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Sample records for based multimodal registration

  1. 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. PMID:22987509

  2. Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI

    NASA Astrophysics Data System (ADS)

    Hwuang, Eileen; Rusu, Mirabela; Karthigeyan, Sudha; Agner, Shannon C.; Sparks, Rachel; Shih, Natalie; Tomaszewski, John E.; Rosen, Mark; Feldman, Michael; Madabhushi, Anant

    2014-03-01

    Multi-modal image registration is needed to align medical images collected from different protocols or imaging sources, thereby allowing the mapping of complementary information between images. One challenge of multimodal image registration is that typical similarity measures rely on statistical correlations between image intensities to determine anatomical alignment. The use of alternate image representations could allow for mapping of intensities into a space or representation such that the multimodal images appear more similar, thus facilitating their co-registration. In this work, we present a spectral embedding based registration (SERg) method that uses non-linearly embedded representations obtained from independent components of statistical texture maps of the original images to facilitate multimodal image registration. Our methodology comprises the following main steps: 1) image-derived textural representation of the original images, 2) dimensionality reduction using independent component analysis (ICA), 3) spectral embedding to generate the alternate representations, and 4) image registration. The rationale behind our approach is that SERg yields embedded representations that can allow for very different looking images to appear more similar, thereby facilitating improved co-registration. Statistical texture features are derived from the image intensities and then reduced to a smaller set by using independent component analysis to remove redundant information. Spectral embedding generates a new representation by eigendecomposition from which only the most important eigenvectors are selected. This helps to accentuate areas of salience based on modality-invariant structural information and therefore better identifies corresponding regions in both the template and target images. The spirit behind SERg is that image registration driven by these areas of salience and correspondence should improve alignment accuracy. In this work, SERg is implemented using Demons

  3. 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.

  4. 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.

  5. Curvelet-based sampling for accurate and efficient multimodal image registration

    NASA Astrophysics Data System (ADS)

    Safran, M. N.; Freiman, M.; Werman, M.; Joskowicz, L.

    2009-02-01

    We present a new non-uniform adaptive sampling method for the estimation of mutual information in multi-modal image registration. The method uses the Fast Discrete Curvelet Transform to identify regions along anatomical curves on which the mutual information is computed. Its main advantages of over other non-uniform sampling schemes are that it captures the most informative regions, that it is invariant to feature shapes, orientations, and sizes, that it is efficient, and that it yields accurate results. Extensive evaluation on 20 validated clinical brain CT images to Proton Density (PD) and T1 and T2-weighted MRI images from the public RIRE database show the effectiveness of our method. Rigid registration accuracy measured at 10 clinical targets and compared to ground truth measurements yield a mean target registration error of 0.68mm(std=0.4mm) for CT-PD and 0.82mm(std=0.43mm) for CT-T2. This is 0.3mm (1mm) more accurate in the average (worst) case than five existing sampling methods. Our method has the lowest registration errors recorded to date for the registration of CT-PD and CT-T2 images in the RIRE website when compared to methods that were tested on at least three patient datasets.

  6. 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

  7. Automatic parameter selection for multimodal image registration.

    PubMed

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

    2010-05-01

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

  8. Graph-based surface extraction of the liver using locally adaptive priors for multimodal interventional image registration

    NASA Astrophysics Data System (ADS)

    Kadoury, Samuel; Wood, Bradford J.; Venkatesan, Aradhana M.; Ardon, Roberto; Jago, James; Kruecker, Jochen

    2012-02-01

    The 3D fusion of tracked ultrasound with a diagnostic CT image has multiple benefits in a variety of interventional applications for oncology. Still, manual registration is a considerable drawback to the clinical workflow and hinders the widespread clinical adoption of this technique. In this paper, we propose a method to allow for an image-based automated registration, aligning multimodal images of the liver. We adopt a model-based approach that rigidly matches segmented liver shapes from ultrasound (U/S) and diagnostic CT imaging. Towards this end, a novel method which combines a dynamic region-growing method with a graph-based segmentation framework is introduced to address the challenging problem of liver segmentation from U/S. The method is able to extract liver boundary from U/S images after a partial surface is generated near the principal vector from an electromagnetically tracked U/S liver sweep. The liver boundary is subsequently expanded by modeling the problem as a graph-cut minimization scheme, where cost functions used to detect optimal surface topology are determined from adaptive priors of neighboring surface points. This allows including boundaries affected by shadow areas by compensating for varying levels of contrast. The segmentation of the liver surface is performed in 3D space for increased accuracy and robustness. The method was evaluated in a study involving 8 patients undergoing biopsy or radiofrequency ablation of the liver, yielding promising surface segmentation results based on ground-truth comparison. The proposed extended segmentation technique improved the fiducial landmark registration error compared to a point-based registration (7.2mm vs. 10.2mm on average, respectively), while achieving tumor target registration errors that are statistically equivalent (p > 0.05) to state-of-the-art methods.

  9. 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.

  10. 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.

  11. 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

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

    PubMed Central

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

    2014-01-01

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

  13. Semiautomated Multimodal Breast Image Registration

    PubMed Central

    Curtis, Charlotte; Frayne, Richard; Fear, Elise

    2012-01-01

    Consideration of information from multiple modalities has been shown to have increased diagnostic power in breast imaging. As a result, new techniques such as microwave imaging continue to be developed. Interpreting these novel image modalities is a challenge, requiring comparison to established techniques such as the gold standard X-ray mammography. However, due to the highly deformable nature of breast tissues, comparison of 3D and 2D modalities is a challenge. To enable this comparison, a registration technique was developed to map features from 2D mammograms to locations in the 3D image space. This technique was developed and tested using magnetic resonance (MR) images as a reference 3D modality, as MR breast imaging is an established technique in clinical practice. The algorithm was validated using a numerical phantom then successfully tested on twenty-four image pairs. Dice's coefficient was used to measure the external goodness of fit, resulting in an excellent overall average of 0.94. Internal agreement was evaluated by examining internal features in consultation with a radiologist, and subjective assessment concludes that reasonable alignment was achieved. PMID:22481910

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

    PubMed

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

    2015-04-01

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

  15. 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

  16. 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. PMID:26736903

  17. Multimodality medical image fusion: probabilistic quantification, segmentation, and registration

    NASA Astrophysics Data System (ADS)

    Wang, Yue J.; Freedman, Matthew T.; Xuan, Jian Hua; Zheng, Qinfen; Mun, Seong K.

    1998-06-01

    Multimodality medical image fusion is becoming increasingly important in clinical applications, which involves information processing, registration and visualization of interventional and/or diagnostic images obtained from different modalities. This work is to develop a multimodality medical image fusion technique through probabilistic quantification, segmentation, and registration, based on statistical data mapping, multiple feature correlation, and probabilistic mean ergodic theorems. The goal of image fusion is to geometrically align two or more image areas/volumes so that pixels/voxels representing the same underlying anatomical structure can be superimposed meaningfully. Three steps are involved. To accurately extract the regions of interest, we developed the model supported Bayesian relaxation labeling, and edge detection and region growing integrated algorithms to segment the images into objects. After identifying the shift-invariant features (i.e., edge and region information), we provided an accurate and robust registration technique which is based on matching multiple binary feature images through a site model based image re-projection. The image was initially segmented into specified number of regions. A rough contour can be obtained by delineating and merging some of the segmented regions. We applied region growing and morphological filtering to extract the contour and get rid of some disconnected residual pixels after segmentation. The matching algorithm is implemented as follows: (1) the centroids of PET/CT and MR images are computed and then translated to the center of both images. (2) preliminary registration is performed first to determine an initial range of scaling factors and rotations, and the MR image is then resampled according to the specified parameters. (3) the total binary difference of the corresponding binary maps in both images is calculated for the selected registration parameters, and the final registration is achieved when the

  18. 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.

  19. Geometric feature-based multimodal image registration of contrast-enhanced cardiac CT with gated myocardial perfusion SPECT

    PubMed Central

    Woo, Jonghye; Slomka, Piotr J.; Dey, Damini; Cheng, Victor Y.; Hong, Byung-Woo; Ramesh, Amit; Berman, Daniel S.; Karlsberg, Ronald P.; Kuo, C.-C. Jay; Germano, Guido

    2009-01-01

    Purpose: Cardiac computed tomography (CT) and single photon emission computed tomography (SPECT) provide clinically complementary information in the diagnosis of coronary artery disease (CAD). Fused anatomical and physiological data acquired sequentially on separate scanners can be coregistered to accurately diagnose CAD in specific coronary vessels. Methods: A fully automated registration method is presented utilizing geometric features from a reliable segmentation of gated myocardial perfusion SPECT (MPS) volumes, where regions of myocardium and blood pools are extracted and used as an anatomical mask to de-emphasize the inhomogeneities of intensity distribution caused by perfusion defects and physiological variations. A multiresolution approach is employed to represent coarse-to-fine details of both volumes. The extracted voxels from each level are aligned using a similarity measure with a piecewise constant image model and minimized using a gradient descent method. The authors then perform limited nonlinear registration of gated MPS to adjust for phase differences by automatic cardiac phase matching between CT and MPS. For phase matching, they incorporate nonlinear registration using thin-plate-spline-based warping. Rigid registration has been compared with manual alignment (n=45) on 20 stress/rest MPS and coronary CTA data sets acquired from two different sites and five stress CT perfusion data sets. Phase matching was also compared to expert visual assessment. Results: As compared with manual alignment obtained from two expert observers, the mean and standard deviation of absolute registration errors of the proposed method for MPS were4.3±3.5, 3.6±2.6, and 3.6±2.1mm for translation and 2.1±3.2°, 0.3±0.8°, and 0.7±1.2° for rotation at site A and 3.8±2.7, 4.0±2.9, and 2.2±1.8mm for translation and 1.1±2.0°, 1.6±3.1°, and 1.9±3.8° for rotation at site B. The results for CT perfusion were 3.0±2.9, 3.5±2.4, and 2.8±1.0mm for translation and 3

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

    PubMed

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

    2004-12-01

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

  1. Distance-Dependent Multimodal Image Registration for Agriculture Tasks

    PubMed Central

    Berenstein, Ron; Hočevar, Marko; Godeša, Tone; Edan, Yael; Ben-Shahar, Ohad

    2015-01-01

    Image registration is the process of aligning two or more images of the same scene taken at different times; from different viewpoints; and/or by different sensors. This research focuses on developing a practical method for automatic image registration for agricultural systems that use multimodal sensory systems and operate in natural environments. While not limited to any particular modalities; here we focus on systems with visual and thermal sensory inputs. Our approach is based on pre-calibrating a distance-dependent transformation matrix (DDTM) between the sensors; and representing it in a compact way by regressing the distance-dependent coefficients as distance-dependent functions. The DDTM is measured by calculating a projective transformation matrix for varying distances between the sensors and possible targets. To do so we designed a unique experimental setup including unique Artificial Control Points (ACPs) and their detection algorithms for the two sensors. We demonstrate the utility of our approach using different experiments and evaluation criteria. PMID:26308000

  2. Non-rigid multi-modal registration on the GPU

    NASA Astrophysics Data System (ADS)

    Vetter, Christoph; Guetter, Christoph; Xu, Chenyang; Westermann, Rüdiger

    2007-03-01

    Non-rigid multi-modal registration of images/volumes is becoming increasingly necessary in many medical settings. While efficient registration algorithms have been published, the speed of the solutions is a problem in clinical applications. Harnessing the computational power of graphics processing unit (GPU) for general purpose computations has become increasingly popular in order to speed up algorithms further, but the algorithms have to be adapted to the data-parallel, streaming model of the GPU. This paper describes the implementation of a non-rigid, multi-modal registration using mutual information and the Kullback-Leibler divergence between observed and learned joint intensity distributions. The entire registration process is implemented on the GPU, including a GPU-friendly computation of two-dimensional histograms using vertex texture fetches as well as an implementation of recursive Gaussian filtering on the GPU. Since the computation is performed on the GPU, interactive visualization of the registration process can be done without bus transfer between main memory and video memory. This allows the user to observe the registration process and to evaluate the result more easily. Two hybrid approaches distributing the computation between the GPU and CPU are discussed. The first approach uses the CPU for lower resolutions and the GPU for higher resolutions, the second approach uses the GPU to compute a first approximation to the registration that is used as starting point for registration on the CPU using double-precision. The results of the CPU implementation are compared to the different approaches using the GPU regarding speed as well as image quality. The GPU performs up to 5 times faster per iteration than the CPU implementation.

  3. 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

  4. 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

  5. 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

  6. 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

  7. Registration of multimodal volume head images via attached markers

    NASA Astrophysics Data System (ADS)

    Mandava, Venkateswara R.; Fitzpatrick, J. Michael; Maurer, Calvin R., Jr.; Maciunas, Robert J.; Allen, George S.

    1992-06-01

    We investigate the accuracy of registering arbitrarily oriented, multimodal, volume images of the human head, both to other images and to physical space, by aligning a configuration of three or more fiducial points that are the centers of attached markers. To compute the centers we use an extension of an adaptive thresholding algorithm due to Kittler. Because the markers are indistinguishable it is necessary to establish their correspondence between images. We have evaluated geometric matching algorithms for this purpose. The inherent errors in fiducial localization arising with digital images limits the accuracy with which anatomical targets can be registered. To accommodate this error we apply a least-squares registration algorithm to the fiducials. To evaluate the resulting target registration accuracy we have conducted experiments on images of internally implanted markers in a cadaver and images of externally attached markers in volunteers. We have also produced computer simulations of volume images of a hemispherical model of the head, randomly picking corresponding fiducial points and targets in the images, introducing uniformly distributed error into the fiducial locations, registering the images, and measuring target registration accuracy at the 95% confidence level. Our results indicate that submillimetric accuracy is feasible for high resolution images with four markers.

  8. 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.

  9. 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. PMID:26672045

  10. Entropy and Laplacian images: structural representations for multi-modal registration.

    PubMed

    Wachinger, Christian; Navab, Nassir

    2012-01-01

    The standard approach to multi-modal registration is to apply sophisticated similarity metrics such as mutual information. The disadvantage of these metrics, in comparison to measuring the intensity difference with, e.g. L1 or L2 distance, is the increase in computational complexity and consequently the increase in runtime of the registration. An alternative approach, which has not yet gained much attention in the literature, is to find image representations, so called structural representations, that allow for the application of the L1 and L2 distance for multi-modal images. This has not only the advantage of a faster similarity calculation but enables also the application of more sophisticated optimization strategies. In this article, we theoretically analyze the requirements for structural representations. Further, we introduce two approaches to create such representations, which are based on the calculation of patch entropy and manifold learning, respectively. While the application of entropy has practical advantages in terms of computational complexity, the usage of manifold learning has theoretical advantages, by presenting an optimal approximation to one of the theoretical requirements. We perform experiments on multiple datasets for rigid, deformable, and groupwise registration with good results with respect to both, runtime and quality of alignment. PMID:21632274

  11. 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.

  12. Multimodal image fusion with SIMS: Preprocessing with image registration.

    PubMed

    Tarolli, Jay Gage; Bloom, Anna; Winograd, Nicholas

    2016-06-01

    In order to utilize complementary imaging techniques to supply higher resolution data for fusion with secondary ion mass spectrometry (SIMS) chemical images, there are a number of aspects that, if not given proper consideration, could produce results which are easy to misinterpret. One of the most critical aspects is that the two input images must be of the same exact analysis area. With the desire to explore new higher resolution data sources that exists outside of the mass spectrometer, this requirement becomes even more important. To ensure that two input images are of the same region, an implementation of the insight segmentation and registration toolkit (ITK) was developed to act as a preprocessing step before performing image fusion. This implementation of ITK allows for several degrees of movement between two input images to be accounted for, including translation, rotation, and scale transforms. First, the implementation was confirmed to accurately register two multimodal images by supplying a known transform. Once validated, two model systems, a copper mesh grid and a group of RAW 264.7 cells, were used to demonstrate the use of the ITK implementation to register a SIMS image with a microscopy image for the purpose of performing image fusion. PMID:26772745

  13. 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. PMID:26936548

  14. 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

  15. Feature-Based Registration Techniques

    NASA Astrophysics Data System (ADS)

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

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

  16. MIND: modality independent neighbourhood descriptor for multi-modal deformable registration.

    PubMed

    Heinrich, Mattias P; Jenkinson, Mark; Bhushan, Manav; Matin, Tahreema; Gleeson, Fergus V; Brady, Sir Michael; Schnabel, Julia A

    2012-10-01

    Deformable registration of images obtained from different modalities remains a challenging task in medical image analysis. This paper addresses this important problem and proposes a modality independent neighbourhood descriptor (MIND) for both linear and deformable multi-modal registration. Based on the similarity of small image patches within one image, it aims to extract the distinctive structure in a local neighbourhood, which is preserved across modalities. The descriptor is based on the concept of image self-similarity, which has been introduced for non-local means filtering for image denoising. It is able to distinguish between different types of features such as corners, edges and homogeneously textured regions. MIND is robust to the most considerable differences between modalities: non-functional intensity relations, image noise and non-uniform bias fields. The multi-dimensional descriptor can be efficiently computed in a dense fashion across the whole image and provides point-wise local similarity across modalities based on the absolute or squared difference between descriptors, making it applicable for a wide range of transformation models and optimisation algorithms. We use the sum of squared differences of the MIND representations of the images as a similarity metric within a symmetric non-parametric Gauss-Newton registration framework. In principle, MIND would be applicable to the registration of arbitrary modalities. In this work, we apply and validate it for the registration of clinical 3D thoracic CT scans between inhale and exhale as well as the alignment of 3D CT and MRI scans. Experimental results show the advantages of MIND over state-of-the-art techniques such as conditional mutual information and entropy images, with respect to clinically annotated landmark locations. PMID:22722056

  17. 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.

  18. Surface-based prostate registration with biomechanical regularization

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  19. Single- and multimodal subvoxel registration of dissimilar medical images using robust similarity measures

    NASA Astrophysics Data System (ADS)

    Nikou, Christophoros; Heitz, Fabrice; Armspach, Jean-Paul; Namer, Izzie-Jacques

    1998-06-01

    Although a large variety of image registration methods have been described in the literature, only a few approaches have attempted to address the rigid registration of medical images showing gross dissimilarities (due for instance to lesion evolution). In the present paper, we develop driven registration algorithms, relying on robust pixel similarity metrics, that enable an accurate (subvoxel) rigid registration of dissimilar single or multimodal 2D/3D images. In the proposed approach, gross dissimilarities are handled by considering similarity measures related to robust M-estimators. A `soft redescending' estimator (the Geman- McClure p-function) has been adopted to reject gross image dissimilarities during the registration. The registration parameters are estimated using a top down stochastic multigrid relaxation algorithm. Thanks to the stochastic multigrid strategy, the registration is not affected by local minima in the objective function and a manual initialization near the optimal solution is not necessary. The proposed robust similarity metrics compare favorably to the most popular standard similarity metrics, on patient image pairs showing gross dissimilarities. Two case studies are considered: the registration of MR/MR and MR/SPECT image volumes of patients suffering from multiple sclerosis and epilepsy.

  20. 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. PMID:25882735

  1. 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

  2. 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.

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

    PubMed

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

    2006-01-21

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

  4. 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.

  5. 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.

  6. Multimodal image registration for preoperative planning and image-guided neurosurgical procedures.

    PubMed

    Risholm, Petter; Golby, Alexandra J; Wells, William

    2011-04-01

    Image registration is the process of transforming images acquired at different time points, or with different imaging modalities, into the same coordinate system. It is an essential part of any neurosurgical planning and navigation system because it facilitates combining images with important complementary, structural, and functional information to improve the information based on which a surgeon makes critical decisions. Brigham and Women's Hospital (BWH) has been one of the pioneers in developing intraoperative registration methods for aligning preoperative and intraoperative images of the brain. This article presents an overview of intraoperative registration and highlights some recent developments at BWH. PMID:21435571

  7. 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

  8. 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.

  9. Evaluation of 3D multimodality image registration using receiver operating characteristic (ROC) analysis

    NASA Astrophysics Data System (ADS)

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

    1995-04-01

    Receiver operating characteristic analysis has evolved as a useful method for evaluating the discriminatory capability and efficacy of visualization. The ability of such analysis to account for the variance in decision criteria of multiple observers, multiple reading, and a wide range of difficulty in detection among case studies makes ROC especially useful for interpreting the results of a viewing experiment. We are currently using ROC analysis to evaluate the effectiveness of using fused multispectral, or complementary multimodality imaging data in the diagnostic process. The use of multispectral image recordings, gathered from multiple imaging modalities, to provide advanced image visualization and quantization capabilities in evaluating medical images is an important challenge facing medical imaging scientists. Such capabilities would potentially significantly enhance the ability of clinicians to extract scientific and diagnostic information from images. a first step in the effective use of multispectral information is the spatial registration of complementary image datasets so that a point-to-point correspondence exists between them. We are developing a paradigm of measuring the accuracy of existing image registration techniques which includes the ability to relate quantitative measurements, taken from the images themselves, to the decisions made by observers about the state of registration (SOR) of the 3D images. We have used ROC analysis to evaluate the ability of observers to discriminate between correctly registered and incorrectly registered multimodality fused images. We believe this experience is original and represents the first time that ROC analysis has been used to evaluate registered/fused images. We have simulated low-resolution and high-resolution images from real patient MR images of the brain, and fused them with the original MR to produce colorwash superposition images whose exact SOR is known. We have also attempted to extend this analysis to

  10. Consistency-based rectification of nonrigid registrations

    PubMed Central

    Gass, Tobias; Székely, Gábor; Goksel, Orcun

    2015-01-01

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

  11. Size-based microfluidic multimodal microparticle sorter.

    PubMed

    Wang, Xiao; Papautsky, Ian

    2015-03-01

    Microfluidic sorting of synthetic and biological microparticles has attracted much interest in recent years. Inertial microfluidics uses hydrodynamic forces to manipulate migration of such microparticles in microfluidic channels to achieve passive sorting based on size with high throughput. However, most inertial microfluidic devices are only capable of bimodal separation with a single cutoff diameter and a well-defined size difference. These limitations inhibit efficient separation of real-world samples that often include heterogeneous mixtures of multiple microparticle components. Our design overcomes these challenges to achieve continuous multimodal sorting of microparticles with high resolution and high tunability of separation cutoff diameters. We demonstrate separations with flexible modulation of the separation bandwidth and the passband location. Our approach offers a number of benefits, including straightforward system design, easily and precisely tuned cutoff diameters, high separation resolution, and high throughput. Ultimately, the unique multimodal separation functionality significantly broadens applications of inertial microfluidics in sorting of complex microparticle samples. PMID:25590954

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

    PubMed Central

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

    2015-01-01

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

  13. 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.

  14. Fast musculoskeletal registration based on shape matching.

    PubMed

    Gilles, Benjamin; Pai, Dinesh K

    2008-01-01

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

  15. 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

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

    PubMed

    Mei, Xue; 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

  17. A multicore based parallel image registration method.

    PubMed

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

    2009-01-01

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

  18. A general technique for interstudy registration of multifunction and multimodality images

    SciTech Connect

    Lin, K.P.; Huang, S.C.; Bacter, L.R.; Phelps, M.E. . School of Medicine)

    1994-12-01

    A technique that can register anatomic/structural brain images (e.g., MRI) with various functional images (e.g., PET-FDG and PET-FDOPA) of the same subject has been developed. The procedure of this technique includes the following steps: (1) segmentation of MRI brain images into gray matter (GM), white matter (WM), cerebral spinal fluid (CSF), and, muscle (MS) components, (2) assignment of appropriate radio-tracer concentrations to various components depending on the kind of functional image that is being registered, (3) generation of simulated functional images to have a spatial resolution that is comparable to that of the measured ones, (4) alignment of the measured functional images to the simulated ones that are based on MRI images. A self-organization clustering method is used to segment the MRI images. The image alignment is based on the criterion of least squares of the pixel-by-pixel differences between the two sets of images that are being matched and on the Powell's algorithm for minimization. The technique was applied successfully for registering the MRI, PET-FDG, and PET-FDOPA images. This technique offers a general solution to the registration of structural images to functional images and to the registration of different functional images of markedly different distributions.

  19. Multimodal cancer imaging using lanthanide-based upconversion nanoparticles.

    PubMed

    Yang, Dongmei; Li, Chunxia; Lin, Jun

    2015-01-01

    Multimodal nanoprobes that integrate different imaging modalities in one nano-system could offer synergistic effect over any modality alone to satisfy the higher requirements on the efficiency and accuracy for clinical diagnosis and medical research. Upconversion nanoparticles (UCNPs), particularly lanthanide (Ln)-based NPs have been regarded as an ideal building block for constructing multimodal bioprobes due to their fascinating properties. In this review, we first summarize recent advances in the optimizations of existing UCNPs. In particular, we highlight the applications of Ln-based UCNPs for multimodal cancer imaging in vitro and in vivo. The explorations of UCNPs-based multimodal nanoprobes for targeting diagnosis and imaging-guided therapeutics are also presented. Finally, the challenges and perspectives of Ln-based UCNPs in this rapid growing field are discussed. PMID:26293416

  20. An image registration based ultrasound probe calibration

    NASA Astrophysics Data System (ADS)

    Li, Xin; Kumar, Dinesh; Sarkar, Saradwata; Narayanan, Ram

    2012-02-01

    Reconstructed 3D ultrasound of prostate gland finds application in several medical areas such as image guided biopsy, therapy planning and dose delivery. In our application, we use an end-fire probe rotated about its axis to acquire a sequence of rotational slices to reconstruct 3D TRUS (Transrectal Ultrasound) image. The image acquisition system consists of an ultrasound transducer situated on a cradle directly attached to a rotational sensor. However, due to system tolerances, axis of probe does not align exactly with the designed axis of rotation resulting in artifacts in the 3D reconstructed ultrasound volume. We present a rigid registration based automatic probe calibration approach. The method uses a sequence of phantom images, each pair acquired at angular separation of 180 degrees and registers corresponding image pairs to compute the deviation from designed axis. A modified shadow removal algorithm is applied for preprocessing. An attribute vector is constructed from image intensity and a speckle-insensitive information-theoretic feature. We compare registration between the presented method and expert-corrected images in 16 prostate phantom scans. Images were acquired at multiple resolutions, and different misalignment settings from two ultrasound machines. Screenshots from 3D reconstruction are shown before and after misalignment correction. Registration parameters from automatic and manual correction were found to be in good agreement. Average absolute differences of translation and rotation between automatic and manual methods were 0.27 mm and 0.65 degree, respectively. The registration parameters also showed lower variability for automatic registration (pooled standard deviation σtranslation = 0.50 mm, σrotation = 0.52 degree) compared to the manual approach (pooled standard deviation σtranslation = 0.62 mm, σrotation = 0.78 degree).

  1. 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.

  2. Multimodal Deformable Registration of Traumatic Brain Injury MR Volumes via the Bhattacharyya Distance

    PubMed Central

    Lou, Yifei; Irimia, Andrei; Vela, Patricio A.; Chambers, Micah C.; Van Horn, John D.; Vespa, Paul M.; Tannenbaum, Allen R.

    2014-01-01

    An important problem of neuroimaging data analysis for traumatic brain injury (TBI) is the task of coregistering MR volumes acquired using distinct sequences in the presence of widely variable pixel movements which are due to the presence and evolution of pathology. We are motivated by this problem to design a numerically stable registration algorithm which handles large deformations. To this end, we propose a new measure of probability distributions based on the Bhattacharyya distance, which is more stable than the widely used mutual information due to better behavior of the square root function than the logarithm at zero. Robustness is illustrated on two TBI patient datasets, each containing 12 MR modalities. We implement our method on graphics processing units (GPU) so as to meet the clinical requirement of time-efficient processing of TBI data. We find that 6 sare required to register a pair of volumes with matrix sizes of 256 256 60 on the GPU. In addition to exceptional time efficiency via its GPU implementation, this methodology provides a clinically informative method for the mapping and evaluation of anatomical changes in TBI. PMID:23962986

  3. 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.

  4. A stationary wavelet transform based approach to registration of planning CT and setup cone beam-CT images in radiotherapy.

    PubMed

    Deng, Jun-Min; Yue, Hai-Zhen; Zhuo, Zhi-Zheng; Yan, Hua-Gang; Liu, Di; Li, Hai-Yun

    2014-05-01

    Image registration between planning CT images and cone beam-CT (CBCT) images is one of the key technologies of image guided radiotherapy (IGRT). Current image registration methods fall roughly into two categories: geometric features-based and image grayscale-based. Mutual information (MI) based registration, which belongs to the latter category, has been widely applied to multi-modal and mono-modal image registration. However, the standard mutual information method only focuses on the image intensity information and overlooks spatial information, leading to the instability of intensity interpolation. Due to its use of positional information, wavelet transform has been applied to image registration recently. In this study, we proposed an approach to setup CT and cone beam-CT (CBCT) image registration in radiotherapy based on the combination of mutual information (MI) and stationary wavelet transform (SWT). Firstly, SWT was applied to generate gradient images and low frequency components produced in various levels of image decomposition were eliminated. Then inverse SWT was performed on the remaining frequency components. Lastly, the rigid registration of gradient images and original images was implemented using a weighting function with the normalized mutual information (NMI) being the similarity measure, which compensates for the lack of spatial information in mutual information based image registration. Our experiment results showed that the proposed method was highly accurate and robust, and indicated a significant clinical potential in improving the accuracy of target localization in image guided radiotherapy (IGRT). PMID:24729043

  5. Magnetic Field Sensing Based on Magnetic-Fluid-Clad Multimode-Singlemode-Multimode Fiber Structures

    PubMed Central

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

    2014-01-01

    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. PMID:25317761

  6. Estimation of line-based target registration error

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  7. Assessment of a Model-Based Deformable Image Registration Approach for Radiation Therapy Planning

    SciTech Connect

    Kaus, Michael R. . E-mail: Michael.kaus@philips.com; Brock, Kristy K.; Pekar, Vladimir; Dawson, Laura A.; Nichol, Alan M.; Jaffray, David A.

    2007-06-01

    Purpose: The aim of this study is to develop a surface-based deformable image registration strategy and to assess the accuracy of the system for the integration of multimodality imaging, image-guided radiation therapy, and assessment of geometrical change during and after therapy. Methods and Materials: A surface-model-based deformable image registration system has been developed that enables quantitative description of geometrical change in multimodal images with high computational efficiency. Based on the deformation of organ surfaces, a volumetric deformation field is derived using different volumetric elasticity models as alternatives to finite-element modeling. Results: The accuracy of the system was assessed both visually and quantitatively by tracking naturally occurring landmarks (bronchial bifurcations in the lung, vessel bifurcations in the liver, implanted gold markers in the prostate). The maximum displacements for lung, liver and prostate were 5.3 cm, 3.2 cm, and 0.6 cm respectively. The largest registration error (direction, mean {+-} SD) for lung, liver and prostate were (inferior-superior, -0.21 {+-} 0.38 cm) (anterior-posterior, -0.09 {+-} 0.34 cm), and (left-right, 0.04 {+-} 0.38 cm) respectively, which was within the image resolution regardless of the deformation model. The computation time (2.7 GHz Intel Xeon) was on the order of seconds (e.g., 10 s for 2 prostate datasets), and deformed axial images could be viewed at interactive speed (less than 1 s for 512 x 512 voxels). Conclusions: Surface-based deformable image registration enables the quantification of geometrical change in normal tissue and tumor with acceptable accuracy and speed.

  8. Analytic regularization for landmark-based image registration

    NASA Astrophysics Data System (ADS)

    Shusharina, Nadezhda; Sharp, Gregory

    2012-03-01

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

  9. 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…

  10. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... valid number portability request as set forth in 47 CFR 52.34; or, if the user does not wish to port a... 47 Telecommunication 3 2014-10-01 2014-10-01 false Internet-based TRS registration. 64.611 Section... Customer Premises Equipment for Persons With Disabilities § 64.611 Internet-based TRS registration....

  11. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... valid number portability request as set forth in 47 CFR 52.34; or, if the user does not wish to port a... 47 Telecommunication 3 2010-10-01 2010-10-01 false Internet-based TRS registration. 64.611 Section... Customer Premises Equipment for Persons With Disabilities § 64.611 Internet-based TRS registration....

  12. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... valid number portability request as set forth in 47 CFR 52.34; or, if the user does not wish to port a... 47 Telecommunication 3 2013-10-01 2013-10-01 false Internet-based TRS registration. 64.611 Section... Customer Premises Equipment for Persons With Disabilities § 64.611 Internet-based TRS registration....

  13. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... valid number portability request as set forth in 47 CFR 52.34; or, if the user does not wish to port a... 47 Telecommunication 3 2012-10-01 2012-10-01 false Internet-based TRS registration. 64.611 Section... Customer Premises Equipment for Persons With Disabilities § 64.611 Internet-based TRS registration....

  14. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... valid number portability request as set forth in 47 CFR 52.34; or, if the user does not wish to port a... 47 Telecommunication 3 2011-10-01 2011-10-01 false Internet-based TRS registration. 64.611 Section... Customer Premises Equipment for Persons With Disabilities § 64.611 Internet-based TRS registration....

  15. 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.

  16. 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. PMID:15988800

  17. Accuracy assessment of an automatic image-based PET/CT registration for ultrasound-guided biopsies and ablations

    NASA Astrophysics Data System (ADS)

    Kadoury, Samuel; Wood, Bradford J.; Venkatesan, Aradhana M.; Dalal, Sandeep; Xu, Sheng; Kruecker, Jochen

    2011-03-01

    The multimodal fusion of spatially tracked real-time ultrasound (US) with a prior CT scan has demonstrated clinical utility, accuracy, and positive impact upon clinical outcomes when used for guidance during biopsy and radiofrequency ablation in the treatment of cancer. Additionally, the combination of CT-guided procedures with positron emission tomography (PET) may not only enhance navigation, but add valuable information regarding the specific location and volume of the targeted masses which may be invisible on CT and US. The accuracy of this fusion depends on reliable, reproducible registration methods between PET and CT. This can avoid extensive manual efforts to correct registration which can be long and tedious in an interventional setting. In this paper, we present a registration workflow for PET/CT/US fusion by analyzing various image metrics based on normalized mutual information and cross-correlation, using both rigid and affine transformations to automatically align PET and CT. Registration is performed between the CT component of the prior PET-CT and the intra-procedural CT scan used for navigation to maximize image congruence. We evaluate the accuracy of the PET/CT registration by computing fiducial and target registration errors using anatomical landmarks and lesion locations respectively. We also report differences to gold-standard manual alignment as well as the root mean square errors for CT/US fusion. Ten patients with prior PET/CT who underwent ablation or biopsy procedures were selected for this study. Studies show that optimal results were obtained using a crosscorrelation based rigid registration with a landmark localization error of 1.1 +/- 0.7 mm using a discrete graphminimizing scheme. We demonstrate the feasibility of automated fusion of PET/CT and its suitability for multi-modality ultrasound guided navigation procedures.

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. Total variation minimization-based multimodality medical image reconstruction

    NASA Astrophysics Data System (ADS)

    Cui, Xuelin; Yu, Hengyong; Wang, Ge; Mili, Lamine

    2014-09-01

    Since its recent inception, simultaneous image reconstruction for multimodality fusion has received a great deal of attention due to its superior imaging performance. On the other hand, the compressed sensing (CS)-based image reconstruction methods have undergone a rapid development because of their ability to significantly reduce the amount of raw data. In this work, we combine computed tomography (CT) and magnetic resonance imaging (MRI) into a single CS-based reconstruction framework. From a theoretical viewpoint, the CS-based reconstruction methods require prior sparsity knowledge to perform reconstruction. In addition to the conventional data fidelity term, the multimodality imaging information is utilized to improve the reconstruction quality. Prior information in this context is that most of the medical images can be approximated as piecewise constant model, and the discrete gradient transform (DGT), whose norm is the total variation (TV), can serve as a sparse representation. More importantly, the multimodality images from the same object must share structural similarity, which can be captured by DGT. The prior information on similar distributions from the sparse DGTs is employed to improve the CT and MRI image quality synergistically for a CT-MRI scanner platform. Numerical simulation with undersampled CT and MRI datasets is conducted to demonstrate the merits of the proposed hybrid image reconstruction approach. Our preliminary results confirm that the proposed method outperforms the conventional CT and MRI reconstructions when they are applied separately.

  4. 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.

  5. Color image registration based on quaternion Fourier transformation

    NASA Astrophysics Data System (ADS)

    Wang, Qiang; Wang, Zhengzhi

    2012-05-01

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

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

    PubMed

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

    2013-09-01

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

  7. Wavelet based free-form deformations for nonrigid registration

    NASA Astrophysics Data System (ADS)

    Sun, Wei; Niessen, Wiro J.; Klein, Stefan

    2014-03-01

    In nonrigid registration, deformations may take place on the coarse and fine scales. For the conventional B-splines based free-form deformation (FFD) registration, these coarse- and fine-scale deformations are all represented by basis functions of a single scale. Meanwhile, wavelets have been proposed as a signal representation suitable for multi-scale problems. Wavelet analysis leads to a unique decomposition of a signal into its coarse- and fine-scale components. Potentially, this could therefore be useful for image registration. In this work, we investigate whether a wavelet-based FFD model has advantages for nonrigid image registration. We use a B-splines based wavelet, as defined by Cai and Wang.1 This wavelet is expressed as a linear combination of B-spline basis functions. Derived from the original B-spline function, this wavelet is smooth, differentiable, and compactly supported. The basis functions of this wavelet are orthogonal across scales in Sobolev space. This wavelet was previously used for registration in computer vision, in 2D optical flow problems,2 but it was not compared with the conventional B-spline FFD in medical image registration problems. An advantage of choosing this B-splines based wavelet model is that the space of allowable deformation is exactly equivalent to that of the traditional B-spline. The wavelet transformation is essentially a (linear) reparameterization of the B-spline transformation model. Experiments on 10 CT lung and 18 T1-weighted MRI brain datasets show that wavelet based registration leads to smoother deformation fields than traditional B-splines based registration, while achieving better accuracy.

  8. Overlay improvement by exposure map based mask registration optimization

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  9. 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.

  10. A new frame-based registration algorithm.

    PubMed

    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. PMID:9472834

  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. 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.

  13. Multimodal based classification of schizophrenia patients.

    PubMed

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

    2015-01-01

    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

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  16. 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.

  17. 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.

  18. 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.

  19. A comparison of thin-plate splines with automatic correspondences and B-splines with uniform grids for multimodal prostate registration

    NASA Astrophysics Data System (ADS)

    Mitra, Jhimli; Marti, Robert; Oliver, Arnau; Llado, Xavier; Vilanova, Joan C.; Meriaudeau, Fabrice

    2011-03-01

    This paper provides a comparison of spline-based registration methods applied to register interventional Trans Rectal Ultrasound (TRUS) and pre-acquired Magnetic Resonance (MR) prostate images for needle guided prostate biopsy. B-splines and Thin-plate Splines (TPS) are the most prevalent spline-based approaches to achieve deformable registration. Pertaining to the strategic selection of correspondences for the TPS registration, we use an automatic method already proposed in our previous work to generate correspondences in the MR and US prostate images. The method exploits the prostate geometry with the principal components of the segmented prostate as the underlying framework and involves a triangulation approach. The correspondences are generated with successive refinements and Normalized Mutual Information (NMI) is employed to determine the optimal number of correspondences required to achieve TPS registration. B-spline registration with successive grid refinements are consecutively applied for a significant comparison of the impact of the strategically chosen correspondences on the TPS registration against the uniform B-spline control grids. The experimental results are validated on 4 patient datasets. Dice Similarity Coefficient (DSC) is used as a measure of the registration accuracy. Average DSC values of 0.97+/-0.01 and 0.95+/-0.03 are achieved for the TPS and B-spline registrations respectively. B-spline registration is observed to be more computationally expensive than the TPS registration with average execution times of 128.09 +/- 21.7 seconds and 62.83 +/- 32.77 seconds respectively for images with maximum width of 264 pixels and a maximum height of 211 pixels.

