parameter optical fiber sensor based on all-fiber in-line single-mode-multimode-no-core-single-mode (SMNS) structure is proposed and experimentally demonstrated. A section of multimode fiber (MMF) is utilized as the mode coupler to enhance the multimode interference (MMI). A 58.5 mm long no-core fiber (NCF) acts as the sensing head, which is modified by the surrounding medium. The experimental results exhibit that the sensor possesses a water level sensitivity of 215.98 pm/mm by monitoring the wavelength shift at 1586.03 nm, and -0.11 dB/mm of the power attenuation at the wavelength of 1600.05 nm with a measurement range of 58.33 mm. At the same time, the RI sensitivities of 131.71 nm/RIU and the axial strain sensitivity of -1.21 pm/με are also obtained.

  19. Design and test of multimode interference based optical fiber temperature sensors

    NASA Astrophysics Data System (ADS)

    Li, Enbang

    2008-12-01

    Fiber-optic temperature sensors offer unique advantages, such as immunity to electromagnetic interferences, stability, repeatability, durability against harsh environments, high sensitivity and resolution, and fast response. Therefore, optical fiber sensors have been widely adopted and applied in various areas for temperature measurements. It has been demonstrated that by using multimode interferences in a segment of multimode fiber, wavelength-encoded fiber optic temperature sensing can be achieved. The advantages of this kind of temperature sensors include the extremely simple structure and the ability for high-temperature measurements. In this work, we investigate the interference of core mode and cladding modes in double cladding fibers. Analysis and simulations are carried out in order to identify the optimal parameters of the temperature sensor. Practical design of the multimode interference based optical fiber temperature sensors is investigated, and sensing probes are fabricated and tested. The design details, temperature measurement experiments, and test results are presented in this paper.

  20. Sensitivity improvement of optical-fiber temperature sensor with solid cladding material based on multimode interference

    NASA Astrophysics Data System (ADS)

    Fukano, Hideki; Kushida, Yohei; Taue, Shuji

    2015-03-01

    We have developed a simple, high-sensitivity optical-fiber temperature sensor based on multimode interference (MMI). The fabricated MMI structure comprises three segmented fibers: a single-mode fiber (SMF); a large-core multimode fiber (MMF), whose outer surface is coated with a temperature-sensitive material; and another SMF. Fluoroacrylate and silicone rubber are tested as temperature-sensitive cladding materials. The silicone rubber coating exhibits a large shift in interference wavelength with temperature, producing a very fine temperature resolution as low as 0.01 °C.

  1. Miniaturized multimodal CARS microscope based on MEMS scanning and a single laser source.

    PubMed

    Murugkar, Sangeeta; Smith, Brett; Srivastava, Prateek; Moica, Adrian; Naji, Majid; Brideau, Craig; Stys, Peter K; Anis, Hanan

    2010-11-08

    We demonstrate a novel miniaturized multimodal coherent anti-Stokes Raman scattering (CARS) microscope based on microelectromechanical systems (MEMS) scanning mirrors and custom miniature optics. A single Ti:sapphire femtosecond pulsed laser is used as the light source to produce the CARS, two photon excitation fluorescence (TPEF) and second harmonic generation (SHG) images using this miniaturized microscope. The high resolution and distortion-free images obtained from various samples such as a USAF target, fluorescent and polystyrene microspheres and biological tissue successfully demonstrate proof of concept, and pave the path towards future integration of parts into a handheld multimodal CARS probe for non- or minimally-invasive in vivo imaging.

  2. A refractive index sensor based on taper Michelson interferometer in multimode fiber

    NASA Astrophysics Data System (ADS)

    Fu, Xinghu; Zhang, Jiangpeng; Wang, Siwen; Fu, Guangwei; Liu, Qiang; Jin, Wa; Bi, Weihong

    2016-11-01

    A refractive index sensor based on taper Michelson interferometer in multimode fiber is proposed. The Hydrofluoric acid corrosion processing is studied in the preparation of single cone multimode optical fiber sensor. The taper Michelson interferometer is fabricated by changing corrosion time. The relationship between fiber sensor feature and corrosion time is analyzed. The experimental results show that the interference spectrum shift in the direction of short wave with the increase of the refractive index. The refractive index sensitivity can reach 115.8008 nm/RIU. Thereby, it can be used in detecting the refractive index in different areas including the environmental protection, health care and food production.

  3. Alcohol sensor based on single-mode-multimode-single-mode fiber structure

    NASA Astrophysics Data System (ADS)

    Mefina Yulias, R.; Hatta, A. M.; Sekartedjo, Sekartedjo

    2016-11-01

    Alcohol sensor based on Single-mode -Multimode-Single-mode (SMS) fiber structure is being proposed to sense alcohol concentration in alcohol-water mixtures. This proposed sensor uses refractive index sensing as its sensing principle. Fabricated SMS fiber structure had 40 m of multimode length. With power input -6 dBm and wavelength 1550 nm, the proposed sensor showed good response with sensitivity 1,983 dB per % v/v with measurement range 05 % v/v and measurement span 0,5% v/v.

  4. Redundant Discrete Wavelet Transform Based Super-Resolution Using Sub-Pixel Image Registration

    DTIC Science & Technology

    2003-03-01

    AFIT/GE/ENG/03-18 REDUNDANT DISCRETE WAVELET TRANSFORM BASED SUPER-RESOLUTION USING SUB-PIXEL IMAGE REGISTRATION THESIS Daniel L. Ward Second...position of the United States Air Force, Department of Defense, or the United States Government. AFIT/GE/ENG/03-18 REDUNDANT DISCRETE WAVELET TRANSFORM BASED...O3-18 REDUNDANT DISCRETE WAVELET TRANSFORM BASED SUPER-RESOLUTION USING SUB-PIXEL IMAGE REGISTRATION THESIS Daniel Lee Ward, B.S.E.E. Second

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

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

    PubMed

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

    2014-11-21

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  8. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... (CONTINUED) MISCELLANEOUS RULES RELATING TO COMMON CARRIERS Telecommunications Relay Services and Related...) Default provider registration. Every provider of VRS or IP Relay must, no later than December 31, 2008, provide users with the capability to register with that VRS or IP Relay provider as a “default...

  9. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... (CONTINUED) MISCELLANEOUS RULES RELATING TO COMMON CARRIERS Telecommunications Relay Services and Related...) Default provider registration. Every provider of VRS or IP Relay must, no later than December 31, 2008, provide users with the capability to register with that VRS or IP Relay provider as a “default...

  10. Efficient registration of multitemporal and multisensor aerial images based on alignment of nonparametric edge features

    NASA Astrophysics Data System (ADS)

    Makrogiannis, Sokratis; Bourbakis, Nikolaos G.

    2010-01-01

    The topic of aerial image registration attracts considerable interest within the imaging research community due to its significance for several applications, including change detection, sensor fusion, and topographic mapping. Our interest is focused on finding the optimal transformation between two aerial images that depict the same visual scene in the presence of pronounced spatial, temporal, and sensor variations. We first introduce a stochastic edge estimation process suitable for geometric shape-based registration, which we also compare to intensity-based registration. Furthermore, we propose an objective function that weights the L2 distances of the edge estimates by the feature points' energy, which we denote by sum of normalized squared differences and compare to standard objective functions, such as mutual information and the sum of absolute centered differences. In the optimization stage, we employ a genetic algorithm scheme in a multiscale image representation scheme to enhance the registration accuracy and reduce the computational load. Our experimental tests, measuring registration accuracy, rate of convergence, and statistical properties of registration errors, suggest that the proposed edge-based representation and objective function in conjunction with genetic algorithm optimization are capable of addressing several forms of imaging variations and producing encouraging registration results.

  11. A Multistage Approach for Image Registration.

    PubMed

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

    2016-09-01

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

  12. Hybrid registration of PET/CT in thoracic region with pre-filtering PET sinogram

    NASA Astrophysics Data System (ADS)

    Mokri, S. S.; Saripan, M. I.; Marhaban, M. H.; Nordin, A. J.; Hashim, S.

    2015-11-01

    The integration of physiological (PET) and anatomical (CT) images in cancer delineation requires an accurate spatial registration technique. Although hybrid PET/CT scanner is used to co-register these images, significant misregistrations exist due to patient and respiratory/cardiac motions. This paper proposes a hybrid feature-intensity based registration technique for hybrid PET/CT scanner. First, simulated PET sinogram was filtered with a 3D hybrid mean-median before reconstructing the image. The features were then derived from the segmented structures (lung, heart and tumor) from both images. The registration was performed based on modified multi-modality demon registration with multiresolution scheme. Apart from visual observations improvements, the proposed registration technique increased the normalized mutual information index (NMI) between the PET/CT images after registration. All nine tested datasets show marked improvements in mutual information (MI) index than free form deformation (FFD) registration technique with the highest MI increase is 25%.

  13. Computer-Based Multimodal Composing Activities, Self-Revision, and L2 Acquisition through Writing

    ERIC Educational Resources Information Center

    Dzekoe, Richmond

    2017-01-01

    This study investigated how 22 advanced-low proficiency ESL students used computer-based multimodal composing activities (CBMCAs) to facilitate self-revision and learn English through academic writing in the USA. The CBMCAs involved a combination of writing, listening, visual analysis, and speaking activities. The research was framed within an…

  14. A Randomized Trial of a Multimodal Community-Based Prisoner Reentry Program Emphasizing Substance Abuse Treatment

    ERIC Educational Resources Information Center

    Grommon, Eric; Davidson, William S., II; Bynum, Timothy S.

    2013-01-01

    Prisoner reentry programs continue to be developed and implemented to ease the process of transition into the community and to curtail fiscal pressures. This study describes and provides relapse and recidivism outcome findings related to a randomized trial evaluating a multimodal, community-based reentry program that prioritized substance abuse…

  15. Investigating the Effects of Multimodal Feedback through Tracking State in Pen-Based Interfaces

    ERIC Educational Resources Information Center

    Sun, Minghui; Ren, Xiangshi

    2011-01-01

    A tracking state increases the bandwidth of pen-based interfaces. However, this state is difficult to detect with default visual feedback. This paper reports on two experiments that are designed to evaluate multimodal feedback for pointing tasks (both 1D and 2D) in tracking state. In 1D pointing experiments, results show that there is a…

  16. Hough-transform-based circle detection using an array of multimode optical fibers

    NASA Astrophysics Data System (ADS)

    Li, Yao; Eichmann, George

    1987-02-01

    The generation of an optical Hough transform (OHT) to detect a circle is proposed. The method is based on the use of a 2D multimode step-index optical fiber array. Both the position and radius of a circle can be detected. Some of the OHT performance parameters are also discussed.

  17. A Randomized Trial of a Multimodal Community-Based Prisoner Reentry Program Emphasizing Substance Abuse Treatment

    ERIC Educational Resources Information Center

    Grommon, Eric; Davidson, William S., II; Bynum, Timothy S.

    2013-01-01

    Prisoner reentry programs continue to be developed and implemented to ease the process of transition into the community and to curtail fiscal pressures. This study describes and provides relapse and recidivism outcome findings related to a randomized trial evaluating a multimodal, community-based reentry program that prioritized substance abuse…

  18. Using Interdisciplinary, Project-Based, Multimodal Activities to Facilitate Literacy across the Content Areas

    ERIC Educational Resources Information Center

    Hill, Archie E.

    2014-01-01

    Tour Across America is an interdisciplinary, project-based, multimodal (IPM) activity where students get the opportunity to apply what they learn to a real-life situation while illustrating the interdisciplinary nature of literacy. It provides students with a high-interest, creative platform to review, reinforce, and integrate learned literacy…

  19. Student's Uncertainty Modeling through a Multimodal Sensor-Based Approach

    ERIC Educational Resources Information Center

    Jraidi, Imene; Frasson, Claude

    2013-01-01

    Detecting the student internal state during learning is a key construct in educational environment and particularly in Intelligent Tutoring Systems (ITS). Students' uncertainty is of primary interest as it is deeply rooted in the process of knowledge construction. In this paper we propose a new sensor-based multimodal approach to model…

  20. Student's Uncertainty Modeling through a Multimodal Sensor-Based Approach

    ERIC Educational Resources Information Center

    Jraidi, Imene; Frasson, Claude

    2013-01-01

    Detecting the student internal state during learning is a key construct in educational environment and particularly in Intelligent Tutoring Systems (ITS). Students' uncertainty is of primary interest as it is deeply rooted in the process of knowledge construction. In this paper we propose a new sensor-based multimodal approach to model…

  1. Creative Multimodal Learning Environments and Blended Interaction for Problem-Based Activity in HCI Education

    ERIC Educational Resources Information Center

    Ioannou, Andri; Vasiliou, Christina; Zaphiris, Panayiotis; Arh, Tanja; Klobucar, Tomaž; Pipan, Matija

    2015-01-01

    This exploratory case study aims to examine how students benefit from a multimodal learning environment while they engage in collaborative problem-based activity in a Human Computer Interaction (HCI) university course. For 12 weeks, 30 students, in groups of 5-7 each, participated in weekly face-to-face meetings and online interactions.…

  2. A Mechanism for Multimodal Presentation Planning Based on Agent Cooperation and Negotiation.

    ERIC Educational Resources Information Center

    Han, Yi; Zukerman, Ingrid

    1997-01-01

    Introduces a multiagent architecture based on the blackboard system that enables different processes that perform multimodal presentation planning to communicate with each other. Describes a constraint propagation mechanism that transfers plan constraints from one level of the presentation planning process to the next. Discusses the cooperation…

  3. Using Interdisciplinary, Project-Based, Multimodal Activities to Facilitate Literacy across the Content Areas

    ERIC Educational Resources Information Center

    Hill, Archie E.

    2014-01-01

    Tour Across America is an interdisciplinary, project-based, multimodal (IPM) activity where students get the opportunity to apply what they learn to a real-life situation while illustrating the interdisciplinary nature of literacy. It provides students with a high-interest, creative platform to review, reinforce, and integrate learned literacy…

  4. Investigating the Effects of Multimodal Feedback through Tracking State in Pen-Based Interfaces

    ERIC Educational Resources Information Center

    Sun, Minghui; Ren, Xiangshi

    2011-01-01

    A tracking state increases the bandwidth of pen-based interfaces. However, this state is difficult to detect with default visual feedback. This paper reports on two experiments that are designed to evaluate multimodal feedback for pointing tasks (both 1D and 2D) in tracking state. In 1D pointing experiments, results show that there is a…

  5. Creative Multimodal Learning Environments and Blended Interaction for Problem-Based Activity in HCI Education

    ERIC Educational Resources Information Center

    Ioannou, Andri; Vasiliou, Christina; Zaphiris, Panayiotis; Arh, Tanja; Klobucar, Tomaž; Pipan, Matija

    2015-01-01

    This exploratory case study aims to examine how students benefit from a multimodal learning environment while they engage in collaborative problem-based activity in a Human Computer Interaction (HCI) university course. For 12 weeks, 30 students, in groups of 5-7 each, participated in weekly face-to-face meetings and online interactions.…

  6. A Mechanism for Multimodal Presentation Planning Based on Agent Cooperation and Negotiation.

    ERIC Educational Resources Information Center

    Han, Yi; Zukerman, Ingrid

    1997-01-01

    Introduces a multiagent architecture based on the blackboard system that enables different processes that perform multimodal presentation planning to communicate with each other. Describes a constraint propagation mechanism that transfers plan constraints from one level of the presentation planning process to the next. Discusses the cooperation…

  7. The method of registration of screw dislocations in polychromatic light based on the Young's interference scheme

    NASA Astrophysics Data System (ADS)

    Shostka, N. V.

    2011-06-01

    A new experimental method of registration of phase dislocations in polychromatic light is proposed and described, which is based on the Young's interference scheme using the screen with lots of pairs of holes.

  8. Social network extraction and analysis based on multimodal dyadic interaction.

    PubMed

    Escalera, Sergio; Baró, Xavier; Vitrià, Jordi; Radeva, Petia; Raducanu, Bogdan

    2012-01-01

    Social interactions are a very important component in people's lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times' Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links' weights are a measure of the "influence" a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.

  9. Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction

    PubMed Central

    Escalera, Sergio; Baró, Xavier; Vitrià, Jordi; Radeva, Petia; Raducanu, Bogdan

    2012-01-01

    Social interactions are a very important component in people’s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links’ weights are a measure of the “influence” a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network. PMID:22438733

  10. Multi-Modal Clique-Graph Matching for View-Based 3D Model Retrieval.

    PubMed

    Liu, An-An; Nie, Wei-Zhi; Gao, Yue; Su, Yu-Ting

    2016-05-01

    Multi-view matching is an important but a challenging task in view-based 3D model retrieval. To address this challenge, we propose an original multi-modal clique graph (MCG) matching method in this paper. We systematically present a method for MCG generation that is composed of cliques, which consist of neighbor nodes in multi-modal feature space and hyper-edges that link pairwise cliques. Moreover, we propose an image set-based clique/edgewise similarity measure to address the issue of the set-to-set distance measure, which is the core problem in MCG matching. The proposed MCG provides the following benefits: 1) preserves the local and global attributes of a graph with the designed structure; 2) eliminates redundant and noisy information by strengthening inliers while suppressing outliers; and 3) avoids the difficulty of defining high-order attributes and solving hyper-graph matching. We validate the MCG-based 3D model retrieval using three popular single-modal data sets and one novel multi-modal data set. Extensive experiments show the superiority of the proposed method through comparisons. Moreover, we contribute a novel real-world 3D object data set, the multi-view RGB-D object data set. To the best of our knowledge, it is the largest real-world 3D object data set containing multi-modal and multi-view information.

  11. Registration and fusion quantification of augmented reality based nasal endoscopic surgery.

    PubMed

    Chu, Yakui; Yang, Jian; Ma, Shaodong; Ai, Danni; Li, Wenjie; Song, Hong; Li, Liang; Chen, Duanduan; Chen, Lei; Wang, Yongtian

    2017-08-03

    This paper quantifies the registration and fusion display errors of augmented reality-based nasal endoscopic surgery (ARNES). We comparatively investigated the spatial calibration process for front-end endoscopy and redefined the accuracy level of a calibrated endoscope by using a calibration tool with improved structural reliability. We also studied how registration accuracy was combined with the number and distribution of the deployed fiducial points (FPs) for positioning and the measured registration time. A physically integrated ARNES prototype was customarily configured for performance evaluation in skull base tumor resection surgery with an innovative approach of dynamic endoscopic vision expansion. As advised by surgical experts in otolaryngology, we proposed a hierarchical rendering scheme to properly adapt the fused images with the required visual sensation. By constraining the rendered sight in a known depth and radius, the visual focus of the surgeon can be induced only on the anticipated critical anatomies and vessel structures to avoid misguidance. Furthermore, error analysis was conducted to examine the feasibility of hybrid optical tracking based on point cloud, which was proposed in our previous work as an in-surgery registration solution. Measured results indicated that the error of target registration for ARNES can be reduced to 0.77 ± 0.07 mm. For initial registration, our results suggest that a trade-off for a new minimal time of registration can be reached when the distribution of five FPs is considered. For in-surgery registration, our findings reveal that the intrinsic registration error is a major cause of performance loss. Rigid model and cadaver experiments confirmed that the scenic integration and display fluency of ARNES are smooth, as demonstrated by three clinical trials that surpassed practicality. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Iris-based cyclotorsional image alignment method for wavefront registration.

    PubMed

    Chernyak, Dimitri A

    2005-12-01

    In refractive surgery, especially wavefront-guided refractive surgery, correct registration of the treatment to the cornea is of paramount importance. The specificity of the custom ablation formula requires that the ablation be applied to the cornea only when it has been precisely aligned with the mapped area. If, however, the eye has rotated between measurement and ablation, and this cyclotorsion is not compensated for, the rotational misalignment could impair the effectiveness of the refractive surgery. To achieve precise registration, a noninvasive method for torsional rotational alignment of the captured wavefront image to the patient's eyes at surgery has been developed. This method applies a common coordinate system to the wavefront and the eye. Video cameras on the laser and wavefront devices precisely establish the spatial relationship between the optics of the eye and the natural features of the iris, enabling the surgeon to identify and compensate for cyclotorsional eye motion, whatever its cause.

  13. Registration based on projective reconstruction technique for augmented reality systems.

    PubMed

    Yuan, M L; Ong, S K; Nee, A Y C

    2005-01-01

    In AR systems, registration is one of the most difficult problems currently limiting their application. In this paper, we propose a simple registration method using projective reconstruction. This method consists of two steps: embedding and tracking. Embedding involves specifying four points to build the world coordinate system on which a virtual object will be superimposed. In tracking, a projective reconstruction technique is used to track these four specified points to compute the model view transformation for augmentation. This method is simple, as only four points need to be specified at the embedding stage and the virtual object can then be easily augmented onto a real scene from a video sequence. In addition, it can be extended to a scenario using the projective matrix that has been obtained from previous registration results using the same AR system. The proposed method has three advantages: 1) It is fast because the linear least square method can be used to estimate the related matrix in the algorithm and it is not necessary to calculate the fundamental matrix in the extended case. 2) A virtual object can still be superimposed on a related area even if some parts of the specified area are occluded during the whole process. 3) This method is robust because it remains effective even when not all the reference points are detected during the whole process, as long as at least six pairs of related reference points correspondences can be found. Some experiments have been conducted to validate the performance of the proposed method.

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

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

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

  15. Validation of elastic registration algorithms based on adaptive irregular grids for medical applications

    NASA Astrophysics Data System (ADS)

    Franz, Astrid; Carlsen, Ingwer C.; Renisch, Steffen; Wischmann, Hans-Aloys

    2006-03-01

    Elastic registration of medical images is an active field of current research. Registration algorithms have to be validated in order to show that they fulfill the requirements of a particular clinical application. Furthermore, validation strategies compare the performance of different registration algorithms and can hence judge which algorithm is best suited for a target application. In the literature, validation strategies for rigid registration algorithms have been analyzed. For a known ground truth they assess the displacement error at a few landmarks, which is not sufficient for elastic transformations described by a huge number of parameters. Hence we consider the displacement error averaged over all pixels in the whole image or in a region-of-interest of clinical relevance. Using artificially, but realistically deformed images of the application domain, we use this quality measure to analyze an elastic registration based on transformations defined on adaptive irregular grids for the following clinical applications: Magnetic Resonance (MR) images of freely moving joints for orthopedic investigations, thoracic Computed Tomography (CT) images for the detection of pulmonary embolisms, and transmission images as used for the attenuation correction and registration of independently acquired Positron Emission Tomography (PET) and CT images. The definition of a region-of-interest allows to restrict the analysis of the registration accuracy to clinically relevant image areas. The behaviour of the displacement error as a function of the number of transformation control points and their placement can be used for identifying the best strategy for the initial placement of the control points.

  16. Integrating segmentation information for improved MRF-based elastic image registration.

    PubMed

    Mahapatra, Dwarikanath; Sun, Ying

    2012-01-01

    In this paper, we propose a method to exploit segmentation information for elastic image registration using a Markov-random-field (MRF)-based objective function. MRFs are suitable for discrete labeling problems, and the labels are defined as the joint occurrence of displacement fields (for registration) and segmentation class probability. The data penalty is a combination of the image intensity (or gradient information) and the mutual dependence of registration and segmentation information. The smoothness is a function of the interaction between the defined labels. Since both terms are a function of registration and segmentation labels, the overall objective function captures their mutual dependence. A multiscale graph-cut approach is used to achieve subpixel registration and reduce the computation time. The user defines the object to be registered in the floating image, which is rigidly registered before applying our method. We test our method on synthetic image data sets with known levels of added noise and simulated deformations, and also on natural and medical images. Compared with other registration methods not using segmentation information, our proposed method exhibits greater robustness to noise and improved registration accuracy.

  17. The Image Registration of Fourier-Mellin Based on the Combination of Projection and Gradient Preprocessing

    NASA Astrophysics Data System (ADS)

    Gao, D.; Zhao, X.; Pan, X.

    2017-09-01

    Image registration is one of the most important applications in the field of image processing. The method of Fourier Merlin transform, which has the advantages of high precision and good robustness to change in light and shade, partial blocking, noise influence and so on, is widely used. However, not only this method can't obtain the unique mutual power pulse function for non-parallel image pairs, even part of image pairs also can't get the mutual power function pulse. In this paper, an image registration method based on Fourier-Mellin transformation in the view of projection-gradient preprocessing is proposed. According to the projection conformational equation, the method calculates the matrix of image projection transformation to correct the tilt image; then, gradient preprocessing and Fourier-Mellin transformation are performed on the corrected image to obtain the registration parameters. Eventually, the experiment results show that the method makes the image registration of Fourier-Mellin transformation not only applicable to the registration of the parallel image pairs, but also to the registration of non-parallel image pairs. What's more, the better registration effect can be obtained

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

    PubMed

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

    2016-07-01

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

  19. Dual-wavelength retinal image registration based on vessel segmentation and optic disc detection

    NASA Astrophysics Data System (ADS)

    Xian, Yong-li; Dai, Yun; Gao, Chun-ming; Du, Rui

    2016-09-01

    The dual-wavelength retinal image registration is one of the critical steps in the spectrophotometric measurements of oxygen saturation in the retinal vasculature. The dual-wavelength images (570 nm and 600 nm) are simultaneously captured by dual-wavelength retinal oximeter based on commercial fundus camera. The retinal oxygen saturation is finally measured after vessel segmentation, image registration and calculation of optical density ratio of the two images. Because the dual-wavelength images are acquired from different optical path, it is necessary to go through image registration before they are used to analyze the oxygen saturation. This paper presents a new approach to dual-wavelength retinal image registration based on vessel segmentation and optic disc detection. Firstly, the multi-scale segmentation algorithm based on the Hessian matrix is used to realize vessel segmentation. Secondly, after optic disc is detected by convergence index filter and the center of the optic disc is obtained by centriod algorithm, the translational difference between the images can be determined. The center of the optic disc is used as the center of rotation, and the registration based on mutual information can be achieved using contour and gray information of vessels through segmented image. So the rotational difference between the images can be determined too. The result shows that the algorithm can provide an accurate registration for the dual-wavelength retinal image.

  20. Learning-based deformable image registration for infant MR images in the first year of life.

    PubMed

    Hu, Shunbo; Wei, Lifang; Gao, Yaozong; Guo, Yanrong; Wu, Guorong; Shen, Dinggang

    2017-01-01

    Many brain development studies have been devoted to investigate dynamic structural and functional changes in the first year of life. To quantitatively measure brain development in such a dynamic period, accurate image registration for different infant subjects with possible large age gap is of high demand. Although many state-of-the-art image registration methods have been proposed for young and elderly brain images, very few registration methods work for infant brain images acquired in the first year of life, because of (a) large anatomical changes due to fast brain development and (b) dynamic appearance changes due to white-matter myelination. To address these two difficulties, we propose a learning-based registration method to not only align the anatomical structures but also alleviate the appearance differences between two arbitrary infant MR images (with large age gap) by leveraging the regression forest to predict both the initial displacement vector and appearance changes. Specifically, in the training stage, two regression models are trained separately, with (a) one model learning the relationship between local image appearance (of one development phase) and its displacement toward the template (of another development phase) and (b) another model learning the local appearance changes between the two brain development phases. Then, in the testing stage, to register a new infant image to the template, we first predict both its voxel-wise displacement and appearance changes by the two learned regression models. Since such initializations can alleviate significant appearance and shape differences between new infant image and the template, it is easy to just use a conventional registration method to refine the remaining registration. We apply our proposed registration method to align 24 infant subjects at five different time points (i.e., 2-week-old, 3-month-old, 6-month-old, 9-month-old, and 12-month-old), and achieve more accurate and robust registration

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

    NASA Astrophysics Data System (ADS)

    Gao, Yanfei; Wang, Hengyou; Bian, Xiaoning

    2015-08-01

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

  2. Interactive virtual endoscopy in coronary arteries based on multimodality fusion.

    PubMed

    Wahle, Andreas; Olszewski, Mark E; Sonka, Milan

    2004-11-01

    A novel approach for platform-independent virtual endoscopy in human coronary arteries is presented in this paper. It incorporates previously developed and validated methodology for multimodality fusion of two X-ray angiographic images with pullback data from intravascular ultrasound (IVUS). These modalities pose inherently different challenges than those present in many tomographic modalities that provide parallel slices. The fusion process results in a three- or four-dimensional (3-D/4-D) model of a coronary artery, specifically of its lumen/plaque and media/adventitia surfaces. The model is used for comprehensive quantitative hemodynamic, morphologic, and functional analyses. The resulting quantitative indexes are then used to supplement the model. Platform-independent visualization is achieved through the use of the ISO/IEC-standardized Virtual Reality Modeling Language (VRML). The visualization includes an endoscopic fly-through animation that enables the user to interactively select vessel location and fly-through speed, as well as to display image pixel data or quantification results in 3-D. The presented VRML virtual-endoscopy system is used in research studies of coronary atherosclerosis development, quantitative assessment of coronary morphology and function, and vascular interventions.

