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Sample records for based multimodal registration

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

    PubMed

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  3. 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).

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

    PubMed

    Bhattacharya, Mahua; Das, Arpita

    2011-01-01

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

  5. Image registration techniques for multimodal sensors

    NASA Astrophysics Data System (ADS)

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

    2002-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    PubMed

    Steger, Sebastian; Wesarg, Stefan

    2012-01-01

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

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

    SciTech Connect

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

    2014-06-15

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

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

    PubMed

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

    2015-01-01

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

  12. 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

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

    PubMed

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

    2013-04-01

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

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

    PubMed

    Spiclin, Ziga; Likar, Bostjan; Pernus, Franjo

    2012-05-01

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

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

    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

  16. 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

  17. 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

  18. 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

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

    NASA Astrophysics Data System (ADS)

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

    2008-03-01

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

  20. 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.

  1. 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.

  2. 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.

  3. Registration of multimodal brain images: some experimental results

    NASA Astrophysics Data System (ADS)

    Chen, Hua-mei; Varshney, Pramod K.

    2002-03-01

    Joint histogram of two images is required to uniquely determine the mutual information between the two images. It has been pointed out that, under certain conditions, existing joint histogram estimation algorithms like partial volume interpolation (PVI) and linear interpolation may result in different types of artifact patterns in the MI based registration function by introducing spurious maxima. As a result, the artifacts may hamper the global optimization process and limit registration accuracy. In this paper we present an extensive study of interpolation-induced artifacts using simulated brain images and show that similar artifact patterns also exist when other intensity interpolation algorithms like cubic convolution interpolation and cubic B-spline interpolation are used. A new joint histogram estimation scheme named generalized partial volume estimation (GPVE) is proposed to eliminate the artifacts. A kernel function is involved in the proposed scheme and when the 1st order B-spline is chosen as the kernel function, it is equivalent to the PVI. A clinical brain image database furnished by Vanderbilt University is used to compare the accuracy of our algorithm with that of PVI. Our experimental results show that the use of higher order kernels can effectively remove the artifacts and, in cases when MI based registration result suffers from the artifacts, registration accuracy can be improved significantly.

  4. 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.

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

    PubMed Central

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

    2016-01-01

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

  6. 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.

  7. 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.

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

    PubMed Central

    2013-01-01

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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

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

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  15. 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.

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

    PubMed

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

    2016-07-01

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

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed Central

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

    2016-01-01

    Atherosclerosis is among the leading causes of death and disability. Combining information from multi-modal vascular images is an effective and efficient way to diagnose and monitor atherosclerosis, in which image registration is a key technique. In this paper a feature-based registration algorithm, Two-step Auto-labeling Conditional Iterative Closed Points (TACICP) algorithm, is proposed to align three-dimensional carotid image datasets from ultrasound (US) and magnetic resonance (MR). Based on 2D segmented contours, a coarse-to-fine strategy is employed with two steps: rigid initialization step and non-rigid refinement step. Conditional Iterative Closest Points (CICP) algorithm is given in rigid initialization step to obtain the robust rigid transformation and label configurations. Then the labels and CICP algorithm with non-rigid thin-plate-spline (TPS) transformation model is introduced to solve non-rigid carotid deformation between different body positions. The results demonstrate that proposed TACICP algorithm has achieved an average registration error of less than 0.2mm with no failure case, which is superior to the state-of-the-art feature-based methods. PMID:26881433

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

    Li, Zhenhua; Xu, Songsong; Guo, Xiaoyan

    2014-01-01

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

  2. A MULTICORE BASED PARALLEL IMAGE REGISTRATION METHOD

    PubMed Central

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

    2012-01-01

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

  3. SAR image registration based on Susan algorithm

    NASA Astrophysics Data System (ADS)

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

    2011-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

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

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

    NASA Astrophysics Data System (ADS)

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

    2000-06-01

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

  6. Canny edge-based deformable image registration

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  7. 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

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

    PubMed

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

    2014-10-14

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

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

    PubMed

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

    2016-11-29

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

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

    ERIC Educational Resources Information Center

    AL-Bastaki, Yousif; Al-Ajeeli, Abid

    2005-01-01

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

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

    PubMed

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

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2003-09-01

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

  13. 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.

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

    PubMed Central

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

    2007-01-01

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

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. Smart automotive bumper based on a multimode optical fiber

    NASA Astrophysics Data System (ADS)

    Meyrueis, Patrick; Kress, Bernard; Fischer, Sylvain

    2007-09-01

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

  20. Registration-based interpolation applied to cardiac MRI

    NASA Astrophysics Data System (ADS)

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

    2010-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

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

    PubMed

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

    2014-11-21

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

  3. A new frame-based registration algorithm

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

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

    PubMed

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

    2017-01-01

    An automated method for registering B-mode ultrasound (US) and magnetic resonance imaging (MRI) of the carotid arteries is proposed. The registration uses geometric features, namely, lumen centerlines and lumen segmentations, which are extracted fully automatically from the images after manual annotation of three seed points in US and MRI. The registration procedure starts with alignment of the lumen centerlines using a point-based registration algorithm. The resulting rigid transformation is used to initialize a rigid and subsequent non-rigid registration procedure that jointly aligns centerlines and segmentations by minimizing a weighted sum of the Euclidean distance between centerlines and the dissimilarity between segmentations. The method was evaluated in 28 carotid arteries from eight patients and six healthy volunteers. First, the automated US lumen segmentation method was validated and optimized in a cross-validation experiment. Next, the effect of the weighting parameter of the proposed registration dissimilarity metric and the control point spacing in the non-rigid registration was evaluated. Finally, the proposed registration method was evaluated in comparison to an existing intensity-and-point-based method, a registration using only the centerlines and a registration using manual US lumen segmentations. Registration accuracy was measured in terms of the mean surface distance between manual US segmentations and the registered MRI segmentations. The average mean surface distance was 0.78 ± 0.34 mm for all subjects, 0.65 ± 0.09 mm for healthy volunteers and 0.87 ± 0.42 mm for patients. The results for the complete set were significantly better (Wilcoxon test, p < 0.01) than the results for the intensity-and-point-based method and the centerline-based registration method. We conclude that the proposed method can robustly and accurately register US and MR images of the carotid artery, allowing multimodal analysis of the carotid plaque to improve

  5. 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.

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

    PubMed

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

    2009-05-01

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

  7. Multimodal sensing-based camera applications

    NASA Astrophysics Data System (ADS)

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

    2011-02-01

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

  8. SAR image registration based on SIFT and MSA

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  9. 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.

  10. 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.

  11. Automated retina identification based on multiscale elastic registration.

    PubMed

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

    2016-12-01

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

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

    PubMed

    Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo

    2005-01-01

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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

    Kirby, Richard; Whitaker, Ross

    2016-09-01

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

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

    PubMed

    Verhagen, Justus V

    2007-02-01

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

  16. 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

  17. 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.

  18. 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.

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

    PubMed

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

    2009-08-01

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

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

    PubMed

    Cižmár, Tomáš; Dholakia, Kishan

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Gass, Tobias; Szekely, Gabor; Goksel, Orcun

    2014-03-01

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

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

    PubMed

    Liang, J; Yan, D

    2003-08-01

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

  3. Optical mode switch based on multimode interference couplers

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  4. 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.

  5. 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

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

    NASA Astrophysics Data System (ADS)

    Lamy, Julien; Summers, Ronald M.

    2007-03-01

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

  7. 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.

  8. 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

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

    PubMed Central

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

    2015-01-01

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

  10. 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.

  11. 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

  12. Silicon CMOS-based vertical multimode interference optical taps

    NASA Astrophysics Data System (ADS)

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

    2001-12-01

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

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

    ERIC Educational Resources Information Center

    Huang, Shin-ying

    2015-01-01

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

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

    PubMed

    Jiang, T; Li, Y

    1997-01-01

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

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

    PubMed Central

    Verhagen, Justus V.

    2007-01-01

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

  16. Optimization Model for Web Based Multimodal Interactive Simulations.

    PubMed

    Halic, Tansel; Ahn, Woojin; De, Suvranu

    2015-07-15

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

  17. Multimodal computational microscopy based on transport of intensity equation

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  18. Optimization Model for Web Based Multimodal Interactive Simulations

    PubMed Central

    Halic, Tansel; Ahn, Woojin; De, Suvranu

    2015-01-01

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

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

    PubMed

    Liu, Yuan; Dawant, Benoit M

    2016-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

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

    PubMed

    Xu, Peng; Yao, Dezhong; Luo, Fen

    2005-08-01

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

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

    PubMed Central

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

    2014-01-01

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

  3. 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

  4. Multimode fiber focusing lens based on plasmonic structures

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  7. 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.

  8. 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.

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

    NASA Astrophysics Data System (ADS)

    Marusarz, Ronald K.; Sayeh, Mohammad R.

    2001-01-01

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

  10. Motion compensation by registration-based catheter tracking

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  11. 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.

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

    PubMed Central

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

    2015-01-01

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

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

    SciTech Connect

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

    1999-11-08

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

  14. 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.

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

    ERIC Educational Resources Information Center

    Freeman, Raoul J.

    1983-01-01

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

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

    SciTech Connect

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

    2015-06-15

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

  17. Point-based rigid-body registration using an unscented Kalman filter.

    PubMed

    Moghari, Mehdi Hedjazi; Abolmaesumi, Purang

    2007-12-01

    We present and validate a novel registration algorithm mapping two data sets, generated from a rigid object, in the presence of Gaussian noise. The proposed method is based on the Unscented Kalman Filter (UKF) algorithm that is generally employed for analyzing nonlinear systems corrupted by additive Gaussian noise. First, we employ our proposed registration algorithm to fit two randomly generated data sets in the presence of isotropic Gaussian noise, when the corresponding points between the two data sets are assumed to be known. Then, we extend the registration method to the case where the data (with known correspondences) is stimulated by anisotropic Gaussian noise. The new registration method not only reliably converges to the correct registration solution, but it also estimates the variance, as a confidence measure, for each of the estimated registration transformation parameters. Furthermore, we employ the proposed registration algorithm for rigid-body, point-based registration where corresponding points between two registering data sets are unknown. The algorithm is tested on point data sets which are garnered from a pelvic cadaver and a scaphoid bone phantom by means of computed tomography (CT) and tracked free-hand ultrasound imaging. The collected 3-D points in the ultrasound frame are registered to the 3-D meshes in the CT frame by using the proposed and the standard Iterative Closest Points (ICP) registration algorithms. Experimental results demonstrate that our proposed method significantly outperforms the ICP registration algorithm in the presence of additive Gaussian noise. It is also shown that the proposed registration algorithm is more robust than the ICP registration algorithm in terms of outliers in data sets and initial misalignment between the two data sets.

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

    PubMed Central

    Wang, Yangping; Wang, Song

    2016-01-01

    The nonrigid registration algorithm based on B-spline Free-Form Deformation (FFD) plays a key role and is widely applied in medical image processing due to the good flexibility and robustness. However, it requires a tremendous amount of computing time to obtain more accurate registration results especially for a large amount of medical image data. To address the issue, a parallel nonrigid registration algorithm based on B-spline is proposed in this paper. First, the Logarithm Squared Difference (LSD) is considered as the similarity metric in the B-spline registration algorithm to improve registration precision. After that, we create a parallel computing strategy and lookup tables (LUTs) to reduce the complexity of the B-spline registration algorithm. As a result, the computing time of three time-consuming steps including B-splines interpolation, LSD computation, and the analytic gradient computation of LSD, is efficiently reduced, for the B-spline registration algorithm employs the Nonlinear Conjugate Gradient (NCG) optimization method. Experimental results of registration quality and execution efficiency on the large amount of medical images show that our algorithm achieves a better registration accuracy in terms of the differences between the best deformation fields and ground truth and a speedup of 17 times over the single-threaded CPU implementation due to the powerful parallel computing ability of Graphics Processing Unit (GPU). PMID:28053653

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

    PubMed

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

    2016-01-01

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

  20. 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.

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

    NASA Astrophysics Data System (ADS)

    Li, Enbang

    2008-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

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

    PubMed

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

    2010-11-08

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

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

    NASA Astrophysics Data System (ADS)

    Fukano, Hideki; Kushida, Yohei; Taue, Shuji

    2015-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  8. 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…

  9. 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…

  10. 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…

  11. 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.…

  12. 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…

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

    NASA Astrophysics Data System (ADS)

    Li, Yao; Eichmann, George

    1987-02-01

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

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

    ERIC Educational Resources Information Center

    Han, Yi; Zukerman, Ingrid

    1997-01-01

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

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2012-01-01

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

  17. 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.

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

    SciTech Connect

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

    2012-01-15

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

  19. A CNN based Hybrid approach towards automatic image registration

    NASA Astrophysics Data System (ADS)

    Arun, Pattathal V.; Katiyar, Sunil K.

    2013-06-01

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

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

    PubMed

    Busayara, Sata; Zrimec, Tatjana

    2006-01-01

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

  1. 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.

  2. 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%.

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

    PubMed

    Selmi, Sonia Y; Promayon, Emmanuel; Troccaz, Jocelyne

    2016-08-01

    The aim of this paper is to describe a 3D-2D ultrasound feature-based registration method for navigated prostate biopsy and its first results obtained on patient data. A system combining a low-cost tracking system and a 3D-2D registration algorithm was designed. The proposed 3D-2D registration method combines geometric and image-based distances. After extracting features from ultrasound images, 3D and 2D features within a defined distance are matched using an intensity-based function. The results are encouraging and show acceptable errors with simulated transforms applied on ultrasound volumes from real patients.

  4. A Multistage Approach for Image Registration.

    PubMed

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

    2016-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

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

  6. 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.

  7. 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

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

    DTIC Science & Technology

    2003-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

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

    PubMed

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

    2014-11-21

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

  11. 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.

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

    NASA Astrophysics Data System (ADS)

    Makrogiannis, Sokratis; Bourbakis, Nikolaos G.

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Shostka, N. V.

    2011-06-01

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

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

    PubMed

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

    2013-09-01

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

  15. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

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

  16. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

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

  17. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

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

  18. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

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

  19. 47 CFR 64.611 - Internet-based TRS registration.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

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

    PubMed

    Mahapatra, Dwarikanath; Sun, Ying

    2012-01-01

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

  3. 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.

  4. 1×2 Multimode interference couplers based on semiconductor hollow waveguides formed from omnidirectional reflectors

    NASA Astrophysics Data System (ADS)

    Lo, Shih-Shou; Chen, Chii-Chang

    2007-07-01

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

  5. 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

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

    PubMed

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

    2014-07-01

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

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

    PubMed

    Chernyak, Dimitri A

    2005-12-01

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

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

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

    PubMed

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

    2013-12-01

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

  11. 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.

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

    PubMed

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

    2005-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Gao, Yanfei; Wang, Hengyou; Bian, Xiaoning

    2015-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

    Fischer, Bernd; Modersitzki, Jan

    2003-05-01

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

  17. 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.

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

    PubMed

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

    2013-03-01

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

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

    PubMed

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

    2011-05-07

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

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

    PubMed

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

    2015-05-18

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

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

    NASA Astrophysics Data System (ADS)

    Kang, Byung Jun; Park, Kang Ryoung

    2009-09-01

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

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

    PubMed

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

    2012-03-01

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

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

    PubMed

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

    2008-03-01

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

  4. 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.

  5. 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.

  6. 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.

  7. Nonunity permeability in metamaterial-based GaInAsP/InP multimode interferometers.

    PubMed

    Amemiya, T; Shindo, T; Takahashi, D; Myoga, S; Nishiyama, N; Arai, S

    2011-06-15

    We demonstrated an InP-based optical multimode interferometer (MMI) combined with metamaterials consisting of minute split-ring resonators (SRRs) arrayed on the MMI. The MMI could operate at an optical fiber communication wavelength of 1.5 μm. Magnetic resonance occurred between the SRR metamaterial and light at 1.5 μm, and the relative permeability of the metamaterial increased to 2.4 around this wavelength. This result shows that it is possible to use new materials with nonunity permeability to construct semiconductor-based photonic devices.

  8. 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.

  9. 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.

  10. Vision based tunnel inspection using non-rigid registration

    NASA Astrophysics Data System (ADS)

    Badshah, Amir; Ullah, Shan; Shahzad, Danish

    2015-04-01

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

  11. 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.

  12. A graph-based approach for the retrieval of multi-modality medical images.

    PubMed

    Kumar, Ashnil; Kim, Jinman; Wen, Lingfeng; Fulham, Michael; Feng, Dagan

    2014-02-01

    In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging. The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours and organs. These attributes and relationships, which are used for tumour staging and classification, can be formulated as a graph. It has been demonstrated that graph-based methods have high accuracy for retrieval by spatial similarity. However, naïvely representing all relationships on a complete graph obscures the structure of the tumour-anatomy relationships. We propose a new graph structure derived from complete graphs that structurally constrains the edges connected to tumour vertices based upon the spatial proximity of tumours and organs. This enables retrieval on the basis of tumour localisation. We also present a similarity matching algorithm that accounts for different feature sets for graph elements from different imaging modalities. Our method emphasises the relationships between a tumour and related organs, while still modelling patient-specific anatomical variations. Constraining tumours to related anatomical structures improves the discrimination potential of graphs, making it easier to retrieve similar images based on tumour location. We evaluated our retrieval methodology on a dataset of clinical PET-CT volumes. Our results showed that our method enabled the retrieval of multi-modality images using spatial features. Our graph-based retrieval algorithm achieved a higher precision than several other retrieval techniques: gray-level histograms as well as state

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  14. 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.

  15. 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.

  16. 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

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

    PubMed

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

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

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

  19. 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.

  20. Automatic sub-volume registration by probabilistic random search

    NASA Astrophysics Data System (ADS)

    Han, Jingfeng; Qiao, Min; Hornegger, Joachim; Kuwert, Torsten; Bautz, Werner; Römer, Wolfgang

    2006-03-01

    Registration of an individual's image data set to an anatomical atlas provides valuable information to the physician. In many cases, the individual image data sets are partial data, which may be mapped to one part or one organ of the entire atlas data. Most of the existing intensity based image registration approaches are designed to align images of the entire view. When they are applied to the registration with partial data, a manual pre-registration is usually required. This paper proposes a fully automatic approach to the registration of the incomplete image data to an anatomical atlas. The spatial transformations are modelled as any parametric functions. The proposed method is built upon a random search mechanism, which allows to find the optimal transformation randomly and globally even when the initialization is not ideal. It works more reliably than the existing methods for the partial data registration because it successfully overcomes the local optimum problem. With appropriate similarity measures, this framework is applicable to both mono-modal and multi-modal registration problems with partial data. The contribution of this work is the description of the mathematical framework of the proposed algorithm and the implementation of the related software. The medical evaluation on the MRI data and the comparison of the proposed method with different existing registration methods show the feasibility and superiority of the proposed method.

  1. 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.

  2. 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.

  3. 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.