  20. Power-compensated displacement sensing based on single mode-multimode fiber Bragg grating structure

    NASA Astrophysics Data System (ADS)

    Sun, An; Wu, Zhishen; Huang, Huang

    2013-01-01

    In this paper, power-compensated displacement sensing is proposed and investigated experimentally based on single mode-multimode fiber Bragg grating (FBG) structure, which is fabricated by a single mode fiber and an FBG written on 105/125 μm graded-index multimode fiber (MMF). Experimental results verify that the reflected peak power of multiple wavelengths in single mode-multimode fiber Bragg grating structure shows different response to displacement induced bending of transmitting multimode fiber as the result of multimode interference (MMI). By employing different bending responses between multiple wavelengths of multimode FBG, ratiometric detection based high sensitive displacement measurement can be achieved, which provides a simple and practical method for displacement sensing and meanwhile a potential solution for multi-parameter measurement.

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

    PubMed

    Chumchob, Noppadol

    2013-11-01

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

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

    PubMed Central

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

    2009-01-01

    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 improvement

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

    PubMed

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

    2009-11-13

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

  4. 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.

  5. 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.

  6. 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. PMID:27180287

  7. 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.

  8. Tip Based Nanofabrication Using Multi-mode Scanning Probe Microscopy

    NASA Astrophysics Data System (ADS)

    Hu, Weihua

    Scanning probe microscopy (SPM) based nanotechnology is a promising technology in nano-device fabrication. It is able to both manipulate nanostructures and characterize the created nanopatterns using the nano-tip of the scanning probe on a mechanical basis or electrical basis. With the tip and device on similar scales, nano-tip based fabrication permits accurate control over the device geometry through tip manipulation with nanometer (or better) accuracy. However, SPM based nanofabrication is a slow process because the scanning velocity of the microscopy is low. Large, multi-tip arrays offer the possibility for parallel device fabrication, allowing mass fabrication with nanometer control. The goal of Tip-directed Field-emission Assisted Nanofabrication (TFAN) project was to realize parallel fabrication using our probe arrays. We started by fabricating nanodevice using one single probe. In this work, we investigated the study of fabricating single electron transistor (SET) using one single SPM probe. There were four stages we went through toward fabricating a SET. The first stage was to accomplish atomic-precision lithography in TFAN system. Atomic level lithography was achieved by desorbing hydrogen atoms, which were previously adsorbed to the Si(100)-2 × 1 surface, in ultrahigh vacuum scanning tunneling microscopy (UHV-STM). The second stage was to develop method for fabricating SET. SPM based local oxidation was chosen as the method to fabricate a SET on a thin titanium (Ti) film. A multi-mode SPM oxidation method was developed, in which both scanning tunneling microscopy (STM) mode and atomic microscopy (AFM) mode local oxidation were used to fabricated Ti-TiOx-Ti structures with the same conductive AFM probe. This multi-mode method enabled significantly fine feature size control by STM mode, working on insulating SiO2 substrates needed to isolate the device by AFM mode and in situ electrical characterization with conductive AFM mode. After developing the multi-mode

  9. Exploiting multimode waveguides for pure fibre-based imaging

    PubMed Central

    Čižmár, 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. PMID:22929784

  10. 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

  11. Affine and deformable registration based on polynomial expansion.

    PubMed

    Farnebäck, Gunnar; Westin, Carl-Fredrik

    2006-01-01

    This paper presents a registration framework based on the polynomial expansion transform. The idea of polynomial expansion is that the image is locally approximated by polynomials at each pixel. Starting with observations of how the coefficients of ideal linear and quadratic polynomials change under translation and affine transformation, algorithms are developed to estimate translation and compute affine and deformable registration between a fixed and a moving image, from the polynomial expansion coefficients. All algorithms can be used for signals of any dimensionality. The algorithms are evaluated on medical data. PMID:17354971

  12. Surface-based registration of liver in ultrasound and CT

    NASA Astrophysics Data System (ADS)

    Dehghan, Ehsan; Lu, Kongkuo; Yan, Pingkun; Tahmasebi, Amir; Xu, Sheng; Wood, Bradford J.; Abi-Jaoudeh, Nadine; Venkatesan, Aradhana; Kruecker, Jochen

    2015-03-01

    Ultrasound imaging is an attractive modality for real-time image-guided interventions. Fusion of US imaging with a diagnostic imaging modality such as CT shows great potential in minimally invasive applications such as liver biopsy and ablation. However, significantly different representation of liver in US and CT turns this image fusion into a challenging task, in particular if some of the CT scans may be obtained without contrast agents. The liver surface, including the diaphragm immediately adjacent to it, typically appears as a hyper-echoic region in the ultrasound image if the proper imaging window and depth setting are used. The liver surface is also well visualized in both contrast and non-contrast CT scans, thus making the diaphragm or liver surface one of the few attractive common features for registration of US and non-contrast CT. We propose a fusion method based on point-to-volume registration of liver surface segmented in CT to a processed electromagnetically (EM) tracked US volume. In this approach, first, the US image is pre-processed in order to enhance the liver surface features. In addition, non-imaging information from the EM-tracking system is used to initialize and constrain the registration process. We tested our algorithm in comparison with a manually corrected vessel-based registration method using 8 pairs of tracked US and contrast CT volumes. The registration method was able to achieve an average deviation of 12.8mm from the ground truth measured as the root mean square Euclidean distance for control points distributed throughout the US volume. Our results show that if the US image acquisition is optimized for imaging of the diaphragm, high registration success rates are achievable.

  13. ME: Multimodal Environment Based on Web Services Architecture

    NASA Astrophysics Data System (ADS)

    Chiara Caschera, Maria; D'Andrea, Alessia; D'Ulizia, Arianna; Ferri, Fernando; Grifoni, Patrizia; Guzzo, Tiziana

    Information, documents and knowledge for each person and for public and private organizations are fundamental in each activity, and they may be the products or services they provide or supply. The daily activities and decision-making processes are usually based on many different pieces of information, which could be handled on PDAs and mobile devices in general, or stored on laptop computers using a lot of different forms, such as spreadsheets, e-mail messages, Web information obtained as the result of a Google search or a query, and so on. Simulating and managing services and information in catastrophic events and emergencies does not represent an exception. This paper describes the Web Services architecture of the Multimodal collaborative knowledge oriented Environment (ME), a platform designed to manage data, information and services for catastrophic events such as earthquakes, floods and dangerous natural phenomena.

  14. 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.

  15. A contour-based approach to multisensor image registration.

    PubMed

    Li, H; Manjunath, B S; Mitra, S K

    1995-01-01

    Image registration is concerned with the establishment of correspondence between images of the same scene. One challenging problem in this area is the registration of multispectral/multisensor images. In general, such images have different gray level characteristics, and simple techniques such as those based on area correlations cannot be applied directly. On the other hand, contours representing region boundaries are preserved in most cases. The authors present two contour-based methods which use region boundaries and other strong edges as matching primitives. The first contour matching algorithm is based on the chain-code correlation and other shape similarity criteria such as invariant moments. Closed contours and the salient segments along the open contours are matched separately. This method works well for image pairs in which the contour information is well preserved, such as the optical images from Landsat and Spot satellites. For the registration of the optical images with synthetic aperture radar (SAR) images, the authors propose an elastic contour matching scheme based on the active contour model. Using the contours from the optical image as the initial condition, accurate contour locations in the SAR image are obtained by applying the active contour model. Both contour matching methods are automatic and computationally quite efficient. Experimental results with various kinds of image data have verified the robustness of the algorithms, which have outperformed manual registration in terms of root mean square error at the control points. PMID:18289982

  16. Improved Image Registration by Sparse Patch-Based Deformation Estimation

    PubMed Central

    Kim, Minjeong; Wu, Guorong; Wang, Qian; Shen, Dinggang

    2014-01-01

    Despite of intensive efforts for decades, deformable image registration is still a challenging problem due to the potential large anatomical differences across individual images, which limits the registration performance. Fortunately, this issue could be alleviated if a good initial deformation can be provided for the two images under registration, which are often termed as the moving subject and the fixed template, respectively. In this work, we present a novel patch-based initial deformation prediction framework for improving the performance of existing registration algorithms. Our main idea is to estimate the initial deformation between subject and template in a patch-wise fashion by using the sparse representation technique. We argue that two image patches should follow the same deformation towards the template image if their patch-wise appearance patterns are similar. To this end, our framework consists of two stages, i.e., the training stage and the application stage. In the training stage, we register all training images to the pre-selected template, such that the deformation of each training image with respect to the template is known. In the application stage, we apply the following four steps to efficiently calculate the initial deformation field for the new test subject: (1) We pick a small number of key points in the distinctive regions of the test subject; (2) For each key point, we extract a local patch and form a coupled appearance-deformation dictionary from training images where each dictionary atom consists of the image intensity patch as well as their respective local deformations; (3) A small set of training image patches in the coupled dictionary are selected to represent the image patch of each subject key point by sparse representation. Then, we can predict the initial deformation for each subject key point by propagating the pre-estimated deformations on the selected training patches with the same sparse representation coefficients. (4) We

  17. 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

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

    NASA Astrophysics Data System (ADS)

    Vallerand, Steve; Kanbara, Masayuki; Yokoya, Naokazu

    2003-05-01

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

  19. 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.

  20. 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.

  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. Point-based registration under a similarity transform

    NASA Astrophysics Data System (ADS)

    West, Jay B.; Fitzpatrick, J. Michael; Batchelor, Philippe G.

    2001-07-01

    This paper investigates the problem of point-based registration under a similarity transformation. This is a transformation that consists of rotation, translation, and isotropic scaling. There are many applications for registration under a similarity transform. First, the medical applications that usually use rigid-body registration may in some cases be improved by using a scale factor to account for particular types of distortion (for example, drift in gradient strength in MR image volumes). Second, similarity transforms are often used in biometrics to analyze and compare different sets of data. It was shown by Gower in 1971 that the choice of scale factor is independent from the choice of rotation and translation. We use a well-known solution for the rotation and translation parts of the transformation, and concentrate on the problem of choosing the scale factor. We examine three different methods of scaling, one of which is a novel maximum likelihood approach. We derive the target registration error and show the bias for each method. We introduce two different models of fiducial localization error, and we show that for one error model, Gower's method of scaling to minimize the sum of squared distances between corresponding points is also the maximum likelihood solution. Under the other error model, however, maximum likelihood leads to a new method of scaling.

  3. A SIFT feature based registration algorithm in automatic seal verification

    NASA Astrophysics Data System (ADS)

    He, Jin; Ding, Xuewen; Zhang, Hao; Liu, Tiegen

    2012-11-01

    A SIFT (Scale Invariant Feature Transform) feature based registration algorithm is presented to prepare for the seal verification, especially for the verification of high quality counterfeit sample seal. The similarities and the spatial relationships between the matched SIFT features are combined for the registration. SIFT features extracted from the binary model seal and sample seal images are matched according to their similarities. The matching rate is used to define the similar sample seal that is similar with its model seal. For the similar sample seal, the false matches are eliminated according to the position relationship. Then the homography between model seal and sample seal is constructed and named HS . The theoretical homography is namedH . The accuracy of registration is evaluated by the Frobenius norm of H-HS . In experiments, translation, filling and rotation transformations are applied to seals with different shapes, stroke number and structures. After registering the transformed seals and their model seals, the maximum value of the Frobenius norm of their H-HS is not more than 0.03. The results prove that this algorithm can accomplish accurate registration, which is invariant to translation, filling, and rotation transformation, and there is no limit to the seal shapes, stroke number and structures.

  4. 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

  5. Multimode evanescent wave-based sensors: enhancement strategies

    NASA Astrophysics Data System (ADS)

    Saaski, Elric W.; Bizak, Michael; Yeatts, Jennifer

    1995-04-01

    There is currently a need for new technologies that are designed specifically for the economical field monitoring of toxins, explosives, and chemical contaminants. The United States has, for example, implemented five regulatory acts to protect its ecologies and its citizens from environmental pollution, and these acts all mandate the monitoring of various chemical contaminants. It is generally accepted that the number of analyses that would be required to meet these new standards would exceed the capacity of all the certified testing labs in the country. New field-portable equipment is needed that can supplement lab-based diagnostic analytical instrumentation, but a continuing problem has been the development of field hardware that can identify and quantify with high specificity a particular species of interest. One of the most promising strategies for performing such narrowly targeted field assays is based on sensors that harness natural immune and protective responses of animals and humans to hone in on a specific compound. This paper discusses the design of a new solid-state portable fluorometer that can be used for the interrogation of a wide range of multimode fiber optic biosensors.

  6. 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

  7. Registration-based initialization during radiation therapy planning

    NASA Astrophysics Data System (ADS)

    Gopalakrishnan, Girish; Mullick, Rakesh

    2007-03-01

    An established challenge in the field of image analysis has been the registration of images having a large initial misalignment. For example in chemo and Radiation Therapy Planning (RTP), there is often a need to register an image delineating a specific anatomy (usually in the surgery position) with that of a whole body image (obtained preoperatively). In such a scenario, there is room for a large misalignment between the two images that are required to be aligned. Large misalignments are traditionally handled in two ways: 1) Semi-automatically with a user initialization or 2) With the help of the origin fields in the image header. The first approach is user dependant and the second method can be used only if the two images are obtained from the same scanner with consistent origins. Our methodology extends a typical registration framework by selecting components that are capable of searching a large parameter space without settling on local optima. We have used an optimizer that is based on an Evolutionary Scheme along with an information theory based similarity metric that can address these needs. The attempt in this study is to convert a large misalignment problem to a small misalignment problem that can then be handled using application specific registration algorithms. Further improvements along local areas can be obtained by subjecting the image to a non-rigid transformation. We have successfully registered the following pairs of images without any user initialization: CTAC - simCT (neuro, lungs); MRPET/ CT (neuro, liver); T2-SPGR (neuro).

  8. Multi-modal image matching based on local frequency information

    NASA Astrophysics Data System (ADS)

    Liu, Xiaochun; Lei, Zhihui; Yu, Qifeng; Zhang, Xiaohu; Shang, Yang; Hou, Wang

    2013-12-01

    This paper challenges the issue of matching between multi-modal images with similar physical structures but different appearances. To emphasize the common structural information while suppressing the illumination and sensor-dependent information between multi-modal images, two image representations namely Mean Local Phase Angle (MLPA) and Frequency Spread Phase Congruency (FSPC) are proposed by using local frequency information in Log-Gabor wavelet transformation space. A confidence-aided similarity (CAS) that consists of a confidence component and a similarity component is designed to establish the correspondence between multi-modal images. The two representations are both invariant to contrast reversal and non-homogeneous illumination variation, and without any derivative or thresholding operation. The CAS that integrates MLPA with FSPC tightly instead of treating them separately can more weight the common structures emphasized by FSPC, and therefore further eliminate the influence of different sensor properties. We demonstrate the accuracy and robustness of our method by comparing it with those popular methods of multi-modal image matching. Experimental results show that our method improves the traditional multi-modal image matching, and can work robustly even in quite challenging situations (e.g. SAR & optical image).

  9. 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

  10. 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…

  11. 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

  12. 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

  13. 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.

  14. Research based on the SoPC platform of feature-based image registration

    NASA Astrophysics Data System (ADS)

    Shi, Yue-dong; Wang, Zhi-hui

    2015-12-01

    This paper focuses on the study of implementing feature-based image registration by System on a Programmable Chip (SoPC) hardware platform. We solidify the image registration algorithm on the FPGA chip, in which embedded soft core processor Nios II can speed up the image processing system. In this way, we can make image registration technology get rid of the PC. And, consequently, this kind of technology will be got an extensive use. The experiment result indicates that our system shows stable performance, particularly in terms of matching processing which noise immunity is good. And feature points of images show a reasonable distribution.

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

    PubMed

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

    2006-06-01

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

  16. Edge-Based Registration for Airborne Imagery and LIDAR Data

    NASA Astrophysics Data System (ADS)

    Chen, L. C.; Lo, C. Y.

    2012-07-01

    Aerial imagery and LIDAR points are two important data sources for building reconstruction in a geospatial area. Aerial imagery implies building contours with planimetric features; LIDAR data explicitly represent building geometries using three-dimensional discrete point clouds. Data integration may take advantage of merits from two data sources in building reconstruction and change detection. However, heterogeneous data may contain a relative displacement because of different sensors and the capture time. To reduce this displacement, data registration should be an essential step. Therefore, this investigation proposes an edge-based approach to register these two data sets in three parts: (1) data preprocessing; (2) feature detection; and (3) data registration. The first step rasterizes laser point clouds into a pseudo-grid digital surface model (PDSM), which describes the relief with the original elevation information. The second step implements topological analyses to detect image edges and three-dimensional structure lines from the aerial image and PDSM. These detected features provide the initial positions of building shapes for registration. The third part registers these two data sets in Hough space to compensate for the displacement. Because each building may have prominent geometric structures, the proposed scheme transforms these two groups of edges, and estimates the correspondence by the Hough distribution. The following procedure then iteratively compares two groups of Hough patterns, which are from an aerial image and LIDAR data. This iterative procedure stops when the displacement is within a threshold. The test area is located in Taipei City, Taiwan. DMC system captured the aerial image with 18-cm spatial resolution. The LIDAR data were scanned with a 10-point density per square meter using the Leica ALS50 system. This study proposed a 50 cm spatial resolution of PDSM, which is slightly larger than the point spacing. The experiment selected two

  17. Prediction-based registration: an automated multi-INT registration algorithm

    NASA Astrophysics Data System (ADS)

    Purman, Benjamin; Spencer, James; Conk, Jennifer M.

    2004-09-01

    This paper presents an algorithm for the automatic georegistration of electro-optical (EO) and synthetic aperture radar (SAR) imagery intelligence (IMINT). The algorithm uses a scene reference model in a global coordinate frame to register the incoming IMINT, or mission image. Auxiliary data from the mission image and this model predict a synthetic reference image of a scene at the same collection geometry as the mission image. This synthetic image provides a traceback structure relating the synthetic reference image to the scene model. A correlation matching technique is used to register the mission image to the synthetic reference image. Once the matching has been completed, mission image pixels can be transformed into the corresponding synthetic reference image. Using the traceback structure associated with the synthetic reference image, these pixels can then be transformed into the scene model space. Since the scene model space exists in a global coordinate frame, the mission image has been georegistered. This algorithm is called Prediction-Based Registration (PBR). There are a number of advantages to the PBR approach. First, the transformation from image space to scene model space is computed as a 3D to 2D transformation. This avoids solving the ill-posed problem of directly transforming a 2D image into 3D space. The generation of a synthetic reference simplifies the image matching process by creating the synthetic reference at the same geometry as the mission image. Further, dissimilar sensor phenomenologies are accounted for by using the appropriate sensor model. This allows sensor platform and image formation errors to be accounted for in their own domain when multiple sensors are being registered.

  18. 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.

  19. 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.

  20. Ridge-based retinal image registration algorithm involving OCT fundus images

    NASA Astrophysics Data System (ADS)

    Li, Ying; Gregori, Giovanni; Knighton, Robert W.; Lujan, Brandon J.; Rosenfeld, Philip J.; Lam, Byron L.

    2011-03-01

    This paper proposes an algorithm for retinal image registration involving OCT fundus images (OFIs). The first application of the algorithm is to register OFIs with color fundus photographs; such registration between multimodal retinal images can help correlate features across imaging modalities, which is important for both clinical and research purposes. The second application is to perform the montage of several OFIs, which allows us to construct 3D OCT images over a large field of view out of separate OCT datasets. We use blood vessel ridges as registration features. The brute force search and an Iterative Closest Point (ICP) algorithm are employed for image pair registration. Global alignment to minimize the distance between matching pixel pairs is used to obtain the montage of OFIs. Quality of OFIs is the big limitation factor of the registration algorithm. In the first experiment, the effect of manual OFI enhancement on registration was evaluated for the affine model on 11 image pairs from diseased eyes. The average root mean square error (RMSE) decreases from 58 μm to 40 μm. This indicates that the registration algorithm is robust to manual enhancement. In the second experiment for the montage of OFIs, the algorithm was tested on 6 sets from healthy eyes and 6 sets from diseased eyes, each set having 8 partially overlapping SD-OCT images. Visual evaluation showed that the montage performance was acceptable for normal cases, and not good for abnormal cases due to low visibility of blood vessels. The average RMSE for a typical montage case from a healthy eye is 2.3 pixels (69 μm).

  1. 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%.

  2. Improved interframe registration based nonuniformity correction for focal plane arrays

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

    In this paper, an improved interframe registration based nonuniformity correction algorithm for focal plane arrays is proposed. The method simultaneously estimates detector parameters and carries out the nonuniformity correction by minimizing the mean square error between the two properly registered image frames. A new masked phase correlation algorithm is introduced to obtain reliable shift estimates in the presence of fixed pattern noise. The use of an outliers exclusion scheme, together with a variable step size strategy, could not only promote the correction precision considerably, but also eliminate ghosting artifacts effectively. The performance of the proposed algorithm is evaluated with clean infrared image sequences with simulated nonuniformity and real pattern noise. We also apply the method to a real-time imaging system to show how effective it is in reducing noise and the ghosting artifacts.

  3. Registration of point cloud data for HDD stamped base inspection

    NASA Astrophysics Data System (ADS)

    Suh, Sungho; Cho, Hansang

    2015-09-01

    As a part of the HDD manufacturing process, HDD stamped base, an exterior container, is one of the most essential components in which various parts become assembled to compose a hard disk drive (HDD). Height errors that are caused by pressing, breaking or cracking can occur on the base, because it is designed by a stamping method. In order to detect the height errors, the inspection process is essential in the production fields. In the current industry, CMM (Coordinate Measurement Machine) is one of the representative machines that inspect certain regions on the product. The machine probes a designated point by an operator and judges the defect by comparing the height of the point to the originally designed height. However, the method takes much time to inspect each designated point resulting in a total of 17 minutes. In order to reduce the total inspection time, we propose an inspection method using 3D point cloud data acquired from a holographic sensor. To compare the height from acquired 3D point cloud data with the one from the originally designed CAD data, the exact point cloud registration is important. There are differences between 2D image registration and 3D point cloud registration, such as translation on each plane, rotation, tilt, and nonlinear transformations. The relationship between the acquired 3D point cloud data and the originally designed CAD data can be obtained by projective transformation. If the projective transformation matrix between the two is obtained, 3D point cloud data registration can be performed. In order to calculate 3D projective transformation matrix, corresponding points between 3D point cloud data and CAD data are required. To find the corresponding points, we use the height map which is projected from 3D point cloud data onto XY plane. The height map has pixel intensity from the height value of each point. If the height maps from 3D point cloud data and CAD data are matched, corresponding points can be estimated. As one of the

  4. 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.

  5. 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)

  6. 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.

  7. 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

  8. 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…

  9. 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.…

  10. Multimodal Media Center Interface Based on Speech, Gestures and Haptic Feedback

    NASA Astrophysics Data System (ADS)

    Turunen, Markku; Hakulinen, Jaakko; Hella, Juho; Rajaniemi, Juha-Pekka; Melto, Aleksi; Mäkinen, Erno; Rantala, Jussi; Heimonen, Tomi; Laivo, Tuuli; Soronen, Hannu; Hansen, Mervi; Valkama, Pellervo; Miettinen, Toni; Raisamo, Roope

    We present a multimodal media center interface based on speech input, gestures, and haptic feedback (hapticons). In addition, the application includes a zoomable context + focus GUI in tight combination with speech output. The resulting interface is designed for and evaluated with different user groups, including visually and physically impaired users. Finally, we present the key results from its user evaluation and public pilot studies.

  11. 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…

  12. 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…

  13. 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…

  14. 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. PMID:26978821

  15. Multimodal Therapy.

    ERIC Educational Resources Information Center

    Lazarus, Arnold A.

    The multimodal therapy (MMT) approach provides a framework that facilitates systematic treatment selection in a broad-based, comprehensive and yet highly focused manner. It respects science, and data driven findings, and endeavors to use empirically supported methods when possible. Nevertheless, it recognizes that many issues still fall into the…

  16. Robust Adaptive Principal Component Analysis Based on Intergraph Matrix for Medical Image Registration

    PubMed Central

    Xiao, Jinjun; Li, Min; Zhang, Haipeng

    2015-01-01

    This paper proposes a novel robust adaptive principal component analysis (RAPCA) method based on intergraph matrix for image registration in order to improve robustness and real-time performance. The contributions can be divided into three parts. Firstly, a novel RAPCA method is developed to capture the common structure patterns based on intergraph matrix of the objects. Secondly, the robust similarity measure is proposed based on adaptive principal component. Finally, the robust registration algorithm is derived based on the RAPCA. The experimental results show that the proposed method is very effective in capturing the common structure patterns for image registration on real-world images. PMID:25960739

  17. 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

  18. 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

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

    NASA Astrophysics Data System (ADS)

    Han, Lianghao; Hawkes, David; Barratt, Dean

    2014-03-01

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

  20. 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.

  1. Co-Registration Airborne LIDAR Point Cloud Data and Synchronous Digital Image Registration Based on Combined Adjustment

    NASA Astrophysics Data System (ADS)

    Yang, Z. H.; Zhang, Y. S.; Zheng, T.; Lai, W. B.; Zou, Z. R.; Zou, B.

    2016-06-01

    Aim at the problem of co-registration airborne laser point cloud data with the synchronous digital image, this paper proposed a registration method based on combined adjustment. By integrating tie point, point cloud data with elevation constraint pseudo observations, using the principle of least-squares adjustment to solve the corrections of exterior orientation elements of each image, high-precision registration results can be obtained. In order to ensure the reliability of the tie point, and the effectiveness of pseudo observations, this paper proposed a point cloud data constrain SIFT matching and optimizing method, can ensure that the tie points are located on flat terrain area. Experiments with the airborne laser point cloud data and its synchronous digital image, there are about 43 pixels error in image space using the original POS data. If only considering the bore-sight of POS system, there are still 1.3 pixels error in image space. The proposed method regards the corrections of the exterior orientation elements of each image as unknowns and the errors are reduced to 0.15 pixels.

  2. 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.

  3. Design and fabrication of multimode interference couplers based on digital micro-mirror system

    NASA Astrophysics Data System (ADS)

    Wu, Sumei; He, Xingdao; Shen, Chenbo

    2008-03-01

    Multimode interference (MMI) couplers, based on the self-imaging effect (SIE), are accepted popularly in integrated optics. According to the importance of MMI devices, in this paper, we present a novel method to design and fabricate MMI couplers. A technology of maskless lithography to make MMI couplers based on a smart digital micro-mirror device (DMD) system is proposed. A 1×4 MMI device is designed as an example, which shows the present method is efficient and cost-effective.

  4. 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

  5. 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.

  6. Elastic registration of prostate MR images based on state estimation of dynamical systems

    NASA Astrophysics Data System (ADS)

    Marami, Bahram; Ghoul, Suha; Sirouspour, Shahin; Capson, David W.; Davidson, Sean R. H.; Trachtenberg, John; Fenster, Aaron

    2014-03-01

    Magnetic resonance imaging (MRI) is being increasingly used for image-guided biopsy and focal therapy of prostate cancer. A combined rigid and deformable registration technique is proposed to register pre-treatment diagnostic 3T magnetic resonance (MR) images, with the identified target tumor(s), to the intra-treatment 1.5T MR images. The pre-treatment 3T images are acquired with patients in strictly supine position using an endorectal coil, while 1.5T images are obtained intra-operatively just before insertion of the ablation needle with patients in the lithotomy position. An intensity-based registration routine rigidly aligns two images in which the transformation parameters is initialized using three pairs of manually selected approximate corresponding points. The rigid registration is followed by a deformable registration algorithm employing a generic dynamic linear elastic deformation model discretized by the finite element method (FEM). The model is used in a classical state estimation framework to estimate the deformation of the prostate based on a similarity metric between pre- and intra-treatment images. Registration results using 10 sets of prostate MR images showed that the proposed method can significantly improve registration accuracy in terms of target registration error (TRE) for all prostate substructures. The root mean square (RMS) TRE of 46 manually identified fiducial points was found to be 2.40+/-1.20 mm, 2.51+/-1.20 mm, and 2.28+/-1.22mm for the whole gland (WG), central gland (CG), and peripheral zone (PZ), respectively after deformable registration. These values are improved from 3.15+/-1.60 mm, 3.09+/-1.50 mm, and 3.20+/-1.73mm in the WG, CG and PZ, respectively resulted from rigid registration. Registration results are also evaluated based on the Dice similarity coefficient (DSC), mean absolute surface distances (MAD) and maximum absolute surface distances (MAXD) of the WG and CG in the prostate images.

  7. 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%.

  8. 3D affine registration using teaching-learning based optimization

    NASA Astrophysics Data System (ADS)

    Jani, Ashish; Savsani, Vimal; Pandya, Abhijit

    2013-09-01

    3D image registration is an emerging research field in the study of computer vision. In this paper, two effective global optimization methods are considered for the 3D registration of point clouds. Experiments were conducted by applying each algorithm and their performance was evaluated with respect to rigidity, similarity and affine transformations. Comparison of algorithms and its effectiveness was tested for the average performance to find the global solution for minimizing the error in the terms of distance between the model cloud and the data cloud. The parameters for the transformation matrix were considered as the design variables. Further comparisons of the considered methods were done for the computational effort, computational time and the convergence of the algorithm. The results reveal that the use of TLBO was outstanding for image processing application involving 3D registration. [Figure not available: see fulltext.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  11. Nonrigid Medical Image Registration Based on Mesh Deformation Constraints

    PubMed Central

    Qiu, TianShuang; Guo, DongMei

    2013-01-01

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

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

    PubMed

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

    2014-11-21

    A unified framework for automatic non-rigid 3D-3D and 3D-2D registration of medical images with static and dynamic deformations is proposed in this paper. The problem of non-rigid image registration is approached as a classical state estimation problem using a generic deformation model for the soft tissue. The registration technique employs a dynamic linear elastic continuum mechanics model of the tissue deformation, which is discretized using the finite element method. In the proposed method, the registration is achieved through a Kalman-like filtering process, which incorporates information from the deformation model and a vector of observation prediction errors computed from an intensity-based similarity/distance metric between images. With this formulation, single and multiple-modality, 3D-3D and 3D-2D image registration problems can all be treated within the same framework. The performance of the proposed registration technique was evaluated in a number of different registration scenarios. First, 3D magnetic resonance (MR) images of uncompressed and compressed breast tissue were co-registered. 3D MR images of the uncompressed breast tissue were also registered to a sequence of simulated 2D interventional MR images of the compressed breast. Finally, the registration algorithm was employed to dynamically track a target sub-volume inside the breast tissue during the process of the biopsy needle insertion based on registering pre-insertion 3D MR images to a sequence of real-time simulated 2D interventional MR images. Registration results indicate that the proposed method can be effectively employed for the registration of medical images in image-guided procedures, such as breast biopsy in which the tissue undergoes static and dynamic deformations. PMID:25350234

  13. 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.

  14. Image fusion of Ultrasound Computer Tomography volumes with X-ray mammograms using a biomechanical model based 2D/3D registration.

    PubMed

    Hopp, T; Duric, N; Ruiter, N V

    2015-03-01

    Ultrasound Computer Tomography (USCT) is a promising breast imaging modality under development. Comparison to a standard method like mammography is essential for further development. Due to significant differences in image dimensionality and compression state of the breast, correlating USCT images and X-ray mammograms is challenging. In this paper we present a 2D/3D registration method to improve the spatial correspondence and allow direct comparison of the images. It is based on biomechanical modeling of the breast and simulation of the mammographic compression. We investigate the effect of including patient-specific material parameters estimated automatically from USCT images. The method was systematically evaluated using numerical phantoms and in-vivo data. The average registration accuracy using the automated registration was 11.9mm. Based on the registered images a method for analysis of the diagnostic value of the USCT images was developed and initially applied to analyze sound speed and attenuation images based on X-ray mammograms as ground truth. Combining sound speed and attenuation allows differentiating lesions from surrounding tissue. Overlaying this information on mammograms, combines quantitative and morphological information for multimodal diagnosis. PMID:25456144

  15. A Multistage Approach for Image Registration.

    PubMed

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

    2016-09-01

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

  16. 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

  17. 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. PMID:25071972

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

    PubMed

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

    2014-03-01

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

  19. Temperature and refractive index sensing characteristics of an MZI-based multimode fiber-dispersion compensation fiber-multimode fiber structure

    NASA Astrophysics Data System (ADS)

    Sun, Hao; Yang, Shen; Zhang, Jing; Rong, Qiangzhou; Liang, Lei; Xu, Qinfang; Xiang, Guanghua; Feng, Dingyi; Du, Yanying; Feng, Zhongyao; Qiao, Xueguang; Hu, Manli

    2012-12-01

    We proposed an optical fiber sensor with simple multimode fiber (MMF)-dispersion compensation fiber (DCF)-multimode fiber structure based on Mach-Zehnder Interferometer (MZI) and researched its temperature and refractive index (RI) sensing characteristics. The sensing principle is based on the interference between core and cladding modes of DCF due to the large core diameter mismatch. Spectral analyses demonstrate that the transmission spectrum is mainly formed by the interference between the dominant excited cladding mode and core modes. The experimental results show that the proposed sensor has high temperature sensitivity of 0.118 nm/°C in the range of 20-250 °C and RI sensitivity of 66.32 nm/RIU within the linear sensing range of 1.33-1.39 RIU. Therefore, the characteristics of compact size, low cost, easy fabrication, high sensitivities, and good anti-interference ability make this sensor have extensive application prospects.

  20. 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. PMID:25214889

  1. 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

  2. Automatic registration of large-scale urban scene point clouds based on semantic feature points

    NASA Astrophysics Data System (ADS)

    Yang, Bisheng; Dong, Zhen; Liang, Fuxun; Liu, Yuan

    2016-03-01

    Point clouds collected by terrestrial laser scanning (TLS) from large-scale urban scenes contain a wide variety of objects (buildings, cars, pole-like objects, and others) with symmetric and incomplete structures, and relatively low-textured surfaces, all of which pose great challenges for automatic registration between scans. To address the challenges, this paper proposes a registration method to provide marker-free and multi-view registration based on the semantic feature points extracted. First, the method detects the semantic feature points within a detection scheme, which includes point cloud segmentation, vertical feature lines extraction and semantic information calculation and finally takes the intersections of these lines with the ground as the semantic feature points. Second, the proposed method matches the semantic feature points using geometrical constraints (3-point scheme) as well as semantic information (category and direction), resulting in exhaustive pairwise registration between scans. Finally, the proposed method implements multi-view registration by constructing a minimum spanning tree of the fully connected graph derived from exhaustive pairwise registration. Experiments have demonstrated that the proposed method performs well in various urban environments and indoor scenes with the accuracy at the centimeter level and improves the efficiency, robustness, and accuracy of registration in comparison with the feature plane-based methods.

  3. Direct estimation of nonrigid registrations with image-based self-occlusion reasoning.

    PubMed

    Gay-Bellile, Vincent; Bartoli, Adrien; Sayd, Patrick

    2010-01-01

    The registration problem for images of a deforming surface has been well studied. External occlusions are usually well handled. In 2D image-based registration, self-occlusions are more challenging. Consequently, the surface is usually assumed to be only slightly self-occluding. This paper is about image-based nonrigid registration with self-occlusion reasoning. A specific framework explicitly modeling self-occlusions is proposed. It is combined with an intensity-based, "direct" data term for registration. Self-occlusions are detected as shrinkage areas in the 2D warp. Experimental results on several challenging data sets show that our approach successfully registers images with self-occlusions while effectively detecting the self-occluded regions. PMID:19926901

  4. IR and visual image registration based on mutual information and PSO-Powell algorithm

    NASA Astrophysics Data System (ADS)

    Zhuang, Youwen; Gao, Kun; Miu, Xianghu

    2014-11-01

    Infrared and visual image registration has a wide application in the fields of remote sensing and military. Mutual information (MI) has proved effective and successful in infrared and visual image registration process. To find the most appropriate registration parameters, optimal algorithms, such as Particle Swarm Optimization (PSO) algorithm or Powell search method, are often used. The PSO algorithm has strong global search ability and search speed is fast at the beginning, while the weakness is low search performance in late search stage. In image registration process, it often takes a lot of time to do useless search and solution's precision is low. Powell search method has strong local search ability. However, the search performance and time is more sensitive to initial values. In image registration, it is often obstructed by local maximum and gets wrong results. In this paper, a novel hybrid algorithm, which combined PSO algorithm and Powell search method, is proposed. It combines both advantages that avoiding obstruction caused by local maximum and having higher precision. Firstly, using PSO algorithm gets a registration parameter which is close to global minimum. Based on the result in last stage, the Powell search method is used to find more precision registration parameter. The experimental result shows that the algorithm can effectively correct the scale, rotation and translation additional optimal algorithm. It can be a good solution to register infrared difference of two images and has a greater performance on time and precision than traditional and visible images.

  5. 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.

  6. 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. PMID:26074561

  7. 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.

  8. Improved DTI registration allows voxel-based analysis that outperforms tract-based spatial statistics.

    PubMed

    Schwarz, Christopher G; Reid, Robert I; Gunter, Jeffrey L; Senjem, Matthew L; Przybelski, Scott A; Zuk, Samantha M; Whitwell, Jennifer L; Vemuri, Prashanthi; Josephs, Keith A; Kantarci, Kejal; Thompson, Paul M; Petersen, Ronald C; Jack, Clifford R

    2014-07-01

    Tract-Based Spatial Statistics (TBSS) is a popular software pipeline to coregister sets of diffusion tensor Fractional Anisotropy (FA) images for performing voxel-wise comparisons. It is primarily defined by its skeleton projection step intended to reduce effects of local misregistration. A white matter "skeleton" is computed by morphological thinning of the inter-subject mean FA, and then all voxels are projected to the nearest location on this skeleton. Here we investigate several enhancements to the TBSS pipeline based on recent advances in registration for other modalities, principally based on groupwise registration with the ANTS-SyN algorithm. We validate these enhancements using simulation experiments with synthetically-modified images. When used with these enhancements, we discover that TBSS's skeleton projection step actually reduces algorithm accuracy, as the improved registration leaves fewer errors to warrant correction, and the effects of this projection's compromises become stronger than those of its benefits. In our experiments, our proposed pipeline without skeleton projection is more sensitive for detecting true changes and has greater specificity in resisting false positives from misregistration. We also present comparative results of the proposed and traditional methods, both with and without the skeleton projection step, on three real-life datasets: two comparing differing populations of Alzheimer's disease patients to matched controls, and one comparing progressive supranuclear palsy patients to matched controls. The proposed pipeline produces more plausible results according to each disease's pathophysiology. PMID:24650605

  9. 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.

  10. An automatic registration algorithm for the scattered point clouds based on the curvature feature

    NASA Astrophysics Data System (ADS)

    He, Bingwei; Lin, Zeming; Li, Y. F.

    2013-03-01

    Object modeling by the registration of multiple range images has important applications in reverse engineering and computer vision. In order to register multi-view scattered point clouds, a novel curvature-based automatic registration algorithm is proposed in this paper, which can solve the registration problem with partial overlapping point clouds. For two sets of scattered point clouds, the curvature of each point is estimated by using the quadratic surface fitting method. The feature points that have the maximum local curvature variations are then extracted. The initial matching points are acquired by computing the Hausdorff distance of curvature, and then the circumference shape feature of the local surface is used to obtain the accurate matching points from the initial matching points. Finally, the rotation and translation matrix are estimated by the quaternion, and an iterative algorithm is used to improve the registration accuracy. Experimental results show that the algorithm is effective.