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

    NASA Astrophysics Data System (ADS)

    Fischer, Bernd; Modersitzki, Jan

    2003-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Hao, Yongfu; Jiang, Tianzi; Fan, Yong

    2012-02-01

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

  5. Liver DCE-MRI Registration in Manifold Space Based on Robust Principal Component Analysis

    NASA Astrophysics Data System (ADS)

    Feng, Qianjin; Zhou, Yujia; Li, Xueli; Mei, Yingjie; Lu, Zhentai; Zhang, Yu; Feng, Yanqiu; Liu, Yaqin; Yang, Wei; Chen, Wufan

    2016-09-01

    A technical challenge in the registration of dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging in the liver is intensity variations caused by contrast agents. Such variations lead to the failure of the traditional intensity-based registration method. To address this problem, a manifold-based registration framework for liver DCE-MR time series is proposed. We assume that liver DCE-MR time series are located on a low-dimensional manifold and determine intrinsic similarities between frames. Based on the obtained manifold, the large deformation of two dissimilar images can be decomposed into a series of small deformations between adjacent images on the manifold through gradual deformation of each frame to the template image along the geodesic path. Furthermore, manifold construction is important in automating the selection of the template image, which is an approximation of the geodesic mean. Robust principal component analysis is performed to separate motion components from intensity changes induced by contrast agents; the components caused by motion are used to guide registration in eliminating the effect of contrast enhancement. Visual inspection and quantitative assessment are further performed on clinical dataset registration. Experiments show that the proposed method effectively reduces movements while preserving the topology of contrast-enhancing structures and provides improved registration performance.

  6. Liver DCE-MRI Registration in Manifold Space Based on Robust Principal Component Analysis

    PubMed Central

    Feng, Qianjin; Zhou, Yujia; Li, Xueli; Mei, Yingjie; Lu, Zhentai; Zhang, Yu; Feng, Yanqiu; Liu, Yaqin; Yang, Wei; Chen, Wufan

    2016-01-01

    A technical challenge in the registration of dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging in the liver is intensity variations caused by contrast agents. Such variations lead to the failure of the traditional intensity-based registration method. To address this problem, a manifold-based registration framework for liver DCE-MR time series is proposed. We assume that liver DCE-MR time series are located on a low-dimensional manifold and determine intrinsic similarities between frames. Based on the obtained manifold, the large deformation of two dissimilar images can be decomposed into a series of small deformations between adjacent images on the manifold through gradual deformation of each frame to the template image along the geodesic path. Furthermore, manifold construction is important in automating the selection of the template image, which is an approximation of the geodesic mean. Robust principal component analysis is performed to separate motion components from intensity changes induced by contrast agents; the components caused by motion are used to guide registration in eliminating the effect of contrast enhancement. Visual inspection and quantitative assessment are further performed on clinical dataset registration. Experiments show that the proposed method effectively reduces movements while preserving the topology of contrast-enhancing structures and provides improved registration performance. PMID:27681452

  7. An improved SIFT algorithm based on KFDA in image registration

    NASA Astrophysics Data System (ADS)

    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.

  8. Landmark optimization using local curvature for point-based nonlinear rodent brain image registration.

    PubMed

    Liu, Yutong; Sajja, Balasrinivasa R; Uberti, Mariano G; Gendelman, Howard E; Kielian, Tammy; Boska, Michael D

    2012-01-01

    Purpose. To develop a technique to automate landmark selection for point-based interpolating transformations for nonlinear medical image registration. Materials and Methods. Interpolating transformations were calculated from homologous point landmarks on the source (image to be transformed) and target (reference image). Point landmarks are placed at regular intervals on contours of anatomical features, and their positions are optimized along the contour surface by a function composed of curvature similarity and displacements of the homologous landmarks. The method was evaluated in two cases (n = 5 each). In one, MRI was registered to histological sections; in the second, geometric distortions in EPI MRI were corrected. Normalized mutual information and target registration error were calculated to compare the registration accuracy of the automatically and manually generated landmarks. Results. Statistical analyses demonstrated significant improvement (P < 0.05) in registration accuracy by landmark optimization in most data sets and trends towards improvement (P < 0.1) in others as compared to manual landmark selection.

  9. An effective non-rigid registration approach for ultrasound image based on "demons" algorithm.

    PubMed

    Liu, Yan; Cheng, H D; Huang, Jianhua; Zhang, Yingtao; Tang, Xianglong; Tian, Jiawei

    2013-06-01

    Medical image registration is an important component of computer-aided diagnosis system in diagnostics, therapy planning, and guidance of surgery. Because of its low signal/noise ratio (SNR), ultrasound (US) image registration is a difficult task. In this paper, a fully automatic non-rigid image registration algorithm based on demons algorithm is proposed for registration of ultrasound images. In the proposed method, an "inertia force" derived from the local motion trend of pixels in a Moore neighborhood system is produced and integrated into optical flow equation to estimate the demons force, which is helpful to handle the speckle noise and preserve the geometric continuity of US images. In the experiment, a series of US images and several similarity measure metrics are utilized for evaluating the performance. The experimental results demonstrate that the proposed method can register ultrasound images efficiently, robust to noise, quickly and automatically.

  10. [Application of elastic registration based on Demons algorithm in cone beam CT].

    PubMed

    Pang, Haowen; Sun, Xiaoyang

    2014-02-01

    We applied Demons and accelerated Demons elastic registration algorithm in radiotherapy cone beam CT (CBCT) images, We provided software support for real-time understanding of organ changes during radiotherapy. We wrote a 3D CBCT image elastic registration program using Matlab software, and we tested and verified the images of two patients with cervical cancer 3D CBCT images for elastic registration, based on the classic Demons algorithm, minimum mean square error (MSE) decreased 59.7%, correlation coefficient (CC) increased 11.0%. While for the accelerated Demons algorithm, MSE decreased 40.1%, CC increased 7.2%. The experimental verification with two methods of Demons algorithm obtained the desired results, but the small difference appeared to be lack of precision, and the total registration time was a little long. All these problems need to be further improved for accuracy and reducing of time.

  11. Dynamic algorithm selection for multi-sensor image registration

    NASA Astrophysics Data System (ADS)

    DelMarco, Stephen; Tom, Victor; Webb, Helen; Lefebvre, David

    2009-05-01

    Modern sensors have a range of modalities including SAR, EO, and IR. Registration of multimodal imagery from such sensors is becoming an increasingly common pre-processing step for various image exploitation activities such as image fusion for ATR. Over the past decades, several approaches to multisensor image registration have been developed. However, performance of these image registration algorithms is highly dependent on scene content and sensor operating conditions, with no single algorithm working well across the entire operating conditions space. To address this problem, in this paper we present an approach for dynamic selection of an appropriate registration algorithm, tuned to the scene content and feature manifestation of the imagery under consideration. We consider feature-based registration using Harris corners, Canny edge detection, and CFAR features, as well as pixel-based registration using cross-correlation and mutual information. We develop an approach for selecting the optimal combination of algorithms to use in the dynamic selection algorithm. We define a performance measure which balances contributions from convergence redundancy and convergence coverage components calculated over sample imagery, and optimize the measure to define an optimal algorithm set. We present numerical results demonstrating the improvement in registration performance through use of the dynamic algorithm selection approach over results generated through use of a fixed registration algorithm approach. The results provide registration convergence probabilities for geo-registering test SAR imagery against associated EO reference imagery. We present convergence results for various match score normalizations used in the dynamic selection algorithm.

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

    NASA Astrophysics Data System (ADS)

    Hu, Jinyan; Li, Li; Yang, Yunfeng

    2017-06-01

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

  13. [The meteorological satellite spectral image registration based on Fourier-Mellin transform].

    PubMed

    Wang, Liang; Liu, Rong; Zhang, Li; Duan, Fu-Qing; Lü, Ke

    2013-03-01

    The meteorological satellite spectral image is an effective tool for researches on meteorological science and environmental remote sensing science. Image registration is the basis for the application of the meteorological satellite spectral image data. In order to realize the registration of the satellite image and the template image, a new registration method based on the Fourier-Mellin transform is presented in this paper. Firstly, we use the global coastline vector map data to build a landmark template, which is a reference for the meteorological satellite spectral image registration. Secondly, we choose infrared sub-image of no cloud according to the cloud channel data, and extract the edges of the infrared image by Sobel operator. Finally, the affine transform model parameters between the landmark template and the satellite image are determined by the Fourier-Mellin transform, and thus the registration is realized. The proposed method is based on the curve matching in essence. It needs no feature point extraction, and can greatly simplify the process of registration. The experimental results using the infrared spectral data of the FY-2D meteorological satellite show that the method is robust and can reach a high speed and high accuracy.

  14. Computer-aided psychotherapy based on multimodal elicitation, estimation and regulation of emotion.

    PubMed

    Cosić, Krešimir; Popović, Siniša; Horvat, Marko; Kukolja, Davor; Dropuljić, Branimir; Kovač, Bernard; Jakovljević, Miro

    2013-09-01

    Contemporary psychiatry is looking at affective sciences to understand human behavior, cognition and the mind in health and disease. Since it has been recognized that emotions have a pivotal role for the human mind, an ever increasing number of laboratories and research centers are interested in affective sciences, affective neuroscience, affective psychology and affective psychopathology. Therefore, this paper presents multidisciplinary research results of Laboratory for Interactive Simulation System at Faculty of Electrical Engineering and Computing, University of Zagreb in the stress resilience. Patient's distortion in emotional processing of multimodal input stimuli is predominantly consequence of his/her cognitive deficit which is result of their individual mental health disorders. These emotional distortions in patient's multimodal physiological, facial, acoustic, and linguistic features related to presented stimulation can be used as indicator of patient's mental illness. Real-time processing and analysis of patient's multimodal response related to annotated input stimuli is based on appropriate machine learning methods from computer science. Comprehensive longitudinal multimodal analysis of patient's emotion, mood, feelings, attention, motivation, decision-making, and working memory in synchronization with multimodal stimuli provides extremely valuable big database for data mining, machine learning and machine reasoning. Presented multimedia stimuli sequence includes personalized images, movies and sounds, as well as semantically congruent narratives. Simultaneously, with stimuli presentation patient provides subjective emotional ratings of presented stimuli in terms of subjective units of discomfort/distress, discrete emotions, or valence and arousal. These subjective emotional ratings of input stimuli and corresponding physiological, speech, and facial output features provides enough information for evaluation of patient's cognitive appraisal deficit

  15. Automatic vertebral identification using surface-based registration

    NASA Astrophysics Data System (ADS)

    Herring, Jeannette L.; Dawant, Benoit M.

    2000-06-01

    This work introduces an enhancement to currently existing methods of intra-operative vertebral registration by allowing the portion of the spinal column surface that correctly matches a set of physical vertebral points to be automatically selected from several possible choices. Automatic selection is made possible by the shape variations that exist among lumbar vertebrae. In our experiments, we register vertebral points representing physical space to spinal column surfaces extracted from computed tomography images. The vertebral points are taken from the posterior elements of a single vertebra to represent the region of surgical interest. The surface is extracted using an improved version of the fully automatic marching cubes algorithm, which results in a triangulated surface that contains multiple vertebrae. We find the correct portion of the surface by registering the set of physical points to multiple surface areas, including all vertebral surfaces that potentially match the physical point set. We then compute the standard deviation of the surface error for the set of points registered to each vertebral surface that is a possible match, and the registration that corresponds to the lowest standard deviation designates the correct match. We have performed our current experiments on two plastic spine phantoms and one patient.

  16. A statistical model for point-based target registration error with anisotropic fiducial localizer error.

    PubMed

    Wiles, Andrew D; Likholyot, Alexander; Frantz, Donald D; Peters, Terry M

    2008-03-01

    Error models associated with point-based medical image registration problems were first introduced in the late 1990s. The concepts of fiducial localizer error, fiducial registration error, and target registration error are commonly used in the literature. The model for estimating the target registration error at a position r in a coordinate frame defined by a set of fiducial markers rigidly fixed relative to one another is ubiquitous in the medical imaging literature. The model has also been extended to simulate the target registration error at the point of interest in optically tracked tools. However, the model is limited to describing the error in situations where the fiducial localizer error is assumed to have an isotropic normal distribution in R3. In this work, the model is generalized to include a fiducial localizer error that has an anisotropic normal distribution. Similar to the previous models, the root mean square statistic rms tre is provided along with an extension that provides the covariance Sigma tre. The new model is verified using a Monte Carlo simulation and a set of statistical hypothesis tests. Finally, the differences between the two assumptions, isotropic and anisotropic, are discussed within the context of their use in 1) optical tool tracking simulation and 2) image registration.

  17. Image registration under illumination variations using region-based confidence weighted M-estimators.

    PubMed

    Fouad, Mohamed M; Dansereau, Richard M; Whitehead, Anthony D

    2012-03-01

    We present an image registration model for image sets with arbitrarily shaped local illumination variations between images. Any nongeometric variations tend to degrade the geometric registration precision and impact subsequent processing. Traditional image registration approaches do not typically account for changes and movement of light sources, which result in interimage illumination differences with arbitrary shape. In addition, these approaches typically use a least-square estimator that is sensitive to outliers, where interimage illumination variations are often large enough to act as outliers. In this paper, we propose an image registration approach that compensates for arbitrarily shaped interimage illumination variations, which are processed using robust M -estimators tuned to that region. Each M-estimator for each illumination region has a distinct cost function by which small and large interimage residuals are unevenly penalized. Since the segmentation of the interimage illumination variations may not be perfect, a segmentation confidence weighting is also imposed to reduce the negative effect of mis-segmentation around illumination region boundaries. The proposed approach is cast in an iterative coarse-to-fine framework, which allows a convergence rate similar to competing intensity-based image registration approaches. The overall proposed approach is presented in a general framework, but experimental results use the bisquare M-estimator with region segmentation confidence weighting. A nearly tenfold improvement in subpixel registration precision is seen with the proposed technique when convergence is attained, as compared with competing techniques using both simulated and real data sets with interimage illumination variations.

  18. Implementation of nonlinear registration of brain atlas based on piecewise grid system

    NASA Astrophysics Data System (ADS)

    Liu, Rong; Gu, Lixu; Xu, Jianrong

    2007-12-01

    In this paper, a multi-step registration method of brain atlas and clinical Magnetic Resonance Imaging (MRI) data based on Thin-Plate Splines (TPS) and Piecewise Grid System (PGS) is presented. The method can help doctors to determine the corresponding anatomical structure between patient image and the brain atlas by piecewise nonlinear registration. Since doctors mostly pay attention to particular Region of Interest (ROI), and a global nonlinear registration is quite time-consuming which is not suitable for real-time clinical application, we propose a novel method to conduct linear registration in global area before nonlinear registration is performed in selected ROI. The homogenous feature points are defined to calculate the transform matrix between patient data and the brain atlas to conclude the mapping function. Finally, we integrate the proposed approach into an application of neurosurgical planning and guidance system which lends great efficiency in both neuro-anatomical education and guiding of neurosurgical operations. The experimental results reveal that the proposed approach can keep an average registration error of 0.25mm in near real-time manner.

  19. An SMS structure based temperature sensor using a chalcogenide multimode fibre

    NASA Astrophysics Data System (ADS)

    Wang, Pengfei; Yuan, Libo; Brambilla, Gilberto; Farrell, Gerald

    2016-11-01

    In this work we investigated the fabrication of a singlemode-multimode-singlemode (SMS) fibre structure based on a chalcogenide (As2S3 and AsxS1-x) multimode fibre (MMF) sandwiched between two standard silica singlemode fibres (SMFs) using a commercial fibre fusion splicer. The temperature dependence of this hybrid fibre structure was also investigated. A first proof of concept showed that the hybrid SMS fibre structure has an average experimental temperature sensitivity of 50.63 pm/°C over a temperature range of 20 °C 100°C at wavelengths around 1.55 μm. The measured results show a general agreement with numerical simulations based on a guided-mode propagation analysis method. Our result provides a potential platform for the development of compact, high-optical-quality and robust sensing devices operating at the mid-infrared wavelength range.

  20. Design and fabrication of polymer-based multimode interference optical splitters

    NASA Astrophysics Data System (ADS)

    Liang, Yuxin; Zhao, Mingshan; Luo, Yuqing; Gu, Yiying; Zhang, Yang; Wang, Linghua; Han, Xiuyou; Wu, Zhenlin

    2016-11-01

    A polymer-based multimode interference optical splitter chip has been designed and fabricated. Fiber-waveguide coupling loss as well as the structure of the multimode waveguide are optimized in the design to achieve higher performance. A simple UV-based soft nanoimprint lithography (Soft UV-NIL) technique is adopted in the fabrication. Fluorinated acrylate resins, LFR, with different refractive indices are used in this work. Both the residual layer and waveguide deformation are improved by controlling the fabrication processes. An average of 12.98 dB insertion loss is obtained from 1×4 splitters with 1.08 dB uniformity and 0.05 dB polarization-dependent loss. The validity of the polymer optical splitters fabricated through Soft UV-NIL technique is demonstrated by software simulation as well as experimental works.

  1. Albumin based versatile multifunctional nanocarriers for cancer therapy: Fabrication, surface modification, multimodal therapeutics and imaging approaches.

    PubMed

    Kudarha, Ritu R; Sawant, Krutika K

    2017-12-01

    Albumin is a versatile protein used as a carrier system for cancer therapeutics. As a carrier it can provide tumor specificity, reduce drug related toxicity, maintain therapeutic concentration of the active moiety like drug, gene, peptide, protein etc. for long period of time and also reduce drug related toxicities. Apart from cancer therapy, it is also utilized in the imaging and multimodal therapy of cancer. This review highlights the important properties, structure and types of albumin based nanocarriers with regards to their use for cancer targeting. It also provides brief discussion on methods of preparation of these nanocarriers and their surface modification. Applications of albumin nanocarriers for cancer therapy, gene delivery, imaging, phototherapy and multimodal therapy have also been discussed. This review also provides brief discussion about albumin based marketed nano formulations and those under clinical trials. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    PubMed Central

    2014-01-01

    Background 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. Methods 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. Results 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

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

    PubMed

    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. Fat-based registration of breast dynamic contrast enhanced water images.

    PubMed

    Srinivasan, Subashini; Hargreaves, Brian A; Daniel, Bruce L

    2017-07-26

    In this study, a 3D fat-based deformable registration algorithm was developed for registering dynamic contrast-enhanced breast images. The mutual information similarity measure with free-form deformation motion correction in rapidly enhancing lesions can introduce motion. However, in Dixon-based fat-water separated acquisitions, the nonenhancing fat signal can directly be used to estimate deformable motion, which can be later used to deform the water images. Qualitative comparison of the fat-based registration method to a water-based registration method, and to the unregistered images, was performed by two experienced readers. Quantitative analysis of the registration was evaluated by estimating the mean-squared signal difference on the fat images. Using a scale of 0 (no motion) to 2 ( > 4 voxels of motion), the average image quality score of the fat-based registered images was 0.5 ± 0.6, water-based registration was 0.8 ± 0.8, and the unregistered dataset was 1.6 ± 0.6. The mean-squared-signal-difference metric on the fat images was significantly lower for fat-based registered images compared with both water-based registered and unregistered images. Fat-based registration of breast dynamic contrast-enhanced images is a promising technique for performing deformable motion correction of breast without introducing new motion. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  5. Registration of 2D to 3D joint images using phase-based mutual information

    NASA Astrophysics Data System (ADS)

    Dalvi, Rupin; Abugharbieh, Rafeef; Pickering, Mark; Scarvell, Jennie; Smith, Paul

    2007-03-01

    Registration of two dimensional to three dimensional orthopaedic medical image data has important applications particularly in the area of image guided surgery and sports medicine. Fluoroscopy to computer tomography (CT) registration is an important case, wherein digitally reconstructed radiographs derived from the CT data are registered to the fluoroscopy data. Traditional registration metrics such as intensity-based mutual information (MI) typically work well but often suffer from gross misregistration errors when the image to be registered contains a partial view of the anatomy visible in the target image. Phase-based MI provides a robust alternative similarity measure which, in addition to possessing the general robustness and noise immunity that MI provides, also employs local phase information in the registration process which makes it less susceptible to the aforementioned errors. In this paper, we propose using the complex wavelet transform for computing image phase information and incorporating that into a phase-based MI measure for image registration. Tests on a CT volume and 6 fluoroscopy images of the knee are presented. The femur and the tibia in the CT volume were individually registered to the fluoroscopy images using intensity-based MI, gradient-based MI and phase-based MI. Errors in the coordinates of fiducials present in the bone structures were used to assess the accuracy of the different registration schemes. Quantitative results demonstrate that the performance of intensity-based MI was the worst. Gradient-based MI performed slightly better, while phase-based MI results were the best consistently producing the lowest errors.

  6. Vision based tunnel inspection using non-rigid registration

    NASA Astrophysics Data System (ADS)

    Badshah, Amir; Ullah, Shan; Shahzad, Danish

    2015-04-01

    Growing numbers of long tunnels across the globe has increased the need for safety measurements and inspections of tunnels in these days. To avoid serious damages, tunnel inspection is highly recommended at regular intervals of time to find any deformations or cracks at the right time. While following the stringent safety and tunnel accessibility standards, conventional geodetic surveying using techniques of civil engineering and other manual and mechanical methods are time consuming and results in troublesome of routine life. An automatic tunnel inspection by image processing techniques using non rigid registration has been proposed. There are many other image processing methods used for image registration purposes. Most of the processes are operation of images in its spatial domain like finding edges and corners by Harris edge detection method. These methods are quite time consuming and fail for some or other reasons like for blurred or images with noise. Due to use of image features directly by these methods in the process, are known by the group, correlation by image features. The other method is featureless correlation, in which the images are converted into its frequency domain and then correlated with each other. The shift in spatial domain is the same as in frequency domain, but the processing is order faster than in spatial domain. In the proposed method modified normalized phase correlation has been used to find any shift between two images. As pre pre-processing the tunnel images i.e. reference and template are divided into small patches. All these relative patches are registered by the proposed modified normalized phase correlation. By the application of the proposed algorithm we get the pixel movement of the images. And then these pixels shifts are converted to measuring units like mm, cm etc. After the complete process if there is any shift in the tunnel at described points are located.

  7. Multi-modal label-free imaging based on a femtosecond fiber laser.

    PubMed

    Xie, Ruxin; Su, Jue; Rentchler, Eric C; Zhang, Ziyan; Johnson, Carey K; Shi, Honglian; Hui, Rongqing

    2014-07-01

    We demonstrate multi-mode microscopy based on a single femtosecond fiber laser. Coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS) and photothermal images can be obtained simultaneously with this simplified setup. Distributions of lipid and hemoglobin in sliced mouse brain samples and blood cells are imaged. The dependency of signal amplitude on the pump power and pump modulation frequency is characterized, which allows to isolate the impact from different contributions.

  8. 1×2 Multimode interference couplers based on semiconductor hollow waveguides formed from omnidirectional reflectors

    NASA Astrophysics Data System (ADS)

    Lo, Shih-Shou; Chen, Chii-Chang

    2007-07-01

    A 1×2 hollow multimode interference (MMI) coupler based on semiconductor hollow waveguides formed from omnidirectional reflectors (SHOW-ODR) is demonstrated. The device has a shorter coupling length than a conventional silicon-on-insulator MMI coupler. A 2 dB uniformity was achieved at operating wavelengths between 1520 and 1562 nm. The device exhibited a weak polarization dependence in the TE and TM modes.

  9. Multi-modal label-free imaging based on a femtosecond fiber laser

    PubMed Central

    Xie, Ruxin; Su, Jue; Rentchler, Eric C.; Zhang, Ziyan; Johnson, Carey K.; Shi, Honglian; Hui, Rongqing

    2014-01-01

    We demonstrate multi-mode microscopy based on a single femtosecond fiber laser. Coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS) and photothermal images can be obtained simultaneously with this simplified setup. Distributions of lipid and hemoglobin in sliced mouse brain samples and blood cells are imaged. The dependency of signal amplitude on the pump power and pump modulation frequency is characterized, which allows to isolate the impact from different contributions. PMID:25071972

  10. Log-Gabor energy based multimodal medical image fusion in NSCT domain.

    PubMed

    Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

    2014-01-01

    Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images.

  11. Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

    PubMed Central

    Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

    2014-01-01

    Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images. PMID:25214889

  12. Content-based medical image retrieval: a survey of applications to multidimensional and multimodality data.

    PubMed

    Kumar, Ashnil; Kim, Jinman; Cai, Weidong; Fulham, Michael; Feng, Dagan

    2013-12-01

    Medical imaging is fundamental to modern healthcare, and its widespread use has resulted in the creation of image databases, as well as picture archiving and communication systems. These repositories now contain images from a diverse range of modalities, multidimensional (three-dimensional or time-varying) images, as well as co-aligned multimodality images. These image collections offer the opportunity for evidence-based diagnosis, teaching, and research; for these applications, there is a requirement for appropriate methods to search the collections for images that have characteristics similar to the case(s) of interest. Content-based image retrieval (CBIR) is an image search technique that complements the conventional text-based retrieval of images by using visual features, such as color, texture, and shape, as search criteria. Medical CBIR is an established field of study that is beginning to realize promise when applied to multidimensional and multimodality medical data. In this paper, we present a review of state-of-the-art medical CBIR approaches in five main categories: two-dimensional image retrieval, retrieval of images with three or more dimensions, the use of nonimage data to enhance the retrieval, multimodality image retrieval, and retrieval from diverse datasets. We use these categories as a framework for discussing the state of the art, focusing on the characteristics and modalities of the information used during medical image retrieval.

