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Sample records for metric mapping registration

  1. Cortical Hemisphere Registration Via Large Deformation Diffeomorphic Metric Curve Mapping

    PubMed Central

    Qiu, Anqi; Miller, Michael I.

    2010-01-01

    We present large deformation diffeomorphic metric curve mapping (LDDMM-Curve) for registering cortical hemispheres. We showed global cortical hemisphere matching and evaluated the mapping accuracy in five subregions of the cortex in fourteen MRI scans. PMID:18051058

  2. Large Deformation Diffeomorphic Metric Mapping Registration of Reconstructed 3D Histological Section Images and in vivo MR Images

    PubMed Central

    Ceritoglu, Can; Wang, Lei; Selemon, Lynn D.; Csernansky, John G.; Miller, Michael I.; Ratnanather, J. Tilak

    2009-01-01

    Our current understanding of neuroanatomical abnormalities in neuropsychiatric diseases is based largely on magnetic resonance imaging (MRI) and post mortem histological analyses of the brain. Further advances in elucidating altered brain structure in these human conditions might emerge from combining MRI and histological methods. We propose a multistage method for registering 3D volumes reconstructed from histological sections to corresponding in vivo MRI volumes from the same subjects: (1) manual segmentation of white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) compartments in histological sections, (2) alignment of consecutive histological sections using 2D rigid transformation to construct a 3D histological image volume from the aligned sections, (3) registration of reconstructed 3D histological volumes to the corresponding 3D MRI volumes using 3D affine transformation, (4) intensity normalization of images via histogram matching, and (5) registration of the volumes via intensity based large deformation diffeomorphic metric (LDDMM) image matching algorithm. Here we demonstrate the utility of our method in the transfer of cytoarchitectonic information from histological sections to identify regions of interest in MRI scans of nine adult macaque brains for morphometric analyses. LDDMM improved the accuracy of the registration via decreased distances between GM/CSF surfaces after LDDMM (0.39 ± 0.13 mm) compared to distances after affine registration (0.76 ± 0.41 mm). Similarly, WM/GM distances decreased to 0.28 ± 0.16 mm after LDDMM compared to 0.54 ± 0.39 mm after affine registration. The multistage registration method may find broad application for mapping histologically based information, for example, receptor distributions, gene expression, onto MRI volumes. PMID:20577633

  3. Simultaneous multi-scale registration using large deformation diffeomorphic metric mapping.

    PubMed

    Risser, Laurent; Vialard, François-Xavier; Wolz, Robin; Murgasova, Maria; Holm, Darryl D; Rueckert, Daniel

    2011-10-01

    In the framework of large deformation diffeomorphic metric mapping (LDDMM), we present a practical methodology to integrate prior knowledge about the registered shapes in the regularizing metric. Our goal is to perform rich anatomical shape comparisons from volumetric images with the mathematical properties offered by the LDDMM framework. We first present the notion of characteristic scale at which image features are deformed. We then propose a methodology to compare anatomical shape variations in a multi-scale fashion, i.e., at several characteristic scales simultaneously. In this context, we propose a strategy to quantitatively measure the feature differences observed at each characteristic scale separately. After describing our methodology, we illustrate the performance of the method on phantom data. We then compare the ability of our method to segregate a group of subjects having Alzheimer's disease and a group of controls with a classical coarse to fine approach, on standard 3D MR longitudinal brain images. We finally apply the approach to quantify the anatomical development of the human brain from 3D MR longitudinal images of pre-term babies. Results show that our method registers accurately volumetric images containing feature differences at several scales simultaneously with smooth deformations. © 2011 British Crown Copyright

  4. Hyperbolic Harmonic Mapping for Surface Registration.

    PubMed

    Shi, Rui; Zeng, Wei; Su, Zhengyu; Jiang, Jian; Damasio, Hanna; Lu, Zhonglin; Wang, Yalin; Yau, Shing-Tung; Gu, Xianfeng

    2016-05-12

    Automatic computation of surface correspondence via harmonic map is an active research field in computer vision, computer graphics and computational geometry. It may help document and understand physical and biological phenomena and also has broad applications in biometrics, medical imaging and motion capture inducstries. Although numerous studies have been devoted to harmonic map research, limited progress has been made to compute a diffeomorphic harmonic map on general topology surfaces with landmark constraints. This work conquers this problem by changing the Riemannian metric on the target surface to a hyperbolic metric so that the harmonic mapping is guaranteed to be a diffeomorphism under landmark constraints. The computational algorithms are based on Ricci flow and nonlinear heat diffusion methods. The approach is general and robust. We employ our algorithm to study the constrained surface registration problem which applies to both computer vision and medical imaging applications. Experimental results demonstrate that, by changing the Riemannian metric, the registrations are always diffeomorphic and achieve relatively high performance when evaluated with some popular surface registration evaluation standards.

  5. Left-invariant metrics for diffeomorphic image registration with spatially-varying regularisation.

    PubMed

    Schmah, Tanya; Risser, Laurent; Vialard, François-Xavier

    2013-01-01

    We present a new framework for diffeomorphic image registration which supports natural interpretations of spatially-varying metrics. This framework is based on left-invariant diffeomorphic metrics (LIDM) and is closely related to the now standard large deformation diffeomorphic metric mapping (LDDMM). We discuss the relationship between LIDM and LDDMM and introduce a computationally convenient class of spatially-varying metrics appropriate for both frameworks. Finally, we demonstrate the effectiveness of our method on a 2D toy example and on the 40 3D brain images of the LPBA40 dataset.