  11. Myocardial motion estimation in tagged MR sequences by using alphaMI-based non rigid registration.

    PubMed

    Oubel, E; Tobon-Gomez, C; Hero, A O; Frangi, A F

    2005-01-01

    Tagged Magnetic Resonance Imaging (MRI) is currently the reference MR modality for myocardial motion and strain analysis. NMI-based non rigid registration has proven to be an accurate method to retrieve cardiac deformation fields. The use of alphaMI permits higher dimensional features to be implemented in myocardial deformation estimation through image registration. This paper demonstrates that this is feasible with a set of Haar wavelet features of high dimension. While we do not demonstrate performance improvement for this set of features, there is no significant degradation as compared to implementing the registration method with the traditional NMI metric. We use Entropic Spanning Graphs (ESGs) to estimate the alphaMI of the wavelet feature vectors WFVs since this is not possible with histograms. To the best of our knowledge, this is the first time that ESGs are used for non rigid registration. PMID:16685969

  12. Satellite image registration based on the geometrical arrangement of objects

    NASA Astrophysics Data System (ADS)

    Bartl, Renate; Schneider, Werner

    1995-11-01

    The knowledge of the geometrical relationship between images is a prerequisite for registration. Assuming a conformal affine transformation, 4 transformation parameters have to be determined. This is done on the basis of the geometrical arrangement of characteristic objects extracted from images in a preprocessing step, for example a land use classification yielding forest, pond, or urban regions. The algorithm introduced establishes correspondence between (centers of gravity of) objects by building and matching so-called ANGLE CHAINS, a linear structure for representing a geometric (2D) arrangement. An example with satellite imagery illustrates the usefulness of the algorithm.

  13. 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.

  14. Subject Based Registration for Individualized Analysis of Diffusion Tensor MRI

    PubMed Central

    Suri, Asif K.; Fleysher, Roman; Lipton, Michael L.

    2015-01-01

    Registration of subject and control brains to a common anatomical space or template is the basis for quantitatively delineating regions of abnormality in an individual brain. Normally, a brain atlas is chosen as the template. Limitations in the registration process result in persistent differences between individual subject brains and template, which can be a source of error in an analysis. We propose a new approach to the registration process where the subject of interest is the registration template. Through this change, we eliminate errors due to differences between a brain template and a subject’s brain. We applied this method to the analysis of FA values derived from DTI data of 20 individual mTBI patients as compared to 48 healthy controls. Subject-centered analysis resulted in identification of significantly fewer regions of abnormally low FA compared to two separate atlas-centered analyses, with subject-centered abnormalities essentially representing the common subset of abnormal low FA regions detected by the two atlas-centered methods. Whereas each atlas-centered approach demonstrated abnormalities in nearly every subject (19/20 and 20/20), the subject-centered approach demonstrated abnormalities in fewer than half the subjects (9/20). This reduction of diffusion abnormalities observed using the subject-centered approach is due to elimination of misregistration errors that occur when registering the subject of interest to a template. Evaluation of atlas-centered analyses demonstrated that 9.8% to 13.3% of subject GM and CSF was misregistered onto the WM of the brain atlas, resulting in the observation of additional low FA clusters compared to the subject-centered approach. Without careful evaluation, these misregistrations could be misinterpreted as pathology. An additional benefit of the subject-centered approach is that diffusion abnormalities can now be visualized directly in the subject’s anatomical space, rather than interpolating results from

  15. Entanglement-based continuous-variable quantum key distribution with multimode states and detectors

    NASA Astrophysics Data System (ADS)

    Usenko, Vladyslav C.; Ruppert, Laszlo; Filip, Radim

    2014-12-01

    Secure quantum key distribution with multimode Gaussian entangled states and multimode homodyne detectors is proposed. In general the multimode character of both the sources of entanglement and the homodyne detectors can cause a security break even for a perfect channel when trusted parties are unaware of the detection structure. Taking into account the multimode structure and potential leakage of information from a homodyne detector reduces the loss of security to some extent. We suggest the symmetrization of the multimode sources of entanglement as an efficient method allowing us to fully recover the security irrespectively to multimode structure of the homodyne detectors. Further, we demonstrate that by increasing the number of the fluctuating but similar source modes the multimode protocol stabilizes the security of the quantum key distribution. The result opens the pathway towards quantum key distribution with multimode sources and detectors.

  16. 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. PMID:24819664

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. Model-based registration of ex vivo and in vivo MRI of the prostate using elastography.

    PubMed

    Nir, Guy; Sahebjavaher, Ramin S; Kozlowski, Piotr; Chang, Silvia D; Sinkus, Ralph

    2013-06-01

    Registration of histopathology to in vivo magnetic resonance imaging (MRI) of the prostate is an important task that can be used to optimize in vivo imaging for cancer detection. Such registration is challenging due to the change in volume and deformation of the prostate during excision and fixation. One approach towards this problem involves the use of an ex vivo MRI of the excised prostate specimen, followed by in vivo to ex vivo MRI registration of the prostate. We propose a novel registration method that uses a patient-specific biomechanical model acquired using magnetic resonance elastography to deform the in vivo volume and match it to the surface of the ex vivo specimen. The forces that drive the deformations are derived from a region-based energy, with the elastic potential used for regularization. The incorporation of elastography data into the registration framework allows inhomogeneous elasticity to be assigned to the in vivo volume. We show that such inhomogeneity improves the registration results by providing a physical regularization of the deformation map. The method is demonstrated and evaluated on six clinical cases. PMID:23475353

  2. Strategy for analysis of flow diverting devices based on multi-modality image-based modeling

    PubMed Central

    Cebral, Juan R.; Mut, Fernando; Raschi, Marcelo; Ding, Yong-Hong; Kadirvel, Ramanathan; Kallmes, David

    2014-01-01

    Quantification and characterization of the hemodynamic environment created after flow diversion treatment of cerebral aneurysms is important to understand the effects of flow diverters and their interactions with the biology of the aneurysm wall and the thrombosis process that takes place subsequently. This paper describes the construction of multi-modality image-based subject-specific CFD models of experimentally created aneurysms in rabbits and subsequently treated with flow diverters. Briefly, anatomical models were constructed from 3D rotational angiography images, flow conditions were derived from Doppler ultrasound measurements, stent models were created and virtually deployed, and the results were compared to in vivo digital subtraction angiography and Doppler ultrasound images. The models were capable of reproducing in vivo observations, including velocity waveforms measured in the parent artery, peak velocity values measured in the aneurysm, and flow structures observed with digital subtraction angiography before and after deployment of flow diverters. The results indicate that regions of aneurysm occlusion after flow diversion coincide with slow and smooth flow patterns, while regions still permeable at the time of animal sacrifice were observed in parts of the aneurysm exposed to larger flow activity, i.e. higher velocities, more swirling and more complex flow structures. PMID:24719392

  3. Strategy for analysis of flow diverting devices based on multi-modality image-based modeling.

    PubMed

    Cebral, Juan R; Mut, Fernando; Raschi, Marcelo; Ding, Yong-Hong; Kadirvel, Ramanathan; Kallmes, David

    2014-10-01

    Quantification and characterization of the hemodynamic environment created after flow diversion treatment of cerebral aneurysms is important to understand the effects of flow diverters and their interactions with the biology of the aneurysm wall and the thrombosis process that takes place subsequently. This paper describes the construction of multi-modality image-based subject-specific CFD models of experimentally created aneurysms in rabbits and subsequently treated with flow diverters. Briefly, anatomical models were constructed from 3D rotational angiography images, flow conditions were derived from Doppler ultrasound measurements, stent models were created and virtually deployed, and the results were compared with in vivo digital subtraction angiography and Doppler ultrasound images. The models were capable of reproducing in vivo observations, including velocity waveforms measured in the parent artery, peak velocity values measured in the aneurysm, and flow structures observed with digital subtraction angiography before and after deployment of flow diverters. The results indicate that regions of aneurysm occlusion after flow diversion coincide with slow and smooth flow patterns, whereas regions still permeable at the time of animal sacrifice were observed in parts of the aneurysm exposed to larger flow activity, that is, higher velocities, more swirling, and more complex flow structures. PMID:24719392

  4. 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.

  5. Multimodal Speaker Verification Based on Electroglottograph Signal and Glottal Activity Detection

    NASA Astrophysics Data System (ADS)

    Ćirović, Zoran; Milosavljević, Milan; Banjac, Zoran

    2010-12-01

    To achieve robust speaker verification, we propose a multimodal method which includes additional nonaudio features and glottal activity detector. As a nonaudio sensor an electroglottograph (EGG) is applied. Parameters of EGG signal are used to augment conventional audio feature vector. Algorithm for EGG parameterization is based on the shape of the idealized waveform and glottal activity detector. We compare our algorithm with conventional one in the term of verification accuracy in high noise environment. All experiments are performed using Gaussian Mixture Model recognition system. Obtained results show a significant improvement of the text-independent speaker verification in high noise environment and opportunity for further improvements in this area.

  6. Design and implementation of software defined radio based multi-mode transceiver

    NASA Astrophysics Data System (ADS)

    Fang, Yixiang; Zhou, Jinhe

    2013-03-01

    In this paper, we aim at the study on multi-mode transceiver based on software defined radio(SDR). Multi-rate signal processing and polyphase filtering technique are both applied in the design and implementation of the transceiver. Simplified FFT butterfly algorithm has been employed in the polyphase filter design as well. Simulation results illustrate that BER performance can be improved by adopting the SDR proposed in this paper. Especially, it has obvious advantages at low SNR. Meanwhile, improved filter design scheme has much more predominant in-band and out-ofband performance.

  7. Automatic 3D image registration using voxel similarity measurements based on a genetic algorithm

    NASA Astrophysics Data System (ADS)

    Huang, Wei; Sullivan, John M., Jr.; Kulkarni, Praveen; Murugavel, Murali

    2006-03-01

    An automatic 3D non-rigid body registration system based upon the genetic algorithm (GA) process is presented. The system has been successfully applied to 2D and 3D situations using both rigid-body and affine transformations. Conventional optimization techniques and gradient search strategies generally require a good initial start location. The GA approach avoids the local minima/maxima traps of conventional optimization techniques. Based on the principles of Darwinian natural selection (survival of the fittest), the genetic algorithm has two basic steps: 1. Randomly generate an initial population. 2. Repeated application of the natural selection operation until a termination measure is satisfied. The natural selection process selects individuals based on their fitness to participate in the genetic operations; and it creates new individuals by inheritance from both parents, genetic recombination (crossover) and mutation. Once the termination criteria are satisfied, the optimum is selected from the population. The algorithm was applied on 2D and 3D magnetic resonance images (MRI). It does not require any preprocessing such as threshold, smoothing, segmentation, or definition of base points or edges. To evaluate the performance of the GA registration, the results were compared with results of the Automatic Image Registration technique (AIR) and manual registration which was used as the gold standard. Results showed that our GA implementation was a robust algorithm and gives very close results to the gold standard. A pre-cropping strategy was also discussed as an efficient preprocessing step to enhance the registration accuracy.

  8. 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. PMID:26771247

  9. 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.

  10. MSM: a new flexible framework for Multimodal Surface Matching☆

    PubMed Central

    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

    2014-01-01

    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 unconstrained by 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 datasets. PMID:24939340

  11. 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. PMID:24939340

  12. 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.

  13. System architecture for intraoperative ultrasound registration in image-based medical navigation.

    PubMed

    Dekomien, Claudia; Roeschies, Benjamin; Winter, Susanne

    2012-08-01

    Medical navigation systems for orthopedic surgery are becoming more and more important with the increasing proportion of older people in the population, and hence the increasing incidence of diseases of the musculoskeletal system. The central problem for such systems is the exact transformation of the preoperatively acquired datasets to the coordinate system of the patient's body, which is crucial for the accuracy of navigation. Our approach, based on the use of intraoperative ultrasound for image registration, is capable of robustly registering bone structures for different applications, e.g., at the spine or the knee. Nevertheless, this new procedure demands additional steps of preparation of preoperative data. To increase the clinical acceptance of this procedure, it is useful to automate most of the data processing steps. In this article, we present the architecture of our system with focus on the automation of the data processing steps. In terms of accuracy, a mean target registration error of 0.68 mm was achieved for automatically segmented and registered phantom data where the reference transformation was obtained by performing point-based registration using artificial structures. As the overall accuracy for subject data cannot be determined non-invasively, automatic segmentation and registration were judged by visual inspection and precision, which showed a promising result of 1.76 mm standard deviation for 100 registration trials based on automatic segmentation of magnetic resonance imaging data of the spine. PMID:22868778

  14. 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.

  15. Nonrigid 3D medical image registration and fusion based on deformable models.

    PubMed

    Liu, Peng; Eberhardt, Benjamin; Wybranski, Christian; Ricke, Jens; Lüdemann, Lutz

    2013-01-01

    For coregistration of medical images, rigid methods often fail to provide enough freedom, while reliable elastic methods are available clinically for special applications only. The number of degrees of freedom of elastic models must be reduced for use in the clinical setting to archive a reliable result. We propose a novel geometry-based method of nonrigid 3D medical image registration and fusion. The proposed method uses a 3D surface-based deformable model as guidance. In our twofold approach, the deformable mesh from one of the images is first applied to the boundary of the object to be registered. Thereafter, the non-rigid volume deformation vector field needed for registration and fusion inside of the region of interest (ROI) described by the active surface is inferred from the displacement of the surface mesh points. The method was validated using clinical images of a quasirigid organ (kidney) and of an elastic organ (liver). The reduction in standard deviation of the image intensity difference between reference image and model was used as a measure of performance. Landmarks placed at vessel bifurcations in the liver were used as a gold standard for evaluating registration results for the elastic liver. Our registration method was compared with affine registration using mutual information applied to the quasi-rigid kidney. The new method achieved 15.11% better quality with a high confidence level of 99% for rigid registration. However, when applied to the quasi-elastic liver, the method has an averaged landmark dislocation of 4.32 mm. In contrast, affine registration of extracted livers yields a significantly (P = 0.000001) smaller dislocation of 3.26 mm. In conclusion, our validation shows that the novel approach is applicable in cases where internal deformation is not crucial, but it has limitations in cases where internal displacement must also be taken into account. PMID:23690883

  16. 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.

  17. 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. PMID:25906944

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  19. Radial subsampling for fast cost function computation in intensity-based 3D image registration

    NASA Astrophysics Data System (ADS)

    Boettger, Thomas; Wolf, Ivo; Meinzer, Hans-Peter; Celi, Juan Carlos

    2007-03-01

    Image registration is always a trade-off between accuracy and speed. Looking towards clinical scenarios the time for bringing two or more images into registration should be around a few seconds only. We present a new scheme for subsampling 3D-image data to allow for efficient computation of cost functions in intensity-based image registration. Starting from an arbitrary center point voxels are sampled along scan lines which do radially extend from the center point. We analyzed the characteristics of different cost functions computed on the sub-sampled data and compared them to known cost functions with respect to local optima. Results show the cost functions are smooth and give high peaks at the expected optima. Furthermore we investigated capture range of cost functions computed under the new subsampling scheme. Capture range was remarkably better for the new scheme compared to metrics using all voxels or different subsampling schemes and high registration accuracy was achieved as well. The most important result is the improvement in terms of speed making this scheme very interesting for clinical scenarios. We conclude using the new subsampling scheme intensity-based 3D image registration can be performed much faster than using other approaches while maintaining high accuracy. A variety of different extensions of the new approach is conceivable, e.g. non-regular distribution of the scan lines or not to let the scan lines start from a center point only, but from the surface of an organ model for example.

  20. Automatic registration of laser-scanned point clouds based on planar features

    NASA Astrophysics Data System (ADS)

    Li, Minglei; Gao, Xinyuan; Wang, Li; Li, Guangyun

    2016-03-01

    Automatic multistation registration of laser-scanned point clouds is a research hotspot in laser-scanned point clouds registration. Some targets such as common buildings have plenty of planar features, and using these features as constraints properly can bring about high accuracy registration results. Starting from this, a new automatic multistation registration method using homologous planar features of two scan stations was proposed. In order to recognize planes from different scan stations and get plane equations in corresponding scan station coordinate systems, k-means dynamic clustering method was improved to be adaptive and robust. And to match the homologous planes of the two scan stations, two different procedures were proposed, respectively, one of which was based on the "common" relationship between planes and the other referenced RANSAC algorithm. And the transformation parameters of the two scan station coordinate systems were calculated after homologous plane matching. Finally, the transformation parameters based on the optimal match of planes was adopted as the final registration result. Comparing with ICP algorithm in experiment, the method is proved to be effective.

  1. A dynamic tree-based registration could handle possible large deformations among MR brain images.

    PubMed

    Zhang, Pei; Wu, Guorong; Gao, Yaozong; Yap, Pew-Thian; Shen, Dinggang

    2016-09-01

    Multi-atlas segmentation is a powerful approach to automated anatomy delineation via fusing label information from a set of spatially normalized atlases. For simplicity, many existing methods perform pairwise image registration, leading to inaccurate segmentation especially when shape variation is large. In this paper, we propose a dynamic tree-based strategy for effective large-deformation registration and multi-atlas segmentation. To deal with local minima caused by large shape variation, coarse estimates of deformations are first obtained via alignment of automatically localized landmark points. The dynamic tree capturing the structural relationships between images is then employed to further reduce misalignment errors. Evaluation based on two real human brain datasets, ADNI and LPBA40, shows that our method significantly improves registration and segmentation accuracy. PMID:27235894

  2. 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.

  3. 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

    2015-01-01

    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

  4. 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

  5. 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

  6. 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. PMID:26880873

  7. 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.

  8. Multimodality Neuromonitoring.

    PubMed

    Kirkman, Matthew A; Smith, Martin

    2016-09-01

    The monitoring of systemic and central nervous system physiology is central to the management of patients with neurologic disease in the perioperative and critical care settings. There exists a range of invasive and noninvasive and global and regional monitors of cerebral hemodynamics, oxygenation, metabolism, and electrophysiology that can be used to guide treatment decisions after acute brain injury. With mounting evidence that a single neuromonitor cannot comprehensively detect all instances of cerebral compromise, multimodal neuromonitoring allows an individualized approach to patient management based on monitored physiologic variables rather than a generic one-size-fits-all approach targeting predetermined and often empirical thresholds. PMID:27521195

  9. 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.

  10. Computer-vision-based registration techniques for augmented reality

    NASA Astrophysics Data System (ADS)

    Hoff, William A.; Nguyen, Khoi; Lyon, Torsten

    1996-10-01

    Augmented reality is a term used to describe systems in which computer-generated information is superimposed on top of the real world; for example, through the use of a see- through head-mounted display. A human user of such a system could still see and interact with the real world, but have valuable additional information, such as descriptions of important features or instructions for performing physical tasks, superimposed on the world. For example, the computer could identify and overlay them with graphic outlines, labels, and schematics. The graphics are registered to the real-world objects and appear to be 'painted' onto those objects. Augmented reality systems can be used to make productivity aids for tasks such as inspection, manufacturing, and navigation. One of the most critical requirements for augmented reality is to recognize and locate real-world objects with respect to the person's head. Accurate registration is necessary in order to overlay graphics accurately on top of the real-world objects. At the Colorado School of Mines, we have developed a prototype augmented reality system that uses head-mounted cameras and computer vision techniques to accurately register the head to the scene. The current system locates and tracks a set of pre-placed passive fiducial targets placed on the real-world objects. The system computes the pose of the objects and displays graphics overlays using a see-through head-mounted display. This paper describes the architecture of the system and outlines the computer vision techniques used.

  11. The appropriate parameter retrieval algorithm for feature-based SAR image registration

    NASA Astrophysics Data System (ADS)

    Li, Dong; Zhang, Yunhua

    2012-09-01

    This paper is dedicated to investigate the appropriate parameter retrieval algorithm for feature-based synthetic aperture radar (SAR) image registration. The widely-used random sample consensus (RANSAC) is observed to be instable for its inappropriate estimation strategy and loss function for SAR images. In order to enable a stable and robust registration for SAR, an extended fast least trimmed squares (EF-LTS) is proposed which conducts the registration by least squares fitting at least half of the correspondences to minimize the squared polynomial residuals instead of fitting the minimal sampling set to maximize the cardinality of the consensus set as RANSAC. Experiment on interferometric SAR image pair demonstrates that the proposed algorithm behaves very stably and the obtained registration is averagely better than that by RANSAC in terms of cross-correlation and spectral SNR. By this algorithm, a stable estimation for any kind of 2D polynomial warp model with high robustness and accuracy can be efficiently achieved. Thus EF-LTS is more appropriate for SAR image registration.

  12. 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

  13. 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.

  14. 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. PMID:16604627

  15. An SOI-based 1550-nm 4×4 multimode interference coupler used for OADC

    NASA Astrophysics Data System (ADS)

    Tian, Ye; Wei, Shile; Qiu, Jifang; Wu, Jian; Zhang, Daolin; Wang, Yue

    2015-08-01

    A novel integrable optical analog-to-digital converter (OADC) scheme based on phase-shifted optical quantization has been proposed for years, the quantization module of which is mainly composed of a 1×2 multi-mode interference (MMI) coupler, a phase modulator and a 4×4MMI. Although the manufacture technology of 1×2 MMI and phase modulator has been very mature, the 4×4MMI on a silicon-on-insulator (SOI) substrate with superior performance has not been realized. Since the 4×4MMI is crucial for the realization of the OADC, we designed and fabricated a 4×4 MMI coupler on SOI substrate. The width and length of the multi-mode section are 10.2 um and 182.6 um respectively. Measurement results show that the imbalance of the four output ports at 1550-nm is around 1.9 dB, while the insertion losses are 5.6 dB.

  16. Variable spatial pattern probe based on offset launch of multimode waveguide for optogenetics.

    PubMed

    Dong, Na; Jiang, Weifeng; Sun, Xiaohan

    2016-05-16

    We propose and demonstrate experimentally a variable spatial pattern probe based on offset launch at the input facet of multi-mode optical waveguide for the use of optogenetics, which could generate variable spatial patterns with micron scale at the output facet of the waveguide so that the optical stimulating location in the neural tissue can be changed. By using of coupling mode theory, finite element method (FEM) and light diffusion Monte-Carlo method, we simulate their mode patterns and evolvements for TE00, TE10, TE20 and TE11 modes, excited by offset launch at different input point of the probe with core size of 17.8 × 7.8 μm2, from the output port to 50μm in the tissue. The experimental chips including array multimode waveguides with different width are fabricated using the Silica-on-Silicon processing. We selectively excite TE00, TE10, TE20 and TE11 modes in the waveguide chip with core size of 17.8 × 7.8 μm2, test their patterns and obtain their evolvements. The experimental results are coincident with the simulation results. PMID:27409913

  17. Hough space parametrization: ensuring global consistency in intensity-based registration.

    PubMed

    Yigitsoy, Mehmet; Fotouhi, Javad; Navab, Nassir

    2014-01-01

    Intensity based registration is a challenge when images to be registered have insufficient amount of information in their overlapping region. Especially, in the absence of dominant structures such as strong edges in this region, obtaining a solution that satisfies global structural consistency becomes difficult. In this work, we propose to exploit the vast amount of available information beyond the overlapping region to support the registration process. To this end, a novel global regularization term using Generalized Hough Transform is designed that ensures the global consistency when the local information in the overlap region is insufficient to drive the registration. Using prior data, we learn a parametrization of the target anatomy in Hough space. This parametrization is then used as a regularization for registering the observed partial images without using any prior data. Experiments on synthetic as well as on sample real medical images demonstrate the good performance and potential use of the proposed concept. PMID:25333128

  18. Real-time estimation of FLE statistics for 3-D tracking with point-based registration.

    PubMed

    Wiles, Andrew D; Peters, Terry M

    2009-09-01

    Target registration error (TRE) has become a widely accepted error metric in point-based registration since the error metric was introduced in the 1990s. It is particularly prominent in image-guided surgery (IGS) applications where point-based registration is used in both image registration and optical tracking. In point-based registration, the TRE is a function of the fiducial marker geometry, location of the target and the fiducial localizer error (FLE). While the first two items are easily obtained, the FLE is usually estimated using an a priori technique and applied without any knowledge of real-time information. However, if the FLE can be estimated in real-time, particularly as it pertains to optical tracking, then the TRE can be estimated more robustly. In this paper, a method is presented where the FLE statistics are estimated from the latest measurement of the fiducial registration error (FRE) statistics. The solution is obtained by solving a linear system of equations of the form Ax=b for each marker at each time frame where x are the six independent FLE covariance parameters and b are the six independent estimated FRE covariance parameters. The A matrix is only a function of the tool geometry and hence the inverse of the matrix can be computed a priori and used at each instant in which the FLE estimation is required, hence minimizing the level of computation at each frame. When using a good estimate of the FRE statistics, Monte Carlo simulations demonstrate that the root mean square of the FLE can be computed within a range of 70-90 microm. Robust estimation of the TRE for an optically tracked tool, using a good estimate of the FLE, will provide two enhancements in IGS. First, better patient to image registration will be obtained by using the TRE of the optical tool as a weighting factor of point-based registration used to map the patient to image space. Second, the directionality of the TRE can be relayed back to the surgeon giving the surgeon the option

  19. 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.

  20. Voxel-based 2-D/3-D registration of fluoroscopy images and CT scans for image-guided surgery.

    PubMed

    Weese, J; Penney, G P; Desmedt, P; Buzug, T M; Hill, D L; Hawkes, D J

    1997-12-01

    Registration of intraoperative fluoroscopy images with preoperative three-dimensional (3-D) CT images can be used for several purposes in image-guided surgery. On the one hand, it can be used to display the position of surgical instruments, which are being tracked by a localizer, in the preoperative CT scan. On the other hand, the registration result can be used to project preoperative planning information or important anatomical structures visible in the CT image onto the fluoroscopy image. For this registration task, a novel voxel-based method in combination with a new similarity measure (pattern intensity) has been developed. The basic concept of the method is explained at the example of two-dimensional (2-D)/3-D registration of a vertebra in an X-ray fluoroscopy image with a 3-D CT image. The registration method is described, and the results for a spine phantom are presented and discussed. Registration has been carried out repeatedly with different starting estimates to study the capture range. Information about registration accuracy has been obtained by comparing the registration results with a highly accurate "ground-truth" registration, which has been derived from fiducial markers attached to the phantom prior to imaging. In addition, registration results for different vertebrae have been compared. The results show that the rotation parameters and the shifts parallel to the projection plane can accurately be determined from a single projection. Because of the projection geometry, the accuracy of the height above the projection plane is significantly lower. PMID:11020832

  1. Registration algorithm research for work-pieces based on affine invariant

    NASA Astrophysics Data System (ADS)

    Chen, Meng; Yan, Bixi

    2011-11-01

    Work-pieces registration is a crucial item in flexible manufacture assembly. In order to finish work-pieces registration, a method is proposed based on affine invariant. After the CAD model data and actual measurement data of a work-piece are acquired, the method consists of the following five steps: sampling point clouds data, extracting characteristic four-points set, searching characteristic congruent four-points set, computing transformation congruent matrix and the last, further precise point clouds data registration. Point clouds data of CAD and measuring model are sampled respectively through calculating the curvature of the two sets of data and selecting the obvious curvature points as their reduced characteristic points. Based on this, the characteristic four-points set from the reduced ones of CAD model and the corresponding matching congruent four-points set of the measuring model are extracted according to RANSAC algorithm. The rotation matrix R and translation vector T of any two matching four-points are then calculated through the algorithm of quaternion. After that, the measuring model is rotated and translated and then compared with the CAD model data, the most congruent transformation matrix is selected as the coarse registration result. Furthermore, Iterative Closest Point (ICP) algorithm is applied to the congruent transformation to improve registration precision. The experiment shows that the run time of the algorithm is 129.56s and mean-error of point-to-point distance is 0.062mm when accessing measuring model data more than 80000 points. Compared with the traditional curvature registration, the experiment also shows that the algorithm is more efficient and robust when the volume of point clouds data is larger.

  2. 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

    2015-04-01

    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. PMID:25767898

  3. 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.

  4. Combination of intensity-based image registration with 3D simulation in radiation therapy

    NASA Astrophysics Data System (ADS)

    Li, Pan; Malsch, Urban; Bendl, Rolf

    2008-09-01

    Modern techniques of radiotherapy like intensity modulated radiation therapy (IMRT) make it possible to deliver high dose to tumors of different irregular shapes at the same time sparing surrounding healthy tissue. However, internal tumor motion makes precise calculation of the delivered dose distribution challenging. This makes analysis of tumor motion necessary. One way to describe target motion is using image registration. Many registration methods have already been developed previously. However, most of them belong either to geometric approaches or to intensity approaches. Methods which take account of anatomical information and results of intensity matching can greatly improve the results of image registration. Based on this idea, a combined method of image registration followed by 3D modeling and simulation was introduced in this project. Experiments were carried out for five patients 4DCT lung datasets. In the 3D simulation, models obtained from images of end-exhalation were deformed to the state of end-inhalation. Diaphragm motions were around -25 mm in the cranial-caudal (CC) direction. To verify the quality of our new method, displacements of landmarks were calculated and compared with measurements in the CT images. Improvement of accuracy after simulations has been shown compared to the results obtained only by intensity-based image registration. The average improvement was 0.97 mm. The average Euclidean error of the combined method was around 3.77 mm. Unrealistic motions such as curl-shaped deformations in the results of image registration were corrected. The combined method required less than 30 min. Our method provides information about the deformation of the target volume, which we need for dose optimization and target definition in our planning system.

  5. 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...

  6. Random forest-based similarity measures for multi-modal classification of Alzheimer's disease.

    PubMed

    Gray, Katherine R; Aljabar, Paul; Heckemann, Rolf A; Hammers, Alexander; Rueckert, Daniel

    2013-01-15

    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. Multi-modality 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 the 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 differs 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 future

  7. 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

  8. 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

  9. The evolution of gadolinium based contrast agents: from single-modality to multi-modality.

    PubMed

    Zhang, Li; Liu, Ruiqing; Peng, Hui; Li, Penghui; Xu, Zushun; Whittaker, Andrew K

    2016-05-19

    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. PMID:27159645

  10. 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.

  11. 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.

  12. High-resolution, lensless endoscope based on digital scanning through a multimode optical fiber.

    PubMed

    Papadopoulos, Ioannis N; Farahi, Salma; Moser, Christophe; Psaltis, Demetri

    2013-02-01

    We propose and experimentally demonstrate an ultra-thin rigid endoscope (450 μm diameter) based on a passive multimode optical fiber. We use digital phase conjugation to overcome the modal scrambling of the fiber to tightly focus and scan the laser light at its distal end. By exploiting the maximum number of modes available, sub-micron resolution, high quality fluorescence images of neuronal cells were acquired. The imaging system is evaluated in terms of fluorescence collection efficiency, resolution and field of view. The small diameter of the proposed endoscope, along with its high quality images offer an opportunity for minimally invasive medical endoscopic imaging and diagnosis based on cellular phenotype via direct tissue penetration. PMID:23411747

  13. Image-based RSA: Roentgen stereophotogrammetric analysis based on 2D-3D image registration.

    PubMed

    de Bruin, P W; Kaptein, B L; Stoel, B C; Reiber, J H C; Rozing, P M; Valstar, E R

    2008-01-01

    Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3D image registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3D image registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: |mu |< 0.083 mm for translations and |mu| < 0.023 degrees for rotations. The precision sigma in x-, y-, and z-direction was 0.090, 0.077, and 0.220 mm for translations and 0.155 degrees , 0.243 degrees , and 0.074 degrees for rotations. Our results show that the accuracy and precision of in vitro IBRSA, performed under ideal laboratory conditions, are lower than in vitro standard RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications. PMID:17706656

  14. 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

  15. Fiber feature map based landmark initialization for highly deformable DTI registration

    PubMed Central

    Gupta, Aditya; Toews, Matthew; Janardhana, Ravikiran; Rathi, Yogesh; Gilmore, John; Escolar, Maria; Styner, Martin

    2013-01-01

    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. PMID:24353392

  16. 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

  17. 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.

  18. 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.

  19. Evaluation of optimization methods for intensity-based 2D-3D registration in x-ray guided interventions

    NASA Astrophysics Data System (ADS)

    van der Bom, I. M. J.; Klein, S.; Staring, M.; Homan, R.; Bartels, L. W.; Pluim, J. P. W.

    2011-03-01

    The advantage of 2D-3D image registration methods versus direct image-to-patient registration, is that these methods generally do not require user interaction (such as manual annotations), additional machinery or additional acquisition of 3D data. A variety of intensity-based similarity measures has been proposed and evaluated for different applications. These studies showed that the registration accuracy and capture range are influenced by the choice of similarity measure. However, the influence of the optimization method on intensity-based 2D-3D image registration has not been investigated. We have compared the registration performance of seven optimization methods in combination with three similarity measures: gradient difference, gradient correlation, and pattern intensity. Optimization methods included in this study were: regular step gradient descent, Nelder-Mead, Powell-Brent, Quasi-Newton, nonlinear conjugate gradient, simultaneous perturbation stochastic approximation, and evolution strategy. Registration experiments were performed on multiple patient data sets that were obtained during cerebral interventions. Various component combinations were evaluated on registration accuracy, capture range, and registration time. The results showed that for the same similarity measure, different registration accuracies and capture ranges were obtained when different optimization methods were used. For gradient difference, largest capture ranges were obtained with Powell-Brent and simultaneous perturbation stochastic approximation. Gradient correlation and pattern intensity had the largest capture ranges in combination with Powell-Brent, Nelder-Mead, nonlinear conjugate gradient, and Quasi-Newton. Average registration time, expressed in the number of DRRs required for convergence, was the lowest for Powell-Brent. Based on these results, we conclude that Powell-Brent is a reliable optimization method for intensity-based 2D-3D registration of x-ray images to CBCT

  20. A local fast marching-based diffusion tensor image registration algorithm by simultaneously considering spatial deformation and tensor orientation.

    PubMed

    Xue, Zhong; Li, Hai; Guo, Lei; Wong, Stephen T C

    2010-08-01

    It is a key step to spatially align diffusion tensor images (DTI) to quantitatively compare neural images obtained from different subjects or the same subject at different timepoints. Different from traditional scalar or multi-channel image registration methods, tensor orientation should be considered in DTI registration. Recently, several DTI registration methods have been proposed in the literature, but deformation fields are purely dependent on the tensor features not the whole tensor information. Other methods, such as the piece-wise affine transformation and the diffeomorphic non-linear registration algorithms, use analytical gradients of the registration objective functions by simultaneously considering the reorientation and deformation of tensors during the registration. However, only relatively local tensor information such as voxel-wise tensor-similarity is utilized. This paper proposes a new DTI image registration algorithm, called local fast marching (FM)-based simultaneous registration. The algorithm not only considers the orientation of tensors during registration but also utilizes the neighborhood tensor information of each voxel to drive the deformation, and such neighborhood tensor information is extracted from a local fast marching algorithm around the voxels of interest. These local fast marching-based tensor features efficiently reflect the diffusion patterns around each voxel within a spherical neighborhood and can capture relatively distinctive features of the anatomical structures. Using simulated and real DTI human brain data the experimental results show that the proposed algorithm is more accurate compared with the FA-based registration and is more efficient than its counterpart, the neighborhood tensor similarity-based registration. PMID:20382233

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Fuzzy decoupling controller based on multimode control algorithm of PI-single neuron and its application

    NASA Astrophysics Data System (ADS)

    Zhang, Xianxia; Wang, Jian; Qin, Tinggao

    2003-09-01

    Intelligent control algorithms are introduced into the control system of temperature and humidity. A multi-mode control algorithm of PI-Single Neuron is proposed for single loop control of temperature and humidity. In order to remove the coupling between temperature and humidity, a new decoupling method is presented, which is called fuzzy decoupling. The decoupling is achieved by using a fuzzy controller that dynamically modifies the static decoupling coefficient. Taking the control algorithm of PI-Single Neuron as the single loop control of temperature and humidity, the paper provides the simulated output response curves with no decoupling control, static decoupling control and fuzzy decoupling control. Those control algorithms are easily implemented in singlechip-based hardware systems.

  6. 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. PMID:27410811

  7. 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.

  8. Medical image registration using fuzzy theory.

    PubMed

    Pan, Meisen; Tang, Jingtian; Xiong, Qi

    2012-01-01

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

  9. 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. PMID:25827811

  10. 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.

  11. Registration of multitemporal low-resolution synthetic aperture radar images based on a new similarity measure

    NASA Astrophysics Data System (ADS)

    Ren, Weilong; Song, Jianshe; Zhang, Xiongmei; Cai, Xingfu

    2016-01-01

    Image registration is concerned with the precise overlap of two images. One challenging problem in this area is the registration of low-resolution synthetic aperture radar (SAR) images. In general, extracting feature points from such images is difficult due to the coarse observation and the severe speckle. The use of area similarity for image registration is another important branch to solve the problem. A similarity measure based on a conditional density function (cdf) is proposed. The cdf is specially tailored for SAR images, where the speckle is generally assumed as multiplicative gamma noise with unit mean. Additionally, a two-step procedure is devised for the registration of intro-model SAR images to improve the computational efficiency. First, the two images are roughly aligned considering only the translational difference. Then small blocks from the two images are accurately aligned and the center point of each block is treated as a control point, which is finally used to obtain the precise affine transformation between the two images. Five SAR image datasets are tested in the experiment part, and the results demonstrate the efficiency and accuracy of the proposed method.

  12. 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

  13. 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.

  14. Validation of 3D multimodality roadmapping in interventional neuroradiology.

    PubMed

    Ruijters, Daniel; Homan, Robert; Mielekamp, Peter; van de Haar, Peter; Babic, Drazenko

    2011-08-21

    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. PMID:21799235

  15. Multimodal MRI-based imputation of the Aβ+ in early mild cognitive impairment

    PubMed Central

    Tosun, Duygu; Joshi, Sarang; Weiner, Michael W; for the Alzheimer's Disease Neuroimaging Initiative

    2014-01-01

    Objective The primary goal of this study was to identify brain atrophy from structural MRI (magnetic resonance imaging) and cerebral blood flow (CBF) patterns from arterial spin labeling perfusion MRI that are best predictors of the Aβ-burden, measured as composite 18F-AV45-PET (positron emission tomography) uptake, in individuals with early mild cognitive impairment (MCI). Furthermore, another objective was to assess the relative importance of imaging modalities in classification of Aβ+/Aβ− early MCI. Methods Sixty-seven Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 participants with early MCI were included. Voxel-wise anatomical shape variation measures were computed by estimating the initial diffeomorphic mapping momenta from an unbiased control template. CBF measures normalized to average motor cortex CBF were mapped onto the template space. Using partial least squares regression, we identified the structural and CBF signatures of Aβ after accounting for normal cofounding effects of age, gender, and education. Results 18F-AV45-positive early MCIs could be identified with 83% classification accuracy, 87% positive predictive value, and 84% negative predictive value by multidisciplinary classifiers combining demographics data, ApoE ε4-genotype, and a multimodal MRI-based Aβ score. Interpretation Multimodal MRI can be used to predict the amyloid status of early-MCI individuals. MRI is a very attractive candidate for the identification of inexpensive and noninvasive surrogate biomarkers of Aβ deposition. Our approach is expected to have value for the identification of individuals likely to be Aβ+ in circumstances where cost or logistical problems prevent Aβ detection using cerebrospinal fluid analysis or Aβ-PET. This can also be used in clinical settings and clinical trials, aiding subject recruitment and evaluation of treatment efficacy. Imputation of the Aβ-positivity status could also complement Aβ-PET by identifying individuals who would

  16. 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.

  17. Transform-invariant feature based functional MR image registration and neural activity modelling.

    PubMed

    Gong, Jiaqi; Hao, Qi; Hu, Fei

    2013-01-01

    In this paper, a set of non-rigid image registration and neural activity modelling methods using functional MR Images (fMRI) are proposed based on transform-invariant feature representations. Our work made two contributions. First, we propose to use a transform-invariant feature to improve image registration performance of Iterative Closest Point (ICP) based methods. The proposed feature utilises Gaussian Mixture Models (GMM) to describe the local topological structure of fMRI data. Second, we propose to use a 3-dimensional Scale-Invariant Feature Transform (SIFT) based descriptor to represent neural activities related to drinking behaviour. As a result, neural activities patterns of different subjects drinking water or intaking glucose can be recognised, with strong robustness against various artefacts. PMID:23900434

  18. Robust Global Image Registration Based on a Hybrid Algorithm Combining Fourier- and Spatial-domain Techniques

    NASA Astrophysics Data System (ADS)

    Crabtree, P.; McNicholl, P.; Seanor, C.; Murray-Krezan, J.