  13. Unified Modeling Language (UML) for hospital-based cancer registration processes.

    PubMed

    Shiki, Naomi; Ohno, Yuko; Fujii, Ayumi; Murata, Taizo; Matsumura, Yasushi

    2008-01-01

    Hospital-based cancer registry involves complex processing steps that span across multiple departments. In addition, management techniques and registration procedures differ depending on each medical facility. Establishing processes for hospital-based cancer registry requires clarifying specific functions and labor needed. In recent years, the business modeling technique, in which management evaluation is done by clearly spelling out processes and functions, has been applied to business process analysis. However, there are few analytical reports describing the applications of these concepts to medical-related work. In this study, we initially sought to model hospital-based cancer registration processes using the Unified Modeling Language (UML), to clarify functions. The object of this study was the cancer registry of Osaka University Hospital. We organized the hospital-based cancer registration processes based on interview and observational surveys, and produced an As-Is model using activity, use-case, and class diagrams. After drafting every UML model, it was fed-back to practitioners to check its validity and improved. We were able to define the workflow for each department using activity diagrams. In addition, by using use-case diagrams we were able to classify each department within the hospital as a system, and thereby specify the core processes and staff that were responsible for each department. The class diagrams were effective in systematically organizing the information to be used for hospital-based cancer registries. Using UML modeling, hospital-based cancer registration processes were broadly classified into three separate processes, namely, registration tasks, quality control, and filing data. An additional 14 functions were also extracted. Many tasks take place within the hospital-based cancer registry office, but the process of providing information spans across multiple departments. Moreover, additional tasks were required in comparison to using a

  14. Surface-based facial scan registration in neuronavigation procedures: a clinical study.

    PubMed

    Shamir, Reuben R; Freiman, Moti; Joskowicz, Leo; Spektor, Sergey; Shoshan, Yigal

    2009-12-01

    Surface-based registration (SBR) with facial surface scans has been proposed as an alternative for the commonly used fiducial-based registration in image-guided neurosurgery. Recent studies comparing the accuracy of SBR and fiducial-based registration have been based on a few targets located on the head surface rather than inside the brain and have yielded contradictory conclusions. Moreover, no visual feedback is provided with either method to inform the surgeon about the estimated target registration error (TRE) at various target locations. The goals in the present study were: 1) to quantify the SBR error in a clinical setup, 2) to estimate the targeting error for many target locations inside the brain, and 3) to create a map of the estimated TRE values superimposed on a patient's head image. The authors randomly selected 12 patients (8 supine and 4 in a lateral position) who underwent neurosurgery with a commercial navigation system. Intraoperatively, scans of the patients' faces were acquired using a fast 3D surface scanner and aligned with their preoperative MR or CT head image. In the laboratory, the SBR accuracy was measured on the facial zone and estimated at various intracranial target locations. Contours related to different TREs were superimposed on the patient's head image and informed the surgeon about the expected anisotropic error distribution. The mean surface registration error in the face zone was 0.9 +/- 0.35 mm. The mean estimated TREs for targets located 60, 105, and 150 mm from the facial surface were 2.0, 3.2, and 4.5 mm, respectively. There was no difference in the estimated TRE between the lateral and supine positions. The entire registration procedure, including positioning of the scanner, surface data acquisition, and the registration computation usually required < 5 minutes. Surface-based registration accuracy is better in the face and frontal zones, and error increases as the target location lies further from the face. Visualization of

  15. Concurrent Tumor Segmentation and Registration with Uncertainty-based Sparse non-Uniform Graphs

    PubMed Central

    Parisot, Sarah; Wells, William; Chemouny, Stéphane; Duffau, Hugues; Paragios, Nikos

    2014-01-01

    In this paper, we present a graph-based concurrent brain tumor segmentation and atlas to diseased patient registration framework. Both segmentation and registration problems are modeled using a unified pairwise discrete Markov Random Field model on a sparse grid superimposed to the image domain. Segmentation is addressed based on pattern classification techniques, while registration is performed by maximizing the similarity between volumes and is modular with respect to the matching criterion. The two problems are coupled by relaxing the registration term in the tumor area, corresponding to areas of high classification score and high dissimilarity between volumes. In order to overcome the main shortcomings of discrete approaches regarding appropriate sampling of the solution space as well as important memory requirements, content driven samplings of the discrete displacement set and the sparse grid are considered, based on the local segmentation and registration uncertainties recovered by the min marginal energies. State of the art results on a substantial low-grade glioma database demonstrate the potential of our method, while our proposed approach shows maintained performance and strongly reduced complexity of the model. PMID:24717540

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

    PubMed

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

    2016-02-01

    Spatial alignment of Computed Tomography (CT) data sets is often required in numerous medical applications and it is usually achieved by applying conventional exhaustive registration techniques, which are mainly based on the intensity of the subject data sets. Those techniques consider the full range of data points composing the data, thus negatively affecting the required processing time. Alternatively, alignment can be performed using the correspondence of extracted data points from both sets. Moreover, various geometrical characteristics of those data points can be used, instead of their chromatic properties, for uniquely characterizing each point, by forming a specific geometrical descriptor. This paper presents a comparative study reviewing variations of geometry-based, descriptor-oriented registration techniques, as well as conventional, exhaustive, intensity-based methods for aligning three-dimensional (3D) CT data pairs. In this context, three general image registration frameworks were examined: a geometry-based methodology featuring three distinct geometrical descriptors, an intensity-based methodology using three different similarity metrics, as well as the commonly used Iterative Closest Point algorithm. All techniques were applied on a total of thirty 3D CT data pairs with both known and unknown initial spatial differences. After an extensive qualitative and quantitative assessment, it was concluded that the proposed geometry-based registration framework performed similarly to the examined exhaustive registration techniques. In addition, geometry-based methods dramatically improved processing time over conventional exhaustive registration. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Acquisition of priori tissue optical structure based on non-rigid image registration

    NASA Astrophysics Data System (ADS)

    Wan, Wenbo; Li, Jiao; Liu, Lingling; Wang, Yihan; Zhang, Yan; Gao, Feng

    2015-03-01

    Shape-parameterized diffuse optical tomography (DOT), which is based on a priori that assumes the uniform distribution of the optical properties in the each region, shows the effectiveness of complex biological tissue optical heterogeneities reconstruction. The priori tissue optical structure could be acquired with the assistance of anatomical imaging methods such as X-ray computed tomography (XCT) which suffers from low-contrast for soft tissues including different optical characteristic regions. For the mouse model, a feasible strategy of a priori tissue optical structure acquisition is proposed based on a non-rigid image registration algorithm. During registration, a mapping matrix is calculated to elastically align the XCT image of reference mouse to the XCT image of target mouse. Applying the matrix to the reference atlas which is a detailed mesh of organs/tissues in reference mouse, registered atlas can be obtained as the anatomical structure of target mouse. By assigning the literature published optical parameters of each organ to the corresponding anatomical structure, optical structure of the target organism can be obtained as a priori information for DOT reconstruction algorithm. By applying the non-rigid image registration algorithm to a target mouse which is transformed from the reference mouse, the results show that the minimum correlation coefficient can be improved from 0.2781 (before registration) to 0.9032 (after fine registration), and the maximum average Euclid distances can be decreased from 12.80mm (before registration) to 1.02mm (after fine registration), which has verified the effectiveness of the algorithm.

  18. High bandwidth all-optical 3×3 switch based on multimode interference structures

    NASA Astrophysics Data System (ADS)

    Le, Duy-Tien; Truong, Cao-Dung; Le, Trung-Thanh

    2017-03-01

    A high bandwidth all-optical 3×3 switch based on general interference multimode interference (GI-MMI) structure is proposed in this study. Two 3×3 multimode interference couplers are cascaded to realize an all-optical switch operating at both wavelengths of 1550 nm and 1310 nm. Two nonlinear directional couplers at two outer-arms of the structure are used as all-optical phase shifters to achieve all switching states and to control the switching states. Analytical expressions for switching operation using the transfer matrix method are presented. The beam propagation method (BPM) is used to design and optimize the whole structure. The optimal design of the all-optical phase shifters and 3×3 MMI couplers are carried out to reduce the switching power and loss.

  19. Multimodal Management of Mechanical Neck Pain Using a Treatment Based Classification System

    PubMed Central

    Heintz, Megan M.; Hegedus, Eric J.

    2008-01-01

    The purpose of this case study was twofold: 1) to illustrate the use of a treatment-based classification (TBC) system to direct the early intervention of a patient with mechanical neck pain, and 2) to show the progression of this patient with multimodal-modal intervention. The patient exhibited axial neck pain with referral into her upper extremity. Her pain peripheralized with cervical range of motion and centralized with joint mobilization placing her primarily in the centralization category. Her poor posture and associated muscle weakness along with the chronicity of symptoms placed her secondarily into the exercise and conditioning group resulting in a multi-modal treatment as the patient progressed. Although the design of this case report prevents wide applicability, this study does illustrate the effective use of the TBC system for the cervical spine as captured by accepted outcomes measures. PMID:19771194

  20. A robo-pigeon based on an innovative multi-mode telestimulation system.

    PubMed

    Yang, Junqing; Huai, Ruituo; Wang, Hui; Lv, Changzhi; Su, Xuecheng

    2015-01-01

    In this paper, we describe a new multi-mode telestimulation system for brain-microstimulation for the navigation of a robo-pigeon, a new type of bio-robot based on Brain-Computer Interface (BCI) techniques. The multi-mode telestimulation system overcomes neuron adaptation that was a key shortcoming of the previous single-mode stimulation by the use of non-steady TTL biphasic pulses accomplished by randomly alternating pulse modes. To improve efficiency, a new behavior model ("virtual fear") is proposed and applied to the robo-pigeon. Unlike the previous "virtual reward" model, the "virtual fear" behavior model does not require special training. The performance and effectiveness of the system to alleviate the adaptation of neurons was verified by a robo-pigeon navigation test, simultaneously confirming the practicality of the "virtual fear" behavioral model.

  1. A shape based rotation invariant method for ultrasound-MR image registration: A phantom study.

    PubMed

    Abdolghaffar, M; Ahmadian, A; Ayoobi, N; Farnia, P; Shabanian, T; Shafiei, N; Alirezaie, J

    2014-01-01

    In this work, a new shape based method to improve the accuracy of Brain Ultrasound-MRI image registration is proposed. The method is based on modified Shape Context (SC) descriptor in combination with CPD algorithm. An extensive experiment was carried out to evaluate the robustness of this method against different initialization conditions. As the results prove, the overall performance of the proposed algorithm outperforms both SC and CPD methods. In order to have control over the registration procedure, we simulated the deformations, missing points and outliers according to our Phantom MRI images.

  2. FMRI 3D registration based on Fourier space subsets using neural networks.

    PubMed

    Freire, Luis C; Gouveia, Ana R; Godinho, Fernando M

    2010-01-01

    In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

  3. Precision of image-based registration for intraoperative navigation in the presence of metal artifacts: Application to corrective osteotomy surgery.

    PubMed

    Dobbe, J G G; Curnier, F; Rondeau, X; Streekstra, G J

    2015-06-01

    Navigation for corrective osteotomy surgery requires patient-to-image registration. When registration is based on intraoperative 3-D cone-beam CT (CBCT) imaging, metal landmarks may be used that deteriorate image quality. This study investigates whether metal artifacts influence the precision of image-to-patient registration, either with or without intermediate user intervention during the registration procedure, in an application for corrective osteotomy of the distal radius. A series of 3-D CBCT scans is made of a cadaver arm with and without metal landmarks. Metal artifact reduction (MAR) based on inpainting techniques is used to improve 3-D CBCT images hampered by metal artifacts. This provides three sets of images (with metal, with MAR, and without metal), which enable investigating the differences in precision of intraoperative registration. Gray-level based point-to-image registration showed a better correlation coefficient if intraoperative images with MAR are used, indicating a better image similarity. The precision of registration without intermediate user intervention during the registration procedure, expressed as the residual angulation and displacement error after repetitive registration was very low and showed no improvement when MAR was used. By adding intermediate user intervention to the registration procedure however, precision was very high but was not affected by the presence of metal artifacts in the specific application.

  4. Model-based 3D/2D deformable registration of MR images.

    PubMed

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

    2011-01-01

    A method is proposed for automatic registration of 3D preoperative magnetic resonance images of deformable tissue to a sequence of its 2D intraoperative images. The algorithm employs a dynamic continuum mechanics model of the deformation and similarity (distance) measures such as correlation ratio, mutual information or sum of squared differences for registration. The registration is solely based on information present in the 3D preoperative and 2D intraoperative images and does not require fiducial markers, feature extraction or image segmentation. Results of experiments with a biopsy training breast phantom show that the proposed method can perform well in the presence of large deformations. This is particularly useful for clinical applications such as MR-based breast biopsy where large tissue deformations occur.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  8. Multimodal imaging probes based on Gd-DOTA conjugated quantum dot nanomicelles.

    PubMed

    Liu, Liwei; Law, Wing-Cheung; Yong, Ken-Tye; Roy, Indrajit; Ding, Hong; Erogbogbo, Folarin; Zhang, Xihe; Prasad, Paras N

    2011-05-07

    Recently, multimodal nanoparticles integrating dual- or tri-imaging modalities into a single hybrid nanosystem have attracted plenty of attention in biomedical research. Here, we report the fabrication of two types of multimodal micelle-encapsulated nanoparticles, which were systematically characterized and thoroughly evaluated in terms of their imaging potential and biocompatibility. Optical and magnetic resonance (MR) imaging probes were integrated by conjugating DOTA-gadolinium (Gd) derivative to quantum dot based nanomicelles. Two amphiphilic block copolymer micelles, amine-terminated mPEG-phospholipid and amine-modified Pluronic F127, were chosen as the capping agents because of their excellent biocompatibility and ability to prevent opsonization and prolong circulation time in vivo. Owing to their different hydrophobic-hydrophilic structure, the micellar aggregates exhibited different sizes and protection of core QDs. This work revealed the differences between these nanomicelles in terms of the stability over a wide range of pH, along with their cytotoxicity and the capacity for chelating gadolinium, thus providing a useful guideline for tailor-making multimodal nanoparticles for specific biomedical applications.

  9. Single-pulse CARS based multimodal nonlinear optical microscope for bioimaging.

    PubMed

    Kumar, Sunil; Kamali, Tschackad; Levitte, Jonathan M; Katz, Ori; Hermann, Boris; Werkmeister, Rene; Považay, Boris; Drexler, Wolfgang; Unterhuber, Angelika; Silberberg, Yaron

    2015-05-18

    Noninvasive label-free imaging of biological systems raises demand not only for high-speed three-dimensional prescreening of morphology over a wide-field of view but also it seeks to extract the microscopic functional and molecular details within. Capitalizing on the unique advantages brought out by different nonlinear optical effects, a multimodal nonlinear optical microscope can be a powerful tool for bioimaging. Bringing together the intensity-dependent contrast mechanisms via second harmonic generation, third harmonic generation and four-wave mixing for structural-sensitive imaging, and single-beam/single-pulse coherent anti-Stokes Raman scattering technique for chemical sensitive imaging in the finger-print region, we have developed a simple and nearly alignment-free multimodal nonlinear optical microscope that is based on a single wide-band Ti:Sapphire femtosecond pulse laser source. Successful imaging tests have been realized on two exemplary biological samples, a canine femur bone and collagen fibrils harvested from a rat tail. Since the ultra-broad band-width femtosecond laser is a suitable source for performing high-resolution optical coherence tomography, a wide-field optical coherence tomography arm can be easily incorporated into the presented multimodal microscope making it a versatile optical imaging tool for noninvasive label-free bioimaging.

  10. Multimodal biometric authentication based on the fusion of finger vein and finger geometry

    NASA Astrophysics Data System (ADS)

    Kang, Byung Jun; Park, Kang Ryoung

    2009-09-01

    We propose a new multimodal biometric recognition based on the fusion of finger vein and finger geometry. This research shows three novelties compared to previous works. First, this is the first approach to combine the finger vein and finger geometry information at the same time. Second, the proposed method includes a new finger geometry recognition based on the sequential deviation values of finger thickness extracted from a single finger. Third, we integrate finger vein and finger geometry by a score-level fusion method based on a support vector machine. Results show that recognition accuracy is significantly enhanced using the proposed method.

  11. Incorporating a measure of local scale in voxel-based 3-D image registration.

    PubMed

    Nyúl, László G; Udupa, Jayaram K; Saha, Punam K

    2003-02-01

    We present a new class of approaches for rigid-body registration and their evaluation in studying multiple sclerosis (MS) via multiprotocol magnetic resonance imaging (MRI). Three pairs of rigid-body registration algorithms were implemented, using cross-correlation and mutual information (MI), operating on original gray-level images, and utilizing the intermediate images resulting from our new scale-based method. In the scale image, every voxel has the local "scale" value assigned to it, defined as the radius of the largest ball centered at the voxel with homogeneous intensities. Three-dimensional image data of the head were acquired from ten MS patients for each of six MRI protocols. Images in some of the protocols were acquired in registration. The registered pairs were used as ground truth. Accuracy and consistency of the six registration methods were measured within and between protocols for known amounts of misregistrations. Our analysis indicates that there is no "best" method. For medium misregistration, the method using MI, for small add large misregistration the method using normalized cross-correlation performs best. For high-resolution data the correlation method and for low-resolution data the MI method, both using the original gray-level images, are the most consistent. We have previously demonstrated the use of local scale information in fuzzy connectedness segmentation and image filtering. Scale may also have potential for image registration as suggested by this work.

  12. Augmented reality based on fast deformable 2D-3D registration for image-guided surgery

    NASA Astrophysics Data System (ADS)

    Scheuering, Michael; Rezk-Salama, Christof; Barfufl, Helmut; Schneider, Armin; Greiner, Guenther

    2002-05-01

    Augmented reality systems (ARS) allow the transparent projection of preoperative CT images onto the physicians view. A significant problem in this context is the registration between the patient and the tomographic images, especially in the case of soft tissue deformation. The basis of our ARS is a volume rendering component on standard PC platform, which allows interactive volumetric deformation as a supplement to the 3D-texture based approaches. The volume is adaptively subdivided into a hierarchy of sub-cubes, each of which is deformed linearly. In order to approximate the Phong illumination model, our system allows pre-calculated gradients to be deformed efficiently. The registration is realized by the introduction of a two-stage procedure. Firstly, we compute a rigid pre-registration by the use of fiducial markers in combination with an electromagnetic navigation system. The second step accounts for the nonlinear deformation. For this purpose, several views of an object are captured and compared with its corresponding synthetic renderings in an optimization method using mutual information as metric. Throughout the experiments with our approach, several tests of the rigid registration has been carried out in a real laparoscopic intervention setup as a supplement to the actual clinical routine. In order to evaluate the nonlinear part of the registration, up until now several dummy objects (synthetically deformed datasets) have been successfully examined.

  13. Tensor-based morphometry with stationary velocity field diffeomorphic registration: Application to ADNI

    PubMed Central

    Bossa, Matias; Zacur, Ernesto; Olmos, Salvador

    2010-01-01

    Tensor-based morphometry (TBM) is an analysis technique where anatomical information is characterized by means of the spatial transformations mapping a customized template with the observed images. Therefore, accurate inter-subject non-rigid registration is an essential prerequisite for both template estimation and image warping. Subsequent statistical analysis on the spatial transformations is performed to highlight voxel-wise differences. Most of previous TBM studies did not explore the influence of the registration parameters, such as the parameters defining the deformation and the regularization models. In this work performance evaluation of TBM using stationary velocity field (SVF) diffeomorphic registration was performed in a subset of subjects from Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. A wide range of values of the registration parameters that define the transformation smoothness and the balance between image matching and regularization were explored in the evaluation. The proposed methodology provided brain atrophy maps with very detailed anatomical resolution and with a high significance level compared with results recently published on the same data set using a non-linear elastic registration method. PMID:20211269

  14. Feature-based US to CT registration of the aortic root

    NASA Astrophysics Data System (ADS)

    Lang, Pencilla; Chen, Elvis C. S.; Guiraudon, Gerard M.; Jones, Doug L.; Bainbridge, Daniel; Chu, Michael W.; Drangova, Maria; Hata, Noby; Jain, Ameet; Peters, Terry M.

    2011-03-01

    A feature-based registration was developed to align biplane and tracked ultrasound images of the aortic root with a preoperative CT volume. In transcatheter aortic valve replacement, a prosthetic valve is inserted into the aortic annulus via a catheter. Poor anatomical visualization of the aortic root region can result in incorrect positioning, leading to significant morbidity and mortality. Registration of pre-operative CT to transesophageal ultrasound and fluoroscopy images is a major step towards providing augmented image guidance for this procedure. The proposed registration approach uses an iterative closest point algorithm to register a surface mesh generated from CT to 3D US points reconstructed from a single biplane US acquisition, or multiple tracked US images. The use of a single simultaneous acquisition biplane image eliminates reconstruction error introduced by cardiac gating and TEE probe tracking, creating potential for real-time intra-operative registration. A simple initialization procedure is used to minimize changes to operating room workflow. The algorithm is tested on images acquired from excised porcine hearts. Results demonstrate a clinically acceptable accuracy of 2.6mm and 5mm for tracked US to CT and biplane US to CT registration respectively.

  15. Geometry-aware multiscale image registration via OBBTree-based polyaffine log-demons.

    PubMed

    Seiler, Christof; Pennec, Xavier; Reyes, Mauricio

    2011-01-01

    Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.

  16. A Rigid Image Registration Based on the Nonsubsampled Contourlet Transform and Genetic Algorithms

    PubMed Central

    Meskine, Fatiha; Chikr El Mezouar, Miloud; Taleb, Nasreddine

    2010-01-01

    Image registration is a fundamental task used in image processing to match two or more images taken at different times, from different sensors or from different viewpoints. The objective is to find in a huge search space of geometric transformations, an acceptable accurate solution in a reasonable time to provide better registered images. Exhaustive search is computationally expensive and the computational cost increases exponentially with the number of transformation parameters and the size of the data set. In this work, we present an efficient image registration algorithm that uses genetic algorithms within a multi-resolution framework based on the Non-Subsampled Contourlet Transform (NSCT). An adaptable genetic algorithm for registration is adopted in order to minimize the search space. This approach is used within a hybrid scheme applying the two techniques fitness sharing and elitism. Two NSCT based methods are proposed for registration. A comparative study is established between these methods and a wavelet based one. Because the NSCT is a shift-invariant multidirectional transform, the second method is adopted for its search speeding up property. Simulation results clearly show that both proposed techniques are really promising methods for image registration compared to the wavelet approach, while the second technique has led to the best performance results of all. Moreover, to demonstrate the effectiveness of these methods, these registration techniques have been successfully applied to register SPOT, IKONOS and Synthetic Aperture Radar (SAR) images. The algorithm has been shown to work perfectly well for multi-temporal satellite images as well, even in the presence of noise. PMID:22163672

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  18. Correspondenceless 3D-2D registration based on expectation conditional maximization

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

    3D-2D registration is a fundamental task in image guided interventions. Due to the physics of the X-ray imaging, however, traditional point based methods meet new challenges, where the local point features are indistinguishable, creating difficulties in establishing correspondence between 2D image feature points and 3D model points. In this paper, we propose a novel method to accomplish 3D-2D registration without known correspondences. Given a set of 3D and 2D unmatched points, this is achieved by introducing correspondence probabilities that we model as a mixture model. By casting it into the expectation conditional maximization framework, without establishing one-to-one point correspondences, we can iteratively refine the registration parameters. The method has been tested on 100 real X-ray images. The experiments showed that the proposed method accurately estimated the rotations (< 1°) and in-plane (X-Y plane) translations (< 1 mm).

  19. Indoor Scene Point Cloud Registration Algorithm Based on RGB-D Camera Calibration

    PubMed Central

    Huang, Chih-Hung

    2017-01-01

    With the increasing popularity of RGB-depth (RGB-D) sensor, research on the use of RGB-D sensors to reconstruct three-dimensional (3D) indoor scenes has gained more and more attention. In this paper, an automatic point cloud registration algorithm is proposed to efficiently handle the task of 3D indoor scene reconstruction using pan-tilt platforms on a fixed position. The proposed algorithm aims to align multiple point clouds using extrinsic parameters of the RGB-D camera obtained from every preset pan-tilt control point. A computationally efficient global registration method is proposed based on transformation matrices formed by the offline calibrated extrinsic parameters. Then, a local registration method, which is an optional operation in the proposed algorithm, is employed to refine the preliminary alignment result. Experimental results validate the quality and computational efficiency of the proposed point cloud alignment algorithm by comparing it with two state-of-the-art methods. PMID:28809787

  20. 3D point cloud registration based on the assistant camera and Harris-SIFT

    NASA Astrophysics Data System (ADS)

    Zhang, Yue; Yu, HongYang

    2016-07-01

    3D(Three-Dimensional) point cloud registration technology is the hot topic in the field of 3D reconstruction, but most of the registration method is not real-time and ineffective. This paper proposes a point cloud registration method of 3D reconstruction based on Harris-SIFT and assistant camera. The assistant camera is used to pinpoint mobile 3D reconstruction device, The feature points of images are detected by using Harris operator, the main orientation for each feature point is calculated, and lastly, the feature point descriptors are generated after rotating the coordinates of the descriptors relative to the feature points' main orientations. Experimental results of demonstrate the effectiveness of the proposed method.

  1. High-Precision Registration of Point Clouds Based on Sphere Feature Constraints.

    PubMed

    Huang, Junhui; Wang, Zhao; Gao, Jianmin; Huang, Youping; Towers, David Peter

    2016-12-30

    Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method.

  2. High-Precision Registration of Point Clouds Based on Sphere Feature Constraints

    PubMed Central

    Huang, Junhui; Wang, Zhao; Gao, Jianmin; Huang, Youping; Towers, David Peter

    2016-01-01

    Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method. PMID:28042846

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

    PubMed

    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.

  4. Global image registration using a symmetric block-matching approach.

    PubMed

    Modat, Marc; Cash, David M; Daga, Pankaj; Winston, Gavin P; Duncan, John S; Ourselin, Sébastien

    2014-07-01

    Most medical image registration algorithms suffer from a directionality bias that has been shown to largely impact subsequent analyses. Several approaches have been proposed in the literature to address this bias in the context of nonlinear registration, but little work has been done for global registration. We propose a symmetric approach based on a block-matching technique and least-trimmed square regression. The proposed method is suitable for multimodal registration and is robust to outliers in the input images. The symmetric framework is compared with the original asymmetric block-matching technique and is shown to outperform it in terms of accuracy and robustness. The methodology presented in this article has been made available to the community as part of the NiftyReg open-source package.

  5. Accelerated gradient-based free form deformable registration for online adaptive radiotherapy.

    PubMed

    Yu, Gang; Liang, Yueqiang; Yang, Guanyu; Shu, Huazhong; Li, Baosheng; Yin, Yong; Li, Dengwang

    2015-04-07

    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.

  6. Accelerated gradient-based free form deformable registration for online adaptive radiotherapy

    NASA Astrophysics Data System (ADS)

    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.

  7. Feature based nonrigid brain MR image registration with symmetric alpha stable filters.

    PubMed

    Liao, Shu; Chung, Albert C S

    2010-01-01

    A new feature based nonrigid image registration method for magnetic resonance (MR) brain images is presented in this paper. Each image voxel is represented by a rotation invariant feature vector, which is computed by passing the input image volumes through a new bank of symmetric alpha stable (SalphaS) filters. There are three main contributions presented in this paper. First, this work is motivated by the fact that the frequency spectrums of the brain MR images often exhibit non-Gaussian heavy-tail behavior which cannot be satisfactorily modeled by the conventional Gabor filters. To this end, we propose the use of SalphaS filters to model such behavior and show that the Gabor filter is a special case of the SalphaS filter. Second, the maximum response orientation (MRO) selection criterion is designed to extract rotation invariant features for registration tasks. The MRO selection criterion also significantly reduces the number of dimensions of feature vectors and therefore lowers the computation time. Third, in case the segmentations of the input image volumes are available, the Fisher's separation criterion (FSC) is introduced such that the discriminating power of different feature types can be directly compared with each other before performing the registration process. Using FSC, weights can also be assigned automatically to different voxels in the brain MR images. The weight of each voxel determined by FSC reflects how distinctive and salient the voxel is. Using the most distinctive and salient voxels at the initial stage to drive the registration can reduce the risk of being trapped in the local optimum during image registration process. The larger the weight, the more important the voxel. With the extracted feature vectors and the associated weights, the proposed method registers the source and the target images in a hierarchical multiresolution manner. The proposed method has been intensively evaluated on both simulated and real 3-D datasets obtained from

  8. 75 FR 77305 - Security-Based Swap Data Repository Registration, Duties, and Core Principles

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-10

    ...In accordance with Section 763(i) of Title VII (``Title VII'') of the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010 (``Dodd-Frank Act''), the Securities and Exchange Commission (``Commission'') is proposing new rules under the Securities Exchange Act of 1934 (``Exchange Act'') governing the security-based swap data repository (``SDR'') registration process, duties, and core......