  6. Accelerating Neuroimage Registration through Parallel Computation of Similarity Metric

    PubMed Central

    Luo, Yun-gang; Liu, Ping; Shi, Lin; Luo, Yishan; Yi, Lei; Li, Ang; Qin, Jing; Heng, Pheng-Ann; Wang, Defeng

    2015-01-01

    Neuroimage registration is crucial for brain morphometric analysis and treatment efficacy evaluation. However, existing advanced registration algorithms such as FLIRT and ANTs are not efficient enough for clinical use. In this paper, a GPU implementation of FLIRT with the correlation ratio (CR) as the similarity metric and a GPU accelerated correlation coefficient (CC) calculation for the symmetric diffeomorphic registration of ANTs have been developed. The comparison with their corresponding original tools shows that our accelerated algorithms can greatly outperform the original algorithm in terms of computational efficiency. This paper demonstrates the great potential of applying these registration tools in clinical applications. PMID:26352412

  7. Implicit Contractive Mappings in Modular Metric and Fuzzy Metric Spaces

    PubMed Central

    Hussain, N.; Salimi, P.

    2014-01-01

    The notion of modular metric spaces being a natural generalization of classical modulars over linear spaces like Lebesgue, Orlicz, Musielak-Orlicz, Lorentz, Orlicz-Lorentz, and Calderon-Lozanovskii spaces was recently introduced. In this paper we investigate the existence of fixed points of generalized α-admissible modular contractive mappings in modular metric spaces. As applications, we derive some new fixed point theorems in partially ordered modular metric spaces, Suzuki type fixed point theorems in modular metric spaces and new fixed point theorems for integral contractions. In last section, we develop an important relation between fuzzy metric and modular metric and deduce certain new fixed point results in triangular fuzzy metric spaces. Moreover, some examples are provided here to illustrate the usability of the obtained results. PMID:25003157

  8. Metrics for comparison of crystallographic maps

    SciTech Connect

    Urzhumtsev, Alexandre; Afonine, Pavel V.; Lunin, Vladimir Y.; Terwilliger, Thomas C.; Adams, Paul D.

    2014-10-01

    Numerical comparison of crystallographic contour maps is used extensively in structure solution and model refinement, analysis and validation. However, traditional metrics such as the map correlation coefficient (map CC, real-space CC or RSCC) sometimes contradict the results of visual assessment of the corresponding maps. This article explains such apparent contradictions and suggests new metrics and tools to compare crystallographic contour maps. The key to the new methods is rank scaling of the Fourier syntheses. The new metrics are complementary to the usual map CC and can be more helpful in map comparison, in particular when only some of their aspects, such as regions of high density, are of interest.

  9. Metrics for comparison of crystallographic maps

    PubMed Central

    Urzhumtsev, Alexandre; Afonine, Pavel V.; Lunin, Vladimir Y.; Terwilliger, Thomas C.; Adams, Paul D.

    2014-01-01

    Numerical comparison of crystallographic contour maps is used extensively in structure solution and model refinement, analysis and validation. However, traditional metrics such as the map correlation coefficient (map CC, real-space CC or RSCC) sometimes contradict the results of visual assessment of the corresponding maps. This article explains such apparent contradictions and suggests new metrics and tools to compare crystallographic contour maps. The key to the new methods is rank scaling of the Fourier syntheses. The new metrics are complementary to the usual map CC and can be more helpful in map comparison, in particular when only some of their aspects, such as regions of high density, are of interest. PMID:25286844

  10. Metrics for comparison of crystallographic maps

    DOE PAGES

    Urzhumtsev, Alexandre; Afonine, Pavel V.; Lunin, Vladimir Y.; ...

    2014-10-01

    Numerical comparison of crystallographic contour maps is used extensively in structure solution and model refinement, analysis and validation. However, traditional metrics such as the map correlation coefficient (map CC, real-space CC or RSCC) sometimes contradict the results of visual assessment of the corresponding maps. This article explains such apparent contradictions and suggests new metrics and tools to compare crystallographic contour maps. The key to the new methods is rank scaling of the Fourier syntheses. The new metrics are complementary to the usual map CC and can be more helpful in map comparison, in particular when only some of their aspects,more » such as regions of high density, are of interest.« less

  11. Image registration using binary boundary maps

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

    Registration technique that matches binary boundary maps extracted from raw data, rather than matching actual data, is considerably faster than other techniques. Boundary maps, which are digital representations of regions where image amplitudes change significantly, typically represent data compression of 60 to 70 percent. Maps allow average products to be computed with addition rather than multiplication, further reducing computation time.

  12. Nonlinear image registration with bidirectional metric and reciprocal regularization

    PubMed Central

    Ying, Shihui; Li, Dan; Xiao, Bin; Peng, Yaxin; Du, Shaoyi; Xu, Meifeng

    2017-01-01

    Nonlinear registration is an important technique to align two different images and widely applied in medical image analysis. In this paper, we develop a novel nonlinear registration framework based on the diffeomorphic demons, where a reciprocal regularizer is introduced to assume that the deformation between two images is an exact diffeomorphism. In detail, first, we adopt a bidirectional metric to improve the symmetry of the energy functional, whose variables are two reciprocal deformations. Secondly, we slack these two deformations into two independent variables and introduce a reciprocal regularizer to assure the deformations being the exact diffeomorphism. Then, we utilize an alternating iterative strategy to decouple the model into two minimizing subproblems, where a new closed form for the approximate velocity of deformation is calculated. Finally, we compare our proposed algorithm on two data sets of real brain MR images with two relative and conventional methods. The results validate that our proposed method improves accuracy and robustness of registration, as well as the gained bidirectional deformations are actually reciprocal. PMID:28231342

  13. Nonlinear image registration with bidirectional metric and reciprocal regularization.

    PubMed

    Ying, Shihui; Li, Dan; Xiao, Bin; Peng, Yaxin; Du, Shaoyi; Xu, Meifeng

    2017-01-01

    Nonlinear registration is an important technique to align two different images and widely applied in medical image analysis. In this paper, we develop a novel nonlinear registration framework based on the diffeomorphic demons, where a reciprocal regularizer is introduced to assume that the deformation between two images is an exact diffeomorphism. In detail, first, we adopt a bidirectional metric to improve the symmetry of the energy functional, whose variables are two reciprocal deformations. Secondly, we slack these two deformations into two independent variables and introduce a reciprocal regularizer to assure the deformations being the exact diffeomorphism. Then, we utilize an alternating iterative strategy to decouple the model into two minimizing subproblems, where a new closed form for the approximate velocity of deformation is calculated. Finally, we compare our proposed algorithm on two data sets of real brain MR images with two relative and conventional methods. The results validate that our proposed method improves accuracy and robustness of registration, as well as the gained bidirectional deformations are actually reciprocal.