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

    PubMed Central

    Bossa, Matias; Zacur, Ernesto; Olmos, Salvador

    2010-01-01

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

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

    PubMed

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

    2003-02-01

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

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

    PubMed Central

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

    2010-01-01

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

  7. Atlas-based automatic mouse brain image segmentation revisited: model complexity vs. image registration.

    PubMed

    Bai, Jordan; Trinh, Thi Lan Huong; Chuang, Kai-Hsiang; Qiu, Anqi

    2012-07-01

    Although many atlas-based segmentation methods have been developed and validated for the human brain, limited work has been done for the mouse brain. This paper investigated roles of image registration and segmentation model complexity in the mouse brain segmentation. We employed four segmentation models [single atlas, multiatlas, simultaneous truth and performance level estimation (STAPLE) and Markov random field (MRF) via four different image registration algorithms (affine, B-spline free-form deformation (FFD), Demons and large deformation diffeomorphic metric mapping (LDDMM)] for delineating 19 structures from in vivo magnetic resonance microscopy images. We validated their accuracies against manual segmentation. Our results revealed that LDDMM outperformed Demons, FFD and affine in any of the segmentation models. Under the same registration, increasing segmentation model complexity from single atlas to multiatlas, STAPLE or MRF significantly improved the segmentation accuracy. Interestingly, the multiatlas-based segmentation using nonlinear registrations (FFD, Demons and LDDMM) had similar performance to their STAPLE counterparts, while they both outperformed their MRF counterparts. Furthermore, when the single-atlas affine segmentation was used as reference, the improvement due to nonlinear registrations (FFD, Demons and LDDMM) in the single-atlas segmentation model was greater than that due to increasing model complexity (multiatlas, STAPLE and MRF affine segmentation). Hence, we concluded that image registration plays a more crucial role in the atlas-based automatic mouse brain segmentation as compared to model complexity. Multiple atlases with LDDMM can best improve the segmentation accuracy in the mouse brain among all segmentation models tested in this study.

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

    PubMed

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

    2016-09-15

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

  9. 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

  10. 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.

  11. Effect of constructional parameters on the performance of a surface plasmon resonance sensor based on a multimode polymer optical fiber.

    PubMed

    Gasior, Katarzyna; Martynkien, Tadeusz; Urbanczyk, Waclaw

    2014-12-10

    We experimentally studied the influence of different constructional parameters on the performance of surface plasmon resonance (SPR) sensors based on a commercially available polymer step-index multimode fiber. For the first time, to the best of our knowledge, we experimentally investigated the influence of polishing depth on the characteristics of SPR sensors based on a straight multimode fiber. We also examined the impact of sensing length on the spectral position and strength of the SPR in side-polished straight fibers. To clarify literature contradictions concerning the effect of fiber bending on SPR, we experimentally investigated the performance of U-bent SPR sensing probes based on multimode fibers. We have shown that the SPR can be significantly amplified by bending the polymer fiber with stripped cladding. We also demonstrated that the side-polishing of U-bent sensing probes has little impact on their performance.

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

    PubMed

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

    2016-12-30

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

  13. 3D point cloud registration based on the assistant camera and Harris-SIFT

    NASA Astrophysics Data System (ADS)

    Zhang, Yue; Yu, HongYang

    2016-07-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

  16. 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.

  17. 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.

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

    PubMed

    Liao, Shu; Chung, Albert C S

    2010-01-01

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

  19. Image Quality Improvement in Adaptive Optics Scanning Laser Ophthalmoscopy Assisted Capillary Visualization Using B-spline-based Elastic Image Registration

    PubMed Central

    Uji, Akihito; Ooto, Sotaro; Hangai, Masanori; Arichika, Shigeta; Yoshimura, Nagahisa

    2013-01-01

    Purpose To investigate the effect of B-spline-based elastic image registration on adaptive optics scanning laser ophthalmoscopy (AO-SLO)-assisted capillary visualization. Methods AO-SLO videos were acquired from parafoveal areas in the eyes of healthy subjects and patients with various diseases. After nonlinear image registration, the image quality of capillary images constructed from AO-SLO videos using motion contrast enhancement was compared before and after B-spline-based elastic (nonlinear) image registration performed using ImageJ. For objective comparison of image quality, contrast-to-noise ratios (CNRS) for vessel images were calculated. For subjective comparison, experienced ophthalmologists ranked images on a 5-point scale. Results All AO-SLO videos were successfully stabilized by elastic image registration. CNR was significantly higher in capillary images stabilized by elastic image registration than in those stabilized without registration. The average ratio of CNR in images with elastic image registration to CNR in images without elastic image registration was 2.10 ± 1.73, with no significant difference in the ratio between patients and healthy subjects. Improvement of image quality was also supported by expert comparison. Conclusions Use of B-spline-based elastic image registration in AO-SLO-assisted capillary visualization was effective for enhancing image quality both objectively and subjectively. PMID:24265796

  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. 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

  3. Progressive Graph-Based Transductive Learning for Multi-modal Classification of Brain Disorder Disease

    PubMed Central

    Wang, Zhengxia; Zhu, Xiaofeng; Adeli, Ehsan; Zhu, Yingying; Zu, Chen; Nie, Feiping; Shen, Dinggang; Wu, Guorong

    2017-01-01

    Graph-based Transductive Learning (GTL) is a powerful tool in computer-assisted diagnosis, especially when the training data is not sufficient to build reliable classifiers. Conventional GTL approaches first construct a fixed subject-wise graph based on the similarities of observed features (i.e., extracted from imaging data) in the feature domain, and then follow the established graph to propagate the existing labels from training to testing data in the label domain. However, such a graph is exclusively learned in the feature domain and may not be necessarily optimal in the label domain. This may eventually undermine the classification accuracy. To address this issue, we propose a progressive GTL (pGTL) method to progressively find an intrinsic data representation. To achieve this, our pGTL method iteratively (1) refines the subject-wise relationships observed in the feature domain using the learned intrinsic data representation in the label domain, (2) updates the intrinsic data representation from the refined subject-wise relationships, and (3) verifies the intrinsic data representation on the training data, in order to guarantee an optimal classification on the new testing data. Furthermore, we extend our pGTL to incorporate multi-modal imaging data, to improve the classification accuracy and robustness as multi-modal imaging data can provide complementary information. Promising classification results in identifying Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI), and Normal Control (NC) subjects are achieved using MRI and PET data.

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

    PubMed

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

    2015-10-23

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

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

    PubMed Central

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

    2015-01-01

    A novel fiber optic temperature sensor based on a liquid-core multimode interference device is demonstrated. The advantage of such structure is that the thermo-optic coefficient (TOC) of the liquid is at least one order of magnitude larger than that of silica and this, combined with the fact that the TOC of silica and the liquid have opposite signs, provides a liquid-core multimode fiber (MMF) highly sensitive to temperature. Since the refractive index of the liquid can be easily modified, this allows us to control the modal properties of the liquid-core MMF at will and the sensor sensitivity can be easily tuned by selecting the refractive index of the liquid in the core of the device. The maximum sensitivity measured in our experiments is 20 nm/°C in the low-temperature regime up to 60 °C. To the best of our knowledge, to date, this is the largest sensitivity reported for fiber-based MMI temperature sensors. PMID:26512664

  6. Non-invasive tissue diagnostics using a multimodal spectroscopic device based on fiber probe

    NASA Astrophysics Data System (ADS)

    Cicchi, Riccardo; Anand, Suresh; Rossari, Susanna; Sturiale, Alessandro; Giordano, Flavio; De Giorgi, Vincenzo; Maio, Vincenza; Massi, Daniela; Nesi, Gabriella; Buccoliero, Anna Maria; Tonelli, Francesco; Guerrini, Renzo; Pimpinelli, Nicola; Pavone, Francesco Saverio

    2014-05-01

    Two different optical fiber probes for combined Raman and fluorescence spectroscopic measurements were designed, developed and used for tissue diagnostics. Two visible laser diodes were used for fluorescence spectroscopy, whereas a laser diode emitting in the NIR was used for Raman spectroscopy. The two probes were based on fiber bundles with a central multimode optical fiber, used for delivering light to the tissue, and 24 surrounding optical fibers for signal collection. Both fluorescence and Raman spectra were acquired using the same detection unit, based on a cooled CCD camera, connected to a spectrograph. The two probes were successfully employed for diagnosing melanocytic lesions in a good agreement with common routine histology. The obtained results demonstrated that the multimodal approach is crucial for improving diagnostic capabilities. Further investigations were performed on colon and brain tissue samples in order to have a benchmark for diagnosing a broader range of tissue lesions and malignancies. The system presented here can improve diagnostic capabilities on a broad range of tissues and has the potential of being used for endoscopic inspections in the near future.

  7. 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.

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

    PubMed

    Wachinger, Christian; Navab, Nassir

    2013-05-01

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

  9. Bus-based park-and-ride system: a stochastic model on multimodal network with congestion pricing schemes

    NASA Astrophysics Data System (ADS)

    Liu, Zhiyuan; Meng, Qiang

    2014-05-01

    This paper focuses on modelling the network flow equilibrium problem on a multimodal transport network with bus-based park-and-ride (P&R) system and congestion pricing charges. The multimodal network has three travel modes: auto mode, transit mode and P&R mode. A continuously distributed value-of-time is assumed to convert toll charges and transit fares to time unit, and the users' route choice behaviour is assumed to follow the probit-based stochastic user equilibrium principle with elastic demand. These two assumptions have caused randomness to the users' generalised travel times on the multimodal network. A comprehensive network framework is first defined for the flow equilibrium problem with consideration of interactions between auto flows and transit (bus) flows. Then, a fixed-point model with unique solution is proposed for the equilibrium flows, which can be solved by a convergent cost averaging method. Finally, the proposed methodology is tested by a network example.

  10. 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.

  11. Medical image registration using fuzzy theory.

    PubMed

    Pan, Meisen; Tang, Jingtian; Xiong, Qi

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-11-01

    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

  13. Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping

    PubMed Central

    Cui, Tingting; Ji, Shunping; Shan, Jie; Gong, Jianya; Liu, Kejian

    2016-01-01

    For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable. PMID:28042855

  14. Feature-based three-dimensional registration for repetitive geometry in machine vision

    PubMed Central

    Gong, Yuanzheng; Seibel, Eric J.

    2016-01-01

    As an important step in three-dimensional (3D) machine vision, 3D registration is a process of aligning two or multiple 3D point clouds that are collected from different perspectives together into a complete one. The most popular approach to register point clouds is to minimize the difference between these point clouds iteratively by Iterative Closest Point (ICP) algorithm. However, ICP does not work well for repetitive geometries. To solve this problem, a feature-based 3D registration algorithm is proposed to align the point clouds that are generated by vision-based 3D reconstruction. By utilizing texture information of the object and the robustness of image features, 3D correspondences can be retrieved so that the 3D registration of two point clouds is to solve a rigid transformation. The comparison of our method and different ICP algorithms demonstrates that our proposed algorithm is more accurate, efficient and robust for repetitive geometry registration. Moreover, this method can also be used to solve high depth uncertainty problem caused by little camera baseline in vision-based 3D reconstruction.

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

    PubMed

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

    2013-03-13

    This paper presents a novel pipeline for the registration of diffusion tensor images (DTI) with large pathological variations to normal controls based on the use of a novel feature map derived from white matter (WM) fiber tracts. The research presented aims towards an atlas based DTI analysis of subjects with considerable brain pathologies such as tumors or hydrocephalus. In this paper, we propose a novel feature map that is robust against variations in WM fiber tract integrity and use these feature maps to determine a landmark correspondence using a 3D point correspondence algorithm. This correspondence drives a deformation field computed using Gaussian radial basis functions(RBF). This field is employed as an initialization to a standard deformable registration method like demons. We present early preliminary results on the registration of a normal control dataset to a dataset with abnormally enlarged lateral ventricles affected by fatal demyelinating Krabbe disease. The results are analyzed based on a regional tensor matching criterion and a visual assessment of overlap of major WM fiber tracts. While further evaluation and improvements are necessary, the results presented in this paper highlight the potential of our method in handling registration of subjects with severe WM pathology.

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

    NASA Astrophysics Data System (ADS)

    Samavati, Navid; Velec, Michael; Brock, Kristy

    2014-03-01

    Deformable Image Registration (DIR) has been extensively studied over the past two decades due to its essential role in many image-guided interventions. Morfeus is a DIR algorithm that works based on finite element biomechanical modeling. However, Morfeus does not utilize the entire image contrast and features which could potentially lead to a more accurate registration result. A hybrid biomechanical intensity-based method is proposed to investigate this potential benefit. Inhale and exhale 4DCT lung images of 26 patients were initially registered using Morfeus by modeling contact surface between the lungs and the chest cavity. The resulting deformations using Morfeus were refined using a B-spline intensity-based algorithm (Drop, Munich, Germany). Important parameters in Drop including grid spacing, number of pyramids, and regularization coefficient were optimized on 10 randomly-chosen patients (out of 26). The remaining parameters were selected empirically. Target Registration Error (TRE) was calculated by measuring the Euclidean distance of common anatomical points on both images before and after registration. For each patient a minimum of 30 points/lung were used. The Hybrid method resulted in mean+/-SD (90th%) TRE of 1.5+/-1.4 (2.8) mm compared to 3.1+/-2.0 (5.6) using Morfeus and 2.6+/-2.6 (6.2) using Drop alone.

  17. Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping.

    PubMed

    Cui, Tingting; Ji, Shunping; Shan, Jie; Gong, Jianya; Liu, Kejian

    2016-12-31

    For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.

  18. Gradient-based 3D-2D registration of cerebral angiograms

    NASA Astrophysics Data System (ADS)

    Mitrović, Uroš; Markelj, Primož; Likar, Boštjan; Miloševič, Zoran; Pernuš, Franjo

    2011-03-01

    Endovascular treatment of cerebral aneurysms and arteriovenous malformations (AVM) involves navigation of a catheter through the femoral artery and vascular system into the brain and into the aneurysm or AVM. Intra-interventional navigation utilizes digital subtraction angiography (DSA) to visualize vascular structures and X-ray fluoroscopy to localize the endovascular components. Due to the two-dimensional (2D) nature of the intra-interventional images, navigation through a complex three-dimensional (3D) structure is a demanding task. Registration of pre-interventional MRA, CTA, or 3D-DSA images and intra-interventional 2D DSA images can greatly enhance visualization and navigation. As a consequence of better navigation in 3D, the amount of required contrast medium and absorbed dose could be significantly reduced. In the past, development and evaluation of 3D-2D registration methods received considerable attention. Several validation image databases and evaluation criteria were created and made publicly available in the past. However, applications of 3D-2D registration methods to cerebral angiograms and their validation are rather scarce. In this paper, the 3D-2D robust gradient reconstruction-based (RGRB) registration algorithm is applied to CTA and DSA images and analyzed. For the evaluation purposes five image datasets, each comprised of a 3D CTA and several 2D DSA-like digitally reconstructed radiographs (DRRs) generated from the CTA, with accurate gold standard registrations were created. A total of 4000 registrations on these five datasets resulted in mean mTRE values between 0.07 and 0.59 mm, capture ranges between 6 and 11 mm and success rates between 61 and 88% using a failure threshold of 2 mm.

  19. A local descriptor based registration method for multispectral remote sensing images with non-linear intensity differences

    NASA Astrophysics Data System (ADS)

    Ye, Yuanxin; Shan, Jie

    2014-04-01

    Image registration is a crucial step for remote sensing image processing. Automatic registration of multispectral remote sensing images could be challenging due to the significant non-linear intensity differences caused by radiometric variations among such images. To address this problem, this paper proposes a local descriptor based registration method for multispectral remote sensing images. The proposed method includes a two-stage process: pre-registration and fine registration. The pre-registration is achieved using the Scale Restriction Scale Invariant Feature Transform (SR-SIFT) to eliminate the obvious translation, rotation, and scale differences between the reference and the sensed image. In the fine registration stage, the evenly distributed interest points are first extracted in the pre-registered image using the Harris corner detector. Then, we integrate the local self-similarity (LSS) descriptor as a new similarity metric to detect the tie points between the reference and the pre-registered image, followed by a global consistency check to remove matching blunders. Finally, image registration is achieved using a piecewise linear transform. The proposed method has been evaluated with three pairs of multispectral remote sensing images from TM, ETM+, ASTER, Worldview, and Quickbird sensors. The experimental results demonstrate that the proposed method can achieve reliable registration outcome, and the LSS-based similarity metric is robust to non-linear intensity differences among multispectral remote sensing images.

  20. Cross-point analysis for a multimode fiber sensor based on surface plasmon resonance

    NASA Astrophysics Data System (ADS)

    Tsai, Woo-Hu; Tsao, Yu-Chia; Lin, Hong-Yu; Sheu, Bor-Chiou

    2005-09-01

    A novel analysis based on surface plasmon resonance (SPR) with a side-polished multimode fiber and a white-light (halogen light) source is presented. The sensing system is a multimode optical fiber in which half of the core has been polished away and a 40 nm gold layer is deposited on to the polished surface by dc sputter. The SPR dip in the optical spectrum is investigated with an optical spectrum analyzer (OSA). In our SPR fiber sensor, the use of liquids with different refractive indices leads to a shift in the spectral dip in the SPR curve. The cross point (CP) of the two SPR spectra obtained from the refractive-index liquid and the deionized water measurements was observed with the OSA. The CP is shifted sensitively in wavelength from 630to1300 nm relative to a change in the refractive index of the liquid from 1.34 to 1.46. High sensitivities of 1.9×10^-6 refractive-index units (RIUs) in the range of the refractive index of the liquid from 1.40 to 1.44 of 5.7×10^-7 RIUs above the value of 1.44 are proposed and demonstrated in our novel SPR analysis.

  1. 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.

  2. A multimodal wave spectrum-based approach for statistical downscaling of local wave climate

    USGS Publications Warehouse

    Hegermiller, Christie; Antolinez, Jose A A; Rueda, Ana C; Camus, Paula; Perez, Jorge; Erikson, Li; Barnard, Patrick; Mendez, Fernando J

    2017-01-01

    Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g. the Pacific). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, we address these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into “wave families,” defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications.

  3. Phantom-based multimodal interactions for medical education and training: the Munich Knee Joint Simulator.

    PubMed

    Riener, Robert; Frey, Martin; Pröll, Thomas; Regenfelder, Felix; Burgkart, Rainer

    2004-06-01

    Simulation environments based on virtual reality technologies can support medical education and training. In this paper, the novel approach of an "interactive phantom" is presented that allows a realistic display of haptic contact information typically generated when touching and moving human organs or segments. The key idea of the haptic interface is to attach passive phantom objects to a mechanical actuator. The phantoms look and feel as real anatomical objects. Additional visualization of internal anatomical and physiological information and sound generated during the interaction with the phantom yield a multimodal approach that can increase performance, didactic value, and immersion into the virtual environment. Compared to classical approaches, this multimodal display is convenient to use, provides realistic tactile properties, and can be partly adjusted to different, e.g., pathological properties. The interactive phantom is exemplified by a virtual human knee joint that can support orthopedic education, especially for the training of clinical knee joint evaluation. It is suggested that the technical principle can be transferred to many other fields of medical education and training such as obstetrics and dentistry.

