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Sample records for based multimodal registration

  1. Incorporating global information in feature-based multimodal image registration

    NASA Astrophysics Data System (ADS)

    Li, Yong; Stevenson, Robert

    2014-03-01

    A multimodal image registration framework based on searching the best matched keypoints and the incorporation of global information is proposed. It comprises two key elements: keypoint detection and an iterative process. Keypoints are detected from both the reference and test images. For each test keypoint, a number of reference keypoints are chosen as mapping candidates. A triplet of keypoint mappings determine an affine transformation that is evaluated using a similarity metric between the reference image and the transformed test image by the determined transformation. An iterative process is conducted on triplets of keypoint mappings, keeping track of the best matched reference keypoint. Random sample consensus and mutual information are applied to eliminate outlier keypoint mappings. The similarity metric is defined to be the number of overlapped edge pixels over the entire images, allowing for global information to be incorporated in the evaluation of triplets of mappings. The performance of the framework is investigated with keypoints extracted by scale invariant feature transform and partial intensity invariant feature descriptor. Experimental results show that the proposed framework can provide more accurate registration than existing methods.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  3. 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

  4. Learning based non-rigid multi-modal image registration using Kullback-Leibler divergence.

    PubMed

    Guetter, Christoph; Xu, Chenyang; Sauer, Frank; Hornegger, Joachim

    2005-01-01

    The need for non-rigid multi-modal registration is becoming increasingly common for many clinical applications. To date, however, existing proposed techniques remain as largely academic research effort with very few methods being validated for clinical product use. It has been suggested by Crum et al. that the context-free nature of these methods is one of the main limitations and that moving towards context-specific methods by incorporating prior knowledge of the underlying registration problem is necessary to achieve registration results that are accurate and robust enough for clinical applications. In this paper, we propose a novel non-rigid multi-modal registration method using a variational formulation that incorporates a prior learned joint intensity distribution. The registration is achieved by simultaneously minimizing the Kullback-Leibler divergence between an observed and a learned joint intensity distribution and maximizing the mutual information between reference and alignment images. We have applied our proposed method on both synthetic and real images with encouraging results.

  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. 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

  7. 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.

  8. 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

  9. Anatomy-based multimodal medical image registration for computer-integrated surgery

    NASA Astrophysics Data System (ADS)

    Hamadeh, Ali; Cinquin, Philippe; Szeliski, Richard; Lavallee, Stephane

    1994-10-01

    In Computer Assisted Surgery, the registration between pre-operative images, intra-operative images, anatomical models and guiding systems such as robots is a crucial step. This paper presents the methodology and the algorithms that we have developed to address the problem of rigid-body registration in this context. Our technique has been validated for many clinical cases where we had to register 3D anatomical surfaces with various sensory data. These sensory data can have 3D representation (3D images, range images, digitized 3D points, 2.5D ultrasound data) or they can be 2D projections (X-ray images, video images). This paper presents an overview of the results we have obtained.

  10. Multi-Modal Robust Inverse-Consistent Linear Registration

    PubMed Central

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

    2016-01-01

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

  11. 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

  12. 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.

  13. Registration, segmentation, and visualization of multimodal brain images.

    PubMed

    Viergever, M A; Maintz, J B; Niessen, W J; Noordmans, H J; Pluim, J P; Stokking, R; Vincken, K L

    2001-01-01

    This paper gives an overview of the studies performed at our institute over the last decade on the processing and visualization of brain images, in the context of international developments in the field. The focus is on multimodal image registration and multimodal visualization, while segmentation is touched upon as a preprocessing step for visualization. The state-of-the-art in these areas is discussed and suggestions for future research are given. PMID:11137791

  14. Registration of large data sets for multimodal inspection

    NASA Astrophysics Data System (ADS)

    Vedula, Venumadhav V. S.; Sheri, George

    2006-08-01

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

  15. 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

  16. 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.

  17. 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

  18. 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

  19. Local rigid registration for multimodal texture feature extraction from medical images

    NASA Astrophysics Data System (ADS)

    Steger, Sebastian

    2011-03-01

    The joint extraction of texture features from medical images of different modalities requires an accurate image registration at the target structures. In many cases rigid registration of the entire images does not achieve the desired accuracy whereas deformable registration is too complex and may result in undesired deformations. This paper presents a novel region of interest alignment approach based on local rigid registration enabling image fusion for multimodal texture feature extraction. First rigid registration on the entire images is performed to obtain an initial guess. Then small cubic regions around the target structure are clipped from all images and individually rigidly registered. The approach was applied to extract texture features in clinically acquired CT and MR images from lymph nodes in the oropharynx for an oral cancer reoccurrence prediction framework. Visual inspection showed that in all of the 30 cases at least a subtle misalignment was perceivable for the globally rigidly aligned images. After applying the presented approach the alignment of the target structure significantly improved in 19 cases. In 12 cases no alignment mismatch whatsoever was perceptible without requiring the complexity of deformable registration and without deforming the target structure. Further investigation showed that if the resolutions of the individual modalities differ significantly, partial volume effects occur, diminishing the significance of the multimodal features even for perfectly aligned images.

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

    PubMed

    Orchard, Jeff

    2007-10-01

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

  1. 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

  2. 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

  3. Tensor scale-based image registration

    NASA Astrophysics Data System (ADS)

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

    2003-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  5. 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.

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  8. 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

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

    PubMed

    Maes, F; Vandermeulen, D; Suetens, P

    1999-12-01

    Maximization of mutual information of voxel intensities has been demonstrated to be a very powerful criterion for three-dimensional medical image registration, allowing robust and accurate fully automated affine registration of multimodal images in a variety of applications, without the need for segmentation or other preprocessing of the images. In this paper, we investigate the performance of various optimization methods and multiresolution strategies for maximization of mutual information, aiming at increasing registration speed when matching large high-resolution images. We show that mutual information is a continuous function of the affine registration parameters when appropriate interpolation is used and we derive analytic expressions of its derivatives that allow numerically exact evaluation of its gradient. Various multiresolution gradient- and non-gradient-based optimization strategies, such as Powell, simplex, steepest-descent, conjugate-gradient, quasi-Newton and Levenberg-Marquardt methods, are evaluated for registration of computed tomography (CT) and magnetic resonance images of the brain. Speed-ups of a factor of 3 on average compared to Powell's method at full resolution are achieved with similar precision and without a loss of robustness with the simplex, conjugate-gradient and Levenberg-Marquardt method using a two-level multiresolution scheme. Large data sets such as 256(2) x 128 MR and 512(2) x 48 CT images can be registered with subvoxel precision in <5 min CPU time on current workstations. PMID:10709702

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

    PubMed

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

    2016-02-01

    Acquisition of dynamic articulatory data is of major importance for studying speech production. It turns out that one technique alone often is not enough to get a correct coverage of the whole vocal tract at a sufficient sampling rate. Ultrasound (US) imaging has been proposed as a good acquisition technique for the tongue surface because it offers a good temporal sampling, does not alter speech production, is cheap, and is widely available. However, it cannot be used alone and this paper describes a multimodal acquisition system which uses electromagnetography sensors to locate the US probe. The paper particularly focuses on the calibration of the US modality which is the key point of the system. This approach enables US data to be merged with other data. The use of the system is illustrated via an experiment consisting of measuring the minimal tongue to palate distance in order to evaluate and design Magnetic Resonance Imaging protocols well suited for the acquisition of three-dimensional images of the vocal tract. Compared to manual registration of acquisition modalities which is often used in acquisition of articulatory data, the approach presented relies on automatic techniques well founded from geometrical and mathematical points of view. PMID:26936548

  11. 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.

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

    PubMed

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

    2016-06-14

    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.

  13. Multi-modal image registration: matching MRI with histology

    NASA Astrophysics Data System (ADS)

    Alic, Lejla; Haeck, Joost C.; Klein, Stefan; Bol, Karin; van Tiel, Sandra T.; Wielopolski, Piotr A.; Bijster, Magda; Niessen, Wiro J.; Bernsen, Monique; Veenland, Jifke F.; de Jong, Marion

    2010-03-01

    Spatial correspondence between histology and multi sequence MRI can provide information about the capabilities of non-invasive imaging to characterize cancerous tissue. However, shrinkage and deformation occurring during the excision of the tumor and the histological processing complicate the co registration of MR images with histological sections. This work proposes a methodology to establish a detailed 3D relation between histology sections and in vivo MRI tumor data. The key features of the methodology are a very dense histological sampling (up to 100 histology slices per tumor), mutual information based non-rigid B-spline registration, the utilization of the whole 3D data sets, and the exploitation of an intermediate ex vivo MRI. In this proof of concept paper, the methodology was applied to one tumor. We found that, after registration, the visual alignment of tumor borders and internal structures was fairly accurate. Utilizing the intermediate ex vivo MRI, it was possible to account for changes caused by the excision of the tumor: we observed a tumor expansion of 20%. Also the effects of fixation, dehydration and histological sectioning could be determined: 26% shrinkage of the tumor was found. The annotation of viable tissue, performed in histology and transformed to the in vivo MRI, matched clearly with high intensity regions in MRI. With this methodology, histological annotation can be directly related to the corresponding in vivo MRI. This is a vital step for the evaluation of the feasibility of multi-spectral MRI to depict histological groundtruth.

  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. A partial intensity invariant feature descriptor for multimodal retinal image registration.

    PubMed

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

    2010-07-01

    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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  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. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2005-04-01

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

  1. Normal distributions transform in multi-modal image registration of optical coherence tomography and computed tomography datasets

    NASA Astrophysics Data System (ADS)

    Díaz Díaz, Jesús; Riva, Mauro H.; Majdani, Omid; Ortmaier, Tobias

    2014-03-01

    In recent years, optical coherence tomography (OCT) has gained increasing attention not only as an imaging device, but also as a navigation system for surgical interventions. This approach demands to register intraoperative OCT to pre-operative computed tomography (CT) data. In this study, we evaluate algorithms for multi-modal image registration of OCT and CT data of a human temporal bone specimen. We focus on similarity measures that are common in this field, e.g., normalized mutual information, normalized cross correlation, and iterative closest point. We evaluate and compare their accuracies to the relatively new normal distribution transform (NDT), that is very common in simultaneous localization and mapping applications, but is not widely used in image registration. Matching is realized considering appropriate image pre-processing, the aforementioned similarity measures, and local optimization algorithms, as well as line search optimization. For evaluation purpose, the results of a point-based registration with fiducial landmarks are regarded as ground truth. First results indicate that state of the art similarity functions do not perform with the desired accuracy, when applied to unprocessed image data. In contrast, NDT seems to achieve higher registration accuracy.

  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. New GPU optimizations for intensity-based registration

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

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

    SciTech Connect

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

    2005-03-31

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

  6. 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.

  7. Real-time deformable registration of multi-modal whole slides for digital pathology.

    PubMed

    Mueller, Dan; Vossen, Dirk; Hulsken, Bas

    2011-01-01

    Digital pathology provides new ways to visualize tissue slides and enables new workflows for analyzing these slides. Analogous to radiology, adjacent tissue sections prepared with different stains or biomarkers (e.g. H&E, IHC, special stains, or ISH; chromogenic or fluorescent) may be seen as different modalities, each representing different structural and/or functional information. Today, the anatomic pathologist views multiple glass slides using an optical microscope and then combines the information in their head to reach a (diagnostic) opinion. Moreover, due to the nature of the slide preparation and digitization process, the tissue and its features do not have the exact same morphology, appearance, or spatial alignment, making it difficult to find the same region on adjacent slides. To address such concerns, this paper presents a method for the spatial alignment of multi-modal whole slide digital microscopy images. To remain practical, the described method employs a two-step registration strategy designed to reduce computation time: the first step computes a B-spline deformable transform on low-resolution images prior to visualization, the second step applies the precomputed transformation only to the high-resolution region currently being viewed. The proposed method is demonstrated using a number of cases comprising H&E and IHC stained slides. These results indicate the feasibility of deformable registration for spatial alignment of multi-modal whole slide digital microscopy images within practical time constraints.

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

    PubMed Central

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

    2016-01-01

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

  9. 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.

  10. 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

  11. Efficient multi-modal dense field non-rigid registration: alignment of histological and section images.

    PubMed

    du Bois d'Aische, Aloys; Craene, Mathieu De; Geets, Xavier; Gregoire, Vincent; Macq, Benoit; Warfield, Simon K

    2005-12-01

    We describe a new algorithm for non-rigid registration capable of estimating a constrained dense displacement field from multi-modal image data. We applied this algorithm to capture non-rigid deformation between digital images of histological slides and digital flat-bed scanned images of cryotomed sections of the larynx, and carried out validation experiments to measure the effectiveness of the algorithm. The implementation was carried out by extending the open-source Insight ToolKit software. In diagnostic imaging of cancer of the larynx, imaging modalities sensitive to both anatomy (such as MRI and CT) and function (PET) are valuable. However, these modalities differ in their capability to discriminate the margins of tumor. Gold standard tumor margins can be obtained from histological images from cryotomed sections of the larynx. Unfortunately, the process of freezing, fixation, cryotoming and staining the tissue to create histological images introduces non-rigid deformations and significant contrast changes. We demonstrate that the non-rigid registration algorithm we present is able to capture these deformations and the algorithm allows us to align histological images with scanned images of the larynx. Our non-rigid registration algorithm constructs a deformation field to warp one image onto another. The algorithm measures image similarity using a mutual information similarity criterion, and avoids spurious deformations due to noise by constraining the estimated deformation field with a linear elastic regularization term. The finite element method is used to represent the deformation field, and our implementation enables us to assign inhomogeneous material characteristics so that hard regions resist internal deformation whereas soft regions are more pliant. A gradient descent optimization strategy is used and this has enabled rapid and accurate convergence to the desired estimate of the deformation field. A further acceleration in speed without cost of accuracy

  12. 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

  13. 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

  14. 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.

  15. 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

  16. 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).

  17. 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

  18. Multimodal Data Fusion Based on Mutual Information.

    PubMed

    Bramon, Roger; Boada, Imma; Bardera, Anton; Rodríguez, Joaquim; Feixas, Miquel; Puig, Josep; Sbert, Mateu

    2012-09-01

    Multimodal visualization aims at fusing different data sets so that the resulting combination provides more information and understanding to the user. To achieve this aim, we propose a new information-theoretic approach that automatically selects the most informative voxels from two volume data sets. Our fusion criteria are based on the information channel created between the two input data sets that permit us to quantify the information associated with each intensity value. This specific information is obtained from three different ways of decomposing the mutual information of the channel. In addition, an assessment criterion based on the information content of the fused data set can be used to analyze and modify the initial selection of the voxels by weighting the contribution of each data set to the final result. The proposed approach has been integrated in a general framework that allows for the exploration of volumetric data models and the interactive change of some parameters of the fused data set. The proposed approach has been evaluated on different medical data sets with very promising results.

  19. 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).

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

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-08-01

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

  2. 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

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

    PubMed

    Diaz, Idanis; Boulanger, Pierre

    2015-08-01

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

  4. 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....

  5. 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....

  6. 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....

  7. 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....

  8. 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....

  9. 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.

  10. Towards a noninvasive intracranial tumor irradiation using 3d optical imaging and multimodal data registration.

    PubMed

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

    2007-01-01

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

  11. 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.

  12. 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

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

    PubMed

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

    2013-07-21

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

  14. 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

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

    NASA Astrophysics Data System (ADS)

    Wang, Hairong; Cheng, Yuanfeng; Ma, Jianwei

    2014-05-01

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

  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.

  17. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  19. 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.

  20. 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.

  1. 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

  2. An automatic registration method based on runway detection

    NASA Astrophysics Data System (ADS)

    Zhang, Xiuqiong; Yu, Li; Huang, Guo

    2014-04-01

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

  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. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

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

    NASA Astrophysics Data System (ADS)

    Parra, Nestor A.; Parra, Carlos A.

    2007-03-01

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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Point-based rigid registration: clinical validation of theory

    NASA Astrophysics Data System (ADS)

    West, Jay B.; Fitzpatrick, J. Michael

    2000-06-01

    This paper presents the first comparison between theoretical estimates and clinically observed values for registration accuracy in point-based rigid-body registration. Rigid-body registration is appropriate for applications in which relatively rigid parts of the body are involved. In some such applications rigid-body registration is accomplished by aligning two sets of discrete points. In neurosurgical guidance, for example, the points are found by localizing the centroids of fiducial markers. We have previously provided two fundamental theoretical results on the relationship between localization error and registration error in rigid-body, point-based registration and have justified these results by showing them to be close to those given by numerical simulations. Rigid-body, point-based registration is accomplished by finding a rigid-body transformation that aligns pairs of homologous 'fiducial' points. The imprecision in locating a fiducial point is known as the 'fiducial localization error' (FLE). Fiducial points may be centroids of attached markers, which tend to have small, equal FLEs, or salient points in segmented anatomic features, whose FLEs tend to be larger and more varied. Alignment is achieved by minimizing the 'fiducial registration error' (FRE), which is the root mean square distance between homologous fiducials after registration. Closed form solutions for the rigid transformation that minimizes FRE have been known since 1966. A more critical and direct measure of registration error is the 'target registration error' (TRE), which is the distance between homologous points other than the centroids of fiducials. This error measure has been investigated by numerical simulation for many years, and we presented at this meeting in 1998 the first derivation of theoretical estimates of TRE. In that paper we showed that these estimates agree well with our simulations and those of others. We made the simplifying assumption in both the derivations and the

  15. 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

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

    PubMed Central

    Zyłkowski, Jaroslaw; Wróblewski, Tadeusz

    2013-01-01

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

  17. 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

  18. 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.

  19. Improved image registration by sparse patch-based deformation estimation.

    PubMed

    Kim, Minjeong; Wu, Guorong; Wang, Qian; Lee, Seong-Whan; Shen, Dinggang

    2015-01-15

    Despite 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 toward 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; and (4) we

  20. Multimode fiber laser beam cleanup based on stochastic parallel gradient descent algorithm

    NASA Astrophysics Data System (ADS)

    Zhao, Hai-Chuan; Ma, Hao-Tong; Zhou, Pu; Wang, Xiao-Lin; Ma, Yan-Xing; Li, Xiao; Xu, Xiao-Jun; Zhao, Yi-Jun

    2011-01-01

    We present experimental research on multimode fiber laser beam cleanup based on a stochastic parallel gradient descent (SPGD) algorithm. The multimode laser is obtained by injecting a 1064 nm central wavelength single mode fiber laser into a multimode fiber and the system is setup by using phase only liquid crystal spatial light modulators (LC-SLM). The quality evaluation function is increased by a factor of 10.5 and 65% of the laser energy is encircled in the central lobe when the system evolves from open-loop into close-loop state. Experimental results indicate the feasibility of the multimode fiber laser beam cleanup by adaptive optics (AO).