    2012-09-01

    A variety of image registration techniques have been investigated for applications such as image analysis, fusion, compression, enhancement, and creating mosaics. In particular, robust registration is a key component for successful multi-frame processing aimed at super-resolution or high dynamic range imaging. Image registration techniques are broadly categorized as global (area) or feature-based, and can also be classified as being performed in either the Fourier- or spatial-domain. Spatial domain methods are typically used for applications requiring accurate estimation of sub-pixel motion, such as multi-frame super-resolution based on de-aliasing. However, these techniques often rely on the availability of a priori information (good initial guess), and are therefore limited in terms of the dynamic range of the global motion estimates. A Gaussian pyramid approach is one standard method for extending the region of convergence of spatial domain techniques. On the other hand, Fourier domain-based correlation techniques such as the log-polar FFT method provide fast and reasonably accurate estimates of global shifts, rotation, and uniform scale changes, and tend to perform well over a large range of frame-to-frame motion magnitudes. In this paper we explore several possible hybrid algorithms for robust global registration based on combining the log-polar FFT and spatial-domain techniques. This includes the straightforward use of the log-polar FFT algorithm to generate an initial guess for use by a spatial domain algorithm, as well as the intertwining of the two methods by applying both global correlation and spatial domain registration at each relevant step within the log-polar FFT algorithm. In addition, we explore the benefits of normalized gradient correlation in performing the coarse log-polar FFT registration. The use of normalized gradient correlation, as opposed to phase-only correlation, has recently been proposed for improving the log-polar FFT method in terms

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

    SciTech Connect

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

    2008-03-15

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

  20. Elastic image registration using hierarchical spatially based mean shift.

    PubMed

    Yang, Xuan; Pei, Jihong; Sun, Wei

    2013-09-01

    In this paper, a novel estimation technique for corresponding points using a hierarchical, spatially based mean shift algorithm is proposed. We proposed a spatially based probability estimation using different spatial masks. For a given point on reference image, its corresponding register point is found along the search trajectory generated by optimizing Bhattacharyya coefficient between two windows centered at the points on the register and reference images. The outliers are further eliminated by analyzing statistical information on the displacements of the candidate register points. Experiments on various monomodal medical images show that the proposed method is feasible and fast. PMID:23930802

  1. Rationale for a Multimodality Strategy to Enhance the Efficacy of Dendritic Cell-Based Cancer Immunotherapy.

    PubMed

    Datta, Jashodeep; Berk, Erik; Cintolo, Jessica A; Xu, Shuwen; Roses, Robert E; Czerniecki, Brian J

    2015-01-01

    Dendritic cells (DC), master antigen-presenting cells that orchestrate interactions between the adaptive and innate immune arms, are increasingly utilized in cancer immunotherapy. Despite remarkable progress in our understanding of DC immunobiology, as well as several encouraging clinical applications - such as DC-based sipuleucel-T for metastatic castration-resistant prostate cancer - clinically effective DC-based immunotherapy as monotherapy for a majority of tumors remains a distant goal. The complex interplay between diverse molecular and immune processes that govern resistance to DC-based vaccination compels a multimodality approach, encompassing a growing arsenal of antitumor agents which target these distinct processes and synergistically enhance DC function. These include antibody-based targeted molecular therapies, immune checkpoint inhibitors, therapies that inhibit immunosuppressive cellular elements, conventional cytotoxic modalities, and immune potentiating adjuvants. It is likely that in the emerging era of "precision" cancer therapeutics, tangible clinical benefits will only be realized with a multifaceted - and personalized - approach combining DC-based vaccination with adjunctive strategies. PMID:26082780

  2. Rationale for a Multimodality Strategy to Enhance the Efficacy of Dendritic Cell-Based Cancer Immunotherapy

    PubMed Central

    Datta, Jashodeep; Berk, Erik; Cintolo, Jessica A.; Xu, Shuwen; Roses, Robert E.; Czerniecki, Brian J.

    2015-01-01

    Dendritic cells (DC), master antigen-presenting cells that orchestrate interactions between the adaptive and innate immune arms, are increasingly utilized in cancer immunotherapy. Despite remarkable progress in our understanding of DC immunobiology, as well as several encouraging clinical applications – such as DC-based sipuleucel-T for metastatic castration-resistant prostate cancer – clinically effective DC-based immunotherapy as monotherapy for a majority of tumors remains a distant goal. The complex interplay between diverse molecular and immune processes that govern resistance to DC-based vaccination compels a multimodality approach, encompassing a growing arsenal of antitumor agents which target these distinct processes and synergistically enhance DC function. These include antibody-based targeted molecular therapies, immune checkpoint inhibitors, therapies that inhibit immunosuppressive cellular elements, conventional cytotoxic modalities, and immune potentiating adjuvants. It is likely that in the emerging era of “precision” cancer therapeutics, tangible clinical benefits will only be realized with a multifaceted – and personalized – approach combining DC-based vaccination with adjunctive strategies. PMID:26082780

  3. Non-rigid registration of cervical spine MRI volumes.

    PubMed

    Aktar, Mst Nargis; Alam, Md Jahangir; Pickering, Mark; Webb, Alexandra; Perriman, Diana

    2015-08-01

    Whiplash is the colloquial term for neck injuries caused by sudden extension of the cervical spine. Patients with chronic whiplash associated disorder (WAD) can experience neck pain for many years after the original injury. Researchers have found some evidence to suggest that chronic whiplash is related to the amount of intra-muscular fat in the cervical spine muscles. Hence, an important step towards developing a treatment for chronic WAD is a technique to accurately and efficiently measure the amount of intra-muscular fat in the muscles of the cervical spine. Our proposed technique for making this measurement is to automatically segment the cervical spine muscles using a fused volume created from multi-modal MRI volumes of the cervical spine. Multiple modes are required to enhance the boundaries between the different muscles to assist the following automatic segmentation process. However, before these multiple modes can be fused it is first necessary to accurately register these volumes. Hence, in this paper, we have proposed a new non-rigid multi-modal registration algorithm using the sum of conditional variance (SCV) with partial volume interpolation (PVI) similarity measure and Gauss-Newton (GN) optimization for the accurate registration of multi-modal cervical spine MRI volumes. The performance of the proposed approach is compared with the existing SCV based registration algorithm and the sum of the conditional squared deviation from the mode (SCSDM) method. The experimental results demonstrate that the proposed approach provides superior performance than the best existing approaches. PMID:26736677

  4. 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

  5. DTI registration in atlas based fiber analysis of infantile Krabbe disease

    PubMed Central

    Wang, Yi; Gupta, Aditya; Liu, Zhexing; Zhang, Hui; Escolar, Maria L.; Gilmore, John H.; Gouttard, Sylvain; Fillard, Pierre; Maltbie, Eric; Gerig, Guido; Styner, Martin

    2011-01-01

    In recent years, diffusion tensor imaging (DTI) has become the modality of choice to investigate white matter pathology in the developing brain. To study neonate Krabbe disease with DTI, we evaluate the performance of linear and non-linear DTI registration algorithms for atlas based fiber tract analysis. The DTI scans of 10 age-matched neonates with infantile Krabbe disease are mapped into an atlas for the analysis of major fiber tracts - the genu and splenium of the corpus callosum, the internal capsules tracts and the uncinate fasciculi. The neonate atlas is based on 377 healthy control subjects, generated using an unbiased diffeomorphic atlas building method. To evaluate the performance of one linear and seven nonlinear commonly used registration algorithms for DTI we propose the use of two novel evaluation metrics: a regional matching quality criterion incorporating the local tensor orientation similarity, and a fiber property profile based metric using normative correlation. Our experimental results indicate that the whole tensor based registration method within the DTI-ToolKit (DTI-TK) shows the best performance for our application. PMID:21256236

  6. 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. PMID

  7. 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.

  8. 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

  9. An ICP variant with anisotropic weighting to accommodate measurement errors in A-Mode ultrasound-based registration.

    PubMed

    Fieten, Lorenz; Radermacher, Klaus; Heger, Stefan

    2012-08-01

    In computer-assisted surgery, navigation based on pre-operative images and intra-operative tracking requires fusion of data from different coordinate systems. Intra-operative registration is used to determine the spatial relationship between these coordinate systems. Feature-based registration methods rely on reference structures localized both in the pre-operative images and in the surgical site. Optically tracked A-Mode ultrasound (US) allows for non-invasive and cost-efficient digitization of bone surface points needed as input data for registration algorithms. It is especially attractive in combination with surface-based registration algorithms, such as the Iterative Closest Point algorithm and its variants, because they automatically localize the corresponding points, which are covered by soft tissue and, hence, not visible in the site. However, as transcutaneous palpation relies on some assumptions, e.g., regarding the average speed of sound of the scanned soft tissue, that are only partly justified in practice, errors occur that make transcutaneous palpation less reliable than direct palpation. Furthermore, optical tracking causes errors that have to be considered, especially if a so-called dynamic reference base is attached to the patient. The present work investigates how to reduce the effect of important error sources in A-Mode US-based registration. The major contributions are techniques for application-specific error modeling and new methods for surface-based registration with anisotropic weighting. This includes a Newton-like optimization scheme for point-to-point registration and a modified kd-tree-based algorithm for closest point computation. Various combinations of registration algorithms and modeling techniques are tested in a simulation study addressing periacetabular osteotomy, and it is clearly demonstrated that standard methods are not recommendable. On the contrary, the new algorithms allow for a substantial increase in registration accuracy

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

    PubMed

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

    2010-02-01

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

  11. Modified maximum likelihood registration based on information fusion

    NASA Astrophysics Data System (ADS)

    Qi, Yongqing; Jing, Zhongliang; Hu, Shiqiang

    2007-11-01

    The bias estimation of passive sensors is considered based on information fusion in multi-platform multi-sensor tracking system. The unobservable problem of bearing-only tracking in blind spot is analyzed. A modified maximum likelihood method, which uses the redundant information of multi-sensor system to calculate the target position, is investigated to estimate the biases. Monte Carlo simulation results show that the modified method eliminates the effect of unobservable problem in the blind spot and can estimate the biases more rapidly and accurately than maximum likelihood method. It is statistically efficient since the standard deviation of bias estimation errors meets the theoretical lower bounds.

  12. 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.

  13. Robust polarization-insensitive strip-slot waveguide mode converter based on symmetric multimode interference.

    PubMed

    Deng, Qingzhong; Yan, Qiaojing; Liu, Lu; Li, Xinbai; Michel, Jurgen; Zhou, Zhiping

    2016-04-01

    Strip-slot waveguide mode converters for TE0 have been widely investigated. Here we demonstrate a polarization-insensitive converter numerically and experimentally. The polarization-insensitive performance is achieved by matching the optical field distribution of the 2-fold image of the Multimode Interference (MMI) and the TE0 (TM0) mode of a slot waveguide. The working principle for this MMI-based mode converter is thoroughly analyzed with the quantitatively evaluated optical field overlap ratio that is theoretically derived from the orthonormal relation of eigenmodes. Based on the analysis, the MMI-based polarization-insensitive converters are then simulated and fabricated. The simulation and measurement results indicate that the proposed scheme is a robust design since it is not only polarization-insensitive but also wavelength-insensitive and fabrication-tolerant. Moreover, the mode converter is as small as 1.22 μm × 4 μm while the measured conversion efficiencies are 95.9% for TE0 and 96.6% for TM0. All these excellent properties make the proposed mode converter an ideal solution for coupling light between strip and slot waveguides when both TE and TM polarizations are considered. PMID:27137024

  14. Intensity-based registration and fusion of thermal and visual facial-images

    NASA Astrophysics Data System (ADS)

    Arslan, Musa Serdar; Elbakaray, Mohamed I.; Reza, Shamim; Iftekharuddin, Khan M.

    2012-10-01

    Fusion of images from different modalities provides information that cannot be obtained by viewing the images separately and consecutively. Automatic fusion of thermal and visual images is of great interest in defense and medical applications. In this study, we implemented automatic intensity-based illumination, translation and scale invariant registration of deformable objects in thermal and visual images by maximization of a similarity measure such as generalized correlation ratio. This method was originally used to register ultrasound (US) and magnetic resonance images (MRI) successfully. In our current work, we propose a major modification to the original algorithm by investigating appropriate information content in the input data. The registration of facial thermal and visual images in this algorithm is achieved by maximization of the similarity measure between the input images in the appropriate image channel. The algorithm is tested using real facial images with illumination, scale, and translation variations and the results show acceptable accuracy.

  15. 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.

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

    PubMed

    An, Yong; Wang, Manning; Song, Zhijian

    2015-01-01

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

  17. Adaptive registration of magnetic resonance images based on a viscous fluid model.

    PubMed

    Chang, Herng-Hua; Tsai, Chih-Yuan

    2014-11-01

    This paper develops a new viscous fluid registration algorithm that makes use of a closed incompressible viscous fluid model associated with mutual information. In our approach, we treat the image pixels as the fluid elements of a viscous fluid governed by the nonlinear Navier-Stokes partial differential equation (PDE) that varies in both temporal and spatial domains. We replace the pressure term with an image-based body force to guide the transformation that is weighted by the mutual information between the template and reference images. A computationally efficient algorithm with staggered grids is introduced to obtain stable solutions of this modified PDE for transformation. The registration process of updating the body force, the velocity and deformation fields is repeated until the mutual information reaches a prescribed threshold. We have evaluated this new algorithm in a number of synthetic and medical images. As consistent with the theory of the viscous fluid model, we found that our method faithfully transformed the template images into the reference images based on the intensity flow. Experimental results indicated that the proposed scheme achieved stable registrations and accurate transformations, which is of potential in large-scale medical image deformation applications. PMID:25176596

  18. 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.

  19. Bias reduction in sub-pixel image registration based on the anti-symmetric feature

    NASA Astrophysics Data System (ADS)

    Wang, Dezhi; Jiang, Yu; Wang, Weizhuo; Wang, Yueqi

    2016-03-01

    A simple but effective bias reduction technique is developed based on the anti-symmetric feature of the sub-pixel image registration bias. Depending on the error propagation theory, the anti-symmetric feature is mathematically derived through a classical subset-based digital image correlation algorithm considering the most common error sources i.e. the grey-intensity interpolation scheme and random noise. This leads to the sub-pixel registration bias formulated in the form of an analytic expression that consists of the interpolation-induced phase error and the random noise induced bias, which is also further illustrated by numerical simulations. Bias reduction is achieved by compensating the bias at a certain sub-pixel displacement with the bias at the corresponding anti-symmetric sub-pixel displacement where the Fourier shift theorem is employed to alter the displacement without introducing extra bias. The performance of proposed method is validated using numerical case studies with different interpolation schemes and noise levels, by which the sub-pixel registration bias is shown to be significantly reduced.

  20. Fast Rotation-Free Feature-Based Image Registration Using Improved N-SIFT and GMM-Based Parallel Optimization.

    PubMed

    Yu, Dongdong; Yang, Feng; Yang, Caiyun; Leng, Chengcai; Cao, Jian; Wang, Yining; Tian, Jie

    2016-08-01

    Image registration is a key problem in a variety of applications, such as computer vision, medical image processing, pattern recognition, etc., while the application of registration is limited by time consumption and the accuracy in the case of large pose differences. Aimed at these two kinds of problems, we propose a fast rotation-free feature-based rigid registration method based on our proposed accelerated-NSIFT and GMM registration-based parallel optimization (PO-GMMREG). Our method is accelerated by using the GPU/CUDA programming and preserving only the location information without constructing the descriptor of each interest point, while its robustness to missing correspondences and outliers is improved by converting the interest point matching to Gaussian mixture model alignment. The accuracy in the case of large pose differences is settled by our proposed PO-GMMREG algorithm by constructing a set of initial transformations. Experimental results demonstrate that our proposed algorithm can fast rigidly register 3-D medical images and is reliable for aligning 3-D scans even when they exhibit a poor initialization. PMID:26259212

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

    PubMed Central

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

    2014-01-01

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

  2. 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

  3. Plasmonic-multimode-interference-based logic circuit with simple phase adjustment

    PubMed Central

    Ota, Masashi; Sumimura, Asahi; Fukuhara, Masashi; Ishii, Yuya; Fukuda, Mitsuo

    2016-01-01

    All-optical logic circuits using surface plasmon polaritons have a potential for high-speed information processing with high-density integration beyond the diffraction limit of propagating light. However, a number of logic gates that can be cascaded is limited by complicated signal phase adjustment. In this study, we demonstrate a half-adder operation with simple phase adjustment using plasmonic multimode interference (MMI) devices, composed of dielectric stripes on a metal film, which can be fabricated by a complementary metal-oxide semiconductor (MOS)-compatible process. Also, simultaneous operations of XOR and AND gates are substantiated experimentally by combining 1 × 1 MMI based phase adjusters and 2 × 2 MMI based intensity modulators. An experimental on-off ratio of at least 4.3 dB is confirmed using scanning near-field optical microscopy. The proposed structure will contribute to high-density plasmonic circuits, fabricated by complementary MOS-compatible process or printing techniques. PMID:27086694

  4. Plasmonic-multimode-interference-based logic circuit with simple phase adjustment.

    PubMed

    Ota, Masashi; Sumimura, Asahi; Fukuhara, Masashi; Ishii, Yuya; Fukuda, Mitsuo

    2016-01-01

    All-optical logic circuits using surface plasmon polaritons have a potential for high-speed information processing with high-density integration beyond the diffraction limit of propagating light. However, a number of logic gates that can be cascaded is limited by complicated signal phase adjustment. In this study, we demonstrate a half-adder operation with simple phase adjustment using plasmonic multimode interference (MMI) devices, composed of dielectric stripes on a metal film, which can be fabricated by a complementary metal-oxide semiconductor (MOS)-compatible process. Also, simultaneous operations of XOR and AND gates are substantiated experimentally by combining 1 × 1 MMI based phase adjusters and 2 × 2 MMI based intensity modulators. An experimental on-off ratio of at least 4.3 dB is confirmed using scanning near-field optical microscopy. The proposed structure will contribute to high-density plasmonic circuits, fabricated by complementary MOS-compatible process or printing techniques. PMID:27086694

  5. Appearance-based human gesture recognition using multimodal features for human computer interaction

    NASA Astrophysics Data System (ADS)

    Luo, Dan; Gao, Hua; Ekenel, Hazim Kemal; Ohya, Jun

    2011-03-01

    The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

  6. Plasmonic-multimode-interference-based logic circuit with simple phase adjustment

    NASA Astrophysics Data System (ADS)

    Ota, Masashi; Sumimura, Asahi; Fukuhara, Masashi; Ishii, Yuya; Fukuda, Mitsuo

    2016-04-01

    All-optical logic circuits using surface plasmon polaritons have a potential for high-speed information processing with high-density integration beyond the diffraction limit of propagating light. However, a number of logic gates that can be cascaded is limited by complicated signal phase adjustment. In this study, we demonstrate a half-adder operation with simple phase adjustment using plasmonic multimode interference (MMI) devices, composed of dielectric stripes on a metal film, which can be fabricated by a complementary metal-oxide semiconductor (MOS)-compatible process. Also, simultaneous operations of XOR and AND gates are substantiated experimentally by combining 1 × 1 MMI based phase adjusters and 2 × 2 MMI based intensity modulators. An experimental on-off ratio of at least 4.3 dB is confirmed using scanning near-field optical microscopy. The proposed structure will contribute to high-density plasmonic circuits, fabricated by complementary MOS-compatible process or printing techniques.

  7. Face-iris multimodal biometric scheme based on feature level fusion

    NASA Astrophysics Data System (ADS)

    Huo, Guang; Liu, Yuanning; Zhu, Xiaodong; Dong, Hongxing; He, Fei

    2015-11-01

    Unlike score level fusion, feature level fusion demands all the features extracted from unimodal traits with high distinguishability, as well as homogeneity and compatibility, which is difficult to achieve. Therefore, most multimodal biometric research focuses on score level fusion, whereas few investigate feature level fusion. We propose a face-iris recognition method based on feature level fusion. We build a special two-dimensional-Gabor filter bank to extract local texture features from face and iris images, and then transform them by histogram statistics into an energy-orientation variance histogram feature with lower dimensions and higher distinguishability. Finally, through a fusion-recognition strategy based on principal components analysis and support vector machine (FRSPS), feature level fusion and one-to-n identification are accomplished. The experimental results demonstrate that this method can not only effectively extract face and iris features but also provide higher recognition accuracy. Compared with some state-of-the-art fusion methods, the proposed method has a significant performance advantage.

  8. Personalized, relevance-based Multimodal Robotic Imaging and augmented reality for Computer Assisted Interventions.

    PubMed

    Navab, Nassir; Fellow, Miccai; Hennersperger, Christoph; Frisch, Benjamin; Fürst, Bernhard

    2016-10-01

    In the last decade, many researchers in medical image computing and computer assisted interventions across the world focused on the development of the Virtual Physiological Human (VPH), aiming at changing the practice of medicine from classification and treatment of diseases to that of modeling and treating patients. These projects resulted in major advancements in segmentation, registration, morphological, physiological and biomechanical modeling based on state of art medical imaging as well as other sensory data. However, a major issue which has not yet come into the focus is personalizing intra-operative imaging, allowing for optimal treatment. In this paper, we discuss the personalization of imaging and visualization process with particular focus on satisfying the challenging requirements of computer assisted interventions. We discuss such requirements and review a series of scientific contributions made by our research team to tackle some of these major challenges. PMID:27475417

  9. 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

  10. Atlas-registration based image segmentation of MRI human thigh muscles in 3D space

    NASA Astrophysics Data System (ADS)

    Ahmad, Ezak; Yap, Moi Hoon; Degens, Hans; McPhee, Jamie S.

    2014-03-01

    Automatic segmentation of anatomic structures of magnetic resonance thigh scans can be a challenging task due to the potential lack of precisely defined muscle boundaries and issues related to intensity inhomogeneity or bias field across an image. In this paper, we demonstrate a combination framework of atlas construction and image registration methods to propagate the desired region of interest (ROI) between atlas image and the targeted MRI thigh scans for quadriceps muscles, femur cortical layer and bone marrow segmentations. The proposed system employs a semi-automatic segmentation method on an initial image in one dataset (from a series of images). The segmented initial image is then used as an atlas image to automate the segmentation of other images in the MRI scans (3-D space). The processes include: ROI labeling, atlas construction and registration, and morphological transform correspondence pixels (in terms of feature and intensity value) between the atlas (template) image and the targeted image based on the prior atlas information and non-rigid image registration methods.

  11. 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.

  12. Cellular neural network-based hybrid approach toward automatic image registration

    NASA Astrophysics Data System (ADS)

    Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

    2013-01-01

    Image registration is a key component of various image processing operations that 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 has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been 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 coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, 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. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

  13. 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.

  14. 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.

  15. Biomedical article retrieval using multimodal features and image annotations in region-based CBIR

    NASA Astrophysics Data System (ADS)

    You, Daekeun; Antani, Sameer; Demner-Fushman, Dina; Rahman, Md Mahmudur; Govindaraju, Venu; Thoma, George R.

    2010-01-01

    Biomedical images are invaluable in establishing diagnosis, acquiring technical skills, and implementing best practices in many areas of medicine. At present, images needed for instructional purposes or in support of clinical decisions appear in specialized databases and in biomedical articles, and are often not easily accessible to retrieval tools. Our goal is to automatically annotate images extracted from scientific publications with respect to their usefulness for clinical decision support and instructional purposes, and project the annotations onto images stored in databases by linking images through content-based image similarity. Authors often use text labels and pointers overlaid on figures and illustrations in the articles to highlight regions of interest (ROI). These annotations are then referenced in the caption text or figure citations in the article text. In previous research we have developed two methods (a heuristic and dynamic time warping-based methods) for localizing and recognizing such pointers on biomedical images. In this work, we add robustness to our previous efforts by using a machine learning based approach to localizing and recognizing the pointers. Identifying these can assist in extracting relevant image content at regions within the image that are likely to be highly relevant to the discussion in the article text. Image regions can then be annotated using biomedical concepts from extracted snippets of text pertaining to images in scientific biomedical articles that are identified using National Library of Medicine's Unified Medical Language System® (UMLS) Metathesaurus. The resulting regional annotation and extracted image content are then used as indices for biomedical article retrieval using the multimodal features and region-based content-based image retrieval (CBIR) techniques. The hypothesis that such an approach would improve biomedical document retrieval is validated through experiments on an expert-marked biomedical article

  16. User-based representation of time-resolved multimodal public transportation networks.

    PubMed

    Alessandretti, Laura; Karsai, Márton; Gauvin, Laetitia

    2016-07-01

    Multimodal transportation systems, with several coexisting services like bus, tram and metro, can be represented as time-resolved multilayer networks where the different transportation modes connecting the same set of nodes are associated with distinct network layers. Their quantitative description became possible recently due to openly accessible datasets describing the geo-localized transportation dynamics of large urban areas. Advancements call for novel analytics, which combines earlier established methods and exploits the inherent complexity of the data. Here, we provide a novel user-based representation of public transportation systems, which combines representations, accounting for the presence of multiple lines and reducing the effect of spatial embeddedness, while considering the total travel time, its variability across the schedule, and taking into account the number of transfers necessary. After the adjustment of earlier techniques to the novel representation framework, we analyse the public transportation systems of several French municipal areas and identify hidden patterns of privileged connections. Furthermore, we study their efficiency as compared to the commuting flow. The proposed representation could help to enhance resilience of local transportation systems to provide better design policies for future developments. PMID:27493773

  17. Organic white-light-emitting devices based on a multimode resonant microcavity

    NASA Astrophysics Data System (ADS)

    Zhang, Hongmei; You, Han; Wang, Wei; Shi, Jiawei; Guo, Shuxu; Liu, Mingda; Ma, Dongge

    2006-08-01

    Organic white-light-emitting devices (OLEDs) based on a multimode resonant microcavity defined by a pair of dielectric mirrors and metal mirrors were presented. By selective effects of the quarter-wave dielectric stack mirror on mode, white light emission containing three individual narrow peaks of red, green and blue was achieved, and showed weak dependence on the viewing angle. The Commission Internationale De L'Eclairage (CIE) chromaticity coordinates changed from (0.29, 0.37) at 0° to (0.31, 0.33) at 40°. Furthermore, the brightness and electroluminescence efficiency of the microcavity OLEDs were enhanced compared with noncavity OLEDs. The maximum brightness reached 1940 cd m-2 at a current density of 200 mA cm-2, and the maximum current efficiency and power efficiency are 1.6 cd A-1 at a current density of 12 mA cm-2 and 0.41 lm W-1 at a current density of 1.6 mA cm-2, which are over 1.6 times higher than that of a noncavity OLED.

  18. Differential diagnosis between mesothelioma and adenocarcinoma: a multimodal approach based on ultrastructure and immunocytochemistry

    SciTech Connect

    Bedrossian, C.W.; Bonsib, S.; Moran, C. )

    1992-05-01

    Most compensations for asbestos-related deaths secondary to cancer center around mesothelioma and bronchogenic carcinoma. The differential diagnosis between mesothelioma and adenocarcinoma is a common and troublesome one, necessitating the correlation between clinical history, radiographic findings, and pathologic examination of tissues and cells. We describe a multimodal approach based on the use of routine and special stains, immunocytochemistry, and electron microscopy for distinguishing between mesothelioma and adenocarcinoma. Once a malignant diagnosis is arrived at by careful pathological examination, the tumor is classified as mesothelioma if mesothelial cells are identified as the constituent cells of the neoplasm. Mesothelial cells are recognized by (1) their main ultrastructural features: slender and elongated microvilli, abundant intermediate filaments, and lacking secretory granules; and (2) their characteristic immunocytochemical reactivity: positivity for cytokeratin, EMA, and vimentin, and negativity for carcinoembryonic antigen (CEA), B72-3, Leu-M1, and other gland-cell markers. A variety of methods have been attempted in an effort to distinguish between reactive and malignant mesothelial cells. In practice, however, such distinction depends more on experience and expertise than in any fool-proof ancillary tests. A number of these tests are discussed along with the illustration of classical and unusual examples of mesothelioma and other pleural tumors.

  19. User-based representation of time-resolved multimodal public transportation networks

    PubMed Central

    Alessandretti, Laura; Gauvin, Laetitia

    2016-01-01

    Multimodal transportation systems, with several coexisting services like bus, tram and metro, can be represented as time-resolved multilayer networks where the different transportation modes connecting the same set of nodes are associated with distinct network layers. Their quantitative description became possible recently due to openly accessible datasets describing the geo-localized transportation dynamics of large urban areas. Advancements call for novel analytics, which combines earlier established methods and exploits the inherent complexity of the data. Here, we provide a novel user-based representation of public transportation systems, which combines representations, accounting for the presence of multiple lines and reducing the effect of spatial embeddedness, while considering the total travel time, its variability across the schedule, and taking into account the number of transfers necessary. After the adjustment of earlier techniques to the novel representation framework, we analyse the public transportation systems of several French municipal areas and identify hidden patterns of privileged connections. Furthermore, we study their efficiency as compared to the commuting flow. The proposed representation could help to enhance resilience of local transportation systems to provide better design policies for future developments. PMID:27493773

  20. 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.

  1. 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. PMID:25817713

  2. SU-E-I-83: Error Analysis of Multi-Modality Image-Based Volumes of Rodent Solid Tumors Using a Preclinical Multi-Modality QA Phantom

    SciTech Connect

    Lee, Y; Fullerton, G; Goins, B

    2015-06-15

    Purpose: In our previous study a preclinical multi-modality quality assurance (QA) phantom that contains five tumor-simulating test objects with 2, 4, 7, 10 and 14 mm diameters was developed for accurate tumor size measurement by researchers during cancer drug development and testing. This study analyzed the errors during tumor volume measurement from preclinical magnetic resonance (MR), micro-computed tomography (micro- CT) and ultrasound (US) images acquired in a rodent tumor model using the preclinical multi-modality QA phantom. Methods: Using preclinical 7-Tesla MR, US and micro-CT scanners, images were acquired of subcutaneous SCC4 tumor xenografts in nude rats (3–4 rats per group; 5 groups) along with the QA phantom using the same imaging protocols. After tumors were excised, in-air micro-CT imaging was performed to determine reference tumor volume. Volumes measured for the rat tumors and phantom test objects were calculated using formula V = (π/6)*a*b*c where a, b and c are the maximum diameters in three perpendicular dimensions determined by the three imaging modalities. Then linear regression analysis was performed to compare image-based tumor volumes with the reference tumor volume and known test object volume for the rats and the phantom respectively. Results: The slopes of regression lines for in-vivo tumor volumes measured by three imaging modalities were 1.021, 1.101 and 0.862 for MRI, micro-CT and US respectively. For phantom, the slopes were 0.9485, 0.9971 and 0.9734 for MRI, micro-CT and US respectively. Conclusion: For both animal and phantom studies, random and systematic errors were observed. Random errors were observer-dependent and systematic errors were mainly due to selected imaging protocols and/or measurement method. In the animal study, there were additional systematic errors attributed to ellipsoidal assumption for tumor shape. The systematic errors measured using the QA phantom need to be taken into account to reduce measurement

  3. Electrically tuneable directional coupling and switching based on multimode interference effect in dielectric loaded graphene plasmon waveguides

    NASA Astrophysics Data System (ADS)

    Qi, Zhe; Zhu, Zhihong; Xu, Wei; Zhang, Jianfa; Guo, Chucai; Liu, Ken; Yuan, Xiaodong; Qin, Shiqiao

    2016-06-01

    We have numerically demonstrated that electrically tuneable directional coupling and switching can be realized based on the multimode interference effect in dielectric-loaded graphene plasmon waveguides (DLGPWs) of our own design. The total field profile resulting from a superposition of all guided modes in the multimode dielectric-loaded graphene plasmon waveguide is electrically controllable because the propagation properties of the first three guided modes supported by the DLGPW can be effectively manipulated by electrostatic doping of graphene. The functional size of the device is only several micrometres, which is much smaller than the working wavelength. Such electrically controlled multifunctional devices may find potential applications in high-density integrated active plasmonic circuits.

  4. Seawater pH sensor based on the long period grating in a single-mode-multimode-single-mode structure

    NASA Astrophysics Data System (ADS)

    Wang, Ke; Klimov, Denis; Kolber, Zbigniew

    2009-03-01

    A pH sensor is developed based on the long-period grating (LPG) inscribed into a single-mode-multimode-single-mode (SMS) structure in order to measure the pH in seawater. The LPG is formed by using a focused CO2 laser at LPG's critical period (1 mm). The transmission characteristics are similar to that of a multimode fiber. However, the SMS structure has a higher sensitivity because mode coupling only happens between the fundamental mode and higher-order modes in the SMS structure. The pH-sensitive hydrogel is made by the thermal cross-link of poly vinyl alcohol and poly acrylic acid. This sensor has been utilized in seawater pH sensing in the range of 6-8. Experiments have confirmed that the sensor is sensitive and repeatable.

  5. A novel method to generate a self-accelerating Bessel-like beam based on graded index multimode optical fiber

    NASA Astrophysics Data System (ADS)

    Zhang, Yaxun; Liu, Chunlan; Yu, Zhang; Liu, Zhihai; Zhao, Enming; Yang, Jun; Yuan, Libo

    2015-09-01

    We propose and demonstrate a transverse self-accelerating Bessel-like beam generator based on a graded index multimode optical fiber(GIF). The single-mode fiber and the graded-index multimode fiber are spliced with a defined offset. The offset Δx and the GIF length L affect the final properties of the Bessel-like beam, here we choose the offset Δx=20μm and the GIF length L=430μm to be optimal. The beam accelerates along the designed parabolic path up to 250μm in z direction and 40μm in x direction, the curvature of bending is 16% (40μm/250μm, x/z). This transverse self-accelerating Bessel-like beam generator based on the graded index multimode optical fiber constitutes a new development for high-precision micro particles experiments and manipulations because of its simple structure, high integration and small size.

  6. A Learning Based Fiducial-driven Registration Scheme for Evaluating Laser Ablation Changes in Neurological Disorders

    PubMed Central

    Wan, Tao; Bloch, B.Nicolas; Danish, Shabbar; Madabhushi, Anant

    2014-01-01

    In this work, we present a novel learning based fiducial driven registration (LeFiR) scheme which utilizes a point matching technique to identify the optimal configuration of landmarks to better recover deformation between a target and a moving image. Moreover, we employ the LeFiR scheme to model the localized nature of deformation introduced by a new treatment modality - laser induced interstitial thermal therapy (LITT) for treating neurological disorders. Magnetic resonance (MR) guided LITT has recently emerged as a minimally invasive alternative to craniotomy for local treatment of brain diseases (such as glioblastoma multiforme (GBM), epilepsy). However, LITT is currently only practised as an investigational procedure world-wide due to lack of data on longer term patient outcome following LITT. There is thus a need to quantitatively evaluate treatment related changes between post- and pre-LITT in terms of MR imaging markers. In order to validate LeFiR, we tested the scheme on a synthetic brain dataset (SBD) and in two real clinical scenarios for treating GBM and epilepsy with LITT. Four experiments under different deformation profiles simulating localized ablation effects of LITT on MRI were conducted on 286 pairs of SBD images. The training landmark configurations were obtained through 2000 iterations of registration where the points with consistently best registration performance were selected. The estimated landmarks greatly improved the quality metrics compared to a uniform grid (UniG) placement scheme, a speeded-up robust features (SURF) based method, and a scale-invariant feature transform (SIFT) based method as well as a generic free-form deformation (FFD) approach. The LeFiR method achieved average 90% improvement in recovering the local deformation compared to 82% for the uniform grid placement, 62% for the SURF based approach, and 16% for the generic FFD approach. On the real GBM and epilepsy data, the quantitative results showed that Le

  7. Multimodal wireless sensor network-based ambient assisted living in real homes with multiple residents.

    PubMed

    Tunca, Can; Alemdar, Hande; Ertan, Halil; Incel, Ozlem Durmaz; Ersoy, Cem

    2014-01-01

    Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting. PMID:24887044

  8. Appearance-Based Multimodal Human Tracking and Identification for Healthcare in the Digital Home

    PubMed Central

    Yang, Mau-Tsuen; Huang, Shen-Yen

    2014-01-01

    There is an urgent need for intelligent home surveillance systems to provide home security, monitor health conditions, and detect emergencies of family members. One of the fundamental problems to realize the power of these intelligent services is how to detect, track, and identify people at home. Compared to RFID tags that need to be worn all the time, vision-based sensors provide a natural and nonintrusive solution. Observing that body appearance and body build, as well as face, provide valuable cues for human identification, we model and record multi-view faces, full-body colors and shapes of family members in an appearance database by using two Kinects located at a home's entrance. Then the Kinects and another set of color cameras installed in other parts of the house are used to detect, track, and identify people by matching the captured color images with the registered templates in the appearance database. People are detected and tracked by multisensor fusion (Kinects and color cameras) using a Kalman filter that can handle duplicate or partial measurements. People are identified by multimodal fusion (face, body appearance, and silhouette) using a track-based majority voting. Moreover, the appearance-based human detection, tracking, and identification modules can cooperate seamlessly and benefit from each other. Experimental results show the effectiveness of the human tracking across multiple sensors and human identification considering the information of multi-view faces, full-body clothes, and silhouettes. The proposed home surveillance system can be applied to domestic applications in digital home security and intelligent healthcare. PMID:25098207

  9. Multimodal Wireless Sensor Network-Based Ambient Assisted Living in Real Homes with Multiple Residents

    PubMed Central

    Tunca, Can; Alemdar, Hande; Ertan, Halil; Incel, Ozlem Durmaz; Ersoy, Cem

    2014-01-01

    Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption monitoring. However, due to the limitations of the sensor devices, challenges in wireless communication and the challenges in processing large amounts of sensor data in order to recognize complex human activities, WSN-based AAL systems are not effectively integrated in the home environment. Additionally, given the variety of sensor types and activities, selecting the most suitable set of sensors in the deployment is an important task. In order to investigate and propose solutions to such challenges, we introduce a WSN-based multimodal AAL system compatible for homes with multiple residents. Particularly, we focus on the details of the system architecture, including the challenges of sensor selection, deployment, networking and data collection and provide guidelines for the design and deployment of an effective AAL system. We also present the details of the field study we conducted, using the systems deployed in two different real home environments with multiple residents. With these systems, we are able to collect ambient sensor data from multiple homes. This data can be used to assess the wellbeing of the residents and identify deviations from everyday routines, which may be indicators of health problems. Finally, in order to elaborate on the possible applications of the proposed AAL system and to exemplify directions for processing the collected data, we provide the results of several human activity inference experiments, along with examples on how such results could be interpreted. We believe that the experiences shared in this work will contribute towards accelerating the acceptance of WSN-based AAL systems in the home setting. PMID:24887044

  10. Non-rigid registration between 3D ultrasound and CT images of the liver based on intensity and gradient information

    NASA Astrophysics Data System (ADS)

    Lee, Duhgoon; Nam, Woo Hyun; Lee, Jae Young; Ra, Jong Beom

    2011-01-01

    In order to utilize both ultrasound (US) and computed tomography (CT) images of the liver concurrently for medical applications such as diagnosis and image-guided intervention, non-rigid registration between these two types of images is an essential step, as local deformation between US and CT images exists due to the different respiratory phases involved and due to the probe pressure that occurs in US imaging. This paper introduces a voxel-based non-rigid registration algorithm between the 3D B-mode US and CT images of the liver. In the proposed algorithm, to improve the registration accuracy, we utilize the surface information of the liver and gallbladder in addition to the information of the vessels inside the liver. For an effective correlation between US and CT images, we treat those anatomical regions separately according to their characteristics in US and CT images. Based on a novel objective function using a 3D joint histogram of the intensity and gradient information, vessel-based non-rigid registration is followed by surface-based non-rigid registration in sequence, which improves the registration accuracy. The proposed algorithm is tested for ten clinical datasets and quantitative evaluations are conducted. Experimental results show that the registration error between anatomical features of US and CT images is less than 2 mm on average, even with local deformation due to different respiratory phases and probe pressure. In addition, the lesion registration error is less than 3 mm on average with a maximum of 4.5 mm that is considered acceptable for clinical applications.