  4. Facial expression recognition in the wild based on multimodal texture features

    NASA Astrophysics Data System (ADS)

    Sun, Bo; Li, Liandong; Zhou, Guoyan; He, Jun

    2016-11-01

    Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal-spatial dense scale-invariant feature transform (SIFT) features and combine multimodal features to recognize expression from image sequences. For the static facial expression recognition based on video frames, we extract dense SIFT and some deep convolutional neural network (CNN) features, including our proposed CNN architecture. We train linear support vector machine and partial least squares classifiers for those kinds of features on the static facial expression in the wild (SFEW) and acted facial expression in the wild (AFEW) dataset, and we propose a fusion network to combine all the extracted features at decision level. The final achievement we gained is 56.32% on the SFEW testing set and 50.67% on the AFEW validation set, which are much better than the baseline recognition rates of 35.96% and 36.08%.

  5. Evaluation of an Automatic Registration-Based Algorithm for Direct Measurement of Volume Change in Tumors

    SciTech Connect

    Sarkar, Saradwata; Johnson, Timothy D.; Ma, Bing; Chenevert, Thomas L.; Bland, Peyton H.; Park, Hyunjin; Schott, Anne F.; Ross, Brian D.; Meyer, Charles R.

    2012-07-01

    Purpose: Assuming that early tumor volume change is a biomarker for response to therapy, accurate quantification of early volume changes could aid in adapting an individual patient's therapy and lead to shorter clinical trials. We investigated an image registration-based approach for tumor volume change quantification that may more reliably detect smaller changes that occur in shorter intervals than can be detected by existing algorithms. Methods and Materials: Variance and bias of the registration-based approach were evaluated using retrospective, in vivo, very-short-interval diffusion magnetic resonance imaging scans where true zero tumor volume change is unequivocally known and synthetic data, respectively. The interval scans were nonlinearly registered using two similarity measures: mutual information (MI) and normalized cross-correlation (NCC). Results: The 95% confidence interval of the percentage volume change error was (-8.93% to 10.49%) for MI-based and (-7.69%, 8.83%) for NCC-based registrations. Linear mixed-effects models demonstrated that error in measuring volume change increased with increase in tumor volume and decreased with the increase in the tumor's normalized mutual information, even when NCC was the similarity measure being optimized during registration. The 95% confidence interval of the relative volume change error for the synthetic examinations with known changes over {+-}80% of reference tumor volume was (-3.02% to 3.86%). Statistically significant bias was not demonstrated. Conclusion: A low-noise, low-bias tumor volume change measurement algorithm using nonlinear registration is described. Errors in change measurement were a function of tumor volume and the normalized mutual information content of the tumor.

  6. 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.

  7. Sequential Registration-Based Segmentation of the Prostate Gland in MR Image Volumes.

    PubMed

    Khalvati, Farzad; Salmanpour, Aryan; Rahnamayan, Shahryar; Haider, Masoom A; Tizhoosh, H R

    2016-04-01

    Accurate and fast segmentation and volume estimation of the prostate gland in magnetic resonance (MR) images are necessary steps in the diagnosis, treatment, and monitoring of prostate cancer. This paper presents an algorithm for the prostate gland volume estimation based on the semi-automated segmentation of individual slices in T2-weighted MR image sequences. The proposed sequential registration-based segmentation (SRS) algorithm, which was inspired by the clinical workflow during medical image contouring, relies on inter-slice image registration and user interaction/correction to segment the prostate gland without the use of an anatomical atlas. It automatically generates contours for each slice using a registration algorithm, provided that the user edits and approves the marking in some previous slices. We conducted comprehensive experiments to measure the performance of the proposed algorithm using three registration methods (i.e., rigid, affine, and nonrigid). Five radiation oncologists participated in the study where they contoured the prostate MR (T2-weighted) images of 15 patients both manually and using the SRS algorithm. Compared to the manual segmentation, on average, the SRS algorithm reduced the contouring time by 62% (a speedup factor of 2.64×) while maintaining the segmentation accuracy at the same level as the intra-user agreement level (i.e., Dice similarity coefficient of 91 versus 90%). The proposed algorithm exploits the inter-slice similarity of volumetric MR image series to achieve highly accurate results while significantly reducing the contouring time.

  8. Coil compaction and aneurysm growth: image-based quantification using non-rigid registration

    NASA Astrophysics Data System (ADS)

    De Craene, Mathieu; Pozo, José María; Villa, Maria Cruz; Vivas, Elio; Sola, Teresa; Guimaraens, Leopoldo; Blasco, Jordi; Macho, Juan; Frangi, Alejandro

    2008-03-01

    Endovascular treatment of intracranial aneurysms is a minimally-invasive technique recognized as a valid alternative to surgical clipping. However, endovascular treatment can be associated to aneurysm recurrence, either due to coil compaction or aneurysm growth. The quantification of coil compaction or aneurysm growth is usually performed by manual measurements or visual inspection of images from consecutive follow-ups. Manual measurements permit to detect large global deformation but might have insufficient accuracy for detecting subtle or more local changes between images. Image inspection permits to detect a residual neck in the aneurysm but do not differentiate aneurysm growth from coil compaction. In this paper, we propose to quantify independently coil compaction and aneurysm growth using non-rigid image registration. Local changes of volume between images at successive time points are identified using the Jacobian of the non-rigid transformation. Two different non-rigid registration strategies are applied in order to explore the sensitivity of Jacobian-based volume changes against the registration method, FFD registration based on mutual information and Demons. This volume-variation measure has been applied to four patients of which a series of 3D Rotational Angiography (3DRA) images obtained at different controls separated from two months to two years were available. The evolution of coil and aneurysm volumes along the period has been obtained separately, which allows distinguishing between coil compaction and aneurysm growth. On the four cases studied in this paper, aneurysm recurrence was always associated to aneurysm growth, as opposed to strict coil compaction.

  9. Effect of nonrigid registration algorithms on deformation-based morphometry: a comparative study with control and Williams syndrome subjects.

    PubMed

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

    2012-07-01

    Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared nonrigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established nonrigid registration algorithms using 13 subjects with Williams syndrome and 13 normal control subjects. The five nonrigid registration algorithms include the following: (1) the adaptive bases algorithm, (2) the image registration toolkit, (3) The FSL nonlinear image registration tool, (4) the automatic registration tool, and (5) the normalization algorithm available in Statistical Parametric Mapping (SPM8). Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. Some regions are detected by several algorithms, but their extent varies. Others are detected only by a subset of the algorithms. Based on these results, we recommend using more than one algorithm when performing DBM studies.

  10. 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

  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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

    Gadolinium-based contrast agents are extensively used as magnetic resonance imaging (MRI) contrast agents due to their outstanding signal enhancement and ease of chemical modification. However, it is increasingly recognized that information obtained from single modal molecular imaging cannot satisfy the higher requirements on the efficiency and accuracy for clinical diagnosis and medical research, due to its limitation and default rooted in single molecular imaging technique itself. To compensate for the deficiencies of single function magnetic resonance imaging contrast agents, the combination of multi-modality imaging has turned to be the research hotpot in recent years. This review presents an overview on the recent developments of the functionalization of gadolinium-based contrast agents, and their application in biomedicine applications.

  13. Co-registration and distortion correction of diffusion and anatomical images based on inverse contrast normalization.

    PubMed

    Bhushan, Chitresh; Haldar, Justin P; Choi, Soyoung; Joshi, Anand A; Shattuck, David W; Leahy, Richard M

    2015-07-15

    Diffusion MRI provides quantitative information about microstructural properties which can be useful in neuroimaging studies of the human brain. Echo planar imaging (EPI) sequences, which are frequently used for acquisition of diffusion images, are sensitive to inhomogeneities in the primary magnetic (B0) field that cause localized distortions in the reconstructed images. We describe and evaluate a new method for correction of susceptibility-induced distortion in diffusion images in the absence of an accurate B0 fieldmap. In our method, the distortion field is estimated using a constrained non-rigid registration between an undistorted T1-weighted anatomical image and one of the distorted EPI images from diffusion acquisition. Our registration framework is based on a new approach, INVERSION (Inverse contrast Normalization for VERy Simple registratION), which exploits the inverted contrast relationship between T1- and T2-weighted brain images to define a simple and robust similarity measure. We also describe how INVERSION can be used for rigid alignment of diffusion images and T1-weighted anatomical images. Our approach is evaluated with multiple in vivo datasets acquired with different acquisition parameters. Compared to other methods, INVERSION shows robust and consistent performance in rigid registration and shows improved alignment of diffusion and anatomical images relative to normalized mutual information for non-rigid distortion correction.

  14. Improved B-spline image registration between exhale and inhale lung CT images based on intensity and gradient orientation information

    NASA Astrophysics Data System (ADS)

    Nam, Woo Hyun; Oh, Jihun; Yi, Jonghyon; Park, Yongsup; Cho, Hansu; Kim, Sukjin

    2016-03-01

    Registration of lung CT images acquired at different respiratory phases is clinically relevant in many applications, such as follow-up analysis, lung function analysis based on mechanical elasticity, or pulmonary airflow analysis, etc. In order to find accurate and reliable transformation for registration, a proper choice of dissimilarity measure is important. Even though various intensity-based measures have been introduced for precise registration, the registration performance may be limited since they mainly take intensity values into account without effectively considering useful spatial information. In this paper, we attempt to improve the non-rigid registration accuracy between exhale and inhale CT images of the lung, by proposing a new dissimilarity measure based on gradient orientation representing the spatial information in addition to vessel-weighted intensity and normalized intensity information. Since it is necessary to develop non-rigid registration that can account for large lung deformations, the B-spline free-form deformation (FFD) is adopted as the transformation model. The experimental tests for six clinical datasets show that the proposed method provides more accurate registration results than competitive registration methods.

  15. 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.

  16. Intensity-based femoral atlas 2D/3D registration using Levenberg-Marquardt optimisation

    NASA Astrophysics Data System (ADS)

    Klima, Ondrej; Kleparnik, Petr; Spanel, Michal; Zemcik, Pavel

    2016-03-01

    The reconstruction of a patient-specific 3D anatomy is the crucial step in the computer-aided preoperative planning based on plain X-ray images. In this paper, we propose a robust and fast reconstruction methods based on fitting the statistical shape and intensity model of a femoral bone onto a pair of calibrated X-ray images. We formulate the registration as a non-linear least squares problem, allowing for the involvement of Levenberg-Marquardt optimisation. The proposed methods have been tested on a set of 96 virtual X-ray images. The reconstruction accuracy was evaluated using the symmetric Hausdorff distance between reconstructed and ground-truth bones. The accuracy of the intensity-based method reached 1.18 +/- 1.57mm on average, the registration took 8.76 seconds on average.

  17. 2.5D Multi-View Gait Recognition Based on Point Cloud Registration

    PubMed Central

    Tang, Jin; Luo, Jian; Tjahjadi, Tardi; Gao, Yan

    2014-01-01

    This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM. PMID:24686727

  18. Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations.

    PubMed

    Meyer, C R; Boes, J L; Kim, B; Bland, P H; Zasadny, K R; Kison, P V; Koral, K; Frey, K A; Wahl, R L

    1997-04-01

    This paper applies and evaluates an automatic mutual information-based registration algorithm across a broad spectrum of multimodal volume data sets. The algorithm requires little or no pre-processing, minimal user input and easily implements either affine, i.e. linear or thin-plate spline (TPS) warped registrations. We have evaluated the algorithm in phantom studies as well as in selected cases where few other algorithms could perform as well, if at all, to demonstrate the value of this new method. Pairs of multimodal gray-scale volume data sets were registered by iteratively changing registration parameters to maximize mutual information. Quantitative registration errors were assessed in registrations of a thorax phantom using PET/CT and in the National Library of Medicine's Visible Male using MRI T2-/T1-weighted acquisitions. Registrations of diverse clinical data sets were demonstrated including rotate-translate mapping of PET/MRI brain scans with significant missing data, full affine mapping of thoracic PET/CT and rotate-translate mapping of abdominal SPECT/CT. A five-point thin-plate spline (TPS) warped registration of thoracic PET/CT is also demonstrated. The registration algorithm converged in times ranging between 3.5 and 31 min for affine clinical registrations and 57 min for TPS warping. Mean error vector lengths for rotate-translate registrations were measured to be subvoxel in phantoms. More importantly the rotate-translate algorithm performs well even with missing data. The demonstrated clinical fusions are qualitatively excellent at all levels. We conclude that such automatic, rapid, robust algorithms significantly increase the likelihood that multimodality registrations will be routinely used to aid clinical diagnoses and post-therapeutic assessment in the near future.

  19. A pragmatic community-based intervention of multimodal physiotherapy plus deep water running (DWR) for fibromyalgia syndrome: a pilot study.

    PubMed

    Cuesta-Vargas, Antonio I; Adams, Nicola

    2011-11-01

    Evidence-based recommendations support the use of multimodal therapy and hydrotherapy for fibromyalgia syndrome; however, there is little standardisation of such programmes. The aim of the study was to assess the effectiveness of a pool-based exercise using deep water running (DWR) as part of a multimodal physiotherapy programme for patients with fibromyalgia syndrome. For a non-randomised clinical study, 44 patients diagnosed with fibromyalgia were recruited from primary care. Patients in the experimental group received a multimodal programme incorporating pool-based exercise using DWR three times a week for an 8-week period. The control group received a leaflet containing advice and continued with normal activities. Patients were evaluated for physical function (Fibromyalgia Impact Questionnaire, FIQ), pain, general health (Short Form-12 Health Survey) and quality of life (European Quality of Life Scale-5D) pre- and post intervention. Statistically significant results were found for the experimental group for FIQ total score, incorporating physical function, pain, fatigue, stiffness and psychological variables (p < 0.05). Statistically significant differences between the experimental group and control were also found for general health (p < 0.05) and quality of life (p < 0.05). The results of this pilot study and the high level of compliance and adherence and low level of attrition suggest that this multimodal programme incorporating DWR is a safe and effective intervention for fibromyalgia syndrome that is acceptable to patients.

  20. Tunable triple Fano resonances based on multimode interference in coupled plasmonic resonator system.

    PubMed

    Li, Shilei; Zhang, Yunyun; Song, Xiaokang; Wang, Yilin; Yu, Li

    2016-07-11

    In this paper, an asymmetric plasmonic structure composed of two MIM (metal-insulator-metal) waveguides and two rectangular cavities is reported, which can support triple Fano resonances originating from three different mechanisms. And the multimode interference coupled mode theory (MICMT) including coupling phases is proposed based on single mode coupled mode theory (CMT), which is used for describing and explaining the multiple Fano resonance phenomenon in coupled plasmonic resonator systems. Just because the triple Fano resonances originate from three different mechanisms, each Fano resonance can be tuned independently or semi-independently by changing the parameters of the two rectangular cavities. Such, a narrow 'M' type of double Lorentzian-like line-shape transmission windows with the position and the full width at half maximum (FWHM) can be tuned freely is constructed by changing the parameters of the two cavities appropriately, which can find widely applications in sensors, nonlinear and slow-light devices.

  1. Multi-modal vibration energy harvesting approach based on nonlinear oscillator arrays under magnetic levitation

    NASA Astrophysics Data System (ADS)

    Abed, I.; Kacem, N.; Bouhaddi, N.; Bouazizi, M. L.

    2016-02-01

    We propose a multi-modal vibration energy harvesting approach based on arrays of coupled levitated magnets. The equations of motion which include the magnetic nonlinearity and the electromagnetic damping are solved using the harmonic balance method coupled with the asymptotic numerical method. A multi-objective optimization procedure is introduced and performed using a non-dominated sorting genetic algorithm for the cases of small magnet arrays in order to select the optimal solutions in term of performances by bringing the eigenmodes close to each other in terms of frequencies and amplitudes. Thanks to the nonlinear coupling and the modal interactions even for only three coupled magnets, the proposed method enable harvesting the vibration energy in the operating frequency range of 4.6-14.5 Hz, with a bandwidth of 190% and a normalized power of 20.2 {mW} {{cm}}-3 {{{g}}}-2.

  2. 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.

  3. Multimodal underwater adsorption of oxide nanoparticles on catechol-based polymer nanosheets

    NASA Astrophysics Data System (ADS)

    Yamamoto, Shunsuke; Uchiyama, Shun; Miyashita, Tokuji; Mitsuishi, Masaya

    2016-03-01

    Multimodal underwater adsorption behaviour of catechol units was demonstrated by examining the adsorption of different oxide nanoparticles on nanoscale-integrated polymer nanosheets. Catechol-based polymer nanosheets were fabricated using the Langmuir-Blodgett (LB) technique with random copolymers (p(DDA/DMA)s) of N-dodecylacrylamide (DDA) and dopamine methacrylamide (DMA). The p(DDA/DMA) nanosheets were immersed into water dispersions of SiO2, Al2O3, and WO3 nanoparticles (NPs) respectively. The results show that the adsorption properties can be altered by varying the NP type: SiO2 NP adsorption was observed only below pH = 6, at which the o-quinone form in p(DDA/DMA) nanosheets transforms into the catechol form or vice versa. However, their transition point for Al2O3 NP adsorption was found at approximately pH 10, at which the surface potential of Al2O3 NPs changes the charge polarity, indicating that the electrostatic interaction is predominant. For WO3 NPs, adsorption was observed when citric acid, which modifies the surface of WO3 NPs by complex formation, was used as a pH-controlling agent, but no adsorption was found for hydrochloric acid used as a pH controlling agent. FT-IR measurements proved that miniscule amounts of water molecules were trapped in p(DDA/DMA) nanosheets and that they acquired hydrogen bonding network formations, which might assist nanoparticle adsorption underwater and make the catechol units adjustable. The results indicate that the nanoscale spatial arrangements of catechol units in films are crucially important for the application of multimodal adsorption of oxide nanoparticles on catechol-based polymer materials.Multimodal underwater adsorption behaviour of catechol units was demonstrated by examining the adsorption of different oxide nanoparticles on nanoscale-integrated polymer nanosheets. Catechol-based polymer nanosheets were fabricated using the Langmuir-Blodgett (LB) technique with random copolymers (p(DDA/DMA)s) of N

  4. 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.