  1. Evaluation of the use of multimodality skin markers for the registration of pre-procedure cardiac MR images and intra-procedure x-ray fluoroscopy images for image guided cardiac electrophysiology procedures

    NASA Astrophysics Data System (ADS)

    Rhode, Kawal; Ma, Yingliang; Chandrasena, Angela; King, Andrew; Gao, Gang; Chinchapatnam, Phani; Sermesant, Maxime; Hawkes, David; Schaeffter, Tobias; Gill, Jaswinder; Razavi, Reza

    2008-03-01

    This paper presents the evaluation of the use of multimodality skin markers for the registration of cardiac magnetic resonance (MR) image data to x-ray fluoroscopy data for the guidance of cardiac electrophysiology procedures. The approach was validated using a phantom study and 3 patients undergoing pulmonary vein (PV) isolation for the treatment of paroxysmal atrial fibrillation. In the patient study, skin markers were affixed to the patients' chest and used to register pre-procedure cardiac MR image data to intra-procedure fluoroscopy data. Registration errors were assessed using contrast angiograms of the left atrium that were available in 2 out of 3 cases. A clinical expert generated "gold standard" registrations by adjusting the registration manually. Target registration errors (TREs) were computed using points on the PV ostia. Ablation locations were computed using biplane x-ray imaging. Registration errors were further assessed by computing the distances of the ablation points to the registered left atrial surface for all 3 patients. The TREs were 6.0 & 3.1mm for patients 1 & 2. The mean ablation point errors were 6.2, 3.8, & 3.0mm for patients 1, 2, & 3. These results are encouraging in the context of a 5mm clinical accuracy requirement for this type of procedure. We conclude that multimodality skin markers have the potential to provide anatomical image integration for x-ray guided cardiac electrophysiology procedures, especially if coupled with an accurate respiratory motion compensation strategy.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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

  8. Intensity-based image registration by minimizing residual complexity.

    PubMed

    Myronenko, Andriy; Song, Xubo

    2010-11-01

    Accurate definition of the similarity measure is a key component in image registration. Most commonly used intensity-based similarity measures rely on the assumptions of independence and stationarity of the intensities from pixel to pixel. Such measures cannot capture the complex interactions among the pixel intensities, and often result in less satisfactory registration performances, especially in the presence of spatially-varying intensity distortions. We propose a novel similarity measure that accounts for intensity nonstationarities and complex spatially-varying intensity distortions in mono-modal settings. We derive the similarity measure by analytically solving for the intensity correction field and its adaptive regularization. The final measure can be interpreted as one that favors a registration with minimum compression complexity of the residual image between the two registered images. One of the key advantages of the new similarity measure is its simplicity in terms of both computational complexity and implementation. This measure produces accurate registration results on both artificial and real-world problems that we have tested, and outperforms other state-of-the-art similarity measures in these cases.

  9. 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.

  10. 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

  11. 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

  12. Validation of histology image registration

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  13. 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.

  14. Content-Based Visual Landmark Search via Multimodal Hypergraph Learning.

    PubMed

    Zhu, Lei; Shen, Jialie; Jin, Hai; Zheng, Ran; Xie, Liang

    2015-12-01

    While content-based landmark image search has recently received a lot of attention and became a very active domain, it still remains a challenging problem. Among the various reasons, high diverse visual content is the most significant one. It is common that for the same landmark, images with a wide range of visual appearances can be found from different sources and different landmarks may share very similar sets of images. As a consequence, it is very hard to accurately estimate the similarities between the landmarks purely based on single type of visual feature. Moreover, the relationships between landmark images can be very complex and how to develop an effective modeling scheme to characterize the associations still remains an open question. Motivated by these concerns, we propose multimodal hypergraph (MMHG) to characterize the complex associations between landmark images. In MMHG, images are modeled as independent vertices and hyperedges contain several vertices corresponding to particular views. Multiple hypergraphs are firstly constructed independently based on different visual modalities to describe the hidden high-order relations from different aspects. Then, they are integrated together to involve discriminative information from heterogeneous sources. We also propose a novel content-based visual landmark search system based on MMHG to facilitate effective search. Distinguished from the existing approaches, we design a unified computational module to support query-specific combination weight learning. An extensive experiment study on a large-scale test collection demonstrates the effectiveness of our scheme over state-of-the-art approaches.

  15. 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

  16. 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…

  17. 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

  18. 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

  19. A registration based nonuniformity correction algorithm for infrared line scanner

    NASA Astrophysics Data System (ADS)

    Liu, Zhe; Ma, Yong; Huang, Jun; Fan, Fan; Ma, Jiayi

    2016-05-01

    A scene-based algorithm is developed for nonuniformity correction in focal plane of line scanning infrared imaging systems (LSIR) based on registration. By utilizing the 2D shift between consecutive frames, an implicit scheme is proposed to determine correction coefficients. All nonuniform biases are corrected to the same designated value, without estimating and removing biases explicitly, permitting quick computation for high-quality nonuniformity correction. Firstly, scene motion is estimated by image registration and consecutive frames exhibiting required 2D subpixel shift are collected. Secondly, we retrieve the difference matrix of adjacent biases by utilizing the 2D shift between consecutive frames. Thirdly, we perform specified elementary transformations and corresponding cumulative sums to the difference matrix to obtain a bias compensator. This bias compensator converts nonuniform biases to a designated detector's bias. Finally, based on the different bias compensators obtained from several frame pairs, we calculate an averaged bias compensator for nonuniformity correction with less error. Quantitative comparisons with other nonuniformity correction methods demonstrate that the proposed algorithm achieves better fixed-pattern noise reduction with low computational complexity.

  20. 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.

  1. Multiresolution parameterization of meshes for improved surface-based registration

    NASA Astrophysics Data System (ADS)

    Jaume, Sylvain; Ferrant, Matthieu; Warfield, Simon K.; Macq, Benoit M. M.

    2001-07-01

    Common problems in medical image analysis involve surface-based registration. The applications range from atlas matching to tracking an object's boundary in an image sequence, or segmenting anatomical structures out of images. Most proposed solutions are based on deformable surface algorithms. The main problem of such methods is that the local accuracy of the matching must often be traded off against global smoothness of the surface in order to reach global convergence of the deformation process. Our contribution is to first build a Multi-Resolution (M-R) surface from a reference segmented image, and then match this surface onto the target image in an M-R fashion using a deformable surface-like algorithm. As we proceed from lower to higher resolution, the smoothing effect of the deformable surface is more and more localized, and the surface gets closer and closer to the target boundary. We present initial results of our algorithm for atlas registration onto brain MRI showing improved convergence and accuracy over classical deformable surface methods.

  2. 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.

  3. Risk-Based Neuro-Grid Architecture for Multimodal Biometrics

    NASA Astrophysics Data System (ADS)

    Venkataraman, Sitalakshmi; Kulkarni, Siddhivinayak

    Recent research indicates that multimodal biometrics is the way forward for a highly reliable adoption of biometric identification systems in various applications, such as banks, businesses, government and even home environments. However, such systems would require large distributed datasets with multiple computational realms spanning organisational boundaries and individual privacies.

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

    SciTech Connect

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

    2006-01-01

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

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

    PubMed

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

    2010-12-01

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

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  8. 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).

  9. 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

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

    PubMed

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

    2010-08-01

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

  11. 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.

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

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

  14. 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%.

  15. 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.

  16. 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

  17. 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

  18. Mutual-information-based registration for ultrasound and CT datasets

    NASA Astrophysics Data System (ADS)

    Firle, Evelyn A.; Wesarg, Stefan; Dold, Christian

    2004-05-01

    In many applications for minimal invasive surgery the acquisition of intra-operative medical images is helpful if not absolutely necessary. Especially for Brachytherapy imaging is critically important to the safe delivery of the therapy. Modern computed tomography (CT) and magnetic resonance (MR) scanners allow minimal invasive procedures to be performed under direct imaging guidance. However, conventional scanners do not have real-time imaging capability and are expensive technologies requiring a special facility. Ultrasound (U/S) is a much cheaper and one of the most flexible imaging modalities. It can be moved to the application room as required and the physician sees what is happening as it occurs. Nevertheless it may be easier to interpret these 3D intra-operative U/S images if they are used in combination with less noisier preoperative data such as CT. The purpose of our current investigation is to develop a registration tool for automatically combining pre-operative CT volumes with intra-operatively acquired 3D U/S datasets. The applied alignment procedure is based on the information theoretic approach of maximizing the mutual information of two arbitrary datasets from different modalities. Since the CT datasets include a much bigger field of view we introduced a bounding box to narrow down the region of interest within the CT dataset. We conducted a phantom experiment using a CIRS Model 53 U/S Prostate Training Phantom to evaluate the feasibility and accuracy of the proposed method.

  19. 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.

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

    ERIC Educational Resources Information Center

    Jraidi, Imene; Frasson, Claude

    2013-01-01

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

  1. 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…

  2. 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.

  3. 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…

  4. 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.…

  5. 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…

  6. 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

  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. 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.

  9. Handheld laser scanner automatic registration based on random coding

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

  10. 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.

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

    PubMed

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

    2014-01-01

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

  12. 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…

  13. 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

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. Image-based registration of ultrasound and magnetic resonance images: a preliminary study

    NASA Astrophysics Data System (ADS)

    Pagoulatos, Niko; Haynor, David R.; Kim, Yongmin

    2000-04-01

    A number of surgical procedures are planned and executed based on medical images. Typically, x-ray computed tomography (CT) and magnetic resonance (MR) images are acquired preoperatively for diagnosis and surgical planning. In the operating room, execution of the surgical plan becomes feasible due to registration between preoperative images and surgical space where patient anatomy lies. In this paper, we present a new automatic algorithm where we use ultrasound (US) 2D B-mode images to register the preoperative MR image coordinate system with the surgical space which in our experiments is represented by the reference coordinate system of a DC magnetic position sensor. The position sensor is also used for tracking the position and orientation of the US images. Furthermore, we simulated patient anatomy by using custom-built phantoms. Our registration algorithm is a hybrid between fiducial- based and image-based registration algorithms. Initially, we perform a fiducial-based rigid-body registration between MR and position sensor space. Then, by changing various parameters of the rigid-body fiducial-based transformation, we produce an MR-sensor misregistration in order to simulate potential movements of the skin fiducials and/or the organs. The perturbed transformation serves as the initial estimate for the image-based registration algorithm, which uses normalized mutual information as a similarity measure, where one or more US images of the phantom are automatically matched with the MR image data set. By using the fiducial- based registration as the gold standard, we could compute the accuracy of the image-based registration algorithm in registering MR and sensor spaces. The registration error varied depending on the number of 2D US images used for registration. A good compromise between accuracy and computation time was the use of 3 US slices. In this case, the registration error had a mean value of 1.88 mm and standard deviation of 0.42 mm, whereas the required

  19. 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.

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

    PubMed

    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 the

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

    PubMed

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

    2016-07-01

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

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

    PubMed Central

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

    2016-01-01

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

  3. 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.

  4. 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

  5. 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

  6. 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

  7. Ensemble and Arithmetic Recombination-Based Speciation Differential Evolution for Multimodal Optimization.

    PubMed

    Hui, Sheldon; Suganthan, Ponnuthurai N

    2016-01-01

    Multimodal optimization problems consists of multiple equal or comparable spatially distributed solutions. Niching and clustering differential evolution (DE) techniques have been demonstrated to be highly effective for solving such problems. The key challenge in the speciation niching technique is to balance between local solution exploitation and global exploration. Our proposal enhances exploration by applying arithmetic recombination with speciation and improves exploitation of individual peaks by applying neighborhood mutation with ensemble strategies. Our novel algorithm, called ensemble and arithmetic recombination-based speciation DE, is shown to either outperform or perform comparably to the state-of-the-art algorithms on 29 common multimodal benchmark problems. Comparable performance is observed only when some problems are solved perfectly by the algorithms in the literature. PMID:25781971

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2002-12-01

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

  10. 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.

  11. 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.

  12. 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.

  13. A Multi-Modality CMOS Sensor Array for Cell-Based Assay and Drug Screening.

    PubMed

    Chi, Taiyun; Park, Jong Seok; Butts, Jessica C; Hookway, Tracy A; Su, Amy; Zhu, Chengjie; Styczynski, Mark P; McDevitt, Todd C; Wang, Hua

    2015-12-01

    In this paper, we present a fully integrated multi-modality CMOS cellular sensor array with four sensing modalities to characterize different cell physiological responses, including extracellular voltage recording, cellular impedance mapping, optical detection with shadow imaging and bioluminescence sensing, and thermal monitoring. The sensor array consists of nine parallel pixel groups and nine corresponding signal conditioning blocks. Each pixel group comprises one temperature sensor and 16 tri-modality sensor pixels, while each tri-modality sensor pixel can be independently configured for extracellular voltage recording, cellular impedance measurement (voltage excitation/current sensing), and optical detection. This sensor array supports multi-modality cellular sensing at the pixel level, which enables holistic cell characterization and joint-modality physiological monitoring on the same cellular sample with a pixel resolution of 80 μm × 100 μm. Comprehensive biological experiments with different living cell samples demonstrate the functionality and benefit of the proposed multi-modality sensing in cell-based assay and drug screening.

  14. 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.

  15. Image-based registration for two-dimensional and three-dimensional ultrasound imaging

    NASA Astrophysics Data System (ADS)

    Krucker, Jochen

    Image based registration techniques were developed, evaluated, and applied to 2D and 3D ultrasound (US) imaging in the context of deformation and aberration detection and correction. The specific applications demonstrated here include 3D compounding, generation of extended fields of view, and sound speed estimation. Despite the enormous clinical importance that diagnostic US has gained over more than four decades, and despite the fact that advances in software development and computer technology have made image registration a widely studied and moderately applied technique in other medical imaging modalities, US and image registration have rarely been combined in research or clinical application. We will show that not only can some image registration methods be transferred from other imaging modalities and adjusted to operate on US images, but also that registration can overcome or greatly ameliorate some of the existing limitations of US imaging. A nonlinear registration algorithm developed specifically for ultrasound showed registration accuracy of 0.2 mm in volumes with synthetic deformations, 0.3 mm in phantom experiments, and 0.6 mm in vivo. Extended high-resolution ultrasound volumes with lateral extents of over 10 cm were created by fusing together 3 or 4 individual volumes, using image registration in the areas of overlap. 3D compounding in the out-of-plane direction was achieved by registration of US volumes obtained from different look directions. Examples of compounding in phantoms and in vivo show increased contrast/noise and better visualization of specular reflectors. Image-based estimates of the average sound speed in the field of view were obtained using registration of steered 2D US images. The accuracy of the estimates was improved by including simulations of the sound field generated by the array. Evaluated over a range of sound speeds from 1490 to 1560 m/s in a custom-made phantom, the simulation results reduced the RMS deviation between the

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

    PubMed

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

    2016-02-01

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

  17. Concurrent tumor segmentation and registration with uncertainty-based sparse non-uniform graphs.

    PubMed

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

    2014-05-01

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

  18. 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.

  19. 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.

  20. 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.

  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. Analysis of Point Based Image Registration Errors With Applications in Single Molecule Microscopy

    PubMed Central

    Cohen, E. A. K.; Ober, R. J.

    2014-01-01

    We present an asymptotic treatment of errors involved in point-based image registration where control point (CP) localization is subject to heteroscedastic noise; a suitable model for image registration in fluorescence microscopy. Assuming an affine transform, CPs are used to solve a multivariate regression problem. With measurement errors existing for both sets of CPs this is an errors-in-variable problem and linear least squares is inappropriate; the correct method being generalized least squares. To allow for point dependent errors the equivalence of a generalized maximum likelihood and heteroscedastic generalized least squares model is achieved allowing previously published asymptotic results to be extended to image registration. For a particularly useful model of heteroscedastic noise where covariance matrices are scalar multiples of a known matrix (including the case where covariance matrices are multiples of the identity) we provide closed form solutions to estimators and derive their distribution. We consider the target registration error (TRE) and define a new measure called the localization registration error (LRE) believed to be useful, especially in microscopy registration experiments. Assuming Gaussianity of the CP localization errors, it is shown that the asymptotic distribution for the TRE and LRE are themselves Gaussian and the parameterized distributions are derived. Results are successfully applied to registration in single molecule microscopy to derive the key dependence of the TRE and LRE variance on the number of CPs and their associated photon counts. Simulations show asymptotic results are robust for low CP numbers and non-Gaussianity. The method presented here is shown to outperform GLS on real imaging data. PMID:24634573

  4. 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

  5. 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

  6. 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

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  11. 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.

  12. Widely tunable erbium-doped fiber laser based on multimode interference effect.

    PubMed

    Castillo-Guzman, A; Antonio-Lopez, J E; Selvas-Aguilar, R; May-Arrioja, D A; Estudillo-Ayala, J; LiKamWa, P

    2010-01-18

    A widely tunable erbium-doped all-fiber laser has been demonstrated. The tunable mechanism is based on a novel tunable filter using multimode interference effects (MMI). The tunable MMI filter was applied to fabricate a tunable erbium-doped fiber laser via a standard ring cavity. A tuning range of 60 nm was obtained, ranging from 1549 nm to 1609 nm, with a signal to noise ratio of 40 dB. The tunable MMI filter mechanism is very simple and inexpensive, but also quite efficient as a wavelength tunable filter.

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

    PubMed

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

    2011-01-01

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

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

    PubMed

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

    2011-01-01

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

  15. 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

  16. 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

  17. 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.

  18. 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

  19. 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.

  20. 75 FR 79320 - Security-Based Swap Data Repository Registration, Duties, and Core Principles

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-20

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

  1. 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...

  2. Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor

    PubMed Central

    Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

    2016-01-01

    Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation. PMID:27649190

  3. Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor.

    PubMed

    Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

    2016-01-01

    Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation. PMID:27649190

  4. Study on algorithm for night vision panoramic image basing on image segmentation and multimode displaying technology

    NASA Astrophysics Data System (ADS)

    Zhang, Zhenhai; Li, Kejie

    2009-07-01

    Based on single panoramic annular lens optical system and external-low-luminance CCD sensors, 360-degree panoramic night vision image processing hardware platform were established. The night vision panoramic image algorithm was presented, grounding on the image segmentation and multimode displaying technology. The annular image can be unwrapped and corrected to conventional rectangular panorama by the panoramic image unwrapping algorithm. The night vision image enhancement algorithm, based on adaptive piecewise linear gray transformation (APLGT) and Laplacian of Gaussian (LOG) edge detection, were given. APLGT algorithm can be adaptively truncate the image histogram on both ends to obtain a smaller dynamic range so as to enhance the contrast of the night vision image. LOG algorithm can be propitious to find and detect dim small targets in night vision circumstance. After abundant experiment, the algorithm for night vision panoramic image was successfully implemented in TMS320DM642, basing on the image Segmentation and multimode displaying algorithm. And the system can reliably and dynamically detect 360-degree view field of panoramic night vision image.

  5. Multimodal region-consistent saliency based on foreground and background priors for indoor scene

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Wang, Q.; Zhao, Y.; Chen, S. Y.

    2016-09-01

    Visual saliency is a very important feature for object detection in a complex scene. However, image-based saliency is influenced by clutter background and similar objects in indoor scenes, and pixel-based saliency cannot provide consistent saliency to a whole object. Therefore, in this paper, we propose a novel method that computes visual saliency maps from multimodal data obtained from indoor scenes, whilst keeping region consistency. Multimodal data from a scene are first obtained by an RGB+D camera. This scene is then segmented into over-segments by a self-adapting approach to combine its colour image and depth map. Based on these over-segments, we develop two cues as domain knowledge to improve the final saliency map, including focus regions obtained from colour images, and planar background structures obtained from point cloud data. Thus, our saliency map is generated by compounding the information of the colour data, the depth data and the point cloud data in a scene. In the experiments, we extensively compare the proposed method with state-of-the-art methods, and we also apply the proposed method to a real robot system to detect objects of interest. The experimental results show that the proposed method outperforms other methods in terms of precisions and recall rates.

  6. Seizure onset detection based on a Uni- or multi-modal intelligent seizure acquisition (UISA/MISA) system.

    PubMed

    Conradsen, Isa; Beniczky, Sandor; Wolf, Peter; Henriksen, Jonas; Sams, Thomas; Sorensen, Helge B D

    2010-01-01

    An automatic Uni- or Multi-modal Intelligent Seizure Acquisition (UISA/MISA) system is highly applicable for onset detection of epileptic seizures based on motion data. The modalities used are surface electromyography (sEMG), acceleration (ACC) and angular velocity (ANG). The new proposed automatic algorithm on motion data is extracting features as "log-sum" measures of discrete wavelet components. Classification into the two groups "seizure" versus "non-seizure" is made based on the support vector machine (SVM) algorithm. The algorithm performs with a sensitivity of 91-100%, a median latency of 1 second and a specificity of 100% on multi-modal data from five healthy subjects simulating seizures. The uni-modal algorithm based on sEMG data from the subjects and patients performs satisfactorily in some cases. As expected, our results clearly show superiority of the multi-modal approach, as compared with the uni-modal one. PMID:21096611

  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

    2010-11-01

    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

  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. 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

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

    PubMed

    Wachinger, Christian; Navab, Nassir

    2013-05-01

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

  11. 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.