  9. 46 CFR 515.19 - Registration of foreign-based unlicensed NVOCC.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 46 Shipping 9 2014-10-01 2014-10-01 false Registration of foreign-based unlicensed NVOCC. 515.19 Section 515.19 Shipping FEDERAL MARITIME COMMISSION REGULATIONS AFFECTING OCEAN SHIPPING IN FOREIGN...) Knowingly and willfully processing, booking, or accepting cargo from, or transporting cargo for the account...

  10. 46 CFR 515.19 - Registration of foreign-based unlicensed NVOCC.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 46 Shipping 9 2013-10-01 2013-10-01 false Registration of foreign-based unlicensed NVOCC. 515.19 Section 515.19 Shipping FEDERAL MARITIME COMMISSION REGULATIONS AFFECTING OCEAN SHIPPING IN FOREIGN...) Knowingly and willfully processing, booking, or accepting cargo from, or transporting cargo for the account...

  11. 75 FR 79320 - Security-Based Swap Data Repository Registration, Duties, and Core Principles

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-20

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION 17 CFR Parts 240 and 249 RIN 3235-AK79 Security-Based Swap Data Repository Registration, Duties, and Core Principles Correction In proposed rule document 2010-29719 beginning on page 77306 in...

  12. 76 FR 2287 - Security-Based Swap Data Repository Registration, Duties, and Core Principles; Correction

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-01-13

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION 17 CFR Parts 240 and 249 RIN 3235-AK79 Security-Based Swap Data Repository Registration, Duties, and Core Principles; Correction Correction In proposed rule document C1-2010-29719 beginning on...

  13. Computational method for multi-modal microscopy based on transport of intensity equation

    NASA Astrophysics Data System (ADS)

    Li, Jiaji; Chen, Qian; Sun, Jiasong; Zhang, Jialin; Zuo, Chao

    2017-02-01

    In this paper, we develop the requisite theory to describe a hybrid virtual-physical multi-modal imaging system which yields quantitative phase, Zernike phase contrast, differential interference contrast (DIC), and light field moment imaging simultaneously based on transport of intensity equation(TIE). We then give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens based TIE system, combined with the appropriate post-processing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

  14. Nonunity permeability in metamaterial-based GaInAsP/InP multimode interferometers.

    PubMed

    Amemiya, T; Shindo, T; Takahashi, D; Myoga, S; Nishiyama, N; Arai, S

    2011-06-15

    We demonstrated an InP-based optical multimode interferometer (MMI) combined with metamaterials consisting of minute split-ring resonators (SRRs) arrayed on the MMI. The MMI could operate at an optical fiber communication wavelength of 1.5 μm. Magnetic resonance occurred between the SRR metamaterial and light at 1.5 μm, and the relative permeability of the metamaterial increased to 2.4 around this wavelength. This result shows that it is possible to use new materials with nonunity permeability to construct semiconductor-based photonic devices.

  15. Automatic sub-volume registration by probabilistic random search

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  16. Image Quality Improvement in Adaptive Optics Scanning Laser Ophthalmoscopy Assisted Capillary Visualization Using B-spline-based Elastic Image Registration

    PubMed Central

    Uji, Akihito; Ooto, Sotaro; Hangai, Masanori; Arichika, Shigeta; Yoshimura, Nagahisa

    2013-01-01

    Purpose To investigate the effect of B-spline-based elastic image registration on adaptive optics scanning laser ophthalmoscopy (AO-SLO)-assisted capillary visualization. Methods AO-SLO videos were acquired from parafoveal areas in the eyes of healthy subjects and patients with various diseases. After nonlinear image registration, the image quality of capillary images constructed from AO-SLO videos using motion contrast enhancement was compared before and after B-spline-based elastic (nonlinear) image registration performed using ImageJ. For objective comparison of image quality, contrast-to-noise ratios (CNRS) for vessel images were calculated. For subjective comparison, experienced ophthalmologists ranked images on a 5-point scale. Results All AO-SLO videos were successfully stabilized by elastic image registration. CNR was significantly higher in capillary images stabilized by elastic image registration than in those stabilized without registration. The average ratio of CNR in images with elastic image registration to CNR in images without elastic image registration was 2.10 ± 1.73, with no significant difference in the ratio between patients and healthy subjects. Improvement of image quality was also supported by expert comparison. Conclusions Use of B-spline-based elastic image registration in AO-SLO-assisted capillary visualization was effective for enhancing image quality both objectively and subjectively. PMID:24265796

  17. Biomechanical-based image registration for head and neck radiation treatment

    NASA Astrophysics Data System (ADS)

    Al-Mayah, Adil; Moseley, Joanne; Hunter, Shannon; Velec, Mike; Chau, Lily; Breen, Stephen; Brock, Kristy

    2010-11-01

    Deformable image registration of four head and neck cancer patients has been conducted using a biomechanical-based model. Patient-specific 3D finite element models have been developed using CT and cone-beam CT image data of the planning and a radiation treatment session. The model consists of seven vertebrae (C1 to C7), mandible, larynx, left and right parotid glands, tumor and body. Different combinations of boundary conditions are applied in the model in order to find the configuration with a minimum registration error. Each vertebra in the planning session is individually aligned with its correspondence in the treatment session. Rigid alignment is used for each individual vertebra and the mandible since no deformation is expected in the bones. In addition, the effect of morphological differences in the external body between the two image sessions is investigated. The accuracy of the registration is evaluated using the tumor and both parotid glands by comparing the calculated Dice similarity index of these structures following deformation in relation to their true surface defined in the image of the second session. The registration is improved when the vertebrae and mandible are aligned in the two sessions with the highest average Dice index of 0.86 ± 0.08, 0.84 ± 0.11 and 0.89 ± 0.04 for the tumor, left and right parotid glands, respectively. The accuracy of the center of mass location of tumor and parotid glands is also improved by deformable image registration where the errors in the tumor and parotid glands decrease from 4.0 ± 1.1, 3.4 ± 1.5 and 3.8 ± 0.9 mm using rigid registration to 2.3 ± 1.0, 2.5 ± 0.8 and 2.0 ± 0.9 mm in the deformable image registration when alignment of vertebrae and mandible is conducted in addition to the surface projection of the body. This work was presented at the SPIE conference, California, 2010: Al-Mayah A, Moseley J, Chau L, Breen S, and Brock K 2010 Biomechanical based deformable image registration of head and neck

  18. Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping

    PubMed Central

    Cui, Tingting; Ji, Shunping; Shan, Jie; Gong, Jianya; Liu, Kejian

    2016-01-01

    For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable. PMID:28042855

  19. Three-dimensional B-spline-based intersubject nonrigid registration with geodesic closest points constraints

    NASA Astrophysics Data System (ADS)

    Zhang, Zhijun; Liu, Feng; Deng, Fuqin; Tsui, Hungtat

    2014-11-01

    Due to the variance between subjects, there is usually ambiguity in intensity-based intersubject registration. The topological constraint in the brain cortical surface might be violated because of the highly convolved nature of the human cortical cortex. We propose an intersubject brain registration method by combining the intensity and the geodesic closest point-based similarity measurements. Each of the brain hemispheres can be topologically equal to a sphere and a one-to-one mapping of the points on the spherical surfaces of the two subjects can be achieved. The correspondences in the cortical surface are obtained by searching the geodesic closest points in the spherical surface. The corresponding features on the cortical surfaces between subjects are then used as anatomical landmarks for intersubject registration. By adding these anatomical constraints of the cortical surfaces, the intersubject registration results are more anatomically plausible and accurate. We validate our method by using real human datasets. Experimental results in visual inspection and alignment error show that the proposed method performs better than the typical joint intensity- and landmark-distance-based methods.

  20. Fiber feature map based landmark initialization for highly deformable DTI registration.

    PubMed

    Gupta, Aditya; Toews, Matthew; Janardhana, Ravikiran; Rathi, Yogesh; Gilmore, John; Escolar, Maria; Styner, Martin

    2013-03-13

    This paper presents a novel pipeline for the registration of diffusion tensor images (DTI) with large pathological variations to normal controls based on the use of a novel feature map derived from white matter (WM) fiber tracts. The research presented aims towards an atlas based DTI analysis of subjects with considerable brain pathologies such as tumors or hydrocephalus. In this paper, we propose a novel feature map that is robust against variations in WM fiber tract integrity and use these feature maps to determine a landmark correspondence using a 3D point correspondence algorithm. This correspondence drives a deformation field computed using Gaussian radial basis functions(RBF). This field is employed as an initialization to a standard deformable registration method like demons. We present early preliminary results on the registration of a normal control dataset to a dataset with abnormally enlarged lateral ventricles affected by fatal demyelinating Krabbe disease. The results are analyzed based on a regional tensor matching criterion and a visual assessment of overlap of major WM fiber tracts. While further evaluation and improvements are necessary, the results presented in this paper highlight the potential of our method in handling registration of subjects with severe WM pathology.

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

    NASA Astrophysics Data System (ADS)

    Samavati, Navid; Velec, Michael; Brock, Kristy

    2014-03-01

    Deformable Image Registration (DIR) has been extensively studied over the past two decades due to its essential role in many image-guided interventions. Morfeus is a DIR algorithm that works based on finite element biomechanical modeling. However, Morfeus does not utilize the entire image contrast and features which could potentially lead to a more accurate registration result. A hybrid biomechanical intensity-based method is proposed to investigate this potential benefit. Inhale and exhale 4DCT lung images of 26 patients were initially registered using Morfeus by modeling contact surface between the lungs and the chest cavity. The resulting deformations using Morfeus were refined using a B-spline intensity-based algorithm (Drop, Munich, Germany). Important parameters in Drop including grid spacing, number of pyramids, and regularization coefficient were optimized on 10 randomly-chosen patients (out of 26). The remaining parameters were selected empirically. Target Registration Error (TRE) was calculated by measuring the Euclidean distance of common anatomical points on both images before and after registration. For each patient a minimum of 30 points/lung were used. The Hybrid method resulted in mean+/-SD (90th%) TRE of 1.5+/-1.4 (2.8) mm compared to 3.1+/-2.0 (5.6) using Morfeus and 2.6+/-2.6 (6.2) using Drop alone.

  2. Feature-based three-dimensional registration for repetitive geometry in machine vision

    PubMed Central

    Gong, Yuanzheng; Seibel, Eric J.

    2016-01-01

    As an important step in three-dimensional (3D) machine vision, 3D registration is a process of aligning two or multiple 3D point clouds that are collected from different perspectives together into a complete one. The most popular approach to register point clouds is to minimize the difference between these point clouds iteratively by Iterative Closest Point (ICP) algorithm. However, ICP does not work well for repetitive geometries. To solve this problem, a feature-based 3D registration algorithm is proposed to align the point clouds that are generated by vision-based 3D reconstruction. By utilizing texture information of the object and the robustness of image features, 3D correspondences can be retrieved so that the 3D registration of two point clouds is to solve a rigid transformation. The comparison of our method and different ICP algorithms demonstrates that our proposed algorithm is more accurate, efficient and robust for repetitive geometry registration. Moreover, this method can also be used to solve high depth uncertainty problem caused by little camera baseline in vision-based 3D reconstruction.

  3. Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping.

    PubMed

    Cui, Tingting; Ji, Shunping; Shan, Jie; Gong, Jianya; Liu, Kejian

    2016-12-31

    For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.

  4. A graph-based approach for the retrieval of multi-modality medical images.

    PubMed

    Kumar, Ashnil; Kim, Jinman; Wen, Lingfeng; Fulham, Michael; Feng, Dagan

    2014-02-01

    In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging. The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours and organs. These attributes and relationships, which are used for tumour staging and classification, can be formulated as a graph. It has been demonstrated that graph-based methods have high accuracy for retrieval by spatial similarity. However, naïvely representing all relationships on a complete graph obscures the structure of the tumour-anatomy relationships. We propose a new graph structure derived from complete graphs that structurally constrains the edges connected to tumour vertices based upon the spatial proximity of tumours and organs. This enables retrieval on the basis of tumour localisation. We also present a similarity matching algorithm that accounts for different feature sets for graph elements from different imaging modalities. Our method emphasises the relationships between a tumour and related organs, while still modelling patient-specific anatomical variations. Constraining tumours to related anatomical structures improves the discrimination potential of graphs, making it easier to retrieve similar images based on tumour location. We evaluated our retrieval methodology on a dataset of clinical PET-CT volumes. Our results showed that our method enabled the retrieval of multi-modality images using spatial features. Our graph-based retrieval algorithm achieved a higher precision than several other retrieval techniques: gray-level histograms as well as state

  5. Gradient-based 3D-2D registration of cerebral angiograms

    NASA Astrophysics Data System (ADS)

    Mitrović, Uroš; Markelj, Primož; Likar, Boštjan; Miloševič, Zoran; Pernuš, Franjo

    2011-03-01

    Endovascular treatment of cerebral aneurysms and arteriovenous malformations (AVM) involves navigation of a catheter through the femoral artery and vascular system into the brain and into the aneurysm or AVM. Intra-interventional navigation utilizes digital subtraction angiography (DSA) to visualize vascular structures and X-ray fluoroscopy to localize the endovascular components. Due to the two-dimensional (2D) nature of the intra-interventional images, navigation through a complex three-dimensional (3D) structure is a demanding task. Registration of pre-interventional MRA, CTA, or 3D-DSA images and intra-interventional 2D DSA images can greatly enhance visualization and navigation. As a consequence of better navigation in 3D, the amount of required contrast medium and absorbed dose could be significantly reduced. In the past, development and evaluation of 3D-2D registration methods received considerable attention. Several validation image databases and evaluation criteria were created and made publicly available in the past. However, applications of 3D-2D registration methods to cerebral angiograms and their validation are rather scarce. In this paper, the 3D-2D robust gradient reconstruction-based (RGRB) registration algorithm is applied to CTA and DSA images and analyzed. For the evaluation purposes five image datasets, each comprised of a 3D CTA and several 2D DSA-like digitally reconstructed radiographs (DRRs) generated from the CTA, with accurate gold standard registrations were created. A total of 4000 registrations on these five datasets resulted in mean mTRE values between 0.07 and 0.59 mm, capture ranges between 6 and 11 mm and success rates between 61 and 88% using a failure threshold of 2 mm.

  6. MSM: a new flexible framework for Multimodal Surface Matching.

    PubMed

    Robinson, Emma C; Jbabdi, Saad; Glasser, Matthew F; Andersson, Jesper; Burgess, Gregory C; Harms, Michael P; Smith, Stephen M; Van Essen, David C; Jenkinson, Mark

    2014-10-15

    Surface-based cortical registration methods that are driven by geometrical features, such as folding, provide sub-optimal alignment of many functional areas due to variable correlation between cortical folding patterns and function. This has led to the proposal of new registration methods using features derived from functional and diffusion imaging. However, as yet there is no consensus over the best set of features for optimal alignment of brain function. In this paper we demonstrate the utility of a new Multimodal Surface Matching (MSM) algorithm capable of driving alignment using a wide variety of descriptors of brain architecture, function and connectivity. The versatility of the framework originates from adapting the discrete Markov Random Field (MRF) registration method to surface alignment. This has the benefit of being very flexible in the choice of a similarity measure and relatively insensitive to local minima. The method offers significant flexibility in the choice of feature set, and we demonstrate the advantages of this by performing registrations using univariate descriptors of surface curvature and myelination, multivariate feature sets derived from resting fMRI, and multimodal descriptors of surface curvature and myelination. We compare the results with two state of the art surface registration methods that use geometric features: FreeSurfer and Spherical Demons. In the future, the MSM technique will allow explorations into the best combinations of features and alignment strategies for inter-subject alignment of cortical functional areas for a wide range of neuroimaging data sets.

  7. A-mode ultrasound-based registration in computer-aided surgery of the skull.

    PubMed

    Amstutz, Christoph; Caversaccio, Marco; Kowal, Jens; Bächler, Richard; Nolte, Lutz-Peter; Häusler, Rudolf; Styner, Martin

    2003-12-01

    To evaluate the integration and accuracy of A (amplitude)-mode ultrasound-based surface matching for noninvasive registration of the head into a frameless computer-aided surgery system for otorhinology and skull base surgery. Experimental study and case series. Academic medical center. Twelve patients underwent anterior and paranasal skull base surgery with the routine use of a computer-aided surgery system. A computer-aided surgery system, based on an optoelectronic localizer, was used to track the skull and the surgical tools, including the A-mode ultrasound probe. The A-mode probe was a 10-MHz immersion transducer. An acoustic lens attached to the transducer focused the ultrasonic beam to a depth of 1 to 10 mm. Accuracy tests were performed for the ultrasound setup. Different surface point distributions were evaluated with respect to matching accuracy on a human cadaver skull specimen equipped with fiducial markers. The matching comparison was based on the fiducial registration error. For the clinical evaluation, the laboratory setup was transferred to the operating room. Noninvasive registration of the skull by using A-mode ultrasound in computer-aided surgery (practical and clinical measurements). The accuracy tests on the human skull specimen revealed that the mean +/- SD fiducial registration error was 1.00 +/- 0.19 mm in the best series for A-mode ultrasound surface matchings and was robust with respect to different sets of surface points. The mean +/- SD root mean square error from the 12 A-mode ultrasound matchings in the patient study was 0.49 +/- 0.20 mm. A-mode ultrasound surface matching can be used as a noninvasive and accurate registration procedure in computer-aided surgery of the head.

  8. Multimodality therapy for locoregional extrahepatic cholangiocarcinoma: a population based analysis

    PubMed Central

    Fuller, Clifton D.; Wang, Samuel J.; Choi, Mehee; Czito, Brian G.; Cornell, John; Welzel, Tania M.; McGlynn, Katherine A.; Luh, Join Y.; Thomas, Charles R.

    2009-01-01

    Introduction: While surgical resection is the mainstay of treatment for extrahepatic cholangiocarcinoma (EHCC), most patients present with advanced disease. Owing in part to numerical rarity, the optimum role of radiotherapy (RT) for EHCC, as well as its relative benefit is an area of debate. The specific aim of this series is to estimate survival for EHCC patients receiving surgery and adjuvant RT using a robust population based dataset. Methods: Data was extracted from the Surveillance, Epidemiology, and End Results (SEER) limited-use dataset for selected EHCC cases. Lognormal multivariate survival analysis was implemented to estimate survival for patients for treatment cohorts based on extent of surgical intervention and RT. Results: Parametric estimated median survival for patients receiving total/radical resection+RT was 26 months, 25 months for total/radical resection alone, 25 months for subtotal/debulking resection+RT, 21 months for subtotal/debulking resection, 12 months for RT alone, and 9 months for those not receiving surgery or RT. Parametric multivariate analysis revealed age, AJCC Stage, grade, and surgical/radiation regimen as statistically significant covariates with survival. Surgery-alone and adjuvant radiotherapy cohorts showed evidence of improved survival compared to no treatment; comparatively, radiation alone was associated with survival decrement. Early improvement in survival in adjuvant cohorts was not observed at later time-points. Conclusions: Survival estimates using SEER data suggest an early survival advantage for adjuvant radiotherapy for locoregional EHCC. While future prospective series are needed to confirm these observations, SEER data represents the largest domestic population-based EHCC cohort, and may provide useful baseline survival estimates for future studies. PMID:19637356

  9. A cloud-based multimodality case file for mobile devices.

    PubMed

    Balkman, Jason D; Loehfelm, Thomas W

    2014-01-01

    Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. ©RSNA, 2014.

  10. A local descriptor based registration method for multispectral remote sensing images with non-linear intensity differences

    NASA Astrophysics Data System (ADS)

    Ye, Yuanxin; Shan, Jie

    2014-04-01

    Image registration is a crucial step for remote sensing image processing. Automatic registration of multispectral remote sensing images could be challenging due to the significant non-linear intensity differences caused by radiometric variations among such images. To address this problem, this paper proposes a local descriptor based registration method for multispectral remote sensing images. The proposed method includes a two-stage process: pre-registration and fine registration. The pre-registration is achieved using the Scale Restriction Scale Invariant Feature Transform (SR-SIFT) to eliminate the obvious translation, rotation, and scale differences between the reference and the sensed image. In the fine registration stage, the evenly distributed interest points are first extracted in the pre-registered image using the Harris corner detector. Then, we integrate the local self-similarity (LSS) descriptor as a new similarity metric to detect the tie points between the reference and the pre-registered image, followed by a global consistency check to remove matching blunders. Finally, image registration is achieved using a piecewise linear transform. The proposed method has been evaluated with three pairs of multispectral remote sensing images from TM, ETM+, ASTER, Worldview, and Quickbird sensors. The experimental results demonstrate that the proposed method can achieve reliable registration outcome, and the LSS-based similarity metric is robust to non-linear intensity differences among multispectral remote sensing images.

  11. MRI signal intensity based B-spline nonrigid registration for pre- and intraoperative imaging during prostate brachytherapy.

    PubMed

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

    2009-11-01

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

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

    PubMed Central

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

    2009-01-01

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

  13. Evaluation of an Automatic Registration-Based Algorithm for Direct Measurement of Volume Change in Tumors

    SciTech Connect

    Sarkar, Saradwata; Johnson, Timothy D.; Ma, Bing; Chenevert, Thomas L.; Bland, Peyton H.; Park, Hyunjin; Schott, Anne F.; Ross, Brian D.; Meyer, Charles R.

    2012-07-01

    Purpose: Assuming that early tumor volume change is a biomarker for response to therapy, accurate quantification of early volume changes could aid in adapting an individual patient's therapy and lead to shorter clinical trials. We investigated an image registration-based approach for tumor volume change quantification that may more reliably detect smaller changes that occur in shorter intervals than can be detected by existing algorithms. Methods and Materials: Variance and bias of the registration-based approach were evaluated using retrospective, in vivo, very-short-interval diffusion magnetic resonance imaging scans where true zero tumor volume change is unequivocally known and synthetic data, respectively. The interval scans were nonlinearly registered using two similarity measures: mutual information (MI) and normalized cross-correlation (NCC). Results: The 95% confidence interval of the percentage volume change error was (-8.93% to 10.49%) for MI-based and (-7.69%, 8.83%) for NCC-based registrations. Linear mixed-effects models demonstrated that error in measuring volume change increased with increase in tumor volume and decreased with the increase in the tumor's normalized mutual information, even when NCC was the similarity measure being optimized during registration. The 95% confidence interval of the relative volume change error for the synthetic examinations with known changes over {+-}80% of reference tumor volume was (-3.02% to 3.86%). Statistically significant bias was not demonstrated. Conclusion: A low-noise, low-bias tumor volume change measurement algorithm using nonlinear registration is described. Errors in change measurement were a function of tumor volume and the normalized mutual information content of the tumor.

  14. Performance study of silica-on-silicon based multimode interference (MMI) optical coupler

    NASA Astrophysics Data System (ADS)

    Chowdhury, A. Zahed

    2014-03-01

    In recent years, the silica-on-silicon based multimode interference (MMI) optical waveguide is an interesting research topic. It is being advanced various researches on the silica based MMI coupler. This paper represents the considerations of the optimal design of the silica-on-silicon based MMI optical coupler for better performance. For that, we have illustrated the simulation results on a particular case of the 4×4 silica-on-silicon based MMI coupler. From the simulation results, it is seen that the performance of the MMI coupler depends on multiple width and length combinations of the MMI waveguide. The results also show that the width of the multimode waveguide could not be too small or too large for optimal performance, and at the widths, 100 μm, 120 μm and 130 μm, the performance could be optimized and be almost 0.62-0.64 in a given length range. Finally, the results have been compared with the optical coupler presently available in the market and show that the silica-on-silicon based MMI coupler is much more efficient in terms of losses and the performance associated with it and the size of the coupler.

  15. Multimodality Imaging with Silica-Based Targeted Nanoparticle Platforms

    SciTech Connect

    Jason S. Lewis

    2012-04-09

    Objectives: To synthesize and characterize a C-Dot silica-based nanoparticle containing 'clickable' groups for the subsequent attachment of targeting moieties (e.g., peptides) and multiple contrast agents (e.g., radionuclides with high specific activity) [1,2]. These new constructs will be tested in suitable tumor models in vitro and in vivo to ensure maintenance of target-specificity and high specific activity. Methods: Cy5 dye molecules are cross-linked to a silica precursor which is reacted to form a dye-rich core particle. This core is then encapsulated in a layer of pure silica to create the core-shell C-Dot (Figure 1) [2]. A 'click' chemistry approach has been used to functionalize the silica shell with radionuclides conferring high contrast and specific activity (e.g. 64Cu and 89Zr) and peptides for tumor targeting (e.g. cRGD and octreotate) [3]. Based on the selective Diels-Alder reaction between tetrazine and norbornene, the reaction is bioorthogonal, highyielding, rapid, and water-compatible. This radiolabeling approach has already been employed successfully with both short peptides (e.g. octreotate) and antibodies (e.g. trastuzumab) as model systems for the ultimate labeling of the nanoparticles [1]. Results: PEGylated C-Dots with a Cy5 core and labeled with tetrazine have been synthesized (d = 55 nm, zeta potential = -3 mV) reliably and reproducibly and have been shown to be stable under physiological conditions for up to 1 month. Characterization of the nanoparticles revealed that the immobilized Cy5 dye within the C-Dots exhibited fluorescence intensities over twice that of the fluorophore alone. The nanoparticles were successfully radiolabeled with Cu-64. Efforts toward the conjugation of targeting peptides (e.g. cRGD) are underway. In vitro stability, specificity, and uptake studies as well as in vivo imaging and biodistribution investigations will be presented. Conclusions: C-Dot silica-based nanoparticles offer a robust, versatile, and multi

  16. A scale space feature based registration technique for fusion of satellite imagery

    NASA Technical Reports Server (NTRS)

    Raghavan, Srini; Cromp, Robert F.; Campbell, William C.

    1997-01-01

    Feature based registration is one of the most reliable methods to register multi-sensor images (both active and passive imagery) since features are often more reliable than intensity or radiometric values. The only situation where a feature based approach will fail is when the scene is completely homogenous or densely textural in which case a combination of feature and intensity based methods may yield better results. In this paper, we present some preliminary results of testing our scale space feature based registration technique, a modified version of feature based method developed earlier for classification of multi-sensor imagery. The proposed approach removes the sensitivity in parameter selection experienced in the earlier version as explained later.

  17. Sequential Registration-Based Segmentation of the Prostate Gland in MR Image Volumes.

    PubMed

    Khalvati, Farzad; Salmanpour, Aryan; Rahnamayan, Shahryar; Haider, Masoom A; Tizhoosh, H R

    2016-04-01

    Accurate and fast segmentation and volume estimation of the prostate gland in magnetic resonance (MR) images are necessary steps in the diagnosis, treatment, and monitoring of prostate cancer. This paper presents an algorithm for the prostate gland volume estimation based on the semi-automated segmentation of individual slices in T2-weighted MR image sequences. The proposed sequential registration-based segmentation (SRS) algorithm, which was inspired by the clinical workflow during medical image contouring, relies on inter-slice image registration and user interaction/correction to segment the prostate gland without the use of an anatomical atlas. It automatically generates contours for each slice using a registration algorithm, provided that the user edits and approves the marking in some previous slices. We conducted comprehensive experiments to measure the performance of the proposed algorithm using three registration methods (i.e., rigid, affine, and nonrigid). Five radiation oncologists participated in the study where they contoured the prostate MR (T2-weighted) images of 15 patients both manually and using the SRS algorithm. Compared to the manual segmentation, on average, the SRS algorithm reduced the contouring time by 62% (a speedup factor of 2.64×) while maintaining the segmentation accuracy at the same level as the intra-user agreement level (i.e., Dice similarity coefficient of 91 versus 90%). The proposed algorithm exploits the inter-slice similarity of volumetric MR image series to achieve highly accurate results while significantly reducing the contouring time.