  5. Side-polished multimode fiber biosensor based on surface plasmon resonance with halogen light

    NASA Astrophysics Data System (ADS)

    Lin, Hong-Yu; Tsai, Woo-Hu; Tsao, Yu-Chia; Sheu, Bor-Chiou

    2007-02-01

    A side-polished multimode fiber sensor based on surface plasmon resonance (SPR) as the transducing element with a halogen light source is proposed. The SPR fiber sensor is side polished until half the core is closed and coated with a 37 nm gold thin film by dc sputtering. The SPR curve on the optical spectrum is described by an optical spectrum analyzer and can sense a range of widths in wavelengths of SPR effects. The measurement system using the halogen light source is constructed for several real-time detections that are carried out for the measurement of the index liquid detections for the sensitivity analysis. The sensing fiber is demonstrated with a series of refractive index (RI) liquids and set for several experiments, including the stability, repeatability, and resolution calibration. The results for the halogen light source with the resolution of the measurement based on wavelength interrogation were 3×10-6 refractive index units (RIUs). The SPR dip shifted in wavelength is used as a measure of the RI change at a surface, and this RI change varies directly with the number of biomolecules at the surface. The SPR dip shift in wavelength, which was hybridized at 0.1 μM of the target DNA to the probe DNA, was 8.66 nm. The all-fiber multimode SPR sensor, which has the advantages of being low cost, being disposable, having high stability and linearity, being free of labeling, and having potential for real-time detection, permit the sensor and system to be used in biochemical sensing and environmental monitoring.

  6. 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

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

    PubMed

    Poreba, Martyna; Goulette, François

    2015-01-14

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

  8. Registration of infrared and visual images based on phase grouping and mutual information of gradient orientation

    NASA Astrophysics Data System (ADS)

    Zhang, Zhilong; Yang, Guopeng; Chen, Dong; Li, Jicheng; Yang, Weiping

    2016-04-01

    This paper presents a novel infrared and visual image registration method based on phase grouping and mutual information of gradient orientation. The method is specially designed for infrared image navigation, which is different from familiar multi-sensor image registration methods in the field of remote sensing. The central idea is to firstly extract common salient structural features from visual and infrared images through phase grouping, then registering infrared image to visual image and estimating the exterior parameters of the infrared camera. Two subjects are involved in this reports: (1) In order to estimate image gradient orientation accurately, a new method based on Leguerre-Gauss filter is presented. Then the image are segmented by grouping of pixels based on their gradient orientations and ling support regions are extracted as common salient structural features from infrared and visual images of the same ground scene. (2)In order for registering infrared and visual image, coordinate systems are constructed, coordinate transformations are formularized, and the new similarity measures based on orientation mutual information is presented. Quantitative evaluations on real and simulated image data reviews that the proposed method can provide registration results with improved robustness and accuracy.

  9. 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.

  10. 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.

  11. 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.

  12. Seed based registration for intraoperative brachytherapy dosimetry: a comparison of methods

    NASA Astrophysics Data System (ADS)

    Su, Yi; Davis, Brian J.; Herman, Michael G.; Robb, Richard A.

    2006-03-01

    Several approaches for registering a subset of imaged points to their true origins were analyzed and compared for seed based TRUS-fluoroscopy registration. The methods include the Downhill Simplex method (DS), the Powell's method (POW), the Iterative Closest Point (ICP) method, the Robust Point Matching method (RPM) and variants of RPM. Several modifications were made to the standard RPM method to improve its performance. One hundred simulations were performed for each combination of noise level, seed detection rate and spurious points and the registration accuracy was evaluated and compared. The noise level ranges from 0 to 5mm, the seed detection ratio ranges from 0.2 to 0.6, and the number of spurious points ranges from 0 to 20. An actual clinical post-implant dataset from permanent prostate brachytherapy was used for the simulation study. The experiments provided evidence that our modified RPM method is superior to other methods, especially when there are many outliers. The RPM based method produced the best results at all noise levels and seed detection rates. The DS based method performed reasonably well, especially at low noise levels without spurious points. There was no significant performance difference between the standard RPM and our modified RPM methods without spurious points. The modified RPM methods outperformed the standard RPM method with large number of spurious points. The registration error was within 2mm, even with 20 outlier points and a noise level of 3mm.

  13. Image registration via level-set motion: applications to atlas-based segmentation.

    PubMed

    Vemuri, B C; Ye, J; Chen, Y; Leonard, C M

    2003-03-01

    Image registration is an often encountered problem in various fields including medical imaging, computer vision and image processing. Numerous algorithms for registering image data have been reported in these areas. In this paper, we present a novel curve evolution approach expressed in a level-set framework to achieve image intensity morphing and a simple non-linear PDE for the corresponding coordinate registration. The key features of the intensity morphing model are that (a) it is very fast and (b) existence and uniqueness of the solution for the evolution model are established in a Sobolev space as opposed to using viscosity methods. The salient features of the coordinate registration model are its simplicity and computational efficiency. The intensity morph is easily achieved via evolving level-sets of one image into the level-sets of the other. To explicitly estimate the coordinate transformation between the images, we derive a non-linear PDE-based motion model which can be solved very efficiently. We demonstrate the performance of our algorithm on a variety of images including synthetic and real data. As an application of the PDE-based motion model, atlas based segmentation of hippocampal shape from several MR brain scans is depicted. In each of these experiments, automated hippocampal shape recovery results are validated via manual "expert" segmentations.

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

    PubMed

    An, Yong; Wang, Manning; Song, Zhijian

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  16. 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.

  17. 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.

  18. Colonoscope navigation system using colonoscope tracking method based on line registration

    NASA Astrophysics Data System (ADS)

    Oda, Masahiro; Kondo, Hiroaki; Kitasaka, Takayuki; Furukawa, Kazuhiro; Miyahara, Ryoji; Hirooka, Yoshiki; Goto, Hidemi; Navab, Nassir; Mori, Kensaku

    2014-03-01

    This paper presents a new colonoscope navigation system. CT colonography is utilized for colon diagnosis based on CT images. If polyps are found while CT colonography, colonoscopic polypectomy can be performed to remove them. While performing a colonoscopic examination, a physician controls colonoscope based on his/her experience. Inexperienced physicians may occur complications such as colon perforation while colonoscopic examinations. To reduce complications, a navigation system of colonoscope while performing the colonoscopic examinations is necessary. We propose a colonoscope navigation system. This system has a new colonoscope tracking method. This method obtains a colon centerline from a CT volume of a patient. A curved line (colonoscope line) representing the shape of colonoscope inserted to the colon is obtained by using electromagnetic sensors. A coordinate system registration process that employs the ICP algorithm is performed to register the CT and sensor coordinate systems. The colon centerline and colonoscope line are registered by using a line registration method. The position of the colonoscope tip in the colon is obtained from the line registration result. Our colonoscope navigation system displays virtual colonoscopic views generated from the CT volumes. A viewpoint of the virtual colonoscopic view is a point on the centerline that corresponds to the colonoscope tip. Experimental results using a colon phantom showed that the proposed colonoscope tracking method can track the colonoscope tip with small tracking errors.

  19. 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

  20. Reflectance and fluorescence hyperspectral elastic image registration

    NASA Astrophysics Data System (ADS)

    Lange, Holger; Baker, Ross; Hakansson, Johan; Gustafsson, Ulf P.

    2004-05-01

    Science and Technology International (STI) presents a novel multi-modal elastic image registration approach for a new hyperspectral medical imaging modality. STI's HyperSpectral Diagnostic Imaging (HSDI) cervical instrument is used for the early detection of uterine cervical cancer. A Computer-Aided-Diagnostic (CAD) system is being developed to aid the physician with the diagnosis of pre-cancerous and cancerous tissue regions. The CAD system uses the fusion of multiple data sources to optimize its performance. The key enabling technology for the data fusion is image registration. The difficulty lies in the image registration of fluorescence and reflectance hyperspectral data due to the occurrence of soft tissue movement and the limited resemblance of these types of imagery. The presented approach is based on embedding a reflectance image in the fluorescence hyperspectral imagery. Having a reflectance image in both data sets resolves the resemblance problem and thereby enables the use of elastic image registration algorithms required to compensate for soft tissue movements. Several methods of embedding the reflectance image in the fluorescence hyperspectral imagery are described. Initial experiments with human subject data are presented where a reflectance image is embedded in the fluorescence hyperspectral imagery.

  1. A novel multimodal chromatography based single step purification process for efficient manufacturing of an E. coli based biotherapeutic protein product.

    PubMed

    Bhambure, Rahul; Gupta, Darpan; Rathore, Anurag S

    2013-11-01

    Methionine oxidized, reduced and fMet forms of a native recombinant protein product are often the critical product variants which are associated with proteins expressed as bacterial inclusion bodies in E. coli. Such product variants differ from native protein in their structural and functional aspects, and may lead to loss of biological activity and immunogenic response in patients. This investigation focuses on evaluation of multimodal chromatography for selective removal of these product variants using recombinant human granulocyte colony stimulating factor (GCSF) as the model protein. Unique selectivity in separation of closely related product variants was obtained using combined pH and salt based elution gradients in hydrophobic charge induction chromatography. Simultaneous removal of process related impurities was also achieved in flow-through leading to single step purification process for the GCSF. Results indicate that the product recovery of up to 90.0% can be obtained with purity levels of greater than 99.0%. Binding the target protein at pHbased elution gradient and removal of the host cell impurities in flow-through are the key novel features of the developed multimodal chromatographic purification step.

  2. Intensity-based 2D 3D registration for lead localization in robot guided deep brain stimulation.

    PubMed

    Hunsche, Stefan; Sauner, Dieter; Majdoub, Faycal El; Neudorfer, Clemens; Poggenborg, Jörg; Goßmann, Axel; Maarouf, Mohammad

    2017-03-21

    Intraoperative assessment of lead localization has become a standard procedure during deep brain stimulation surgery in many centers, allowing immediate verification of targeting accuracy and, if necessary, adjustment of the trajectory. The most suitable imaging modality to determine lead positioning, however, remains controversially discussed. Current approaches entail the implementation of computed tomography and magnetic resonance imaging. In the present study, we adopted the technique of intensity-based 2D 3D registration that is commonly employed in stereotactic radiotherapy and spinal surgery. For this purpose, intraoperatively acquired 2D x-ray images were fused with preoperative 3D computed tomography (CT) data to verify lead placement during stereotactic robot assisted surgery. Accuracy of lead localization determined from 2D 3D registration was compared to conventional 3D 3D registration in a subsequent patient study. The mean Euclidian distance of lead coordinates estimated from intensity-based 2D 3D registration versus flat-panel detector CT 3D 3D registration was 0.7 mm  ±  0.2 mm. Maximum values of these distances amounted to 1.2 mm. To further investigate 2D 3D registration a simulation study was conducted, challenging two observers to visually assess artificially generated 2D 3D registration errors. 95% of deviation simulations, which were visually assessed as sufficient, had a registration error below 0.7 mm. In conclusion, 2D 3D intensity-based registration revealed high accuracy and reliability during robot guided stereotactic neurosurgery and holds great potential as a low dose, cost effective means for intraoperative lead localization.

  3. Intensity-based 2D 3D registration for lead localization in robot guided deep brain stimulation

    NASA Astrophysics Data System (ADS)

    Hunsche, Stefan; Sauner, Dieter; El Majdoub, Faycal; Neudorfer, Clemens; Poggenborg, Jörg; Goßmann, Axel; Maarouf, Mohammad

    2017-03-01

    Intraoperative assessment of lead localization has become a standard procedure during deep brain stimulation surgery in many centers, allowing immediate verification of targeting accuracy and, if necessary, adjustment of the trajectory. The most suitable imaging modality to determine lead positioning, however, remains controversially discussed. Current approaches entail the implementation of computed tomography and magnetic resonance imaging. In the present study, we adopted the technique of intensity-based 2D 3D registration that is commonly employed in stereotactic radiotherapy and spinal surgery. For this purpose, intraoperatively acquired 2D x-ray images were fused with preoperative 3D computed tomography (CT) data to verify lead placement during stereotactic robot assisted surgery. Accuracy of lead localization determined from 2D 3D registration was compared to conventional 3D 3D registration in a subsequent patient study. The mean Euclidian distance of lead coordinates estimated from intensity-based 2D 3D registration versus flat-panel detector CT 3D 3D registration was 0.7 mm  ±  0.2 mm. Maximum values of these distances amounted to 1.2 mm. To further investigate 2D 3D registration a simulation study was conducted, challenging two observers to visually assess artificially generated 2D 3D registration errors. 95% of deviation simulations, which were visually assessed as sufficient, had a registration error below 0.7 mm. In conclusion, 2D 3D intensity-based registration revealed high accuracy and reliability during robot guided stereotactic neurosurgery and holds great potential as a low dose, cost effective means for intraoperative lead localization.

  4. 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

  5. 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.

  6. Recognition-based segmentation and registration method for image guided shoulder surgery.

    PubMed

    Chaoui, J; Hamitouche, C; Stindel, E; Roux, C

    2011-01-01

    For any image guided surgery, independently of the technique which is used (navigation, templates, robotics), it is necessary to get a 3D bone surface model from CT or MR images. Such model is used for planning, registration and visualization. We report that graphical representation of patient bony structure and the surgical tools, interconnectively with the tracking device and patient-to-image registration are crucial components in such a system. For Total Shoulder Arthroplasty (TSA), there are many challenges, The most of cases that we are working with are pathological cases such as rheumatoid arthritis, osteoarthritis disease. The CT images of these cases often show a fusion area between the glenoid cavity and the humeral head. They also show severe deformations of the humeral head surface that result in a loss of contours. This fusion area and image quality problems are also amplified by well-known CT-scan artifacts like beam-hardening or partial volume effects. The state of the art shows that several segmentation techniques, applied to CT-Scans of the shoulder, have already been disclosed. Unfortunately, their performances, when used on pathological data, are quite poor [1, 2]. The aim of this paper is to present a new image guided surgery system based on CT scan of the patient and using bony structure recognition, morphological analysis for the operated region and robust image-to-patient registration.

  7. 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.

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

    PubMed

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

    2012-09-01

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

  9. Multimodal Discrimination of Alzheimer's Disease Based on Regional Cortical Atrophy and Hypometabolism.

    PubMed

    Yun, Hyuk Jin; Kwak, Kichang; Lee, Jong-Min

    2015-01-01

    Structural MR image (MRI) and 18F-Fluorodeoxyglucose-positron emission tomography (FDG-PET) have been widely employed in diagnosis of both Alzheimer's disease (AD) and mild cognitive impairment (MCI) pathology, which has led to the development of methods to distinguish AD and MCI from normal controls (NC). Synaptic dysfunction leads to a reduction in the rate of metabolism of glucose in the brain and is thought to represent AD progression. FDG-PET has the unique ability to estimate glucose metabolism, providing information on the distribution of hypometabolism. In addition, patients with AD exhibit significant neuronal loss in cerebral regions, and previous AD research has shown that structural MRI can be used to sensitively measure cortical atrophy. In this paper, we introduced a new method to discriminate AD from NC based on complementary information obtained by FDG and MRI. For accurate classification, surface-based features were employed and 12 predefined regions were selected from previous studies based on both MRI and FDG-PET. Partial least square linear discriminant analysis was employed for making diagnoses. We obtained 93.6% classification accuracy, 90.1% sensitivity, and 96.5% specificity in discriminating AD from NC. The classification scheme had an accuracy of 76.5% and sensitivity and specificity of 46.5% and 89.6%, respectively, for discriminating MCI from AD. Our method exhibited a superior classification performance compared with single modal approaches and yielded parallel accuracy to previous multimodal classification studies using MRI and FDG-PET.

  10. 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.

  11. Refractometric sensors based on multimode interference in a thin-film coated single-mode-multimode-single-mode structure with reflection configuration.

    PubMed

    Del Villar, Ignacio; Socorro, Abian B; Corres, Jesus M; Arregui, Francisco J; Matias, Ignacio R

    2014-06-20

    Thin-film coated single-mode-multimode-single-mode (SMS) structures have been analyzed both theoretically and experimentally with the aim of detecting different refractive indices. By adequate selection of the thickness of the thin film and of the diameter of the multimode segment in the SMS structure, a seven-fold improvement can be obtained in the sensitivity of the device to the surrounding medium refractive index, achieving a maximum sensitivity of 1199.18  nm/refractive index unit for the range of refractive indices from 1.321 to 1.382. Using layer-by-layer self-assembly for deposition, both on the cladding and on the tip of the multimode segment, allows the reflected power to increase, which avoids the application of a mirror on the tip of the multimode segment.

  12. 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.

  13. 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.

  14. A molecular receptor targeted, hydroxyapatite nanocrystal based multi-modal contrast agent.

    PubMed

    Ashokan, Anusha; Menon, Deepthy; Nair, Shantikumar; Koyakutty, Manzoor

    2010-03-01

    Multi-modal molecular imaging can significantly improve the potential of non-invasive medical diagnosis by combining basic anatomical descriptions with in-depth phenotypic characteristics of disease. Contrast agents with multifunctional properties that can sense and enhance the signature of specific molecular markers, together with high biocompatibility are essential for combinatorial molecular imaging approaches. Here, we report a multi-modal contrast agent based on hydroxyapatite nanocrystals (nHAp), which is engineered to show simultaneous contrast enhancement for three major molecular imaging techniques such as magnetic resonance imaging (MRI), X-ray imaging and near-infrared (NIR) fluorescence imaging. Monodispersed nHAp crystals of average size approximately 30 nm and hexagonal crystal structure were in situ doped with multiple rare-earth impurities by a surfactant-free, aqueous wet-chemical method at 100 degrees C. Doping of nHAp with Eu(3+) (3 at%) resulted bright near-infrared fluorescence (700 nm) due to efficient (5)D(0)-(7)F(4) electronic transition and co-doping with Gd(3+) resulted enhanced paramagnetic longitudinal relaxivity (r(1) approximately 12 mM(-1) s(-1)) suitable for T(1) weighted MR imaging together with approximately 80% X-ray attenuation suitable for X-ray contrast imaging. Capability of MF-nHAp to specifically target and enhance the signature of molecular receptors (folate) in cancer cells was realized by carbodiimide grafting of cell-membrane receptor ligand folic acid (FA) on MF-nHAp surface aminized with dendrigraft polymer, polyethyleneimine (PEI). The FA-PEI-MF-nHAp conjugates showed specific aggregation on FR(+ve) cells while leaving the negative control cells untouched. Nanotoxicity evaluation of this multifunctional nHAp carried out on primary human endothelial cells (HUVEC), normal mouse lung fibroblast cell line (L929), human nasopharyngeal carcinoma (KB) and human lung cancer cell line (A549) revealed no apparent toxicity even

  15. Liquid-filled photonic-crystal-fiber-based multimodal interferometer for simultaneous measurement of temperature and force.

    PubMed

    Lin, Wei; Song, Binbin; Miao, Yinping; Zhang, Hao; Yan, Donglin; Liu, Bo; Liu, Yange

    2015-02-20

    In this paper, a multimodal interferometer based on the liquid-filled photonic crystal fiber (PCF) has been proposed and experimentally demonstrated for simultaneous measurement of temperature and force. Experimental results show that different spectral minima have distinctive sensitivities to the temperature and force. The proposed interferometer shows the temperature sensitivities of -9.214 nm/°C, -24.757 nm/°C, and -12.543/°C and the force sensitivities of 0 nm/N, 4.978 nm/N, and 0 nm/N, respectively, for the three selected spectral minima. The sensing matrices are thus established and simultaneous measurement of temperature and force has been experimentally demonstrated. The proposed liquid-filled PCF-based multimodal interferometer would find potential applications in multiple-parameter sensing owing to its high sensitivity, compactness, ease of fabrication, and low cost.