  12. 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

  13. Genetic algorithms-based inversion of multimode guided waves for cortical bone characterization

    NASA Astrophysics Data System (ADS)

    Bochud, N.; Vallet, Q.; Bala, Y.; Follet, H.; Minonzio, J.-G.; Laugier, P.

    2016-10-01

    Recent progress in quantitative ultrasound has exploited the multimode waveguide response of long bones. Measurements of the guided modes, along with suitable waveguide modeling, have the potential to infer strength-related factors such as stiffness (mainly determined by cortical porosity) and cortical thickness. However, the development of such model-based approaches is challenging, in particular because of the multiparametric nature of the inverse problem. Current estimation methods in the bone field rely on a number of assumptions for pairing the incomplete experimental data with the theoretical guided modes (e.g. semi-automatic selection and classification of the data). The availability of an alternative inversion scheme that is user-independent is highly desirable. Thus, this paper introduces an efficient inversion method based on genetic algorithms using multimode guided waves, in which the mode-order is kept blind. Prior to its evaluation on bone, our proposal is validated using laboratory-controlled measurements on isotropic plates and bone-mimicking phantoms. The results show that the model parameters (i.e. cortical thickness and porosity) estimated from measurements on a few ex vivo human radii are in good agreement with the reference values derived from x-ray micro-computed tomography. Further, the cortical thickness estimated from in vivo measurements at the third from the distal end of the radius is in good agreement with the values delivered by site-matched high-resolution x-ray peripheral computed tomography.

  14. 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

  15. 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

  16. Highly Sensitive Liquid Core Temperature Sensor Based on Multimode Interference Effects.

    PubMed

    Fuentes-Fuentes, Miguel A; May-Arrioja, Daniel A; Guzman-Sepulveda, José R; Torres-Cisneros, Miguel; Sánchez-Mondragón, José J

    2015-10-23

    A novel fiber optic temperature sensor based on a liquid-core multimode interference device is demonstrated. The advantage of such structure is that the thermo-optic coefficient (TOC) of the liquid is at least one order of magnitude larger than that of silica and this, combined with the fact that the TOC of silica and the liquid have opposite signs, provides a liquid-core multimode fiber (MMF) highly sensitive to temperature. Since the refractive index of the liquid can be easily modified, this allows us to control the modal properties of the liquid-core MMF at will and the sensor sensitivity can be easily tuned by selecting the refractive index of the liquid in the core of the device. The maximum sensitivity measured in our experiments is 20 nm/°C in the low-temperature regime up to 60 °C. To the best of our knowledge, to date, this is the largest sensitivity reported for fiber-based MMI temperature sensors.

  17. 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.

  18. Evaluation of similarity measures for reconstruction-based registration in image-guided radiotherapy and surgery

    SciTech Connect

    Skerl, Darko . E-mail: franjo.pernus@fe.uni-lj.si; Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo

    2006-07-01

    Purpose: A promising patient positioning technique is based on registering computed tomographic (CT) or magnetic resonance (MR) images to cone-beam CT images (CBCT). The extra radiation dose delivered to the patient can be substantially reduced by using fewer projections. This approach results in lower quality CBCT images. The purpose of this study is to evaluate a number of similarity measures (SMs) suitable for registration of CT or MR images to low-quality CBCTs. Methods and Materials: Using the recently proposed evaluation protocol, we evaluated nine SMs with respect to pretreatment imaging modalities, number of two-dimensional (2D) images used for reconstruction, and number of reconstruction iterations. The image database consisted of 100 X-ray and corresponding CT and MR images of two vertebral columns. Results: Using a higher number of 2D projections or reconstruction iterations results in higher accuracy and slightly lower robustness. The similarity measures that behaved the best also yielded the best registration results. The most appropriate similarity measure was the asymmetric multi-feature mutual information (AMMI). Conclusions: The evaluation protocol proved to be a valuable tool for selecting the best similarity measure for the reconstruction-based registration. The results indicate that accurate and robust CT/CBCT or even MR/CBCT registrations are possible if the AMMI similarity measure is used.

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

    NASA Astrophysics Data System (ADS)

    Yue, Chunyu; Jiang, Wanshou

    2014-10-01

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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Evaluating a mobile location-based multimodal game for first-year students

    NASA Astrophysics Data System (ADS)

    Klante, Palle; Kroesche, Jens; Boll, Susanne C. J.

    2005-03-01

    We developed an exciting location-based, mobile game that allows first year students to explore the university campus in the fashion of a paper chase game. The players try to find virtual, geo-referenced riddles, located at different interesting spots. When approaching such a spot the corresponding multimedia riddle is displayed and the player tries to solve it. To support the player's orientation and navigation, we developed a multimodal user interface. On the one hand the checkpoints and current position are shown on a geo-referenced graphical map. Alternatively, a weakly intrusive auditory display tells the player by sounds of different loudness if he or she is walking in the right or wrong direction when looking for the way to the next checkpoint. We conducted a first usability evaluation with five teams of two players each. The process of the game, the interaction of the players with each other, and additional persons were observed and recorded; the players also answered a short questionnaire. The results are very promising: playing the game was fun, the players quickly got used to the game idea, and the multimodal user interface of the mobile device had been easily understood. The auditory support was considered helpful and a good complement for graphical visualisation.

  5. A statistics-based approach to binary image registration with uncertainty analysis.

    PubMed

    Simonson, Katherine M; Drescher, Steven M; Tanner, Franklin R

    2007-01-01

    A new technique is described for the registration of edge-detected images. While an extensive literature exists on the problem of image registration, few of the current approaches include a well-defined measure of the statistical confidence associated with the solution. Such a measure is essential for many autonomous applications, where registration solutions that are dubious (involving poorly focused images or terrain that is obscured by clouds) must be distinguished from those that are reliable (based on clear images of highly structured scenes). The technique developed herein utilizes straightforward edge pixel matching to determine the "best" among a class of candidate translations. A well-established statistical procedure, the McNemar test, is then applied to identify which other candidate solutions are not significantly worse than the best solution. This allows for the construction of confidence regions in the space of the registration parameters. The approach is validated through a simulation study and examples are provided of its application in numerous challenging scenarios. While the algorithm is limited to solving for two-dimensional translations, its use in validating solutions to higher-order (rigid body, affine) transformation problems is demonstrated.

  6. 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.

  7. Automated Feature Based Tls Data Registration for 3d Building Modeling

    NASA Astrophysics Data System (ADS)

    Kitamura, K.; Kochi, N.; Kaneko, S.

    2012-07-01

    In this paper we present a novel method for the registration of point cloud data obtained using terrestrial laser scanner (TLS). The final goal of our investigation is the automated reconstruction of CAD drawings and the 3D modeling of objects surveyed by TLS. Because objects are scanned from multiple positions, individual point cloud need to be registered to the same coordinate system. We propose in this paper an automated feature based registration procedure. Our proposed method does not require the definition of initial values or the placement of targets and is robust against noise and background elements. A feature extraction procedure is performed for each point cloud as pre-processing. The registration of the point clouds from different viewpoints is then performed by utilizing the extracted features. The feature extraction method which we had developed previously (Kitamura, 2010) is used: planes and edges are extracted from the point cloud. By utilizing these features, the amount of information to process is reduced and the efficiency of the whole registration procedure is increased. In this paper, we describe the proposed algorithm and, in order to demonstrate its effectiveness, we show the results obtained by using real data.

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

    PubMed

    Jin, Feng; Feng, Dazheng

    2014-01-01

    Feature detection and matching are crucial for robust and reliable image registration. Although many methods have been developed, they commonly focus on only one class of image features. The methods that combine two or more classes of features are still novel and significant. In this work, methods for feature detection and matching are proposed. A Mexican hat function-based operator is used for image feature detection, including the local area detection and the feature point detection. For the local area detection, we use the Mexican hat operator for image filtering, and then the zero-crossing points are extracted and merged into the area borders. For the feature point detection, the Mexican hat operator is performed in scale space to get the key points. After the feature detection, an image registration is achieved by using the two classes of image features. The feature points are grouped according to a standardized region that contains correspondence to the local area, precise registration is achieved eventually by the grouped points. An image transformation matrix is estimated by the feature points in a region and then the best one is chosen through competition of a set of the transformation matrices. This strategy has been named the Grouped Sample Consensus (GCS). The GCS has also ability for removing the outliers effectively. The experimental results show that the proposed algorithm has high registration accuracy and small computational volume. PMID:24752223

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

    PubMed

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

    2013-11-01

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

  10. Globally multimodal problem optimization via an estimation of distribution algorithm based on unsupervised learning of Bayesian networks.

    PubMed

    Peña, J M; Lozano, J A; Larrañaga, P

    2005-01-01

    Many optimization problems are what can be called globally multimodal, i.e., they present several global optima. Unfortunately, this is a major source of difficulties for most estimation of distribution algorithms, making their effectiveness and efficiency degrade, due to genetic drift. With the aim of overcoming these drawbacks for discrete globally multimodal problem optimization, this paper introduces and evaluates a new estimation of distribution algorithm based on unsupervised learning of Bayesian networks. We report the satisfactory results of our experiments with symmetrical binary optimization problems.

  11. MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck.

    PubMed

    Iacono, Maria Ida; Neufeld, Esra; Akinnagbe, Esther; Bower, Kelsey; Wolf, Johanna; Vogiatzis Oikonomidis, Ioannis; Sharma, Deepika; Lloyd, Bryn; Wilm, Bertram J; Wyss, Michael; Pruessmann, Klaas P; Jakab, Andras; Makris, Nikos; Cohen, Ethan D; Kuster, Niels; Kainz, Wolfgang; Angelone, Leonardo M

    2015-01-01

    Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1-2 mm and with 10-50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named "MIDA". The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community. PMID:25901747

  12. 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

  13. 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

  14. 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.

  15. 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

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

    PubMed Central

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

    2013-01-01

    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

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. 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

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

    PubMed

    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%.

  4. 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.

  5. 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.

  6. Registration of real and virtual endoscopy--a model and image based approach.

    PubMed

    Kukuk, M; Geiger, B

    2000-01-01

    This paper describes work in progress to integrate real and virtual endoscopy and to apply virtual endoscopy to the intra-operative guidance of endoscopic procedures. We propose a method for real-time tracking of the endoscope's shape and position. Our approach makes use of a simple and small external device, a computer model of a flexible endoscope and an image-based registration technique.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Population of 100 realistic, patient-based computerized breast phantoms for multi-modality imaging research

    NASA Astrophysics Data System (ADS)

    Segars, W. Paul; Veress, Alexander I.; Wells, Jered R.; Sturgeon, Gregory M.; Kiarashi, Nooshin; Lo, Joseph Y.; Samei, Ehsan; Dobbins, James T.

    2014-03-01

    Breast imaging is an important area of research with many new techniques being investigated to further reduce the morbidity and mortality of breast cancer through early detection. Computerized phantoms can provide an essential tool to quantitatively compare new imaging systems and techniques. Current phantoms, however, lack sufficient realism in depicting the complex 3D anatomy of the breast. In this work, we created one-hundred realistic and detailed 3D computational breast phantoms based on high-resolution CT datasets from normal patients. We also developed a finiteelement application to simulate different compression states of the breast, making the phantoms applicable to multimodality imaging research. The breast phantoms and tools developed in this work were packaged into user-friendly software applications to distribute for breast imaging research.

  13. 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

  14. Fiber Fabry-Perot tip sensor based on multimode photonic crystal fiber

    NASA Astrophysics Data System (ADS)

    Wu, Di; Huang, Yu; Fu, Jian-Yu; Wang, Guo-Yin

    2015-03-01

    We propose a novel Fabry-Perot interferometer (FPI) sensor for simultaneous measurement of refractive index (RI) and temperature based on Fresnel reflection and the thermo-optic effect of silica. The sensor head consists of a short section of multimode photonic crystal fiber (MPCF) and a conventional single mode fiber (SMF), where two thin films are formed by collapsing the air holes of MPCF with a commercialized fusion splicer. Experimental results show that such a device has a linear RI sensitivity of ~21.52 dB/RIU (RI unit) and a linear optical path difference (OPD) temperature sensitivity of ~25 nm/°C. In addition, a high RI resolution of about ~1.7×10-5 is obtained by using the Fourier transformation to decompose the spectral response in different spatial frequencies. Low-cost, easy fabrication and high resolution make it appropriate for practical applications.

  15. Multi-mode sliding mode control for precision linear stage based on fixed or floating stator.

    PubMed

    Fang, Jiwen; Long, Zhili; Wang, Michael Yu; Zhang, Lufan; Dai, Xufei

    2016-02-01

    This paper presents the control performance of a linear motion stage driven by Voice Coil Motor (VCM). Unlike the conventional VCM, the stator of this VCM is regulated, which means it can be adjusted as a floating-stator or fixed-stator. A Multi-Mode Sliding Mode Control (MMSMC), including a conventional Sliding Mode Control (SMC) and an Integral Sliding Mode Control (ISMC), is designed to control the linear motion stage. The control is switched between SMC and IMSC based on the error threshold. To eliminate the chattering, a smooth function is adopted instead of a signum function. The experimental results with the floating stator show that the positioning accuracy and tracking performance of the linear motion stage are improved with the MMSMC approach.

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

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

  17. A water-soluble temperature nanoprobe based on a multimodal magnetic-luminescent nanocolloid.

    PubMed

    Chen, Shu; Hoskins, Clare; Wang, Lijun; MacDonald, Michael P; André, Pascal

    2012-03-01

    This communication demonstrates that hybrid nanocolloids can be designed and used to create nanoprobes for remotely sensing the temperature of aqueous media. Such multi-modal nanocolloids combine development opportunities not only for multimodal magnetic-optical imaging but also for non-invasive and remote absolute temperature optical monitoring suitable for hyperthermia treatments and cell poration.

  18. Evaluation of Elekta 4D cone beam CT-based automatic image registration for radiation treatment of lung cancer

    PubMed Central

    Harrison, Amy; Yu, Yan; Xiao, Ying; Werner-Wasik, Maria; Lu, Bo

    2015-01-01

    Objective: The study was aimed to evaluate the precision of Elekta four-dimensional (4D) cone beam CT (CBCT)-based automatic dual-image registrations using different landmarks for clipbox for radiation treatment of lung cancer. Methods: 30 4D CBCT scans from 15 patients were studied. 4D CBCT images were registered with reference CT images using dual-image registration: a clipbox registration and a mask registration. The image registrations performed in clinic using a physician-defined clipbox, were reviewed by physicians, and were taken as the standard. Studies were conducted to evaluate the automatic dual registrations using three kinds of landmarks for clipbox: spine, spine plus internal target volume (ITV) and lung (including as much of the lung as possible). Translational table shifts calculated from the automatic registrations were compared with those of the standard. Results: The mean of the table shift differences in the lateral direction were 0.03, 0.03 and 0.03 cm, for clipboxes based on spine, spine plus ITV and lung, respectively. The mean of the shift differences in the longitudinal direction were 0.08, 0.08 and 0.08 cm, respectively. The mean of the shift differences in the vertical direction were 0.03, 0.03 and 0.03 cm, respectively. Conclusion: The automatic registrations using three different landmarks for clipbox showed similar results. One can use any of the three landmarks in 4D CBCT dual-image registration. Advance in knowledge: The study provides knowledge and recommendations for application of Elekta 4D CBCT image registration in radiation therapy of lung cancer. PMID:26183932

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

    PubMed

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

    2008-07-01

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

  20. 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.

  1. 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.

  2. Optical flow based deformable volume registration using a novel second-order regularization prior

    NASA Astrophysics Data System (ADS)

    Grbić, Saša; Urschler, Martin; Pock, Thomas; Bischof, Horst

    2010-03-01

    Nonlinear image registration is an initial step for a large number of medical image analysis applications. Optical flow based intensity registration is often used for dealing with intra-modality applications involving motion differences. In this work we present an energy functional which uses a novel, second-order regularization prior of the displacement field. Compared to other methods our scheme is robust to non-Gaussian noise and does not penalize locally affine deformation fields in homogeneous areas. We propose an efficient and stable numerical scheme to find the minimizer of the presented energy. We implemented our algorithm using modern consumer graphics processing units and thereby increased the execution performance dramatically. We further show experimental evaluations on clinical CT thorax data sets at different breathing states and on dynamic 4D CT cardiac data sets.

  3. Strain Rate Tensor Estimation in Cine Cardiac MRI Based on Elastic Image Registration

    NASA Astrophysics Data System (ADS)

    Sánchez-Ferrero, Gonzalo Vegas; Vega, Antonio Tristán; Grande, Lucilio Cordero; de La Higuera, Pablo Casaseca; Fernández, Santiago Aja; Fernández, Marcos Martín; López, Carlos Alberola

    In this work we propose an alternative method to estimate and visualize the Strain Rate Tensor (SRT) in Magnetic Resonance Images (MRI) when Phase Contrast MRI (PCMRI) and Tagged MRI (TMRI) are not available. This alternative is based on image processing techniques. Concretely, image registration algorithms are used to estimate the movement of the myocardium at each point. Additionally, a consistency checking method is presented to validate the accuracy of the estimates when no golden standard is available. Results prove that the consistency checking method provides an upper bound of the mean squared error of the estimate. Our experiments with real data show that the registration algorithm provides a useful deformation field to estimate the SRT fields. A classification between regional normal and dysfunctional contraction patterns, as compared with experts diagnosis, points out that the parameters extracted from the estimated SRT can represent these patterns. Additionally, a scheme for visualizing and analyzing the local behavior of the SRT field is presented.

  4. 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

  5. Scan-based volume animation driven by locally adaptive articulated registrations.

    PubMed

    Rhee, Taehyun; Lewis, J P; Neumann, Ulrich; Nayak, Krishna S

    2011-03-01

    This paper describes a complete system to create anatomically accurate example-based volume deformation and animation of articulated body regions, starting from multiple in vivo volume scans of a specific individual. In order to solve the correspondence problem across volume scans, a template volume is registered to each sample. The wide range of pose variations is first approximated by volume blend deformation (VBD), providing proper initialization of the articulated subject in different poses. A novel registration method is presented to efficiently reduce the computation cost while avoiding strong local minima inherent in complex articulated body volume registration. The algorithm highly constrains the degrees of freedom and search space involved in the nonlinear optimization, using hierarchical volume structures and locally constrained deformation based on the biharmonic clamped spline. Our registration step establishes a correspondence across scans, allowing a data-driven deformation approach in the volume domain. The results provide an occlusion-free person-specific 3D human body model, asymptotically accurate inner tissue deformations, and realistic volume animation of articulated movements driven by standard joint control estimated from the actual skeleton. Our approach also addresses the practical issues arising in using scans from living subjects. The robustness of our algorithms is tested by their applications on the hand, probably the most complex articulated region in the body, and the knee, a frequent subject area for medical imaging due to injuries.

  6. 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

  7. 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

  8. Hybrid point-and-intensity-based deformable registration for abdominal CT images

    NASA Astrophysics Data System (ADS)

    West, Jay B.; Maurer, Calvin R., Jr.; Dooley, John R.