  18. Evaluation of similarity measures for reconstruction-based registration in image-guided radiotherapy and surgery

    SciTech Connect

    Skerl, Darko . E-mail: franjo.pernus@fe.uni-lj.si; Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo

    2006-07-01

    Purpose: A promising patient positioning technique is based on registering computed tomographic (CT) or magnetic resonance (MR) images to cone-beam CT images (CBCT). The extra radiation dose delivered to the patient can be substantially reduced by using fewer projections. This approach results in lower quality CBCT images. The purpose of this study is to evaluate a number of similarity measures (SMs) suitable for registration of CT or MR images to low-quality CBCTs. Methods and Materials: Using the recently proposed evaluation protocol, we evaluated nine SMs with respect to pretreatment imaging modalities, number of two-dimensional (2D) images used for reconstruction, and number of reconstruction iterations. The image database consisted of 100 X-ray and corresponding CT and MR images of two vertebral columns. Results: Using a higher number of 2D projections or reconstruction iterations results in higher accuracy and slightly lower robustness. The similarity measures that behaved the best also yielded the best registration results. The most appropriate similarity measure was the asymmetric multi-feature mutual information (AMMI). Conclusions: The evaluation protocol proved to be a valuable tool for selecting the best similarity measure for the reconstruction-based registration. The results indicate that accurate and robust CT/CBCT or even MR/CBCT registrations are possible if the AMMI similarity measure is used.

  19. Coil compaction and aneurysm growth: image-based quantification using non-rigid registration

    NASA Astrophysics Data System (ADS)

    De Craene, Mathieu; Pozo, José María; Villa, Maria Cruz; Vivas, Elio; Sola, Teresa; Guimaraens, Leopoldo; Blasco, Jordi; Macho, Juan; Frangi, Alejandro

    2008-03-01

    Endovascular treatment of intracranial aneurysms is a minimally-invasive technique recognized as a valid alternative to surgical clipping. However, endovascular treatment can be associated to aneurysm recurrence, either due to coil compaction or aneurysm growth. The quantification of coil compaction or aneurysm growth is usually performed by manual measurements or visual inspection of images from consecutive follow-ups. Manual measurements permit to detect large global deformation but might have insufficient accuracy for detecting subtle or more local changes between images. Image inspection permits to detect a residual neck in the aneurysm but do not differentiate aneurysm growth from coil compaction. In this paper, we propose to quantify independently coil compaction and aneurysm growth using non-rigid image registration. Local changes of volume between images at successive time points are identified using the Jacobian of the non-rigid transformation. Two different non-rigid registration strategies are applied in order to explore the sensitivity of Jacobian-based volume changes against the registration method, FFD registration based on mutual information and Demons. This volume-variation measure has been applied to four patients of which a series of 3D Rotational Angiography (3DRA) images obtained at different controls separated from two months to two years were available. The evolution of coil and aneurysm volumes along the period has been obtained separately, which allows distinguishing between coil compaction and aneurysm growth. On the four cases studied in this paper, aneurysm recurrence was always associated to aneurysm growth, as opposed to strict coil compaction.

  20. Widely tunable erbium-doped fiber laser based on multimode interference effect.

    PubMed

    Castillo-Guzman, A; Antonio-Lopez, J E; Selvas-Aguilar, R; May-Arrioja, D A; Estudillo-Ayala, J; LiKamWa, P

    2010-01-18

    A widely tunable erbium-doped all-fiber laser has been demonstrated. The tunable mechanism is based on a novel tunable filter using multimode interference effects (MMI). The tunable MMI filter was applied to fabricate a tunable erbium-doped fiber laser via a standard ring cavity. A tuning range of 60 nm was obtained, ranging from 1549 nm to 1609 nm, with a signal to noise ratio of 40 dB. The tunable MMI filter mechanism is very simple and inexpensive, but also quite efficient as a wavelength tunable filter.

  1. Design and simulation of multimode interference based demultiplexers aided by computer-generated planar holograms.

    PubMed

    Wu, Ming-Chan; Tseng, Shuo-Yen

    2010-05-24

    A 1.31/1.55 microm multimode interference based wavelength demultiplexer aided by computer-generated planar holograms is proposed. The device length is not limited to the common multiples of the beat lengths for the two wavelengths. The demultiplexer length is chosen as the first self-imaging length for 1.55 microm input, and a computer-generated holographic pattern is used to image the 1.31 microm input to the cross output port. The design and optimization of the holographic pattern is presented. The device performance is investigated using the beam propagation method.

  2. OAM states generation/detection based on the multimode interference effect in a ring core fiber.

    PubMed

    Zhou, Junhe

    2015-04-20

    In this paper, we propose to generate/detect orbital angular momentum (OAM) states based on the multimode interference (MMI) effect in a piece of ring core fiber. A comprehensive theory for the MMI process inside ring core fibers is presented. The MMI process inside ring core fibers will convert one input image into multiple equally spaced duplicated output images. After phase adjustment by a fixed phase shifter array, these output images will stimulate OAM states in the ring core fiber or in free space. Henceforth, a novel OAM multiplexer/de-multiplexer (MUX/DEMUX) can be realized by a piece of ring core fiber and a fixed phase shifters array.

  3. PDE based scheme for multi-modal medical image watermarking.

    PubMed

    Aherrahrou, N; Tairi, H

    2015-11-25

    This work deals with copyright protection of digital images, an issue that needs protection of intellectual property rights. It is an important issue with a large number of medical images interchanged on the Internet every day. So, it is a challenging task to ensure the integrity of received images as well as authenticity. Digital watermarking techniques have been proposed as valid solution for this problem. It is worth mentioning that the Region Of Interest (ROI)/Region Of Non Interest (RONI) selection can be seen as a significant limitation from which suffers most of ROI/RONI based watermarking schemes and that in turn affects and limit their applicability in an effective way. Generally, the ROI/RONI is defined by a radiologist or a computer-aided selection tool. And thus, this will not be efficient for an institute or health care system, where one has to process a large number of images. Therefore, developing an automatic ROI/RONI selection is a challenge task. The major aim of this work is to develop an automatic selection algorithm of embedding region based on the so called Partial Differential Equation (PDE) method. Thus avoiding ROI/RONI selection problems including: (1) computational overhead, (2) time consuming, and (3) modality dependent selection. The algorithm is evaluated in terms of imperceptibility, robustness, tamper localization and recovery using MRI, Ultrasound, CT and X-ray grey scale medical images. From experimental results that we have conducted on a database of 100 medical images of four modalities, it can be inferred that our method can achieve high imperceptibility, while showing good robustness against attacks. Furthermore, the experiment results confirm the effectiveness of the proposed algorithm in detecting and recovering the various types of tampering. The highest PSNR value reached over the 100 images is 94,746 dB, while the lowest PSNR value is 60,1272 dB, which demonstrates the higher imperceptibility nature of the proposed

  4. Medical image registration using fuzzy theory.

    PubMed

    Pan, Meisen; Tang, Jingtian; Xiong, Qi

    2012-01-01

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

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

    PubMed

    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.

  6. Arbitrary-ratio power splitter based on nonlinear multimode interference coupler

    SciTech Connect

    Tajaldini, Mehdi; Jafri, Mohd Zubir Mat

    2015-04-24

    We propose an ultra-compact multimode interference (MMI) power splitter based on nonlinear effects from simulations using nonlinear modal propagation analysis (NMPA) cooperation with finite difference Method (FDM) to access free choice of splitting ratio. Conventional multimode interference power splitter could only obtain a few discrete ratios. The power splitting ratio may be adjusted continuously while the input set power is varying by a tunable laser. In fact, using an ultra- compact MMI with a simple structure that is launched by a tunable nonlinear input fulfills the problem of arbitrary-ratio in integrated photonics circuits. Silicon on insulator (SOI) is used as the offered material due to the high contrast refractive index and Centro symmetric properties. The high-resolution images at the end of the multimode waveguide in the simulated power splitter have a high power balance, whereas access to a free choice of splitting ratio is not possible under the linear regime in the proposed length range except changes in the dimension for any ratio. The compact dimensions and ideal performance of the device are established according to optimized parameters. The proposed regime can be extended to the design of M×N arbitrary power splitters ratio for programmable logic devices in all optical digital signal processing. The results of this study indicate that nonlinear modal propagation analysis solves the miniaturization problem for all-optical devices based on MMI couplers to achieve multiple functions in a compact planar integrated circuit and also overcomes the limitations of previously proposed methods for nonlinear MMI.

  7. Arbitrary-ratio power splitter based on nonlinear multimode interference coupler

    NASA Astrophysics Data System (ADS)

    Tajaldini, Mehdi; Jafri, Mohd Zubir Mat

    2015-04-01

    We propose an ultra-compact multimode interference (MMI) power splitter based on nonlinear effects from simulations using nonlinear modal propagation analysis (NMPA) cooperation with finite difference Method (FDM) to access free choice of splitting ratio. Conventional multimode interference power splitter could only obtain a few discrete ratios. The power splitting ratio may be adjusted continuously while the input set power is varying by a tunable laser. In fact, using an ultra- compact MMI with a simple structure that is launched by a tunable nonlinear input fulfills the problem of arbitrary-ratio in integrated photonics circuits. Silicon on insulator (SOI) is used as the offered material due to the high contrast refractive index and Centro symmetric properties. The high-resolution images at the end of the multimode waveguide in the simulated power splitter have a high power balance, whereas access to a free choice of splitting ratio is not possible under the linear regime in the proposed length range except changes in the dimension for any ratio. The compact dimensions and ideal performance of the device are established according to optimized parameters. The proposed regime can be extended to the design of M×N arbitrary power splitters ratio for programmable logic devices in all optical digital signal processing. The results of this study indicate that nonlinear modal propagation analysis solves the miniaturization problem for all-optical devices based on MMI couplers to achieve multiple functions in a compact planar integrated circuit and also overcomes the limitations of previously proposed methods for nonlinear MMI

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

    PubMed

    Wachinger, Christian; Navab, Nassir

    2013-05-01

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

  9. Effect of nonrigid registration algorithms on deformation-based morphometry: a comparative study with control and Williams syndrome subjects.

    PubMed

    Han, Zhaoying; Thornton-Wells, Tricia A; Dykens, Elisabeth M; Gore, John C; Dawant, Benoit M

    2012-07-01

    Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared nonrigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established nonrigid registration algorithms using 13 subjects with Williams syndrome and 13 normal control subjects. The five nonrigid registration algorithms include the following: (1) the adaptive bases algorithm, (2) the image registration toolkit, (3) The FSL nonlinear image registration tool, (4) the automatic registration tool, and (5) the normalization algorithm available in Statistical Parametric Mapping (SPM8). Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. Some regions are detected by several algorithms, but their extent varies. Others are detected only by a subset of the algorithms. Based on these results, we recommend using more than one algorithm when performing DBM studies.

  10. MO-F-BRA-04: Voxel-Based Statistical Analysis of Deformable Image Registration Error via a Finite Element Method.

    PubMed

    Li, S; Lu, M; Kim, J; Glide-Hurst, C; Chetty, I; Zhong, H

    2012-06-01

    Purpose Clinical implementation of adaptive treatment planning is limited by the lack of quantitative tools to assess deformable image registration errors (R-ERR). The purpose of this study was to develop a method, using finite element modeling (FEM), to estimate registration errors based on mechanical changes resulting from them. Methods An experimental platform to quantify the correlation between registration errors and their mechanical consequences was developed as follows: diaphragm deformation was simulated on the CT images in patients with lung cancer using a finite element method (FEM). The simulated displacement vector fields (F-DVF) were used to warp each CT image to generate a FEM image. B-Spline based (Elastix) registrations were performed from reference to FEM images to generate a registration DVF (R-DVF). The F- DVF was subtracted from R-DVF. The magnitude of the difference vector was defined as the registration error, which is a consequence of mechanically unbalanced energy (UE), computed using 'in-house-developed' FEM software. A nonlinear regression model was used based on imaging voxel data and the analysis considered clustered voxel data within images. Results A regression model analysis showed that UE was significantly correlated with registration error, DVF and the product of registration error and DVF respectively with R̂2=0.73 (R=0.854). The association was verified independently using 40 tracked landmarks. A linear function between the means of UE values and R- DVF*R-ERR has been established. The mean registration error (N=8) was 0.9 mm. 85.4% of voxels fit this model within one standard deviation. Conclusions An encouraging relationship between UE and registration error has been found. These experimental results suggest the feasibility of UE as a valuable tool for evaluating registration errors, thus supporting 4D and adaptive radiotherapy. The research was supported by NIH/NCI R01CA140341. © 2012 American Association of Physicists in

  11. Assessment of artery dilation by using image registration based on spatial features

    NASA Astrophysics Data System (ADS)

    Oubel, Estanislao; Neemuchwala, Huzefa; Hero, Alfred; Boisrobert, Loic; Laclaustra, Martin; Frangi, Alejandro F.

    2005-04-01

    The use of affine image registration based on normalized mutual information (NMI) has recently been proposed by Frangi et al. as an automatic method for assessing brachial artery flow mediated dilation (FMD) for the characterization of endothelial function. Even though this method solves many problems of previous approaches, there are still some situations that can lead to misregistration between frames, such as the presence of adjacent vessels due to probe movement, muscle fibres or poor image quality. Despite its widespread use as a registration metric and its promising results, MI is not the panacea and can occasionally fail. Previous work has attempted to include spatial information into the image similarity metric. Among these methods the direct estimation of alpha-MI through Minimum Euclidean Graphs allows to include spatial information and it seems suitable to tackle the registration problem in vascular images, where well oriented structures corresponding to vessel walls and muscle fibres are present. The purpose of this work is twofold. Firstly, we aim to evaluate the effect of including spatial information in the performance of the method suggested by Frangi et al. by using alpha-MI of spatial features as similarity metric. Secondly, the application of image registration to long image sequences in which both rigid motion and deformation are present will be used as a benchmark to prove the value of alpha-MI as a similarity metric, and will also allow us to make a comparative study with respect to NMI.

  12. Co-registration and distortion correction of diffusion and anatomical images based on inverse contrast normalization.

    PubMed

    Bhushan, Chitresh; Haldar, Justin P; Choi, Soyoung; Joshi, Anand A; Shattuck, David W; Leahy, Richard M

    2015-07-15

    Diffusion MRI provides quantitative information about microstructural properties which can be useful in neuroimaging studies of the human brain. Echo planar imaging (EPI) sequences, which are frequently used for acquisition of diffusion images, are sensitive to inhomogeneities in the primary magnetic (B0) field that cause localized distortions in the reconstructed images. We describe and evaluate a new method for correction of susceptibility-induced distortion in diffusion images in the absence of an accurate B0 fieldmap. In our method, the distortion field is estimated using a constrained non-rigid registration between an undistorted T1-weighted anatomical image and one of the distorted EPI images from diffusion acquisition. Our registration framework is based on a new approach, INVERSION (Inverse contrast Normalization for VERy Simple registratION), which exploits the inverted contrast relationship between T1- and T2-weighted brain images to define a simple and robust similarity measure. We also describe how INVERSION can be used for rigid alignment of diffusion images and T1-weighted anatomical images. Our approach is evaluated with multiple in vivo datasets acquired with different acquisition parameters. Compared to other methods, INVERSION shows robust and consistent performance in rigid registration and shows improved alignment of diffusion and anatomical images relative to normalized mutual information for non-rigid distortion correction.

  13. Mouse Atlas Registration with Non-tomographic Imaging Modalities—a Pilot Study Based on Simulation

    PubMed Central

    Wang, Hongkai; Stout, David B.; Chatziioannou, Arion F.

    2012-01-01

    Purpose This study investigates methodologies for the estimation of small animal anatomy from non-tomographic modalities, such as planar X-ray projections, optical cameras, and surface scanners. The key goal is to register a digital mouse atlas to a combination of non-tomographic modalities, in order to provide organ-level anatomical references of small animals in 3D. Procedures A 2D/3D registration method was developed to register the 3D atlas to the combination of non-tomographic imaging modalities. Eleven combinations of three non-tomographic imaging modalities were simulated, and the registration accuracy of each combination was evaluated. Results Comparing the 11 combinations, the top-view X-ray projection combined with the side-view optical camera yielded the best overall registration accuracy of all organs. The use of a surface scanner improved the registration accuracy of skin, spleen, and kidneys. Conclusions The methodologies and evaluation presented in this study should provide helpful information for designing preclinical atlas-based anatomical data acquisition systems. PMID:21983855

  14. Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor

    PubMed Central

    Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

    2016-01-01

    Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation. PMID:27649190

  15. Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor.

    PubMed

    Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

    2016-09-15

    Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation.

  16. Multimodal region-consistent saliency based on foreground and background priors for indoor scene

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Wang, Q.; Zhao, Y.; Chen, S. Y.

    2016-09-01

    Visual saliency is a very important feature for object detection in a complex scene. However, image-based saliency is influenced by clutter background and similar objects in indoor scenes, and pixel-based saliency cannot provide consistent saliency to a whole object. Therefore, in this paper, we propose a novel method that computes visual saliency maps from multimodal data obtained from indoor scenes, whilst keeping region consistency. Multimodal data from a scene are first obtained by an RGB+D camera. This scene is then segmented into over-segments by a self-adapting approach to combine its colour image and depth map. Based on these over-segments, we develop two cues as domain knowledge to improve the final saliency map, including focus regions obtained from colour images, and planar background structures obtained from point cloud data. Thus, our saliency map is generated by compounding the information of the colour data, the depth data and the point cloud data in a scene. In the experiments, we extensively compare the proposed method with state-of-the-art methods, and we also apply the proposed method to a real robot system to detect objects of interest. The experimental results show that the proposed method outperforms other methods in terms of precisions and recall rates.

  17. Effect of constructional parameters on the performance of a surface plasmon resonance sensor based on a multimode polymer optical fiber.

    PubMed

    Gasior, Katarzyna; Martynkien, Tadeusz; Urbanczyk, Waclaw

    2014-12-10

    We experimentally studied the influence of different constructional parameters on the performance of surface plasmon resonance (SPR) sensors based on a commercially available polymer step-index multimode fiber. For the first time, to the best of our knowledge, we experimentally investigated the influence of polishing depth on the characteristics of SPR sensors based on a straight multimode fiber. We also examined the impact of sensing length on the spectral position and strength of the SPR in side-polished straight fibers. To clarify literature contradictions concerning the effect of fiber bending on SPR, we experimentally investigated the performance of U-bent SPR sensing probes based on multimode fibers. We have shown that the SPR can be significantly amplified by bending the polymer fiber with stripped cladding. We also demonstrated that the side-polishing of U-bent sensing probes has little impact on their performance.

  18. Registration of phase-contrast images in propagation-based X-ray phase tomography.

    PubMed

    Weber, L; Hänsch, A; Wolfram, U; Pacureanu, A; Cloetens, P; Peyrin, F; Rit, S; Langer, M

    2017-08-16

    X-ray phase tomography aims at reconstructing the 3D electron density distribution of an object. It offers enhanced sensitivity compared to attenuation-based X-ray absorption tomography. In propagation-based methods, phase contrast is achieved by letting the beam propagate after interaction with the object. The phase shift is then retrieved at each projection angle, and subsequently used in tomographic reconstruction to obtain the refractive index decrement distribution, which is proportional to the electron density. Accurate phase retrieval is achieved by combining images at different propagation distances. For reconstructions of good quality, the phase-contrast images recorded at different distances need to be accurately aligned. In this work, we characterise the artefacts related to misalignment of the phase-contrast images, and investigate the use of different registration algorithms for aligning in-line phase-contrast images. The characterisation of artefacts is done by a simulation study and comparison with experimental data. Loss in resolution due to vibrations is found to be comparable to attenuation-based computed tomography. Further, it is shown that registration of phase-contrast images is nontrivial due to the difference in contrast between the different images, and the often periodical artefacts present in the phase-contrast images if multilayer X-ray optics are used. To address this, we compared two registration algorithms for aligning phase-contrast images acquired by magnified X-ray nanotomography: one based on cross-correlation and one based on mutual information. We found that the mutual information-based registration algorithm was more robust than a correlation-based method. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

  19. Study protocol - efficacy of an attachment-based working alliance in the multimodal pain treatment.

    PubMed

    Pfeifer, Ann-Christin; Amelung, Dorothee; Gerigk, Carina; Schroeter, Corinna; Ehrenthal, Johannes; Neubauer, Eva; Schiltenwolf, Marcus

    2016-02-16

    The concept of attachment is relevant for the onset and development of chronic pain. Insecure attachment styles negatively affect therapeutic outcome. Insecurely attached patients seem to be less able to sustain positive effects of a multimodal treatment program. However, it has never been tested before if an attachment-oriented approach can improve treatment results of insecurely attached patients in a multimodal outpatient setting. To test this assumption, we compare the short- and long-term outcomes for pain patients who will receive multidisciplinary, attachment-oriented treatment with the outcomes for patients in a control group, who will receive the multidisciplinary state-of-the-art treatment. Two patient groups (baseline, attachment intervention) are assessed before treatment, after treatment, and at a 6 month follow-up. The study is conducted in a block design: After data collection of the first block (controls) and before as well as during data collection for the second block (treatment group), the health care personnel of the outpatient pain clinic receives training on attachment theory and its use in the therapeutic context. Pain intensity as measured with visual analogue scales and physical functioning will serve as the primary outcome measures. The design of our study allows for a continuous exchange of experienced team members, which may help bring about concrete attachment related guidelines for the enhancement of therapeutic outcome. This would be the first attempt at an attachment-oriented improvement of multimodal pain programs. An attachment-based approach may be a promising way to enhance long-term treatment outcomes for insecurely attached pain patients. DRKS00008715 (registered on the 3(rd) of June 2015).

  20. Improved B-spline image registration between exhale and inhale lung CT images based on intensity and gradient orientation information

    NASA Astrophysics Data System (ADS)

    Nam, Woo Hyun; Oh, Jihun; Yi, Jonghyon; Park, Yongsup; Cho, Hansu; Kim, Sukjin

    2016-03-01

    Registration of lung CT images acquired at different respiratory phases is clinically relevant in many applications, such as follow-up analysis, lung function analysis based on mechanical elasticity, or pulmonary airflow analysis, etc. In order to find accurate and reliable transformation for registration, a proper choice of dissimilarity measure is important. Even though various intensity-based measures have been introduced for precise registration, the registration performance may be limited since they mainly take intensity values into account without effectively considering useful spatial information. In this paper, we attempt to improve the non-rigid registration accuracy between exhale and inhale CT images of the lung, by proposing a new dissimilarity measure based on gradient orientation representing the spatial information in addition to vessel-weighted intensity and normalized intensity information. Since it is necessary to develop non-rigid registration that can account for large lung deformations, the B-spline free-form deformation (FFD) is adopted as the transformation model. The experimental tests for six clinical datasets show that the proposed method provides more accurate registration results than competitive registration methods.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  2. 2.5D Multi-View Gait Recognition Based on Point Cloud Registration

    PubMed Central

    Tang, Jin; Luo, Jian; Tjahjadi, Tardi; Gao, Yan

    2014-01-01

    This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM. PMID:24686727

  3. EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme.

    PubMed

    Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

    2016-01-01

    Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI.

  4. Highly Sensitive Liquid Core Temperature Sensor Based on Multimode Interference Effects.

    PubMed

    Fuentes-Fuentes, Miguel A; May-Arrioja, Daniel A; Guzman-Sepulveda, José R; Torres-Cisneros, Miguel; Sánchez-Mondragón, José J

    2015-10-23

    A novel fiber optic temperature sensor based on a liquid-core multimode interference device is demonstrated. The advantage of such structure is that the thermo-optic coefficient (TOC) of the liquid is at least one order of magnitude larger than that of silica and this, combined with the fact that the TOC of silica and the liquid have opposite signs, provides a liquid-core multimode fiber (MMF) highly sensitive to temperature. Since the refractive index of the liquid can be easily modified, this allows us to control the modal properties of the liquid-core MMF at will and the sensor sensitivity can be easily tuned by selecting the refractive index of the liquid in the core of the device. The maximum sensitivity measured in our experiments is 20 nm/°C in the low-temperature regime up to 60 °C. To the best of our knowledge, to date, this is the largest sensitivity reported for fiber-based MMI temperature sensors.

  5. Highly Sensitive Liquid Core Temperature Sensor Based on Multimode Interference Effects

    PubMed Central

    Fuentes-Fuentes, Miguel A.; May-Arrioja, Daniel A.; Guzman-Sepulveda, José R.; Torres-Cisneros, Miguel; Sánchez-Mondragón, José J.

    2015-01-01

    A novel fiber optic temperature sensor based on a liquid-core multimode interference device is demonstrated. The advantage of such structure is that the thermo-optic coefficient (TOC) of the liquid is at least one order of magnitude larger than that of silica and this, combined with the fact that the TOC of silica and the liquid have opposite signs, provides a liquid-core multimode fiber (MMF) highly sensitive to temperature. Since the refractive index of the liquid can be easily modified, this allows us to control the modal properties of the liquid-core MMF at will and the sensor sensitivity can be easily tuned by selecting the refractive index of the liquid in the core of the device. The maximum sensitivity measured in our experiments is 20 nm/°C in the low-temperature regime up to 60 °C. To the best of our knowledge, to date, this is the largest sensitivity reported for fiber-based MMI temperature sensors. PMID:26512664

  6. Progressive Graph-Based Transductive Learning for Multi-modal Classification of Brain Disorder Disease.

    PubMed

    Wang, Zhengxia; Zhu, Xiaofeng; Adeli, Ehsan; Zhu, Yingying; Zu, Chen; Nie, Feiping; Shen, Dinggang; Wu, Guorong

    2016-10-01

    Graph-based Transductive Learning (GTL) is a powerful tool in computer-assisted diagnosis, especially when the training data is not sufficient to build reliable classifiers. Conventional GTL approaches first construct a fixed subject-wise graph based on the similarities of observed features (i.e., extracted from imaging data) in the feature domain, and then follow the established graph to propagate the existing labels from training to testing data in the label domain. However, such a graph is exclusively learned in the feature domain and may not be necessarily optimal in the label domain. This may eventually undermine the classification accuracy. To address this issue, we propose a progressive GTL (pGTL) method to progressively find an intrinsic data representation. To achieve this, our pGTL method iteratively (1) refines the subject-wise relationships observed in the feature domain using the learned intrinsic data representation in the label domain, (2) updates the intrinsic data representation from the refined subject-wise relationships, and (3) verifies the intrinsic data representation on the training data, in order to guarantee an optimal classification on the new testing data. Furthermore, we extend our pGTL to incorporate multi-modal imaging data, to improve the classification accuracy and robustness as multi-modal imaging data can provide complementary information. Promising classification results in identifying Alzheimer's disease (AD), Mild Cognitive Impairment (MCI), and Normal Control (NC) subjects are achieved using MRI and PET data.

  7. Non-invasive tissue diagnostics using a multimodal spectroscopic device based on fiber probe

    NASA Astrophysics Data System (ADS)

    Cicchi, Riccardo; Anand, Suresh; Rossari, Susanna; Sturiale, Alessandro; Giordano, Flavio; De Giorgi, Vincenzo; Maio, Vincenza; Massi, Daniela; Nesi, Gabriella; Buccoliero, Anna Maria; Tonelli, Francesco; Guerrini, Renzo; Pimpinelli, Nicola; Pavone, Francesco Saverio

    2014-05-01

    Two different optical fiber probes for combined Raman and fluorescence spectroscopic measurements were designed, developed and used for tissue diagnostics. Two visible laser diodes were used for fluorescence spectroscopy, whereas a laser diode emitting in the NIR was used for Raman spectroscopy. The two probes were based on fiber bundles with a central multimode optical fiber, used for delivering light to the tissue, and 24 surrounding optical fibers for signal collection. Both fluorescence and Raman spectra were acquired using the same detection unit, based on a cooled CCD camera, connected to a spectrograph. The two probes were successfully employed for diagnosing melanocytic lesions in a good agreement with common routine histology. The obtained results demonstrated that the multimodal approach is crucial for improving diagnostic capabilities. Further investigations were performed on colon and brain tissue samples in order to have a benchmark for diagnosing a broader range of tissue lesions and malignancies. The system presented here can improve diagnostic capabilities on a broad range of tissues and has the potential of being used for endoscopic inspections in the near future.