  14. Unbiased atlas formation via large deformations metric mapping.

    PubMed

    Lorenzen, Peter; Davis, Brad; Joshi, Sarang

    2005-01-01

    The construction of population atlases is a key issue in medical image analysis, and particularly in brain mapping. Large sets of images are mapped into a common coordinate system to study intra-population variability and inter-population differences, to provide voxel-wise mapping of functional sites, and to facilitate tissue and object segmentation via registration of anatomical labels. We formulate the unbiased atlas construction problem as a Fréchet mean estimation in the space of diffeomorphisms via large deformations metric mapping. A novel method for computing constant speed velocity fields and an analysis of atlas stability and robustness using entropy are presented. We address the question: how many images are required to build a stable brain atlas?

  15. Active edge maps for medical image registration

    NASA Astrophysics Data System (ADS)

    Kerwin, William; Yuan, Chun

    2001-07-01

    Applying edge detection prior to performing image registration yields several advantages over raw intensity- based registration. Advantages include the ability to register multicontrast or multimodality images, immunity to intensity variations, and the potential for computationally efficient algorithms. In this work, a common framework for edge-based image registration is formulated as an adaptation of snakes used in boundary detection. Called active edge maps, the new formulation finds a one-to-one transformation T(x) that maps points in a source image to corresponding locations in a target image using an energy minimization approach. The energy consists of an image component that is small when edge features are well matched in the two images, and an internal term that restricts T(x) to allowable configurations. The active edge map formulation is illustrated here with a specific example developed for affine registration of carotid artery magnetic resonance images. In this example, edges are identified using a magnitude of gradient operator, image energy is determined using a Gaussian weighted distance function, and the internal energy includes separate, adjustable components that control volume preservation and rigidity.

  16. Large deformation diffeomorphic metric mapping of orientation distribution functions.

    PubMed

    Du, Jia; Goh, Alvina; Qiu, Anqi

    2011-01-01

    We propose a novel large deformation diffeomorphic registration algorithm to align high angular resolution diffusion images (HARDI) characterized by Orientation Distribution Functions (ODF). Our proposed algorithm seeks an optimal diffeomorphism of large deformation between two ODF fields in a spatial volume domain and at the same time, locally reorients an ODF in a manner such that it remains consistent with the surrounding anatomical structure. We first extend ODFs traditionally defined in a unit sphere to a generalized ODF defined in R3. This makes it easy for an affine transformation as well as a diffeomorphic group action to be applied on the ODF. We then construct a Riemannian space of the generalized ODFs and incorporate its Riemannian metric for the similarity of ODFs into a variational problem defined under the large deformation diffeomorphic metric mapping (LDDMM) framework. We finally derive the gradient of the cost function in both Riemannian spaces of diffeomorphisms and the generalized ODFs, and present its numerical implementation. Both synthetic and real brain HARDI data are used to illustrate the performance of our registration algorithm.

  17. Diffeomorphic brain mapping based on T1-weighted images: improvement of registration accuracy by multichannel mapping.

    PubMed

    Djamanakova, Aigerim; Faria, Andreia V; Hsu, John; Ceritoglu, Can; Oishi, Kenichi; Miller, Michael I; Hillis, Argye E; Mori, Susumu

    2013-01-01

    To improve image registration accuracy in neurodegenerative populations. This study used primary progressive aphasia, aged control, and young control T1-weighted images. Mapping to a template image was performed using single-channel Large Deformation Diffeomorphic Metric Mapping (LDDMM), a dual-channel method with ventricular anatomy in the second channel, and a dual-channel with appendage method, which utilized a priori knowledge of template ventricular anatomy in the deformable atlas. Our results indicated substantial improvement in the registration accuracy over single-contrast-based brain mapping, mainly in the lateral ventricles and regions surrounding them. Dual-channel mapping significantly (P < 0.001) reduced the number of misclassified lateral ventricle voxels (based on a manually defined reference) over single-channel mapping. The dual-channel (w/appendage) method further reduced (P < 0.001) misclassification over the dual-channel method, indicating that the appendage provides more accurate anatomical correspondence for deformation. Brain anatomical mapping by shape normalization is widely used for quantitative anatomical analysis. However, in many geriatric and neurodegenerative disorders, severe tissue atrophy poses a unique challenge for accurate mapping of voxels, especially around the lateral ventricles. In this study we demonstrate our ability to improve mapping accuracy by incorporating ventricular anatomy in LDDMM and by utilizing a priori knowledge of ventricular anatomy in the deformable atlas. Copyright © 2012 Wiley Periodicals, Inc.