  11. 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.

  12. Automatic registration of multisensor images with affine deformation based on triangle area representation

    NASA Astrophysics Data System (ADS)

    Li, Bin; Wang, Wei; Ye, Hao

    2013-01-01

    A new automatic feature-based registration algorithm of multisensor images with affine deformation is presented. Although the feature-based registration methods have an advantage in reducing computational load over the area-based ones, certain typical issues such as complex deformation and grayscale discrepancy existing in a multisensor image pair will make the design of a robust feature descriptor challenging. To deal with these issues, in contrast with most existing feature-based methods that describe feature points directly, we introduce an additional procedure of feature quadrilateral construction in the proposed algorithm. Then the descriptors for the constructed feature quadrilaterals are designed based on the affine-invariance property of triangle area representation. By doing these, the proposed algorithm's robustness to both affine deformation and grayscale discrepancy can be guaranteed. Besides, since the calculation of feature descriptors only involves simple algebraic operations, the proposed method has low computational load. Experimental results using real multisensor image pairs are presented to show the merits of the proposed method.

  13. User-oriented summary extraction for soccer video based on multimodal analysis

    NASA Astrophysics Data System (ADS)

    Liu, Huayong; Jiang, Shanshan; He, Tingting

    2011-11-01

    An advanced user-oriented summary extraction method for soccer video is proposed in this work. Firstly, an algorithm of user-oriented summary extraction for soccer video is introduced. A novel approach that integrates multimodal analysis, such as extraction and analysis of the stadium features, moving object features, audio features and text features is introduced. By these features the semantic of the soccer video and the highlight mode are obtained. Then we can find the highlight position and put them together by highlight degrees to obtain the video summary. The experimental results for sports video of world cup soccer games indicate that multimodal analysis is effective for soccer video browsing and retrieval.

  14. A simultaneous multimodal imaging system for tissue functional parameters

    NASA Astrophysics Data System (ADS)

    Ren, Wenqi; Zhang, Zhiwu; Wu, Qiang; Zhang, Shiwu; Xu, Ronald

    2014-02-01

    Simultaneous and quantitative assessment of skin functional characteristics in different modalities will facilitate diagnosis and therapy in many clinical applications such as wound healing. However, many existing clinical practices and multimodal imaging systems are subjective, qualitative, sequential for multimodal data collection, and need co-registration between different modalities. To overcome these limitations, we developed a multimodal imaging system for quantitative, non-invasive, and simultaneous imaging of cutaneous tissue oxygenation and blood perfusion parameters. The imaging system integrated multispectral and laser speckle imaging technologies into one experimental setup. A Labview interface was developed for equipment control, synchronization, and image acquisition. Advanced algorithms based on a wide gap second derivative reflectometry and laser speckle contrast analysis (LASCA) were developed for accurate reconstruction of tissue oxygenation and blood perfusion respectively. Quantitative calibration experiments and a new style of skinsimulating phantom were designed to verify the accuracy and reliability of the imaging system. The experimental results were compared with a Moor tissue oxygenation and perfusion monitor. For In vivo testing, a post-occlusion reactive hyperemia (PORH) procedure in human subject and an ongoing wound healing monitoring experiment using dorsal skinfold chamber models were conducted to validate the usability of our system for dynamic detection of oxygenation and perfusion parameters. In this study, we have not only setup an advanced multimodal imaging system for cutaneous tissue oxygenation and perfusion parameters but also elucidated its potential for wound healing assessment in clinical practice.

  15. 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.

  16. Assessment of eye fatigue caused by 3D displays based on multimodal measurements.

    PubMed

    Bang, Jae Won; Heo, Hwan; Choi, Jong-Suk; Park, Kang Ryoung

    2014-01-01

    With the development of 3D displays, user's eye fatigue has been an important issue when viewing these displays. There have been previous studies conducted on eye fatigue related to 3D display use, however, most of these have employed a limited number of modalities for measurements, such as electroencephalograms (EEGs), biomedical signals, and eye responses. In this paper, we propose a new assessment of eye fatigue related to 3D display use based on multimodal measurements. compared to previous works Our research is novel in the following four ways: first, to enhance the accuracy of assessment of eye fatigue, we measure EEG signals, eye blinking rate (BR), facial temperature (FT), and a subjective evaluation (SE) score before and after a user watches a 3D display; second, in order to accurately measure BR in a manner that is convenient for the user, we implement a remote gaze-tracking system using a high speed (mega-pixel) camera that measures eye blinks of both eyes; thirdly, changes in the FT are measured using a remote thermal camera, which can enhance the measurement of eye fatigue, and fourth, we perform various statistical analyses to evaluate the correlation between the EEG signal, eye BR, FT, and the SE score based on the T-test, correlation matrix, and effect size. Results show that the correlation of the SE with other data (FT, BR, and EEG) is the highest, while those of the FT, BR, and EEG with other data are second, third, and fourth highest, respectively. PMID:25192315

  17. Multimodal Classification of Mild Cognitive Impairment Based on Partial Least Squares.

    PubMed

    Wang, Pingyue; Chen, Kewei; Yao, Li; Hu, Bin; Wu, Xia; Zhang, Jiacai; Ye, Qing; Guo, Xiaojuan

    2016-08-10

    In recent years, increasing attention has been given to the identification of the conversion of mild cognitive impairment (MCI) to Alzheimer's disease (AD). Brain neuroimaging techniques have been widely used to support the classification or prediction of MCI. The present study combined magnetic resonance imaging (MRI), 18F-fluorodeoxyglucose PET (FDG-PET), and 18F-florbetapir PET (florbetapir-PET) to discriminate MCI converters (MCI-c, individuals with MCI who convert to AD) from MCI non-converters (MCI-nc, individuals with MCI who have not converted to AD in the follow-up period) based on the partial least squares (PLS) method. Two types of PLS models (informed PLS and agnostic PLS) were built based on 64 MCI-c and 65 MCI-nc from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The results showed that the three-modality informed PLS model achieved better classification accuracy of 81.40%, sensitivity of 79.69%, and specificity of 83.08% compared with the single-modality model, and the three-modality agnostic PLS model also achieved better classification compared with the two-modality model. Moreover, combining the three modalities with clinical test score (ADAS-cog), the agnostic PLS model (independent data: florbetapir-PET; dependent data: FDG-PET and MRI) achieved optimal accuracy of 86.05%, sensitivity of 81.25%, and specificity of 90.77%. In addition, the comparison of PLS, support vector machine (SVM), and random forest (RF) showed greater diagnostic power of PLS. These results suggested that our multimodal PLS model has the potential to discriminate MCI-c from the MCI-nc and may therefore be helpful in the early diagnosis of AD. PMID:27567818

  18. Assessment of Eye Fatigue Caused by 3D Displays Based on Multimodal Measurements

    PubMed Central

    Bang, Jae Won; Heo, Hwan; Choi, Jong-Suk; Park, Kang Ryoung

    2014-01-01

    With the development of 3D displays, user's eye fatigue has been an important issue when viewing these displays. There have been previous studies conducted on eye fatigue related to 3D display use, however, most of these have employed a limited number of modalities for measurements, such as electroencephalograms (EEGs), biomedical signals, and eye responses. In this paper, we propose a new assessment of eye fatigue related to 3D display use based on multimodal measurements. compared to previous works Our research is novel in the following four ways: first, to enhance the accuracy of assessment of eye fatigue, we measure EEG signals, eye blinking rate (BR), facial temperature (FT), and a subjective evaluation (SE) score before and after a user watches a 3D display; second, in order to accurately measure BR in a manner that is convenient for the user, we implement a remote gaze-tracking system using a high speed (mega-pixel) camera that measures eye blinks of both eyes; thirdly, changes in the FT are measured using a remote thermal camera, which can enhance the measurement of eye fatigue, and fourth, we perform various statistical analyses to evaluate the correlation between the EEG signal, eye BR, FT, and the SE score based on the T-test, correlation matrix, and effect size. Results show that the correlation of the SE with other data (FT, BR, and EEG) is the highest, while those of the FT, BR, and EEG with other data are second, third, and fourth highest, respectively. PMID:25192315

  19. Multi-modal vibration based MEMS energy harvesters for ultra-low power wireless functional nodes

    NASA Astrophysics Data System (ADS)

    Iannacci, J.; Gottardi, M.; Serra, E.; Di Criscienzo, R.; Borrielli, A.; Bonaldi, M.

    2013-05-01

    The aim of this contribution is to report and discuss a preliminary study and rough optimization of a novel concept of MEMS device for vibration energy harvesting, based on a multi-modal dynamic behavior. The circular-shaped device features Four-Leaf Clover-like (FLC) double spring-mass cascaded systems, kept constrained to the surrounding frame by means of four straight beams. The combination of flexural bending behavior of the slender beams plus deformable parts of the petals enable to populate the desired vibration frequency range with a number of resonant modes, and improve the energy conversion capability of the micro-transducer. The harvester device, conceived for piezoelectric mechanical into electric energy conversion, is intended to sense environmental vibrations and, thereby, its geometry is optimized to have a large concentration of resonant modes in a frequency range below 5-10 kHz. The results of FEM (Finite Element Method) based analysis performed in ANSYSTM Workbench are reported, both concerning modal and harmonic response, providing important indications related to the device geometry optimization. The analysis reported in this work is limited to the sole mechanical modeling of the proposed MEMS harvester device concept. Future developments of the study will encompass the inclusion of piezoelectric conversion in the FEM simulations, in order to have indications of the actual power levels achievable with the proposed harvester concept. Furthermore, the results of the FEM studies here discussed, will be validated against experimental data, as soon as the MEMS resonator specimens, currently under fabrication, are ready for testing.

  20. 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

  1. 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.

  2. Toward efficient biomechanical-based deformable image registration of lungs for image-guided radiotherapy

    NASA Astrophysics Data System (ADS)

    Al-Mayah, Adil; Moseley, Joanne; Velec, Mike; Brock, Kristy

    2011-08-01

    Both accuracy and efficiency are critical for the implementation of biomechanical model-based deformable registration in clinical practice. The focus of this investigation is to evaluate the potential of improving the efficiency of the deformable image registration of the human lungs without loss of accuracy. Three-dimensional finite element models have been developed using image data of 14 lung cancer patients. Each model consists of two lungs, tumor and external body. Sliding of the lungs inside the chest cavity is modeled using a frictionless surface-based contact model. The effect of the type of element, finite deformation and elasticity on the accuracy and computing time is investigated. Linear and quadrilateral tetrahedral elements are used with linear and nonlinear geometric analysis. Two types of material properties are applied namely: elastic and hyperelastic. The accuracy of each of the four models is examined using a number of anatomical landmarks representing the vessels bifurcation points distributed across the lungs. The registration error is not significantly affected by the element type or linearity of analysis, with an average vector error of around 2.8 mm. The displacement differences between linear and nonlinear analysis methods are calculated for all lungs nodes and a maximum value of 3.6 mm is found in one of the nodes near the entrance of the bronchial tree into the lungs. The 95 percentile of displacement difference ranges between 0.4 and 0.8 mm. However, the time required for the analysis is reduced from 95 min in the quadratic elements nonlinear geometry model to 3.4 min in the linear element linear geometry model. Therefore using linear tetrahedral elements with linear elastic materials and linear geometry is preferable for modeling the breathing motion of lungs for image-guided radiotherapy applications.

  3. SU-F-BRF-08: Conformal Mapping-Based 3D Surface Matching and Registration

    SciTech Connect

    Song, Y; Zeng, W; Gu, X; Liu, C

    2014-06-15

    Purpose: Recently, non-rigid 3D surface matching and registration has been used extensively in engineering and medicine. However, matching 3D surfaces undergoing non-rigid deformation accurately is still a challenging mathematical problem. In this study, we present a novel algorithm to address this issue by introducing intrinsic symmetry to the registration Methods: Our computational algorithm for symmetric conformal mapping is divided into three major steps: 1) Finding the symmetric plane; 2) Finding feature points; and 3) Performing cross registration. The key strategy is to preserve the symmetry during the conformal mapping, such that the image on the parameter domain is symmetric and the area distortion factor on the parameter image is also symmetric. Several novel algorithms were developed using different conformal geometric tools. One was based on solving Riemann-Cauchy equation and the other one employed curvature flow Results: Our algorithm was implemented using generic C++ on Windows XP and used conjugate gradient search optimization for acceleration. The human face 3D surface images were acquired using a high speed 3D scanner based on the phase-shifting method. The scanning speed was 30 frames/sec. The image resolution for each frame was 640 × 480. For 3D human face surfaces with different expressions, postures, and boundaries, our algorithms were able to produce consistent result on the texture pattern on the overlapping region Conclusion: We proposed a novel algorithm to improve the robustness of conformal geometric methods by incorporating the symmetric information into the mapping process. To objectively evaluate its performance, we compared it with most existing techniques. Experimental results indicated that our method outperformed all the others in terms of robustness. The technique has a great potential in real-time patient monitoring and tracking in image-guided radiation therapy.

  4. An Automated Parallel Image Registration Technique Based on the Correlation of Wavelet Features

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; Campbell, William J.; Cromp, Robert F.; Zukor, Dorothy (Technical Monitor)

    2001-01-01

    With the increasing importance of multiple platform/multiple remote sensing missions, fast and automatic integration of digital data from disparate sources has become critical to the success of these endeavors. Our work utilizes maxima of wavelet coefficients to form the basic features of a correlation-based automatic registration algorithm. Our wavelet-based registration algorithm is tested successfully with data from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and the Landsat/Thematic Mapper(TM), which differ by translation and/or rotation. By the choice of high-frequency wavelet features, this method is similar to an edge-based correlation method, but by exploiting the multi-resolution nature of a wavelet decomposition, our method achieves higher computational speeds for comparable accuracies. This algorithm has been implemented on a Single Instruction Multiple Data (SIMD) massively parallel computer, the MasPar MP-2, as well as on the CrayT3D, the Cray T3E and a Beowulf cluster of Pentium workstations.

  5. Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography

    PubMed Central

    Yang, Xiaofeng; Torres, Mylin; Kirkpatrick, Stephanie; Curran, Walter J.; Liu, Tian

    2015-01-01

    In this paper, we present a new approach to calculate 2D strain through the registration of the pre- and post-compression (deformation) B-mode image sequences based on an intensity-based non-rigid registration algorithm (INRA). Compared with the most commonly used cross-correlation (CC) method, our approach is not constrained to any particular set of directions, and can overcome displacement estimation errors introduced by incoherent motion and variations in the signal under high compression. This INRA method was tested using phantom and in vivo data. The robustness of our approach was demonstrated in the axial direction as well as the lateral direction where the standard CC method frequently fails. In addition, our approach copes well under large compression (over 6%). In the phantom study, we computed the strain image under various compressions and calculated the signal-to-noise (SNR) and contrast-to-noise (CNS) ratios. The SNR and CNS values of the INRA method were much higher than those calculated from the CC-based method. Furthermore, the clinical feasibility of our approach was demonstrated with the in vivo data from patients with arm lymphedema. PMID:25914492

  6. Ultrasound 2D strain estimator based on image registration for ultrasound elastography

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Torres, Mylin; Kirkpatrick, Stephanie; Curran, Walter J.; Liu, Tian

    2014-03-01

    In this paper, we present a new approach to calculate 2D strain through the registration of the pre- and post-compression (deformation) B-mode image sequences based on an intensity-based non-rigid registration algorithm (INRA). Compared with the most commonly used cross-correlation (CC) method, our approach is not constrained to any particular set of directions, and can overcome displacement estimation errors introduced by incoherent motion and variations in the signal under high compression. This INRA method was tested using phantom and in vivo data. The robustness of our approach was demonstrated in the axial direction as well as the lateral direction where the standard CC method frequently fails. In addition, our approach copes well under large compression (over 6%). In the phantom study, we computed the strain image under various compressions and calculated the signal-to-noise (SNR) and contrast-to-noise (CNS) ratios. The SNR and CNS values of the INRA method were much higher than those calculated from the CC-based method. Furthermore, the clinical feasibility of our approach was demonstrated with the in vivo data from patients with arm lymphedema.

  7. Active illumination based 3D surface reconstruction and registration for image guided medialization laryngoplasty

    NASA Astrophysics Data System (ADS)

    Jin, Ge; Lee, Sang-Joon; Hahn, James K.; Bielamowicz, Steven; Mittal, Rajat; Walsh, Raymond

    2007-03-01

    The medialization laryngoplasty is a surgical procedure to improve the voice function of the patient with vocal fold paresis and paralysis. An image guided system for the medialization laryngoplasty will help the surgeons to accurately place the implant and thus reduce the failure rates of the surgery. One of the fundamental challenges in image guided system is to accurately register the preoperative radiological data to the intraoperative anatomical structure of the patient. In this paper, we present a combined surface and fiducial based registration method to register the preoperative 3D CT data to the intraoperative surface of larynx. To accurately model the exposed surface area, a structured light based stereo vision technique is used for the surface reconstruction. We combined the gray code pattern and multi-line shifting to generate the intraoperative surface of the larynx. To register the point clouds from the intraoperative stage to the preoperative 3D CT data, a shape priori based ICP method is proposed to quickly register the two surfaces. The proposed approach is capable of tracking the fiducial markers and reconstructing the surface of larynx with no damage to the anatomical structure. We used off-the-shelf digital cameras, LCD projector and rapid 3D prototyper to develop our experimental system. The final RMS error in the registration is less than 1mm.

  8. Multimode interference coupler based photonic analog-to-digital conversion scheme.

    PubMed

    Shile, Wei; Jian, Wu; Lingjuan, Zhao; Chen, Yao; Chen, Ji; Dan, Lu; Xilin, Zhang; Zuoshan, Yin

    2012-09-01

    A novel phase-shifted optical quantization scheme for an all-optical analog-to-digital converter, which uses 4×4 multimode interference couplers, is demonstrated and theoretically analyzed. The whole scheme can be integrated on a chip. PMID:22940995

  9. Cross Space: The Exploration of SNS-Based Writing Activities in a Multimodal Learning Environment

    ERIC Educational Resources Information Center

    Lee, Kwang-Soon; Kim, Bong-Gyu

    2016-01-01

    This study explores the positive learning effect of formulating English sentences via Social Network Service (SNS; "Kakao-Talk") on less proficient L2 university students' (LPSs') writing, when the application is utilized as a tool to link in and out-of class activities in a multimodal-learning environment. Its objective is also to…

  10. Constructing and Using Multimodal Narratives to Research in Science Education: Contributions Based on Practical Classroom

    ERIC Educational Resources Information Center

    Lopes, J. B.; Silva, A. A.; Cravino, J. P.; Santos, C. A.; Cunha, A.; Pinto, A.; Silva, A.; Viegas, C.; Saraiva, E.; Branco, M. J.

    2014-01-01

    This study deals with the problem of how to collect genuine and useful data about science classroom practices, and preserving the complex and holistic nature of teaching and learning. Additionally, we were looking for an instrument that would allow comparability and verifiability for teaching and research purposes. Given the multimodality of…

  11. Multimodal MRI-Based Study in Patients with SPG4 Mutations

    PubMed Central

    Rezende, Thiago J. R.; de Albuquerque, Milena; Lamas, Gustavo M.; Martinez, Alberto R. M.; Campos, Brunno M.; Casseb, Raphael F.; Silva, Cynthia B.; Branco, Lucas M. T.; D'Abreu, Anelyssa; Lopes-Cendes, Iscia; Cendes, Fernando; França, Marcondes C.

    2015-01-01

    Mutations in the SPG4 gene (SPG4-HSP) are the most frequent cause of hereditary spastic paraplegia, but the extent of the neurodegeneration related to the disease is not yet known. Therefore, our objective is to identify regions of the central nervous system damaged in patients with SPG4-HSP using a multi-modal neuroimaging approach. In addition, we aimed to identify possible clinical correlates of such damage. Eleven patients (mean age 46.0 ± 15.0 years, 8 men) with molecular confirmation of hereditary spastic paraplegia, and 23 matched healthy controls (mean age 51.4 ± 14.1years, 17 men) underwent MRI scans in a 3T scanner. We used 3D T1 images to perform volumetric measurements of the brain and spinal cord. We then performed tract-based spatial statistics and tractography analyses of diffusion tensor images to assess microstructural integrity of white matter tracts. Disease severity was quantified with the Spastic Paraplegia Rating Scale. Correlations were then carried out between MRI metrics and clinical data. Volumetric analyses did not identify macroscopic abnormalities in the brain of hereditary spastic paraplegia patients. In contrast, we found extensive fractional anisotropy reduction in the corticospinal tracts, cingulate gyri and splenium of the corpus callosum. Spinal cord morphometry identified atrophy without flattening in the group of patients with hereditary spastic paraplegia. Fractional anisotropy of the corpus callosum and pyramidal tracts did correlate with disease severity. Hereditary spastic paraplegia is characterized by relative sparing of the cortical mantle and remarkable damage to the distal portions of the corticospinal tracts, extending into the spinal cord. PMID:25658484

  12. Multimodal MRI-based study in patients with SPG4 mutations.

    PubMed

    Rezende, Thiago J R; de Albuquerque, Milena; Lamas, Gustavo M; Martinez, Alberto R M; Campos, Brunno M; Casseb, Raphael F; Silva, Cynthia B; Branco, Lucas M T; D'Abreu, Anelyssa; Lopes-Cendes, Iscia; Cendes, Fernando; França, Marcondes C

    2015-01-01

    Mutations in the SPG4 gene (SPG4-HSP) are the most frequent cause of hereditary spastic paraplegia, but the extent of the neurodegeneration related to the disease is not yet known. Therefore, our objective is to identify regions of the central nervous system damaged in patients with SPG4-HSP using a multi-modal neuroimaging approach. In addition, we aimed to identify possible clinical correlates of such damage. Eleven patients (mean age 46.0 ± 15.0 years, 8 men) with molecular confirmation of hereditary spastic paraplegia, and 23 matched healthy controls (mean age 51.4 ± 14.1years, 17 men) underwent MRI scans in a 3T scanner. We used 3D T1 images to perform volumetric measurements of the brain and spinal cord. We then performed tract-based spatial statistics and tractography analyses of diffusion tensor images to assess microstructural integrity of white matter tracts. Disease severity was quantified with the Spastic Paraplegia Rating Scale. Correlations were then carried out between MRI metrics and clinical data. Volumetric analyses did not identify macroscopic abnormalities in the brain of hereditary spastic paraplegia patients. In contrast, we found extensive fractional anisotropy reduction in the corticospinal tracts, cingulate gyri and splenium of the corpus callosum. Spinal cord morphometry identified atrophy without flattening in the group of patients with hereditary spastic paraplegia. Fractional anisotropy of the corpus callosum and pyramidal tracts did correlate with disease severity. Hereditary spastic paraplegia is characterized by relative sparing of the cortical mantle and remarkable damage to the distal portions of the corticospinal tracts, extending into the spinal cord. PMID:25658484

  13. Atomic clocks based on extened-cavity diode laser in multimode operation

    NASA Astrophysics Data System (ADS)

    Yim, Sin; Cho, D.

    2011-05-01

    We demonstrated the possibilities to develope an atomic clock based on coherent population trapping (CPT) without using a local oscillator and a modulator. Instead of using a modulator, we use two modes from a single extended-cavity diode laser in multimode operation. Two different types of feedback system are applied to stabilize a difference frequency between the two modes and eliminate the need for an extra frequency modulation. In the first type, we employ an electronic feedback using dispersion of the CPT resonance as an error signal. The two modes are phase locked with reference to a dispersion signal from a CPT resonance of 85Rb at 3.036 GHz ground hyperfine splitting. We use D1 transition at 794.8 nm with lin ⊥lin polarizations to obtain large-contrast CPT signal. Allan deviation of the beat frequency between the two modes is 1 ×10-10 at 200-s integration time. In the second type, we employ optoelectronic feedback to construct an opto-electronic oscillator (OEO). In an OEO, the beating signal between two modes is recovered by a fast photodiode, and its output is amplified and fed back to the laser diode by using a direct modulation of an injection current. When the OEO loop is closed, oscillation frequency depends on variations of the loop length. In order to stabilize an OEO loop length and thereby its oscillation frequency, CPT cell is inserted to play a role of microwave band pass filter. Allan deviation of the CPT-stabilized OEO is 2 ×10-10 at 100-s integration time.

  14. Generating Multimodal References

    ERIC Educational Resources Information Center

    van der Sluis, Ielka; Krahmer, Emiel

    2007-01-01

    This article presents a new computational model for the generation of multimodal referring expressions (REs), based on observations in human communication. The algorithm is an extension of the graph-based algorithm proposed by Krahmer, van Erk, and Verleg (2003) and makes use of a so-called Flashlight Model for pointing. The Flashlight Model…

  15. Parallel image registration with a thin client interface

    NASA Astrophysics Data System (ADS)

    Saiprasad, Ganesh; Lo, Yi-Jung; Plishker, William; Lei, Peng; Ahmad, Tabassum; Shekhar, Raj

    2010-03-01

    Despite its high significance, the clinical utilization of image registration remains limited because of its lengthy execution time and a lack of easy access. The focus of this work was twofold. First, we accelerated our course-to-fine, volume subdivision-based image registration algorithm by a novel parallel implementation that maintains the accuracy of our uniprocessor implementation. Second, we developed a thin-client computing model with a user-friendly interface to perform rigid and nonrigid image registration. Our novel parallel computing model uses the message passing interface model on a 32-core cluster. The results show that, compared with the uniprocessor implementation, the parallel implementation of our image registration algorithm is approximately 5 times faster for rigid image registration and approximately 9 times faster for nonrigid registration for the images used. To test the viability of such systems for clinical use, we developed a thin client in the form of a plug-in in OsiriX, a well-known open source PACS workstation and DICOM viewer, and used it for two applications. The first application registered the baseline and follow-up MR brain images, whose subtraction was used to track progression of multiple sclerosis. The second application registered pretreatment PET and intratreatment CT of radiofrequency ablation patients to demonstrate a new capability of multimodality imaging guidance. The registration acceleration coupled with the remote implementation using a thin client should ultimately increase accuracy, speed, and access of image registration-based interpretations in a number of diagnostic and interventional applications.

  16. Three-dimensional elastic image registration based on strain energy minimization: application to prostate magnetic resonance imaging.

    PubMed

    Zhang, Bao; Arola, Dwayne D; Roys, Steve; Gullapalli, Rao P

    2011-08-01

    The use of magnetic resonance (MR) imaging in conjunction with an endorectal coil is currently the clinical standard for the diagnosis of prostate cancer because of the increased sensitivity and specificity of this approach. However, imaging in this manner provides images and spectra of the prostate in the deformed state because of the insertion of the endorectal coil. Such deformation may lead to uncertainties in the localization of prostate cancer during therapy. We propose a novel 3-D elastic registration procedure that is based on the minimization of a physically motivated strain energy function that requires the identification of similar features (points, curves, or surfaces) in the source and target images. The Gauss-Seidel method was used in the numerical implementation of the registration algorithm. The registration procedure was validated on synthetic digital images, MR images from prostate phantom, and MR images obtained on patients. The registration error, assessed by averaging the displacement of a fiducial landmark in the target to its corresponding point in the registered image, was 0.2 ± 0.1 pixels on synthetic images. On the prostate phantom and patient data, the registration errors were 1.0 ± 0.6 pixels (0.6 ± 0.4 mm) and 1.8 ± 0.7 pixels (1.1 ± 0.4 mm), respectively. Registration also improved image similarity (normalized cross-correlation) from 0.72 ± 0.10 to 0.96 ± 0.03 on patient data. Registration results on digital images, phantom, and prostate data in vivo demonstrate that the registration procedure can be used to significantly improve both the accuracy of localized therapies such as brachytherapy or external beam therapy and can be valuable in the longitudinal follow-up of patients after therapy. PMID:20552248

  17. MARS: a mouse atlas registration system based on a planar x-ray projector and an optical camera

    NASA Astrophysics Data System (ADS)

    Wang, Hongkai; Stout, David B.; Taschereau, Richard; Gu, Zheng; Vu, Nam T.; Prout, David L.; Chatziioannou, Arion F.

    2012-10-01

    This paper introduces a mouse atlas registration system (MARS), composed of a stationary top-view x-ray projector and a side-view optical camera, coupled to a mouse atlas registration algorithm. This system uses the x-ray and optical images to guide a fully automatic co-registration of a mouse atlas with each subject, in order to provide anatomical reference for small animal molecular imaging systems such as positron emission tomography (PET). To facilitate the registration, a statistical atlas that accounts for inter-subject anatomical variations was constructed based on 83 organ-labeled mouse micro-computed tomography (CT) images. The statistical shape model and conditional Gaussian model techniques were used to register the atlas with the x-ray image and optical photo. The accuracy of the atlas registration was evaluated by comparing the registered atlas with the organ-labeled micro-CT images of the test subjects. The results showed excellent registration accuracy of the whole-body region, and good accuracy for the brain, liver, heart, lungs and kidneys. In its implementation, the MARS was integrated with a preclinical PET scanner to deliver combined PET/MARS imaging, and to facilitate atlas-assisted analysis of the preclinical PET images.

  18. Location constraint based 2D-3D registration of fluoroscopic images and CT volumes for image-guided EP procedures

    NASA Astrophysics Data System (ADS)

    Liao, Rui; Xu, Ning; Sun, Yiyong

    2008-03-01

    Presentation of detailed anatomical structures via 3D Computed Tomographic (CT) volumes helps visualization and navigation in electrophysiology procedures (EP). Registration of the CT volume with the online fluoroscopy however is a challenging task for EP applications due to the lack of discernable features in fluoroscopic images. In this paper, we propose to use the coronary sinus (CS) catheter in bi-plane fluoroscopic images and the coronary sinus in the CT volume as a location constraint to accomplish 2D-3D registration. Two automatic registration algorithms are proposed in this study, and their performances are investigated on both simulated and real data. It is shown that compared to registration using mono-plane fluoroscopy, registration using bi-plane images results in substantially higher accuracy in 3D and enhanced robustness. In addition, compared to registering the projection of CS to the 2D CS catheter, it is more desirable to reconstruct a 3D CS catheter from the bi-plane fluoroscopy and then perform a 3D-3D registration between the CS and the reconstructed CS catheter. Quantitative validation based on simulation and visual inspection on real data demonstrates the feasibility of the proposed workflow in EP procedures.

  19. Multi-camera calibration based on openCV and multi-view registration

    NASA Astrophysics Data System (ADS)

    Deng, Xiao-ming; Wan, Xiong; Zhang, Zhi-min; Leng, Bi-yan; Lou, Ning-ning; He, Shuai

    2010-10-01

    For multi-camera calibration systems, a method based on OpenCV and multi-view registration combining calibration algorithm is proposed. First of all, using a Zhang's calibration plate (8X8 chessboard diagram) and a number of cameras (with three industrial-grade CCD) to be 9 group images shooting from different angles, using OpenCV to calibrate the parameters fast in the camera. Secondly, based on the corresponding relationship between each camera view, the computation of the rotation matrix and translation matrix is formulated as a constrained optimization problem. According to the Kuhn-Tucker theorem and the properties on the derivative of the matrix-valued function, the formulae of rotation matrix and translation matrix are deduced by using singular value decomposition algorithm. Afterwards an iterative method is utilized to get the entire coordinate transformation of pair-wise views, thus the precise multi-view registration can be conveniently achieved and then can get the relative positions in them(the camera outside the parameters).Experimental results show that the method is practical in multi-camera calibration .

  20. Target location for IR image based on IR/visual image registration

    NASA Astrophysics Data System (ADS)

    Liu, Zhao-ying; Zhou, Fu-gen; Bai, Xiang-zhi

    2009-07-01

    We propose an effective algorithm of IR target location based on image registration. This approach includes four steps--pre-processing, typical region and feature points extraction, point pattern matching, target location. Firstly, by analying the characters of the visual and IR images, a pre-processing procedure is introduced to improve the IR image quality and to make the gray distribution in IR and visual images more consistent. Secondly, mathematical morphology is used to extract typical regions around the target, and we mark the feature points based on the extracted typical regions. Thirdly, point pattern matching algorithm is applied to realize the preliminary registration of IR/visual images, triangle geometry similarity is utilized as the similarity measure to establish two points set correspondance. Finally, we take twostage location strategy to accurately locate the IR targets, least square method and mutual information theory are applied in the location strategy. Experiment results demonstrate a high rate (above 93%) of success for predicting target location, the results showed that this method can effectively meet the requirement of target detection in low resolution and low contrast IR images.

  1. Impact of Computed Tomography Image Quality on Image-Guided Radiation Therapy Based on Soft Tissue Registration

    SciTech Connect

    Morrow, Natalya V.; Lawton, Colleen A.; Qi, X. Sharon; Li, X. Allen

    2012-04-01

    Purpose: In image-guided radiation therapy (IGRT), different computed tomography (CT) modalities with varying image quality are being used to correct for interfractional variations in patient set-up and anatomy changes, thereby reducing clinical target volume to the planning target volume (CTV-to-PTV) margins. We explore how CT image quality affects patient repositioning and CTV-to-PTV margins in soft tissue registration-based IGRT for prostate cancer patients. Methods and Materials: Four CT-based IGRT modalities used for prostate RT were considered in this study: MV fan beam CT (MVFBCT) (Tomotherapy), MV cone beam CT (MVCBCT) (MVision; Siemens), kV fan beam CT (kVFBCT) (CTVision, Siemens), and kV cone beam CT (kVCBCT) (Synergy; Elekta). Daily shifts were determined by manual registration to achieve the best soft tissue agreement. Effect of image quality on patient repositioning was determined by statistical analysis of daily shifts for 136 patients (34 per modality). Inter- and intraobserver variability of soft tissue registration was evaluated based on the registration of a representative scan for each CT modality with its corresponding planning scan. Results: Superior image quality with the kVFBCT resulted in reduced uncertainty in soft tissue registration during IGRT compared with other image modalities for IGRT. The largest interobserver variations of soft tissue registration were 1.1 mm, 2.5 mm, 2.6 mm, and 3.2 mm for kVFBCT, kVCBCT, MVFBCT, and MVCBCT, respectively. Conclusions: Image quality adversely affects the reproducibility of soft tissue-based registration for IGRT and necessitates a careful consideration of residual uncertainties in determining different CTV-to-PTV margins for IGRT using different image modalities.

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

    PubMed

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

    2014-07-01

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

  3. Experimental verification of MMI by singlemode-multimode-singlemode and multimode-singlemode structures

    NASA Astrophysics Data System (ADS)

    Majumder, Saikat; Ghosh, Amarnath; Roy, Bapita; Chakraborty, Rajib

    2015-06-01

    Multimode Interference (MMI) based on self imaging phenomenon is investigated using matrix approach. Experimentally MMI is verified using singlemode-multimode-singlemode and multimodesinglemode structures of optical fiber. The results obtained are also verified by BPM technique.

  4. A Task-Based Approach to Adaptive and Multimodality Imaging: Computation techniques are proposed for figures-of-merit to establish feasibility and optimize use of multiple imaging systems for disease diagnosis and treatment-monitoring.

    PubMed

    Clarkson, Eric; Kupinski, Matthew A; Barrett, Harrison H; Furenlid, Lars

    2008-03-01

    Multimodality imaging is becoming increasingly important in medical imaging. Since the motivation for combining multiple imaging modalities is generally to improve diagnostic or prognostic accuracy, the benefits of multimodality imaging cannot be assessed through the display of example images. Instead, we must use objective, task-based measures of image quality to draw valid conclusions about system performance. In this paper, we will present a general framework for utilizing objective, task-based measures of image quality in assessing multimodality and adaptive imaging systems. We introduce a classification scheme for multimodality and adaptive imaging systems and provide a mathematical description of the imaging chain along with block diagrams to provide a visual illustration. We show that the task-based methodology developed for evaluating single-modality imaging can be applied, with minor modifications, to multimodality and adaptive imaging. We discuss strategies for practical implementing of task-based methods to assess and optimize multimodality imaging systems. PMID:19079563

  5. 2D-3D registration for prostate radiation therapy based on a statistical model of transmission images

    SciTech Connect

    Munbodh, Reshma; Tagare, Hemant D.; Chen Zhe; Jaffray, David A.; Moseley, Douglas J.; Knisely, Jonathan P. S.; Duncan, James S.

    2009-10-15

    Purpose: In external beam radiation therapy of pelvic sites, patient setup errors can be quantified by registering 2D projection radiographs acquired during treatment to a 3D planning computed tomograph (CT). We present a 2D-3D registration framework based on a statistical model of the intensity values in the two imaging modalities. Methods: The model assumes that intensity values in projection radiographs are independently but not identically distributed due to the nonstationary nature of photon counting noise. Two probability distributions are considered for the intensity values: Poisson and Gaussian. Using maximum likelihood estimation, two similarity measures, maximum likelihood with a Poisson (MLP) and maximum likelihood with Gaussian (MLG), distribution are derived. Further, we investigate the merit of the model-based registration approach for data obtained with current imaging equipment and doses by comparing the performance of the similarity measures derived to that of the Pearson correlation coefficient (ICC) on accurately collected data of an anthropomorphic phantom of the pelvis and on patient data. Results: Registration accuracy was similar for all three similarity measures and surpassed current clinical requirements of 3 mm for pelvic sites. For pose determination experiments with a kilovoltage (kV) cone-beam CT (CBCT) and kV projection radiographs of the phantom in the anterior-posterior (AP) view, registration accuracies were 0.42 mm (MLP), 0.29 mm (MLG), and 0.29 mm (ICC). For kV CBCT and megavoltage (MV) AP portal images of the same phantom, registration accuracies were 1.15 mm (MLP), 0.90 mm (MLG), and 0.69 mm (ICC). Registration of a kV CT and MV AP portal images of a patient was successful in all instances. Conclusions: The results indicate that high registration accuracy is achievable with multiple methods including methods that are based on a statistical model of a 3D CT and 2D projection images.

  6. Control over structure-specific flexibility improves anatomical accuracy for point-based deformable registration in bladder cancer radiotherapy

    SciTech Connect

    Wognum, S.; Chai, X.; Hulshof, M. C. C. M.; Bel, A.; Bondar, L.; Zolnay, A. G.; Hoogeman, M. S.

    2013-02-15

    Purpose: Future developments in image guided adaptive radiotherapy (IGART) for bladder cancer require accurate deformable image registration techniques for the precise assessment of tumor and bladder motion and deformation that occur as a result of large bladder volume changes during the course of radiotherapy treatment. The aim was to employ an extended version of a point-based deformable registration algorithm that allows control over tissue-specific flexibility in combination with the authors' unique patient dataset, in order to overcome two major challenges of bladder cancer registration, i.e., the difficulty in accounting for the difference in flexibility between the bladder wall and tumor and the lack of visible anatomical landmarks for validation. Methods: The registration algorithm used in the current study is an extension of the symmetric-thin plate splines-robust point matching (S-TPS-RPM) algorithm, a symmetric feature-based registration method. The S-TPS-RPM algorithm has been previously extended to allow control over the degree of flexibility of different structures via a weight parameter. The extended weighted S-TPS-RPM algorithm was tested and validated on CT data (planning- and four to five repeat-CTs) of five urinary bladder cancer patients who received lipiodol injections before radiotherapy. The performance of the weighted S-TPS-RPM method, applied to bladder and tumor structures simultaneously, was compared with a previous version of the S-TPS-RPM algorithm applied to bladder wall structure alone and with a simultaneous nonweighted S-TPS-RPM registration of the bladder and tumor structures. Performance was assessed in terms of anatomical and geometric accuracy. The anatomical accuracy was calculated as the residual distance error (RDE) of the lipiodol markers and the geometric accuracy was determined by the surface distance, surface coverage, and inverse consistency errors. Optimal parameter values for the flexibility and bladder weight

  7. Feature-Based Quality Evaluation of 3d Point Clouds - Study of the Performance of 3d Registration Algorithms

    NASA Astrophysics Data System (ADS)

    Ridene, T.; Goulette, F.; Chendeb, S.