  8. Progressive Graph-Based Transductive Learning for Multi-modal Classification of Brain Disorder Disease

    PubMed Central

    Wang, Zhengxia; Zhu, Xiaofeng; Adeli, Ehsan; Zhu, Yingying; Zu, Chen; Nie, Feiping; Shen, Dinggang; Wu, Guorong

    2017-01-01

    Graph-based Transductive Learning (GTL) is a powerful tool in computer-assisted diagnosis, especially when the training data is not sufficient to build reliable classifiers. Conventional GTL approaches first construct a fixed subject-wise graph based on the similarities of observed features (i.e., extracted from imaging data) in the feature domain, and then follow the established graph to propagate the existing labels from training to testing data in the label domain. However, such a graph is exclusively learned in the feature domain and may not be necessarily optimal in the label domain. This may eventually undermine the classification accuracy. To address this issue, we propose a progressive GTL (pGTL) method to progressively find an intrinsic data representation. To achieve this, our pGTL method iteratively (1) refines the subject-wise relationships observed in the feature domain using the learned intrinsic data representation in the label domain, (2) updates the intrinsic data representation from the refined subject-wise relationships, and (3) verifies the intrinsic data representation on the training data, in order to guarantee an optimal classification on the new testing data. Furthermore, we extend our pGTL to incorporate multi-modal imaging data, to improve the classification accuracy and robustness as multi-modal imaging data can provide complementary information. Promising classification results in identifying Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI), and Normal Control (NC) subjects are achieved using MRI and PET data. PMID:28386606

  9. EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme

    PubMed Central

    Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

    2016-01-01

    Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI. PMID:26880873

  10. Genetic algorithms-based inversion of multimode guided waves for cortical bone characterization

    NASA Astrophysics Data System (ADS)

    Bochud, N.; Vallet, Q.; Bala, Y.; Follet, H.; Minonzio, J.-G.; Laugier, P.

    2016-10-01

    Recent progress in quantitative ultrasound has exploited the multimode waveguide response of long bones. Measurements of the guided modes, along with suitable waveguide modeling, have the potential to infer strength-related factors such as stiffness (mainly determined by cortical porosity) and cortical thickness. However, the development of such model-based approaches is challenging, in particular because of the multiparametric nature of the inverse problem. Current estimation methods in the bone field rely on a number of assumptions for pairing the incomplete experimental data with the theoretical guided modes (e.g. semi-automatic selection and classification of the data). The availability of an alternative inversion scheme that is user-independent is highly desirable. Thus, this paper introduces an efficient inversion method based on genetic algorithms using multimode guided waves, in which the mode-order is kept blind. Prior to its evaluation on bone, our proposal is validated using laboratory-controlled measurements on isotropic plates and bone-mimicking phantoms. The results show that the model parameters (i.e. cortical thickness and porosity) estimated from measurements on a few ex vivo human radii are in good agreement with the reference values derived from x-ray micro-computed tomography. Further, the cortical thickness estimated from in vivo measurements at the third from the distal end of the radius is in good agreement with the values delivered by site-matched high-resolution x-ray peripheral computed tomography.

  11. Automated Coarse Registration of Point Clouds in 3d Urban Scenes Using Voxel Based Plane Constraint

    NASA Astrophysics Data System (ADS)

    Xu, Y.; Boerner, R.; Yao, W.; Hoegner, L.; Stilla, U.

    2017-09-01

    For obtaining a full coverage of 3D scans in a large-scale urban area, the registration between point clouds acquired via terrestrial laser scanning (TLS) is normally mandatory. However, due to the complex urban environment, the automatic registration of different scans is still a challenging problem. In this work, we propose an automatic marker free method for fast and coarse registration between point clouds using the geometric constrains of planar patches under a voxel structure. Our proposed method consists of four major steps: the voxelization of the point cloud, the approximation of planar patches, the matching of corresponding patches, and the estimation of transformation parameters. In the voxelization step, the point cloud of each scan is organized with a 3D voxel structure, by which the entire point cloud is partitioned into small individual patches. In the following step, we represent points of each voxel with the approximated plane function, and select those patches resembling planar surfaces. Afterwards, for matching the corresponding patches, a RANSAC-based strategy is applied. Among all the planar patches of a scan, we randomly select a planar patches set of three planar surfaces, in order to build a coordinate frame via their normal vectors and their intersection points. The transformation parameters between scans are calculated from these two coordinate frames. The planar patches set with its transformation parameters owning the largest number of coplanar patches are identified as the optimal candidate set for estimating the correct transformation parameters. The experimental results using TLS datasets of different scenes reveal that our proposed method can be both effective and efficient for the coarse registration task. Especially, for the fast orientation between scans, our proposed method can achieve a registration error of less than around 2 degrees using the testing datasets, and much more efficient than the classical baseline methods.

  12. a SAR Image Registration Method Based on Sift Algorithm

    NASA Astrophysics Data System (ADS)

    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.

  13. A nonlinear multi-mode wideband piezoelectric vibration-based energy harvester using compliant orthoplanar spring

    SciTech Connect

    Dhote, Sharvari Zu, Jean; Zhu, Yang

    2015-04-20

    In this paper, a nonlinear wideband multi-mode piezoelectric vibration-based energy harvester (PVEH) is proposed based on a compliant orthoplanar spring (COPS), which has an advantage of providing multiple vibration modes at relatively low frequencies. The PVEH is made of a tri-leg COPS flexible structure, where three fixed-guided beams are capable of generating strong nonlinear oscillations under certain base excitation. A prototype harvester was fabricated and investigated through both finite-element analysis and experiments. The frequency response shows multiple resonance which corresponds to a hardening type of nonlinear resonance. By adding masses at different locations on the COPS structure, the first three vibration modes are brought close to each other, where the three hardening nonlinear resonances provide a wide bandwidth for the PVEH. The proposed PVEH has enhanced performance of the energy harvester in terms of a wide frequency bandwidth and a high-voltage output under base excitations.

  14. SU-E-J-91: FFT Based Medical Image Registration Using a Graphics Processing Unit (GPU).

    PubMed

    Luce, J; Hoggarth, M; Lin, J; Block, A; Roeske, J

    2012-06-01

    To evaluate the efficiency gains obtained from using a Graphics Processing Unit (GPU) to perform a Fourier Transform (FT) based image registration. Fourier-based image registration involves obtaining the FT of the component images, and analyzing them in Fourier space to determine the translations and rotations of one image set relative to another. An important property of FT registration is that by enlarging the images (adding additional pixels), one can obtain translations and rotations with sub-pixel resolution. The expense, however, is an increased computational time. GPUs may decrease the computational time associated with FT image registration by taking advantage of their parallel architecture to perform matrix computations much more efficiently than a Central Processor Unit (CPU). In order to evaluate the computational gains produced by a GPU, images with known translational shifts were utilized. A program was written in the Interactive Data Language (IDL; Exelis, Boulder, CO) to performCPU-based calculations. Subsequently, the program was modified using GPU bindings (Tech-X, Boulder, CO) to perform GPU-based computation on the same system. Multiple image sizes were used, ranging from 256×256 to 2304×2304. The time required to complete the full algorithm by the CPU and GPU were benchmarked and the speed increase was defined as the ratio of the CPU-to-GPU computational time. The ratio of the CPU-to- GPU time was greater than 1.0 for all images, which indicates the GPU is performing the algorithm faster than the CPU. The smallest improvement, a 1.21 ratio, was found with the smallest image size of 256×256, and the largest speedup, a 4.25 ratio, was observed with the largest image size of 2304×2304. GPU programming resulted in a significant decrease in computational time associated with a FT image registration algorithm. The inclusion of the GPU may provide near real-time, sub-pixel registration capability. © 2012 American Association of Physicists in

  15. Bus-based park-and-ride system: a stochastic model on multimodal network with congestion pricing schemes

    NASA Astrophysics Data System (ADS)

    Liu, Zhiyuan; Meng, Qiang

    2014-05-01

    This paper focuses on modelling the network flow equilibrium problem on a multimodal transport network with bus-based park-and-ride (P&R) system and congestion pricing charges. The multimodal network has three travel modes: auto mode, transit mode and P&R mode. A continuously distributed value-of-time is assumed to convert toll charges and transit fares to time unit, and the users' route choice behaviour is assumed to follow the probit-based stochastic user equilibrium principle with elastic demand. These two assumptions have caused randomness to the users' generalised travel times on the multimodal network. A comprehensive network framework is first defined for the flow equilibrium problem with consideration of interactions between auto flows and transit (bus) flows. Then, a fixed-point model with unique solution is proposed for the equilibrium flows, which can be solved by a convergent cost averaging method. Finally, the proposed methodology is tested by a network example.

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

    PubMed Central

    Poreba, Martyna; Goulette, François

    2015-01-01

    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%. PMID:25594589

  17. Registration of infrared and visual images based on phase grouping and mutual information of gradient orientation

    NASA Astrophysics Data System (ADS)

    Zhang, Zhilong; Yang, Guopeng; Chen, Dong; Li, Jicheng; Yang, Weiping

    2016-04-01

    This paper presents a novel infrared and visual image registration method based on phase grouping and mutual information of gradient orientation. The method is specially designed for infrared image navigation, which is different from familiar multi-sensor image registration methods in the field of remote sensing. The central idea is to firstly extract common salient structural features from visual and infrared images through phase grouping, then registering infrared image to visual image and estimating the exterior parameters of the infrared camera. Two subjects are involved in this reports: (1) In order to estimate image gradient orientation accurately, a new method based on Leguerre-Gauss filter is presented. Then the image are segmented by grouping of pixels based on their gradient orientations and ling support regions are extracted as common salient structural features from infrared and visual images of the same ground scene. (2)In order for registering infrared and visual image, coordinate systems are constructed, coordinate transformations are formularized, and the new similarity measures based on orientation mutual information is presented. Quantitative evaluations on real and simulated image data reviews that the proposed method can provide registration results with improved robustness and accuracy.

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

    PubMed

    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%.

  19. Autofocusing algorithm of interferogram based on object image and registration technology.

    PubMed

    Yang, Pengcheng; Fang, Suping; Zhu, Xindong; Komori, Masaharu; Kubo, Aizoh

    2013-12-20

    Because the depth of field (DOF) of lenses is limited, a captured interferogram usually includes a focused region and defocused region simultaneously when the form deviation of the helical tooth flank is measured with laser interferometry. Because of the impact of the interference fringe, the existing autofocusing algorithms are difficult for identifying the focused region of the interferogram directly. This paper proposes a new autofocusing algorithm based on the object image and registration technology. First, the reliability region is evaluated according to the gray level. Then the corresponding pixels in the image sequence are determined with the registration technology. Next, the focused region is judged by comparing the average gray gradients in object images. Based on the characteristics of measured gear and the DOF of lens, an experiment is designed. The experimental results are given to verify the feasibility and accuracy of the proposed autofocusing algorithm.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed Central

    Samavati, Navid; Velec, Michael; Brock, Kristy

    2015-01-01

    Purpose 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. Methods and Materials 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 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. Results 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. Conclusions 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. PMID

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

    PubMed

    Samavati, Navid; Velec, Michael; Brock, Kristy

    2015-04-21

    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.

  3. Elastic registration of prostate MR images based on estimation of deformation states.

    PubMed

    Marami, Bahram; Sirouspour, Shahin; Ghoul, Suha; Cepek, Jeremy; Davidson, Sean R H; Capson, David W; Trachtenberg, John; Fenster, Aaron

    2015-04-01

    Magnetic resonance imaging (MRI) is being used increasingly for image-guided targeted biopsy and focal therapy of prostate cancer. In this paper, a combined rigid and deformable registration technique is proposed to register pre-treatment diagnostic 3T magnetic resonance (MR) images of the prostate, with the identified target tumor(s), to intra-treatment 1.5T MR images. The pre-treatment T2-weighted MR images were acquired with patients in a supine position using an endorectal coil in a 3T scanner, while the intra-treatment T2-weighted MR images were acquired in a 1.5T scanner before insertion of the needle with patients in the semi-lithotomy position. Both the rigid and deformable registration algorithms employ an intensity-based distance metric defined based on the modality independent neighborhood descriptors (MIND) between images. The optimization routine for estimating the rigid transformation parameters is initialized using four pairs of manually selected approximate corresponding points on the boundaries of the prostate. In this paper, the problem of deformable image registration is approached from the perspective of state estimation for dynamical systems. The registration algorithm employs a rather generic dynamic linear elastic model of the tissue deformation discretized by the finite element method (FEM). We use the model in a classical state estimation framework to estimate the deformation of the prostate based on the distance metric between pre- and intra-treatment images. Our deformable registration results using 17 sets of prostate MR images showed that the proposed method yielded a target registration error (TRE) of 1.87 ± 0.94 mm,2.03 ± 0.94 mm, and 1.70 ± 0.93 mm for the whole gland (WG), central gland (CG), and peripheral zone (PZ), respectively, using 76 manually-identified fiducial points. This was an improvement over the 2.67 ± 1.31 mm, 2.95 ± 1.43 mm, and 2.34 ± 1.11 mm, respectively for the WG, CG, and PZ after rigid registration alone

  4. A multimodal wave spectrum-based approach for statistical downscaling of local wave climate

    USGS Publications Warehouse

    Hegermiller, Christie; Antolinez, Jose A A; Rueda, Ana C; Camus, Paula; Perez, Jorge; Erikson, Li; Barnard, Patrick; Mendez, Fernando J

    2017-01-01

    Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g. the Pacific). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, we address these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into “wave families,” defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications.

  5. Cross-point analysis for a multimode fiber sensor based on surface plasmon resonance

    NASA Astrophysics Data System (ADS)

    Tsai, Woo-Hu; Tsao, Yu-Chia; Lin, Hong-Yu; Sheu, Bor-Chiou

    2005-09-01

    A novel analysis based on surface plasmon resonance (SPR) with a side-polished multimode fiber and a white-light (halogen light) source is presented. The sensing system is a multimode optical fiber in which half of the core has been polished away and a 40 nm gold layer is deposited on to the polished surface by dc sputter. The SPR dip in the optical spectrum is investigated with an optical spectrum analyzer (OSA). In our SPR fiber sensor, the use of liquids with different refractive indices leads to a shift in the spectral dip in the SPR curve. The cross point (CP) of the two SPR spectra obtained from the refractive-index liquid and the deionized water measurements was observed with the OSA. The CP is shifted sensitively in wavelength from 630to1300 nm relative to a change in the refractive index of the liquid from 1.34 to 1.46. High sensitivities of 1.9×10^-6 refractive-index units (RIUs) in the range of the refractive index of the liquid from 1.40 to 1.44 of 5.7×10^-7 RIUs above the value of 1.44 are proposed and demonstrated in our novel SPR analysis.

  6. Phantom-based multimodal interactions for medical education and training: the Munich Knee Joint Simulator.

    PubMed

    Riener, Robert; Frey, Martin; Pröll, Thomas; Regenfelder, Felix; Burgkart, Rainer

    2004-06-01

    Simulation environments based on virtual reality technologies can support medical education and training. In this paper, the novel approach of an "interactive phantom" is presented that allows a realistic display of haptic contact information typically generated when touching and moving human organs or segments. The key idea of the haptic interface is to attach passive phantom objects to a mechanical actuator. The phantoms look and feel as real anatomical objects. Additional visualization of internal anatomical and physiological information and sound generated during the interaction with the phantom yield a multimodal approach that can increase performance, didactic value, and immersion into the virtual environment. Compared to classical approaches, this multimodal display is convenient to use, provides realistic tactile properties, and can be partly adjusted to different, e.g., pathological properties. The interactive phantom is exemplified by a virtual human knee joint that can support orthopedic education, especially for the training of clinical knee joint evaluation. It is suggested that the technical principle can be transferred to many other fields of medical education and training such as obstetrics and dentistry.

  7. Facial expression recognition in the wild based on multimodal texture features

    NASA Astrophysics Data System (ADS)

    Sun, Bo; Li, Liandong; Zhou, Guoyan; He, Jun

    2016-11-01

    Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal-spatial dense scale-invariant feature transform (SIFT) features and combine multimodal features to recognize expression from image sequences. For the static facial expression recognition based on video frames, we extract dense SIFT and some deep convolutional neural network (CNN) features, including our proposed CNN architecture. We train linear support vector machine and partial least squares classifiers for those kinds of features on the static facial expression in the wild (SFEW) and acted facial expression in the wild (AFEW) dataset, and we propose a fusion network to combine all the extracted features at decision level. The final achievement we gained is 56.32% on the SFEW testing set and 50.67% on the AFEW validation set, which are much better than the baseline recognition rates of 35.96% and 36.08%.

  8. Simulation of the novel compact structure of an interferometric biosensor based on multimode interference waveguides

    NASA Astrophysics Data System (ADS)

    Xhoxhi, Moisi; Dudia, Alma; Ymeti, Aurel

    2017-05-01

    We propose the novel structure of an interferometric biosensor based on multimode interference (MMI) waveguides. We present the design of the biosensor using eigenmode expansion (EME) method in accordance with the requirements and standards of today's photonic technology. The MMI structures with a 90 nm Si3N4 core are used as power splitters with 5 outputs. The 5 high-resolution images at the end of the multimode region show high power balance. We analyze the coupling efficiency of the laser source with the structure, the excess loss and power imbalance for different compact MMI waveguides with widths ranging from 45 μm to 15 μm. For a laser source with a tolerance of +/-1mm in linearization we could achieve a coupling efficiency of 52%. MMI waveguides with tapered channels show excess loss values under 0.5 dB and power imbalance values under 0.08 dB. In addition, we show that for a 10 nm deviation of the source wavelength from its optimal value and for a 10 μm deviation of the MMI length from its optimal value, the performance of the MMI waveguides remains acceptable. Finally, we analyze the power budget of the whole biosensor structure and show that it is sufficient for the proper operation of this device.

  9. MINERVA: a multi-modality plugin-based radiation therapy treatment planning system.

    PubMed

    Wemple, C A; Wessol, D E; Nigg, D W; Cogliati, J J; Milvich, M; Fredrickson, C M; Perkins, M; Harkin, G J; Hartmann-Siantar, C L; Lehmann, J; Flickinger, T; Pletcher, D; Yuan, A; DeNardo, G L

    2005-01-01

    Researchers at the INEEL, MSU, LLNL and UCD have undertaken development of MINERVA, a patient-centric, multi-modal, radiation treatment planning system, which can be used for planning and analysing several radiotherapy modalities, either singly or combined, using common treatment planning tools. It employs an integrated, lightweight plugin architecture to accommodate multi-modal treatment planning using standard interface components. The design also facilitates the future integration of improved planning technologies. The code is being developed with the Java programming language for interoperability. The MINERVA design includes the image processing, model definition and data analysis modules with a central module to coordinate communication and data transfer. Dose calculation is performed by source and transport plugin modules, which communicate either directly through the database or through MINERVA's openly published, extensible markup language (XML)-based application programmer's interface (API). All internal data are managed by a database management system and can be exported to other applications or new installations through the API data formats. A full computation path has been established for molecular-targeted radiotherapy treatment planning, with additional treatment modalities presently under development.

  10. Evanescent wave absorption sensor based on tapered multimode fiber coated with monolayer graphene film

    NASA Astrophysics Data System (ADS)

    Qiu, Hengwei; Gao, Saisai; Chen, Peixi; Li, Zhen; Liu, Xiaoyun; Zhang, Chao; Xu, Yuanyuan; Jiang, Shouzhen; Yang, Cheng; Huo, Yanyan; Yue, Weiwei

    2016-05-01

    An evanescent wave absorption (EWA) sensor based on tapered multimode fiber (TMMF) coated with monolayer graphene film for the detection of double-stranded DNA (DS-DNA) is investigated in this work. The TMMF is a silica multimode fiber (nominally at 62.5 μm), which was tapered to symmetric taper with waist diameters of ~30 μm and total length of ~3 mm. Monolayer graphene film was grown on a copper foil via chemical vapor deposition (CVD) technology and transferred onto skinless tapered fiber core via dry transfer technology. All the components of the sensor are coupled together by fusion splicer in order to eliminate the external disturbance. DS-DNA is created by the assembly of two relatively complemented oligonucleotides. The measurements are obtained by using a spectrometer in the optical wavelength range of 400-900 nm. With the increase of DS-DNA concentration, the output light intensity (OPLI) arisen an obvious attenuation. Importantly, the absorbance (A) and the DS-DNA concentrations shown a reasonable linear variation in a wide range of 5-400 μM. Through a series of comparison, the accuracy of TMMF sensor with graphene (G-TMMF) is much better than that without graphene (TMMF), which can be attributed to the molecular enrichment of graphene by π-π stacking.

  11. Anatomic structure-based deformable image registration of brachytherapy implants in the treatment of locally advanced cervix cancer.

    PubMed

    Ryckman, Jeffrey M; Shelton, Joseph W; Waller, Anthony F; Schreibmann, Eduard; Latifi, Kujtim; Diaz, Roberto

    2016-01-01

    To examine the impact of anatomic structure-based image sets in deformable image registration (DIR) for cervical cancer patients. CT examinations of 7 patients previously treated for locally advanced cervical cancer with external beam radiation therapy and from three to five fractions of high-dose-rate brachytherapy (HDR-BT) were used. Structure-based image sets were created from "free" structures already made for planning purposes, with each structure of interest assigned a unique, homogeneous Hounsfield number. Subsequent HDR fractions were registered to the pretreatment external beam radiation therapy and/or the first HDR fraction using commercially available software by rigid alignment (RIG) followed by DIR. Comparison methods included quantification of external contour displacement between source and target images and calculation of mean voxel displacement values. Registration results for structure-based image sets were then compared and contrasted to intensity-based registrations of the original grayscale images. Utilization of anatomic structure-based image sets resulted in better initial rigid matching (A-RIG) with more importance on applicator positioning and soft tissue structures. Subsequent DIR of anatomic structure-based images allowed for intermodality registrations, whereas all intermodality registrations using original CT images failed to produce anatomically feasible results. We have investigated the use of structure-based CT image sets for image registrations and have produced anatomically favorable registrations with excellent matching of external contours as compared to registrations of original grayscale images. Commercial software registrations using treatment-planning structures required no manual tweaking on a per-patient basis, suggesting results are reproducible and broadly applicable. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

  12. Seed based registration for intraoperative brachytherapy dosimetry: a comparison of methods

    NASA Astrophysics Data System (ADS)

    Su, Yi; Davis, Brian J.; Herman, Michael G.; Robb, Richard A.

    2006-03-01

    Several approaches for registering a subset of imaged points to their true origins were analyzed and compared for seed based TRUS-fluoroscopy registration. The methods include the Downhill Simplex method (DS), the Powell's method (POW), the Iterative Closest Point (ICP) method, the Robust Point Matching method (RPM) and variants of RPM. Several modifications were made to the standard RPM method to improve its performance. One hundred simulations were performed for each combination of noise level, seed detection rate and spurious points and the registration accuracy was evaluated and compared. The noise level ranges from 0 to 5mm, the seed detection ratio ranges from 0.2 to 0.6, and the number of spurious points ranges from 0 to 20. An actual clinical post-implant dataset from permanent prostate brachytherapy was used for the simulation study. The experiments provided evidence that our modified RPM method is superior to other methods, especially when there are many outliers. The RPM based method produced the best results at all noise levels and seed detection rates. The DS based method performed reasonably well, especially at low noise levels without spurious points. There was no significant performance difference between the standard RPM and our modified RPM methods without spurious points. The modified RPM methods outperformed the standard RPM method with large number of spurious points. The registration error was within 2mm, even with 20 outlier points and a noise level of 3mm.

  13. Image registration via level-set motion: applications to atlas-based segmentation.

    PubMed

    Vemuri, B C; Ye, J; Chen, Y; Leonard, C M

    2003-03-01

    Image registration is an often encountered problem in various fields including medical imaging, computer vision and image processing. Numerous algorithms for registering image data have been reported in these areas. In this paper, we present a novel curve evolution approach expressed in a level-set framework to achieve image intensity morphing and a simple non-linear PDE for the corresponding coordinate registration. The key features of the intensity morphing model are that (a) it is very fast and (b) existence and uniqueness of the solution for the evolution model are established in a Sobolev space as opposed to using viscosity methods. The salient features of the coordinate registration model are its simplicity and computational efficiency. The intensity morph is easily achieved via evolving level-sets of one image into the level-sets of the other. To explicitly estimate the coordinate transformation between the images, we derive a non-linear PDE-based motion model which can be solved very efficiently. We demonstrate the performance of our algorithm on a variety of images including synthetic and real data. As an application of the PDE-based motion model, atlas based segmentation of hippocampal shape from several MR brain scans is depicted. In each of these experiments, automated hippocampal shape recovery results are validated via manual "expert" segmentations.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  15. Automated diagnosis of prostate cancer in multi-parametric MRI based on multimodal convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Le, Minh Hung; Chen, Jingyu; Wang, Liang; Wang, Zhiwei; Liu, Wenyu; (Tim Cheng, Kwang-Ting; Yang, Xin

    2017-08-01

    Automated methods for prostate cancer (PCa) diagnosis in multi-parametric magnetic resonance imaging (MP-MRIs) are critical for alleviating requirements for interpretation of radiographs while helping to improve diagnostic accuracy (Artan et al 2010 IEEE Trans. Image Process. 19 2444-55, Litjens et al 2014 IEEE Trans. Med. Imaging 33 1083-92, Liu et al 2013 SPIE Medical Imaging (International Society for Optics and Photonics) p 86701G, Moradi et al 2012 J. Magn. Reson. Imaging 35 1403-13, Niaf et al 2014 IEEE Trans. Image Process. 23 979-91, Niaf et al 2012 Phys. Med. Biol. 57 3833, Peng et al 2013a SPIE Medical Imaging (International Society for Optics and Photonics) p 86701H, Peng et al 2013b Radiology 267 787-96, Wang et al 2014 BioMed. Res. Int. 2014). This paper presents an automated method based on multimodal convolutional neural networks (CNNs) for two PCa diagnostic tasks: (1) distinguishing between cancerous and noncancerous tissues and (2) distinguishing between clinically significant (CS) and indolent PCa. Specifically, our multimodal CNNs effectively fuse apparent diffusion coefficients (ADCs) and T2-weighted MP-MRI images (T2WIs). To effectively fuse ADCs and T2WIs we design a new similarity loss function to enforce consistent features being extracted from both ADCs and T2WIs. The similarity loss is combined with the conventional classification loss functions and integrated into the back-propagation procedure of CNN training. The similarity loss enables better fusion results than existing methods as the feature learning processes of both modalities are mutually guided, jointly facilitating CNN to ‘see’ the true visual patterns of PCa. The classification results of multimodal CNNs are further combined with the results based on handcrafted features using a support vector machine classifier. To achieve a satisfactory accuracy for clinical use, we comprehensively investigate three critical factors which could greatly affect the performance of our

  16. Evaluation of Elekta 4D cone beam CT-based automatic image registration for radiation treatment of lung cancer.

    PubMed

    Li, Jun; Harrison, Amy; Yu, Yan; Xiao, Ying; Werner-Wasik, Maria; Lu, Bo

    2015-09-01

    The study was aimed to evaluate the precision of Elekta four-dimensional (4D) cone beam CT (CBCT)-based automatic dual-image registrations using different landmarks for clipbox for radiation treatment of lung cancer. 30 4D CBCT scans from 15 patients were studied. 4D CBCT images were registered with reference CT images using dual-image registration: a clipbox registration and a mask registration. The image registrations performed in clinic using a physician-defined clipbox, were reviewed by physicians, and were taken as the standard. Studies were conducted to evaluate the automatic dual registrations using three kinds of landmarks for clipbox: spine, spine plus internal target volume (ITV) and lung (including as much of the lung as possible). Translational table shifts calculated from the automatic registrations were compared with those of the standard. The mean of the table shift differences in the lateral direction were 0.03, 0.03 and 0.03 cm, for clipboxes based on spine, spine plus ITV and lung, respectively. The mean of the shift differences in the longitudinal direction were 0.08, 0.08 and 0.08 cm, respectively. The mean of the shift differences in the vertical direction were 0.03, 0.03 and 0.03 cm, respectively. The automatic registrations using three different landmarks for clipbox showed similar results. One can use any of the three landmarks in 4D CBCT dual-image registration. Advance in knowledge: The study provides knowledge and recommendations for application of Elekta 4D CBCT image registration in radiation therapy of lung cancer.