  18. Large Deformation Diffeomorphic Metric Curve Mapping

    PubMed Central

    Glaunès, Joan; Miller, Michael I.; Younes, Laurent

    2010-01-01

    We present a matching criterion for curves and integrate it into the large deformation diffeomorphic metric mapping (LDDMM) scheme for computing an optimal transformation between two curves embedded in Euclidean space ℝd. Curves are first represented as vector-valued measures, which incorporate both location and the first order geometric structure of the curves. Then, a Hilbert space structure is imposed on the measures to build the norm for quantifying the closeness between two curves. We describe a discretized version of this, in which discrete sequences of points along the curve are represented by vector-valued functionals. This gives a convenient and practical way to define a matching functional for curves. We derive and implement the curve matching in the large deformation framework and demonstrate mapping results of curves in ℝ2 and ℝ3. Behaviors of the curve mapping are discussed using 2D curves. The applications to shape classification is shown and experiments with 3D curves extracted from brain cortical surfaces are presented. PMID:20419045

  19. 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.

  20. Local Metric Learning in 2D/3D Deformable Registration With Application in the Abdomen

    PubMed Central

    Chou, Chen-Rui; Mageras, Gig; Pizer, Stephen

    2015-01-01

    In image-guided radiotherapy (IGRT) of disease sites subject to respiratory motion, soft tissue deformations can affect localization accuracy. We describe the application of a method of 2D/3D deformable registration to soft tissue localization in abdomen. The method, called registration efficiency and accuracy through learning a metric on shape (REALMS), is designed to support real-time IGRT. In a previously developed version of REALMS, the method interpolated 3D deformation parameters for any credible deformation in a deformation space using a single globally-trained Riemannian metric for each parameter. We propose a refinement of the method in which the metric is trained over a particular region of the deformation space, such that interpolation accuracy within that region is improved. We report on the application of the proposed algorithm to IGRT in abdominal disease sites, which is more challenging than in lung because of low intensity contrast and nonrespiratory deformation. We introduce a rigid translation vector to compensate for nonrespiratory deformation, and design a special region-of-interest around fiducial markers implanted near the tumor to produce a more reliable registration. Both synthetic data and actual data tests on abdominal datasets show that the localized approach achieves more accurate 2D/3D deformable registration than the global approach. PMID:24771575

  1. Multiview marker-free registration of forest terrestrial laser scanner data with embedded confidence metrics

    DOE PAGES

    Kelbe, David; van Aardt, Jan; Romanczyk, Paul; ...

    2016-10-18

    Terrestrial laser scanning has demonstrated increasing potential for rapid comprehensive measurement of forest structure, especially when multiple scans are spatially registered in order to reduce the limitations of occlusion. Although marker-based registration techniques (based on retro-reflective spherical targets) are commonly used in practice, a blind marker-free approach is preferable, insofar as it supports rapid operational data acquisition. To support these efforts, we extend the pairwise registration approach of our earlier work, and develop a graph-theoretical framework to perform blind marker-free global registration of multiple point cloud data sets. Pairwise pose estimates are weighted based on their estimated error, in ordermore » to overcome pose conflict while exploiting redundant information and improving precision. The proposed approach was tested for eight diverse New England forest sites, with 25 scans collected at each site. Quantitative assessment was provided via a novel embedded confidence metric, with a mean estimated root-mean-square error of 7.2 cm and 89% of scans connected to the reference node. Lastly, this paper assesses the validity of the embedded multiview registration confidence metric and evaluates the performance of the proposed registration algorithm.« less

  2. Multiview marker-free registration of forest terrestrial laser scanner data with embedded confidence metrics

    SciTech Connect

    Kelbe, David; van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin; Cawse-Nicholson, Kerry

    2016-10-18

    Terrestrial laser scanning has demonstrated increasing potential for rapid comprehensive measurement of forest structure, especially when multiple scans are spatially registered in order to reduce the limitations of occlusion. Although marker-based registration techniques (based on retro-reflective spherical targets) are commonly used in practice, a blind marker-free approach is preferable, insofar as it supports rapid operational data acquisition. To support these efforts, we extend the pairwise registration approach of our earlier work, and develop a graph-theoretical framework to perform blind marker-free global registration of multiple point cloud data sets. Pairwise pose estimates are weighted based on their estimated error, in order to overcome pose conflict while exploiting redundant information and improving precision. The proposed approach was tested for eight diverse New England forest sites, with 25 scans collected at each site. Quantitative assessment was provided via a novel embedded confidence metric, with a mean estimated root-mean-square error of 7.2 cm and 89% of scans connected to the reference node. Lastly, this paper assesses the validity of the embedded multiview registration confidence metric and evaluates the performance of the proposed registration algorithm.

  3. Whole brain diffeomorphic metric mapping via integration of sulcal and gyral curves, cortical surfaces, and images.

    PubMed

    Du, Jia; Younes, Laurent; Qiu, Anqi

    2011-05-01

    This paper introduces a novel large deformation diffeomorphic metric mapping algorithm for whole brain registration where sulcal and gyral curves, cortical surfaces, and intensity images are simultaneously carried from one subject to another through a flow of diffeomorphisms. To the best of our knowledge, this is the first time that the diffeomorphic metric from one brain to another is derived in a shape space of intensity images and point sets (such as curves and surfaces) in a unified manner. We describe the Euler-Lagrange equation associated with this algorithm with respect to momentum, a linear transformation of the velocity vector field of the diffeomorphic flow. The numerical implementation for solving this variational problem, which involves large-scale kernel convolution in an irregular grid, is made feasible by introducing a class of computationally friendly kernels. We apply this algorithm to align magnetic resonance brain data. Our whole brain mapping results show that our algorithm outperforms the image-based LDDMM algorithm in terms of the mapping accuracy of gyral/sulcal curves, sulcal regions, and cortical and subcortical segmentation. Moreover, our algorithm provides better whole brain alignment than combined volumetric and surface registration (Postelnicu et al., 2009) and hierarchical attribute matching mechanism for elastic registration (HAMMER) (Shen and Davatzikos, 2002) in terms of cortical and subcortical volume segmentation. Copyright © 2011 Elsevier Inc. All rights reserved.