    2005-04-01

    In this paper, we examine the problem of non-rigid, image-to-image registration for CT images of the abdomen. This problem has been previously addressed in many different contexts (e.g., visualization using different imaging modalities, modelling of organ deformation after surgical resection). The particular application in which we are interested is modelling of respiratory motion of abdominal organs, so that we may achieve a more accurate representation of the dose distribution in both targeted structures and non-targeted areas during radiosurgical treatment. Our goal is to register two CT images, each acquired at different positions in the respiratory cycle. We use a transformation model based on B-splines, and take advantage of B-splines' "locality" or "compact support" property to ensure computational efficiency and robust convergence to a satisfactory result. We demonstrate that, although a purely intensity-based registration metric performs well in matching the deformation of the lungs during the respiratory cycle, the movement of other organs (e.g., liver and kidney) is poorly represented due to the poor contrast within and between these organs in the CT images. We introduce a registration metric that is a weighted combination of intensity difference and distance between corresponding points that are manually identified in the two images being registered; we show how the influence of these points can be elegantly added to the metric so that it remains differentiable with respect to the spline control points. Visual inspection reveals that resulting registrations appear to be superior to the intensity-only ones in terms of representation of visceral organ deformation and movement.

  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. 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.

  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. 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.

  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. 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

  16. Multi-atlas segmentation of the cartilage in knee MR images with sequential volume- and bone-mask-based registrations

    NASA Astrophysics Data System (ADS)

    Lee, Han Sang; Kim, Hyeun A.; Kim, Hyeonjin; Hong, Helen; Yoon, Young Cheol; Kim, Junmo

    2016-03-01

    In spite of its clinical importance in diagnosis of osteoarthritis, segmentation of cartilage in knee MRI remains a challenging task due to its shape variability and low contrast with surrounding soft tissues and synovial fluid. In this paper, we propose a multi-atlas segmentation of cartilage in knee MRI with sequential atlas registrations and locallyweighted voting (LWV). First, bone is segmented by sequential volume- and object-based registrations and LWV. Second, to overcome the shape variability of cartilage, cartilage is segmented by bone-mask-based registration and LWV. In experiments, the proposed method improved the bone segmentation by reducing misclassified bone region, and enhanced the cartilage segmentation by preventing cartilage leakage into surrounding similar intensity region, with the help of sequential registrations and LWV.

  17. 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.

  18. 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.

  19. 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.

  20. Two-port multimode interference reflectors based on aluminium mirrors in a thick SOI platform.

    PubMed

    Fandiño, Javier S; Doménech, José David; Muñoz, Pascual

    2015-08-10

    Multimode interference reflectors (MIRs) were recently introduced as a new type of photonic integrated devices for on-chip, broadband light reflection. In the original proposal, different MIRs were demonstrated based on total internal reflection mirrors made of two deep-etched facets. Although simpler to fabricate, this approach imposes certain limits on the shape of the field pattern at the reflecting facets, which in turn restricts the types of MIRs that can be implemented. In this work, we propose and experimentally demonstrate the use of aluminium-based mirrors for the design of 2-port MIRs with variable reflectivity. These mirrors do not impose any restrictions on the incident field, and thus give more flexibility at the design stage. Devices with different reflectivities in the range between 0 and 0.5 were fabricated in a 3 um thick SOI platform, and characterization of multiple dies was performed to extract statistical data about their performance. Our measurements show that, on average, losses both in the aluminium mirror and in the access waveguides reduce the reflectivities to about 79% of their target value. Moreover, standard deviations lower than ±5% are obtained over a 20 nm wavelength range (1540-1560 nm). We also provide a theoretical model of the aluminium mirror based on the effective index method and Fresnel equations in multilayer thin films, which shows good agreement with FDTD simulations.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Strip-slot waveguide mode converter based on symmetric multimode interference.

    PubMed

    Deng, Qingzhong; Liu, Lu; Li, Xinbai; Zhou, Zhiping

    2014-10-01

    Optical mode mismatch makes coupling between strip and slot waveguides a tough issue in integrated photonics. This Letter presents both numerical and experimental results of a strip-slot mode converter based on symmetric multimode interference (MMI). Distinct from previous reported converters which gradually convert the mode through sharp tips, the proposed solution makes full use of the symmetry of the two-fold image of MMI, and its field distribution similarity with a slot waveguide to convert the mode. A converter based on this mechanism is able to convert light from a TE-polarized fundamental mode of a strip waveguide to that of a slot waveguide, and vice versa. Strip-slot waveguide coupling though this mode converter has a measured efficiency of 97% (-0.13  dB), and the dimensions are as small as 1.24×6  μm. Further analysis shows that the proposed converter is highly tolerant to fabrication imperfections, and is wavelength-insensitive.

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. Image-based device tracking for the co-registration of angiography and intravascular ultrasound images.

    PubMed

    Wang, Peng; Chen, Terrence; Ecabert, Olivier; Prummer, Simone; Ostermeier, Martin; Comaniciu, Dorin

    2011-01-01

    The accurate and robust tracking of catheters and transducers employed during image-guided coronary intervention is critical to improve the clinical workflow and procedure outcome. Image-based device detection and tracking methods are preferred due to the straightforward integration into existing medical equipments. In this paper, we present a novel computational framework for image-based device detection and tracking applied to the co-registration of angiography and intravascular ultrasound (IVUS), two modalities commonly used in interventional cardiology. The proposed system includes learning-based detections, model-based tracking, and registration using the geodesic distance. The system receives as input the selection of the coronary branch under investigation in a reference angiography image. During the subsequent pullback of the IVUS transducers, the system automatically tracks the position of the medical devices, including the IVUS transducers and guiding catheter tips, under fluoroscopy imaging. The localization of IVUS transducers and guiding catheter tips is used to continuously associate an IVUS imaging plane to the vessel branch under investigation. We validated the system on a set of 65 clinical cases, with high accuracy (mean errors less than 1.5mm) and robustness (98.46% success rate). To our knowledge, this is the first reported system able to automatically establish a robust correspondence between the angiography and IVUS images, thus providing clinicians with a comprehensive view of the coronaries.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Model-based registration of multi-rigid-body for augmented reality

    NASA Astrophysics Data System (ADS)

    Ikeda, Sei; Hori, Hajime; Imura, Masataka; Manabe, Yoshitsugu; Chihara, Kunihiro

    2009-02-01

    Geometric registration between a virtual object and the real space is the most basic problem in augmented reality. Model-based tracking methods allow us to estimate three-dimensional (3-D) position and orientation of a real object by using a textured 3-D model instead of visual marker. However, it is difficult to apply existing model-based tracking methods to the objects that have movable parts such as a display of a mobile phone, because these methods suppose a single, rigid-body model. In this research, we propose a novel model-based registration method for multi rigid-body objects. For each frame, the 3-D models of each rigid part of the object are first rendered according to estimated motion and transformation from the previous frame. Second, control points are determined by detecting the edges of the rendered image and sampling pixels on these edges. Motion and transformation are then simultaneously calculated from distances between the edges and the control points. The validity of the proposed method is demonstrated through experiments using synthetic videos.

  18. Spline-based image-to-volume registration for three-dimensional electron microscopy.

    PubMed

    Jonić, S; Sorzano, C O S; Thévenaz, P; El-Bez, C; De Carlo, S; Unser, M

    2005-07-01

    This paper presents an algorithm based on a continuous framework for a posteriori angular and translational assignment in three-dimensional electron microscopy (3DEM) of single particles. Our algorithm can be used advantageously to refine the assignment of standard quantized-parameter methods by registering the images to a reference 3D particle model. We achieve the registration by employing a gradient-based iterative minimization of a least-squares measure of dissimilarity between an image and a projection of the volume in the Fourier transform (FT) domain. We compute the FT of the projection using the central-slice theorem (CST). To compute the gradient accurately, we take advantage of a cubic B-spline model of the data in the frequency domain. To improve the robustness of the algorithm, we weight the cost function in the FT domain and apply a "mixed" strategy for the assignment based on the minimum value of the cost function at registration for several different initializations. We validate our algorithm in a fully controlled simulation environment. We show that the mixed strategy improves the assignment accuracy; on our data, the quality of the angular and translational assignment was better than 2 voxel (i.e., 6.54 angstroms). We also test the performance of our algorithm on real EM data. We conclude that our algorithm outperforms a standard projection-matching refinement in terms of both consistency of 3D reconstructions and speed. PMID:15885434

  19. 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

  20. 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.

  1. 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

  2. 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

  3. 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

  4. 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.

  5. A temperature sensor based on the splicing of a core offset multi-mode fiber with two single mode fiber

    NASA Astrophysics Data System (ADS)

    Fu, Xing-hu; Liu, Qin; Xiu, Yan-li; Xie, Hai-yang; Yang, Chuan-qing; Zhang, Shun-yang; Fu, Guang-wei; Bi, Wei-hong

    2015-11-01

    In this paper, a temperature sensor based on the splicing of a core offset multi-mode fiber with two single mode fibers is proposed and demonstrated experimentally. The temperature sensing principle is analyzed and related experiment is performed. By controlling the core offset and splicing length of the specialty multi-mode fiber (SMMF), two sensors with different temperature sensing properties are obtained, and experimental results show that the temperature sensitivity can be up to 48.76 pm/°C in the range of 25—95 °C. Moreover, it has many advantages, including small size, high sensitivity, and simple structure. So it can be used in potential temperature sensing applications, such as industrial production, biomedical science, power electronics, and so on.

  6. Dual Reaction-Based Multimodal Assay for Dopamine with High Sensitivity and Selectivity Using Functionalized Gold Nanoparticles.

    PubMed

    Zeng, Zhanghua; Cui, Bo; Wang, Yan; Sun, Changjiao; Zhao, Xiang; Cui, Haixin

    2015-08-01

    A simple and dual chemical reaction-based multimodal assay for dopamine with high sensitivity and selectivity using two types of functionalized gold nanoparticles (FB-AuNPs/NsNHS-AuNPs), i.e. fluorescein modified gold nanoparticles (FB-AuNPs) and Nile blue modified gold nanoparticles (NsNHS-AuNPs), was successfully fabricated. This assay for dopamine presents colorimetric visualization and double channel fluorescence enhancement at 515 and 665 nm. The absorbance and fluorescence changes were linearly proportional to the amounts of dopamine in the range of nanomolar scale (5-100 nM). The detection limits for absorbance and fluorescence were as low as 1.2 nM and 2.9 nM (S/N = 3), respectively. Furthermore, the extent application of this multimodal assay has been successfully demonstrated in human urine samples with high reliability and applicability, showing remarkable promise in diagnostic purposes.

  7. Visible-light optical coherence tomography-based multimodal retinal imaging for improvement of fluorescent intensity quantification

    PubMed Central

    Nafar, Zahra; Jiang, Minshan; Wen, Rong; Jiao, Shuliang

    2016-01-01

    We developed a spectral-domain visible-light optical coherence tomography (VIS-OCT) based multimodal imaging technique which can accomplish simultaneous OCT and fluorescence imaging with a single broadband light source. Phantom experiments showed that by using the simultaneously acquired OCT images as a reference, the effect of light attenuation on the intensity of the fluorescent images by materials in front of the fluorescent target can be compensated. This capability of the multimodal imaging technique is of high importance for achieving quantification of the true intensities of autofluorescence (AF) imaging of the retina. We applied the technique in retinal imaging including AF imaging of the retinal pigment epithelium and fluorescein angiography (FA). We successfully demonstrated the effect of compensation on AF and FA images with the simultaneously acquired VIS-OCT images. PMID:27699094

  8. Visible-light optical coherence tomography-based multimodal retinal imaging for improvement of fluorescent intensity quantification

    PubMed Central

    Nafar, Zahra; Jiang, Minshan; Wen, Rong; Jiao, Shuliang

    2016-01-01

    We developed a spectral-domain visible-light optical coherence tomography (VIS-OCT) based multimodal imaging technique which can accomplish simultaneous OCT and fluorescence imaging with a single broadband light source. Phantom experiments showed that by using the simultaneously acquired OCT images as a reference, the effect of light attenuation on the intensity of the fluorescent images by materials in front of the fluorescent target can be compensated. This capability of the multimodal imaging technique is of high importance for achieving quantification of the true intensities of autofluorescence (AF) imaging of the retina. We applied the technique in retinal imaging including AF imaging of the retinal pigment epithelium and fluorescein angiography (FA). We successfully demonstrated the effect of compensation on AF and FA images with the simultaneously acquired VIS-OCT images.

  9. 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.

  10. 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 .

  11. 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.

  12. Simultaneous registration of structural and diffusion weighed images using the full DTI information

    NASA Astrophysics Data System (ADS)

    Nadeau, Hélène; Chai, Yaqiong; Thompson, Paul; Leporé, Natasha

    2015-01-01

    Banks of high-quality, multimodal neurological images offer new possibilities for analyses based on brain registration. To take full advantage of these, current algorithms should be significantly enhanced. We present here a new brain registration method driven simultaneously by the structural intensity and the total diffusion information of MRI scans. Using the two modalities together allows for a better alignment of general and specific aspects of the anatomy. Furthermore, keeping the full diffusion tensor in the cost function, rather than only some of its scalar measures, will allow for a thorough statistical analysis once the Jacobian of the transformation is obtained.

  13. 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

  14. PetroSPIRE: a multimodal content-based retrieval system for petroleum applications

    NASA Astrophysics Data System (ADS)

    Bergman, Lawrence D.; Castelli, Vittorio; Li, Chung-Sheng; Tilke, Peter; Bryant, Ian

    1999-08-01

    In this paper we present a novel content-based search application for petroleum exploration and production. The target application is specification of and search for geologically significant features to be extracted from 2D imagery acquired from oil well bores, in conjunction with 1D parameter traces. The PetroSPIRE system permits a user to define rock strata using image examples in conjunction with parameter constraints. Similarity retrieval is based multimodal search, an relies on texture-matching techniques using pre-extracted texture features, employing high- dimensional indexing and nearest neighbor search. Special- purpose visualization techniques allow a user to evalute object definitions, which can then be iteratively refined by supplying multiple positive and negative image examples as well as multiple parameter constraints. Higher-level semantic constructs can be created from simpler entities by specifying sets of inter-object constraints. A delta-lobe riverbed, for examples, might be specified as layer of siltstone which is above and within 10 feet of a layer of sandstone, with an intervening layer of shale. These 'compound objects', along with simple objects, from a library of searchable entities that can be used in an operational setting. Both object definition and search are accomplished using a web-based Java client, supporting image and parameter browsing, drag-and-drop query specification, and thumbnail viewing of query results. Initial results from this search engine have been deemed encouraging by oil- industry E and P researchers. A more ambitious pilot is underway to evaluate the efficacy of this approach on a large database from a North Sea drilling site.

  15. Appearance-based multimodal human tracking and identification for healthcare in the digital home.

    PubMed

    Yang, Mau-Tsuen; Huang, Shen-Yen

    2014-08-05

    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.

  16. 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

  17. 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

  18. 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

  19. Multimode fiber laser for simultaneous measurement of strain and temperature based on beat frequency demodulation.

    PubMed

    Gao, Liang; Chen, Lin; Huang, Long; Chen, Xiangfei

    2012-09-24

    A multimode fiber laser sensor system for simultaneous measurement of strain and temperature is proposed and demonstrated. Because of the long cavity and birefringence, longitudinal mode beat frequency and polarization mode beat frequency are achieved in the beat frequency signals of the multimode fiber laser. The strain and temperature can be obtained by monitoring both of them for their different strain and temperature responses. The experimental measurement errors are within ± 16.2 με and ± 1.9 °C. The usage of only one fiber laser and one demodulation system makes the system simple, cost-effective and portable.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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…

  9. 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.

  10. 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…

  11. 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…

  12. Agile multi-scale decompositions for automatic image registration

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  13. Multi-feature-based plaque characterization in ex vivo MRI trained by registration to 3D histology

    NASA Astrophysics Data System (ADS)

    van Engelen, Arna; Niessen, Wiro J.; Klein, Stefan; Groen, Harald C.; Verhagen, Hence JM; Wentzel, Jolanda J.; van der Lugt, Aad; de Bruijne, Marleen

    2012-01-01

    We present a new method for automated characterization of atherosclerotic plaque composition in ex vivo MRI. It uses MRI intensities as well as four other types of features: smoothed, gradient magnitude and Laplacian images at several scales, and the distances to the lumen and outer vessel wall. The ground truth for fibrous, necrotic and calcified tissue was provided by histology and μCT in 12 carotid plaque specimens. Semi-automatic registration of a 3D stack of histological slices and μCT images to MRI allowed for 3D rotations and in-plane deformations of histology. By basing voxelwise classification on different combinations of features, we evaluated their relative importance. To establish whether training by 3D registration yields different results than training by 2D registration, we determined plaque composition using (1) a 2D slice-based registration approach for three manually selected MRI and histology slices per specimen, and (2) an approach that uses only the three corresponding MRI slices from the 3D-registered volumes. Voxelwise classification accuracy was best when all features were used (73.3 ± 6.3%) and was significantly better than when only original intensities and distance features were used (Friedman, p < 0.05). Although 2D registration or selection of three slices from the 3D set slightly decreased accuracy, these differences were non-significant.

  14. 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.

  15. 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

  16. 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.

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

    PubMed

    Lee, Joohwi; Lyu, Ilwoo; Styner, Martin

    2014-03-21

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

  18. Fiber-optic Fabry-Perot sensor based on graded-index multimode fiber: numerical simulations and experiments

    NASA Astrophysics Data System (ADS)

    Gong, Yuan; Zhao, Tian; Rao, Yun-Jiang; Wu, Yu; Guo, Yu

    2011-05-01

    Numerical simulations based on the ray-transfer-matrix (RTM) method is realized for explaining the principle of a graded-index multimode fiber (GI-MMF) based hybrid fiber Fabry-Perot (GI-FFP) sensor. It is verified by the numerical simulations and experimental results that the high fringe contrast of the reflective spectrum of the sensor is due to the periodic focusing effect of the GI-MMF. Experimental results are in good agreement with the theory. A typical GI-FFP sensor is fabricated and its response to the external refractive index is measured with a maximum sensitivity of ~160 dB/RIU.

  19. 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

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

    PubMed

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

    1998-10-01

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

  1. Nanoengineered multimodal contrast agent for medical image guidance

    NASA Astrophysics Data System (ADS)

    Perkins, Gregory J.; Zheng, Jinzi; Brock, Kristy; Allen, Christine; Jaffray, David A.

    2005-04-01

    Multimodality imaging has gained momentum in radiation therapy planning and image-guided treatment delivery. Specifically, computed tomography (CT) and magnetic resonance (MR) imaging are two complementary imaging modalities often utilized in radiation therapy for visualization of anatomical structures for tumour delineation and accurate registration of image data sets for volumetric dose calculation. The development of a multimodal contrast agent for CT and MR with prolonged in vivo residence time would provide long-lasting spatial and temporal correspondence of the anatomical features of interest, and therefore facilitate multimodal image registration, treatment planning and delivery. The multimodal contrast agent investigated consists of nano-sized stealth liposomes encapsulating conventional iodine and gadolinium-based contrast agents. The average loading achieved was 33.5 +/- 7.1 mg/mL of iodine for iohexol and 9.8 +/- 2.0 mg/mL of gadolinium for gadoteridol. The average liposome diameter was 46.2 +/- 13.5 nm. The system was found to be stable in physiological buffer over a 15-day period, releasing 11.9 +/- 1.1% and 11.2 +/- 0.9% of the total amounts of iohexol and gadoteridol loaded, respectively. 200 minutes following in vivo administration, the contrast agent maintained a relative contrast enhancement of 81.4 +/- 13.05 differential Hounsfield units (ΔHU) in CT (40% decrease from the peak signal value achieved 3 minutes post-injection) and 731.9 +/- 144.2 differential signal intensity (ΔSI) in MR (46% decrease from the peak signal value achieved 3 minutes post-injection) in the blood (aorta), a relative contrast enhancement of 38.0 +/- 5.1 ΔHU (42% decrease from the peak signal value achieved 3 minutes post-injection) and 178.6 +/- 41.4 ΔSI (62% decrease from the peak signal value achieved 3 minutes post-injection) in the liver (parenchyma), a relative contrast enhancement of 9.1 +/- 1.7 ΔHU (94% decrease from the peak signal value achieved 3 minutes

  2. Feasibility of a novel deformable image registration technique to facilitate classification, targeting, and monitoring of tumor and normal tissue

    SciTech Connect

    Brock, Kristy K. . E-mail: kristy.brock@rmp.uhn.on.ca; Dawson, Laura A.; Sharpe, Michael B.; Moseley, Douglas J.; Jaffray, David A.