    2013-08-01

    The production of realistic 3D map databases is continuously growing. We studied an approach of 3D mapping database producing based on the fusion of heterogeneous 3D data. In this term, a rigid registration process was performed. Before starting the modeling process, we need to validate the quality of the registration results, and this is one of the most difficult and open research problems. In this paper, we suggest a new method of evaluation of 3D point clouds based on feature extraction and comparison with a 2D reference model. This method is based on tow metrics: binary and fuzzy.

  8. Spectral demixing avoids registration errors and reduces noise in multicolor localization-based super-resolution microscopy

    NASA Astrophysics Data System (ADS)

    Lampe, André; Tadeus, Georgi; Schmoranzer, Jan

    2015-09-01

    Multicolor single molecule localization-based super-resolution microscopy (SMLM) approaches are challenged by channel crosstalk and errors in multi-channel registration. We recently introduced a spectral demixing-based variant of direct stochastic optical reconstruction microscopy (SD-dSTORM) to perform multicolor SMLM with minimal color crosstalk. Here, we demonstrate that the spectral demixing procedure is inherently free of errors in multicolor registration and therefore does not require multicolor channel alignment. Furthermore, spectral demixing significantly reduces single molecule noise and is applicable to astigmatism-based 3D multicolor imaging achieving 25 nm lateral and 66 nm axial resolution on cellular nanostructures.

  9. An intensity-based approach to x-ray mammography: MRI registration

    NASA Astrophysics Data System (ADS)

    Mertzanidou, Thomy; Hipwell, John H.; Tanner, Christine; Hawkes, David J.

    2010-03-01

    This paper presents a novel approach to X-ray mammography - MRI registration. The proposed method uses an intensity-based technique and an affine transformation matrix to approximate the 3D deformation of the breast resulting from the compression applied during mammogram acquisition. The registration is driven by a similarity measure that is calculated at each iteration of the algorithm between the target X-ray mammogram and a simulated X-ray image, created from the MR volume. Although the similarity measure is calculated in 2D, we compute a 3D transformation that is updated at each iteration. We have performed two types of experiments. In the first set, we used simulated X-ray target data, for which the ground truth deformation of the volume was known and thus the results could be validated. For this case, we examined the performance of 4 different similarity measures and we show that Normalized Cross Correlation and Gradient Difference perform best. The calculated mean reprojection error was for both similarity measures 4mm, for an initial misregistration of 14mm. In the second set of experiments, we present the initial results of registering real X-ray mammograms with MR volumes. The results indicate that the breast boundaries were registered well and the volume was deformed in 3D in a similar way to the deformation of the breast during X-ray mammogram acquisition. The experiments were carried out on five patients.

  10. Installed Base Registration of Decentralised Solar Panels with Applications in Crisis Management

    NASA Astrophysics Data System (ADS)

    Aarsen, R.; Janssen, M.; Ramkisoen, M.; Biljecki, F.; Quak, W.; Verbree, E.

    2015-08-01

    In case of a calamity in the Netherlands - e.g. a dike breach - parts of the nationwide electric network can fall out. In these occasions it would be useful if decentralised energy sources of the Smart Grid would contribute to balance out the fluctuations of the energy network. Decentralised energy sources include: solar energy, wind energy, combined heat and power, and biogas. In this manner, parts of the built environment - e.g. hospitals - that are in need of a continuous power flow, could be secured of this power. When a calamity happens, information about the Smart Grid is necessary to control the crisis and to ensure a shared view on the energy networks for both the crisis managers and network operators. The current situation of publishing, storing and sharing data of solar energy has been shown a lack of reliability about the current number, physical location, and capacity of installed decentralised photovoltaic (PV) panels in the Netherlands. This study focuses on decentralised solar energy in the form of electricity via PV panels in the Netherlands and addresses this challenge by proposing a new, reliable and up-to-date database. The study reveals the requirements for a registration of the installed base of PV panels in the Netherlands. This new database should serve as a replenishment for the current national voluntary registration, called Production Installation Register of Energy Data Services Netherland (EDSN-PIR), of installed decentralised PV panel installations in the Smart Grid, and provide important information in case of a calamity.

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

    PubMed Central

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

    2010-01-01

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

  12. Registration based super-resolution reconstruction for lung 4D-CT.

    PubMed

    Wu, Xiuxiu; Xiao, Shan; Zhang, Yu

    2014-01-01

    Lung 4D-CT plays an important role in lung cancer radiotherapy for tumor localization and treatment planning. In lung 4D-CT data, the resolution in the slice direction is often much lower than the in-plane resolution. For multi-plane display, isotropic resolution is necessary, but the commonly used interpolation operation will blur the images. In this paper, we present a registration based method for super resolution enhancement of the 4D-CT multi-plane images. Our working premise is that the low-resolution images of different phases at the corresponding position can be regarded as input "frames" to reconstruct high resolution images. First, we employ the Demons registration algorithm to estimate the motion field between different "frames". Then, the projections onto convex sets (POCS) approach is employed to reconstruction high-resolution lung images. We show that our method can get clearer lung images and enhance image structure, compared with the cubic spline interpolation and back projection method. PMID:25570484

  13. Inverse-consistent rigid registration of CT and MR for MR-based planning and adaptive prostate radiation therapy

    NASA Astrophysics Data System (ADS)

    Rivest-Hénault, David; Dowson, Nicholas; Greer, Peter; Dowling, Jason

    2014-03-01

    MRI-alone treatment planning and adaptive MRI-based prostate radiation therapy are two promising techniques that could significantly increase the accuracy of the curative dose delivery processes while reducing the total radiation dose. State-of-the-art methods rely on the registration of a patient MRI with a MR-CT atlas for the estimation of pseudo-CT [5]. This atlas itself is generally created by registering many CT and MRI pairs. Most registration methods are not symmetric, but the order of the images influences the result [8]. The computed transformation is therefore biased, introducing unwanted variability. This work examines how much a symmetric algorithm improves the registration. Methods: A robust symmetric registration algorithm is proposed that simultaneously optimises a half space transform and its inverse. During the registration process, the two input volumetric images are transformed to a common position in space, therefore minimising any computational bias. An asymmetrical implementation of the same algorithm was used for comparison purposes. Results: Whole pelvis MRI and CT scans from 15 prostate patients were registered, as in the creation of MR-CT atlases. In each case, two registrations were performed, with different input image orders, and the transformation error quantified. Mean residuals of 0.63±0.26 mm (translation) and (8.7±7.3) × 10--3 rad (rotation) were found for the asymmetrical implementation with corresponding values of 0.038±0.039 mm and (1.6 ± 1.3) × 10--3 rad for the proposed symmetric algorithm, a substantial improvement. Conclusions: The increased registration precision will enhance the generation of pseudo-CT from MRI for atlas based MR planning methods.

  14. Multimodal fiber source for nonlinear microscopy based on a dissipative soliton laser

    PubMed Central

    Lamb, Erin S.; Wise, Frank W.

    2015-01-01

    Recent developments in high energy femtosecond fiber lasers have enabled robust and lower-cost sources for multiphoton-fluorescence and harmonic-generation imaging. However, picosecond pulses are better suited for Raman scattering microscopy, so the ideal multimodal source for nonlinear microcopy needs to provide both durations. Here we present spectral compression of a high-power femtosecond fiber laser as a route to producing transform-limited picosecond pulses. These pulses pump a fiber optical parametric oscillator to yield a robust fiber source capable of providing the synchronized picosecond pulse trains needed for Raman scattering microscopy. Thus, this system can be used as a multimodal platform for nonlinear microscopy techniques. PMID:26417497

  15. Triple-band high-temperature superconducting microstrip filter based on multimode split ring resonator

    NASA Astrophysics Data System (ADS)

    Liu, Hai-Wen; Wang, Yan; Fan, Yi-Chao; Guan, Xue-Hui; He, Yusheng

    2013-09-01

    A compact triple-band high-temperature superconducting (HTS) YBa2Cu3Oy microstrip bandpass filter using multimode split ring resonator (SRR) is presented in this letter. Also, its properties and equivalent circuit models are investigated by even- and odd-mode analysis. Moreover, design method of the proposed triple-band HTS filter for the applications of global positioning system at 1.57 GHz, worldwide interoperability for microwave access at 3.5 GHz, and wireless local area networks at 5.8 GHz is discussed. The centre frequencies and the bandwidths of the three passbands can be allocated properly choosing the dimension parameters of the multimode SRR. In addition, four transmission zeros are produced to improve the selectivity of this filter.

  16. Multimodal fiber source for nonlinear microscopy based on a dissipative soliton laser.

    PubMed

    Lamb, Erin S; Wise, Frank W

    2015-09-01

    Recent developments in high energy femtosecond fiber lasers have enabled robust and lower-cost sources for multiphoton-fluorescence and harmonic-generation imaging. However, picosecond pulses are better suited for Raman scattering microscopy, so the ideal multimodal source for nonlinear microcopy needs to provide both durations. Here we present spectral compression of a high-power femtosecond fiber laser as a route to producing transform-limited picosecond pulses. These pulses pump a fiber optical parametric oscillator to yield a robust fiber source capable of providing the synchronized picosecond pulse trains needed for Raman scattering microscopy. Thus, this system can be used as a multimodal platform for nonlinear microscopy techniques. PMID:26417497

  17. Molecular Bases of Multimodal Regulation of a Fungal Transient Receptor Potential (TRP) Channel*

    PubMed Central

    Ihara, Makoto; Hamamoto, Shin; Miyanoiri, Yohei; Takeda, Mitsuhiro; Kainosho, Masatsune; Yabe, Isamu; Uozumi, Nobuyuki; Yamashita, Atsuko

    2013-01-01

    Multimodal activation by various stimuli is a fundamental characteristic of TRP channels. We identified a fungal TRP channel, TRPGz, exhibiting activation by hyperosmolarity, temperature increase, cytosolic Ca2+ elevation, membrane potential, and H2O2 application, and thus it is expected to represent a prototypic multimodal TRP channel. TRPGz possesses a cytosolic C-terminal domain (CTD), primarily composed of intrinsically disordered regions with some regulatory modules, a putative coiled-coil region and a basic residue cluster. The CTD oligomerization mediated by the coiled-coil region is required for the hyperosmotic and temperature increase activations but not for the tetrameric channel formation or other activation modalities. In contrast, the basic cluster is responsible for general channel inhibition, by binding to phosphatidylinositol phosphates. The crystal structure of the presumed coiled-coil region revealed a tetrameric assembly in an offset spiral rather than a canonical coiled-coil. This structure underlies the observed moderate oligomerization affinity enabling the dynamic assembly and disassembly of the CTD during channel functions, which are compatible with the multimodal regulation mediated by each functional module. PMID:23553631

  18. Multimodal Information Exploration.

    ERIC Educational Resources Information Center

    Stock, Oliviero; Zancanaro, Massimo; Strapparava, Carlo

    1997-01-01

    Discussion of information exploration and software design in computer-based educational systems focuses on the integration of hypermedia and natural language dialog. AlFRESCO is described, an interactive natural language-centered multimodal system that was developed for users interested in frescoes and paintings. (LRW)

  19. Registration of 3D spectral OCT volumes combining ICP with a graph-based approach

    NASA Astrophysics Data System (ADS)

    Niemeijer, Meindert; Lee, Kyungmoo; Garvin, Mona K.; Abràmoff, Michael D.; Sonka, Milan

    2012-02-01

    The introduction of spectral Optical Coherence Tomography (OCT) scanners has enabled acquisition of high resolution, 3D cross-sectional volumetric images of the retina. 3D-OCT is used to detect and manage eye diseases such as glaucoma and age-related macular degeneration. To follow-up patients over time, image registration is a vital tool to enable more precise, quantitative comparison of disease states. In this work we present a 3D registrationmethod based on a two-step approach. In the first step we register both scans in the XY domain using an Iterative Closest Point (ICP) based algorithm. This algorithm is applied to vessel segmentations obtained from the projection image of each scan. The distance minimized in the ICP algorithm includes measurements of the vessel orientation and vessel width to allow for a more robust match. In the second step, a graph-based method is applied to find the optimal translation along the depth axis of the individual A-scans in the volume to match both scans. The cost image used to construct the graph is based on the mean squared error (MSE) between matching A-scans in both images at different translations. We have applied this method to the registration of Optic Nerve Head (ONH) centered 3D-OCT scans of the same patient. First, 10 3D-OCT scans of 5 eyes with glaucoma imaged in vivo were registered for a qualitative evaluation of the algorithm performance. Then, 17 OCT data set pairs of 17 eyes with known deformation were used for quantitative assessment of the method's robustness.

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

    PubMed

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

    2011-06-01

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

  1. The Development of Cadastral Domain Model Oriented at Unified Real Estate Registration of China Based on Ontology

    NASA Astrophysics Data System (ADS)

    Li, M.; Zhu, X.; Shen, C.; Chen, D.; Guo, W.

    2012-07-01

    With the certain regulation of unified real estate registration taken by the Property Law and the step-by-step advance of simultaneous development in urban and rural in China, it is the premise and foundation to clearly specify property rights and their relations in promoting the integrated management of urban and rural land. This paper aims at developing a cadastral domain model oriented at unified real estate registration of China from the perspective of legal and spatial, which set up the foundation for unified real estate registration, and facilitates the effective interchange of cadastral information and the administration of land use. The legal cadastral model is provided based on the analysis of gap between current model and the demand of unified real estate registration, which implies the restrictions between different rights. Then the new cadastral domain model is constructed based on the legal cadastral domain model and CCDM (van Oosterom et al., 2006), which integrate real estate rights of urban land and rural land. Finally, the model is validated by a prototype system. The results show that the model is applicable for unified real estate registration in China.

  2. Fast voxel-based 2D/3D registration algorithm using a volume rendering method based on the shear-warp factorization

    NASA Astrophysics Data System (ADS)

    Weese, Juergen; Goecke, Roland; Penney, Graeme P.; Desmedt, Paul; Buzug, Thorsten M.; Schumann, Heidrun

    1999-05-01

    2D/3D registration makes it possible to use pre-operative CT scans for navigation purposes during X-ray fluoroscopy guided interventions. We present a fast voxel-based method for this registration task, which uses a recently introduced similarity measure (pattern intensity). This measure is especially suitable for 2D/3D registration, because it is robust with respect to structures such as a stent visible in the X-ray fluoroscopy image but not in the CT scan. The method uses only a part of the CT scan for the generation of digitally reconstructed radiographs (DRRs) to accelerate their computation. Nevertheless, computation time is crucial for intra-operative application and a further speed-up is required, because numerous DRRs must be computed. For that reason, the suitability of different volume rendering methods for 2D/3D registration has been investigated. A method based on the shear-warp factorization of the viewing transformation turned out to be especially suitable and builds the basis of the registration algorithm. The algorithm has been applied to images of a spine phantom and to clinical images. For comparison, registration results have been calculated using ray-casting. The shear-warp factorization based rendering method accelerates registration by a factor of up to seven compared to ray-casting without degrading registration accuracy. Using a vertebra as feature for registration, computation time is in the range of 3-4s (Sun UltraSparc, 300 MHz) which is acceptable for intra-operative application.

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

    PubMed

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

    2016-08-01

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

  4. Silicon band-rejection and band-pass filter based on asymmetric Bragg sidewall gratings in a multimode waveguide.

    PubMed

    Qiu, Huiye; Jiang, Jianfei; Yu, Ping; Dai, Tingge; Yang, Jianyi; Yu, Hui; Jiang, Xiaoqing

    2016-06-01

    A silicon photonic wire filter based on an asymmetric sidewall Bragg grating in a multimode silicon-on-insulator strip waveguide is demonstrated. The operating principle is based on the contra-directional coupling between the transverse electric fundamental (TE0) and first-order (TE1) modes, which is enabled by the asymmetric spatially periodic refractive-index perturbations. An asymmetric Y-junction is cascaded at the input port of the filter so as to drop the Bragg reflection. Compared with conventional Bragg grating-based filters, this device eliminates the back reflection at the input port and the 6 dB inherent insertion loss at the drop port; moreover, a narrow 3 dB bandwidth can be obtained with a large critical dimension as a result of the weak coupling strength between the TE0 and TE1 modes inside the multimode waveguide. Experimental results show that a bandwidth of ∼2.8  nm is achieved by a large corrugation width of 150 nm. The insertion loss at the drop port is -2.1  dB, and the extinction ratio is -33  dB at the through port. PMID:27244386

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

    NASA Astrophysics Data System (ADS)

    Kacenjar, Steve; Zook, Matthew; Balint, Michael

    2011-03-01

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

  6. Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments.

    PubMed

    Li, Guang; Xie, Huchen; Ning, Holly; Citrin, Deborah; Capala, Jacek; Maass-Moreno, Roberto; Guion, Peter; Arora, Barbara; Coleman, Norman; Camphausen, Kevin; Miller, Robert W

    2008-01-01

    Registration is critical for image-based treatment planning and image-guided treatment delivery. Although automatic registration is available, manual, visual-based image fusion using three orthogonal planar views (3P) is always employed clinically to verify and adjust an automatic registration result. However, the 3P fusion can be time consuming, observer dependent, as well as prone to errors, owing to the incomplete 3-dimensional (3D) volumetric image representations. It is also limited to single-pixel precision (the screen resolution). The 3D volumetric image registration (3DVIR) technique was developed to overcome these shortcomings. This technique introduces a 4th dimension in the registration criteria beyond the image volume, offering both visual and quantitative correlation of corresponding anatomic landmarks within the two registration images, facilitating a volumetric image alignment, and minimizing potential registration errors. The 3DVIR combines image classification in real-time to select and visualize a reliable anatomic landmark, rather than using all voxels for alignment. To determine the detection limit of the visual and quantitative 3DVIR criteria, slightly misaligned images were simulated and presented to eight clinical personnel for interpretation. Both of the criteria produce a detection limit of 0.1 mm and 0.1 degree. To determine the accuracy of the 3DVIR method, three imaging modalities (CT, MR and PET/CT) were used to acquire multiple phantom images with known spatial shifts. Lateral shifts were applied to these phantoms with displacement intervals of 5.0+/-0.1 mm. The accuracy of the 3DVIR technique was determined by comparing the image shifts determined through registration to the physical shifts made experimentally. The registration accuracy, together with precision, was found to be: 0.02+/-0.09 mm for CT/CT images, 0.03+/-0.07 mm for MR/MR images, and 0.03+/-0.35 mm for PET/CT images. This accuracy is consistent with the detection limit

  7. Artifact reduction in mutual-information-based CT-MR image registration

    NASA Astrophysics Data System (ADS)

    Wei, Mingxiu; Liu, Jundong; Liu, Junhong

    2004-05-01

    Abstract Mutual information (MI) is currently the most popular match metric in handling the registration problem for multi modality images. However, interpolation artifacts impose deteriorating effects to the accuracy and robustness of MI-based methods. This paper analyzes the generation mechanism of the artifacts inherent in linear partial volume interpolation (PVI) and shows that the mutual information resulted from PVI is a convex function within each voxel grid. We conclude that the generation of the artifacts is due to two facts: 1) linear interpolation causes the histogram bin values to change at a synchronized pace; 2) entropy computation function Σxlgx is convex. As a remedy we propose to use non-uniform interpolation functions as the interpolation kernels in estimating the joint histogram. Cubic B-splin and Gaussian interpolators are compared and we demonstrate the improvements via experiments on misalignments between CT/MR brain scans.

  8. Deformable Registration of Feature-Endowed Point Sets Based on Tensor Fields.

    PubMed

    Wassermann, Demian; Ross, James; Washko, George; Wells, William M; San Jose-Estepar, Raul

    2014-06-01

    The main contribution of this work is a framework to register anatomical structures characterized as a point set where each point has an associated symmetric matrix. These matrices can represent problem-dependent characteristics of the registered structure. For example, in airways, matrices can represent the orientation and thickness of the structure. Our framework relies on a dense tensor field representation which we implement sparsely as a kernel mixture of tensor fields. We equip the space of tensor fields with a norm that serves as a similarity measure. To calculate the optimal transformation between two structures we minimize this measure using an analytical gradient for the similarity measure and the deformation field, which we restrict to be a diffeomorphism. We illustrate the value of our tensor field model by comparing our results with scalar and vector field based models. Finally, we evaluate our registration algorithm on synthetic data sets and validate our approach on manually annotated airway trees. PMID:25473253

  9. Deformable Registration of Feature-Endowed Point Sets Based on Tensor Fields

    PubMed Central

    Wassermann, Demian; Ross, James; Washko, George; Wells, William M.; San Jose-Estepar, Raul

    2014-01-01

    The main contribution of this work is a framework to register anatomical structures characterized as a point set where each point has an associated symmetric matrix. These matrices can represent problem-dependent characteristics of the registered structure. For example, in airways, matrices can represent the orientation and thickness of the structure. Our framework relies on a dense tensor field representation which we implement sparsely as a kernel mixture of tensor fields. We equip the space of tensor fields with a norm that serves as a similarity measure. To calculate the optimal transformation between two structures we minimize this measure using an analytical gradient for the similarity measure and the deformation field, which we restrict to be a diffeomorphism. We illustrate the value of our tensor field model by comparing our results with scalar and vector field based models. Finally, we evaluate our registration algorithm on synthetic data sets and validate our approach on manually annotated airway trees. PMID:25473253

  10. Finding a Good Feature Detector-Descriptor Combination for the 2d Keypoint-Based Registration of Tls Point Clouds

    NASA Astrophysics Data System (ADS)

    Urban, S.; Weinmann, M.

    2015-08-01

    The automatic and accurate registration of terrestrial laser scanning (TLS) data is a topic of great interest in the domains of city modeling, construction surveying or cultural heritage. While numerous of the most recent approaches focus on keypoint-based point cloud registration relying on forward-projected 2D keypoints detected in panoramic intensity images, little attention has been paid to the selection of appropriate keypoint detector-descriptor combinations. Instead, keypoints are commonly detected and described by applying well-known methods such as the Scale Invariant Feature Transform (SIFT) or Speeded-Up Robust Features (SURF). In this paper, we present a framework for evaluating the influence of different keypoint detector-descriptor combinations on the results of point cloud registration. For this purpose, we involve five different approaches for extracting local features from the panoramic intensity images and exploit the range information of putative feature correspondences in order to define bearing vectors which, in turn, may be exploited to transfer the task of point cloud registration from the object space to the observation space. With an extensive evaluation of our framework on a standard benchmark TLS dataset, we clearly demonstrate that replacing SIFT and SURF detectors and descriptors by more recent approaches significantly alleviates point cloud registration in terms of accuracy, efficiency and robustness.

  11. Finite element model-based tumor registration of microPET and high-resolution MR images for photodynamic therapy in mice

    NASA Astrophysics Data System (ADS)

    Fei, Baowei; Wang, Hesheng; Muzic, Raymond F., Jr.; Flask, Chris A.; Feyes, Denise; Wilson, David L.; Duerk, Jeffrey L.; Oleinick, Nancy L.

    2006-03-01

    We are investigating imaging techniques to study the tumor response to photodynamic therapy (PDT). PET can provide physiological and functional information. High-resolution MRI can provide anatomical and morphological changes. Image registration can combine MRI and PET images for improved tumor monitoring. In this study, we acquired high-resolution MRI and microPET [ 18F]fluorodeoxyglucose (FDG) images from C3H mice with RIF-1 tumors that were treated with Pc 4-based PDT. For tumor registration, we developed a finite element model (FEM)-based deformable registration scheme. To assess the registration quality, we performed slice by slice review of both image volumes, computed the volume overlap ratios, and visualized both volumes in color overlay. The mean volume overlap ratios for tumors were 94.7% after registration. Registration of high-resolution MRI and microPET images combines anatomical and functional information of the tumors and provides a useful tool for evaluating photodynamic therapy.

  12. Efficient feature-based 2D/3D registration of transesophageal echocardiography to x-ray fluoroscopy for cardiac interventions

    NASA Astrophysics Data System (ADS)

    Hatt, Charles R.; Speidel, Michael A.; Raval, Amish N.

    2014-03-01

    We present a novel 2D/ 3D registration algorithm for fusion between transesophageal echocardiography (TEE) and X-ray fluoroscopy (XRF). The TEE probe is modeled as a subset of 3D gradient and intensity point features, which facilitates efficient 3D-to-2D perspective projection. A novel cost-function, based on a combination of intensity and edge features, evaluates the registration cost value without the need for time-consuming generation of digitally reconstructed radiographs (DRRs). Validation experiments were performed with simulations and phantom data. For simulations, in silica XRF images of a TEE probe were generated in a number of different pose configurations using a previously acquired CT image. Random misregistrations were applied and our method was used to recover the TEE probe pose and compare the result to the ground truth. Phantom experiments were performed by attaching fiducial markers externally to a TEE probe, imaging the probe with an interventional cardiac angiographic x-ray system, and comparing the pose estimated from the external markers to that estimated from the TEE probe using our algorithm. Simulations found a 3D target registration error of 1.08(1.92) mm for biplane (monoplane) geometries, while the phantom experiment found a 2D target registration error of 0.69mm. For phantom experiments, we demonstrated a monoplane tracking frame-rate of 1.38 fps. The proposed feature-based registration method is computationally efficient, resulting in near real-time, accurate image based registration between TEE and XRF.

  13. A multi-mode operation control strategy for flexible microgrid based on sliding-mode direct voltage and hierarchical controls.

    PubMed

    Zhang, Qinjin; Liu, Yancheng; Zhao, Youtao; Wang, Ning

    2016-03-01

    Multi-mode operation and transient stability are two problems that significantly affect flexible microgrid (MG). This paper proposes a multi-mode operation control strategy for flexible MG based on a three-layer hierarchical structure. The proposed structure is composed of autonomous, cooperative, and scheduling controllers. Autonomous controller is utilized to control the performance of the single micro-source inverter. An adaptive sliding-mode direct voltage loop and an improved droop power loop based on virtual negative impedance are presented respectively to enhance the system disturbance-rejection performance and the power sharing accuracy. Cooperative controller, which is composed of secondary voltage/frequency control and phase synchronization control, is designed to eliminate the voltage/frequency deviations produced by the autonomous controller and prepare for grid connection. Scheduling controller manages the power flow between the MG and the grid. The MG with the improved hierarchical control scheme can achieve seamless transitions from islanded to grid-connected mode and have a good transient performance. In addition the presented work can also optimize the power quality issues and improve the load power sharing accuracy between parallel VSIs. Finally, the transient performance and effectiveness of the proposed control scheme are evaluated by theoretical analysis and simulation results. PMID:26686458

  14. Ultra-compact, broadband tunable optical bandstop filters based on a multimode one-dimensional photonic crystal waveguide.

    PubMed

    Huang, Qingzhong; Jie, Kun; Liu, Qiang; Huang, Ying; Wang, Yi; Xia, Jinsong

    2016-09-01

    In this paper, ultra-compact, broadband tunable optical bandstop filters (OBSFs) based on a multimode one-dimensional photonic crystal waveguide (PhCW) are proposed and systematically investigated. For the wavelengths in the mini-stopband, the input mode is coupled to a contra-propagating higher order mode by the PhCW and then radiates in a taper, resulting in a stopband at the output with low backreflection at the input. Three-dimensional finite-difference time-domain method is employed to study the OBSFs. The influence of main structural parameters is analyzed, and the design is optimized to reduce the back-reflection and band sidelobes. Using localized heating, we can shift the stopband and tune the bandwidth continuously by cascading the proposed structures. Due to the strong grating strength, our device provides a more compact footprint (40 μm × 1 μm) and much broader stopband (bandwidth of up to 84 nm), compared to the counterparts based on microrings, long-period waveguide gratings, and multimode two-dimensional PhCWs. PMID:27607658

  15. SU-E-J-112: Intensity-Based Pulmonary Image Registration: An Evaluation Study

    SciTech Connect

    Yang, F; Meyer, J; Sandison, G

    2015-06-15

    Purpose: Accurate alignment of thoracic CT images is essential for dose tracking and to safely implement adaptive radiotherapy in lung cancers. At the same time it is challenging given the highly elastic nature of lung tissue deformations. The objective of this study was to assess the performances of three state-of-art intensity-based algorithms in terms of their ability to register thoracic CT images subject to affine, barrel, and sinusoid transformation. Methods: Intensity similarity measures of the evaluated algorithms contained sum-of-squared difference (SSD), local mutual information (LMI), and residual complexity (RC). Five thoracic CT scans obtained from the EMPIRE10 challenge database were included and served as reference images. Each CT dataset was distorted by realistic affine, barrel, and sinusoid transformations. Registration performances of the three algorithms were evaluated for each distortion type in terms of intensity root mean square error (IRMSE) between the reference and registered images in the lung regions. Results: For affine distortions, the three algorithms differed significantly in registration of thoracic images both visually and nominally in terms of IRMSE with a mean of 0.011 for SSD, 0.039 for RC, and 0.026 for LMI (p<0.01; Kruskal-Wallis test). For barrel distortion, the three algorithms showed nominally no significant difference in terms of IRMSE with a mean of 0.026 for SSD, 0.086 for RC, and 0.054 for LMI (p=0.16) . A significant difference was seen for sinusoid distorted thoracic CT data with mean lung IRMSE of 0.039 for SSD, 0.092 for RC, and 0.035 for LMI (p=0.02). Conclusion: Pulmonary deformations might vary to a large extent in nature in a daily clinical setting due to factors ranging from anatomy variations to respiratory motion to image quality. It can be appreciated from the results of the present study that the suitability of application of a particular algorithm for pulmonary image registration is deformation-dependent.

  16. Concurrent multimodality image segmentation by active contours for radiotherapy treatment planning

    SciTech Connect

    El Naqa, Issam; Yang Deshan; Apte, Aditya; Khullar, Divya; Mutic, Sasa; Zheng Jie; Bradley, Jeffrey D.; Grigsby, Perry; Deasy, Joseph O.

    2007-12-15

    Multimodality imaging information is regularly used now in radiotherapy treatment planning for cancer patients. The authors are investigating methods to take advantage of all the imaging information available for joint target registration and segmentation, including multimodality images or multiple image sets from the same modality. In particular, the authors have developed variational methods based on multivalued level set deformable models for simultaneous 2D or 3D segmentation of multimodality images consisting of combinations of coregistered PET, CT, or MR data sets. The combined information is integrated to define the overall biophysical structure volume. The authors demonstrate the methods on three patient data sets, including a nonsmall cell lung cancer case with PET/CT, a cervix cancer case with PET/CT, and a prostate patient case with CT and MRI. CT, PET, and MR phantom data were also used for quantitative validation of the proposed multimodality segmentation approach. The corresponding Dice similarity coefficient (DSC) was 0.90{+-}0.02 (p<0.0001) with an estimated target volume error of 1.28{+-}1.23% volume. Preliminary results indicate that concurrent multimodality segmentation methods can provide a feasible and accurate framework for combining imaging data from different modalities and are potentially useful tools for the delineation of biophysical structure volumes in radiotherapy treatment planning.

  17. Multimodal MRI-Based Classification of Trauma Survivors with and without Post-Traumatic Stress Disorder

    PubMed Central

    Zhang, Qiongmin; Wu, Qizhu; Zhu, Hongru; He, Ling; Huang, Hua; Zhang, Junran; Zhang, Wei

    2016-01-01

    Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder. It can be difficult to discern the symptoms of PTSD and obtain an accurate diagnosis. Different magnetic resonance imaging (MRI) modalities focus on different aspects, which may provide complementary information for PTSD discrimination. However, none of the published studies assessed the diagnostic potential of multimodal MRI in identifying individuals with and without PTSD. In the current study, we investigated whether the complementary information conveyed by multimodal MRI scans could be combined to improve PTSD classification performance. Structural and resting-state functional MRI (rs-fMRI) scans were conducted on 17 PTSD patients, 20 trauma-exposed controls without PTSD (TEC) and 20 non-traumatized healthy controls (HC). Gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and regional homogeneity were extracted as classification features, and in order to integrate the information of structural and functional MRI data, the extracted features were combined by a multi-kernel combination strategy. Then a support vector machine (SVM) classifier was trained to distinguish the subjects at individual level. The performance of the classifier was evaluated using the leave-one-out cross-validation (LOOCV) method. In the pairwise comparison of PTSD, TEC, and HC groups, classification accuracies obtained by the proposed approach were 2.70, 2.50, and 2.71% higher than the best single feature way, with the accuracies of 89.19, 90.00, and 67.57% for PTSD vs. HC, TEC vs. HC, and PTSD vs. TEC respectively. The proposed approach could improve PTSD identification at individual level. Additionally, it provides preliminary support to develop the multimodal MRI method as a clinical diagnostic aid. PMID:27445664

  18. Multimodal MRI-Based Classification of Trauma Survivors with and without Post-Traumatic Stress Disorder.

    PubMed

    Zhang, Qiongmin; Wu, Qizhu; Zhu, Hongru; He, Ling; Huang, Hua; Zhang, Junran; Zhang, Wei

    2016-01-01

    Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder. It can be difficult to discern the symptoms of PTSD and obtain an accurate diagnosis. Different magnetic resonance imaging (MRI) modalities focus on different aspects, which may provide complementary information for PTSD discrimination. However, none of the published studies assessed the diagnostic potential of multimodal MRI in identifying individuals with and without PTSD. In the current study, we investigated whether the complementary information conveyed by multimodal MRI scans could be combined to improve PTSD classification performance. Structural and resting-state functional MRI (rs-fMRI) scans were conducted on 17 PTSD patients, 20 trauma-exposed controls without PTSD (TEC) and 20 non-traumatized healthy controls (HC). Gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and regional homogeneity were extracted as classification features, and in order to integrate the information of structural and functional MRI data, the extracted features were combined by a multi-kernel combination strategy. Then a support vector machine (SVM) classifier was trained to distinguish the subjects at individual level. The performance of the classifier was evaluated using the leave-one-out cross-validation (LOOCV) method. In the pairwise comparison of PTSD, TEC, and HC groups, classification accuracies obtained by the proposed approach were 2.70, 2.50, and 2.71% higher than the best single feature way, with the accuracies of 89.19, 90.00, and 67.57% for PTSD vs. HC, TEC vs. HC, and PTSD vs. TEC respectively. The proposed approach could improve PTSD identification at individual level. Additionally, it provides preliminary support to develop the multimodal MRI method as a clinical diagnostic aid. PMID:27445664

  19. Compact Si photonic multimode interference-based optical circuit for mode division multiplexing applications

    NASA Astrophysics Data System (ADS)

    El-Sabban, Salwa; Khalil, Diaa

    2016-07-01

    A design for a compact Si photonic two mode demultiplexer for mode division multiplexing (MDM) applications is presented. The design uses the self-imaging in multimode interference structures to achieve MDM with an insertion loss less than 0.5 dB and a cross talk better than 20 dB over the C band. The imaging is achieved within a length that is half the length reported in the literature, and its overall dimensions are 42 μm×3 μm. The minimum cross talk is affected by the structure geometry. The tolerance of the design to variations in the dimensions is also studied.

  20. Recent advances in magnetic nanoparticle-based multi-modal imaging.

    PubMed

    Shin, Tae-Hyun; Choi, Youngseon; Kim, Soojin; Cheon, Jinwoo

    2015-07-21

    Magnetic nanoparticles have been extensively explored as a versatile platform for magnetic resonance imaging (MRI) contrast agents due to their strong contrast enhancement effects together with the platform capability for multiple imaging modalities. In this tutorial review, we focus on recent progress in the use of magnetic nanoparticles for MRI contrast agents and multi-mode imaging agents such as T1-T2 MRI, MRI-optical, and MRI-radioisotopes. This review also highlights emerging magnetic imaging techniques such as magnetic particle imaging (MPI), magneto-motive ultrasound imaging (MMUS), and magneto-photoacoustic imaging (MPA). PMID:25652670

  1. Towards multimodal detection of melanoma thickness based on optical coherence tomography and optoacoustics

    NASA Astrophysics Data System (ADS)

    Rahlves, M.; Varkentin, A.; Stritzel, J.; Blumenröther, E.; Mazurenka, M.; Wollweber, M.; Roth, B.

    2016-03-01

    Melanoma skin cancer has one of the highest mortality rates of all types of cancer if not detected at an early stage. The survival rate is highly dependent on its penetration depth, which is commonly determined by histopathology. In this work, we aim at combining optical coherence tomography and optoacoustic as a non-invasive all-optical method to measure the penetration depth of melanoma. We present our recent achievements to setup a handheld multimodal device and also results from first in vivo measurements on healthy and cancerous skin tissue, which are compared to measurements obtained by ultrasound and histopathology.

  2. 3D TEE registration with MR for cardiac interventional applications

    NASA Astrophysics Data System (ADS)

    Woo, Jonghye; Parthasarathy, Vijay; Sandeep, Dalal; Jain, Ameet

    2010-02-01

    Live three dimensional (3D) transesophageal echocardiography (TEE) provides real-time imaging of cardiac structure and function, and has been shown to be useful in interventional cardiac procedures. Its application in catheter based cardiac procedures is, however, limited by its limited field of view (FOV). In order to mitigate this limitation, we register pre-operative magnetic resonance (MR) images to live 3D TEE images. Conventional multimodal image registration techniques that use mutual information (MI) as the similarity measure use statistics from the entire image. In these cases, correct registration, however, may not coincide with the global maximum of MI metric. In order to address this problem, we present an automated registration algorithm that balances a combination global and local edge-based statistics. The weighted sum of global and local statistics is computed as the similarity measure, where the weights are decided based on the strength of the local statistics. Phantom validation experiments shows improved capture ranges when compared with conventional MI based methods. The proposed method provided robust results with accuracy better than 3 mm (5°) in the range of -10 to 12 mm (-6 to 3°), -14 to 12 mm (-6 to 6°) and -16 to 6 mm (-6 to 3°) in x-, y-, and z- axes respectively. We believe that the proposed registration method has the potential for real time intra-operative image fusion during percutaneous cardiac interventions.

  3. Multimodal imaging of ischemic wounds

    NASA Astrophysics Data System (ADS)

    Zhang, Shiwu; Gnyawali, Surya; Huang, Jiwei; Liu, Peng; Gordillo, Gayle; Sen, Chandan K.; Xu, Ronald

    2012-12-01

    The wound healing process involves the reparative phases of inflammation, proliferation, and remodeling. Interrupting any of these phases may result in chronically unhealed wounds, amputation, or even patient death. Quantitative assessment of wound tissue ischemia, perfusion, and inflammation provides critical information for appropriate detection, staging, and treatment of chronic wounds. However, no method is available for noninvasive, simultaneous, and quantitative imaging of these tissue parameters. We integrated hyperspectral, laser speckle, and thermographic imaging modalities into a single setup for multimodal assessment of tissue oxygenation, perfusion, and inflammation characteristics. Advanced algorithms were developed for accurate reconstruction of wound oxygenation and appropriate co-registration between different imaging modalities. The multimodal wound imaging system was validated by an ongoing clinical trials approved by OSU IRB. In the clinical trial, a wound of 3mm in diameter was introduced on a healthy subject's lower extremity and the healing process was serially monitored by the multimodal imaging setup. Our experiments demonstrated the clinical usability of multimodal wound imaging.

  4. Multi-Modality Phantom Development

    SciTech Connect

    Huber, Jennifer S.; Peng, Qiyu; Moses, William W.

    2009-03-20

    Multi-modality imaging has an increasing role in the diagnosis and treatment of a large number of diseases, particularly if both functional and anatomical information are acquired and accurately co-registered. Hence, there is a resulting need for multi modality phantoms in order to validate image co-registration and calibrate the imaging systems. We present our PET-ultrasound phantom development, including PET and ultrasound images of a simple prostate phantom. We use agar and gelatin mixed with a radioactive solution. We also present our development of custom multi-modality phantoms that are compatible with PET, transrectal ultrasound (TRUS), MRI and CT imaging. We describe both our selection of tissue mimicking materials and phantom construction procedures. These custom PET-TRUS-CT-MRI prostate phantoms use agargelatin radioactive mixtures with additional contrast agents and preservatives. We show multi-modality images of these custom prostate phantoms, as well as discuss phantom construction alternatives. Although we are currently focused on prostate imaging, this phantom development is applicable to many multi-modality imaging applications.