  4. Whole brain diffeomorphic metric mapping via integration of sulcal and gyral curves, cortical surfaces, and images

    PubMed Central

    Du, Jia; Younes, Laurent; Qiu, Anqi

    2011-01-01

    This paper introduces a novel large deformation diffeomorphic metric mapping algorithm for whole brain registration where sulcal and gyral curves, cortical surfaces, and intensity images are simultaneously carried from one subject to another through a flow of diffeomorphisms. To the best of our knowledge, this is the first time that the diffeomorphic metric from one brain to another is derived in a shape space of intensity images and point sets (such as curves and surfaces) in a unified manner. We describe the Euler–Lagrange equation associated with this algorithm with respect to momentum, a linear transformation of the velocity vector field of the diffeomorphic flow. The numerical implementation for solving this variational problem, which involves large-scale kernel convolution in an irregular grid, is made feasible by introducing a class of computationally friendly kernels. We apply this algorithm to align magnetic resonance brain data. Our whole brain mapping results show that our algorithm outperforms the image-based LDDMM algorithm in terms of the mapping accuracy of gyral/sulcal curves, sulcal regions, and cortical and subcortical segmentation. Moreover, our algorithm provides better whole brain alignment than combined volumetric and surface registration (Postelnicu et al., 2009) and hierarchical attribute matching mechanism for elastic registration (HAMMER) (Shen and Davatzikos, 2002) in terms of cortical and subcortical volume segmentation. PMID:21281722

  5. Spatially-varying metric learning for diffeomorphic image registration: a variational framework.

    PubMed

    Vialard, François-Xavier; Risser, Laurent

    2014-01-01

    This paper introduces a variational strategy to learn spatially-varying metrics on large groups of images, in the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework. Spatially-varying metrics we learn not only favor local deformations but also correlated deformations in different image regions and in different directions. In addition, metric parameters can be efficiently estimated using a gradient descent method. We first describe the general strategy and then show how to use it on 3D medical images with reasonable computational ressources. Our method is assessed on the 3D brain images of the LPBA40 dataset. Results are compared with ANTS-SyN and LDDMM with spatially-homogeneous metrics.

  6. Resisting anchoring effects: The roles of metric and mapping knowledge.

    PubMed

    Smith, Andrew R; Windschitl, Paul D

    2015-10-01

    The biasing influence of anchors on numerical estimates is well established, but the relationship between knowledge level and the susceptibility to anchoring effects is less clear. In two studies, we addressed the potential mitigating effects of having knowledge in a domain on vulnerability to anchoring effects in that domain. Of critical interest was a distinction between two forms of knowledge-metric and mapping knowledge. In Study 1, participants who had studied question-relevant information-that is, high-knowledge participants-were less influenced by anchors than were participants who had studied irrelevant information. The results from knowledge measures suggested that the reduction in anchoring was tied to increases in metric rather than mapping knowledge. In Study 2, participants studied information specifically designed to influence different types of knowledge. As we predicted, increases in metric knowledge-and not mapping knowledge-led to reduced anchoring effects. Implications for debiasing anchoring effects are discussed.

  7. Registration of Heat Capacity Mapping Mission day and night images

    NASA Technical Reports Server (NTRS)

    Watson, K.; Hummer-Miller, S.; Sawatzky, D. L. (Principal Investigator)

    1982-01-01

    Neither iterative registration, using drainage intersection maps for control, nor cross correlation techniques were satisfactory in registering day and night HCMM imagery. A procedure was developed which registers the image pairs by selecting control points and mapping the night thermal image to the daytime thermal and reflectance images using an affine transformation on a 1300 by 1100 pixel image. The resulting image registration is accurate to better than two pixels (RMS) and does not exhibit the significant misregistration that was noted in the temperature-difference and thermal-inertia products supplied by NASA. The affine transformation was determined using simple matrix arithmetic, a step that can be performed rapidly on a minicomputer.

  8. Overlay improvement by exposure map based mask registration optimization

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  9. Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

    DOE PAGES

    Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin; ...

    2016-04-04

    Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

  10. Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

    SciTech Connect

    Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin; Kelbe, David; Cawse-Nicholson, Kerry

    2016-04-04

    Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud data and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.

  11. Riemannian Metric Optimization for Connectivity-driven Surface Mapping.

    PubMed

    Gahm, Jin Kyu; Shi, Yonggang

    2016-10-01

    With the advance of human connectome research, there are great interests in computing diffeomorphic maps of brain surfaces with rich connectivity features. In this paper, we propose a novel framework for connectivity-driven surface mapping based on Riemannian metric optimization on surfaces (RMOS) in the Laplace-Beltrami (LB) embedding space. The mathematical foundation of our method is that we can use the pullback metric to define an isometry between surfaces for an arbitrary diffeomorphism, which in turn results in identical LB embeddings from the two surfaces. For connectivity-driven surface mapping, our goal is to compute a diffeomorphism that can match a set of connectivity features defined over anatomical surfaces. The proposed RMOS approach achieves this goal by iteratively optimizing the Riemannian metric on surfaces to match the connectivity features in the LB embedding space. At the core of our framework is an optimization approach that converts the cost function of connectivity features into a distance measure in the LB embedding space, and optimizes it using gradients of the LB eigen-system with respect to the Riemannian metric. We demonstrate our method on the mapping of thalamic surfaces according to connectivity to ten cortical regions, which we compute with the multi-shell diffusion imaging data from the Human Connectome Project (HCP). Comparisons with a state-of-the-art method show that the RMOS method can more effectively match anatomical features and detect thalamic atrophy due to normal aging.