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

    PubMed

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

    2014-09-04

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

  17. 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.

  18. 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.

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

    PubMed

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

    2016-04-18

    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.

  20. 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.

  1. 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.

  2. A novel wavelength multiplexer/demutiplexer based on side-port multimode interference coupler

    NASA Astrophysics Data System (ADS)

    Wei, Shile; Jian, Wu; Zhao, Lingjuan; Qiu, Jifang; Yin, Zuoshan; Hui, Rongqing

    2014-05-01

    Based on side-port multimode interference coupler, a novel design of 1.31/1.55-μm wavelength multiplexer/demutiplexer on SOI platform with conventional channel waveguides is proposed and analyzed by using wide-angle beam propagation method. With a 25.9μm long ultra-short MMI section, nearly an order of magnitude shorter than that of the previously reported 1.31/1.55-μm wavelength MMI splitters on SOI, simulation results exhibit contrasts of 28dB and 25dB at wavelength 1.31 and 1.55 μm, respectively, and the insertion losses are both below 0.55dB. Meanwhile, the analysis shows that the proposed structure has larger fabrication tolerances than restricted MMI based structures and the present design methodology also applies to split other wavelengths and in different material platforms, such as InP, GaAs and PLC guides, etc.

  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.

  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. 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.

  6. 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

  7. 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

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

    PubMed

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

    2008-01-01

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

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

    SciTech Connect

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

    1992-05-01

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

  10. 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

  11. Integrated multimodal network approach to PET and MRI based on multidimensional persistent homology.

    PubMed

    Lee, Hyekyoung; Kang, Hyejin; Chung, Moo K; Lim, Seonhee; Kim, Bung-Nyun; Lee, Dong Soo

    2017-03-01

    Finding underlying relationships among multiple imaging modalities in a coherent fashion is one of the challenging problems in multimodal analysis. In this study, we propose a novel approach based on multidimensional persistence. In the extension of the previous threshold-free method of persistent homology, we visualize and discriminate the topological change of integrated brain networks by varying not only threshold but also mixing ratio between two different imaging modalities. The multidimensional persistence is implemented by a new bimodal integration method called 1D projection. When the mixing ratio is predefined, it constructs an integrated edge weight matrix by projecting two different connectivity information onto the one dimensional shared space. We applied the proposed methods to PET and MRI data from 23 attention deficit hyperactivity disorder (ADHD) children, 21 autism spectrum disorder (ASD), and 10 pediatric control subjects. From the results, we found that the brain networks of ASD, ADHD children and controls differ, with ASD and ADHD showing asymmetrical changes of connected structures between metabolic and morphological connectivities. The difference of connected structure between ASD and the controls was mainly observed in the metabolic connectivity. However, ADHD showed the maximum difference when two connectivity information were integrated with the ratio 0.6. These results provide a multidimensional homological understanding of disease-related PET and MRI networks that disclose the network association with ASD and ADHD. Hum Brain Mapp 38:1387-1402, 2017. © 2016 Wiley Periodicals, Inc.

  12. Highly sensitive curvature sensor based on asymmetrical twin core fiber and multimode fiber

    NASA Astrophysics Data System (ADS)

    Wu, Yue; Pei, Li; Jin, Wenxing; Jiang, Youchao; Yang, Yuguang; Shen, Ya; Jian, Shuisheng

    2017-07-01

    A highly sensitive curvature sensor based on asymmetrical twin core fiber (TCF) and multimode fiber (MMF) is proposed and experimentally demonstrated. By applying the coupled-mode theory and equivalent refractive index model, we theoretically analyze the uncoupled feature of the TCF and the relationship between peak wavelength and the curvature. Two segments of MMF used as beam splitter and combiner are embedded on the two ends of the TCF, and the extinction ratio of the comb transmission spectrum is about 15 dB. The experimental result shows that the curvature sensitivity of the sensor can be achieved as high as 103.35 nm/m-1 ranging from 0.24 m-1 to 0.6 m-1, and the strain sensitivity is up to -4.01 pm/με in the range from 0 μεto 1400 με. The simultaneous detection of the curvature and strain can be realized. The temperature sensitivity is 0.431 nm/°C in the range from 40 °C to 70 °C. This fiber sensor exhibits the advantages of low cost, easy and repeated fabrication, and high sensitivity.

  13. Dual-parameter optical fiber sensor based on concatenated down-taper and multimode fiber

    NASA Astrophysics Data System (ADS)

    Tong, Zhengrong; Luan, Panpan; Cao, Ye; Zhang, Weihua; Su, Jun

    2016-01-01

    A novel dual-parameter optical fiber sensor based on a single-mode fiber (SMF) down-taper and multimode fiber (MMF) is proposed and demonstrated. The sensor structure is formed by cascading a down-taper and MMF through a segment of SMF. The transmission spectrum exhibits response of the interference between core and different cladding modes. Two interference dips can be observed within a certain range of detection. Due to the different wavelength shifts of the selected two dips, simultaneous measurement of temperature and liquid level can be achieved. Experiment results indicate a good linear relation between the wavelength shift and external parameters (temperature and liquid level). The measured temperature sensitivities are 0.02 nm/°C and 0.031 nm/°C, and liquid level sensitivities are 0.022 nm/mm and 0.07 nm/mm, respectively. In addition, the fiber sensor has the advantages of compact size, simple fabrication and cost-effective.

  14. 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.

  15. A self-recalibration method based on scale-invariant registration for structured light measurement systems

    NASA Astrophysics Data System (ADS)

    Chen, Rui; Xu, Jing; Zhang, Song; Chen, Heping; Guan, Yong; Chen, Ken

    2017-01-01

    The accuracy of structured light measurement depends on delicate offline calibration. However, in some practical applications, the system is supposed to be reconfigured so frequently to track the target that an online calibration is required. To this end, this paper proposes a rapid and autonomous self-recalibration method. For the proposed method, first, the rotation matrix and the normalized translation vector are attained from the fundamental matrix; second, the scale factor is acquired based on scale-invariant registration such that the actual translation vector is obtained. Experiments have been conducted to verify the effectiveness of our proposed method and the results indicate a high degree of accuracy.

  16. 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

  17. Registration-Based Morphometry for Shape Analysis of the Bones of the Human Wrist.

    PubMed

    Joshi, Anand A; Leahy, Richard M; Badawi, Ramsey D; Chaudhari, Abhijit J

    2016-02-01

    We present a method that quantifies point-wise changes in surface morphology of the bones of the human wrist. The proposed method, referred to as Registration-based Bone Morphometry (RBM), consists of two steps: an atlas selection step and an atlas warping step. The atlas for individual wrist bones was selected based on the shortest ℓ2 distance to the ensemble of wrist bones from a database of a healthy population of subjects. The selected atlas was then warped to the corresponding bones of individuals in the population using a non-linear registration method based on regularized ℓ2 distance minimization. The displacement field thus calculated showed local differences in bone shape that then were used for the analysis of group differences. Our results indicate that RBM has potential to provide a standardized approach to shape analysis of bones of the human wrist. We demonstrate the performance of RBM for examining group differences in wrist bone shapes based on sex and between those of the right and left wrists in healthy individuals. We also present data to show the application of RBM for tracking bone erosion status in rheumatoid arthritis.

  18. Registration-based Bone Morphometry for Shape Analysis of the Bones of the Human Wrist

    PubMed Central

    Joshi, Anand A.; Leahy, Richard M.; Badawi, Ramsey D.; Chaudhari, Abhijit J.

    2015-01-01

    We present a method that quantifies point-wise changes in surface morphology of the bones of the human wrist. The proposed method, referred to as Registration-based Bone Morphometry (RBM), consists of two steps: an atlas selection step and an atlas warping step. The atlas for individual wrist bones was selected based on the shortest l2 distance to the ensemble of wrist bones from a database of a healthy population of subjects. The selected atlas was then warped to the corresponding bones of individuals in the population using a non-linear registration method based on regularized l2 distance minimization. The displacement field thus calculated showed local differences in bone shape that then were used for the analysis of group differences. Our results indicate that RBM has potential to provide a standardized approach to shape analysis of bones of the human wrist. We demonstrate the performance of RBM for examining group differences in wrist bone shapes based on sex and between those of the right and left wrists in healthy individuals. We also present data to show the application of RBM for tracking bone erosion status in rheumatoid arthritis. PMID:26353369

  19. NSCT-based multimodal medical image fusion using pulse-coupled neural network and modified spatial frequency.

    PubMed

    Das, Sudeb; Kundu, Malay Kumar

    2012-10-01

    In this article, a novel multimodal medical image fusion (MIF) method based on non-subsampled contourlet transform (NSCT) and pulse-coupled neural network (PCNN) is presented. The proposed MIF scheme exploits the advantages of both the NSCT and the PCNN to obtain better fusion results. The source medical images are first decomposed by NSCT. The low-frequency subbands (LFSs) are fused using the 'max selection' rule. For fusing the high-frequency subbands (HFSs), a PCNN model is utilized. Modified spatial frequency in NSCT domain is input to motivate the PCNN, and coefficients in NSCT domain with large firing times are selected as coefficients of the fused image. Finally, inverse NSCT (INSCT) is applied to get the fused image. Subjective as well as objective analysis of the results and comparisons with state-of-the-art MIF techniques show the effectiveness of the proposed scheme in fusing multimodal medical images.

  20. 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

  1. Optical fiber magnetic field sensor based on single-mode-multimode-single-mode structure and magnetic fluid.

    PubMed

    Chen, Yaofei; Han, Qun; Liu, Tiegen; Lan, Xinwei; Xiao, Hai

    2013-10-15

    An optical fiber magnetic field sensor based on the single-mode-multimode-single-mode (SMS) structure and magnetic fluid (MF) is proposed and demonstrated. By using a piece of no-core fiber as the multimode waveguide in the SMS structure and MF sealed in a capillary tube as the magnetic sensitive media, which totally immersing the no-core fiber, an all-fiber magnetic sensor was fabricated. Interrogation of the magnetic field strength can be achieved either by measuring the dip wavelength shift of the transmission spectrum or by detecting the transmission loss at a specific wavelength. A demonstration sensor with sensitivities up to 905 pm/mT and 0.748 dB/mT was fabricated and investigated. A theoretical model for the design of the proposed device was developed and numerical simulations were performed.

  2. Research on high-temperature sensing characteristics based on modular interference of single-mode multimode single-mode fiber

    NASA Astrophysics Data System (ADS)

    Peng, Zhaozhuang; Wang, Li; Yan, Huanhuan

    2016-11-01

    Application of high temperature fiber sensing system is very extensive. It can be mainly used in high temperature test aerospace, such as, materials, chemicals, and energy. In recent years, various on-line optical fiber interferometric sensors based on modular interference of single-mode-multimode-single-mode(SMS) fiber have been largely explored in high temperature fiber sensor. In this paper we use the special fiber of a polyimide coating, its sensor head is composed of a section of multimode fiber spliced in the middle of Single-mode fiber. When the light is launched into the multimode fiber(MMF) through the lead-in single-mode fiber(SMF), the core mode and cladding modes are excited and propagate in the MMF respectively. Then, at the MMF-SMF spliced point, the excited cladding modes coupled back into the core of lead-out SMF interfere with SMF core mode. And the wavelength of the interference dip would shift differently with the variation of the temperature. By this mean, we can achieve the measurement of temperature. The experimental results also show that the fiber sensor based on SMS structure has a highly temperature sensitivity. From 30° to 300°, with the temperature increasing, the interference dip slightly shifts toward longer wavelength and the temperature sensitivity coefficient is 0.0115nm/°. With high sensitivity, simple structure, immunity to electromagnetic interferences and a good linearity of the experimental results, the structure has an excellent application prospect in engineering field.

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

    SciTech Connect

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

    2014-06-15

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

  4. A Parallel Point Matching Algorithm for Landmark Based Image Registration Using Multicore Platform

    PubMed Central

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

    2013-01-01

    Point matching is crucial for many computer vision applications. Establishing the correspondence between a large number of data points is a computationally intensive process. Some point matching related applications, such as medical image registration, require real time or near real time performance if applied to critical clinical applications like image assisted surgery. In this paper, we report a new multicore platform based parallel algorithm for fast point matching in the context of landmark based medical image registration. We introduced a non-regular data partition algorithm which utilizes the K-means clustering algorithm to group the landmarks based on the number of available processing cores, which optimize the memory usage and data transfer. We have tested our method using the IBM Cell Broadband Engine (Cell/B.E.) platform. The results demonstrated a significant speed up over its sequential implementation. The proposed data partition and parallelization algorithm, though tested only on one multicore platform, is generic by its design. Therefore the parallel algorithm can be extended to other computing platforms, as well as other point matching related applications. PMID:24308014

  5. 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.

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  8. 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.

  9. Multimodal Discrimination of Alzheimer’s Disease Based on Regional Cortical Atrophy and Hypometabolism

    PubMed Central

    Yun, Hyuk Jin; Kwak, Kichang; Lee, Jong-Min

    2015-01-01

    Structural MR image (MRI) and 18F-Fluorodeoxyglucose-positron emission tomography (FDG-PET) have been widely employed in diagnosis of both Alzheimer’s disease (AD) and mild cognitive impairment (MCI) pathology, which has led to the development of methods to distinguish AD and MCI from normal controls (NC). Synaptic dysfunction leads to a reduction in the rate of metabolism of glucose in the brain and is thought to represent AD progression. FDG-PET has the unique ability to estimate glucose metabolism, providing information on the distribution of hypometabolism. In addition, patients with AD exhibit significant neuronal loss in cerebral regions, and previous AD research has shown that structural MRI can be used to sensitively measure cortical atrophy. In this paper, we introduced a new method to discriminate AD from NC based on complementary information obtained by FDG and MRI. For accurate classification, surface-based features were employed and 12 predefined regions were selected from previous studies based on both MRI and FDG-PET. Partial least square linear discriminant analysis was employed for making diagnoses. We obtained 93.6% classification accuracy, 90.1% sensitivity, and 96.5% specificity in discriminating AD from NC. The classification scheme had an accuracy of 76.5% and sensitivity and specificity of 46.5% and 89.6%, respectively, for discriminating MCI from AD. Our method exhibited a superior classification performance compared with single modal approaches and yielded parallel accuracy to previous multimodal classification studies using MRI and FDG-PET. PMID:26061669

  10. 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

  11. Arbitrary-ratio 1 × 2 power splitter based on asymmetric multimode interference.

    PubMed

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

    2014-10-01

    Free choice of splitting ratio is one of the main properties of a power splitter required in integrated photonics, but conventional multimode interference (MMI) power splitters can only obtain a few discrete ratios. This Letter presents both numerical and experimental results of an arbitrary-ratio 1×2 MMI power splitter, which is constructed by simply breaking the symmetry of the multimode region. In the new device, the power splitting ratio can be adjusted continuously from 100:0 to 50:50, while the dimension of the multimode section stays in the range of 1.5×(1.8-2.8)  μm. The experimental data also indicate that the proposed arbitrary-ratio splitter keeps the original advantages of MMI devices, such as low excess loss, weak wavelength dependence, and large fabrication tolerance.

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

    PubMed

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

    2011-08-01

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

  13. 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.

  14. 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.

  15. 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.

  16. 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 .

  17. A constrained registration problem based on Ciarlet-Geymonat stored energy

    NASA Astrophysics Data System (ADS)

    Derfoul, Ratiba; Le Guyader, Carole

    2014-03-01

    In this paper, we address the issue of designing a theoretically well-motivated registration model capable of handling large deformations and including geometrical constraints, namely landmark points to be matched, in a variational framework. The theory of linear elasticity being unsuitable in this case, since assuming small strains and the validity of Hooke's law, the introduced functional is based on nonlinear elasticity principles. More precisely, the shapes to be matched are viewed as Ciarlet-Geymonat materials. We demonstrate the existence of minimizers of the related functional minimization problem and prove a convergence result when the number of geometric constraints increases. We then describe and analyze a numerical method of resolution based on the introduction of an associated decoupled problem under inequality constraint in which an auxiliary variable simulates the Jacobian matrix of the deformation field. A theoretical result of 􀀀-convergence is established. We then provide preliminary 2D results of the proposed matching model for the registration of mouse brain gene expression data to a neuroanatomical mouse atlas.

  18. Local sphere-based co-registration for SAM group analysis in subjects without individual MRI.

    PubMed

    Steinstraeter, O; Teismann, Inga K; Wollbrink, A; Suntrup, S; Stoeckigt, K; Dziewas, R; Pantev, C

    2009-03-01

    Synthetic aperture magnetometry (SAM) is a powerful MEG source localization method to analyze evoked as well as induced brain activity. To gain structural information of the underlying sources, especially in group studies, individual magnetic resonance images (MRI) are required for co-registration. During the last few years, the relevance of MEG measurements on understanding the pathophysiology of different diseases has noticeable increased. Unfortunately, especially in patients and small children, structural MRI scans cannot always be performed. Therefore, we developed a new method for group analysis of SAM results without requiring structural MRI data that derives its geometrical information from the individual volume conductor model constructed for the SAM analysis. The normalization procedure is fast, easy to implement and integrates seamlessly into an existing landmark based MEG-MRI co-registration procedure. This new method was evaluated on different simulated points as well as on a pneumatic index finger stimulation paradigm analyzed with SAM. Compared with an established MRI-based normalization procedure (SPM2) the new method shows only minor errors in single subject results as well as in group analysis. The mean difference between the two methods was about 4 mm for the simulated as well as for finger stimulation data. The variation between individual subjects was generally higher than the error induced by the missing MRIs. The method presented here is therefore sufficient for most MEG group studies. It allows accomplishing MEG studies with subject groups where MRI measurements cannot be performed.

  19. 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…

  20. 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.

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

    PubMed Central

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

    2014-01-01

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

  2. 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.

  3. 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

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

    NASA Astrophysics Data System (ADS)

    Lampe, André; Tadeus, Georgi; Schmoranzer, Jan

    2015-09-01

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

  5. 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…

  6. 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…

  7. 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.