    2006-03-15

    Purpose: To investigate the feasibility of a biomechanical-based deformable image registration technique for the integration of multimodality imaging, image guided treatment, and response monitoring. Methods and Materials: A multiorgan deformable image registration technique based on finite element modeling (FEM) and surface projection alignment of selected regions of interest with biomechanical material and interface models has been developed. FEM also provides an inherent method for direct tracking specified regions through treatment and follow-up. Results: The technique was demonstrated on 5 liver cancer patients. Differences of up to 1 cm of motion were seen between the diaphragm and the tumor center of mass after deformable image registration of exhale and inhale CT scans. Spatial differences of 5 mm or more were observed for up to 86% of the surface of the defined tumor after deformable image registration of the computed tomography (CT) and magnetic resonance images. Up to 6.8 mm of motion was observed for the tumor after deformable image registration of the CT and cone-beam CT scan after rigid registration of the liver. Deformable registration of the CT to the follow-up CT allowed a more accurate assessment of tumor response. Conclusions: This biomechanical-based deformable image registration technique incorporates classification, targeting, and monitoring of tumor and normal tissue using one methodology.

  3. 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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  6. 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.

  7. 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.

  8. 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)

  9. 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.

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

    PubMed Central

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

    2013-01-01

    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 10 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. PMID:22971564

  11. 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

  12. 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…

  13. 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

  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. Femtosecond laser fabricated multimode fiber sensors interrogated by optical-carrier-based microwave interferometry technique for distributed strain sensing

    NASA Astrophysics Data System (ADS)

    Hua, Liwei; Song, Yang; Huang, Jie; Cheng, Baokai; Zhu, Wenge; Xiao, Hai

    2016-03-01

    A multimode fiber (MMF) based cascaded intrinsic Fabry-Perot interferometers (IFPIs) system is presented and the distributed strain sensing has been experimentally demonstrated by using such system. The proposed 13 cascaded IFPIs have been formed by 14 cascaded reflectors that have been fabricated on a grade index MMF. Each reflector has been made by drawing a line on the center of the cross-section of the MMF through a femtosecond laser. The distance between any two adjacent reflectors is around 100 cm. The optical carrier based microwave interferometry (OCMI) technique has been used to interrogate the MMF based cascaded FPIs system by reading the optical interference information in the microwave domain. The location along with the shift of the interference fringe pattern for each FPI can be resolved though signal processing based on the microwave domain information. The multimode interference showed very little influence to the microwave domain signals. By using such system the strain of 10-4 for each FPI sensor and the spatial resolution of less than 5 cm for the system can be easily achieved.

  17. Mode converter based on an inverse taper for multimode silicon nanophotonic integrated circuits.

    PubMed

    Dai, Daoxin; Mao, Mao

    2015-11-01

    An inverse taper on silicon is proposed and designed to realize an efficient mode converter available for the connection between multimode silicon nanophotonic integrated circuits and few-mode fibers. The present mode converter has a silicon-on-insulator inverse taper buried in a 3 × 3μm(2) SiN strip waveguide to deal with not only for the fundamental mode but also for the higher-order modes. The designed inverse taper enables the conversion between the six modes (i.e., TE(11), TE(21), TE(31), TE(41), TM(11), TM(12)) in a 1.4 × 0.22μm(2) multimode SOI waveguide and the six modes (like the LP(01), LP(11a), LP(11b) modes in a few-mode fiber) in a 3 × 3μm(2) SiN strip waveguide. The conversion efficiency for any desired mode is higher than 95.6% while any undesired mode excitation ratio is lower than 0.5%. This is helpful to make multimode silicon nanophotonic integrated circuits (e.g., the on-chip mode (de)multiplexers developed well) available to work together with few-mode fibers in the future.

  18. Mode converter based on an inverse taper for multimode silicon nanophotonic integrated circuits.

    PubMed

    Dai, Daoxin; Mao, Mao

    2015-11-01

    An inverse taper on silicon is proposed and designed to realize an efficient mode converter available for the connection between multimode silicon nanophotonic integrated circuits and few-mode fibers. The present mode converter has a silicon-on-insulator inverse taper buried in a 3 × 3μm(2) SiN strip waveguide to deal with not only for the fundamental mode but also for the higher-order modes. The designed inverse taper enables the conversion between the six modes (i.e., TE(11), TE(21), TE(31), TE(41), TM(11), TM(12)) in a 1.4 × 0.22μm(2) multimode SOI waveguide and the six modes (like the LP(01), LP(11a), LP(11b) modes in a few-mode fiber) in a 3 × 3μm(2) SiN strip waveguide. The conversion efficiency for any desired mode is higher than 95.6% while any undesired mode excitation ratio is lower than 0.5%. This is helpful to make multimode silicon nanophotonic integrated circuits (e.g., the on-chip mode (de)multiplexers developed well) available to work together with few-mode fibers in the future. PMID:26561108

  19. 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

  20. 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

  1. 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

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

    PubMed

    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

  3. 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

  4. 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.

  5. 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.

  6. 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes.

    PubMed

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

    2016-01-01

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

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

  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.

  14. PACS and multimodality in medical imaging.

    PubMed

    D'Asseler, Y; Koole, M; Van Laere, K; Vandenberghe, S; Bouwens, L; Van de Walle, R; Van de Wiele, C; Lemahieu, I; Dierckx, R A

    2000-01-01

    A PACS (Picture Archiving and Communication System) is a system that is able to store, exchange, display and manipulate images and associated diagnoses from any modality within a hospital in a timely and cost-effective way. Several developments, such as the DICOM standard, fast and convenient networking, and new storage solutions for large amounts of data, make the setup of such a PACS system possible. As the information acquired with various imaging modalities is then available and often complementary, it is desirable for the clinician to have a point-by-point spatial co-registration of images from different modalities in order to enable a synergistic use of the multimodality imaging of a patient for increased diagnostic accuracy. Various types of algorithms are available for the matching of medical images from the same or from different modalities. Co-registration algorithms based on voxel properties consist of a similarity or dissimilarity measure and an iterative or non-iterative method minimizing the dissimilarity or maximizing the similarity between the two images by a transformation of one image relative to the other. PMID:10942990

  15. Establishing an internet-based paediatric cancer registration and communication system for the Hungarian paediatric oncology network.

    PubMed

    Borgulya, Gábor; Jakab, Zsuzsanna; Schuler, Dezso; Garami, Miklós

    2004-01-01

    Cancer registration has developed in Europe over the last 50 years, and in the last decade intensive joint activities between the European Cancer Registries, in response to the need of pan-European harmonization of registration practices, have taken place. The Hungarian Paediatric Cancer Registry has been functioning as the database of the Hungarian Paediatric Oncology Network since 1971, aiming to follow the incidence and the treatment efficacy of malignant diseases. The goals of this globally unique open source information system are the following: 1) to raise the quality of the registration system to the European level by developing an Internet-based registration and communication system, modernizing the database, establishing automatic statistical analyses and adding an Internet website, 2) to support clinical epidemiological studies that we conduct with international collaborators on detailed analyses of the characteristics of patients and their diseases, evaluation of new diagnostic and therapeutic methods, prevention programs, and long-term quality of life and side effects. The benefits of the development of the Internet-based registration and communication system are as follows: a) introduction of an Internet-based case reporting system, b) modernization of the registry database according to international recommendations, c) automatic statistical summaries, encrypted mail systems, document repository, d) application of data security and privacy standards, e) establishment of a website and compilation of educational materials. The overall objective of this scientific project is to contribute towards the improvement of cancer prevention and cancer care for the benefit of the public in general and of cancer patients in particular. PMID:15718593

  16. Navigation systems based on registration of endoscopic and CT-derived virtual images for bronchofiberoscopic procedures.

    PubMed

    Turcza, Paweł; Duplaga, Mariusz

    2004-01-01

    Bronchofiberoscopy is an essential diagnostic procedure in patients with lung cancer. Sampling methods employed during endoscopy of the respiratory tract are performed with the aim of diagnosis confirmation and staging. Transbronchial needle aspiration may be used for evaluation of lymph nodes neighbouring with trachea and bronchi. Many efforts have been undertaken to increase the sensitivity of this procedure including the application of endobronchial ultrasonography. In recent years several research groups have proposed models of navigating systems to provide computer assistance during bronchoscopic interventions. Although they have used different techniques, their objective was the same - enabling tracking location and movement of bronchofiberoscope tip with reference to previously-acquired computed tomography (CT) images. Since a fiber-optic bronchoscope is a rather long and flexible device, determination of its tip location is not an easy task. The adoption of optical tracking methods used in neurosurgery or laparoscopic surgery to endoscopy of the tracheobronchial tree is usually not possible. Another obstacle is related to the fact that bronchofiberoscopes usually have only one operational channel. This feature considerably limits the feasibility of navigation systems based on the use of small electromagnetic sensing devices or USG probes. The sources of positioning errors in such systems are respiratory movements and the lack of external referential coordinate system associated with the tracheobronchial tree.A promising option for development of a bronchoscopic guidance system is the application of image registration algorithms. Such an approach encompasses registration of endoscopic images to views derived from advanced imaging methods, e.g. CT. In the first step, reconstruction of a three-dimensional, endoluminal views is performed. Next, the position of the virtual camera in a CT-derived virtual model is determined using a complex multi-level image

  17. 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

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  20. 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

  1. 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

  2. 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.

  3. Demodulation of fiber bragg grating sensors based on dynamic tuning of a multimode laser diode.

    PubMed

    Ferreira, L A; Diatzikis, E V; Santos, J L; Farahi, F

    1999-08-01

    Dither demodulation of fiber Bragg grating sensors illuminated with multimode light from laser diodes is theoretically and experimentally investigated. Quasi-static temperature and strain sensitivities of 0.09 degrees C/ radical Hz and 0.6 microepsilon/ radical Hz are obtained. We show that it is possible to measure small ac signals that lie outside the feedback loop bandwidth by using a synchronous detection referenced to twice the dither frequency. In this situation, dynamic strain sensitivity of 3.3 n(epsilon)/ radical Hz is achieved. PMID:18323963

  4. 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.

  5. 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

  6. 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).

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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.

  14. 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

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

    PubMed

    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

  16. 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.

  17. 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.

  18. Multimodal voxel-based meta-analysis of white matter abnormalities in obsessive-compulsive disorder.

    PubMed

    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

    2014-06-01

    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.

  19. Inorganic Nanoparticles for Multimodal Molecular Imaging

    PubMed Central

    Swierczewska, Magdalena; Lee, Seulki; Chen, Xiaoyuan

    2013-01-01

    Multimodal molecular imaging can offer a synergistic improvement of diagnostic ability over a single imaging modality. Recent development of hybrid imaging systems has profoundly impacted the pool of available multimodal imaging probes. In particular, much interest has been focused on biocompatible, inorganic nanoparticle–based multimodal probes. Inorganic nanoparticles offer exceptional advantages to the field of multimodal imaging owing to their unique characteristics, such as nanometer dimensions, tunable imaging properties, and multifunctionality. Nanoparticles mainly based on iron oxide, quantum dots, gold, and silica have been applied to various imaging modalities to characterize and image specific biologic processes on a molecular level. A combination of nanoparticles and other materials such as biomolecules, polymers, and radiometals continue to increase functionality for in vivo multimodal imaging and therapeutic agents. In this review, we discuss the unique concepts, characteristics, and applications of the various multimodal imaging probes based on inorganic nanoparticles. PMID:21303611

  20. 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

  1. Efficient generation of sum-of-products representations of high-dimensional potential energy surfaces based on multimode expansions.

    PubMed

    Ziegler, Benjamin; Rauhut, Guntram

    2016-03-21

    The transformation of multi-dimensional potential energy surfaces (PESs) from a grid-based multimode representation to an analytical one is a standard procedure in quantum chemical programs. Within the framework of linear least squares fitting, a simple and highly efficient algorithm is presented, which relies on a direct product representation of the PES and a repeated use of Kronecker products. It shows the same scalings in computational cost and memory requirements as the potfit approach. In comparison to customary linear least squares fitting algorithms, this corresponds to a speed-up and memory saving by several orders of magnitude. Different fitting bases are tested, namely, polynomials, B-splines, and distributed Gaussians. Benchmark calculations are provided for the PESs of a set of small molecules.

  2. Child abuse registration, fetal growth, and preterm birth: a population based study

    PubMed Central

    Spencer, Nick; Wallace, Ann; Sundrum, Ratna; Bacchus, Claire; Logan, Stuart

    2006-01-01

    Objectives To study the relation of intra‐uterine growth and gestational age with child protection registration in a 20 year whole population birth cohort. Setting West Sussex area of England. Study design Retrospective whole population birth cohort. Outcomes Child protection registration; individual categories of registration—sexual abuse, physical abuse, emotional abuse, and neglect. Population and participants 119 771 infants born in West Sussex between January 1983 and December 2001 with complete data including birth weight, gestational age, maternal age, and postcode. Results In all categories of registration a linear trend was noted such that the lower the birth weight z score the higher the likelihood of child protection registration. Similar trends were noted for gestational age. All these trends were robust to adjustment for maternal age and socioeconomic status. Conclusions The results of this study suggest that lower levels of fetal growth and shorter gestational duration are associated with increased likelihood of child protection registration in all categories including sexual abuse independent of maternal age or socioeconomic status. This study does not permit comment on whether poor fetal growth or preterm birth predispose to child abuse and neglect or the association arises because they share a common pathway. PMID:16537351

  3. 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.

  4. 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.

  5. 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

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

    PubMed

    Michalek, Jan; Capek, Martin

    2013-05-01

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

  9. 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.

  10. Decoherence of multimode thermal squeezed coherent states

    SciTech Connect

    Yeh, L.

    1992-08-14

    It is well known that any multimode positive definite quadratic Hamiltonian can be transformed into a hamiltonian of uncoupled harmonic oscillators. Based on this theorem, the multimode thermal squeezed coherent states are constructed in terms of density operators. Decoherence of multimode thermal squeezed coherent states in investigated via the characteristic function and it is shown that the decohered (reduced) states are still thermal squeezed coherent states in general.

  11. Decoherence of multimode thermal squeezed coherent states

    NASA Technical Reports Server (NTRS)

    Yeh, Leehwa

    1993-01-01

    It is well known that any multimode positive definite quadratic Hamiltonian can be transformed into a Hamiltonian of uncoupled harmonic oscillators. Based on this theorem, the multimode thermal squeezed coherent states are constructed in terms of density operators. Decoherence of multimode thermal squeezed coherent states is investigated via the characteristic function and it is shown that the decohered (reduced) states are still thermal squeezed coherent states in general.

  12. Widely tunable and ultrasensitive leaky-guided multimode fiber interferometer based on refractive-index-matched coupling.

    PubMed

    Lee, Cheng-Ling; Lin, Kuo-Hsiang; Lin, Yuanyao; Hsu, Jui-Ming

    2012-02-01

    This investigation presents a simple, widely tunable, and ultrasensitive sensor that is based on a leaky-guided multimode fiber interferometer (MMFI) operated under refractive-index-matched coupling. By use of a material with an appropriate dispersion profile around the MMFI as a cladding yields strong index-matched coupling, which performs ultrasensitive sensing in variations of the surroundings. Index matching at a single wavelength yields a coupling wavelength dip with a narrow bandwidth and a high extinction ratio of over 25 dB. The wavelength dip can also be effectively tuned, greatly shifting with a variation in temperature (T) or refractive index (RI), when the index-matched condition is satisfied. This work demonstrates that the proposed sensor responds sensitively to T with an extremely high tuning efficiency of 50 nm/°C and an excellent sensitivity to RI of 113,500 nm per RI unit.

  13. 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.

  14. The processes of registration seismic wave, using laser microinterferometry based on w-lightguid

    NASA Astrophysics Data System (ADS)

    Rzhavin, Yuri; Ignatiev, Alex

    2003-04-01

    The present work describes a theoretical and experimantal modeling of registration seismic wave [1], application of optical fibre sensor whose sensitive is made on the basis of two Mach-Zender interferometers.The measuring and reference channels of the device are made in the form of signal-mode lightguides with w-profile, which retain the polarization of light .The effect of seismic pressure leads to axial compression of the w-fiber guides in the measuring channel.The measured signal is recorded by the relative displasement of the structure of the interference pattern, which is caused by phase modulation of a coherent light wave [2] propagating in the measuring channel. It has been demonstrated that the method based on calculation of the mutual correlation function [3] of the output signals of the interferometers makes it possible to raise the signal/noise ratio of the device by eliminating irregular noise waves and reproducing an accurate shape of the measured seismic pressure signal.As the light source, we have used single-frequency semiconductor injection laser which external resonator was used and one of a resonator mirrors was the w-lightguide end with reflection structure deposited on it .The w-lightguidess had the cup-off wave length 1,1 um, the degree of retention of polarization 99 %. Described model is applied for seismic monitoring in deep boreholes, volcanoes, in harsh environment-high temperature, pressure, chemically aggressive media, using telecom fibres. REFERENCES 1.Yu.I.Rzhavin et al., Radiotekhnika and Electronika, 1991,v.36, No 3 ,pp. 625-627 2.Yu.I .Rzhavin Proceeding SPIE, 1994, vol. 2349, pp.154-157 3. Yu.I.Rzhavin Proceeding SPIE, 2002, vol.4827, pp.253-257

  15. 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.

  16. 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.

  17. 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...

  18. Multimodal eye recognition

    NASA Astrophysics Data System (ADS)

    Zhou, Zhi; Du, Yingzi; Thomas, N. L.; Delp, Edward J., III

    2010-04-01

    Multimodal biometrics use more than one means of biometric identification to achieve higher recognition accuracy, since sometimes a unimodal biometric is not good enough used to do identification and classification. In this paper, we proposed a multimodal eye recognition system, which can obtain both iris and sclera patterns from one color eye image. Gabor filter and 1-D Log-Gabor filter algorithms have been applied as the iris recognition algorithms. In sclera recognition, we introduced automatic sclera segmentation, sclera pattern enhancement, sclera pattern template generation, and sclera pattern matching. We applied kernelbased matching score fusion to improve the performance of the eye recognition system. The experimental results show that the proposed eye recognition method can achieve better performance compared to unimodal biometric identification, and the accuracy of our proposed kernel-based matching score fusion method is higher than two classic linear matching score fusion methods: Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

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

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

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

  20. 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.

  1. 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

  2. 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 from a 3D B-mode US image. We then automatically estimate an initial registration transformation by using the proposed edge matching algorithm. The algorithm finds the most likely correspondences between the vessel centerlines of both images in a non-iterative manner based on a modified Viterbi algorithm. Finally, the registration is iteratively refined on the basis of the global affine transformation by jointly using the vessel and liver surface information. The proposed registration algorithm is validated on synthesized datasets and 20 clinical datasets, through both qualitative and quantitative evaluations. Experimental results show that automatic registration can be successfully achieved between 3D B-mode US and CT images even with a large initial misalignment.