  12. Contractive Maps in Locally Transitive Relational Metric Spaces

    PubMed Central

    2014-01-01

    Some fixed point results are given for a class of Meir-Keeler contractive maps acting on metric spaces endowed with locally transitive relations. Technical connections with the related statements due to Berzig et al. (2014) are also being discussed. PMID:24737960

  13. California Sea Cliff Metrics: Mapping and Validation

    NASA Astrophysics Data System (ADS)

    Palaseanu, M.; Thatcher, C.; Danielson, J.; Logan, J. B.; Foxgrover, A. C.; Brock, J. C.; Barnard, P.

    2015-12-01

    Seacliff erosion is a serious hazard with implications for coastal management, and is often estimated using successive hand digitized cliff tops or bases (toe) to assess cliff retreat. We developed an automated procedure to extract the location of the cliff top from high resolution lidar-derived digital elevation models using transects generated at approximately 1-m intervals. The automated method to define cliff tops is repeatable, takes advantage of detailed topographic information within high-resolution elevation data, and is more efficient than hand-digitizing. To validate the results obtained from a 2010 aerial lidar survey, we conducted a terrestrial lidar (tlidar) survey at Bonny Doon beach near Santa Cruz California in 2014 and mapped the location of the cliff tops using real-time kinematic GPS. Bonny Doon beach has highly irregular cliffs, with several small sea caves and erosion features that were not distinguishable in the aerial lidar digital terrain model (DTM). We extracted the location of the cliff top from the tlidar point cloud along the same transects used previously to automatically derive cliff tops from the aerial lidar derived DTM. The minimum horizontal distance between the tlidar derived cliff top points and GPS points was calculated. The error measurements between GPS and terrestrial lidar are 0.19 m mean absolute error (MAE) and 0.51 m root mean square error (RMSE) respectively. The MAE and the RMSE between the GPS and aerial lidar cliff top points were 0.96 and 1.82 m respectively. The larger errors between aerial lidar cliff top points and GPS are likely due to the failure to remove all vegetation from the aerial lidar data, the positional accuracy of the aerial lidar, and a 4-year gap between surveys. The error assessment indicates that the automated procedure mapped the cliff top location successfully using both the aerial and terrestrial lidar, although the cliff top delineation based on the tlidar data was more accurate.

  14. Large Deformation Multiresolution Diffeomorphic Metric Mapping for Multiresolution Cortical Surfaces: A Coarse-to-Fine Approach.

    PubMed

    Tan, Mingzhen; Qiu, Anqi

    2016-09-01

    Brain surface registration is an important tool for characterizing cortical anatomical variations and understanding their roles in normal cortical development and psychiatric diseases. However, surface registration remains challenging due to complicated cortical anatomy and its large differences across individuals. In this paper, we propose a fast coarse-to-fine algorithm for surface registration by adapting the large diffeomorphic deformation metric mapping (LDDMM) framework for surface mapping and show improvements in speed and accuracy via a multiresolution analysis of surface meshes and the construction of multiresolution diffeomorphic transformations. The proposed method constructs a family of multiresolution meshes that are used as natural sparse priors of the cortical morphology. At varying resolutions, these meshes act as anchor points where the parameterization of multiresolution deformation vector fields can be supported, allowing the construction of a bundle of multiresolution deformation fields, each originating from a different resolution. Using a coarse-to-fine approach, we show a potential reduction in computation cost along with improvements in sulcal alignment when compared with LDDMM surface mapping.

  15. SU-E-J-159: Intra-Patient Deformable Image Registration Uncertainties Quantified Using the Distance Discordance Metric

    SciTech Connect

    Saleh, Z; Thor, M; Apte, A; Deasy, J; Sharp, G; Muren, L

    2014-06-01

    Purpose: The quantitative evaluation of deformable image registration (DIR) is currently challenging due to lack of a ground truth. In this study we test a new method proposed for quantifying multiple-image based DIRrelated uncertainties, for DIR of pelvic images. Methods: 19 patients were analyzed, each with 6 CT scans, who previously had radiotherapy for prostate cancer. Manually delineated structures for rectum and bladder, which served as ground truth structures, were delineated on the planning CT and each subsequent scan. For each patient, voxel-by-voxel DIR-related uncertainties were evaluated, following B-spline based DIR, by applying a previously developed metric, the distance discordance metric (DDM; Saleh et al., PMB (2014) 59:733). The DDM map was superimposed on the first acquired CT scan and DDM statistics were assessed, also relative to two metrics estimating the agreement between the propagated and the manually delineated structures. Results: The highest DDM values which correspond to greatest spatial uncertainties were observed near the body surface and in the bowel due to the presence of gas. The mean rectal and bladder DDM values ranged from 1.1–11.1 mm and 1.5–12.7 mm, respectively. There was a strong correlation in the DDMs between the rectum and bladder (Pearson R = 0.68 for the max DDM). For both structures, DDM was correlated with the ratio between the DIR-propagated and manually delineated volumes (R = 0.74 for the max rectal DDM). The maximum rectal DDM was negatively correlated with the Dice Similarity Coefficient between the propagated and the manually delineated volumes (R= −0.52). Conclusion: The multipleimage based DDM map quantified considerable DIR variability across different structures and among patients. Besides using the DDM for quantifying DIR-related uncertainties it could potentially be used to adjust for uncertainties in DIR-based accumulated dose distributions.

  16. Deformable structure registration of bladder through surface mapping

    SciTech Connect

    Li Xiong; Viswanathan, Akila; Stewart, Alexandra J.; Haker, Steven; Tempany, Clare M.; Chin, Lee M.; Cormack, Robert A.