  5. Registration-based segmentation of murine 4D cardiac micro-CT data using symmetric normalization

    NASA Astrophysics Data System (ADS)

    Clark, Darin; Badea, Alexandra; Liu, Yilin; Johnson, G. Allan; Badea, Cristian T.

    2012-10-01

    Micro-CT can play an important role in preclinical studies of cardiovascular disease because of its high spatial and temporal resolution. Quantitative analysis of 4D cardiac images requires segmentation of the cardiac chambers at each time point, an extremely time consuming process if done manually. To improve throughput this study proposes a pipeline for registration-based segmentation and functional analysis of 4D cardiac micro-CT data in the mouse. Following optimization and validation using simulations, the pipeline was applied to in vivo cardiac micro-CT data corresponding to ten cardiac phases acquired in C57BL/6 mice (n = 5). After edge-preserving smoothing with a novel adaptation of 4D bilateral filtration, one phase within each cardiac sequence was manually segmented. Deformable registration was used to propagate these labels to all other cardiac phases for segmentation. The volumes of each cardiac chamber were calculated and used to derive stroke volume, ejection fraction, cardiac output, and cardiac index. Dice coefficients and volume accuracies were used to compare manual segmentations of two additional phases with their corresponding propagated labels. Both measures were, on average, >0.90 for the left ventricle and >0.80 for the myocardium, the right ventricle, and the right atrium, consistent with trends in inter- and intra-segmenter variability. Segmentation of the left atrium was less reliable. On average, the functional metrics of interest were underestimated by 6.76% or more due to systematic label propagation errors around atrioventricular valves; however, execution of the pipeline was 80% faster than performing analogous manual segmentation of each phase.

  6. Registration of partially overlapping surfaces for range image based augmented reality on mobile devices

    NASA Astrophysics Data System (ADS)

    Kilgus, T.; Franz, A. M.; Seitel, A.; Marz, K.; Bartha, L.; Fangerau, M.; Mersmann, S.; Groch, A.; Meinzer, H.-P.; Maier-Hein, L.

    2012-02-01

    Visualization of anatomical data for disease diagnosis, surgical planning, or orientation during interventional therapy is an integral part of modern health care. However, as anatomical information is typically shown on monitors provided by a radiological work station, the physician has to mentally transfer internal structures shown on the screen to the patient. To address this issue, we recently presented a new approach to on-patient visualization of 3D medical images, which combines the concept of augmented reality (AR) with an intuitive interaction scheme. Our method requires mounting a range imaging device, such as a Time-of-Flight (ToF) camera, to a portable display (e.g. a tablet PC). During the visualization process, the pose of the camera and thus the viewing direction of the user is continuously determined with a surface matching algorithm. By moving the device along the body of the patient, the physician is given the impression of looking directly into the human body. In this paper, we present and evaluate a new method for camera pose estimation based on an anisotropic trimmed variant of the well-known iterative closest point (ICP) algorithm. According to in-silico and in-vivo experiments performed with computed tomography (CT) and ToF data of human faces, knees and abdomens, our new method is better suited for surface registration with ToF data than the established trimmed variant of the ICP, reducing the target registration error (TRE) by more than 60%. The TRE obtained (approx. 4-5 mm) is promising for AR visualization, but clinical applications require maximization of robustness and run-time.

  7. Template-based CTA X-ray angio rigid registration of coronary arteries in frequency domain

    NASA Astrophysics Data System (ADS)

    Aksoy, Timur; Demirci, Stefanie; Degertekin, Muzaffer; Navab, Nassir; Unal, Gozde

    2013-03-01

    This study performs 3D to 2D rigid registration of segmented pre-operative CTA coronary arteries with a single segmented intra-operative X-ray Angio frame in both frequency and spatial domains for real-time Angiography interventions by C-arm fluoroscopy. Most of the work on rigid registration in literature required a close initial- ization of poses and/or positions because of the abundance of local minima and high complexity that searching algorithms face. This study avoids such setbacks by transforming the projections into translation-invariant Fourier domain for estimating the 3D pose. First, template DRRs as candidate poses of 3D vessels of segmented CTA are produced by rotating the camera (image intensifier) around the DICOM angle values with a wide range as in C-arm setup. We have compared the 3D poses of template DRRs with the real X-ray after equalizing the scales (due to disparities in focal length distances) in 3 domains, namely Fourier magnitude, Fourier phase and Fourier polar. The best pose candidate was chosen by one of the highest similarity measures returned by the methods in these domains. It has been noted in literature that these methods are robust against noise and occlusion which was also validated by our results. Translation of the volume was then recovered by distance-map based BFGS optimization well suited to convex structure of our objective function without local minima due to distance maps. Final results were evaluated in 2D projection space rather than with actual values in 3D due to lack of ground truth, ill-posedness of the problem which we intend to address in future.

  8. E-Advisory Based Analysis of Student Expressions throughout the University Courses' Registration Period on Digital Media

    ERIC Educational Resources Information Center

    Kaysi, Feyzi; Gurol, Aysun

    2016-01-01

    One other factor that determines university characteristics is the present students receiving education. Especially the feeling of content or the difficulty that students encounter during the registration period at the beginning of the term is strictly crucial for them. Internet based solutions have been offered rather than the other methods that…

  9. Effect of Non-rigid Registration Algorithms on Deformation Based Morphometry: A Comparative Study with Control and Williams Syndrome Subjects

    PubMed Central

    Han, Zhaoying; Thornton-Wells, Tricia A.; Dykens, Elisabeth M.; Gore, John C.; Dawant, Benoit M.

    2014-01-01

    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 non-rigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared non-rigid 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 non-rigid registration algorithms using thirteen subjects with Williams Syndrome (WS) and thirteen Normal Control (NC) subjects. The five non-rigid registration algorithms include: (1) The Adaptive Bases Algorithm (ABA); (2) The Image Registration Toolkit (IRTK); (3) The FSL Nonlinear Image Registration Tool (FSL); (4) The Automatic Registration Tool (ART); and (5) the normalization algorithm available in 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. The unique nature of the data set used in this study also permits comparison of visible anatomical differences between the groups and regions of difference detected by each algorithm. Results show that the interpretation of DBM results is difficult. Four out of the five algorithms we have evaluated detect bilateral differences between the two groups in the insular cortex, the basal ganglia, orbitofrontal cortex, as well as in the cerebellum. These correspond to differences that have been reported in the literature and that are visible in our samples. But our results also show that some algorithms detect regions that are not detected by the others and that the extent of the detected regions varies from algorithm to algorithm. These results suggest

  10. Medical case-based retrieval: integrating query MeSH terms for query-adaptive multi-modal fusion

    NASA Astrophysics Data System (ADS)

    Seco de Herrera, Alba G.; Foncubierta-Rodríguez, Antonio; Müller, Henning

    2015-03-01

    Advances in medical knowledge give clinicians more objective information for a diagnosis. Therefore, there is an increasing need for bibliographic search engines that can provide services helping to facilitate faster information search. The ImageCLEFmed benchmark proposes a medical case-based retrieval task. This task aims at retrieving articles from the biomedical literature that are relevant for differential diagnosis of query cases including a textual description and several images. In the context of this campaign many approaches have been investigated showing that the fusion of visual and text information can improve the precision of the retrieval. However, fusion does not always lead to better results. In this paper, a new query-adaptive fusion criterion to decide when to use multi-modal (text and visual) or only text approaches is presented. The proposed method integrates text information contained in MeSH (Medical Subject Headings) terms extracted and visual features of the images to find synonym relations between them. Given a text query, the query-adaptive fusion criterion decides when it is suitable to also use visual information for the retrieval. Results show that this approach can decide if a text or multi{modal approach should be used with 77.15% of accuracy.

  11. Design of a 1 × 4 silicon-alumina wavelength demultiplexer based on multimode interference in slot waveguide structures

    NASA Astrophysics Data System (ADS)

    Malka, Dror; Sintov, Yoav; Zalevsky, Zeev

    2015-12-01

    In this paper we present 1 × 4 wavelength demultiplexer operating at 1.4 μm, 1.45 μm, 1.5 μm and 1.55 μm wavelengths, based on multimode interference (MMI) coupler in slot waveguide structure. Alumina was used as the slot material. The design is based on three cascaded 1 × 2 MMI demultiplexers. Tapered waveguide structures are being in the input/output of the MMI section, for reducing the excess loss. Since the slot waveguide encompasses true guided modes, confined by total internal reflections, there are no noticeable confinement losses. Full vectorial-beam propagation method (FV-BPM) and BPM simulations were used for optimizing the device parameters and assessing its performance. To the best of our knowledge it is the first time that a 1 × 4 demultiplexer is being implemented by a slot waveguide based MMI.

  12. Constructing and Using Multimodal Narratives to Research in Science Education: Contributions Based on Practical Classroom

    NASA Astrophysics Data System (ADS)

    Lopes, J. B.; Silva, A. A.; Cravino, J. P.; Santos, C. A.; Cunha, A.; Pinto, A.; Silva, A.; Viegas, C.; Saraiva, E.; Branco, M. J.

    2014-06-01

    This study deals with the problem of how to collect genuine and useful data about science classroom practices, and preserving the complex and holistic nature of teaching and learning. Additionally, we were looking for an instrument that would allow comparability and verifiability for teaching and research purposes. Given the multimodality of teaching and learning processes, we developed the multimodal narrative (MN), which describes what happens during a task and incorporates data such as examples of students' work, photos, diagrams, etc. Also, it describes teachers' intentions, preserving the nature of teaching practice in natural settings and it is verifiable and comparable. In this paper, we show how the MN was developed and present the protocol that was used for its construction. We identify the main characteristics of the MN and place it in the context of international research. We explore the potential of the MN for research purposes, illustrating its use in a research study that we carried out. We find that the MN provides a way to gather, organize and transform data, avoiding confusing and time-consuming manipulation of data, while minimizing the natural subjectivity of the narrator. The same MN can be used by the same or by different researchers for different purposes. Furthermore, the same MN can be used with different analysis techniques. It is also possible to study research practices on a large scale using MNs from different teachers and lessons. We propose that MNs can also be useful for teachers' professional development.

  13. Widely continuous-tuning single-wavelength laser based on commercial multimode VCSELs

    NASA Astrophysics Data System (ADS)

    Yen, Tsu-Chiang; Hsu, Chuan-Pi; Wu, Yu-Heng; Cheng, Da-Long; Kuo, Wang-Chuang

    2010-08-01

    The conventional vertical-cavity surface-emitting lasers (VCSELs) are designed to have a very short resonant cavity. Therefore, the longitudinal mode of the VCSELs is intrinsically single; and the VCSELs are expected to be an excellent instrument for many precision measurements that demand high-purity single-wavelength light sources. However, the laser facet of the conventional VCSELs is relatively large, around 10 μm, which admits the emission of multi-transverse modes. Accordingly, conducting a single transverse mode from VCSELs is an important research topic. In this research, the beam-profile-adapted optical feedback (BPAF) method was investigated by a single-mode fiber cavity (SMFC), in which the beam profile of the multimode-VCSEL's output was adapted to the fundamental-transverse mode of an optical fiber to feedback into the laser's cavity. The operational principle and performance of BPAF will be presented. The experimental results successfully demonstrated that BPAF can efficiently conduct multimode VCSELs to stably lase the fundamental transverse mode with a wide tuning range of about 1090 GHz, or 2.62 nm, and a spectrum purity around 20 dB. Some precision spectrum measurements will be exhibited. These results will help to extend the application of the VCSELs in many precision measurements.

  14. Model-based fusion of multi-modal volumetric images: application to transcatheter valve procedures.

    PubMed

    Grbić, Sasa; Ionasec, Razvan; Wang, Yang; Mansi, Tommaso; Georgescu, Bogdan; John, Matthias; Boese, Jan; Zheng, Yefeng; Navab, Nassir; Comaniciu, Dorin

    2011-01-01

    Minimal invasive procedures such as transcatheter valve interventions are substituting conventional surgical techniques. Thus, novel operating rooms have been designed to augment traditional surgical equipment with advanced imaging systems to guide the procedures. We propose a novel method to fuse pre-operative and intra-operative information by jointly estimating anatomical models from multiple image modalities. Thereby high-quality patient-specific models are integrated into the imaging environment of operating rooms to guide cardiac interventions. Robust and fast machine learning techniques are utilized to guide the estimation process. Our method integrates both the redundant and complementary multimodal information to achieve a comprehensive modeling and simultaneously reduce the estimation uncertainty. Experiments performed on 28 patients with pairs of multimodal volumetric data are used to demonstrate high quality intra-operative patient-specific modeling of the aortic valve with a precision of 1.09mm in TEE and 1.73mm in 3D C-arm CT. Within a processing time of 10 seconds we additionally obtain model sensitive mapping between the pre- and intraoperative images. PMID:22003620

  15. Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

    PubMed Central

    Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

    2016-01-01

    An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

  16. Robust FFT-based scale-invariant image registration with image gradients.

    PubMed

    Tzimiropoulos, Georgios; Argyriou, Vasileios; Zafeiriou, Stefanos; Stathaki, Tania

    2010-10-01

    We present a robust FFT-based approach to scale-invariant image registration. Our method relies on FFT-based correlation twice: once in the log-polar Fourier domain to estimate the scaling and rotation and once in the spatial domain to recover the residual translation. Previous methods based on the same principles are not robust. To equip our scheme with robustness and accuracy, we introduce modifications which tailor the method to the nature of images. First, we derive efficient log-polar Fourier representations by replacing image functions with complex gray-level edge maps. We show that this representation both captures the structure of salient image features and circumvents problems related to the low-pass nature of images, interpolation errors, border effects, and aliasing. Second, to recover the unknown parameters, we introduce the normalized gradient correlation. We show that, using image gradients to perform correlation, the errors induced by outliers are mapped to a uniform distribution for which our normalized gradient correlation features robust performance. Exhaustive experimentation with real images showed that, unlike any other Fourier-based correlation techniques, the proposed method was able to estimate translations, arbitrary rotations, and scale factors up to 6. PMID:20479492

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  18. COLLINARUS: collection of image-derived non-linear attributes for registration using splines

    NASA Astrophysics Data System (ADS)

    Chappelow, Jonathan; Bloch, B. Nicolas; Rofsky, Neil; Genega, Elizabeth; Lenkinski, Robert; DeWolf, William; Viswanath, Satish; Madabhushi, Anant

    2009-02-01

    We present a new method for fully automatic non-rigid registration of multimodal imagery, including structural and functional data, that utilizes multiple texutral feature images to drive an automated spline based non-linear image registration procedure. Multimodal image registration is significantly more complicated than registration of images from the same modality or protocol on account of difficulty in quantifying similarity between different structural and functional information, and also due to possible physical deformations resulting from the data acquisition process. The COFEMI technique for feature ensemble selection and combination has been previously demonstrated to improve rigid registration performance over intensity-based MI for images of dissimilar modalities with visible intensity artifacts. Hence, we present here the natural extension of feature ensembles for driving automated non-rigid image registration in our new technique termed Collection of Image-derived Non-linear Attributes for Registration Using Splines (COLLINARUS). Qualitative and quantitative evaluation of the COLLINARUS scheme is performed on several sets of real multimodal prostate images and synthetic multiprotocol brain images. Multimodal (histology and MRI) prostate image registration is performed for 6 clinical data sets comprising a total of 21 groups of in vivo structural (T2-w) MRI, functional dynamic contrast enhanced (DCE) MRI, and ex vivo WMH images with cancer present. Our method determines a non-linear transformation to align WMH with the high resolution in vivo T2-w MRI, followed by mapping of the histopathologic cancer extent onto the T2-w MRI. The cancer extent is then mapped from T2-w MRI onto DCE-MRI using the combined non-rigid and affine transformations determined by the registration. Evaluation of prostate registration is performed by comparison with the 3 time point (3TP) representation of functional DCE data, which provides an independent estimate of cancer

  19. Significant acceleration of 2D-3D registration-based fusion of ultrasound and x-ray images by mesh-based DRR rendering

    NASA Astrophysics Data System (ADS)

    Kaiser, Markus; John, Matthias; Borsdorf, Anja; Mountney, Peter; Ionasec, Razvan; Nöttling, Alois; Kiefer, Philipp; Seeburger, Jörg; Neumuth, Thomas

    2013-03-01

    For transcatheter-based minimally invasive procedures in structural heart disease ultrasound and X-ray are the two enabling imaging modalities. A live fusion of both real-time modalities can potentially improve the workflow and the catheter navigation by combining the excellent instrument imaging of X-ray with the high-quality soft tissue imaging of ultrasound. A recently published approach to fuse X-ray fluoroscopy with trans-esophageal echo (TEE) registers the ultrasound probe to X-ray images by a 2D-3D registration method which inherently provides a registration of ultrasound images to X-ray images. In this paper, we significantly accelerate the 2D-3D registration method in this context. The main novelty is to generate the projection images (DRR) of the 3D object not via volume ray-casting but instead via a fast rendering of triangular meshes. This is possible, because in the setting for TEE/X-ray fusion the 3D geometry of the ultrasound probe is known in advance and their main components can be described by triangular meshes. We show that the new approach can achieve a speedup factor up to 65 and does not affect the registration accuracy when used in conjunction with the gradient correlation similarity measure. The improvement is independent of the underlying registration optimizer. Based on the results, a TEE/X-ray fusion could be performed with a higher frame rate and a shorter time lag towards real-time registration performance. The approach could potentially accelerate other applications of 2D-3D registrations, e.g. the registration of implant models with X-ray images.

  20. High sensitivity high temperature sensor based on SMS structure with large-core all-solid bandgap fiber as the multimode section

    NASA Astrophysics Data System (ADS)

    Franco, Marcos A. R.; Cruz, Alice L. S.; Serrão, Valdir A.; Barbosa, Carmem L.

    2014-05-01

    A fiber optic interferometric device based on a singlemode-multimode-singlemode (SMS) structure is proposed as a high sensitive high temperature sensor. The multimode section (MMF) consists of a large-core all-solid photonic bandgap fiber (AS-PBF) with silica as the background material and germanium-doped silica at the high index regions. The numerical analyses were carried out by beam propagation method. The numerical results indicate a constant high temperature sensitivity of ~-35 pm/°C over a large temperature range from 20oC to 930°C.

  1. 40 CFR 155.58 - Procedures for issuing a decision on a registration review case.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... (CONTINUED) PESTICIDE PROGRAMS REGISTRATION STANDARDS AND REGISTRATION REVIEW Registration Review Procedures... pesticide's registration review docket the Agency's proposed decision and the bases for the decision. There... standard for registration and describe the basis for such proposed findings. (2) Identify proposed...

  2. Refractive index sensing characteristic of single-mode-multimode-single-mode fiber structure based on self-imaging effect

    NASA Astrophysics Data System (ADS)

    Bai, Xuekun; Wang, Haotian; Wang, Shaofei; Pu, Shengli; Zeng, Xianglong

    2015-10-01

    We research the refractive index (RI) sensing characteristic based on the bandpass spectrum caused by the self-imaging effect in the single-mode-multimode-single-mode (SMS) fiber structure theoretically and experimentally. A new selectable parameter, i.e., no-core fiber (NCF) length, is investigated for improving the sensitivity of the sensor. The results show that the sensor's sensitivity will be enhanced by shortening the NCF length when the self-imaging number remains constant. Experimentally, a maximum sensitivity of 1923 nm/RIU (RI unit) has been achieved when the RI ranges from 1.334 to 1.434. This work demonstrates a method to improve the sensitivity of SMS-fiber-structure-based RI sensors featuring a low cost, compact size, low insert loss, and high sensitivity optical fiber RI sensor.

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

    PubMed Central

    Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun

    2016-01-01

    By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes. PMID:27019849

  4. Ant colony optimization image registration algorithm based on wavelet transform and mutual information

    NASA Astrophysics Data System (ADS)

    Zhang, Hong; Sun, Yanfeng; Zhai, Bing; Wang, Yiding

    2013-07-01

    This paper studies on the image registration of the medical images. Wavelet transform is adopted to decompose the medical images because the resolution of the medical image is high and the computational amount of the registration is large. Firstly, the low frequency sub-images are matched. Then source images are matched. The image registration was fulfilled by the ant colony optimization algorithm to search the extremum of the mutual information. The experiment result demonstrates the proposed approach can not only reduce calculation amount, but also skip from the local extremum during optimization process, and search the optimization value.

  5. MRI-based treatment planning with pseudo CT generated through atlas registration

    SciTech Connect

    Uh, Jinsoo Merchant, Thomas E.; Hua, Chiaho; Li, Yimei; Li, Xingyu

    2014-05-15

    Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the

  6. Achromatic approach to phase-based multi-modal imaging with conventional X-ray sources.

    PubMed

    Endrizzi, Marco; Vittoria, Fabio A; Kallon, Gibril; Basta, Dario; Diemoz, Paul C; Vincenzi, Alessandro; Delogu, Pasquale; Bellazzini, Ronaldo; Olivo, Alessandro

    2015-06-15

    Compatibility with polychromatic radiation is an important requirement for an imaging system using conventional rotating anode X-ray sources. With a commercially available energy-resolving single-photon-counting detector we investigated how broadband radiation affects the performance of a multi-modal edge-illumination phase-contrast imaging system. The effect of X-ray energy on phase retrieval is presented, and the achromaticity of the method is experimentally demonstrated. Comparison with simulated measurements integrating over the energy spectrum shows that there is no significant loss of image quality due to the use of polychromatic radiation. This means that, to a good approximation, the imaging system exploits radiation in the same way at all energies typically used in hard-X-ray imaging. PMID:26193618

  7. An optical authentication system based on encryption technique and multimodal biometrics

    NASA Astrophysics Data System (ADS)

    Yuan, Sheng; Zhang, Tong; Zhou, Xin; Liu, Xuemei; Liu, Mingtang

    2013-12-01

    A major concern nowadays for a biometric credential management system is its potential vulnerability to protect its information sources. To prevent a genuine user's templates from both internal and external threats, a novel and simple method combined optical encryption with multimodal biometric authentication technique is proposed. In this method, the standard biometric templates are generated real-timely by the verification keys owned by legal user so that they are unnecessary to be stored in a database. Compared with the traditional recognition algorithms, storage space and matching time are greatly saved. In addition, the verification keys are difficult to be forged due to the utilization of optical encryption technique. Although the verification keys are lost or stolen, they are useless for others in absence of the legal owner's biometric. A series of numerical simulations are performed to demonstrate the feasibility and performance of this method.

  8. Patient-specific port placement for laparoscopic surgery using atlas-based registration

    NASA Astrophysics Data System (ADS)

    Enquobahrie, Andinet; Shivaprabhu, Vikas; Aylward, Stephen; Finet, Julien; Cleary, Kevin; Alterovitz, Ron

    2013-03-01

    Laparoscopic surgery is a minimally invasive surgical approach, in which abdominal surgical procedures are performed through trocars via small incisions. Patients benefit by reduced postoperative pain, shortened hospital stays, improved cosmetic results, and faster recovery times. Optimal port placement can improve surgeon dexterity and avoid the need to move the trocars, which would cause unnecessary trauma to the patient. We are building an intuitive open source visualization system to help surgeons identify ports. Our methodology is based on an intuitive port placement visualization module and atlas-based registration algorithm to transfer port locations to individual patients. The methodology follows three steps:1) Use a port placement visualization module to manually place ports in an abdominal organ atlas. This step generates port-augmented abdominal atlas. This is done only once for a given patient population. 2) Register the atlas data with the patient CT data, to transfer the prescribed ports to the individual patient 3) Review and adjust the transferred port locations using the port placement visualization module. Tool maneuverability and target reachability can be tested using the visualization system. Our methodology would decrease the amount of physician input necessary to optimize port placement for each patient case. In a follow up work, we plan to use the transferred ports as starting point for further optimization of the port locations by formulating a cost function that will take into account factors such as tool dexterity and likelihood of collision between instruments.

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

    SciTech Connect

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

    2014-06-15

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

  10. Neurofunctional maps of the 'maternal brain' and the effects of oxytocin: a multimodal voxel-based meta-analysis.

    PubMed

    Rocchetti, Matteo; Radua, Joaquim; Paloyelis, Yannis; Xenaki, Lida-Alkisti; Frascarelli, Marianna; Caverzasi, Edgardo; Politi, Pierluigi; Fusar-Poli, Paolo

    2014-10-01

    Several studies have tried to understand the possible neurobiological basis of mothering. The putative involvement of oxytocin, in this regard, has been deeply investigated. Performing a voxel-based meta-analysis, we aimed at testing the hypothesis of overlapping brain activation in functional magnetic resonance imaging (fMRI) studies investigating the mother-infant interaction and the oxytocin modulation of emotional stimuli in humans. We performed two systematic literature searches: fMRI studies investigating the neurofunctional correlates of the 'maternal brain' by employing mother-infant paradigms; and fMRI studies employing oxytocin during emotional tasks. A unimodal voxel-based meta-analysis was performed on each database, whereas a multimodal voxel-based meta-analytical tool was adopted to assess the hypothesis that the neurofunctional effects of oxytocin are detected in brain areas implicated in the 'maternal brain.' We found greater activation in the bilateral insula extending to the inferior frontal gyrus, basal ganglia and thalamus during mother-infant interaction and greater left insular activation associated with oxytocin administration versus placebo. Left insula extending to basal ganglia and frontotemporal gyri as well as bilateral thalamus and amygdala showed consistent activation across the two paradigms. Right insula also showed activation across the two paradigms, and dorsomedial frontal cortex activation in mothers but deactivation with oxytocin. Significant activation in areas involved in empathy, emotion regulation, motivation, social cognition and theory of mind emerged from our multimodal meta-analysis, supporting the need for further studies directly investigating the neurobiology of oxytocin in the mother-infant relationship. PMID:24734987

  11. Multimodal Voxel-Based Meta-Analysis of White Matter Abnormalities in Obsessive–Compulsive Disorder

    PubMed Central

    Radua, Joaquim; Grau, Mar; van den Heuvel, Odile A; Thiebaut de Schotten, Michel; Stein, Dan J; Canales-Rodríguez, Erick J; Catani, Marco; Mataix-Cols, David

    2014-01-01

    White matter (WM) abnormalities have long been suspected in obsessive–compulsive disorder (OCD) but the available evidence has been inconsistent. We conducted the first multimodal meta-analysis of WM volume (WMV) and fractional anisotropy (FA) studies in OCD. All voxel-wise studies comparing WMV or FA between patients with OCD and healthy controls in the PubMed, ScienceDirect, Google Scholar, Web of Knowledge and Scopus databases were retrieved. Manual searches were also conducted and authors were contacted soliciting additional data. Thirty-four data sets were identified, of which 22 met inclusion criteria (five of them unpublished; comprising 537 adult and pediatric patients with OCD and 575 matched healthy controls). Whenever possible, raw statistical parametric maps were also obtained from the authors. Peak and raw WMV and FA data were combined using novel multimodal meta-analytic methods implemented in effect-size signed differential mapping. Patients with OCD showed widespread WM abnormalities, but findings were particularly robust in the anterior midline tracts (crossing between anterior parts of cingulum bundle and body of corpus callosum), which showed both increased WMV and decreased FA, possibly suggesting an increase of fiber crossing in these regions. This finding was also observed when the analysis was limited to adult participants, and especially pronounced in samples with a higher proportion of medicated patients. Therefore, patients with OCD may have widespread WM abnormalities, particularly evident in anterior midline tracts, although these changes might be, at least in part, attributable to the effects of therapeutic drugs. PMID:24407265

  12. Mutual information image registration based on improved bee evolutionary genetic algorithm

    NASA Astrophysics Data System (ADS)

    Xu, Gang; Tu, Jingzhi

    2009-07-01

    In recent years, the mutual information is regarded as a more efficient similarity metrics in the image registration. According to the features of mutual information image registration, the Bee Evolution Genetic Algorithm (BEGA) is chosen for optimizing parameters, which imitates swarm mating. Besides, we try our best adaptively set the initial parameters to improve the BEGA. The programming result shows the wonderful precision of the algorithm.

  13. Radiation dose response simulation for biomechanical-based deformable image registration of head and neck cancer treatment

    NASA Astrophysics Data System (ADS)

    Al-Mayah, Adil; Moseley, Joanne; Hunter, Shannon; Brock, Kristy

    2015-11-01

    Biomechanical-based deformable image registration is conducted on the head and neck region. Patient specific 3D finite element models consisting of parotid glands (PG), submandibular glands (SG), tumor, vertebrae (VB), mandible, and external body are used to register pre-treatment MRI to post-treatment MR images to model the dose response using image data of five patients. The images are registered using combinations of vertebrae and mandible alignments, and surface projection of the external body as boundary conditions. In addition, the dose response is simulated by applying a new loading technique in the form of a dose-induced shrinkage using the dose-volume relationship. The dose-induced load is applied as dose-induced shrinkage of the tumor and four salivary glands. The Dice Similarity Coefficient (DSC) is calculated for the four salivary glands, and tumor to calculate the volume overlap of the structures after deformable registration. A substantial improvement in the registration is found by including the dose-induced shrinkage. The greatest registration improvement is found in the four glands where the average DSC increases from 0.53, 0.55, 0.32, and 0.37 to 0.68, 0.68, 0.51, and 0.49 in the left PG, right PG, left SG, and right SG, respectively by using bony alignment of vertebrae and mandible (M), body (B) surface projection and dose (D) (VB+M+B+D).

  14. Radiation dose response simulation for biomechanical-based deformable image registration of head and neck cancer treatment.

    PubMed

    Al-Mayah, Adil; Moseley, Joanne; Hunter, Shannon; Brock, Kristy

    2015-11-01

    Biomechanical-based deformable image registration is conducted on the head and neck region. Patient specific 3D finite element models consisting of parotid glands (PG), submandibular glands (SG), tumor, vertebrae (VB), mandible, and external body are used to register pre-treatment MRI to post-treatment MR images to model the dose response using image data of five patients. The images are registered using combinations of vertebrae and mandible alignments, and surface projection of the external body as boundary conditions. In addition, the dose response is simulated by applying a new loading technique in the form of a dose-induced shrinkage using the dose-volume relationship. The dose-induced load is applied as dose-induced shrinkage of the tumor and four salivary glands. The Dice Similarity Coefficient (DSC) is calculated for the four salivary glands, and tumor to calculate the volume overlap of the structures after deformable registration. A substantial improvement in the registration is found by including the dose-induced shrinkage. The greatest registration improvement is found in the four glands where the average DSC increases from 0.53, 0.55, 0.32, and 0.37 to 0.68, 0.68, 0.51, and 0.49 in the left PG, right PG, left SG, and right SG, respectively by using bony alignment of vertebrae and mandible (M), body (B) surface projection and dose (D) (VB+M+B+D). PMID:26485227

  15. Mapping of the prostate in endorectal coil-based MRI/MRSI and CT: A deformable registration and validation study

    SciTech Connect

    Lian, J.; Xing, L.; Hunjan, S.; Dumoulin, C.; Levin, J.; Lo, A.; Watkins, R.; Rohling, K.; Giaquinto, R.; Kim, D.; Spielman, D.; Daniel, B.

    2004-11-01

    The endorectal coil is being increasingly used in magnetic resonance imaging (MRI) and MR spectroscopic imaging (MRSI) to obtain anatomic and metabolic images of the prostate with high signal-to-noise ratio (SNR). In practice, however, the use of endorectal probe inevitably distorts the prostate and other soft tissue organs, making the analysis and the use of the acquired image data in treatment planning difficult. The purpose of this work is to develop a deformable image registration algorithm to map the MRI/MRSI information obtained using an endorectal probe onto CT images and to verify the accuracy of the registration by phantom and patient studies. A mapping procedure involved using a thin plate spline (TPS) transformation was implemented to establish voxel-to-voxel correspondence between a reference image and a floating image with deformation. An elastic phantom with a number of implanted fiducial markers was designed for the validation of the quality of the registration. Radiographic images of the phantom were obtained before and after a series of intentionally introduced distortions. After mapping the distorted phantom to the original one, the displacements of the implanted markers were measured with respect to their ideal positions and the mean error was calculated. In patient studies, CT images of three prostate patients were acquired, followed by 3 Tesla (3 T) MR images with a rigid endorectal coil. Registration quality was estimated by the centroid position displacement and image coincidence index (CI). Phantom and patient studies show that TPS-based registration has achieved significantly higher accuracy than the previously reported method based on a rigid-body transformation and scaling. The technique should be useful to map the MR spectroscopic dataset acquired with ER probe onto the treatment planning CT dataset to guide radiotherapy planning.

  16. Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction.

    PubMed

    Yip, Stephen S F; Coroller, Thibaud P; Sanford, Nina N; Huynh, Elizabeth; Mamon, Harvey; Aerts, Hugo J W L; Berbeco, Ross I

    2016-01-21

    Change in PET-based textural features has shown promise in predicting cancer response to treatment. However, contouring tumour volumes on longitudinal scans is time-consuming. This study investigated the usefulness of contour propagation in texture analysis for the purpose of pathologic response prediction in esophageal cancer. Forty-five esophageal cancer patients underwent PET/CT scans before and after chemo-radiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumour ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. PET images were converted into 256 discrete values. Co-occurrence, run-length, and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs from different algorithms were compared using Dice similarity index (DSI). Contours propagated by the fast-demons, fast-free-form and rigid algorithms did not fully capture the high FDG uptake regions of tumours. Fast-demons propagated ROIs had the least agreement with other contours (DSI = 58%). Moderate to substantial overlap were found in the ROIs propagated by all other algorithms (DSI = 69%-79%). Rigidly propagated ROIs with co-occurrence texture failed to significantly differentiate between responders and non-responders (AUC = 0.58, q-value = 0.33), while the differentiation was significant with other textures (AUC = 0.71-0.73, p < 0.009). Among the deformable algorithms, fast-demons (AUC = 0.68-0.70, q-value < 0.03) and fast-free-form (AUC = 0.69-0.74, q-value < 0.04) were the least predictive. ROIs propagated by all other deformable algorithms with any texture significantly predicted pathologic responders (AUC = 0.72-0.78, q

  17. Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction

    NASA Astrophysics Data System (ADS)

    Yip, Stephen S. F.; Coroller, Thibaud P.; Sanford, Nina N.; Huynh, Elizabeth; Mamon, Harvey; Aerts, Hugo J. W. L.; Berbeco, Ross I.

    2016-01-01

    Change in PET-based textural features has shown promise in predicting cancer response to treatment. However, contouring tumour volumes on longitudinal scans is time-consuming. This study investigated the usefulness of contour propagation in texture analysis for the purpose of pathologic response prediction in esophageal cancer. Forty-five esophageal cancer patients underwent PET/CT scans before and after chemo-radiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumour ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. PET images were converted into 256 discrete values. Co-occurrence, run-length, and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs from different algorithms were compared using Dice similarity index (DSI). Contours propagated by the fast-demons, fast-free-form and rigid algorithms did not fully capture the high FDG uptake regions of tumours. Fast-demons propagated ROIs had the least agreement with other contours (DSI  =  58%). Moderate to substantial overlap were found in the ROIs propagated by all other algorithms (DSI  =  69%-79%). Rigidly propagated ROIs with co-occurrence texture failed to significantly differentiate between responders and non-responders (AUC  =  0.58, q-value  =  0.33), while the differentiation was significant with other textures (AUC  =  0.71‒0.73, p  <  0.009). Among the deformable algorithms, fast-demons (AUC  =  0.68‒0.70, q-value  <  0.03) and fast-free-form (AUC  =  0.69‒0.74, q-value  <  0.04) were the least predictive. ROIs propagated by all other

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

    PubMed Central

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

    2015-01-01

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

  19. Novel registration-based image enhancement for x-ray fluoroscopy

    NASA Astrophysics Data System (ADS)

    Dixon, Adam; Areste, Romain; Jabri, Kadri N.; Walimbe, Vivek

    2010-03-01

    High image noise in low-dose fluoroscopic x-ray often necessitates additional radiographic-dose exposures to patients to include as part of the medical records. We present an image registration based approach for the generation of highquality images from a sequence of low-dose x-ray fluoroscopy exposures. Image subregions in consecutively acquired fluoroscopy frames are registered to subregions in a pre-selected reference frame using a two-dimensional transformation model. Frames neighboring the reference image are resampled using a smooth deformation field generated by interpolation of the individual subregion deformations. Motion-corrected neighboring frames are then combined with the reference frame using a weighted, frequency-specific multi-resolution combination method. Using this method, image noise (localized standard deviation) was reduced by 38% in phantom data and by 29% in clinical barium swallow examinations. We demonstrate an effective method for generating a simulated radiographic-dose x-ray image from a set of consecutively acquired low-dose fluoroscopy images. The significant improvement in image quality indicates the potential of this approach to lower average patient dose by substantially reducing the need for additional exposures for patient records.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  1. Feature-based registration of historical aerial images by Area Minimization

    NASA Astrophysics Data System (ADS)

    Nagarajan, Sudhagar; Schenk, Toni

    2016-06-01

    The registration of historical images plays a significant role in assessing changes in land topography over time. By comparing historical aerial images with recent data, geometric changes that have taken place over the years can be quantified. However, the lack of ground control information and precise camera parameters has limited scientists' ability to reliably incorporate historical images into change detection studies. Other limitations include the methods of determining identical points between recent and historical images, which has proven to be a cumbersome task due to continuous land cover changes. Our research demonstrates a method of registering historical images using Time Invariant Line (TIL) features. TIL features are different representations of the same line features in multi-temporal data without explicit point-to-point or straight line-to-straight line correspondence. We successfully determined the exterior orientation of historical images by minimizing the area formed between corresponding TIL features in recent and historical images. We then tested the feasibility of the approach with synthetic and real data and analyzed the results. Based on our analysis, this method shows promise for long-term 3D change detection studies.

  2. Subject-specific four-dimensional liver motion modeling based on registration of dynamic MRI.

    PubMed

    Noorda, Yolanda H; Bartels, Lambertus W; Viergever, Max A; Pluim, Josien P W

    2016-01-01

    Magnetic resonance-guided high intensity focused ultrasound treatment of the liver is a promising noninvasive technique for ablation of liver lesions. For the technique to be used in clinical practice, however, the issue of liver motion needs to be addressed. A subject-specific four-dimensional liver motion model is presented that is created based on registration of dynamically acquired magnetic resonance data. This model can be used for predicting the tumor motion trajectory for treatment planning and to indicate the tumor position for treatment guidance. The performance of the model was evaluated on a dynamic scan series that was not used to build the model. The method achieved an average Dice coefficient of 0.93 between the predicted and actual liver profiles and an average vessel misalignment of 3.0 mm. The model performed robustly, with a small variation in the results per subject. The results demonstrate the potential of the model to be used for MRI-guided treatment of liver lesions. Furthermore, the model can possibly be applied in other image-guided therapies, for instance radiotherapy of the liver. PMID:27493981

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

    PubMed

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

    2016-01-01

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

  4. Topography-Based Registration of Developing Cortical Surfaces in Infants Using Multidirectional Varifold Representation

    PubMed Central

    Rekik, Islem; Li, Gang; Lin, Weili; Shen, Dinggang

    2016-01-01

    Cortical surface registration or matching facilitates atlasing, cortical morphology-function comparison and statistical analysis. Methods that geodesically shoot surfaces into one another, as currents or varifolds, provide an elegant mathematical framework for generic surface matching and dynamic local features estimation, such as deformation momenta. However, conventional current and varifold matching methods only use the normals of the surface to measure its geometry and guide the warping process, which overlooks the importance of the direction in the convoluted cortical sulcal and gyral folds. To cope with the stated limitation, we decompose each cortical surface into its normal and tangent varifold representations, by integrating principal curvature direction field into the varifold matching framework, thus providing rich information for the direction of cortical folding and better characterization of the cortical geometry. To include more informative cortical geometric features in the matching process, we adaptively place control points based on the surface topography, hence the deformation is controlled by points lying on gyral crests (or “hills”) and sulcal fundi (or “valleys”) of the cortical surface, which are the most reliable and important topographic and anatomical landmarks on the cortex. We applied our method for registering the developing cortical surfaces in 12 infants from 0 to 6 months of age. Both of these variants significantly improved the matching accuracy in terms of closeness to the target surface and the precision of alignment with regional anatomical boundaries, when compared with several state-of-the-art methods: (1) diffeomorphic spectral matching, (2) current-based surface matching and (3) original varifold-based surface matching. PMID:27169137

  5. Image registration with uncertainty analysis

    DOEpatents

    Simonson, Katherine M.