  3. Registration of knee joint surfaces for the in vivo study of joint injuries based on magnetic resonance imaging

    NASA Astrophysics Data System (ADS)

    Cheng, Rita W. T.; Habib, Ayman F.; Frayne, Richard; Ronsky, Janet L.

    2006-03-01

    In-vivo quantitative assessments of joint conditions and health status can help to increase understanding of the pathology of osteoarthritis, a degenerative joint disease that affects a large population each year. Magnetic resonance imaging (MRI) provides a non-invasive and accurate means to assess and monitor joint properties, and has become widely used for diagnosis and biomechanics studies. Quantitative analyses and comparisons of MR datasets require accurate alignment of anatomical structures, thus image registration becomes a necessary procedure for these applications. This research focuses on developing a registration technique for MR knee joint surfaces to allow quantitative study of joint injuries and health status. It introduces a novel idea of translating techniques originally developed for geographic data in the field of photogrammetry and remote sensing to register 3D MR data. The proposed algorithm works with surfaces that are represented by randomly distributed points with no requirement of known correspondences. The algorithm performs matching locally by identifying corresponding surface elements, and solves for the transformation parameters relating the surfaces by minimizing normal distances between them. This technique was used in three applications to: 1) register temporal MR data to verify the feasibility of the algorithm to help monitor diseases, 2) quantify patellar movement with respect to the femur based on the transformation parameters, and 3) quantify changes in contact area locations between the patellar and femoral cartilage at different knee flexion angles. The results indicate accurate registration and the proposed algorithm can be applied for in-vivo study of joint injuries with MRI.

  4. Registration of head volume images using implantable fiducial markers

    NASA Astrophysics Data System (ADS)

    Maurer, Calvin R., Jr.; Fitzpatrick, J. Michael; Wang, Matthew Y.; Galloway, Robert L., Jr.; Maciunas, Robert J.; Allen, George S.

    1997-04-01

    In this paper, we describe an extrinsic point-based, interactive image-guided neurosurgical system designed at Vanderbilt University as part of a collaborative effort among the departments of neurological surgery, computer science, and biomedical engineering. Multimodal image-to- image and image-to-physical registration is accomplished using implantable markers. Physical space tracking is accomplished with optical triangulation. We investigate the theoretical accuracy of point-based registration using numerical simulations, the experimental accuracy of our system using data obtained with a phantom, and the clinical accuracy of our system using data acquired in a prospective clinical trial by six neurosurgeons at four medical centers from 158 patients undergoing craniotomies to resect cerebral lesions. We can determine the position of our markers with an error of approximately 0.4 mm in x-ray computed tomography (CT) and magnetic resonance (MR) images and 0.3 mm in physical space. The theoretical registration error using four such markers distributed around the head in a configuration that is clinically practical is approximately 0.5 - 0.6 mm. The mean CT-physical registration error for the phantom experiments is 0.5 mm and for the clinical data obtained with rigid head fixation during scanning is 0.7 mm. The mean CT-MR registration error for the clinical data obtained without rigid head fixation during scanning is 1.4 mm, which is the highest mean error that we observed. These theoretical and experimental findings indicate that this system is an accurate navigational aid that can provide real-time feedback to the surgeon about anatomical structures encountered in the surgical field.

  5. SU-E-J-237: Image Feature Based DRR and Portal Image Registration

    SciTech Connect

    Wang, X; Chang, J

    2014-06-01

    Purpose: Two-dimensional (2D) matching of the kV X-ray and digitally reconstructed radiography (DRR) images is an important setup technique for image-guided radiotherapy (IGRT). In our clinics, mutual information based methods are used for this purpose on commercial linear accelerators, but with often needs for manual corrections. This work proved the feasibility that feature based image transform can be used to register kV and DRR images. Methods: The scale invariant feature transform (SIFT) method was implemented to detect the matching image details (or key points) between the kV and DRR images. These key points represent high image intensity gradients, and thus the scale invariant features. Due to the poor image contrast from our kV image, direct application of the SIFT method yielded many detection errors. To assist the finding of key points, the center coordinates of the kV and DRR images were read from the DICOM header, and the two groups of key points with similar relative positions to their corresponding centers were paired up. Using these points, a rigid transform (with scaling, horizontal and vertical shifts) was estimated. We also artificially introduced vertical and horizontal shifts to test the accuracy of our registration method on anterior-posterior (AP) and lateral pelvic images. Results: The results provided a satisfactory overlay of the transformed kV onto the DRR image. The introduced vs. detected shifts were fit into a linear regression. In the AP image experiments, linear regression analysis showed a slope of 1.15 and 0.98 with an R2 of 0.89 and 0.99 for the horizontal and vertical shifts, respectively. The results are 1.2 and 1.3 with R2 of 0.72 and 0.82 for the lateral image shifts. Conclusion: This work provided an alternative technique for kV to DRR alignment. Further improvements in the estimation accuracy and image contrast tolerance are underway.

  6. Co-Registration of Terrestrial and Uav-Based Images - Experimental Results

    NASA Astrophysics Data System (ADS)

    Gerke, M.; Nex, F.; Jende, P.

    2016-03-01

    For many applications within urban environments the combined use of images taken from the ground and from unmanned aerial platforms seems interesting: while from the airborne perspective the upper parts of objects including roofs can be observed, the ground images can complement the data from lateral views to retrieve a complete visualisation or 3D reconstruction of interesting areas. The automatic co-registration of air- and ground-based images is still a challenge and cannot be considered solved. The main obstacle is originating from the fact that objects are photographed from quite different angles, and hence state-of-the-art tie point measurement approaches cannot cope with the induced perspective transformation. One first important step towards a solution is to use airborne images taken under slant directions. Those oblique views not only help to connect vertical images and horizontal views but also provide image information from 3D-structures not visible from the other two directions. According to our experience, however, still a good planning and many images taken under different viewing angles are needed to support an automatic matching across all images and complete bundle block adjustment. Nevertheless, the entire process is still quite sensible - the removal of a single image might lead to a completely different or wrong solution, or separation of image blocks. In this paper we analyse the impact different parameters and strategies have on the solution. Those are a) the used tie point matcher, b) the used software for bundle adjustment. Using the data provided in the context of the ISPRS benchmark on multi-platform photogrammetry, we systematically address the mentioned influences. Concerning the tie-point matching we test the standard SIFT point extractor and descriptor, but also the SURF and ASIFT-approaches, the ORB technique, as well as (A)KAZE, which are based on a nonlinear scale space. In terms of pre-processing we analyse the Wallis

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

    SciTech Connect

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

    2011-04-15

    with rigid registration. Conclusions: A method was developed to iteratively correct CT-CBCT intensity disparity during Demons registration, enabling fast, intensity-based registration in CBCT-guided procedures such as surgery and radiotherapy, in which CBCT voxel values may be inaccurate. Accurate CT-CBCT registration in turn facilitates registration of multimodality preoperative image and planning data to intraoperative CBCT by way of the preoperative CT, thereby linking the intraoperative frame of reference to a wealth of preoperative information that could improve interventional guidance.

  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. 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.

  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. Multimodal Segmentation of Optic Disc and Cup From SD-OCT and Color Fundus Photographs Using a Machine-Learning Graph-Based Approach.

    PubMed

    Miri, Mohammad Saleh; Abràmoff, Michael D; Lee, Kyungmoo; Niemeijer, Meindert; Wang, Jui-Kai; Kwon, Young H; Garvin, Mona K

    2015-09-01

    In this work, a multimodal approach is proposed to use the complementary information from fundus photographs and spectral domain optical coherence tomography (SD-OCT) volumes in order to segment the optic disc and cup boundaries. The problem is formulated as an optimization problem where the optimal solution is obtained using a machine-learning theoretical graph-based method. In particular, first the fundus photograph is registered to the 2D projection of the SD-OCT volume. Three in-region cost functions are designed using a random forest classifier corresponding to three regions of cup, rim, and background. Next, the volumes are resampled to create radial scans in which the Bruch's Membrane Opening (BMO) endpoints are easier to detect. Similar to in-region cost function design, the disc-boundary cost function is designed using a random forest classifier for which the features are created by applying the Haar Stationary Wavelet Transform (SWT) to the radial projection image. A multisurface graph-based approach utilizes the in-region and disc-boundary cost images to segment the boundaries of optic disc and cup under feasibility constraints. The approach is evaluated on 25 multimodal image pairs from 25 subjects in a leave-one-out fashion (by subject). The performances of the graph-theoretic approach using three sets of cost functions are compared: 1) using unimodal (OCT only) in-region costs, 2) using multimodal in-region costs, and 3) using multimodal in-region and disc-boundary costs. Results show that the multimodal approaches outperform the unimodal approach in segmenting the optic disc and cup.

  13. Multimodal Segmentation of Optic Disc and Cup from SD-OCT and Color Fundus Photographs Using a Machine-Learning Graph-Based Approach

    PubMed Central

    Miri, Mohammad Saleh; Abràmoff, Michael D.; Lee, Kyungmoo; Niemeijer, Meindert; Wang, Jui-Kai; Kwon, Young H.

    2015-01-01

    In this work, a multimodal approach is proposed to use the complementary information from fundus photographs and spectral domain optical coherence tomography (SD-OCT) volumes in order to segment the optic disc and cup boundaries. The problem is formulated as an optimization problem where the optimal solution is obtained using a machine-learning theoretical graph-based method. In particular, first the fundus photograph is registered to the 2D projection of the SD-OCT volume. Three in-region cost functions are designed using a random forest classifier corresponding to three regions of cup, rim, and background. Next, the volumes are resampled to create radial scans in which the Bruch’s Membrane Opening (BMO) endpoints are easier to detect. Similar to in-region cost function design, the disc-boundary cost function is designed using a random forest classifier for which the features are created by applying the Haar Stationary Wavelet Transform (SWT) to the radial projection image. A multisurface graph-based approach utilizes the in-region and disc-boundary cost images to segment the boundaries of optic disc and cup under feasibility constraints. The approach is evaluated on 25 multimodal image pairs from 25 subjects in a leave-one-out fashion (by subject). The performances of the graph-theoretic approach using three sets of cost functions are compared: 1) using unimodal (OCT only) in-region costs, 2) using multimodal in-region costs, and 3) using multimodal in-region and disc-boundary costs. Results show that the multimodal approaches outperform the unimodal approach in segmenting the optic disc and cup. PMID:25781623

  14. SU-E-J-263: Dosimetric Analysis On Breast Brachytherapy Based On Deformable Image Registration

    SciTech Connect

    Chen, T; Nie, K; Narra, V; Zou, J; Zhang, M; Khan, A; Haffty, B; Yue, N

    2014-06-01

    Purpose: To quantitatively compare and evaluate the dosimetry difference between breast brachytherapy protocols with different fractionation using deformable image registration. Methods: The accumulative dose distribution for multiple breast brachytherapy patients using four different applicators: Contura, Mammosite, Savi, and interstitial catheters, under two treatment protocols: 340cGy by 10 fractions in 5 days and 825cGy by 3 fractions in 2days has been reconstructed using a two stage deformable image registration approach. For all patients, daily CT was acquired with the same slice thickness (2.5mm). In the first stage, the daily CT images were rigidly registered to the initial planning CT using the registration module in Eclipse (Varian) to align the applicators. In the second stage, the tissues surrounding the applicator in the rigidly registered daily CT image were non-rigidly registered to the initial CT using a combination of image force and the local constraint that enforce zero normal motion on the surface of the applicator, using a software developed in house. We calculated the dose distribution in the daily CTs and deformed them using the final registration to convert into the image domain of the initial planning CT. The accumulative dose distributions were evaluated by dosimetry parameters including D90, V150 and V200, as well as DVH. Results: Dose reconstruction results showed that the two day treatment has a significant dosimetry improvement over the five day protocols. An average daily drop of D90 at 1.3% of the prescription dose has been observed on multiple brachytherapy patients. There is no significant difference on V150 and V200 between those two protocols. Conclusion: Brachytherapy with higher fractional dose and less fractions has an improved performance on being conformal to the dose distribution in the initial plan. Elongated brachytherapy treatments need to consider the dose uncertainty caused by the temporal changes of the soft tissue.

  15. Comparison of demons deformable registration-based methods for texture analysis of serial thoracic CT scans

    NASA Astrophysics Data System (ADS)

    Cunliffe, Alexandra R.; Al-Hallaq, Hania A.; Fei, Xianhan M.; Tuohy, Rachel E.; Armato, Samuel G.

    2013-02-01

    To determine how 19 image texture features may be altered by three image registration methods, "normal" baseline and follow-up computed tomography (CT) scans from 27 patients were analyzed. Nineteen texture feature values were calculated in over 1,000 32x32-pixel regions of interest (ROIs) randomly placed in each baseline scan. All three methods used demons registration to map baseline scan ROIs to anatomically matched locations in the corresponding transformed follow-up scan. For the first method, the follow-up scan transformation was subsampled to achieve a voxel size identical to that of the baseline scan. For the second method, the follow-up scan was transformed through affine registration to achieve global alignment with the baseline scan. For the third method, the follow-up scan was directly deformed to the baseline scan using demons deformable registration. Feature values in matched ROIs were compared using Bland- Altman 95% limits of agreement. For each feature, the range spanned by the 95% limits was normalized to the mean feature value to obtain the normalized range of agreement, nRoA. Wilcoxon signed-rank tests were used to compare nRoA values across features for the three methods. Significance for individual tests was adjusted using the Bonferroni method. nRoA was significantly smaller for affine-registered scans than for the resampled scans (p=0.003), indicating lower feature value variability between baseline and follow-up scan ROIs using this method. For both of these methods, however, nRoA was significantly higher than when feature values were calculated directly on demons-deformed followup scans (p<0.001). Across features and methods, nRoA values remained below 26%.

  16. 3D-2D registration of cerebral angiograms based on vessel directions and intensity gradients

    NASA Astrophysics Data System (ADS)

    Mitrovic, Uroš; Špiclin, Žiga; Štern, Darko; Markelj, Primož; Likar, Boštjan; Miloševic, Zoran; Pernuš, Franjo

    2012-02-01

    Endovascular treatment of cerebral aneurysms and arteriovenous malformations (AVM) involves navigation of a catheter through the femoral artery and vascular system to the site of pathology. Intra-interventional navigation is done under the guidance of one or at most two two-dimensional (2D) X-ray fluoroscopic images or 2D digital subtracted angiograms (DSA). Due to the projective nature of 2D images, the interventionist needs to mentally reconstruct the position of the catheter in respect to the three-dimensional (3D) patient vasculature, which is not a trivial task. By 3D-2D registration of pre-interventional 3D images like CTA, MRA or 3D-DSA and intra-interventional 2D images, intra-interventional tools such as catheters can be visualized on the 3D model of patient vasculature, allowing easier and faster navigation. Such a navigation may consequently lead to the reduction of total ionizing dose and delivered contrast medium. In the past, development and evaluation of 3D-2D registration methods for endovascular treatments received considerable attention. The main drawback of these methods is that they have to be initialized rather close to the correct position as they mostly have a rather small capture range. In this paper, a novel registration method that has a higher capture range and success rate is proposed. The proposed method and a state-of-the-art method were tested and evaluated on synthetic and clinical 3D-2D image-pairs. The results on both databases indicate that although the proposed method was slightly less accurate, it significantly outperformed the state-of-the-art 3D-2D registration method in terms of robustness measured by capture range and success rate.

  17. Symmetric log-domain diffeomorphic Registration: a demons-based approach.

    PubMed

    Vercauteren, Tom; Pennec, Xavier; Perchant, Aymeric; Ayache, Nicholas

    2008-01-01

    Modern morphometric studies use non-linear image registration to compare anatomies and perform group analysis. Recently, log-Euclidean approaches have contributed to promote the use of such computational anatomy tools by permitting simple computations of statistics on a rather large class of invertible spatial transformations. In this work, we propose a non-linear registration algorithm perfectly fit for log-Euclidean statistics on diffeomorphisms. Our algorithm works completely in the log-domain, i.e. it uses a stationary velocity field. This implies that we guarantee the invertibility of the deformation and have access to the true inverse transformation. This also means that our output can be directly used for log-Euclidean statistics without relying on the heavy computation of the log of the spatial transformation. As it is often desirable, our algorithm is symmetric with respect to the order of the input images. Furthermore, we use an alternate optimization approach related to Thirion's demons algorithm to provide a fast non-linear registration algorithm. First results show that our algorithm outperforms both the demons algorithm and the recently proposed diffeomorphic demons algorithm in terms of accuracy of the transformation while remaining computationally efficient. PMID:18979814

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

    NASA Astrophysics Data System (ADS)

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

    2001-07-01

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

  19. NON-RIGID IMAGE REGISTRATION BASED STRAIN ESTIMATOR FOR INTRAVASCULAR ULTRASOUND ELASTOGRAPHY

    PubMed Central

    Richards, Michael S.; Doyley, Marvin M.

    2013-01-01

    Intravascular ultrasound elastography (IVUSe) could improve the diagnosis of cardiovascular disease by revealing vulnerable plaques through their mechanical tissue properties. To improve the performance of IVUSe, we developed and implemented a non-rigid image-registration method to visualize the radial and circumferential component of strain within vascular tissues. We evaluated the algorithm’s performance with four initialization schemes using simulated and experimentally acquired ultrasound images. Applying the registration method to radio-frequency (RF) echo frames improved the accuracy of displacements compared to when B-mode images were employed. However, strain elastograms measured from RF echo frames produce erroneous results when both the zero-initialization method and the mesh-refinement scheme were employed. For most strain levels, the cross-correlation-initialization method produced the best performance. The simulation study predicted that elastograms obtained from vessels with average strains in the range of 3%–5% should have high elastographic signal-to-noise ratio (SNRe)–on the order of 4.5 and 7.5 for the radial and circumferential components of strain, respectively. The preliminary in vivo validation study (phantom and an atherosclerotic rabbit) demonstrated that the non-rigid registration method could produce useful radial and circumferential strain elastograms under realistic physiologic conditions. The results of this investigation were sufficiently encouraging to warrant a more comprehensive in vivo validation. PMID:23245827

  20. Contrast-Based 3D/2D Registration of the Left Atrium: Fast versus Consistent

    PubMed Central

    Kowalewski, Christopher; Kurzidim, Klaus; Strobel, Norbert; Hornegger, Joachim

    2016-01-01

    For augmented fluoroscopy during cardiac ablation, a preoperatively acquired 3D model of a patient's left atrium (LA) can be registered to X-ray images recorded during a contrast agent (CA) injection. An automatic registration method that works also for small amounts of CA is desired. We propose two similarity measures: The first focuses on edges of the patient anatomy. The second computes a contrast agent distribution estimate (CADE) inside the 3D model and rates its consistency with the CA as seen in biplane fluoroscopic images. Moreover, temporal filtering on the obtained registration results of a sequence is applied using a Markov chain framework. Evaluation was performed on 11 well-contrasted clinical angiographic sequences and 10 additional sequences with less CA. For well-contrasted sequences, the error for all 73 frames was 7.9 ± 6.3 mm and it dropped to 4.6 ± 4.0 mm when registering to an automatically selected, well enhanced frame in each sequence. Temporal filtering reduced the error for all frames from 7.9 ± 6.3 mm to 5.7 ± 4.6 mm. The error was typically higher if less CA was used. A combination of both similarity measures outperforms a previously proposed similarity measure. The mean accuracy for well contrasted sequences is in the range of other proposed manual registration methods. PMID:27051412

  1. Deformable Medical Image Registration: A Survey

    PubMed Central

    Sotiras, Aristeidis; Davatzikos, Christos; Paragios, Nikos

    2013-01-01

    Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: i) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; ii) longitudinal studies, where temporal structural or anatomical changes are investigated; and iii) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner. PMID:23739795

  2. Serial Scanning and Registration of High Resolution Quantitative Computed Tomography Volume Scans for the Determination of Local Bone Density Changes

    NASA Technical Reports Server (NTRS)

    Whalen, Robert T.; Napel, Sandy; Yan, Chye H.