    2006-06-15

    Cumulative dose distributions in fractionated radiation therapy depict the dose to normal tissues and therefore may permit an estimation of the risk of normal tissue complications. However, calculation of these distributions is highly challenging because of interfractional changes in the geometry of patient anatomy. This work presents an algorithm for deformable structure registration of the bladder and the verification of the accuracy of the algorithm using phantom and patient data. In this algorithm, the registration process involves conformal mapping of genus zero surfaces using finite element analysis, and guided by three control landmarks. The registration produces a correspondence between fractions of the triangular meshes used to describe the bladder surface. For validation of the algorithm, two types of balloons were inflated gradually to three times their original size, and several computerized tomography (CT) scans were taken during the process. The registration algorithm yielded a local accuracy of 4 mm along the balloon surface. The algorithm was then applied to CT data of patients receiving fractionated high-dose-rate brachytherapy to the vaginal cuff, with the vaginal cylinder in situ. The patients' bladder filling status was intentionally different for each fraction. The three required control landmark points were identified for the bladder based on anatomy. Out of an Institutional Review Board (IRB) approved study of 20 patients, 3 had radiographically identifiable points near the bladder surface that were used for verification of the accuracy of the registration. The verification point as seen in each fraction was compared with its predicted location based on affine as well as deformable registration. Despite the variation in bladder shape and volume, the deformable registration was accurate to 5 mm, consistently outperforming the affine registration. We conclude that the structure registration algorithm presented works with reasonable accuracy and

  17. Deformable structure registration of bladder through surface mapping.

    PubMed

    Xiong, Li; Viswanathan, Akila; Stewart, Alexandra J; Haker, Steven; Tempany, Clare M; Chin, Lee M; Cormack, Robert A

    2006-06-01

    Cumulative dose distributions in fractionated radiation therapy depict the dose to normal tissues and therefore may permit an estimation of the risk of normal tissue complications. However, calculation of these distributions is highly challenging because of interfractional changes in the geometry of patient anatomy. This work presents an algorithm for deformable structure registration of the bladder and the verification of the accuracy of the algorithm using phantom and patient data. In this algorithm, the registration process involves conformal mapping of genus zero surfaces using finite element analysis, and guided by three control landmarks. The registration produces a correspondence between fractions of the triangular meshes used to describe the bladder surface. For validation of the algorithm, two types of balloons were inflated gradually to three times their original size, and several computerized tomography (CT) scans were taken during the process. The registration algorithm yielded a local accuracy of 4 mm along the balloon surface. The algorithm was then applied to CT data of patients receiving fractionated high-dose-rate brachytherapy to the vaginal cuff, with the vaginal cylinder in situ. The patients' bladder filling status was intentionally different for each fraction. The three required control landmark points were identified for the bladder based on anatomy. Out of an Institutional Review Board (IRB) approved study of 20 patients, 3 had radiographically identifiable points near the bladder surface that were used for verification of the accuracy of the registration. The verification point as seen in each fraction was compared with its predicted location based on affine as well as deformable registration. Despite the variation in bladder shape and volume, the deformable registration was accurate to 5 mm, consistently outperforming the affine registration. We conclude that the structure registration algorithm presented works with reasonable accuracy and

  18. WE-AB-BRA-01: 3D-2D Image Registration for Target Localization in Spine Surgery: Comparison of Similarity Metrics Against Robustness to Content Mismatch

    SciTech Connect

    De Silva, T; Ketcha, M; Siewerdsen, J H; Uneri, A; Reaungamornrat, S; Vogt, S; Kleinszig, G; Lo, S F; Wolinsky, J P; Gokaslan, Z L; Aygun, N

    2015-06-15

    Purpose: In image-guided spine surgery, mapping 3D preoperative images to 2D intraoperative images via 3D-2D registration can provide valuable assistance in target localization. However, the presence of surgical instrumentation, hardware implants, and soft-tissue resection/displacement causes mismatches in image content, confounding existing registration methods. Manual/semi-automatic methods to mask such extraneous content is time consuming, user-dependent, error prone, and disruptive to clinical workflow. We developed and evaluated 2 novel similarity metrics within a robust registration framework to overcome such challenges in target localization. Methods: An IRB-approved retrospective study in 19 spine surgery patients included 19 preoperative 3D CT images and 50 intraoperative mobile radiographs in cervical, thoracic, and lumbar spine regions. A neuroradiologist provided truth definition of vertebral positions in CT and radiography. 3D-2D registration was performed using the CMA-ES optimizer with 4 gradient-based image similarity metrics: (1) gradient information (GI); (2) gradient correlation (GC); (3) a novel variant referred to as gradient orientation (GO); and (4) a second variant referred to as truncated gradient correlation (TGC). Registration accuracy was evaluated in terms of the projection distance error (PDE) of the vertebral levels. Results: Conventional similarity metrics were susceptible to gross registration error and failure modes associated with the presence of surgical instrumentation: for GI, the median PDE and interquartile range was 33.0±43.6 mm; similarly for GC, PDE = 23.0±92.6 mm respectively. The robust metrics GO and TGC, on the other hand, demonstrated major improvement in PDE (7.6 ±9.4 mm and 8.1± 18.1 mm, respectively) and elimination of gross failure modes. Conclusion: The proposed GO and TGC similarity measures improve registration accuracy and robustness to gross failure in the presence of strong image content mismatch. Such

  19. A hyperspectral vessel image registration method for blood oxygenation mapping.

    PubMed

    Wang, Qian; Li, Qingli; Zhou, Mei; Sun, Zhen; Liu, Hongying; Wang, Yiting

    2017-01-01

    Blood oxygenation mapping by the means of optical oximetry is of significant importance in clinical trials. This paper uses hyperspectral imaging technology to obtain in vivo images for blood oxygenation detection. The experiment involves dorsal skin fold window chamber preparation which was built on adult (8-10 weeks of age) female BALB/c nu/nu mice and in vivo image acquisition which was performed by hyperspectral imaging system. To get the accurate spatial and spectral information of targets, an automatic registration scheme is proposed. An adaptive feature detection method which combines the local threshold method and the level-set filter is presented to extract target vessels. A reliable feature matching algorithm with the correlative information inherent in hyperspectral images is used to kick out the outliers. Then, the registration images are used for blood oxygenation mapping. Registration evaluation results show that most of the false matches are removed and the smooth and concentrated spectra are obtained. This intensity invariant feature detection with outliers-removing feature matching proves to be effective in hyperspectral vessel image registration. Therefore, in vivo hyperspectral imaging system by the assistance of the proposed registration scheme provides a technique for blood oxygenation research.