    2011-03-22

    In an image registration method, edges are detected in a first image and a second image. A percentage of edge pixels in a subset of the second image that are also edges in the first image shifted by a translation is calculated. A best registration point is calculated based on a maximum percentage of edges matched. In a predefined search region, all registration points other than the best registration point are identified that are not significantly worse than the best registration point according to a predetermined statistical criterion.

  6. Magnetic microbubble-mediated ultrasound-MRI registration based on robust optical flow model

    PubMed Central

    2015-01-01

    Background As a dual-modality contrast agent, magnetic microbubbles (MMBs) can not only improve contrast of ultrasound (US) image, but can also serve as a contrast agent of magnetic resonance image (MRI). With the help of MMBs, a new registration method between US image and MRI is presented. Methods In this method, MMBs were used in both ultrasound and magnetic resonance imaging process to enhance the most important information of interest. In order to reduce the influence of the speckle noise to registration, semi-automatic segmentations of US image and MRI were carried out by using active contour model. After that, a robust optical flow model between US image segmentation (floating image) and MRI segmentation (reference image) was built, and the vector flow field was estimated by using the Coarse-to-fine Gaussian pyramid and graduated non-convexity (GNC) schemes. Results Qualitative and quantitative analyses of multiple group comparison experiments showed that registration results using all methods tested in this paper without MMBs were unsatisfactory. On the contrary, the proposed method combined with MMBs led to the best registration results. Conclusion The proposed algorithm combined with MMBs contends with larger deformation and performs well not only for local deformation but also for global deformation. The comparison experiments also demonstrated that ultrasound-MRI registration using the above-mentioned method might be a promising method for obtaining more accurate image information. PMID:25602434

  7. Rendering-based video-CT registration with physical constraints for image-guided endoscopic sinus surgery

    NASA Astrophysics Data System (ADS)

    Otake, Y.; Leonard, S.; Reiter, A.; Rajan, P.; Siewerdsen, J. H.; Ishii, M.; Taylor, R. H.; Hager, G. D.

    2015-03-01

    We present a system for registering the coordinate frame of an endoscope to pre- or intra- operatively acquired CT data based on optimizing the similarity metric between an endoscopic image and an image predicted via rendering of CT. Our method is robust and semi-automatic because it takes account of physical constraints, specifically, collisions between the endoscope and the anatomy, to initialize and constrain the search. The proposed optimization method is based on a stochastic optimization algorithm that evaluates a large number of similarity metric functions in parallel on a graphics processing unit. Images from a cadaver and a patient were used for evaluation. The registration error was 0.83 mm and 1.97 mm for cadaver and patient images respectively. The average registration time for 60 trials was 4.4 seconds. The patient study demonstrated robustness of the proposed algorithm against a moderate anatomical deformation.

  8. A Fuzzy-Based Fusion Method of Multimodal Sensor-Based Measurements for the Quantitative Evaluation of Eye Fatigue on 3D Displays

    PubMed Central

    Bang, Jae Won; Choi, Jong-Suk; Heo, Hwan; Park, Kang Ryoung

    2015-01-01

    With the rapid increase of 3-dimensional (3D) content, considerable research related to the 3D human factor has been undertaken for quantitatively evaluating visual discomfort, including eye fatigue and dizziness, caused by viewing 3D content. Various modalities such as electroencephalograms (EEGs), biomedical signals, and eye responses have been investigated. However, the majority of the previous research has analyzed each modality separately to measure user eye fatigue. This cannot guarantee the credibility of the resulting eye fatigue evaluations. Therefore, we propose a new method for quantitatively evaluating eye fatigue related to 3D content by combining multimodal measurements. This research is novel for the following four reasons: first, for the evaluation of eye fatigue with high credibility on 3D displays, a fuzzy-based fusion method (FBFM) is proposed based on the multimodalities of EEG signals, eye blinking rate (BR), facial temperature (FT), and subjective evaluation (SE); second, to measure a more accurate variation of eye fatigue (before and after watching a 3D display), we obtain the quality scores of EEG signals, eye BR, FT and SE; third, for combining the values of the four modalities we obtain the optimal weights of the EEG signals BR, FT and SE using a fuzzy system based on quality scores; fourth, the quantitative level of the variation of eye fatigue is finally obtained using the weighted sum of the values measured by the four modalities. Experimental results confirm that the effectiveness of the proposed FBFM is greater than other conventional multimodal measurements. Moreover, the credibility of the variations of the eye fatigue using the FBFM before and after watching the 3D display is proven using a t-test and descriptive statistical analysis using effect size. PMID:25961382

  9. A Context-Aware-Based Audio Guidance System for Blind People Using a Multimodal Profile Model

    PubMed Central

    Lin, Qing; Han, Youngjoon

    2014-01-01

    A wearable guidance system is designed to provide context-dependent guidance messages to blind people while they traverse local pathways. The system is composed of three parts: moving scene analysis, walking context estimation and audio message delivery. The combination of a downward-pointing laser scanner and a camera is used to solve the challenging problem of moving scene analysis. By integrating laser data profiles and image edge profiles, a multimodal profile model is constructed to estimate jointly the ground plane, object locations and object types, by using a Bayesian network. The outputs of the moving scene analysis are further employed to estimate the walking context, which is defined as a fuzzy safety level that is inferred through a fuzzy logic model. Depending on the estimated walking context, the audio messages that best suit the current context are delivered to the user in a flexible manner. The proposed system is tested under various local pathway scenes, and the results confirm its efficiency in assisting blind people to attain autonomous mobility. PMID:25302812

  10. Time-Dependent Properties of Multimodal Polyoxymethylene Based Binder for Powder Injection Molding

    NASA Astrophysics Data System (ADS)

    Gonzalez-Gutierrez, Joamin; Stringari, Gustavo Beulke; Zupancic, Barbara; Kubyshkina, Galina; Bernstorff, Bernd Von; Emri, Igor

    Powder injection molding (PIM) is one of the most versatile methods for the manufacturing of small complex shaped components from metal, ceramic or cemented carbide powders for the use in many applications. PIM consists of mixing the powder and a polymeric binder, injecting this mixture in a mold, debinding and then sintering. Catalytic debinding of polyoxymethylene (POM) is attractive since it shows high debinding rates and low risk of cracking. This work examines the possibility of using POM with bimodal molecular mass distribution as the main component of the binding agent by studying its time-dependent properties and comparing them to monomodal POM. Furthermore, possible optimization of the binder formulation was investigated by the addition of shorter polymeric chains (wax) to bimodal POM, as to create a multimodal material. It was observed that the magnitude of the complex viscosity for the commercial bimodal material was more than 2 times lower than for the chemically identical monomodal POM within the investigated frequency range and temperature. Viscosity values were observed to drop as the content of wax was increased, without compromising the binders mechanical properties in solid state. A new formulation of bimodal POM plus 8 wt.% of added wax provided the most appropriate results from investigated combinations. This work has shown how the addition of short polymeric chains in POM influences its time-dependent properties in solid and molten state, which can be an important tool for the optimization of binders designed to be used in PIM technology.

  11. Towards an automatic early stress recognition system for office environments based on multimodal measurements: A review.

    PubMed

    Alberdi, Ane; Aztiria, Asier; Basarab, Adrian

    2016-02-01

    Stress is a major problem of our society, as it is the cause of many health problems and huge economic losses in companies. Continuous high mental workloads and non-stop technological development, which leads to constant change and need for adaptation, makes the problem increasingly serious for office workers. To prevent stress from becoming chronic and provoking irreversible damages, it is necessary to detect it in its early stages. Unfortunately, an automatic, continuous and unobtrusive early stress detection method does not exist yet. The multimodal nature of stress and the research conducted in this area suggest that the developed method will depend on several modalities. Thus, this work reviews and brings together the recent works carried out in the automatic stress detection looking over the measurements executed along the three main modalities, namely, psychological, physiological and behavioural modalities, along with contextual measurements, in order to give hints about the most appropriate techniques to be used and thereby, to facilitate the development of such a holistic system. PMID:26621099

  12. Multimodality Neurological Data Visualization With Multi-VOI-Based DTI Fiber Dynamic Integration.

    PubMed

    Zhang, Qi; Alexander, Murray; Ryner, Lawrence

    2016-01-01

    Brain lesions are usually located adjacent to critical spinal structures, so it is a challenging task for neurosurgeons to precisely plan a surgical procedure without damaging healthy tissues and nerves. The advancement of medical imaging technologies produces a large amount of neurological data, which are capable of showing a wide variety of brain properties. Advanced algorithms of medical data computing and visualization are critically helpful in efficiently utilizing the acquired data for disease diagnosis and brain function and structure exploration, which is helpful for treatment planning. In this paper, we describe new algorithms and a software framework for multiple volume of interest specified diffusion tensor imaging (DTI) fiber dynamic visualization. The displayed results have been integrated with a volume rendering pipeline for multimodality neurological data exploration. A depth texture indexing algorithm is used to detect DTI fiber tracts in graphics process units (GPUs), which makes fibers to be displayed and interactively manipulated with brain data acquired from functional magnetic resonance imaging, T1- and T2-weighted anatomic imaging, and angiographic imaging. The developed software platform is built on an object-oriented structure, which is transparent and extensible. It provides a comprehensive human-computer interface for data exploration and information extraction. The GPU-accelerated high-performance computing kernels have been implemented to enable our software to dynamically visualize neurological data. The developed techniques will be useful in computer-aided neurological disease diagnosis, brain structure exploration, and general cognitive neuroscience. PMID:25376048

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

    PubMed

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

    2010-04-01

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

  14. Implementation of Fiducial-Based Image Registration in the Cyberknife Robotic System

    SciTech Connect

    Saw, Cheng B. Chen Hungcheng; Wagner, Henry

    2008-07-01

    Fiducial-based image registration methodology as implemented in the Cyberknife system is explored. The Cyberknife is a radiosurgery system that uses image guidance technology and computer-controlled robotics to determine target positions and adjust beam directions accordingly during the dose delivery. The image guidance system consists of 2 x-ray sources mounted on the ceiling and a detection system mounted on both sides of the treatment couch. Two orthogonal live radiographs are taken prior to and during patient treatment. Fiducial markers are identified on these radiographs and compared to a library of digital reconstructed radiographs (DRRs) using the fiducial extraction software. The fiducial extraction software initially sets an intensity threshold on the live radiographs to generate white areas on black images referred to as 'blobs.' Different threshold values are being used and blobs at the same location are assumed to originate from the same object. The number of blobs is then reduced by examining each blob against a predefined set of properties such as shape and exposure levels. The remaining blobs are further reduced by examining the location of the blobs in the inferior-superior patient axis. Those blobs that have the corresponding positions are assumed to originate from the same object. The remaining blobs are used to create fiducial configurations and are compared to the reference configuration from the computed tomography (CT) image dataset for treatment planning. The best-fit configuration is considered to have the appropriate fiducial markers. The patient position is determined based on these fiducial markers. During the treatment, the radiation beam is turned off when the Cyberknife changes nodes. This allows a time window to acquire live radiographs for the determination of the patient target position and to update the robotic manipulator to change beam orientations accordingly.

  15. Implementation of fiducial-based image registration in the Cyberknife robotic system.

    PubMed

    Saw, Cheng B; Chen, Hungcheng; Wagner, Henry

    2008-01-01

    Fiducial-based image registration methodology as implemented in the Cyberknife system is explored. The Cyberknife is a radiosurgery system that uses image guidance technology and computer-controlled robotics to determine target positions and adjust beam directions accordingly during the dose delivery. The image guidance system consists of 2 x-ray sources mounted on the ceiling and a detection system mounted on both sides of the treatment couch. Two orthogonal live radiographs are taken prior to and during patient treatment. Fiducial markers are identified on these radiographs and compared to a library of digital reconstructed radiographs (DRRs) using the fiducial extraction software. The fiducial extraction software initially sets an intensity threshold on the live radiographs to generate white areas on black images referred to as "blobs." Different threshold values are being used and blobs at the same location are assumed to originate from the same object. The number of blobs is then reduced by examining each blob against a predefined set of properties such as shape and exposure levels. The remaining blobs are further reduced by examining the location of the blobs in the inferior-superior patient axis. Those blobs that have the corresponding positions are assumed to originate from the same object. The remaining blobs are used to create fiducial configurations and are compared to the reference configuration from the computed tomography (CT) image dataset for treatment planning. The best-fit configuration is considered to have the appropriate fiducial markers. The patient position is determined based on these fiducial markers. During the treatment, the radiation beam is turned off when the Cyberknife changes nodes. This allows a time window to acquire live radiographs for the determination of the patient target position and to update the robotic manipulator to change beam orientations accordingly. PMID:18456167

  16. Multiple Vehicle Cooperative Localization with Spatial Registration Based on a Probability Hypothesis Density Filter

    PubMed Central

    Zhang, Feihu; Buckl, Christian; Knoll, Alois

    2014-01-01

    This paper studies the problem of multiple vehicle cooperative localization with spatial registration in the formulation of the probability hypothesis density (PHD) filter. Assuming vehicles are equipped with proprioceptive and exteroceptive sensors (with biases) to cooperatively localize positions, a simultaneous solution for joint spatial registration and state estimation is proposed. For this, we rely on the sequential Monte Carlo implementation of the PHD filtering. Compared to other methods, the concept of multiple vehicle cooperative localization with spatial registration is first proposed under Random Finite Set Theory. In addition, the proposed solution also addresses the challenges for multiple vehicle cooperative localization, e.g., the communication bandwidth issue and data association uncertainty. The simulation result demonstrates its reliability and feasibility in large-scale environments. PMID:24406860

  17. Validation of a hybrid Doppler ultrasound vessel-based registration algorithm for neurosurgery

    PubMed Central

    Chen, Sean Jy-Shyang; Reinertsen, Ingerid; Coupé, Pierrick; Yan, Charles X B; Mercier, Laurence; Del Maestro, D Rolando; Collins, D Louis

    2012-01-01

    Purpose We describe and validate a novel hybrid non-linear vessel registration algorithm for intraoperative updating of preoperative magnetic resonance (MR) images using Doppler ultrasound (US) images acquired on the dura for the correction of brain-shift and registration inaccuracies. We also introduce an US vessel appearance simulator that generates vessel images similar in appearance to that acquired with US from MR angiography data. Methods Our registration uses the minimum amount of preprocessing to extract vessels from the raw volumetric images. This prevents the removal of important registration information and minimizes the introduction of artifacts that may affect robustness, while reducing the amount of extraneous information in the image to be processed, thus improving the convergence speed of the algorithm. We then completed 3 rounds of validation for our vessel registration method for robustness and accuracy using (i)a large number of synthetic trials generated with our US vessel simulator, (ii)US images acquired from a real physical phantom made from polyvinyl alcohol cryogel (PVAc), and (iii)real clinical data gathered intraoperatively from 3 patients. Results Resulting target registration errors (TRE) of less than 2.5mm are achieved in more than 90% of the synthetic trials when the initial TREs are less than 20mm. TREs of less than 2mm were achieved when the technique was applied to the physical phantom, and TREs of less than 3mm were achieved on clinical data. Conclusions These test trials show that the proposed algorithm is not only accurate but also highly robust to noise and missing vessel segments when working with US images acquired in a wide range of real-world conditions. PMID:22447435

  18. SU-E-J-111: Finite Element-Based Deformable Image Registration of Pleural Cavity for Photodynamic Therapy

    SciTech Connect

    Penjweini, R; Zhu, T

    2015-06-15

    Purpose: The pleural volumes will deform during surgery portion of the pleural photodynamic therapy (PDT) of lung cancer when the pleural cavity is opened. This impact the delivered dose when using highly conformal treatment techniques. In this study, a finite element-based (FEM) deformable image registration is used to quantify the anatomical variation between the contours for the pleural cavities obtained in the operating room and those determined from pre-surgery computed tomography (CT) scans. Methods: An infrared camera-based navigation system (NDI) is used during PDT to track the anatomical changes and contour the lung and chest cavity. A series of CTs of the lungs, in the same patient, are also acquired before the surgery. The structure contour of lung and the CTs are processed and contoured in Matlab and MeshLab. Then, the contours are imported into COMSOL Multiphysics 5.0, where the FEM-based deformable image registration is obtained using the deformed mesh - moving mesh (ALE) model. The NDI acquired lung contour is considered as the reference contour, and the CT contour is used as the target one, which will be deformed. Results: The reconstructed three-dimensional contours from both NDI and CT can be converted to COMSOL so that a three-dimensional ALE model can be developed. The contours can be registered using COMSOL ALE moving mesh model, which takes into account the deformation along x, y and z-axes. The deformed contour has good matches to the reference contour after the dynamic matching process. The resulting 3D deformation map can be used to obtain the locations of other critical anatomic structures, e.g., heart, during surgery. Conclusion: Deformable image registration can fuse images acquired by different modalities. It provides insights into the development of phenomenon and variation in normal anatomical structures over time. The initial assessments of three-dimensional registration show good agreement.

  19. Development of an eye model from multimodal data

    NASA Astrophysics Data System (ADS)

    Yu, Chun P.; Jagannathan, Lakshmipathy; Srinivasan, Rajagopalan; Nowinski, Wieslaw L.

    1998-06-01

    We are building a 3D eye model from multimodal data and this paper describes our progress in using images from the Visible Human project and Scheimpflug images. The former is being targeted at muscles and the eyeball and the latter is being used to model the cornea. In this regard, the orbital anatomy of the Visible Human is being segmented and the relevant segmented data are then used to create geometric models. The lessons and methods we have learnt here will then be applied to MRI data when these become available. For Scheimpflug data, we are mutually registering individual images to reconstruct the cornea first, after which volumetric models can then be obtained. Our registration method is based on the fact that each image has a common point which can be used as a landmark. Future work includes registration of cornea and eyeball models, the incorporation of CT and biometric norms, as well as the identification of anatomical landmarks for deformation and registration.

  20. Propagating labels of the human brain based on non-rigid MR image registration: an evaluation

    NASA Astrophysics Data System (ADS)

    Heckemann, Rolf A.; Hajnal, Joseph V.; Rueckert, Daniel; Hill, Derek L. G.; Hammers, Alexander

    2005-04-01

    Background: In order to perform statistical analysis of cohorts based on images, reliable methods for automated anatomical segmentation are required. Label propagation (LP) from manually segmented atlases onto newly acquired images is a particularly promising approach. Methods: We investigated LP on a set of 6 three-dimensional T1-weighted magnetic resonance data sets of the brains of normal individuals. For each image, a manually prepared segmentation of 67 structures was available. Each subject image was used in turn as an atlas and registered non-rigidly to each other subject's image. The resulting transformations were applied to the label sets, yielding five different generated segmentations for each subject, which we compared with the native manual segmentations using an overlap measure (similarity index, SI). We then reviewed the LP results for five structures with varied anatomical and label characteristics visually to determine how the registration procedure had affected the delineation of their boundaries. Results: The majority of structures propagated well as measured by SI (SI > 70 in 80% of measurements). Boundaries that were marked in the atlas image by definite intensity differences were congruent, with good agreement between the manual and the generated segmentations. Some boundaries in the manual segmentation were defined as planes marked by landmarks; such boundaries showed greater mismatch. In some cases, the proximity of structures with similar intensity distorted the LP results: e.g., parts of the parahippocampal gyrus were labeled as hippocampus in two cases. Conclusion: The size and shape of anatomical structures can be determined reliably using label propagation, especially where boundaries are defined by distinct differences in grey scale image intensity. These results will inform further work to evaluate potential clinical uses of information extracted from images in this way.

  1. Intra-operative prostate brachytherapy dosimetry based on partial seed localization in ultrasound and registration to C-arm fluoroscopy.

    PubMed

    Moradi, Mehdi; Mahdavi, Sara S; Deshmukh, Sanchit; Lobo, Julio; Dehghan, Ehsan; Fichtinger, Gabor; Morris, William J; Salcudean, Septimiu E

    2011-01-01

    Intraoperative dosimetry during prostate brachytherapy is a long standing clinical problem. We propose a novel framework to address this problem by reliable detection of a subset of seeds from 3D transrectal ultrasound and registration to fluoroscopy. Seed detection in ultrasound is achieved through template matching in the RF ultrasound domain followed by thresholding and spatial filtering based on the fixed distance between stranded seeds. This subset of seeds is registered to the complete reconstruction of the implant in C-arm fluoroscopy. We report results, validated with a leave-one-needle-out approach, both in a phantom (average post-registration seed distance of 2.5 mm) and in three clinical patient datasets (average error: 3.9 mm over 113 seeds). PMID:22003629

  2. New nanoplatforms based on UCNPs linking with polyhedral oligomeric silsesquioxane (POSS) for multimodal bioimaging

    NASA Astrophysics Data System (ADS)

    Ge, Xiaoqian; Dong, Liang; Sun, Lining; Song, Zhengmei; Wei, Ruoyan; Shi, Liyi; Chen, Haige

    2015-04-01

    A new and facile method was used to transfer upconversion luminescent nanoparticles from hydrophobic to hydrophilic using polyhedral oligomeric silsesquioxane (POSS) linking on the surface of upconversion nanoparticles. In comparison with the unmodified upconversion nanoparticles, the POSS modified upconversion nanoplatforms [POSS-UCNPs(Er), POSS-UCNPs(Tm)] displayed good monodispersion in water and exhibited good water-solubility, while their particle size did not change substantially. Due to the low cytotoxicity and good biocompatibility as determined by methyl thiazolyl tetrazolium (MTT) assay and histology and hematology analysis, the POSS modified upconversion nanoplatforms were successfully applied to upconversion luminescence imaging of living cells in vitro and nude mouse in vivo (upon excitation at 980 nm). In addition, the doped Gd3+ ion endows the POSS-UCNPs with effective T1 signal enhancement and the POSS-UCNPs were successfully applied to in vivo magnetic resonance imaging (MRI) for a Kunming mouse, which makes them potential MRI positive-contrast agents. More importantly, the corner organic groups of POSS can be easily modified, resulting in kinds of POSS-UCNPs with many potential applications. Therefore, the method and results may provide more exciting opportunities for multimodal bioimaging and multifunctional applications.A new and facile method was used to transfer upconversion luminescent nanoparticles from hydrophobic to hydrophilic using polyhedral oligomeric silsesquioxane (POSS) linking on the surface of upconversion nanoparticles. In comparison with the unmodified upconversion nanoparticles, the POSS modified upconversion nanoplatforms [POSS-UCNPs(Er), POSS-UCNPs(Tm)] displayed good monodispersion in water and exhibited good water-solubility, while their particle size did not change substantially. Due to the low cytotoxicity and good biocompatibility as determined by methyl thiazolyl tetrazolium (MTT) assay and histology and hematology

  3. Easily processable multimodal spectral converters based on metal oxide/organic—inorganic hybrid nanocomposites

    NASA Astrophysics Data System (ADS)

    Julián-López, Beatriz; Gonell, Francisco; Lima, Patricia P.; Freitas, Vânia T.; André, Paulo S.; Carlos, Luis D.; Ferreira, Rute A. S.

    2015-10-01

    This manuscript reports the synthesis and characterization of the first organic-inorganic hybrid material exhibiting efficient multimodal spectral converting properties. The nanocomposite, made of Er3+, Yb3+ codoped zirconia nanoparticles (NPs) entrapped in a di-ureasil d-U(600) hybrid matrix, is prepared by an easy two-step sol-gel synthesis leading to homogeneous and transparent materials that can be very easily processed as monolith or film. Extensive structural characterization reveals that zirconia nanocrystals of 10-20 nm in size are efficiently dispersed into the hybrid matrix and that the local structure of the di-ureasil is not affected by the presence of the NPs. A significant enhancement in the refractive index of the di-ureasil matrix with the incorporation of the ZrO2 nanocrystals is observed. The optical study demonstrates that luminescent properties of both constituents are perfectly preserved in the final hybrid. Thus, the material displays a white-light photoluminescence from the di-ureasil component upon excitation at UV/visible radiation and also intense green and red emissions from the Er3+- and Yb3+-doped NPs after NIR excitation. The dynamics of the optical processes were also studied as a function of the lanthanide content and the thickness of the films. Our results indicate that these luminescent hybrids represent a low-cost, environmentally friendly, size-controlled, easily processed and chemically stable alternative material to be used in light harvesting devices such as luminescent solar concentrators, optical fibres and sensors. Furthermore, this synthetic approach can be extended to a wide variety of luminescent NPs entrapped in hybrid matrices, thus leading to multifunctional and versatile materials for efficient tuneable nonlinear optical nanodevices.

  4. Multimodal neuroimaging based classification of autism spectrum disorder using anatomical, neurochemical, and white matter correlates

    PubMed Central

    Libero, Lauren E.; DeRamus, Thomas P.; Lahti, Adrienne C.; Deshpande, Gopikrishna; Kana, Rajesh K.

    2016-01-01

    Neuroimaging techniques, such as fMRI, structural MRI, diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (1H-MRS) have uncovered evidence for widespread functional and anatomical brain abnormalities in autism spectrum disorder (ASD) suggesting it to be a system-wide neural systems disorder. Nevertheless, most previous studies have focused on examining one index of neuropathology through a single neuroimaging modality, and seldom using multiple modalities to examine the same cohort of individuals. The current study aims to bring together multiple brain imaging modalities (structural MRI, DTI, and 1H-MRS) to investigate the neural architecture in the same set of individuals (19 high-functioning adults with ASD and 18 typically developing (TD) peers). Morphometry analysis revealed increased cortical thickness in ASD participants, relative to typical controls, across the left cingulate, left pars opercularis of the inferior frontal gyrus, left inferior temporal cortex, and right precuneus, and reduced cortical thickness in right cuneus and right precentral gyrus. ASD adults also had reduced fractional anisotropy (FA) and increased radial diffusivity (RD) for two clusters on the forceps minor of the corpus callosum, revealed by DTI analyses. 1H-MRS results showed a reduction in the N-acetylaspartate/Creatine ratio in dorsal anterior cingulate cortex (dACC) in ASD participants. A decision tree classification analysis across the three modalities resulted in classification accuracy of 91.9% with FA, RD, and cortical thickness as key predictors. Examining the same cohort of adults with ASD and their TD peers, this study found alterations in cortical thickness, white matter (WM) connectivity, and neurochemical concentration in ASD. These findings underscore the potential for multimodal imaging to better inform on the neural characteristics most relevant to the disorder. PMID:25797658

  5. Easily processable multimodal spectral converters based on metal oxide/organic-inorganic hybrid nanocomposites.

    PubMed

    Julián-López, Beatriz; Gonell, Francisco; Lima, Patricia P; Freitas, Vânia T; André, Paulo S; Carlos, Luis D; Ferreira, Rute A S

    2015-10-01

    This manuscript reports the synthesis and characterization of the first organic-inorganic hybrid material exhibiting efficient multimodal spectral converting properties. The nanocomposite, made of Er(3+), Yb(3+) codoped zirconia nanoparticles (NPs) entrapped in a di-ureasil d-U(600) hybrid matrix, is prepared by an easy two-step sol-gel synthesis leading to homogeneous and transparent materials that can be very easily processed as monolith or film. Extensive structural characterization reveals that zirconia nanocrystals of 10-20 nm in size are efficiently dispersed into the hybrid matrix and that the local structure of the di-ureasil is not affected by the presence of the NPs. A significant enhancement in the refractive index of the di-ureasil matrix with the incorporation of the ZrO2 nanocrystals is observed. The optical study demonstrates that luminescent properties of both constituents are perfectly preserved in the final hybrid. Thus, the material displays a white-light photoluminescence from the di-ureasil component upon excitation at UV/visible radiation and also intense green and red emissions from the Er(3+)- and Yb(3+)-doped NPs after NIR excitation. The dynamics of the optical processes were also studied as a function of the lanthanide content and the thickness of the films. Our results indicate that these luminescent hybrids represent a low-cost, environmentally friendly, size-controlled, easily processed and chemically stable alternative material to be used in light harvesting devices such as luminescent solar concentrators, optical fibres and sensors. Furthermore, this synthetic approach can be extended to a wide variety of luminescent NPs entrapped in hybrid matrices, thus leading to multifunctional and versatile materials for efficient tuneable nonlinear optical nanodevices. PMID:26374133

  6. Photonic crystal fiber refractive-index sensor based on multimode interferometry

    NASA Astrophysics Data System (ADS)

    Gong, Zhenfeng; Zhang, Xinpu; Liu, Yun; Liu, Zigeng; Peng, Wei

    2014-11-01

    We report a type of multimode fiber interferometers (MMI) formed in photonic crystal fiber (PCF). To excite the cladding modes from the fundamental core mode of a PCF, a coupling point is formed. To form the coupling point, we used the method that is blowing compressed gas into the air-holes and discharging at one point, and the air-holes in this point will expand due to gas expansion in the discharge process. By placing two coupling points in series, a very simple all-fiber MMI can be implemented. The detailed fabrication process is that the one end of the PCF is tightly sealed by a short section of single mode fiber (SMF) spliced to the PCF. The other end of the PCF is sealed into a gas chamber and the opened air holes are pressurized. The PCF is then heated locally by the fusion splicer and the holes with higher gas pressure will expand locally where two bubbles formed. We tested the RI responses of fabricated sensors at room temperature by immersing the sensor into solutions with different NaCl concentration. Experimental results show that as refractive-index (RI) increases, the resonance wavelength of the MMI moves toward longer wavelengths. The sensitivity coefficients are estimated by the linear fitting line, which is 46nm/RIU, 154mn/RIU with the interferometer lengths (IL) of 3mm and 6mm. The interferometer with larger IL has higher RI sensitivity. The temperature cross-sensitivity of the sensor is also tested. The temperature sensitivity can be as low as -16.0pm/°C.

  7. Inter-slice bidirectional registration-based segmentation of the prostate gland in MR and CT image sequences

    SciTech Connect

    Khalvati, Farzad Tizhoosh, Hamid R.; Salmanpour, Aryan; Rahnamayan, Shahryar; Rodrigues, George

    2013-12-15

    Purpose: Accurate segmentation and volume estimation of the prostate gland in magnetic resonance (MR) and computed tomography (CT) images are necessary steps in diagnosis, treatment, and monitoring of prostate cancer. This paper presents an algorithm for the prostate gland volume estimation based on the semiautomated segmentation of individual slices in T2-weighted MR and CT image sequences. Methods: The proposedInter-Slice Bidirectional Registration-based Segmentation (iBRS) algorithm relies on interslice image registration of volume data to segment the prostate gland without the use of an anatomical atlas. It requires the user to mark only three slices in a given volume dataset, i.e., the first, middle, and last slices. Next, the proposed algorithm uses a registration algorithm to autosegment the remaining slices. We conducted comprehensive experiments to measure the performance of the proposed algorithm using three registration methods (i.e., rigid, affine, and nonrigid techniques). Results: The results with the proposed technique were compared with manual marking using prostate MR and CT images from 117 patients. Manual marking was performed by an expert user for all 117 patients. The median accuracies for individual slices measured using the Dice similarity coefficient (DSC) were 92% and 91% for MR and CT images, respectively. The iBRS algorithm was also evaluated regarding user variability, which confirmed that the algorithm was robust to interuser variability when marking the prostate gland. Conclusions: The proposed algorithm exploits the interslice data redundancy of the images in a volume dataset of MR and CT images and eliminates the need for an atlas, minimizing the computational cost while producing highly accurate results which are robust to interuser variability.

  8. Population-based prediction of subject-specific prostate deformation for MR-to-ultrasound image registration

    PubMed Central

    Hu, Yipeng; Gibson, Eli; Ahmed, Hashim Uddin; Moore, Caroline M.; Emberton, Mark; Barratt, Dean C.

    2015-01-01

    Statistical shape models of soft-tissue organ motion provide a useful means of imposing physical constraints on the displacements allowed during non-rigid image registration, and can be especially useful when registering sparse and/or noisy image data. In this paper, we describe a method for generating a subject-specific statistical shape model that captures prostate deformation for a new subject given independent population data on organ shape and deformation obtained from magnetic resonance (MR) images and biomechanical modelling of tissue deformation due to transrectal ultrasound (TRUS) probe pressure. The characteristics of the models generated using this method are compared with corresponding models based on training data generated directly from subject-specific biomechanical simulations using a leave-one-out cross validation. The accuracy of registering MR and TRUS images of the prostate using the new prostate models was then estimated and compared with published results obtained in our earlier research. No statistically significant difference was found between the specificity and generalisation ability of prostate shape models generated using the two approaches. Furthermore, no statistically significant difference was found between the landmark-based target registration errors (TREs) following registration using different models, with a median (95th percentile) TRE of 2.40 (6.19) mm versus 2.42 (7.15) mm using models generated with the new method versus a model built directly from patient-specific biomechanical simulation data, respectively (N = 800; 8 patient datasets; 100 registrations per patient). We conclude that the proposed method provides a computationally efficient and clinically practical alternative to existing complex methods for modelling and predicting subject-specific prostate deformation, such as biomechanical simulations, for new subjects. The method may also prove useful for generating shape models for other organs, for example, where

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

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... registration; (vi) Failure to maintain a Form FMC-1 or a tariff in compliance with 46 CFR part 520; (vii... of business address (including telephone number, facsimile number); contact person and email address...) (including physical address, mailing address, email address, telephone and facsimile number(s), and...

  10. A 3D neurovascular bundles segmentation method based on MR-TRUS deformable registration

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

    In this paper, we propose a 3D neurovascular bundles (NVB) segmentation method for ultrasound (US) image by integrating MR and transrectal ultrasound (TRUS) images through MR-TRUS deformable registration. First, 3D NVB was contoured by a physician in MR images, and the 3D MRdefined NVB was then transformed into US images using a MR-TRUS registration method, which models the prostate tissue as an elastic material, and jointly estimates the boundary deformation and the volumetric deformations under the elastic constraint. This technique was validated with a clinical study of 6 patients undergoing radiation therapy (RT) treatment for prostate cancer. The accuracy of our approach was assessed through the locations of landmarks, as well as previous ultrasound Doppler images of patients. MR-TRUS registration was successfully performed for all patients. The mean displacement of the landmarks between the post-registration MR and TRUS images was less than 2 mm, and the average NVB volume Dice Overlap Coefficient was over 89%. This NVB segmentation technique could be a useful tool as we try to spare the NVB in prostate RT, monitor NVB response to RT, and potentially improve post-RT potency outcomes.

  11. Automatic co-registration of space-based sensors for precision change detection and analysis

    NASA Technical Reports Server (NTRS)

    Bryant, N.; Zobrist, A.; Logan, T.

    2003-01-01

    A variety of techniques were developed at JPL to assure sub-pixel co-registration of scenes and ortho-rectification of satellite imagery to other georeferenced information to permit precise change detection and analysis of low and moderate resolution space sensors.

  12. A Review of Intravascular Ultrasound–Based Multimodal Intravascular Imaging: The Synergistic Approach to Characterizing Vulnerable Plaques

    PubMed Central

    Ma, Teng; Zhou, Bill; Hsiai, Tzung K.; Shung, K. Kirk

    2015-01-01

    Catheter-based intravascular imaging modalities are being developed to visualize pathologies in coronary arteries, such as high-risk vulnerable atherosclerotic plaques known as thin-cap fibroatheroma, to guide therapeutic strategy at preventing heart attacks. Mounting evidences have shown three distinctive histopathological features—the presence of a thin fibrous cap, a lipid-rich necrotic core, and numerous infiltrating macrophages—are key markers of increased vulnerability in atherosclerotic plaques. To visualize these changes, the majority of catheter-based imaging modalities used intravascular ultrasound (IVUS) as the technical foundation and integrated emerging intravascular imaging techniques to enhance the characterization of vulnerable plaques. However, no current imaging technology is the unequivocal “gold standard” for the diagnosis of vulnerable atherosclerotic plaques. Each intravascular imaging technology possesses its own unique features that yield valuable information although encumbered by inherent limitations not seen in other modalities. In this context, the aim of this review is to discuss current scientific innovations, technical challenges, and prospective strategies in the development of IVUS-based multi-modality intravascular imaging systems aimed at assessing atherosclerotic plaque vulnerability. PMID:26400676

  13. A Review of Intravascular Ultrasound-based Multimodal Intravascular Imaging: The Synergistic Approach to Characterizing Vulnerable Plaques.

    PubMed

    Ma, Teng; Zhou, Bill; Hsiai, Tzung K; Shung, K Kirk

    2016-09-01

    Catheter-based intravascular imaging modalities are being developed to visualize pathologies in coronary arteries, such as high-risk vulnerable atherosclerotic plaques known as thin-cap fibroatheroma, to guide therapeutic strategy at preventing heart attacks. Mounting evidences have shown three distinctive histopathological features-the presence of a thin fibrous cap, a lipid-rich necrotic core, and numerous infiltrating macrophages-are key markers of increased vulnerability in atherosclerotic plaques. To visualize these changes, the majority of catheter-based imaging modalities used intravascular ultrasound (IVUS) as the technical foundation and integrated emerging intravascular imaging techniques to enhance the characterization of vulnerable plaques. However, no current imaging technology is the unequivocal "gold standard" for the diagnosis of vulnerable atherosclerotic plaques. Each intravascular imaging technology possesses its own unique features that yield valuable information although encumbered by inherent limitations not seen in other modalities. In this context, the aim of this review is to discuss current scientific innovations, technical challenges, and prospective strategies in the development of IVUS-based multi-modality intravascular imaging systems aimed at assessing atherosclerotic plaque vulnerability. PMID:26400676

  14. 3D Mandibular Superimposition: Comparison of Regions of Reference for Voxel-Based Registration

    PubMed Central

    Ruellas, Antonio Carlos de Oliveira; Yatabe, Marilia Sayako; Souki, Bernardo Quiroga; Benavides, Erika; Nguyen, Tung; Luiz, Ronir Raggio; Franchi, Lorenzo; Cevidanes, Lucia Helena Soares

    2016-01-01

    Introduction The aim was to evaluate three regions of reference (Björk, Modified Björk and mandibular Body) for mandibular registration testing them in a patients’ CBCT sample. Methods Mandibular 3D volumetric label maps were built from CBCTs taken before (T1) and after treatment (T2) in a sample of 16 growing subjects and labeled with eight landmarks. Registrations of T1 and T2 images relative to the different regions of reference were performed, and 3D surface models were generated. Seven mandibular dimensions were measured separately for each time-point (T1 and T2) in relation to a stable reference structure (lingual cortical of symphysis), and the T2-T1 differences were calculated. These differences were compared to differences measured between the superimposed T2 (generated from different regions of reference: Björk, Modified Björk and Mandibular Body) over T1 surface models. ICC and the Bland-Altman method tested the agreement of the changes obtained by nonsuperimposition measurements from the patients’ sample, and changes between the overlapped surfaces after registration using the different regions of reference. Results The Björk region of reference (or mask) did work properly only in 2 of 16 patients. Evaluating the two other masks (Modified Björk and Mandibular body) on patients’ scans registration, the concordance and agreement of the changes obtained from superimpositions (registered T2 over T1) compared to results obtained from non superimposed T1 and T2 separately, indicated that Mandibular Body mask displayed more consistent results. Conclusions The mandibular body mask (mandible without teeth, alveolar bone, rami and condyles) is a reliable reference for 3D regional registration. PMID:27336366

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

    NASA Astrophysics Data System (ADS)

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

    2012-01-01

    The registration of a three-dimensional (3D) ultrasound (US) image with a computed tomography (CT) or magnetic resonance image is beneficial in various clinical applications such as diagnosis and image-guided intervention of the liver. However, conventional methods usually require a time-consuming and inconvenient manual process for pre-alignment, and the success of this process strongly depends on the proper selection of initial transformation parameters. In this paper, we present an automatic feature-based affine registration procedure of 3D intra-operative US and pre-operative CT images of the liver. In the registration procedure, we first segment vessel lumens and the liver surface fr