  17. Random forest-based similarity measures for multi-modal classification of Alzheimer’s disease

    PubMed Central

    Gray, Katherine R.; Aljabar, Paul; Heckemann, Rolf A.; Hammers, Alexander; Rueckert, Daniel

    2012-01-01

    Neurodegenerative disorders, such as Alzheimer’s disease, are associated with changes in multiple neuroimaging and biological measures. These may provide complementary information for diagnosis and prognosis. We present a multi-modality classification framework in which manifolds are constructed based on pairwise similarity measures derived from random forest classifiers. Similarities from multiple modalities are combined to generate an embedding that simultaneously encodes information about all the available features. Multimodality classification is then performed using coordinates from this joint embedding. We evaluate the proposed framework by application to neuroimaging and biological data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Features include regional MRI volumes, voxel-based FDG-PET signal intensities, CSF biomarker measures, and categorical genetic information. Classification based on the joint embedding constructed using information from all four modalities out-performs classification based on any individual modality for comparisons between Alzheimer’s disease patients and healthy controls, as well as between mild cognitive impairment patients and healthy controls. Based on the joint embedding, we achieve classification accuracies of 89% between Alzheimer’s disease patients and healthy controls, and 75% between mild cognitive impairment patients and healthy controls. These results are comparable with those reported in other recent studies using multi-kernel learning. Random forests provide consistent pairwise similarity measures for multiple modalities, thus facilitating the combination of different types of feature data. We demonstrate this by application to data in which the number of features differ by several orders of magnitude between modalities. Random forest classifiers extend naturally to multi-class problems, and the framework described here could be applied to distinguish between multiple patient groups in the

  18. MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck

    PubMed Central

    Iacono, Maria Ida; Neufeld, Esra; Akinnagbe, Esther; Bower, Kelsey; Wolf, Johanna; Vogiatzis Oikonomidis, Ioannis; Sharma, Deepika; Lloyd, Bryn; Wilm, Bertram J.; Wyss, Michael; Pruessmann, Klaas P.; Jakab, Andras; Makris, Nikos; Cohen, Ethan D.; Kuster, Niels; Kainz, Wolfgang; Angelone, Leonardo M.

    2015-01-01

    Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1–2 mm and with 10–50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named “MIDA”. The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community. PMID:25901747

  19. MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck.

    PubMed

    Iacono, Maria Ida; Neufeld, Esra; Akinnagbe, Esther; Bower, Kelsey; Wolf, Johanna; Vogiatzis Oikonomidis, Ioannis; Sharma, Deepika; Lloyd, Bryn; Wilm, Bertram J; Wyss, Michael; Pruessmann, Klaas P; Jakab, Andras; Makris, Nikos; Cohen, Ethan D; Kuster, Niels; Kainz, Wolfgang; Angelone, Leonardo M

    2015-01-01

    Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1-2 mm and with 10-50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named "MIDA". The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community.

  20. A framework based on hidden Markov trees for multimodal PET/CT image co-segmentation.

    PubMed

    Hanzouli-Ben Salah, Houda; Lapuyade-Lahorgue, Jerome; Bert, Julien; Benoit, Didier; Lambin, Philippe; Van Baardwijk, Angela; Monfrini, Emmanuel; Pieczynski, Wojciech; Visvikis, Dimitris; Hatt, Mathieu

    2017-08-24

    The purpose of this study was to investigate the use of a probabilistic quad-tree graph (hidden Markov tree, HMT) to provide fast computation, robustness and an interpretational framework for multimodality image processing and to evaluate this framework for single gross tumor target (GTV) delineation from both positron emission tomography (PET) and computed tomography (CT) images. We exploited joint statistical dependencies between hidden states to handle the data stack using multi-observation, multi-resolution of HMT and Bayesian inference. This framework was applied to segmentation of lung tumors in PET/CT datasets taking into consideration simultaneously the CT and the PET image information. PET and CT images were considered using either the original voxels intensities, or after wavelet/contourlet enhancement. The Dice similarity coefficient (DSC), sensitivity (SE), positive predictive value (PPV) were used to assess the performance of the proposed approach on one simulated and 15 clinical PET/CT datasets of non-small cell lung cancer (NSCLC) cases. The surrogate of truth was a statistical consensus (obtained with the Simultaneous Truth and Performance Level Estimation algorithm) of three manual delineations performed by experts on fused PET/CT images. The proposed framework was applied to PET-only, CT-only and PET/CT datasets, and were compared to standard and improved fuzzy c-means (FCM) multimodal implementations. A high agreement with the consensus of manual delineations was observed when using both PET and CT images. Contourlet-based HMT led to the best results with a DSC of 0.92 ± 0.11 compared to 0.89 ± 0.13 and 0.90 ± 0.12 for Intensity-based HMT and Wavelet-based HMT, respectively. Considering PET or CT only in the HMT led to much lower accuracy. Standard and improved FCM led to comparatively lower accuracy than HMT, even when considering multimodal implementations. We evaluated the accuracy of the proposed HMT-based framework for PET/CT image

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

    NASA Astrophysics Data System (ADS)

    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.

  2. Optical flow based deformable volume registration using a novel second-order regularization prior

    NASA Astrophysics Data System (ADS)

    Grbić, Saša; Urschler, Martin; Pock, Thomas; Bischof, Horst

    2010-03-01

    Nonlinear image registration is an initial step for a large number of medical image analysis applications. Optical flow based intensity registration is often used for dealing with intra-modality applications involving motion differences. In this work we present an energy functional which uses a novel, second-order regularization prior of the displacement field. Compared to other methods our scheme is robust to non-Gaussian noise and does not penalize locally affine deformation fields in homogeneous areas. We propose an efficient and stable numerical scheme to find the minimizer of the presented energy. We implemented our algorithm using modern consumer graphics processing units and thereby increased the execution performance dramatically. We further show experimental evaluations on clinical CT thorax data sets at different breathing states and on dynamic 4D CT cardiac data sets.

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

    PubMed

    An, Yong; Wang, Manning; Song, Zhijian

    2015-01-01

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

  4. Strain Rate Tensor Estimation in Cine Cardiac MRI Based on Elastic Image Registration

    NASA Astrophysics Data System (ADS)

    Sánchez-Ferrero, Gonzalo Vegas; Vega, Antonio Tristán; Grande, Lucilio Cordero; de La Higuera, Pablo Casaseca; Fernández, Santiago Aja; Fernández, Marcos Martín; López, Carlos Alberola

    In this work we propose an alternative method to estimate and visualize the Strain Rate Tensor (SRT) in Magnetic Resonance Images (MRI) when Phase Contrast MRI (PCMRI) and Tagged MRI (TMRI) are not available. This alternative is based on image processing techniques. Concretely, image registration algorithms are used to estimate the movement of the myocardium at each point. Additionally, a consistency checking method is presented to validate the accuracy of the estimates when no golden standard is available. Results prove that the consistency checking method provides an upper bound of the mean squared error of the estimate. Our experiments with real data show that the registration algorithm provides a useful deformation field to estimate the SRT fields. A classification between regional normal and dysfunctional contraction patterns, as compared with experts diagnosis, points out that the parameters extracted from the estimated SRT can represent these patterns. Additionally, a scheme for visualizing and analyzing the local behavior of the SRT field is presented.

  5. An octree based approach to multi-grid B-spline registration

    NASA Astrophysics Data System (ADS)

    Jiang, Pingge; Shackleford, James A.

    2017-02-01

    In this paper we propose a new strategy for the recovery of complex anatomical deformations that exhibit local discontinuities, such as the shearing found at the lung-ribcage interface, using multi-grid octree B-splines. B- spline based image registration is widely used in the recovery of respiration induced deformations between CT images. However, the continuity imposed upon the computed deformation field by the parametrizing cubic B- spline basis function results in an inability to correctly capture discontinuities such as the sliding motion at organ boundaries. The proposed technique efficiently captures deformation within and at organ boundaries without the need for prior knowledge, such as segmentation, by selectively increasing deformation freedom within image regions exhibiting poor local registration. Experimental results show that the proposed method achieves more physically plausible deformations than traditional global B-spline methods.

  6. Colonoscope navigation system using colonoscope tracking method based on line registration

    NASA Astrophysics Data System (ADS)

    Oda, Masahiro; Kondo, Hiroaki; Kitasaka, Takayuki; Furukawa, Kazuhiro; Miyahara, Ryoji; Hirooka, Yoshiki; Goto, Hidemi; Navab, Nassir; Mori, Kensaku

    2014-03-01

    This paper presents a new colonoscope navigation system. CT colonography is utilized for colon diagnosis based on CT images. If polyps are found while CT colonography, colonoscopic polypectomy can be performed to remove them. While performing a colonoscopic examination, a physician controls colonoscope based on his/her experience. Inexperienced physicians may occur complications such as colon perforation while colonoscopic examinations. To reduce complications, a navigation system of colonoscope while performing the colonoscopic examinations is necessary. We propose a colonoscope navigation system. This system has a new colonoscope tracking method. This method obtains a colon centerline from a CT volume of a patient. A curved line (colonoscope line) representing the shape of colonoscope inserted to the colon is obtained by using electromagnetic sensors. A coordinate system registration process that employs the ICP algorithm is performed to register the CT and sensor coordinate systems. The colon centerline and colonoscope line are registered by using a line registration method. The position of the colonoscope tip in the colon is obtained from the line registration result. Our colonoscope navigation system displays virtual colonoscopic views generated from the CT volumes. A viewpoint of the virtual colonoscopic view is a point on the centerline that corresponds to the colonoscope tip. Experimental results using a colon phantom showed that the proposed colonoscope tracking method can track the colonoscope tip with small tracking errors.

  7. Scan-based volume animation driven by locally adaptive articulated registrations.

    PubMed

    Rhee, Taehyun; Lewis, J P; Neumann, Ulrich; Nayak, Krishna S

    2011-03-01

    This paper describes a complete system to create anatomically accurate example-based volume deformation and animation of articulated body regions, starting from multiple in vivo volume scans of a specific individual. In order to solve the correspondence problem across volume scans, a template volume is registered to each sample. The wide range of pose variations is first approximated by volume blend deformation (VBD), providing proper initialization of the articulated subject in different poses. A novel registration method is presented to efficiently reduce the computation cost while avoiding strong local minima inherent in complex articulated body volume registration. The algorithm highly constrains the degrees of freedom and search space involved in the nonlinear optimization, using hierarchical volume structures and locally constrained deformation based on the biharmonic clamped spline. Our registration step establishes a correspondence across scans, allowing a data-driven deformation approach in the volume domain. The results provide an occlusion-free person-specific 3D human body model, asymptotically accurate inner tissue deformations, and realistic volume animation of articulated movements driven by standard joint control estimated from the actual skeleton. Our approach also addresses the practical issues arising in using scans from living subjects. The robustness of our algorithms is tested by their applications on the hand, probably the most complex articulated region in the body, and the knee, a frequent subject area for medical imaging due to injuries.

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

    NASA Astrophysics Data System (ADS)

    Liang, Yongfang; Chen, Hua-mei

    2005-04-01

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

  9. A Matlab user interface for the statistically assisted fluid registration algorithm and tensor-based morphometry

    NASA Astrophysics Data System (ADS)

    Yepes-Calderon, Fernando; Brun, Caroline; Sant, Nishita; Thompson, Paul; Lepore, Natasha

    2015-01-01

    Tensor-Based Morphometry (TBM) is an increasingly popular method for group analysis of brain MRI data. The main steps in the analysis consist of a nonlinear registration to align each individual scan to a common space, and a subsequent statistical analysis to determine morphometric differences, or difference in fiber structure between groups. Recently, we implemented the Statistically-Assisted Fluid Registration Algorithm or SAFIRA,1 which is designed for tracking morphometric differences among populations. To this end, SAFIRA allows the inclusion of statistical priors extracted from the populations being studied as regularizers in the registration. This flexibility and degree of sophistication limit the tool to expert use, even more so considering that SAFIRA was initially implemented in command line mode. Here, we introduce a new, intuitive, easy to use, Matlab-based graphical user interface for SAFIRA's multivariate TBM. The interface also generates different choices for the TBM statistics, including both the traditional univariate statistics on the Jacobian matrix, and comparison of the full deformation tensors.2 This software will be freely disseminated to the neuroimaging research community.

  10. Capturing molecular multimode relaxation processes in excitable gases based on decomposition of acoustic relaxation spectra

    NASA Astrophysics Data System (ADS)

    Zhu, Ming; Liu, Tingting; Wang, Shu; Zhang, Kesheng

    2017-08-01

    Existing two-frequency reconstructive methods can only capture primary (single) molecular relaxation processes in excitable gases. In this paper, we present a reconstructive method based on the novel decomposition of frequency-dependent acoustic relaxation spectra to capture the entire molecular multimode relaxation process. This decomposition of acoustic relaxation spectra is developed from the frequency-dependent effective specific heat, indicating that a multi-relaxation process is the sum of the interior single-relaxation processes. Based on this decomposition, we can reconstruct the entire multi-relaxation process by capturing the relaxation times and relaxation strengths of N interior single-relaxation processes, using the measurements of acoustic absorption and sound speed at 2N frequencies. Experimental data for the gas mixtures CO2-N2 and CO2-O2 validate our decomposition and reconstruction approach.

  11. Design of Radio Frequency Link in Automatic Test System for Multimode Mobile Communication Base Station

    NASA Astrophysics Data System (ADS)

    Zhang, Weipeng

    2015-12-01

    A modularized design for the radio frequency (RF) link in automatic test system of multimode mobile communication base station is presented, considering also the characteristics of wireless communication indices and composition of signals of base stations. The test link is divided into general module, time division duplex (TDD) module, module of spurious noise filter, module of downlink intermodulation, module of uplink intermodulation and uplink block module. The composition of modules and link functions are defined, and the interfaces of the general module and the module of spurious noise filter are described. Finally, the estimated gain budget of the test link is presented. It is verified by experiments that the system is reliable and the test efficiency is improved.

  12. The evolution of gadolinium based contrast agents: from single-modality to multi-modality

    NASA Astrophysics Data System (ADS)

    Zhang, Li; Liu, Ruiqing; Peng, Hui; Li, Penghui; Xu, Zushun; Whittaker, Andrew K.

    2016-05-01

    Gadolinium-based contrast agents are extensively used as magnetic resonance imaging (MRI) contrast agents due to their outstanding signal enhancement and ease of chemical modification. However, it is increasingly recognized that information obtained from single modal molecular imaging cannot satisfy the higher requirements on the efficiency and accuracy for clinical diagnosis and medical research, due to its limitation and default rooted in single molecular imaging technique itself. To compensate for the deficiencies of single function magnetic resonance imaging contrast agents, the combination of multi-modality imaging has turned to be the research hotpot in recent years. This review presents an overview on the recent developments of the functionalization of gadolinium-based contrast agents, and their application in biomedicine applications.

  13. Two-channel highly sensitive sensors based on 4 × 4 multimode interference couplers

    NASA Astrophysics Data System (ADS)

    Le, Trung-Thanh

    2017-08-01

    We propose a new kind of microring resonators (MRR) based on 4 × 4 multimode interference (MMI) couplers for multichannel and highly sensitive chemical and biological sensors. The proposed sensor structure has advantages of compactness and high sensitivity compared with the reported sensing structures. By using the transfer matrix method (TMM) and numerical simulations, the designs of the sensor based on silicon waveguides are optimized and demonstrated in detail. We apply our structure to detect glucose and ethanol concentrations simultaneously. A high sensitivity of 9000 nm/RIU, detection limit of 2 × 10‒4 for glucose sensing and sensitivity of 6000 nm/RIU, detection limit of 1.3 × 10‒5 for ethanol sensing are achieved.

  14. Active edge maps for medical image registration

    NASA Astrophysics Data System (ADS)

    Kerwin, William; Yuan, Chun

    2001-07-01

    Applying edge detection prior to performing image registration yields several advantages over raw intensity- based registration. Advantages include the ability to register multicontrast or multimodality images, immunity to intensity variations, and the potential for computationally efficient algorithms. In this work, a common framework for edge-based image registration is formulated as an adaptation of snakes used in boundary detection. Called active edge maps, the new formulation finds a one-to-one transformation T(x) that maps points in a source image to corresponding locations in a target image using an energy minimization approach. The energy consists of an image component that is small when edge features are well matched in the two images, and an internal term that restricts T(x) to allowable configurations. The active edge map formulation is illustrated here with a specific example developed for affine registration of carotid artery magnetic resonance images. In this example, edges are identified using a magnitude of gradient operator, image energy is determined using a Gaussian weighted distance function, and the internal energy includes separate, adjustable components that control volume preservation and rigidity.

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

    SciTech Connect

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

    2014-04-15

    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 cm{sup 3}), 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

  16. Imaging Neurodegeneration: Steps Toward Brain Network-Based Pathophysiology and Its Potential for Multi-modal Imaging Diagnostics.

    PubMed

    Sorg, C; Göttler, J; Zimmer, C

    2015-10-01

    Multi-modal brain imaging provides different in vivo windows into the human brain and thereby different ways to characterize brain disorders. Particularly, resting-state functional magnetic resonance imaging facilitates the study of macroscopic intrinsic brain networks, which are critical for development and spread of neurodegenerative processes in different neurodegenerative diseases. The aim of the current study is to present and highlight some paradigmatic findings in intrinsic network-based pathophysiology of neurodegenerative diseases and its potential for new network-based multimodal tools in imaging diagnostics. Qualitative review of selected multi-modal imaging studies in neurodegenerative diseases particularly in Alzheimer's disease (AD). Functional connectivity of intrinsic brain networks is selectively and progressively impaired in AD, with changes likely starting before the onset of symptoms in fronto-parietal key networks such as default mode or attention networks. Patterns of distribution and development of both amyloid-β plaques and atrophy are linked with network connectivity changes, suggesting that start and spread of pathology interacts with network connectivity. Qualitatively similar findings have been observed in other neurodegenerative disorders, suggesting shared mechanisms of network-based pathophysiology across diseases. Spread of neurodegeneration is intimately linked with the functional connectivity of intrinsic brain networks. These pathophysiological insights pave the way for new multi-modal network-based tools to detect and characterize neurodegeneration in individual patients.

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

    SciTech Connect

    Yip, Stephen Chen, Aileen B.; Berbeco, Ross; Aerts, Hugo J. W. L.

    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

  18. Removal of local and biased global maxima in intensity-based registration.

    PubMed

    Salvado, Olivier; Wilson, David L

    2007-04-01

    Intensity based registration (e.g., mutual information) suffers from a scalloping artifact giving rise to local maxima and sometimes a biased global maximum in a similarity objective function. Here, we demonstrate that scalloping is principally due to the noise reduction filtering that occurs when image samples are interpolated. Typically at a much smaller scale (100 times less in our test cases), there are also fluctuations in the similarity objective function due to interpolation of the signal and to sampling of a continuous, band-limited image signal. Focusing on the larger problem from noise, we show that this phenomenon can even bias global maxima, giving inaccurate registrations. This phenomenon is readily seen when one registers an image onto itself with different noise realizations but is absent when the same noise realization is present in both images. For linear interpolation, local maxima and global bias are removed if one filters the interpolated image using a new constant variance filter for linear interpolation (cv-lin filter), which equalizes the variance across the interpolated image. We use 2D synthetic and MR images and characterize the effect of cv-lin on similarity objective functions. With a reduction of local and biased maxima, image registration becomes more robust and accurate. An efficient implementation adds insignificant computation time per iteration, and because optimization proceeds more smoothly, sometimes fewer iterations are needed.

  19. [Rapid 2D-3D medical image registration based on CUDA].

    PubMed

    Li, Lingzhi; Zou, Beiji

    2014-08-01

    The medical image registration between preoperative three-dimensional (3D) scan data and intraoperative two-dimensional (2D) image is a key technology in the surgical navigation. Most previous methods need to generate 2D digitally reconstructed radiographs (DRR) images from the 3D scan volume data, then use conventional image similarity function for comparison. This procedure includes a large amount of calculation and is difficult to archive real-time processing. In this paper, with using geometric feature and image density mixed characteristics, we proposed a new similarity measure function for fast 2D-3D registration of preoperative CT and intraoperative X-ray images. This algorithm is easy to implement, and the calculation process is very short, while the resulting registration accuracy can meet the clinical use. In addition, the entire calculation process is very suitable for highly parallel numerical calculation by using the algorithm based on CUDA hardware acceleration to satisfy the requirement of real-time application in surgery.

  20. Recognition-based segmentation and registration method for image guided shoulder surgery.

    PubMed

    Chaoui, J; Hamitouche, C; Stindel, E; Roux, C

    2011-01-01

    For any image guided surgery, independently of the technique which is used (navigation, templates, robotics), it is necessary to get a 3D bone surface model from CT or MR images. Such model is used for planning, registration and visualization. We report that graphical representation of patient bony structure and the surgical tools, interconnectively with the tracking device and patient-to-image registration are crucial components in such a system. For Total Shoulder Arthroplasty (TSA), there are many challenges, The most of cases that we are working with are pathological cases such as rheumatoid arthritis, osteoarthritis disease. The CT images of these cases often show a fusion area between the glenoid cavity and the humeral head. They also show severe deformations of the humeral head surface that result in a loss of contours. This fusion area and image quality problems are also amplified by well-known CT-scan artifacts like beam-hardening or partial volume effects. The state of the art shows that several segmentation techniques, applied to CT-Scans of the shoulder, have already been disclosed. Unfortunately, their performances, when used on pathological data, are quite poor [1, 2]. The aim of this paper is to present a new image guided surgery system based on CT scan of the patient and using bony structure recognition, morphological analysis for the operated region and robust image-to-patient registration.

  1. Two-step FEM-based Liver-CT registration: improving internal and external accuracy

    NASA Astrophysics Data System (ADS)

    Oyarzun Laura, Cristina; Drechsler, Klaus; Wesarg, Stefan

    2014-03-01

    To know the exact location of the internal structures of the organs, especially the vasculature, is of great importance for the clinicians. This information allows them to know which structures/vessels will be affected by certain therapy and therefore to better treat the patients. However the use of internal structures for registration is often disregarded especially in physical based registration methods. In this paper we propose an algorithm that uses finite element methods to carry out a registration of liver volumes that will not only have accuracy in the boundaries of the organ but also in the interior. Therefore a graph matching algorithm is used to find correspondences between the vessel trees of the two livers to be registered. In addition to this an adaptive volumetric mesh is generated that contains nodes in the locations in which correspondences were found. The displacements derived from those correspondences are the input for the initial deformation of the model. The first deformation brings the internal structures to their final deformed positions and the surfaces close to it. Finally, thin plate splines are used to refine the solution at the boundaries of the organ achieving an improvement in the accuracy of 71%. The algorithm has been evaluated in CT clinical images of the abdomen.

  2. Automatic markerless registration of point clouds with semantic-keypoint-based 4-points congruent sets

    NASA Astrophysics Data System (ADS)

    Ge, Xuming

    2017-08-01

    The coarse registration of point clouds from urban building scenes has become a key topic in applications of terrestrial laser scanning technology. Sampling-based algorithms in the random sample consensus (RANSAC) model have emerged as mainstream solutions to address coarse registration problems. In this paper, we propose a novel combined solution to automatically align two markerless point clouds from building scenes. Firstly, the method segments non-ground points from ground points. Secondly, the proposed method detects feature points from each cross section and then obtains semantic keypoints by connecting feature points with specific rules. Finally, the detected semantic keypoints from two point clouds act as inputs to a modified 4PCS algorithm. Examples are presented and the results compared with those of K-4PCS to demonstrate the main contributions of the proposed method, which are the extension of the original 4PCS to handle heavy datasets and the use of semantic keypoints to improve K-4PCS in relation to registration accuracy and computational efficiency.

  3. Validation of 3D multimodality roadmapping in interventional neuroradiology

    NASA Astrophysics Data System (ADS)

    Ruijters, Daniel; Homan, Robert; Mielekamp, Peter; van de Haar, Peter; Babic, Drazenko

    2011-08-01

    Three-dimensional multimodality roadmapping is entering clinical routine utilization for neuro-vascular treatment. Its purpose is to navigate intra-arterial and intra-venous endovascular devices through complex vascular anatomy by fusing pre-operative computed tomography (CT) or magnetic resonance (MR) with the live fluoroscopy image. The fused image presents the real-time position of the intra-vascular devices together with the patient's 3D vascular morphology and its soft-tissue context. This paper investigates the effectiveness, accuracy, robustness and computation times of the described methods in order to assess their suitability for the intended clinical purpose: accurate interventional navigation. The mutual information-based 3D-3D registration proved to be of sub-voxel accuracy and yielded an average registration error of 0.515 mm and the live machine-based 2D-3D registration delivered an average error of less than 0.2 mm. The capture range of the image-based 3D-3D registration was investigated to characterize its robustness, and yielded an extent of 35 mm and 25° for >80% of the datasets for registration of 3D rotational angiography (3DRA) with CT, and 15 mm and 20° for >80% of the datasets for registration of 3DRA with MR data. The image-based 3D-3D registration could be computed within 8 s, while applying the machine-based 2D-3D registration only took 1.5 µs, which makes them very suitable for interventional use.

  4. Intensity-based 2D 3D registration for lead localization in robot guided deep brain stimulation.

    PubMed

    Hunsche, Stefan; Sauner, Dieter; Majdoub, Faycal El; Neudorfer, Clemens; Poggenborg, Jörg; Goßmann, Axel; Maarouf, Mohammad

    2017-03-21

    Intraoperative assessment of lead localization has become a standard procedure during deep brain stimulation surgery in many centers, allowing immediate verification of targeting accuracy and, if necessary, adjustment of the trajectory. The most suitable imaging modality to determine lead positioning, however, remains controversially discussed. Current approaches entail the implementation of computed tomography and magnetic resonance imaging. In the present study, we adopted the technique of intensity-based 2D 3D registration that is commonly employed in stereotactic radiotherapy and spinal surgery. For this purpose, intraoperatively acquired 2D x-ray images were fused with preoperative 3D computed tomography (CT) data to verify lead placement during stereotactic robot assisted surgery. Accuracy of lead localization determined from 2D 3D registration was compared to conventional 3D 3D registration in a subsequent patient study. The mean Euclidian distance of lead coordinates estimated from intensity-based 2D 3D registration versus flat-panel detector CT 3D 3D registration was 0.7 mm  ±  0.2 mm. Maximum values of these distances amounted to 1.2 mm. To further investigate 2D 3D registration a simulation study was conducted, challenging two observers to visually assess artificially generated 2D 3D registration errors. 95% of deviation simulations, which were visually assessed as sufficient, had a registration error below 0.7 mm. In conclusion, 2D 3D intensity-based registration revealed high accuracy and reliability during robot guided stereotactic neurosurgery and holds great potential as a low dose, cost effective means for intraoperative lead localization.