  8. Entropy-Based Registration of Point Clouds Using Terrestrial Laser Scanning and Smartphone GPS

    PubMed Central

    Chen, Maolin; Wang, Siying; Wang, Mingwei; Wan, Youchuan; He, Peipei

    2017-01-01

    Automatic registration of terrestrial laser scanning point clouds is a crucial but unresolved topic that is of great interest in many domains. This study combines terrestrial laser scanner with a smartphone for the coarse registration of leveled point clouds with small roll and pitch angles and height differences, which is a novel sensor combination mode for terrestrial laser scanning. The approximate distance between two neighboring scan positions is firstly calculated with smartphone GPS coordinates. Then, 2D distribution entropy is used to measure the distribution coherence between the two scans and search for the optimal initial transformation parameters. To this end, we propose a method called Iterative Minimum Entropy (IME) to correct initial transformation parameters based on two criteria: the difference between the average and minimum entropy and the deviation from the minimum entropy to the expected entropy. Finally, the presented method is evaluated using two data sets that contain tens of millions of points from panoramic and non-panoramic, vegetation-dominated and building-dominated cases and can achieve high accuracy and efficiency. PMID:28117693

  9. Entropy-Based Registration of Point Clouds Using Terrestrial Laser Scanning and Smartphone GPS.

    PubMed

    Chen, Maolin; Wang, Siying; Wang, Mingwei; Wan, Youchuan; He, Peipei

    2017-01-20

    Automatic registration of terrestrial laser scanning point clouds is a crucial but unresolved topic that is of great interest in many domains. This study combines terrestrial laser scanner with a smartphone for the coarse registration of leveled point clouds with small roll and pitch angles and height differences, which is a novel sensor combination mode for terrestrial laser scanning. The approximate distance between two neighboring scan positions is firstly calculated with smartphone GPS coordinates. Then, 2D distribution entropy is used to measure the distribution coherence between the two scans and search for the optimal initial transformation parameters. To this end, we propose a method called Iterative Minimum Entropy (IME) to correct initial transformation parameters based on two criteria: the difference between the average and minimum entropy and the deviation from the minimum entropy to the expected entropy. Finally, the presented method is evaluated using two data sets that contain tens of millions of points from panoramic and non-panoramic, vegetation-dominated and building-dominated cases and can achieve high accuracy and efficiency.

  10. Joint geometric and photometric direct image registration based on Lie algebra parameterization

    NASA Astrophysics Data System (ADS)

    Li, Chenxi; Shi, Zelin; Liu, Yunpeng

    2016-10-01

    In this paper, we consider direct image registration problem which estimate the geometric and photometric transformations between two images. The efficient second-order minimization method (ESM) is based on a second-order Taylor series of image differences without computing the Hessian under brightness constancy assumption. This can be done due to the fact that the considered geometric transformations is Lie group and can be parameterized by its Lie algebra. In order to deal with lighting changes, we extend ESM to the compositional dual efficient second-order minimization method (CDESM). In our approach, the photometric transformations is parameterized by its Lie algebra with compositional operation, which is similar to that of geometric transformations. Our algorithm can give a second-order approximation of image differences with respect to geometric and photometric parameters. The geometric and photometric parameters are simultaneously obtained by non-linear least-square optimization. Our algorithm preserves the advantages of the original ESM method which has high convergence rate and large capture radius. Experimental results show that our algorithm is more robust to lighting changes and has higher registration accuracy compared to previous algorithms.

  11. Multimodal, high-dimensional, model-based, Bayesian inverse problems with applications in biomechanics

    NASA Astrophysics Data System (ADS)

    Franck, I. M.; Koutsourelakis, P. S.

    2017-01-01

    This paper is concerned with the numerical solution of model-based, Bayesian inverse problems. We are particularly interested in cases where the cost of each likelihood evaluation (forward-model call) is expensive and the number of unknown (latent) variables is high. This is the setting in many problems in computational physics where forward models with nonlinear PDEs are used and the parameters to be calibrated involve spatio-temporarily varying coefficients, which upon discretization give rise to a high-dimensional vector of unknowns. One of the consequences of the well-documented ill-posedness of inverse problems is the possibility of multiple solutions. While such information is contained in the posterior density in Bayesian formulations, the discovery of a single mode, let alone multiple, poses a formidable computational task. The goal of the present paper is two-fold. On one hand, we propose approximate, adaptive inference strategies using mixture densities to capture multi-modal posteriors. On the other, we extend our work in [1] with regard to effective dimensionality reduction techniques that reveal low-dimensional subspaces where the posterior variance is mostly concentrated. We validate the proposed model by employing Importance Sampling which confirms that the bias introduced is small and can be efficiently corrected if the analyst wishes to do so. We demonstrate the performance of the proposed strategy in nonlinear elastography where the identification of the mechanical properties of biological materials can inform non-invasive, medical diagnosis. The discovery of multiple modes (solutions) in such problems is critical in achieving the diagnostic objectives.

  12. MIND Demons: Symmetric Diffeomorphic Deformable Registration of MR and CT for Image-Guided Spine Surgery

    PubMed Central

    Reaungamornrat, Sureerat; De Silva, Tharindu; Uneri, Ali; Vogt, Sebastian; Kleinszig, Gerhard; Khanna, Akhil J; Wolinsky, Jean-Paul; Prince, Jerry L.

    2016-01-01

    Intraoperative localization of target anatomy and critical structures defined in preoperative MR/CT images can be achieved through the use of multimodality deformable registration. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality-independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. The method, called MIND Demons, finds a deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the integrated velocity fields, a modality-insensitive similarity function suitable to multimodality images, and smoothness on the diffeomorphisms themselves. Direct optimization without relying on the exponential map and stationary velocity field approximation used in conventional diffeomorphic Demons is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, normalized MI (NMI) Demons, and MIND with a diffusion-based registration method (MIND-elastic). The method yielded sub-voxel invertibility (0.008 mm) and nonzero-positive Jacobian determinants. It also showed improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.7 mm compared to 11.3, 3.1, 5.6, and 2.4 mm for MI FFD, LMI FFD, NMI Demons, and MIND-elastic methods, respectively. Validation in clinical studies demonstrated realistic deformations with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. PMID:27295656

  13. MIND Demons: Symmetric Diffeomorphic Deformable Registration of MR and CT for Image-Guided Spine Surgery.

    PubMed

    Reaungamornrat, Sureerat; De Silva, Tharindu; Uneri, Ali; Vogt, Sebastian; Kleinszig, Gerhard; Khanna, Akhil J; Wolinsky, Jean-Paul; Prince, Jerry L; Siewerdsen, Jeffrey H

    2016-11-01

    Intraoperative localization of target anatomy and critical structures defined in preoperative MR/CT images can be achieved through the use of multimodality deformable registration. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality-independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. The method, called MIND Demons, finds a deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the integrated velocity fields, a modality-insensitive similarity function suitable to multimodality images, and smoothness on the diffeomorphisms themselves. Direct optimization without relying on the exponential map and stationary velocity field approximation used in conventional diffeomorphic Demons is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, normalized MI (NMI) Demons, and MIND with a diffusion-based registration method (MIND-elastic). The method yielded sub-voxel invertibility (0.008 mm) and nonzero-positive Jacobian determinants. It also showed improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.7 mm compared to 11.3, 3.1, 5.6, and 2.4 mm for MI FFD, LMI FFD, NMI Demons, and MIND-elastic methods, respectively. Validation in clinical studies demonstrated realistic deformations with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine.

  14. 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.

  15. 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

  16. 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.

  17. Registration and machine learning-based automated segmentation of subcortical and cerebellar brain structures.

    PubMed

    Powell, Stephanie; Magnotta, Vincent A; Johnson, Hans; Jammalamadaka, Vamsi K; Pierson, Ronald; Andreasen, Nancy C

    2008-01-01

    The large amount of imaging data collected in several ongoing multi-center studies requires automated methods to delineate brain structures of interest. We have previously reported on using artificial neural networks (ANN) to define subcortical brain structures. Here we present several automated segmentation methods using multidimensional registration. A direct comparison between template, probability, artificial neural network (ANN) and support vector machine (SVM)-based automated segmentation methods is presented. Three metrics for each segmentation method are reported in the delineation of subcortical and cerebellar brain regions. Results show that the machine learning methods outperform the template and probability-based methods. Utilization of these automated segmentation methods may be as reliable as manual raters and require no rater intervention.

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  20. 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.

  1. 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)

  2. The Direct Registration of LIDAR Point Clouds and High Resolution Image Based on Linear Feature by Introducing AN Unknown Parameter

    NASA Astrophysics Data System (ADS)

    Chunjing, Y.; Guang, G.

    2012-07-01

    The registration between optical images and point clouds is the first task when the combination of these two datasets is concerned. Due to the discrete nature of the point clouds, and the 2D-3D transformation in particular, a tie points based registration strategy which is commonly adopted in image-to-image registration is hard to be used directly in this scenario. A derived collinear equation describing the map relationship between an image point and a ground point is used as the mathematical model for registration, with the point in the LiDAR space expressed by its parametric form. such a map relation can be viewed as the mathematical model which registers the image pixels to point clouds. This model is not only suitable for a single image registration but also applicable to multiple consecutive images. We also studied scale problem in image and point clouds registration, with scale problem is defined by the optimal corresponding between the image resolution and the density of point clouds. Test dataset includes the DMC images and point clouds acquired by the Leica ALS50 II over an area in Henan Prov., China. Main contributions of the paper includes: [1] an derived collinear equation is introduced by which a ground point is expressed by its parametric form, which makes it possible to replace point feature by linear feature, hence avoiding the problem that it is almost impossible to find a point in the point clouds which is accurately corresponds to a point in the image space; [2] least square method is used to calculate the registration transformation parameters and the unknown parameter λ in the same time;[3] scale problem is analyzed semi-quantitatively and to the authors' best knowledge, it is the first time in literature that clearly defines the scale problem and carries out semi-quantitative analysis in the context of LiDAR data processing.

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

    PubMed

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

    2016-08-01

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

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

    PubMed Central

    Lee, Joohwi; Lyu, Ilwoo; Styner, Martin

    2014-01-01

    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. PMID:25075158

  5. A novel skull registration based on global and local deformations for craniofacial reconstruction.

    PubMed

    Deng, Qingqiong; Zhou, Mingquan; Shui, Wuyang; Wu, Zhongke; Ji, Yuan; Bai, Ruyi

    2011-05-20

    Craniofacial reconstruction is important in forensic identification. It aims to estimate a facial appearance for human skeletal remains using the relationship between the soft tissue and the underlying bone structure. Various computerized methods have been developed in recent decades. An effective way is to deform a reference skull to the discovered skull, and then apply the same deformation to the skin associated with the reference skull to provide an approximate face for the discovered skull. For this method, the better the two skulls match each other, the more face-like the reconstructed skin surface will be. In this paper, we present a novel skull registration method that can match the two skulls closely, so as to improve the accuracy of the reconstruction. It combines both global and local deformations. A generic thin-plate spline (TPS)-based deformation, which is global, is applied first to roughly align the two skulls based on two groups of manually defined landmarks. Afterwards, the two skulls are largely matched, except some regions, on which some new landmarks are automatically marked. A compact support radial basis functions (CSRBF)-based deformation, which is local, will then be performed on these regions to adjust the initial alignment of the two skulls. Such adjustment can be repeatedly implemented until the two skulls have optimal alignment. In addition, all the skulls and face involved in the registration are represented by their single outer surfaces to facilitate the reconstruction procedure. The experiments demonstrate that our method can create a plausible face even when the reference skull is very different from the discovered skull. As a result, we can make full use of our database to provide multiple estimates for a principle components analysis (PCA) for the final reconstruction.

  6. 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

  7. A comparative study of Powell's and Downhill Simplex algorithms for a fast multimodal surface matching in brain imaging.

    PubMed

    Bernon, J L; Boudousq, V; Rohmer, J F; Fourcade, M; Zanca, M; Rossi, M; Mariano-Goulart, D

    2001-01-01

    Multimodal images registration can be very helpful for diagnostic applications. However, even if a lot of registration algorithms exist, only a few really work in clinical routines. We developed a method based on surface matching and compared two minimization algorithms: Powell's and Downhill Simplex. We studied the influence of some factors (chamfer map computation, number and order of parameters to determine, minimization criteria) on the final accuracy of the algorithm. Using this comparison, we improved some processing steps to allow a clinical use, and selected the simplex algorithm which presented the best results.

  8. 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.

  9. Spatial Frequency Multiplexing of Fiber-Optic Interferometric Refractive Index Sensors Based on Graded-Index Multimode Fibers

    PubMed Central

    Liu, Li; Gong, Yuan; Wu, Yu; Zhao, Tian; Wu, Hui-Juan; Rao, Yun-Jiang

    2012-01-01

    Fiber-optic interferometric sensors based on graded-index multimode fibers have very high refractive-index sensitivity, as we previously demonstrated. In this paper, spatial-frequency multiplexing of this type of fiber-optic refractive index sensors is investigated. It is estimated that multiplexing of more than 10 such sensors is possible. In the multiplexing scheme, one of the sensors is used to investigate the refractive index and temperature responses. The fast Fourier transform (FFT) of the combined reflective spectra is analyzed. The intensity of the FFT spectra is linearly related with the refractive index and is not sensitive to the temperature.

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  11. 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.

  12. Relative humidity sensor based on SMS fiber structure using multimode coreless fiber

    NASA Astrophysics Data System (ADS)

    Syafrani, Sanif; Hatta, Agus M.; Kusumawardhani, Apriani

    2016-11-01

    Singlemode-Multimode-Singlemode (SMS) optical fiber structure using multimode coreless have been able to sense changes in relative humidity. In this experiment the measured humidity is 60 % -90 %, while the method is done by comparing the relative humidity changes with the change in output power in the optical fiber. Then the underlying phenomena is the change in the refractive index of air as the cladding MMF coreless due to changes in relative humidity. It has been done three length variations MMF coreless to add sensitivity sensor, and the obtained sensor by 22.30 mm MMF length have the greatest sensitivity, that is 0.0747 dBm / %. Obtained conclusions on length variation will cause any change in the sensitivity significantly in relative humidity between 75 % -80 %.

  13. 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.

  14. 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.

  15. 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.

  16. An Automatic Registration-Fusion Scheme Based on Similarity Measures: An Application to Dental Imaging

    DTIC Science & Technology

    2007-11-02

    calculation of similarity measures between two dental radiographic images to be registered. Moreover, a fusion process has been developed to combine...information from registered dental images. Result on clinical data reveals the advantageous performance of the proposed automatic registration method...registration approach outperforms despite the fuzzy dental boundaries and the lack of characteristic edges of the radiographic images. These preliminary

  17. The heterogeneity of the left dorsal premotor cortex evidenced by multimodal connectivity-based parcellation and functional characterization.

    PubMed

    Genon, Sarah; Reid, Andrew; Li, Hai; Fan, Lingzhong; Müller, Veronika I; Cieslik, Edna C; Hoffstaedter, Felix; Langner, Robert; Grefkes, Christian; Laird, Angela R; Fox, Peter T; Jiang, Tianzi; Amunts, Katrin; Eickhoff, Simon B

    2017-02-14

    Despite the common conception of the dorsal premotor cortex (PMd) as a single brain region, its diverse connectivity profiles and behavioral heterogeneity argue for a differentiated organization of the PMd. A previous study revealed that the right PMd is characterized by a rostro-caudal and a ventro-dorsal distinction dividing it into five subregions: rostral, central, caudal, ventral and dorsal. The present study assessed whether a similar organization is present in the left hemisphere, by capitalizing on a multimodal data-driven approach combining connectivity-based parcellation (CBP) based on meta-analytic modeling, resting-state functional connectivity, and probabilistic diffusion tractography. The resulting PMd modules were then characterized based on multimodal functional connectivity and a quantitative analysis of associated behavioral functions. Analyzing the clusters consistent across all modalities revealed an organization of the left PMd that mirrored its right counterpart to a large degree. Again, caudal, central and rostral modules reflected a cognitive-motor gradient and a premotor eye-field was found in the ventral part of the left PMd. In addition, a distinct module linked to abstract cognitive functions was observed in the rostro-ventral left PMd across all CBP modalities, implying greater differentiation of higher cognitive functions for the left than the right PMd.

  18. 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.

  19. Registration of Vehicle-Borne Point Clouds and Panoramic Images Based on Sensor Constellations.

    PubMed

    Yao, Lianbi; Wu, Hangbin; Li, Yayun; Meng, Bin; Qian, Jinfei; Liu, Chun; Fan, Hongchao

    2017-04-11

    A mobile mapping system (MMS) is usually utilized to collect environmental data on and around urban roads. Laser scanners and panoramic cameras are the main sensors of an MMS. This paper presents a new method for the registration of the point clouds and panoramic images based on sensor constellation. After the sensor constellation was analyzed, a feature point, the intersection of the connecting line between the global positioning system (GPS) antenna and the panoramic camera with a horizontal plane, was utilized to separate the point clouds into blocks. The blocks for the central and sideward laser scanners were extracted with the segmentation feature points. Then, the point clouds located in the blocks were separated from the original point clouds. Each point in the blocks was used to find the accurate corresponding pixel in the relative panoramic images via a collinear function, and the position and orientation relationship amongst different sensors. A search strategy is proposed for the correspondence of laser scanners and lenses of panoramic cameras to reduce calculation complexity and improve efficiency. Four cases of different urban road types were selected to verify the efficiency and accuracy of the proposed method. Results indicate that most of the point clouds (with an average of 99.7%) were successfully registered with the panoramic images with great efficiency. Geometric evaluation results indicate that horizontal accuracy was approximately 0.10-0.20 m, and vertical accuracy was approximately 0.01-0.02 m for all cases. Finally, the main factors that affect registration accuracy, including time synchronization amongst different sensors, system positioning and vehicle speed, are discussed.

  20. 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…

  1. 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.

  2. 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.

  3. 40 CFR 155.58 - Procedures for issuing a decision on a registration review case.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

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

  4. 40 CFR 155.58 - Procedures for issuing a decision on a registration review case.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

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

  5. 40 CFR 155.58 - Procedures for issuing a decision on a registration review case.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

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

  6. 40 CFR 155.58 - Procedures for issuing a decision on a registration review case.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

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

  7. A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

    PubMed Central

    Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu

    2017-01-01

    The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. Evaluation of accuracy of B-spline transformation-based deformable image registration with different parameter settings for thoracic images.

    PubMed

    Kanai, Takayuki; Kadoya, Noriyuki; Ito, Kengo; Onozato, Yusuke; Cho, Sang Yong; Kishi, Kazuma; Dobashi, Suguru; Umezawa, Rei; Matsushita, Haruo; Takeda, Ken; Jingu, Keiichi

    2014-11-01

    Deformable image registration (DIR) is fundamental technique for adaptive radiotherapy and image-guided radiotherapy. However, further improvement of DIR is still needed. We evaluated the accuracy of B-spline transformation-based DIR implemented in elastix. This registration package is largely based on the Insight Segmentation and Registration Toolkit (ITK), and several new functions were implemented to achieve high DIR accuracy. The purpose of this study was to clarify whether new functions implemented in elastix are useful for improving DIR accuracy. Thoracic 4D computed tomography images of ten patients with esophageal or lung cancer were studied. Datasets for these patients were provided by DIR-lab (dir-lab.com) and included a coordinate list of anatomical landmarks that had been manually identified. DIR between peak-inhale and peak-exhale images was performed with four types of parameter settings. The first one represents original ITK (Parameter 1). The second employs the new function of elastix (Parameter 2), and the third was created to verify whether new functions improve DIR accuracy while keeping computational time (Parameter 3). The last one partially employs a new function (Parameter 4). Registration errors for these parameter settings were calculated using the manually determined landmark pairs. 3D registration errors with standard deviation over all cases were 1.78 (1.57), 1.28 (1.10), 1.44 (1.09) and 1.36 (1.35) mm for Parameter 1, 2, 3 and 4, respectively, indicating that the new functions are useful for improving DIR accuracy, even while maintaining the computational time, and this B-spline-based DIR could be used clinically to achieve high-accuracy adaptive radiotherapy.