    1996-01-01

    Progress in development of the methods required to study bone remodeling as a function of time is reported. The following topics are presented: 'A New Methodology for Registration Accuracy Evaluation', 'Registration of Serial Skeletal Images for Accurately Measuring Changes in Bone Density', and 'Precise and Accurate Gold Standard for Multimodality and Serial Registration Method Evaluations.'

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

    PubMed

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

    2009-10-01

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

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. Fast simulated annealing and adaptive Monte Carlo sampling based parameter optimization for dense optical-flow deformable image registration of 4DCT lung anatomy

    NASA Astrophysics Data System (ADS)

    Dou, Tai H.; Min, Yugang; Neylon, John; Thomas, David; Kupelian, Patrick; Santhanam, Anand P.

    2016-03-01

    Deformable image registration (DIR) is an important step in radiotherapy treatment planning. An optimal input registration parameter set is critical to achieve the best registration performance with the specific algorithm. Methods In this paper, we investigated a parameter optimization strategy for Optical-flow based DIR of the 4DCT lung anatomy. A novel fast simulated annealing with adaptive Monte Carlo sampling algorithm (FSA-AMC) was investigated for solving the complex non-convex parameter optimization problem. The metric for registration error for a given parameter set was computed using landmark-based mean target registration error (mTRE) between a given volumetric image pair. To reduce the computational time in the parameter optimization process, a GPU based 3D dense optical-flow algorithm was employed for registering the lung volumes. Numerical analyses on the parameter optimization for the DIR were performed using 4DCT datasets generated with breathing motion models and open-source 4DCT datasets. Results showed that the proposed method efficiently estimated the optimum parameters for optical-flow and closely matched the best registration parameters obtained using an exhaustive parameter search method.

  9. 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

  10. Osteo-cise: Strong Bones for Life: Protocol for a community-based randomised controlled trial of a multi-modal exercise and osteoporosis education program for older adults at risk of falls and fractures

    PubMed Central

    2012-01-01

    , balance and function (four square step test, functional reach test, timed up-and-go test and 30-second sit-to-stand), falls incidence and health-related quality of life. Cost-effectiveness will also be assessed. Discussion The findings from the Osteo-cise: Strong Bones for Life study will provide new information on the efficacy of a targeted multi-modal community-based exercise program incorporating high velocity resistance training, together with an osteoporosis education and behavioural change program for improving multiple risk factors for falls and fracture in older adults at risk of fragility fracture. Trial registration Australian New Zealand Clinical Trials Registry reference ACTRN12609000100291 PMID:22640372

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

    PubMed

    Liu, Yixun; Kot, Andriy; Drakopoulos, Fotis; Yao, Chengjun; Fedorov, Andriy; Enquobahrie, Andinet; Clatz, Olivier; Chrisochoides, Nikos P

    2014-01-01

    As part of the ITK v4 project efforts, we have developed ITK filters for physics-based non-rigid registration (PBNRR), which satisfies the following requirements: account for tissue properties in the registration, improve accuracy compared to rigid registration, and reduce execution time using GPU and multi-core accelerators. The implementation has three main components: (1) Feature Point Selection, (2) Block Matching (mapped to both multi-core and GPU processors), and (3) a Robust Finite Element Solver. The use of multi-core and GPU accelerators in ITK v4 provides substantial performance improvements. For example, for the non-rigid registration of brain MRIs, the performance of the block matching filter on average is about 10 times faster when 12 hyperthreaded multi-cores are used and about 83 times faster when the NVIDIA Tesla GPU is used in Dell Workstation.

  12. Registration-based segmentation of three-dimensional ultrasound images for quantitative measurement of fetal craniofacial structure.

    PubMed

    Chen, Hsin-Chen; Tsai, Pei-Yin; Huang, Hsiao-Han; Shih, Hui-Hsuan; Wang, Yi-Ying; Chang, Chiung-Hsin; Sun, Yung-Nien

    2012-05-01

    Segmentation of a fetal head from three-dimensional (3-D) ultrasound images is a critical step in the quantitative measurement of fetal craniofacial structure. However, two main issues complicate segmentation, including fuzzy boundaries and large variations in pose and shape among different ultrasound images. In this article, we propose a new registration-based method for automatically segmenting the fetal head from 3-D ultrasound images. The proposed method first detects the eyes based on Gabor features to identify the pose of the fetus image. Then, a reference model, which is constructed from a fetal phantom and contains prior knowledge of head shape, is aligned to the image via feature-based registration. Finally, 3-D snake deformation is utilized to improve the boundary fitness between the model and image. Four clinically useful parameters including inter-orbital diameter (IOD), bilateral orbital diameter (BOD), occipital frontal diameter (OFD) and bilateral parietal diameter (BPD) are measured based on the results of the eye detection and head segmentation. Ultrasound volumes from 11 subjects were used for validation of the method accuracy. Experimental results showed that the proposed method was able to overcome the aforementioned difficulties and achieve good agreement between automatic and manual measurements.

  13. Dynamic 2D ultrasound and 3D CT image registration of the beating heart.

    PubMed

    Huang, Xishi; Moore, John; Guiraudon, Gerard; Jones, Douglas L; Bainbridge, Daniel; Ren, Jing; Peters, Terry M

    2009-08-01

    Two-dimensional ultrasound (US) is widely used in minimally invasive cardiac procedures due to its convenience of use and noninvasive nature. However, the low quality of US images often limits their utility as a means for guiding procedures, since it is often difficult to relate the images to their anatomical context. To improve the interpretability of the US images while maintaining US as a flexible anatomical and functional real-time imaging modality, we describe a multimodality image navigation system that integrates 2D US images with their 3D context by registering them to high quality preoperative models based on magnetic resonance imaging (MRI) or computed tomography (CT) images. The mapping from such a model to the patient is completed using spatial and temporal registrations. Spatial registration is performed by a two-step rapid registration method that first approximately aligns the two images as a starting point to an automatic registration procedure. Temporal alignment is performed with the aid of electrocardiograph (ECG) signals and a latency compensation method. Registration accuracy is measured by calculating the TRE. Results show that the error between the US and preoperative images of a beating heart phantom is 1.7 +/-0.4 mm, with a similar performance being observed in in vivo animal experiments.

  14. Estimation of lung motion fields in 4D CT data by variational non-linear intensity-based registration: A comparison and evaluation study.

    PubMed

    Werner, René; Schmidt-Richberg, Alexander; Handels, Heinz; Ehrhardt, Jan

    2014-08-01

    Accurate and robust estimation of motion fields in respiration-correlated CT (4D CT) images, usually performed by non-linear registration of the temporal CT frames, is a precondition for the analysis of patient-specific breathing dynamics and subsequent image-supported diagnostics and treatment planning. In this work, we present a comprehensive comparison and evaluation study of non-linear registration variants applied to the task of lung motion estimation in thoracic 4D CT data. In contrast to existing multi-institutional comparison studies (e.g. MIDRAS and EMPIRE10), we focus on the specific but common class of variational intensity-based non-parametric registration and analyze the impact of the different main building blocks of the underlying optimization problem: the distance measure to be minimized, the regularization approach and the transformation space considered during optimization. In total, 90 different combinations of building block instances are compared. Evaluated on proprietary and publicly accessible 4D CT images, landmark-based registration errors (TRE) between 1.14 and 1.20 mm for the most accurate registration variants demonstrate competitive performance of the applied general registration framework compared to other state-of-the-art approaches for lung CT registration. Although some specific trends can be observed, effects of interchanging individual instances of the building blocks on the TRE are in general rather small (no single outstanding registration variant existing); the same level of accuracy is, however, associated with significantly different degrees of motion field smoothness and computational demands. Consequently, the building block combination of choice will depend on application-specific requirements on motion field characteristics.

  15. SU-E-J-132: Automated Segmentation with Post-Registration Atlas Selection Based On Mutual Information

    SciTech Connect

    Ren, X; Gao, H; Sharp, G

    2015-06-15

    Purpose: The delineation of targets and organs-at-risk is a critical step during image-guided radiation therapy, for which manual contouring is the gold standard. However, it is often time-consuming and may suffer from intra- and inter-rater variability. The purpose of this work is to investigate the automated segmentation. Methods: The automatic segmentation here is based on mutual information (MI), with the atlas from Public Domain Database for Computational Anatomy (PDDCA) with manually drawn contours.Using dice coefficient (DC) as the quantitative measure of segmentation accuracy, we perform leave-one-out cross-validations for all PDDCA images sequentially, during which other images are registered to each chosen image and DC is computed between registered contour and ground truth. Meanwhile, six strategies, including MI, are selected to measure the image similarity, with MI to be the best. Then given a target image to be segmented and an atlas, automatic segmentation consists of: (a) the affine registration step for image positioning; (b) the active demons registration method to register the atlas to the target image; (c) the computation of MI values between the deformed atlas and the target image; (d) the weighted image fusion of three deformed atlas images with highest MI values to form the segmented contour. Results: MI was found to be the best among six studied strategies in the sense that it had the highest positive correlation between similarity measure (e.g., MI values) and DC. For automated segmentation, the weighted image fusion of three deformed atlas images with highest MI values provided the highest DC among four proposed strategies. Conclusion: MI has the highest correlation with DC, and therefore is an appropriate choice for post-registration atlas selection in atlas-based segmentation. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)

  16. Toward a real time multi-tissue Adaptive Physics-Based Non-Rigid Registration framework for brain tumor resection.

    PubMed

    Drakopoulos, Fotis; Foteinos, Panagiotis; Liu, Yixun; Chrisochoides, Nikos P

    2014-01-01

    This paper presents an adaptive non-rigid registration method for aligning pre-operative MRI with intra-operative MRI (iMRI) to compensate for brain deformation during brain tumor resection. This method extends a successful existing Physics-Based Non-Rigid Registration (PBNRR) technique implemented in ITKv4.5. The new method relies on a parallel adaptive heterogeneous biomechanical Finite Element (FE) model for tissue/tumor removal depicted in the iMRI. In contrast the existing PBNRR in ITK relies on homogeneous static FE model designed for brain shift only (i.e., it is not designed to handle brain tumor resection). As a result, the new method (1) accurately captures the intra-operative deformations associated with the tissue removal due to tumor resection and (2) reduces the end-to-end execution time to within the time constraints imposed by the neurosurgical procedure. The evaluation of the new method is based on 14 clinical cases with: (i) brain shift only (seven cases), (ii) partial tumor resection (two cases), and (iii) complete tumor resection (five cases). The new adaptive method can reduce the alignment error up to seven and five times compared to a rigid and ITK's PBNRR registration methods, respectively. On average, the alignment error of the new method is reduced by 9.23 and 5.63 mm compared to the alignment error from the rigid and PBNRR method implemented in ITK. Moreover, the total execution time for all the case studies is about 1 min or less in a Linux Dell workstation with 12 Intel Xeon 3.47 GHz CPU cores and 96 GB of RAM.

  17. Gelatin-based Hydrogel Degradation and Tissue Interaction in vivo: Insights from Multimodal Preclinical Imaging in Immunocompetent Nude Mice

    PubMed Central

    Tondera, Christoph; Hauser, Sandra; Krüger-Genge, Anne; Jung, Friedrich; Neffe, Axel T.; Lendlein, Andreas; Klopfleisch, Robert; Steinbach, Jörg; Neuber, Christin; Pietzsch, Jens

    2016-01-01

    Hydrogels based on gelatin have evolved as promising multifunctional biomaterials. Gelatin is crosslinked with lysine diisocyanate ethyl ester (LDI) and the molar ratio of gelatin and LDI in the starting material mixture determines elastic properties of the resulting hydrogel. In order to investigate the clinical potential of these biopolymers, hydrogels with different ratios of gelatin and diisocyanate (3-fold (G10_LNCO3) and 8-fold (G10_LNCO8) molar excess of isocyanate groups) were subcutaneously implanted in mice (uni- or bilateral implantation). Degradation and biomaterial-tissue-interaction were investigated in vivo (MRI, optical imaging, PET) and ex vivo (autoradiography, histology, serum analysis). Multimodal imaging revealed that the number of covalent net points correlates well with degradation time, which allows for targeted modification of hydrogels based on properties of the tissue to be replaced. Importantly, the degradation time was also dependent on the number of implants per animal. Despite local mechanisms of tissue remodeling no adverse tissue responses could be observed neither locally nor systemically. Finally, this preclinical investigation in immunocompetent mice clearly demonstrated a complete restoration of the original healthy tissue.

  18. Multimodal Nonlinear Optical Imaging of MoS₂ and MoS₂-Based van der Waals Heterostructures.

    PubMed

    Li, Dawei; Xiong, Wei; Jiang, Lijia; Xiao, Zhiyong; Golgir, Hossein Rabiee; Wang, Mengmeng; Huang, Xi; Zhou, Yunshen; Lin, Zhe; Song, Jingfeng; Ducharme, Stephen; Jiang, Lan; Silvain, Jean-Francois; Lu, Yongfeng

    2016-03-22

    van der Waals layered structures, notably the transitional metal dichalcogenides (TMDs) and TMD-based heterostructures, have recently attracted immense interest due to their unique physical properties and potential applications in electronics, optoelectronics, and energy harvesting. Despite the recent progress, it is still a challenge to perform comprehensive characterizations of critical properties of these layered structures, including crystal structures, chemical dynamics, and interlayer coupling, using a single characterization platform. In this study, we successfully developed a multimodal nonlinear optical imaging method to characterize these critical properties of molybdenum disulfide (MoS2) and MoS2-based heterostructures. Our results demonstrate that MoS2 layers exhibit strong four-wave mixing (FWM), sum-frequency generation (SFG), and second-harmonic generation (SHG) nonlinear optical characteristics. We believe this is the first observation of FWM and SFG from TMD layers. All three kinds of optical nonlinearities are sensitive to layer numbers, crystal orientation, and interlayer coupling. The combined and simultaneous SHG/SFG-FWM imaging not only is capable of rapid evaluation of crystal quality and precise determination of odd-even layers but also provides in situ monitoring of the chemical dynamics of thermal oxidation in MoS2 and interlayer coupling in MoS2-graphene heterostructures. This method has the advantages of versatility, high fidelity, easy operation, and fast imaging, enabling comprehensive characterization of van der Waals layered structures for fundamental research and practical applications. PMID:26914313

  19. Gelatin-based Hydrogel Degradation and Tissue Interaction in vivo: Insights from Multimodal Preclinical Imaging in Immunocompetent Nude Mice

    PubMed Central

    Tondera, Christoph; Hauser, Sandra; Krüger-Genge, Anne; Jung, Friedrich; Neffe, Axel T.; Lendlein, Andreas; Klopfleisch, Robert; Steinbach, Jörg; Neuber, Christin; Pietzsch, Jens

    2016-01-01

    Hydrogels based on gelatin have evolved as promising multifunctional biomaterials. Gelatin is crosslinked with lysine diisocyanate ethyl ester (LDI) and the molar ratio of gelatin and LDI in the starting material mixture determines elastic properties of the resulting hydrogel. In order to investigate the clinical potential of these biopolymers, hydrogels with different ratios of gelatin and diisocyanate (3-fold (G10_LNCO3) and 8-fold (G10_LNCO8) molar excess of isocyanate groups) were subcutaneously implanted in mice (uni- or bilateral implantation). Degradation and biomaterial-tissue-interaction were investigated in vivo (MRI, optical imaging, PET) and ex vivo (autoradiography, histology, serum analysis). Multimodal imaging revealed that the number of covalent net points correlates well with degradation time, which allows for targeted modification of hydrogels based on properties of the tissue to be replaced. Importantly, the degradation time was also dependent on the number of implants per animal. Despite local mechanisms of tissue remodeling no adverse tissue responses could be observed neither locally nor systemically. Finally, this preclinical investigation in immunocompetent mice clearly demonstrated a complete restoration of the original healthy tissue. PMID:27698944

  20. A reflective fiber-optic refractive index sensor based on multimode interference in a coreless silica fiber

    NASA Astrophysics Data System (ADS)

    Zhou, Xinlei; Chen, Ke; Mao, Xuefeng; peng, Wei; Yu, Qingxu

    2015-04-01

    A reflective fiber-optic refractive index (RI) sensor based on multimode interference (MMI) is presented and investigated in this paper. The sensor is made by splicing a small section of coreless silica fiber (CSF) to the standard single mode fiber (SMF). A wide-angle beam propagation method (WA-BPM) is employed for numerical simulation and design of the proposed RI sensor. Based on the simulation results, a RI sensor with a length of 1.7 cm of CSF is fabricated and experimentally studied. Experimental results show that the characteristic wavelength shift has an approximately linear relationship with the RI of the sample. A sensitivity of 141 nm/RIU (refractive index unit) and a resolution of 2.8×10-5 are obtained in the RI range from 1.33 to 1.38. As the RI value is higher than 1.38, the sensitivity of the sensor increase rapidly as the RI increase and a maximum sensitivity of 1561 nm/RIU can be achieved, corresponding to a resolution of 2.6×10-6. The experimental results fit well with the numerical simulation results.

  1. Multimodality Imaging of Gene Transfer with a Receptor-Based Reporter Gene

    PubMed Central

    Chen, Ron; Parry, Jesse J.; Akers, Walter J.; Berezin, Mikhail Y.; El Naqa, Issam M.; Achilefu, Samuel; Edwards, W. Barry; Rogers, Buck E.

    2010-01-01

    Gene therapy trials have traditionally used tumor and tissue biopsies for assessing the efficacy of gene transfer. Non-invasive imaging techniques offer a distinct advantage over tissue biopsies in that the magnitude and duration of gene transfer can be monitored repeatedly. Human somatostatin receptor subtype 2 (SSTR2) has been used for the nuclear imaging of gene transfer. To extend this concept, we have developed a somatostatin receptor–enhanced green fluorescent protein fusion construct (SSTR2-EGFP) for nuclear and fluorescent multimodality imaging. Methods An adenovirus containing SSTR2-EGFP (AdSSTR2-EGFP) was constructed and evaluated in vitro and in vivo. SCC-9 human squamous cell carcinoma cells were infected with AdEGFP, AdSSTR2, or AdSSTR2-EGFP for in vitro evaluation by saturation binding, internalization, and fluorescence spectroscopy assays. In vivo biodistribution and nano-SPECT imaging studies were conducted with mice bearing SCC-9 tumor xenografts directly injected with AdSSTR2-EGFP or AdSSTR2 to determine the tumor localization of 111In-diethylenetriaminepentaacetic acid (DTPA)-Tyr3-octreotate. Fluorescence imaging was conducted in vivo with mice receiving intratumoral injections of AdSSTR2, AdSSTR2-EGFP, or AdEGFP as well as ex vivo with tissues extracted from mice. Results The similarity between AdSSTR2-EGFP and wild-type AdSSTR2 was demonstrated in vitro by the saturation binding and internalization assays, and the fluorescence emission spectra of cells infected with AdSSTR2-EGFP was almost identical to the spectra of cells infected with wild-type AdEGFP. Biodistribution studies demonstrated that the tumor uptake of 111In-DTPA-Tyr3-octreotate was not significantly different (P > 0.05) when tumors (n = 5) were injected with AdSSTR2 or AdSSTR2-EGFP but was significantly greater than the uptake in control tumors. Fluorescence was observed in tumors injected with AdSSTR2-EGFP and AdEGFP in vivo and ex vivo but not in tumors injected with AdSSTR2

  2. A Markov random field approach for topology-preserving registration: application to object-based tomographic image interpolation.