  5. Intensity-based 2D 3D registration for lead localization in robot guided deep brain stimulation

    NASA Astrophysics Data System (ADS)

    Hunsche, Stefan; Sauner, Dieter; El Majdoub, Faycal; Neudorfer, Clemens; Poggenborg, Jörg; Goßmann, Axel; Maarouf, Mohammad

    2017-03-01

    Intraoperative assessment of lead localization has become a standard procedure during deep brain stimulation surgery in many centers, allowing immediate verification of targeting accuracy and, if necessary, adjustment of the trajectory. The most suitable imaging modality to determine lead positioning, however, remains controversially discussed. Current approaches entail the implementation of computed tomography and magnetic resonance imaging. In the present study, we adopted the technique of intensity-based 2D 3D registration that is commonly employed in stereotactic radiotherapy and spinal surgery. For this purpose, intraoperatively acquired 2D x-ray images were fused with preoperative 3D computed tomography (CT) data to verify lead placement during stereotactic robot assisted surgery. Accuracy of lead localization determined from 2D 3D registration was compared to conventional 3D 3D registration in a subsequent patient study. The mean Euclidian distance of lead coordinates estimated from intensity-based 2D 3D registration versus flat-panel detector CT 3D 3D registration was 0.7 mm  ±  0.2 mm. Maximum values of these distances amounted to 1.2 mm. To further investigate 2D 3D registration a simulation study was conducted, challenging two observers to visually assess artificially generated 2D 3D registration errors. 95% of deviation simulations, which were visually assessed as sufficient, had a registration error below 0.7 mm. In conclusion, 2D 3D intensity-based registration revealed high accuracy and reliability during robot guided stereotactic neurosurgery and holds great potential as a low dose, cost effective means for intraoperative lead localization.

  6. GPU accelerated optical coherence tomography angiography using strip-based registration (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Heisler, Morgan; Lee, Sieun; Mammo, Zaid; Jian, Yifan; Ju, Myeong Jin; Miao, Dongkai; Raposo, Eric; Wahl, Daniel J.; Merkur, Andrew; Navajas, Eduardo; Balaratnasingam, Chandrakumar; Beg, Mirza Faisal; Sarunic, Marinko V.

    2017-02-01

    High quality visualization of the retinal microvasculature can improve our understanding of the onset and development of retinal vascular diseases, which are a major cause of visual morbidity and are increasing in prevalence. Optical Coherence Tomography Angiography (OCT-A) images are acquired over multiple seconds and are particularly susceptible to motion artifacts, which are more prevalent when imaging patients with pathology whose ability to fixate is limited. The acquisition of multiple OCT-A images sequentially can be performed for the purpose of removing motion artifact and increasing the contrast of the vascular network through averaging. Due to the motion artifacts, a robust registration pipeline is needed before feature preserving image averaging can be performed. In this report, we present a novel method for a GPU-accelerated pipeline for acquisition, processing, segmentation, and registration of multiple, sequentially acquired OCT-A images to correct for the motion artifacts in individual images for the purpose of averaging. High performance computing, blending CPU and GPU, was introduced to accelerate processing in order to provide high quality visualization of the retinal microvasculature and to enable a more accurate quantitative analysis in a clinically useful time frame. Specifically, image discontinuities caused by rapid micro-saccadic movements and image warping due to smoother reflex movements were corrected by strip-wise affine registration estimated using Scale Invariant Feature Transform (SIFT) keypoints and subsequent local similarity-based non-rigid registration. These techniques improve the image quality, increasing the value for clinical diagnosis and increasing the range of patients for whom high quality OCT-A images can be acquired.

  7. Model-based registration for assessment of spinal deformities in idiopathic scoliosis

    NASA Astrophysics Data System (ADS)

    Forsberg, Daniel; Lundström, Claes; Andersson, Mats; Knutsson, Hans

    2014-01-01

    Detailed analysis of spinal deformity is important within orthopaedic healthcare, in particular for assessment of idiopathic scoliosis. This paper addresses this challenge by proposing an image analysis method, capable of providing a full three-dimensional spine characterization. The proposed method is based on the registration of a highly detailed spine model to image data from computed tomography. The registration process provides an accurate segmentation of each individual vertebra and the ability to derive various measures describing the spinal deformity. The derived measures are estimated from landmarks attached to the spine model and transferred to the patient data according to the registration result. Evaluation of the method provides an average point-to-surface error of 0.9 mm ± 0.9 (comparing segmentations), and an average target registration error of 2.3 mm ± 1.7 (comparing landmarks). Comparing automatic and manual measurements of axial vertebral rotation provides a mean absolute difference of 2.5° ± 1.8, which is on a par with other computerized methods for assessing axial vertebral rotation. A significant advantage of our method, compared to other computerized methods for rotational measurements, is that it does not rely on vertebral symmetry for computing the rotational measures. The proposed method is fully automatic and computationally efficient, only requiring three to four minutes to process an entire image volume covering vertebrae L5 to T1. Given the use of landmarks, the method can be readily adapted to estimate other measures describing a spinal deformity by changing the set of employed landmarks. In addition, the method has the potential to be utilized for accurate segmentations of the vertebrae in routine computed tomography examinations, given the relatively low point-to-surface error.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  9. A pragmatic community-based intervention of multimodal physiotherapy plus deep water running (DWR) for fibromyalgia syndrome: a pilot study.

    PubMed

    Cuesta-Vargas, Antonio I; Adams, Nicola

    2011-11-01

    Evidence-based recommendations support the use of multimodal therapy and hydrotherapy for fibromyalgia syndrome; however, there is little standardisation of such programmes. The aim of the study was to assess the effectiveness of a pool-based exercise using deep water running (DWR) as part of a multimodal physiotherapy programme for patients with fibromyalgia syndrome. For a non-randomised clinical study, 44 patients diagnosed with fibromyalgia were recruited from primary care. Patients in the experimental group received a multimodal programme incorporating pool-based exercise using DWR three times a week for an 8-week period. The control group received a leaflet containing advice and continued with normal activities. Patients were evaluated for physical function (Fibromyalgia Impact Questionnaire, FIQ), pain, general health (Short Form-12 Health Survey) and quality of life (European Quality of Life Scale-5D) pre- and post intervention. Statistically significant results were found for the experimental group for FIQ total score, incorporating physical function, pain, fatigue, stiffness and psychological variables (p < 0.05). Statistically significant differences between the experimental group and control were also found for general health (p < 0.05) and quality of life (p < 0.05). The results of this pilot study and the high level of compliance and adherence and low level of attrition suggest that this multimodal programme incorporating DWR is a safe and effective intervention for fibromyalgia syndrome that is acceptable to patients.

  10. Multi-mode sliding mode control for precision linear stage based on fixed or floating stator.

    PubMed

    Fang, Jiwen; Long, Zhili; Wang, Michael Yu; Zhang, Lufan; Dai, Xufei

    2016-02-01

    This paper presents the control performance of a linear motion stage driven by Voice Coil Motor (VCM). Unlike the conventional VCM, the stator of this VCM is regulated, which means it can be adjusted as a floating-stator or fixed-stator. A Multi-Mode Sliding Mode Control (MMSMC), including a conventional Sliding Mode Control (SMC) and an Integral Sliding Mode Control (ISMC), is designed to control the linear motion stage. The control is switched between SMC and IMSC based on the error threshold. To eliminate the chattering, a smooth function is adopted instead of a signum function. The experimental results with the floating stator show that the positioning accuracy and tracking performance of the linear motion stage are improved with the MMSMC approach.

  11. Multimodal underwater adsorption of oxide nanoparticles on catechol-based polymer nanosheets

    NASA Astrophysics Data System (ADS)

    Yamamoto, Shunsuke; Uchiyama, Shun; Miyashita, Tokuji; Mitsuishi, Masaya

    2016-03-01

    Multimodal underwater adsorption behaviour of catechol units was demonstrated by examining the adsorption of different oxide nanoparticles on nanoscale-integrated polymer nanosheets. Catechol-based polymer nanosheets were fabricated using the Langmuir-Blodgett (LB) technique with random copolymers (p(DDA/DMA)s) of N-dodecylacrylamide (DDA) and dopamine methacrylamide (DMA). The p(DDA/DMA) nanosheets were immersed into water dispersions of SiO2, Al2O3, and WO3 nanoparticles (NPs) respectively. The results show that the adsorption properties can be altered by varying the NP type: SiO2 NP adsorption was observed only below pH = 6, at which the o-quinone form in p(DDA/DMA) nanosheets transforms into the catechol form or vice versa. However, their transition point for Al2O3 NP adsorption was found at approximately pH 10, at which the surface potential of Al2O3 NPs changes the charge polarity, indicating that the electrostatic interaction is predominant. For WO3 NPs, adsorption was observed when citric acid, which modifies the surface of WO3 NPs by complex formation, was used as a pH-controlling agent, but no adsorption was found for hydrochloric acid used as a pH controlling agent. FT-IR measurements proved that miniscule amounts of water molecules were trapped in p(DDA/DMA) nanosheets and that they acquired hydrogen bonding network formations, which might assist nanoparticle adsorption underwater and make the catechol units adjustable. The results indicate that the nanoscale spatial arrangements of catechol units in films are crucially important for the application of multimodal adsorption of oxide nanoparticles on catechol-based polymer materials.Multimodal underwater adsorption behaviour of catechol units was demonstrated by examining the adsorption of different oxide nanoparticles on nanoscale-integrated polymer nanosheets. Catechol-based polymer nanosheets were fabricated using the Langmuir-Blodgett (LB) technique with random copolymers (p(DDA/DMA)s) of N

  12. Multi-modal vibration energy harvesting approach based on nonlinear oscillator arrays under magnetic levitation

    NASA Astrophysics Data System (ADS)

    Abed, I.; Kacem, N.; Bouhaddi, N.; Bouazizi, M. L.

    2016-02-01

    We propose a multi-modal vibration energy harvesting approach based on arrays of coupled levitated magnets. The equations of motion which include the magnetic nonlinearity and the electromagnetic damping are solved using the harmonic balance method coupled with the asymptotic numerical method. A multi-objective optimization procedure is introduced and performed using a non-dominated sorting genetic algorithm for the cases of small magnet arrays in order to select the optimal solutions in term of performances by bringing the eigenmodes close to each other in terms of frequencies and amplitudes. Thanks to the nonlinear coupling and the modal interactions even for only three coupled magnets, the proposed method enable harvesting the vibration energy in the operating frequency range of 4.6-14.5 Hz, with a bandwidth of 190% and a normalized power of 20.2 {mW} {{cm}}-3 {{{g}}}-2.

  13. Multi-mode sliding mode control for precision linear stage based on fixed or floating stator

    NASA Astrophysics Data System (ADS)

    Fang, Jiwen; Long, Zhili; Wang, Michael Yu; Zhang, Lufan; Dai, Xufei

    2016-02-01

    This paper presents the control performance of a linear motion stage driven by Voice Coil Motor (VCM). Unlike the conventional VCM, the stator of this VCM is regulated, which means it can be adjusted as a floating-stator or fixed-stator. A Multi-Mode Sliding Mode Control (MMSMC), including a conventional Sliding Mode Control (SMC) and an Integral Sliding Mode Control (ISMC), is designed to control the linear motion stage. The control is switched between SMC and IMSC based on the error threshold. To eliminate the chattering, a smooth function is adopted instead of a signum function. The experimental results with the floating stator show that the positioning accuracy and tracking performance of the linear motion stage are improved with the MMSMC approach.

  14. Tunable triple Fano resonances based on multimode interference in coupled plasmonic resonator system.

    PubMed

    Li, Shilei; Zhang, Yunyun; Song, Xiaokang; Wang, Yilin; Yu, Li

    2016-07-11

    In this paper, an asymmetric plasmonic structure composed of two MIM (metal-insulator-metal) waveguides and two rectangular cavities is reported, which can support triple Fano resonances originating from three different mechanisms. And the multimode interference coupled mode theory (MICMT) including coupling phases is proposed based on single mode coupled mode theory (CMT), which is used for describing and explaining the multiple Fano resonance phenomenon in coupled plasmonic resonator systems. Just because the triple Fano resonances originate from three different mechanisms, each Fano resonance can be tuned independently or semi-independently by changing the parameters of the two rectangular cavities. Such, a narrow 'M' type of double Lorentzian-like line-shape transmission windows with the position and the full width at half maximum (FWHM) can be tuned freely is constructed by changing the parameters of the two cavities appropriately, which can find widely applications in sensors, nonlinear and slow-light devices.

  15. Refractive index measurement based on fiber Bragg grating connected with a multimode fiber core

    NASA Astrophysics Data System (ADS)

    Shao, Min; Qiao, Xueguang; Jiasurname, Zhenan; Fusurname, Haiwei; Liu, Yinggang; Li, Huidong; Zhao, Xue

    2015-09-01

    A novel fiber refractive index sensor based on a fiber-Bragg grating (FBG) connected with a section of multimode fiber core (MMFC) is proposed and demonstrated. The MMFC excites high-order modes to form modal interference, and the core mode reflected by the FBG is sensitive to the surrounding refractive index (SRI) for the power of the core mode within MMFC is dependent on SRI. Measuring the reflective power variation of the core mode could realize the refractive index (RI) detection. Experimental results show that the core mode of FBG has a linear response to RI with enhanced sensitivity of 193.55 dB/RIU in the RI range of 1.3350-1.4042 RIU. The temperature effect of the sensor is also discussed.

  16. Refractive index sensors based on the fused tapered special multi-mode fiber

    NASA Astrophysics Data System (ADS)

    Fu, Xing-hu; Xiu, Yan-li; Liu, Qin; Xie, Hai-yang; Yang, Chuan-qing; Zhang, Shun-yang; Fu, Guang-wei; Bi, Wei-hong

    2016-01-01

    In this paper, a novel refractive index (RI) sensor is proposed based on the fused tapered special multi-mode fiber (SMMF). Firstly, a section of SMMF is spliced between two single-mode fibers (SMFs). Then, the SMMF is processed by a fused tapering machine, and a tapered fiber structure is fabricated. Finally, a fused tapered SMMF sensor is obtained for measuring external RI. The RI sensing mechanism of tapered SMMF sensor is analyzed in detail. For different fused tapering lengths, the experimental results show that the RI sensitivity can be up to 444.517 81 nm/RIU in the RI range of 1.334 9—1.347 0. The RI sensitivity is increased with the increase of fused tapering length. Moreover, it has many advantages, including high sensitivity, compact structure, fast response and wide application range. So it can be used to measure the solution concentration in the fields of biochemistry, health care and food processing.

  17. Side-polished multimode fiber biosensor based on surface plasmon resonance with halogen light

    NASA Astrophysics Data System (ADS)

    Lin, Hong-Yu; Tsai, Woo-Hu; Tsao, Yu-Chia; Sheu, Bor-Chiou

    2007-02-01

    A side-polished multimode fiber sensor based on surface plasmon resonance (SPR) as the transducing element with a halogen light source is proposed. The SPR fiber sensor is side polished until half the core is closed and coated with a 37 nm gold thin film by dc sputtering. The SPR curve on the optical spectrum is described by an optical spectrum analyzer and can sense a range of widths in wavelengths of SPR effects. The measurement system using the halogen light source is constructed for several real-time detections that are carried out for the measurement of the index liquid detections for the sensitivity analysis. The sensing fiber is demonstrated with a series of refractive index (RI) liquids and set for several experiments, including the stability, repeatability, and resolution calibration. The results for the halogen light source with the resolution of the measurement based on wavelength interrogation were 3×10-6 refractive index units (RIUs). The SPR dip shifted in wavelength is used as a measure of the RI change at a surface, and this RI change varies directly with the number of biomolecules at the surface. The SPR dip shift in wavelength, which was hybridized at 0.1 μM of the target DNA to the probe DNA, was 8.66 nm. The all-fiber multimode SPR sensor, which has the advantages of being low cost, being disposable, having high stability and linearity, being free of labeling, and having potential for real-time detection, permit the sensor and system to be used in biochemical sensing and environmental monitoring.

  18. Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations.

    PubMed

    Meyer, C R; Boes, J L; Kim, B; Bland, P H; Zasadny, K R; Kison, P V; Koral, K; Frey, K A; Wahl, R L

    1997-04-01

    This paper applies and evaluates an automatic mutual information-based registration algorithm across a broad spectrum of multimodal volume data sets. The algorithm requires little or no pre-processing, minimal user input and easily implements either affine, i.e. linear or thin-plate spline (TPS) warped registrations. We have evaluated the algorithm in phantom studies as well as in selected cases where few other algorithms could perform as well, if at all, to demonstrate the value of this new method. Pairs of multimodal gray-scale volume data sets were registered by iteratively changing registration parameters to maximize mutual information. Quantitative registration errors were assessed in registrations of a thorax phantom using PET/CT and in the National Library of Medicine's Visible Male using MRI T2-/T1-weighted acquisitions. Registrations of diverse clinical data sets were demonstrated including rotate-translate mapping of PET/MRI brain scans with significant missing data, full affine mapping of thoracic PET/CT and rotate-translate mapping of abdominal SPECT/CT. A five-point thin-plate spline (TPS) warped registration of thoracic PET/CT is also demonstrated. The registration algorithm converged in times ranging between 3.5 and 31 min for affine clinical registrations and 57 min for TPS warping. Mean error vector lengths for rotate-translate registrations were measured to be subvoxel in phantoms. More importantly the rotate-translate algorithm performs well even with missing data. The demonstrated clinical fusions are qualitatively excellent at all levels. We conclude that such automatic, rapid, robust algorithms significantly increase the likelihood that multimodality registrations will be routinely used to aid clinical diagnoses and post-therapeutic assessment in the near future.

  19. Reflectance and fluorescence hyperspectral elastic image registration

    NASA Astrophysics Data System (ADS)

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

    2004-05-01

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

  20. Evaluation of Demons- and FEM-Based Registration Algorithms for Lung Cancer.

    PubMed

    Yang, Juan; Li, Dengwang; Yin, Yong; Zhao, Fen; Wang, Hongjun

    2016-04-01

    We evaluated and compared the accuracy of 2 deformable image registration algorithms in 4-dimensional computed tomography images for patients with lung cancer. Ten patients with non-small cell lung cancer or small cell lung cancer were enrolled in this institutional review board-approved study. The displacement vector fields relative to a specific reference image were calculated by using the diffeomorphic demons (DD) algorithm and the finite element method (FEM)-based algorithm. The registration accuracy was evaluated by using normalized mutual information (NMI), the sum of squared intensity difference (SSD), modified Hausdorff distance (dH_M), and ratio of gross tumor volume (rGTV) difference between reference image and deformed phase image. We also compared the registration speed of the 2 algorithms. Of all patients, the FEM-based algorithm showed stronger ability in aligning 2 images than the DD algorithm. The means (±standard deviation) of NMI were 0.86 (±0.05) and 0.90 (±0.05) using the DD algorithm and the FEM-based algorithm, respectively. The means of SSD were 0.006 (±0.003) and 0.003 (±0.002) using the DD algorithm and the FEM-based algorithm, respectively. The means of dH_M were 0.04 (±0.02) and 0.03 (±0.03) using the DD algorithm and the FEM-based algorithm, respectively. The means of rGTV were 3.9% (±1.01%) and 2.9% (±1.1%) using the DD algorithm and the FEM-based algorithm, respectively. However, the FEM-based algorithm costs a longer time than the DD algorithm, with the average running time of 31.4 minutes compared to 21.9 minutes for all patients. The preliminary results showed that the FEM-based algorithm was more accurate than the DD algorithm while compromised with the registration speed. © The Author(s) 2015.

  1. Multi-atlas segmentation of the cartilage in knee MR images with sequential volume- and bone-mask-based registrations

    NASA Astrophysics Data System (ADS)

    Lee, Han Sang; Kim, Hyeun A.; Kim, Hyeonjin; Hong, Helen; Yoon, Young Cheol; Kim, Junmo

    2016-03-01

    In spite of its clinical importance in diagnosis of osteoarthritis, segmentation of cartilage in knee MRI remains a challenging task due to its shape variability and low contrast with surrounding soft tissues and synovial fluid. In this paper, we propose a multi-atlas segmentation of cartilage in knee MRI with sequential atlas registrations and locallyweighted voting (LWV). First, bone is segmented by sequential volume- and object-based registrations and LWV. Second, to overcome the shape variability of cartilage, cartilage is segmented by bone-mask-based registration and LWV. In experiments, the proposed method improved the bone segmentation by reducing misclassified bone region, and enhanced the cartilage segmentation by preventing cartilage leakage into surrounding similar intensity region, with the help of sequential registrations and LWV.

  2. Automated geographic registration and radiometric correction for UAV-based mosaics

    NASA Astrophysics Data System (ADS)

    Thomasson, J. Alex; Shi, Yeyin; Sima, Chao; Yang, Chenghai; Cope, Dale A.

    2017-05-01

    Texas A and M University has been operating a large-scale, UAV-based, agricultural remote-sensing research project since 2015. To use UAV-based images in agricultural production, many high-resolution images must be mosaicked together to create an image of an agricultural field. Two key difficulties to science-based utilization of such mosaics are geographic registration and radiometric calibration. In our current research project, image files are taken to the computer laboratory after the flight, and semi-manual pre-processing is implemented on the raw image data, including ortho-mosaicking and radiometric calibration. Ground control points (GCPs) are critical for high-quality geographic registration of images during mosaicking. Applications requiring accurate reflectance data also require radiometric-calibration references so that reflectance values of image objects can be calculated. We have developed a method for automated geographic registration and radiometric correction with targets that are installed semi-permanently at distributed locations around fields. The targets are a combination of black (≍5% reflectance), dark gray (≍20% reflectance), and light gray (≍40% reflectance) sections that provide for a transformation of pixel-value to reflectance in the dynamic range of crop fields. The exact spectral reflectance of each target is known, having been measured with a spectrophotometer. At the time of installation, each target is measured for position with a real-time kinematic GPS receiver to give its precise latitude and longitude. Automated location of the reference targets in the images is required for precise, automated, geographic registration; and automated calculation of the digital-number to reflectance transformation is required for automated radiometric calibration. To validate the system for radiometric calibration, a calibrated UAV-based image mosaic of a field was compared to a calibrated single image from a manned aircraft. Reflectance

  3. Voxel-based statistical analysis of uncertainties associated with deformable image registration

    NASA Astrophysics Data System (ADS)

    Li, Shunshan; Glide-Hurst, Carri; Lu, Mei; Kim, Jinkoo; Wen, Ning; Adams, Jeffrey N.; Gordon, James; Chetty, Indrin J.; Zhong, Hualiang

    2013-09-01

    Deformable image registration (DIR) algorithms have inherent uncertainties in their displacement vector fields (DVFs).The purpose of this study is to develop an optimal metric to estimate DIR uncertainties. Six computational phantoms have been developed from the CT images of lung cancer patients using a finite element method (FEM). The FEM generated DVFs were used as a standard for registrations performed on each of these phantoms. A mechanics-based metric, unbalanced energy (UE), was developed to evaluate these registration DVFs. The potential correlation between UE and DIR errors was explored using multivariate analysis, and the results were validated by landmark approach and compared with two other error metrics: DVF inverse consistency (IC) and image intensity difference (ID). Landmark-based validation was performed using the POPI-model. The results show that the Pearson correlation coefficient between UE and DIR error is rUE-error = 0.50. This is higher than rIC-error = 0.29 for IC and DIR error and rID-error = 0.37 for ID and DIR error. The Pearson correlation coefficient between UE and the product of the DIR displacements and errors is rUE-error × DVF = 0.62 for the six patients and rUE-error × DVF = 0.73 for the POPI-model data. It has been demonstrated that UE has a strong correlation with DIR errors, and the UE metric outperforms the IC and ID metrics in estimating DIR uncertainties. The quantified UE metric can be a useful tool for adaptive treatment strategies, including probability-based adaptive treatment planning.

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

    NASA Astrophysics Data System (ADS)

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

    2008-03-01

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

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

    PubMed Central

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

    2015-01-01

    Abstract. 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 3.50±1.34  mm for the rigid registration and 2.24±0.71  mm 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. PMID

  6. MatchGUI: A Graphical MATLAB-Based Tool for Automatic Image Co-Registration

    NASA Technical Reports Server (NTRS)

    Ansar, Adnan I.

    2011-01-01

    MatchGUI software, based on MATLAB, automatically matches two images and displays the match result by superimposing one image on the other. A slider bar allows focus to shift between the two images. There are tools for zoom, auto-crop to overlap region, and basic image markup. Given a pair of ortho-rectified images (focused primarily on Mars orbital imagery for now), this software automatically co-registers the imagery so that corresponding image pixels are aligned. MatchGUI requires minimal user input, and performs a registration over scale and inplane rotation fully automatically

  7. A self-recalibration method based on scale-invariant registration for structured light measurement systems

    NASA Astrophysics Data System (ADS)

    Chen, Rui; Xu, Jing; Zhang, Song; Chen, Heping; Guan, Yong; Chen, Ken

    2017-01-01

    The accuracy of structured light measurement depends on delicate offline calibration. However, in some practical applications, the system is supposed to be reconfigured so frequently to track the target that an online calibration is required. To this end, this paper proposes a rapid and autonomous self-recalibration method. For the proposed method, first, the rotation matrix and the normalized translation vector are attained from the fundamental matrix; second, the scale factor is acquired based on scale-invariant registration such that the actual translation vector is obtained. Experiments have been conducted to verify the effectiveness of our proposed method and the results indicate a high degree of accuracy.

  8. Analysis to feature-based video stabilization/registration techniques within application of traffic data collection

    NASA Astrophysics Data System (ADS)

    Sadat, Mojtaba T.; Viti, Francesco

    2015-02-01

    Machine vision is rapidly gaining popularity in the field of Intelligent Transportation Systems. In particular, advantages are foreseen by the exploitation of Aerial Vehicles (AV) in delivering a superior view on traffic phenomena. However, vibration on AVs makes it difficult to extract moving objects on the ground. To partly overcome this issue, image stabilization/registration procedures are adopted to correct and stitch multiple frames taken of the same scene but from different positions, angles, or sensors. In this study, we examine the impact of multiple feature-based techniques for stabilization, and we show that SURF detector outperforms the others in terms of time efficiency and output similarity.

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

    PubMed

    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.

  10. Registration-based Bone Morphometry for Shape Analysis of the Bones of the Human Wrist

    PubMed Central

    Joshi, Anand A.; Leahy, Richard M.; Badawi, Ramsey D.; Chaudhari, Abhijit J.

    2015-01-01

    We present a method that quantifies point-wise changes in surface morphology of the bones of the human wrist. The proposed method, referred to as Registration-based Bone Morphometry (RBM), consists of two steps: an atlas selection step and an atlas warping step. The atlas for individual wrist bones was selected based on the shortest l2 distance to the ensemble of wrist bones from a database of a healthy population of subjects. The selected atlas was then warped to the corresponding bones of individuals in the population using a non-linear registration method based on regularized l2 distance minimization. The displacement field thus calculated showed local differences in bone shape that then were used for the analysis of group differences. Our results indicate that RBM has potential to provide a standardized approach to shape analysis of bones of the human wrist. We demonstrate the performance of RBM for examining group differences in wrist bone shapes based on sex and between those of the right and left wrists in healthy individuals. We also present data to show the application of RBM for tracking bone erosion status in rheumatoid arthritis. PMID:26353369

  11. Registration-Based Morphometry for Shape Analysis of the Bones of the Human Wrist.

    PubMed

    Joshi, Anand A; Leahy, Richard M; Badawi, Ramsey D; Chaudhari, Abhijit J

    2016-02-01

    We present a method that quantifies point-wise changes in surface morphology of the bones of the human wrist. The proposed method, referred to as Registration-bas