  19. 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.

  20. 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

  1. 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.

  2. Gene to mouse atlas registration using a landmark-based nonlinear elasticity smoother

    NASA Astrophysics Data System (ADS)

    Lin, Tungyou; Le Guyader, Carole; Lee, Erh-Fang; Dinov, Ivo D.; Thompson, Paul M.; Toga, Arthur W.; Vese, Luminita A.

    2009-02-01

    We propose a unified variational approach for registration of gene expression data to neuroanatomical mouse atlas in two dimensions. The proposed energy (minimized in the unknown displacement u) is composed of three terms: a standard data fidelity term based on L2 similarity measure, a regularizing term based on nonlinear elasticity (allowing larger smooth deformations), and a geometric penalty constraint for landmark matching. We overcome the difficulty of minimizing the nonlinear elasticity functional by introducing an auxiliary variable v that approximates ∇u, the Jacobian of the unknown displacement u. We therefore minimize now the functional with respect to the unknowns u (a vector-valued function of two dimensions) and v (a two-by-two matrix-valued function). An additional quadratic term is added, to insure good agreement between v and ∇u. In this way, the nonlinearity in the derivatives of the unknown u no longer exists in the obtained Euler-Lagrange equations, producing simpler implementations. Several satisfactory experimental results show that gene expression data are mapped to a mouse atlas with good landmark matching and smooth deformation. We also present comparisons with the biharmonic regularization. An advantage of the proposed nonlinear elasticity model is that usually no numerical correction such as regridding is necessary to keep the deformation smooth, while unifying the data fidelity term, regularization term, and landmark constraints in a single minimization approach.

  3. Ultrasound calibration using intensity-based image registration: for application in cardiac catheterization procedures

    NASA Astrophysics Data System (ADS)

    Ma, Y. L.; Rhode, K. S.; Gao, G.; King, A. P.; Chinchapatnam, P.; Schaeffter, T.; Hawkes, D. J.; Razavi, R.; Penney, G. P.

    2008-03-01

    We present a novel method to calibrate a 3D ultrasound probe which has a 2D transducer array. By optically tracking a calibrated 3D probe we are able to produce extended field of view 3D ultrasound images. Tracking also enables us to register our ultrasound images to other tracked and calibrated surgical instruments or to other tracked and calibrated imaging devices. Our method applies rigid intensity-based image registration to three or more ultrasound images. These images can either be of a simple phantom, or could potentially be images of the patient. In this latter case we would have an automated calibration system which required no phantom, no image segmentation and was optimized to the patient's ultrasound characteristics i.e. speed of sound. We have carried out experiments using a simple calibration phantom and with ultrasound images of a volunteer's liver. Results are compared to an independent gold-standard. These showed our method to be accurate to 1.43mm using the phantom images and 1.56mm using the liver data, which is slightly better than the traditional point-based calibration method (1.7mm in our experiments).

  4. 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.

  5. 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.

  6. A New Approach to Evaluate Drug Treatment Response of Ovarian Cancer Patients Based on Deformable Image Registration

    PubMed Central

    Tan, Maxine; Li, Zheng; Qiu, Yuchen; McMeekin, Scott D.; Thai, Theresa C.; Ding, Kai; Moore, Kathleen N.; Liu, Hong; Zheng, Bin

    2016-01-01

    Although Response Evaluation Criteria in Solid Tumors (RECIST) is the current clinical guideline to assess size change of solid tumors after therapeutic treatment, it has a relatively lower association to the clinical outcome of progression free survival (PFS) of the patients. In this paper, we presented a new approach to assess responses of ovarian cancer patients to new chemotherapy drugs in clinical trials. We first developed and applied a multi-resolution B-spline based deformable image registration method to register two sets of computed tomography (CT) image data acquired pre- and post-treatment. The B-spline difference maps generated from the co-registered CT images highlight the regions related to the volumetric growth or shrinkage of the metastatic tumors, and density changes related to variation of necrosis inside the solid tumors. Using a testing dataset involving 19 ovarian cancer patients, we compared patients’ response to the treatment using the new image registration method and RECIST guideline. The results demonstrated that using the image registration method yielded higher association with the six-month PFS outcomes of the patients than using RECIST. The image registration results also provided a solid foundation of developing new computerized quantitative image feature analysis schemes in the future studies. PMID:26336119

  7. 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).

  8. Tissue Feature-Based and Segmented Deformable Image Registration for Improved Modeling of Shear Movement of Lungs

    SciTech Connect

    Xie Yaoqin; Chao Ming; Xing Lei

    2009-07-15

    Purpose: To report a tissue feature-based image registration strategy with explicit inclusion of the differential motions of thoracic structures. Methods and Materials: The proposed technique started with auto-identification of a number of corresponding points with distinct tissue features. The tissue feature points were found by using the scale-invariant feature transform method. The control point pairs were then sorted into different 'colors' according to the organs in which they resided and used to model the involved organs individually. A thin-plate spline method was used to register a structure characterized by the control points with a given 'color.' The proposed technique was applied to study a digital phantom case and 3 lung and 3 liver cancer patients. Results: For the phantom case, a comparison with the conventional thin-plate spline method showed that the registration accuracy was markedly improved when the differential motions of the lung and chest wall were taken into account. On average, the registration error and standard deviation of the 15 points against the known ground truth were reduced from 3.0 to 0.5 mm and from 1.5 to 0.2 mm, respectively, when the new method was used. A similar level of improvement was achieved for the clinical cases. Conclusion: The results of our study have shown that the segmented deformable approach provides a natural and logical solution to model the discontinuous organ motions and greatly improves the accuracy and robustness of deformable registration.

  9. Image registration with uncertainty analysis

    DOEpatents

    Simonson, Katherine M [Cedar Crest, NM

    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.

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

    NASA Astrophysics Data System (ADS)

    Ziegler, Benjamin; Rauhut, Guntram

    2016-03-01

    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.

  11. C-band fundamental/first-order mode converter based on multimode interference coupler on InP substrate

    NASA Astrophysics Data System (ADS)

    Limeng, Zhang; Dan, Lu; Zhaosong, Li; Biwei, Pan; Lingjuan, Zhao

    2016-12-01

    The design, fabrication and characterization of a fundamental/first-order mode converter based on multimode interference coupler on InP substrate were reported. Detailed optimization of the device parameters were investigated using 3D beam propagation method. In the experiments, the fabricated mode converter realized mode conversion from the fundamental mode to the first-order mode in the wavelength range of 1530-1565 nm with excess loss less than 3 dB. Moreover, LP01 and LP11 fiber modes were successfully excited from a few-mode fiber by using the device. This InP-based mode converter can be a possible candidate for integrated transceivers for future mode-division multiplexing system. Project supported by the National Basic Research Program of China (No. 2014CB340102) and in part by the National Natural Science Foundation of China (Nos. 61274045, 61335009).

  12. Multimodal interference based on large-core air-clad photonic crystal fibres for simultaneous measurement of multiparameters

    NASA Astrophysics Data System (ADS)

    Silva, Susana; Santos, J. L.; Malcata, F. X.; Kobelke, Jens; Schuster, Kay; Frazão, O.

    2011-05-01

    This work describes a large-core air-clad photonic crystal fibre-based sensing structure that is sensitive to refractive index, temperature and strain. The sensing head is based on multimodal interference, and relies on a single mode - largecore air-clad photonic crystal fibre - single mode fibre configuration. Using two distinct large-core air-clad PCF geometries it is possible to obtain an optical spectrum with two dominant loss bands, at wavelengths that have different sensitivities to physical parameters. This characteristic is explored to demonstrate a sensing head that permits the straintemperature discrimination functionality. It is also shown the large-core air-clad photonic crystal fibre can be applied to implement a sensing head sensitive to the water refractive index changes induced by temperature variations.

  13. Evaluation of accuracy in frame-based versus fiducial-based registration for stereotaxy in Parkinson's deep electrode implantation

    NASA Astrophysics Data System (ADS)

    Abbasi, Hamid R.; Hariri, Sanaz; Lee, Jeffrey; Martin, David; Hill, B.; Heit, Gary

    2001-05-01

    After several years of levodopa treatment, patients with Parkinson's Disease (PD) can develop difficult-to-control motor fluctuations and levodopa-induced dyskinesias (LID). Surgical options for these medically intractable PD patients include deep nucleus lesioning and stimulation. Because it is adjustable and reversible, deep brain stimulations (DBS) is preferable to ablative procedures. Traditionally, frame- based stereotaxy has been used to register these patients during deep electrode implantation. This study investigated the accuracy of the less invasive frameless registration method in 9 patients and found an overall mean error of 1.9mm (range: 1.1mm min, 2.7mm max) with an overall SD of 0.7mm. This error range is not acceptable for the submillimeter precision needed in microelectrode implantation. The lab is currently investing the accuracy of the frameless bone-screw marker method that is still less invasive and cumbersome than the frame-based system.

  14. 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

  15. Problems in data registration for persistent sensing

    NASA Astrophysics Data System (ADS)

    Jwa, Sangil; Özgüner, Ümit

    2008-04-01

    Persistent sensing by Unmanned Airborne Vehicles (UAVs) has brought up challenging issues including multi-scale analysis, multi-modal sensor fusion, and scene localization. As for the first issue, the multi-scale and multi-resolution issues occur when a mobile sensor changes altitudes or two different sensors with the same camera provide any redundant images from different altitudes. To overcome these issues, we first focus on collecting invariant feature data from the multi-resolution representation of a high resolution image. Recently, an information-theoretic matching criterion has been developed for robust data registration without any knowledge of feature correspondence. This criterion is used as an intelligent computing algorithm of choosing a good scale-representation that helps to find an unknown scaling factor between two different and redundant measurements. As for the second issue of multi-modal sensor fusion, we observe that Electro-optical (EO) and Infrared (IR) images in the DARPA VIVID database have an inherent scaling-difference, even though the different modalities come from the two fixed EO and IR sensors attached on the same mobile sensor. Here we provide a new experimental result of multi-modal data fusion that successfully combines complementary information via the process of data refinement. The recovered transformation reveals one of the fundamental characteristics of the two different modalities. The last issue of scene localization is required for identifying the scene visited before. In this paper, we demonstrate the trajectory of the mobile sensor based only on the extracted transformations (not relying on any telemetric data of the mobile sensor which is not available persistently) by projecting the center locations of image measurements onto the two dimensional reference coordinate.

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

    PubMed Central

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

    2016-01-01

    Abstract. 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

  17. An Approach of Registration between Remote Sensing Image and Electronic Chart Based on Coastal Line

    NASA Astrophysics Data System (ADS)

    Li, Ying; Yu, Shuiming; Li, Chuanlong

    Remote sensing plays an important role marine oil spill emergency. In order to implement a timely and effective countermeasure, it is important to provide exact position of oil spills. Therefore it is necessary to match remote sensing image and electronic chart properly. Variance ordinarily exists between oil spill image and electronic chart, although geometric correction is applied to remote sensing image. It is difficult to find the steady control points on sea to make exact rectification of remote sensing image. An improved relaxation algorithm was developed for finding the control points along the coastline since oil spills occurs generally near the coast. A conversion function is created with the least square, and remote sensing image can be registered with the vector map based on this function. SAR image was used as the remote sensing data and shape format map as the electronic chart data. The results show that this approach can guarantee the precision of the registration, which is essential for oil spill monitoring.

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

    PubMed Central

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

    2015-01-01

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

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  1. Symmetric Biomechanically Guided Prone-to-Supine Breast Image Registration.

    PubMed

    Eiben, Björn; Vavourakis, Vasileios; Hipwell, John H; Kabus, Sven; Buelow, Thomas; Lorenz, Cristian; Mertzanidou, Thomy; Reis, Sara; Williams, Norman R; Keshtgar, Mohammed; Hawkes, David J

    2016-01-01

    Prone-to-supine breast image registration has potential application in the fields of surgical and radiotherapy planning, image guided interventions, and multi-modal cancer diagnosis, staging, and therapy response prediction. However, breast image registration of three dimensional images acquired in different patient positions is a challenging problem, due to large deformations induced to the soft breast tissue caused by the change in gravity loading. We present a symmetric, biomechanical simulation based registration framework which aligns the images in a central, virtually unloaded configuration. The breast tissue is modelled as a neo-Hookean material and gravity is considered as the main source of deformation in the original images. In addition to gravity, our framework successively applies image derived forces directly into the unloading simulation in place of a subsequent image registration step. This results in a biomechanically constrained deformation. Using a finite difference scheme avoids an explicit meshing step and enables simulations to be performed directly in the image space. The explicit time integration scheme allows the motion at the interface between chest and breast to be constrained along the chest wall. The feasibility and accuracy of the approach presented here was assessed by measuring the target registration error (TRE) using a numerical phantom with known ground truth deformations, nine clinical prone MRI and supine CT image pairs, one clinical prone-supine CT image pair and four prone-supine MRI image pairs. The registration reduced the mean TRE for the numerical phantom experiment from initially 19.3 to 0.9 mm and the combined mean TRE for all fourteen clinical data sets from 69.7 to 5.6 mm.

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2014-10-01

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

  4. 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.

  5. Tunable 1 × 2 plasmonic splitter of dielectric-loaded graphene waveguide based on multimode interference

    NASA Astrophysics Data System (ADS)

    Wang, YueKe; Hong, XiaoRong; Sang, Tian; Yang, GuoFeng

    2016-12-01

    We study the multimode interference (MMI) effect in a dielectric-loaded graphene waveguide (DLGW) numerically by the finite element method. By conducting the dispersion relation of graphene plasmon (GP) modes, a 1 × 2 splitter of GPs is proposed. Structure parameters are designed on the basis of the self-imaging principle, and the calculation of electrical field distributions illustrates two-wavelength splitting. Owing to the tunable permittivity of graphene by bias voltages, the active control of wavelength routing is achieved. High extinction ratios can also be obtained, which proves good splitting performance. It is considered that our findings provide a smart way of designing a tunable plasmonic splitter in the infrared region.

  6. Optical fibre sensors based on multi-mode fibres and MIMO signal processing: an experimental approach

    NASA Astrophysics Data System (ADS)

    Ahrens, Andreas; Sandmann, Andre; Bremer, Kort; Roth, Bernhard; Lochmann, Steffen

    2015-09-01

    In this paper multiple-input multiple-output (MIMO) signal processing is investigated for fibre optic sensor applications. A (2 × 2) MIMO implementation is realized by using lower-order and higher-order mode groups of a graded-index (GI) multi-mode fibre (MMF) as separate transmission channels. A micro-bending pressure sensor changes these separate transmission characteristics and introduces additional crosstalk. By observing the weight-factors of the MIMO system the amount of load applied was determined. Experiments verified a good correlation between the change of the MIMO weight coefficients and the load applied to the sensor and thus verified that MIMO signal processing can beneficially be used for fibre optic sensor applications.

  7. Research on optical fiber magnetic field sensors based on multi-mode fiber and spherical structure

    NASA Astrophysics Data System (ADS)

    Wang, Yan; Tong, Zheng-rong; Zhang, Wei-hua; Luan, Pan-pan; Zhao, Yue; Xue, Li-fang

    2017-01-01

    A magnetic field sensor with a magnetic fluid (MF)-coated intermodal interferometer is proposed and experimentally demonstrated. The interferometer is formed by sandwiching a segment of single mode fiber (SMF) between a segment of multi-mode fiber (MMF) and a spherical structure. It can be considered as a cascade of the traditional SMF-MMF-SMF structure and MMF-SMF-sphere structure. The transmission spectral characteristics change with the variation of applied magnetic field. The experimental results exhibit that the magnetic field sensitivities for wavelength and transmission loss are 0.047 nm/mT and 0.215 dB/mT for the interference dip around 1 535.36 nm. For the interference dip around 1548.41nm, the sensitivities are 0.077 nm/mT and 0.243 dB/mT. Simultaneous measurement can be realized according to the different spectral responses.

  8. Multimodal human-machine interface based on a brain-computer interface and an electrooculography interface.

    PubMed

    Iáñez, Eduardo; Ùbeda, Andrés; Azorín, José M

    2011-01-01

    This paper describes a multimodal interface that combines a Brain-Computer Interface (BCI) with an electrooculography (EOG) interface. The non-invasive spontaneous BCI registers the electrical brain activity through surface electrodes. The EOG interface detects the eye movements through electrodes placed on the face around the eyes. Both kind of signals are registered together and processed to obtain the mental task that the user is thinking and the eye movement performed by the user. Both commands (mental task and eye movement) are combined in order to move a dot in a graphic user interface (GUI). Several experimental tests have been made where the users perform a trajectory to get closer to some targets. To perform the trajectory the user moves the dot in a plane with the EOG interface and using the BCI the dot changes its height.

  9. A wavelength encoded optical fiber sensor based on multimode interference in a coreless silica fiber

    NASA Astrophysics Data System (ADS)

    Zhang, Chenliang; Li, Enbang; Lv, Peng; Wang, Wei

    2008-12-01

    A wavelength encoded optical fiber sensor using a three-segmented fiber structure is proposed. The device consists of a coreless silica fiber (CSF) which is coated with a thin film and spliced between two standard single-mode fibers (SMFs), forming a SMF-CSF-SMF (SCS) structure. When light is transmitted from the SMF into the CSF, the LP01 mode in the SMF is coupled to the LP0n modes, and a multimode interference occurs in the CSF. These modes interact with the thin film, hence the thickness and refractive index of the thin film can affect the modal interference. We analyze the transmission spectra of the SCS structure to obtain the characteristics of the sensor including sensing sensitivity. Numerical simulations are carried out by using the Beam Propagation Method (BPM) to investigate the multimode interference in the SCS. Two different conditions are considered in our studies: 1) changing the refractive index of a fixed-thickness film, and 2) varying the film thickness with certain refractive index. It has been found that the wavelength corresponding to the minimum output power increases 0.33509 nm when the refractive index changes every 0.01 from 1.33 up to 1.40, and 6.760 nm when the thickness enhances form 0 to 1000 nm. The trend of the raise is mostly linear for the former simulation, but gets slower and slower for the latter. The SCS structure can serve as a fiber platform for non-labeling bio-sensing when a bio-film is coated to the CSF.

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  11. A compact thermo-optical multimode-interference silicon-based 1 × 4 nano-photonic switch.