    PubMed

    Cordero-Grande, Lucilio; Vegas-Sánchez-Ferrero, Gonzalo; Casaseca-de-la-Higuera, Pablo; Alberola-López, Carlos

    2012-04-01

    This paper proposes a topology-preserving multiresolution elastic registration method based on a discrete Markov random field of deformations and a block-matching procedure. The method is applied to the object-based interpolation of tomographic slices. For that purpose, the fidelity of a given deformation to the data is established by a block-matching strategy based on intensity- and gradient-related features, the smoothness of the transformation is favored by an appropriate prior on the field, and the deformation is guaranteed to maintain the topology by imposing some hard constraints on the local configurations of the field. The resulting deformation is defined as the maximum a posteriori configuration. Additionally, the relative influence of the fidelity and smoothness terms is weighted by the unsupervised estimation of the field parameters. In order to obtain an unbiased interpolation result, the registration is performed both in the forward and backward directions, and the resulting transformations are combined by using the local information content of the deformation. The method is applied to magnetic resonance and computed tomography acquisitions of the brain and the torso. Quantitative comparisons offer an overall improvement in performance with respect to related works in the literature. Additionally, the application of the interpolation method to cardiac magnetic resonance images has shown that the removal of any of the main components of the algorithm results in a decrease in performance which has proven to be statistically significant.

  3. Intraoperative Image-based Multiview 2D/3D Registration for Image-Guided Orthopaedic Surgery: Incorporation of Fiducial-Based C-Arm Tracking and GPU-Acceleration

    PubMed Central

    Armand, Mehran; Armiger, Robert S.; Kutzer, Michael D.; Basafa, Ehsan; Kazanzides, Peter; Taylor, Russell H.

    2012-01-01

    Intraoperative patient registration may significantly affect the outcome of image-guided surgery (IGS). Image-based registration approaches have several advantages over the currently dominant point-based direct contact methods and are used in some industry solutions in image-guided radiation therapy with fixed X-ray gantries. However, technical challenges including geometric calibration and computational cost have precluded their use with mobile C-arms for IGS. We propose a 2D/3D registration framework for intraoperative patient registration using a conventional mobile X-ray imager combining fiducial-based C-arm tracking and graphics processing unit (GPU)-acceleration. The two-stage framework 1) acquires X-ray images and estimates relative pose between the images using a custom-made in-image fiducial, and 2) estimates the patient pose using intensity-based 2D/3D registration. Experimental validations using a publicly available gold standard dataset, a plastic bone phantom and cadaveric specimens have been conducted. The mean target registration error (mTRE) was 0.34 ± 0.04 mm (success rate: 100%, registration time: 14.2 s) for the phantom with two images 90° apart, and 0.99 ± 0.41 mm (81%, 16.3 s) for the cadaveric specimen with images 58.5° apart. The experimental results showed the feasibility of the proposed registration framework as a practical alternative for IGS routines. PMID:22113773

  4. Shape-based diffeomorphic registration on hippocampal surfaces using Beltrami holomorphic flow.

    PubMed

    Lui, Lok Ming; Wong, Tsz Wai; Thompson, Paul; Chan, Tony; Gu, Xianfeng; Yau, Shing-Tung

    2010-01-01

    We develop a new algorithm to automatically register hippocampal (HP) surfaces with complete geometric matching, avoiding the need to manually label landmark features. A good registration depends on a reasonable choice of shape energy that measures the dissimilarity between surfaces. In our work, we first propose a complete shape index using the Beltrami coefficient and curvatures, which measures subtle local differences. The proposed shape energy is zero if and only if two shapes are identical up to a rigid motion. We then seek the best surface registration by minimizing the shape energy. We propose a simple representation of surface diffeomorphisms using Beltrami coefficients, which simplifies the optimization process. We then iteratively minimize the shape energy using the proposed Beltrami Holomorphic flow (BHF) method. Experimental results on 212 HP of normal and diseased (Alzheimer's disease) subjects show our proposed algorithm is effective in registering HP surfaces with complete geometric matching. The proposed shape energy can also capture local shape differences between HP for disease analysis. PMID:20879331

  5. SU-C-18A-02: Image-Based Camera Tracking: Towards Registration of Endoscopic Video to CT

    SciTech Connect

    Ingram, S; Rao, A; Wendt, R; Castillo, R; Court, L; Yang, J; Beadle, B

    2014-06-01

    Purpose: Endoscopic examinations are routinely performed on head and neck and esophageal cancer patients. However, these images are underutilized for radiation therapy because there is currently no way to register them to a CT of the patient. The purpose of this work is to develop a method to track the motion of an endoscope within a structure using images from standard clinical equipment. This method will be incorporated into a broader endoscopy/CT registration framework. Methods: We developed a software algorithm to track the motion of an endoscope within an arbitrary structure. We computed frame-to-frame rotation and translation of the camera by tracking surface points across the video sequence and utilizing two-camera epipolar geometry. The resulting 3D camera path was used to recover the surrounding structure via triangulation methods. We tested this algorithm on a rigid cylindrical phantom with a pattern spray-painted on the inside. We did not constrain the motion of the endoscope while recording, and we did not constrain our measurements using the known structure of the phantom. Results: Our software algorithm can successfully track the general motion of the endoscope as it moves through the phantom. However, our preliminary data do not show a high degree of accuracy in the triangulation of 3D point locations. More rigorous data will be presented at the annual meeting. Conclusion: Image-based camera tracking is a promising method for endoscopy/CT image registration, and it requires only standard clinical equipment. It is one of two major components needed to achieve endoscopy/CT registration, the second of which is tying the camera path to absolute patient geometry. In addition to this second component, future work will focus on validating our camera tracking algorithm in the presence of clinical imaging features such as patient motion, erratic camera motion, and dynamic scene illumination.

  6. 3D Assessment of Mandibular Growth Based on Image Registration: A Feasibility Study in a Rabbit Model

    PubMed Central

    Kim, I.; Oliveira, M. E.; Duncan, W. J.; Cioffi, I.; Farella, M.

    2014-01-01

    Background. Our knowledge of mandibular growth mostly derives from cephalometric radiography, which has inherent limitations due to the two-dimensional (2D) nature of measurement. Objective. To assess 3D morphological changes occurring during growth in a rabbit mandible. Methods. Serial cone-beam computerised tomographic (CBCT) images were made of two New Zealand white rabbits, at baseline and eight weeks after surgical implantation of 1 mm diameter metallic spheres as fiducial markers. A third animal acted as an unoperated (no implant) control. CBCT images were segmented and registered in 3D (Implant Superimposition and Procrustes Method), and the remodelling pattern described used color maps. Registration accuracy was quantified by the maximal of the mean minimum distances and by the Hausdorff distance. Results. The mean error for image registration was 0.37 mm and never exceeded 1 mm. The implant-based superimposition showed most remodelling occurred at the mandibular ramus, with bone apposition posteriorly and vertical growth at the condyle. Conclusion. We propose a method to quantitatively describe bone remodelling in three dimensions, based on the use of bone implants as fiducial markers and CBCT as imaging modality. The method is feasible and represents a promising approach for experimental studies by comparing baseline growth patterns and testing the effects of growth-modification treatments. PMID:24527442

  7. Lesion registration for longitudinal disease tracking in an imaging informatics-based multiple sclerosis eFolder

    NASA Astrophysics Data System (ADS)

    Ma, Kevin; Liu, Joseph; Zhang, Xuejun; Lerner, Alex; Shiroishi, Mark; Amezcua, Lilyana; Liu, Brent

    2016-03-01

    We have designed and developed a multiple sclerosis eFolder system for patient data storage, image viewing, and automatic lesion quantification results stored in DICOM-SR format. The web-based system aims to be integrated in DICOM-compliant clinical and research environments to aid clinicians in patient treatments and data analysis. The system needs to quantify lesion volumes, identify and register lesion locations to track shifts in volume and quantity of lesions in a longitudinal study. In order to perform lesion registration, we have developed a brain warping and normalizing methodology using Statistical Parametric Mapping (SPM) MATLAB toolkit for brain MRI. Patients' brain MR images are processed via SPM's normalization processes, and the brain images are analyzed and warped according to the tissue probability map. Lesion identification and contouring are completed by neuroradiologists, and lesion volume quantification is completed by the eFolder's CAD program. Lesion comparison results in longitudinal studies show key growth and active regions. The results display successful lesion registration and tracking over a longitudinal study. Lesion change results are graphically represented in the web-based user interface, and users are able to correlate patient progress and changes in the MRI images. The completed lesion and disease tracking tool would enable the eFolder to provide complete patient profiles, improve the efficiency of patient care, and perform comprehensive data analysis through an integrated imaging informatics system.

  8. An efficient nano-based theranostic system for multi-modal imaging-guided photothermal sterilization in gastrointestinal tract.

    PubMed

    Liu, Zhen; Liu, Jianhua; Wang, Rui; Du, Yingda; Ren, Jinsong; Qu, Xiaogang

    2015-07-01

    Since understanding the healthy status of gastrointestinal tract (GI tract) is of vital importance, clinical implementation for GI tract-related disease have attracted much more attention along with the rapid development of modern medicine. Here, a multifunctional theranostic system combining X-rays/CT/photothermal/photoacoustic mapping of GI tract and imaging-guided photothermal anti-bacterial treatment is designed and constructed. PEGylated W18O49 nanosheets (PEG-W18O49) are created via a facile solvothermal method and an in situ probe-sonication approach. In terms of excellent colloidal stability, low cytotoxicity, and neglectable hemolysis of PEG-W18O49, we demonstrate the first example of high-performance four-modal imaging of GI tract by using these nanosheets as contrast agents. More importantly, due to their intrinsic absorption of NIR light, glutaraldehyde-modified PEG-W18O49 are successfully applied as fault-free targeted photothermal agents for imaging-guided killing of bacteria on a mouse infection model. Critical to pre-clinical and clinical prospects, long-term toxicity is further investigated after oral administration of these theranostic agents. These kinds of tungsten-based nanomaterials exhibit great potential as multi-modal contrast agents for directed visualization of GI tract and anti-bacterial agents for phothothermal sterilization. PMID:25934293

  9. Refractive index sensitivity characteristics near the dispersion turning point of the multimode microfiber-based Mach-Zehnder interferometer.

    PubMed

    Luo, Haipeng; Sun, Qizhen; Li, Xiaolei; Yan, Zhijun; Li, Yanpeng; Liu, Deming; Zhang, Lin

    2015-11-01

    The turning point of the refractive index (RI) sensitivity based on the multimode microfiber (MMMF) in-line Mach-Zehnder interferometer (MZI) is observed. By tracking the resonant wavelength shift of the MZI generated between the HE(11) and HE(12) modes in the MMMF, the surrounding RI (SRI) could be detected. Theoretical analysis demonstrates that the RI sensitivity will reach ±∞ on either side of the turning point due to the group effective RI difference (G) approaching zero. Significantly, the positive sensitivity exists in a very wide fiber diameter range, while the negative sensitivity can be achieved in a narrow diameter range of only 0.3 μm. Meanwhile, the experimental sensitivities and variation trend at different diameters exhibit high consistency with the theoretical results. High RI sensitivity of 10777.8 nm/RIU (RI unit) at the fiber diameter of 4.6 μm and the RI around 1.3334 is realized. The discovery of the sensitivity turning points has great significance on trace detection due to the possibility of ultrahigh RI sensitivity. PMID:26512514

  10. Multimodal Physiotherapy Based on a Biobehavioral Approach as a Treatment for Chronic Tension-Type Headache: A Case Report

    PubMed Central

    Beltran-Alacreu, Hector; Lopez-de-Uralde-Villanueva, Ibai; La Touche, Roy

    2015-01-01

    Introduction: Tension-type headache (TTH) is the most common primary headache affecting the general population, which is characterized by bilateral headache and mild to moderate pain. This disorder causes high levels of disability and recent scientific evidence suggests that manual therapy (MT) and therapeutic exercise are effective in reducing medication intake and decreasing the frequency and intensity of headaches in patients with TTH. Case Presentation: A 34-year-old woman was known to have chronic TTH. Initially, the patient presented moderate headaches 5 days per week, mechanical neck pain and no positive response to analgesics. A battery of self-reports was given to the patient to assess disability (using the Spanish versions of the Headache Impact Test-6 and the neck disability index), pain (visual analogue scale) and psychosocial issues (Spanish version of the pain catastrophizing scale) involved in the headaches. All measurements were taken four times during 161 days. Eleven sessions of treatment including MT, motor control therapeutic exercise (MCTE) and therapeutic patient education (TPE) were applied. Conclusions: This biobehavioral-based multimodal physical rehabilitation treatment combining MT, TPE and MCTE produced a substantial reduction in pain intensity, pain catastrophizing, disability and the impact of headaches on patient’s life. PMID:26705532

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

    PubMed Central

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

    2014-01-01

    Purpose: The technological advances in real-time ultrasound image guidance for high-dose-rate (HDR) prostate brachytherapy have placed this treatment modality at the forefront of innovation in cancer radiotherapy. Prostate HDR treatment often involves placing the HDR catheters (needles) into the prostate gland under the transrectal ultrasound (TRUS) guidance, then generating a radiation treatment plan based on CT prostate images, and subsequently delivering high dose of radiation through these catheters. The main challenge for this HDR procedure is to accurately segment the prostate volume in the CT images for the radiation treatment planning. In this study, the authors propose a novel approach that integrates the prostate volume from 3D TRUS images into the treatment planning CT images to provide an accurate prostate delineation for prostate HDR treatment. Methods: The authors’ approach requires acquisition of 3D TRUS prostate images in the operating room right after the HDR catheters are inserted, which takes 1–3 min. These TRUS images are used to create prostate contours. The HDR catheters are reconstructed from the intraoperative TRUS and postoperative CT images, and subsequently used as landmarks for the TRUS–CT image fusion. After TRUS–CT fusion, the TRUS-based prostate volume is deformed to the CT images for treatment planning. This method was first validated with a prostate-phantom study. In addition, a pilot study of ten patients undergoing HDR prostate brachytherapy was conducted to test its clinical feasibility. The accuracy of their approach was assessed through the locations of three implanted fiducial (gold) markers, as well as T2-weighted MR prostate images of patients. Results: For the phantom study, the target registration error (TRE) of gold-markers was 0.41 ± 0.11 mm. For the ten patients, the TRE of gold markers was 1.18 ± 0.26 mm; the prostate volume difference between the authors’ approach and the MRI-based volume was 7.28% ± 0

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

    SciTech Connect

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

    2014-11-01

    Purpose: The technological advances in real-time ultrasound image guidance for high-dose-rate (HDR) prostate brachytherapy have placed this treatment modality at the forefront of innovation in cancer radiotherapy. Prostate HDR treatment often involves placing the HDR catheters (needles) into the prostate gland under the transrectal ultrasound (TRUS) guidance, then generating a radiation treatment plan based on CT prostate images, and subsequently delivering high dose of radiation through these catheters. The main challenge for this HDR procedure is to accurately segment the prostate volume in the CT images for the radiation treatment planning. In this study, the authors propose a novel approach that integrates the prostate volume from 3D TRUS images into the treatment planning CT images to provide an accurate prostate delineation for prostate HDR treatment. Methods: The authors’ approach requires acquisition of 3D TRUS prostate images in the operating room right after the HDR catheters are inserted, which takes 1–3 min. These TRUS images are used to create prostate contours. The HDR catheters are reconstructed from the intraoperative TRUS and postoperative CT images, and subsequently used as landmarks for the TRUS–CT image fusion. After TRUS–CT fusion, the TRUS-based prostate volume is deformed to the CT images for treatment planning. This method was first validated with a prostate-phantom study. In addition, a pilot study of ten patients undergoing HDR prostate brachytherapy was conducted to test its clinical feasibility. The accuracy of their approach was assessed through the locations of three implanted fiducial (gold) markers, as well as T2-weighted MR prostate images of patients. Results: For the phantom study, the target registration error (TRE) of gold-markers was 0.41 ± 0.11 mm. For the ten patients, the TRE of gold markers was 1.18 ± 0.26 mm; the prostate volume difference between the authors’ approach and the MRI-based volume was 7.28% ± 0

  13. Radiolabeled Nanoparticles for Multimodality Tumor Imaging

    PubMed Central

    Xing, Yan; Zhao, Jinhua; Conti, Peter S.; Chen, Kai

    2014-01-01

    Each imaging modality has its own unique strengths. Multimodality imaging, taking advantages of strengths from two or more imaging modalities, can provide overall structural, functional, and molecular information, offering the prospect of improved diagnostic and therapeutic monitoring abilities. The devices of molecular imaging with multimodality and multifunction are of great value for cancer diagnosis and treatment, and greatly accelerate the development of radionuclide-based multimodal molecular imaging. Radiolabeled nanoparticles bearing intrinsic properties have gained great interest in multimodality tumor imaging over the past decade. Significant breakthrough has been made toward the development of various radiolabeled nanoparticles, which can be used as novel cancer diagnostic tools in multimodality imaging systems. It is expected that quantitative multimodality imaging with multifunctional radiolabeled nanoparticles will afford accurate and precise assessment of biological signatures in cancer in a real-time manner and thus, pave the path towards personalized cancer medicine. This review addresses advantages and challenges in developing multimodality imaging probes by using different types of nanoparticles, and summarizes the recent advances in the applications of radiolabeled nanoparticles for multimodal imaging of tumor. The key issues involved in the translation of radiolabeled nanoparticles to the clinic are also discussed. PMID:24505237

  14. A multiple-image-based method to evaluate the performance of deformable image registration in the pelvis.

    PubMed

    Saleh, Ziad; Thor, Maria; Apte, Aditya P; Sharp, Gregory; Tang, Xiaoli; Veeraraghavan, Harini; Muren, Ludvig; Deasy, Joseph

    2016-08-21

    Deformable image registration (DIR) is essential for adaptive radiotherapy (RT) for tumor sites subject to motion, changes in tumor volume, as well as changes in patient normal anatomy due to weight loss. Several methods have been published to evaluate DIR-related uncertainties but they are not widely adopted. The aim of this study was, therefore, to evaluate intra-patient DIR for two highly deformable organs-the bladder and the rectum-in prostate cancer RT using a quantitative metric based on multiple image registration, the distance discordance metric (DDM). Voxel-by-voxel DIR uncertainties of the bladder and rectum were evaluated using DDM on weekly CT scans of 38 subjects previously treated with RT for prostate cancer (six scans/subject). The DDM was obtained from group-wise B-spline registration of each patient's collection of repeat CT scans. For each structure, registration uncertainties were derived from DDM-related metrics. In addition, five other quantitative measures, including inverse consistency error (ICE), transitivity error (TE), Dice similarity (DSC) and volume ratios between corresponding structures from pre- and post- registered images were computed and compared with the DDM. The DDM varied across subjects and structures; DDMmean of the bladder ranged from 2 to 13 mm and from 1 to 11 mm for the rectum. There was a high correlation between DDMmean of the bladder and the rectum (Pearson's correlation coefficient, R p  =  0.62). The correlation between DDMmean and the volume ratios post-DIR was stronger (R p  =  0.51; 0.68) than the correlation with the TE (bladder: R p  =  0.46; rectum: R p  =  0.47), or the ICE (bladder: R p  =  0.34; rectum: R p  =  0.37). There was a negative correlation between DSC and DDMmean of both the bladder (R p  =  -0.23) and the rectum (R p  =  -0.63). The DDM uncertainty metric indicated considerable DIR variability across subjects and structures. Our

  15. Motion tracking in the liver: Validation of a method based on 4D ultrasound using a nonrigid registration technique

    SciTech Connect

    Vijayan, Sinara; Klein, Stefan; Hofstad, Erlend Fagertun; Langø, Tho