    PubMed

    Zhou, Haifeng; Song, Junfeng; Chee, Edward K S; Li, Chao; Zhang, Huijuan; Lo, Guoqiang

    2013-09-09

    An ultra-compact multimode-interference (MMI)-based 1 × 4 nano-photonic switch is demonstrated by employing silicon thermo-optical effect on SOI platform. The device performance is systematically characterized by comprehensively investigating the constituent building blocks, including 1 × 4 power splitter, 4 × 4 MMI coupler and groove-isolated thermo-optical heaters. An instructive model is established to statistically estimate the required power consumption and investigate the influence of the power imbalance of the 4 × 4 MMI coupler on the switching performance. At the designed wavelength of 1550 nm, the average insertion loss of different switching states is 1.7 dB, and the transmission imbalance is 1.05 dB. The worst extinction ratio and crosstalk of all the output ports reach 11.48 dB and -11.38 dB, respectively.

  12. Acoustic emission source localization in thin metallic plates: A single-sensor approach based on multimodal edge reflections.

    PubMed

    Ebrahimkhanlou, A; Salamone, S

    2017-03-14

    This paper presents a new acoustic emission (AE) source localization for isotropic plates with reflecting boundaries. This approach that has no blind spot leverages multimodal edge reflections to identify AE sources with only a single sensor. The implementation of the proposed approach involves three main steps. First, the continuous wavelet transform (CWT) and the dispersion curves of the fundamental Lamb wave modes are utilized to estimate the distance between an AE source and a sensor. This step uses a modal acoustic emission approach. Then, an analytical model is proposed that uses the estimated distances to simulate the edge-reflected waves. Finally, the correlation between the experimental and the simulated waveforms is used to estimate the location of AE sources. Hsu-Nielsen pencil lead break (PLB) tests were performed on an aluminum plate to validate this algorithm and promising results were achieved. Based on these results, the paper reports the statistics of the localization errors.

  13. 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).

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

    SciTech Connect

    Saw, Cheng B. Chen Hungcheng; Wagner, Henry

    2008-07-01

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

  15. Adaptive robust image registration approach based on adequately sampling polar transform and weighted angular projection function

    NASA Astrophysics Data System (ADS)

    Wei, Zhao; Tao, Feng; Jun, Wang

    2013-10-01

    An efficient, robust, and accurate approach is developed for image registration, which is especially suitable for large-scale change and arbitrary rotation. It is named the adequately sampling polar transform and weighted angular projection function (ASPT-WAPF). The proposed ASPT model overcomes the oversampling problem of conventional log-polar transform. Additionally, the WAPF presented as the feature descriptor is robust to the alteration in the fovea area of an image, and reduces the computational cost of the following registration process. The experimental results show two major advantages of the proposed method. First, it can register images with high accuracy even when the scale factor is up to 10 and the rotation angle is arbitrary. However, the maximum scaling estimated by the state-of-the-art algorithms is 6. Second, our algorithm is more robust to the size of the sampling region while not decreasing the accuracy of the registration.

  16. Evaluating the Validity of Volume-Based and Surface-Based Brain Image Registration for Developmental Cognitive Neuroscience Studies in Children 4-to-11 Years of Age

    PubMed Central

    Ghosh, Satrajit S.; Kakunoori, Sita; Augustinack, Jean; Nieto-Castanon, Alfonso; Kovelman, Ioulia; Gaab, Nadine; Christodoulou, Joanna A.; Triantafyllou, Christina; Gabrieli, John D. E.; Fischl, Bruce

    2010-01-01

    Understanding the neurophysiology of human cognitive development relies on methods that enable accurate comparison of structural and functional neuroimaging data across brains from people of different ages. A fundamental question is whether the substantial brain growth and related changes in brain morphology that occur in early childhood permit valid comparisons of brain structure and function across ages. Here we investigated whether valid comparisons can be made in children from ages 4–11, and whether there are differences in the use of volume-based versus surface-based registration approaches for aligning structural landmarks across these ages. Regions corresponding to the calcarine sulcus, central sulcus, and Sylvian fissure in both the hemispheres were manually labeled on T1-weighted structural magnetic resonance images from 31 children ranging in age from 4.2 to 11.2 years old. Quantitative measures of shape similarity and volumetric-overlap of these manually labeled regions were calculated when brains were aligned using a 12-parameter affine transform, SPM's nonlinear normalization, a diffeomorphic registration (ANTS), and FreeSurfer's surface-based registration. Registration error for normalization into a common reference framework across participants in this age range was lower than commonly used functional imaging resolutions. Surface-based registration provided significantly better alignment of cortical landmarks than volume-based registration. In addition, registering children's brains to a common space does not result in an age-associated bias between older and younger children, making it feasible to accurately compare structural properties and patterns of brain activation in children from ages 4–11. PMID:20621657

  17. GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration

    NASA Astrophysics Data System (ADS)

    Sharp, G. C.; Kandasamy, N.; Singh, H.; Folkert, M.

    2007-09-01

    This paper shows how to significantly accelerate cone-beam CT reconstruction and 3D deformable image registration using the stream-processing model. We describe data-parallel designs for the Feldkamp, Davis and Kress (FDK) reconstruction algorithm, and the demons deformable registration algorithm, suitable for use on a commodity graphics processing unit. The streaming versions of these algorithms are implemented using the Brook programming environment and executed on an NVidia 8800 GPU. Performance results using CT data of a preserved swine lung indicate that the GPU-based implementations of the FDK and demons algorithms achieve a substantial speedup—up to 80 times for FDK and 70 times for demons when compared to an optimized reference implementation on a 2.8 GHz Intel processor. In addition, the accuracy of the GPU-based implementations was found to be excellent. Compared with CPU-based implementations, the RMS differences were less than 0.1 Hounsfield unit for reconstruction and less than 0.1 mm for deformable registration.

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

    SciTech Connect

    Penjweini, R; Zhu, T

    2015-06-15

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

  19. 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.

  20. MO-DE-202-02: Advances in Image Registration and Reconstruction for Image-Guided Neurosurgery.

    PubMed

    Siewerdsen, J

    2016-06-01

    At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: (1) Keyvan Farahani, "Image-guided focused ultrasound surgery and therapy" (2) Jeffrey H. Siewerdsen, "Advances in image registration and reconstruction for image-guided neurosurgery" (3) Tina Kapur, "Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite" (4) Raj Shekhar, "Multimodality image-guided interventions: Multimodality for the rest of us" Learning Objectives: 1. Understand the principles and applications of HIFU in surgical ablation. 2. Learn about recent advances in 3D-2D and 3D deformable image registration in support of surgical safety and precision. 3. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. 4. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. 5. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and

  1. Registration-based estimates of local lung tissue expansion compared to xenon-CT measures of specific ventilation

    PubMed Central

    Reinhardt, Joseph M.; Ding, Kai; Cao, Kunlin; Christensen, Gary E.; Hoffman, Eric A.; Bodas, Shalmali V.

    2008-01-01

    The main function of the respiratory system is gas exchange. Since many disease or injury conditions can cause biomechanical or material property changes that can alter lung function, there is a great interest in measuring regional lung ventilation and regional specific volume change. We describe a registration-based technique for estimating local lung expansion from multiple respiratory-gated CT images of the thorax. The degree of regional lung expansion is measured using the Jacobian (a function of local partial derivatives) of the registration displacement field, which we show is directly related to specific volume change. We compare the ventral-dorsal patterns of lung expansion estimated across five pressure changes to a xenon CT based measure of specific ventilation in five anesthetized sheep studied in the supine orientation. Using 3D image registration to match images acquired at 10 cm H2O and 15 H2O airway pressures gave the best match between the average Jacobian and the xenon CT specific ventilation (linear regression, average r2 = 0.73). PMID:18501665

  2. Registration-based estimates of local lung tissue expansion compared to xenon CT measures of specific ventilation.

    PubMed

    Reinhardt, Joseph M; Ding, Kai; Cao, Kunlin; Christensen, Gary E; Hoffman, Eric A; Bodas, Shalmali V

    2008-12-01

    The main function of the respiratory system is gas exchange. Since many disease or injury conditions can cause biomechanical or material property changes that can alter lung function, there is a great interest in measuring regional lung ventilation and regional specific volume change. We describe a registration-based technique for estimating local lung expansion from multiple respiratory-gated CT images of the thorax. The degree of regional lung expansion is measured using the Jacobian (a function of local partial derivatives) of the registration displacement field, which we show is directly related to specific volume change. We compare the ventral-dorsal patterns of lung expansion estimated across five pressure changes to a xenon CT based measure of specific ventilation in five anesthetized sheep studied in the supine orientation. Using 3D image registration to match images acquired at 10 cm H(2)O and 15 cm H(2)O airway pressures gave the best match between the average Jacobian and the xenon CT specific ventilation (linear regression, average r(2)=0.73).

  3. 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.

  4. 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).

  5. 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.

  6. 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

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

    PubMed

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

    2015-05-07

    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.

  8. 3D registration method based on scattered point cloud from B-model ultrasound image

    NASA Astrophysics Data System (ADS)

    Hu, Lei; Xu, Xiaojun; Wang, Lifeng; Guo, Na; Xie, Feng

    2017-01-01

    The paper proposes a registration method on 3D point cloud of the bone tissue surface extracted by B-mode ultrasound image and the CT model . The B-mode ultrasound is used to get two-dimensional images of the femur tissue . The binocular stereo vision tracker is used to obtain spatial position and orientation of the optical positioning device fixed on the ultrasound probe. The combining of the two kind of data generates 3D point cloud of the bone tissue surface. The pixel coordinates of the bone surface are automatically obtained from ultrasound image using an improved local phase symmetry (phase symmetry, PS) . The mapping of the pixel coordinates on the ultrasound image and 3D space is obtained through a series of calibration methods. In order to detect the effect of registration, six markers are implanted on a complete fresh pig femoral .The actual coordinates of the marks are measured with two methods. The first method is to get the coordinates with measuring tools under a coordinate system. The second is to measure the coordinates of the markers in the CT model registered with 3D point cloud using the ICP registration algorithm under the same coordinate system. Ten registration experiments are carried out in the same way. Error results are obtained by comparing the two sets of mark point coordinates obtained by two different methods. The results is that a minimum error is 1.34mm, the maximum error is 3.22mm,and the average error of 2.52mm; ICP registration algorithm calculates the average error of 0.89mm and a standard deviation of 0.62mm.This evaluation standards of registration accuracy is different from the average error obtained by the ICP registration algorithm. It can be intuitive to show the error caused by the operation of clinical doctors. Reference to the accuracy requirements of different operation in the Department of orthopedics, the method can be apply to the bone reduction and the anterior cruciate ligament surgery.

  9. 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

  10. 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

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

    PubMed

    Zhang, Qi; Alexander, Murray; Ryner, Lawrence

    2016-01-01

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

  12. 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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

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

  15. [Spectra modulated surface plasmon resonance sensor based on side polished multi-mode optical fiber].

    PubMed

    Luo, Yun-Han; Chen, Xiao-Long; Xu, Meng-Yun; Ge, Jia; Zhang, Yi-Long; He, Yong-Hong; Tang, Jie-Yuan; Yu, Jian-Hui; Zhang, Jun; Chen, Zhe; Chen, Xing-Dan

    2014-03-01

    Surface plasmon resonance, which utilizes the resonance of optical evanescent wave with the metal surface plasmon wave, has been developed into a high sensitivity, rapid, label-less measurement method for chemical and biological analysis. In order to improve the spectral sensitivity in refractive index for a side polished fiber surface plasmon resonance sensor, the whole cladding layer and part of core of a multimode fiber was polished off. Additionally, an extra chrome layer with relatively high refractive index was coated on the polished zone before a gold film. The results showed that the sensor can measure the refractive index range from 1.333 to 1. 431 RIU, with the average spectral sensitivity of 4.11 x 10(3) nm RIU(-1), which is better than the reported results. Especially, in the refractive index range of 1. 417 1. 431 RIU, the sensitivity reaches to 1.09 x 10(4) nm RIU(-1). The minimum resolution of approximately 3.6 x 10(-5) RIU was estimated by a combination analysis with the sensor sensitivity and stability. The superiorities possessed by the proposed sensor in high sensitivity, wide detection range, small size and good stability and reproducibility, etc., make it a good candidate for food testing, environmental monitoring, biomedical testing and other related fields.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. A patient alignment solution for lung SBRT setups based on a deformable registration technique

    SciTech Connect

    Lu Bo; Mittauer, Kathryn; Li, Jonathan; Samant, Sanjiv; Dagan, Roi; Okunieff, Paul; Kahler, Darren; Liu, Chihray

    2012-12-15

    Purpose: In this work, the authors propose a novel registration strategy for translation-only correction scenarios of lung stereotactic body radiation therapy setups, which can achieve optimal dose coverage for tumors as well as preserve the consistency of registrations with minimal human interference. Methods: The proposed solution (centroid-to-centroidor CTC solution) uses the average four-dimensional CT (A4DCT) as the reference CT. The cone-beam CT (CBCT) is deformed to acquire a new centroid for the internal target volume (ITV) on the CBCT. The registration is then accomplished by simply aligning the centroids of the ITVs between the A4DCT and the CBCT. Sixty-seven cases using 64 patients (each case is associated with separate isocenters) have been investigated with the CTC method and compared with the conventional gray-value (G) mode and bone (B) mode registration methods. Dosimetric effects among the tree methods were demonstrated by 18 selected cases. The uncertainty of the CTC method has also been studied. Results: The registration results demonstrate the superiority of the CTC method over the other two methods. The differences in the D99 and D95 ITV dose coverage between the CTC method and the original plan is small (within 5%) for all of the selected cases except for one for which the tumor presented significant growth during the period between the CT scan and the treatment. Meanwhile, the dose coverage differences between the original plan and the registration results using either the B or G method are significant, as tumor positions varied dramatically, relative to the rib cage, from their positions on the original CT. The largest differences between the D99 and D95 dose coverage of the ITV using the B or G method versus the original plan are as high as 50%. The D20 differences between any of the methods versus the original plan are all less than 2%. Conclusions: The CTC method can generate optimal dose coverage to tumors with much better consistency

  1. Pulmonary nodule registration in serial CT scans based on rib anatomy and nodule template matching

    PubMed Central

    Shi, Jiazheng; Sahiner, Berkman; Chan, Heang-Ping; Hadjiiski, Lubomir; Zhou, Chuan; Cascade, Philip N.; Bogot, Naama; Kazerooni, Ella A.; Wu, Yi-Ta; Wei, Jun

    2009-01-01

    An automated method is being developed in order to identify corresponding nodules in serial thoracic CT scans for interval change analysis. The method uses the rib centerlines as the reference for initial nodule registration. A spatially adaptive rib segmentation method first locates the regions where the ribs join the spine, which define the starting locations for rib tracking. Each rib is tracked and locally segmented by expectation-maximization. The ribs are automatically labeled, and the centerlines are estimated using skeletonization. For a given nodule in the source scan, the closest three ribs are identified. A three-dimensional (3D) rigid affine transformation guided by simplex optimization aligns the centerlines of each of the three rib pairs in the source and target CT volumes. Automatically defined control points along the centerlines of the three ribs in the source scan and the registered ribs in the target scan are used to guide an initial registration using a second 3D rigid affine transformation. A search volume of interest (VOI) is then located in the target scan. Nodule candidate locations within the search VOI are identified as regions with high Hessian responses. The initial registration is refined by searching for the maximum cross-correlation between the nodule template from the source scan and the candidate locations. The method was evaluated on 48 CT scans from 20 patients. Experienced radiologists identified 101 pairs of corresponding nodules. Three metrics were used for performance evaluation. The first metric was the Euclidean distance between the nodule centers identified by the radiologist and the computer registration, the second metric was a volume overlap measure between the nodule VOIs identified by the radiologist and the computer registration, and the third metric was the hit rate, which measures the fraction of nodules whose centroid computed by the computer registration in the target scan falls within the VOI identified by the

  2. A neural network-based 2D/3D image registration quality evaluator for pediatric patient setup in external beam radiotherapy.

    PubMed

    Wu, Jian; Su, Zhong; Li, Zuofeng

    2016-01-01

    Our purpose was to develop a neural network-based registration quality evaluator (RQE) that can improve the 2D/3D image registration robustness for pediatric patient setup in external beam radiotherapy. Orthogonal daily setup X-ray images of six pediatric patients with brain tumors receiving proton therapy treatments were retrospectively registered with their treatment planning computed tomography (CT) images. A neural network-based pattern classifier was used to determine whether a registration solution was successful based on geometric features of the similarity measure values near the point-of-solution. Supervised training and test datasets were generated by rigidly registering a pair of orthogonal daily setup X-ray images to the treatment planning CT. The best solution for each registration task was selected from 50 optimizing attempts that differed only by the randomly generated initial transformation parameters. The distance from each individual solution to the best solution in the normalized parametrical space was compared to a user-defined error tolerance to determine whether that solution was acceptable. A supervised training was then used to train the RQE. Performance of the RQE was evaluated using test dataset consisting of registration results that were not used in training. The RQE was integrated with our in-house 2D/3D registration system and its performance was evaluated using the same patient dataset. With an optimized sampling step size (i.e., 5 mm) in the feature space, the RQE has the sensitivity and the specificity in the ranges of 0.865-0.964 and 0.797-0.990, respectively, when used to detect registration error with mean voxel displacement (MVD) greater than 1 mm. The trial-to-acceptance ratio of the integrated 2D/3D registration system, for all patients, is equal to 1.48. The final acceptance ratio is 92.4%. The proposed RQE can potentially be used in a 2D/3D rigid image registration system to improve the overall robustness by rejecting

  3. 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.'

  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. 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

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

    PubMed

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

    2015-10-09

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

  7. 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.

  8. 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

  9. Temperature insensitive single-mode-multimode-single-mode fiber optic structures with two multimode fibers in series.

    PubMed

    Tripathi, Saurabh Mani; Kumar, Arun; Kumar, Manoj; Bock, Wojtek J

    2014-06-01

    We propose and demonstrate a temperature insensitive single-mode-multimode-single-mode fiber optic structure consisting of two in-series multimode fibers of appropriate lengths and of opposite temperature sensitivities. A simple approximate expression to estimate the required length ratio of the multimode fiber sections has also been derived whose prediction is found in good agreement with the experiment. The study should be useful in realizing various fiber optic devices based on multimode interference with zero temperature cross sensitivity.

  10. Numerical analysis of a 3D optical sensor based on single mode fiber to multimode interference graphene design

    NASA Astrophysics Data System (ADS)

    Mutter, Kussay N.; Jafri, Zubir M.; Tan, Kok Chooi

    2016-04-01

    In this paper, the simulation and design of a waveguide for water turbidity sensing are presented. The structure of the proposed sensor uses a 2x2 array of multimode interference (MMI) coupler based on micro graphene waveguide for high sensitivity. The beam propagation method (BPM) are used to efficiently design the sensor structure. The structure is consist of an array of two by two elements of sensors. Each element has three sections of single mode for field input tapered to MMI as the main core sensor without cladding which is graphene based material, and then a single mode fiber as an output. In this configuration MMI responses to any change in the environment. We validate and present the results by implementing the design on a set of sucrose solution and showing how these samples lead to a sensitivity change in the sensor based on the MMI structures. Overall results, the 3D design has a feasible and effective sensing by drawing topographical distribution of suspended particles in the water.

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

    PubMe