  20. The role of image registration in brain mapping

    PubMed Central

    Toga, A.W.; Thompson, P.M.

    2008-01-01

    Image registration is a key step in a great variety of biomedical imaging applications. It provides the ability to geometrically align one dataset with another, and is a prerequisite for all imaging applications that compare datasets across subjects, imaging modalities, or across time. Registration algorithms also enable the pooling and comparison of experimental findings across laboratories, the construction of population-based brain atlases, and the creation of systems to detect group patterns in structural and functional imaging data. We review the major types of registration approaches used in brain imaging today. We focus on their conceptual basis, the underlying mathematics, and their strengths and weaknesses in different contexts. We describe the major goals of registration, including data fusion, quantification of change, automated image segmentation and labeling, shape measurement, and pathology detection. We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical analysis. The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the anatomy or physiology of the brain. PMID:19890483

  1. The role of image registration in brain mapping.

    PubMed

    Toga, A W; Thompson, P M

    2001-01-01

    Image registration is a key step in a great variety of biomedical imaging applications. It provides the ability to geometrically align one dataset with another, and is a prerequisite for all imaging applications that compare datasets across subjects, imaging modalities, or across time. Registration algorithms also enable the pooling and comparison of experimental findings across laboratories, the construction of population-based brain atlases, and the creation of systems to detect group patterns in structural and functional imaging data. We review the major types of registration approaches used in brain imaging today. We focus on their conceptual basis, the underlying mathematics, and their strengths and weaknesses in different contexts. We describe the major goals of registration, including data fusion, quantification of change, automated image segmentation and labeling, shape measurement, and pathology detection. We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical analysis. The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the anatomy or physiology of the brain.

  2. Surface-Constrained Volumetric Brain Registration Using Harmonic Mappings

    PubMed Central

    Joshi, Anand A.; Shattuck, David W.; Thompson, Paul M.; Leahy, Richard M.

    2015-01-01

    In order to compare anatomical and functional brain imaging data across subjects, the images must first be registered to a common coordinate system in which anatomical features are aligned. Intensity-based volume registration methods can align subcortical structures well, but the variability in sulcal folding patterns typically results in misalignment of the cortical surface. Conversely, surface-based registration using sulcal features can produce excellent cortical alignment but the mapping between brains is restricted to the cortical surface. Here we describe a method for volumetric registration that also produces an accurate one-to-one point correspondence between cortical surfaces. This is achieved by first parameterizing and aligning the cortical surfaces using sulcal landmarks. We then use a constrained harmonic mapping to extend this surface correspondence to the entire cortical volume. Finally, this mapping is refined using an intensity-based warp. We demonstrate the utility of the method by applying it to T1-weighted magnetic resonance images (MRI). We evaluate the performance of our proposed method relative to existing methods that use only intensity information; for this comparison we compute the inter-subject alignment of expert-labeled sub-cortical structures after registration. PMID:18092736

  3. Dose mapping sensitivity to deformable registration uncertainties in fractionated radiotherapy - applied to prostate proton treatments.

    PubMed

    Tilly, David; Tilly, Nina; Ahnesjö, Anders

    2013-06-14

    Calculation of accumulated dose in fractionated radiotherapy based on spatial mapping of the dose points generally requires deformable image registration (DIR). The accuracy of the accumulated dose thus depends heavily on the DIR quality. This motivates investigations of how the registration uncertainty influences dose planning objectives and treatment outcome predictions.A framework was developed where the dose mapping can be associated with a variable known uncertainty to simulate the DIR uncertainties in a clinical workflow. The framework enabled us to study the dependence of dose planning metrics, and the predicted treatment outcome, on the DIR uncertainty. The additional planning margin needed to compensate for the dose mapping uncertainties can also be determined. We applied the simulation framework to a hypofractionated proton treatment of the prostate using two different scanning beam spot sizes to also study the dose mapping sensitivity to penumbra widths. The planning parameter most sensitive to the DIR uncertainty was found to be the target D95. We found that the registration mean absolute error needs to be ≤0.20 cm to obtain an uncertainty better than 3% of the calculated D95 for intermediate sized penumbras. Use of larger margins in constructing PTV from CTV relaxed the registration uncertainty requirements to the cost of increased dose burdens to the surrounding organs at risk. The DIR uncertainty requirements should be considered in an adaptive radiotherapy workflow since this uncertainty can have significant impact on the accumulated dose. The simulation framework enabled quantification of the accuracy requirement for DIR algorithms to provide satisfactory clinical accuracy in the accumulated dose.

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

    PubMed

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

    2014-12-01

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

  5. Orbit Design Based on the Global Maps of Telecom Metrics

    NASA Technical Reports Server (NTRS)

    Lee, Charles H.; Cheung, Kar-Ming; Edwards, Chad; Noreen, Gary K.; Vaisnys, Arvydas

    2004-01-01

    In this paper we describe an orbit design aide tool, called Telecom Orbit Analysis and Simulation Tool(TOAST). Although it can be used for studying and selecting orbits for any planet, we solely concentrate on its use for Mars. By specifying the six orbital elements for an orbit, a time frame of interest, a horizon mask angle, and some telecom parameters such as the transmitting power, frequency, antenna gains, antenna losses, link margin, received threshold powers for the rates, etc. this tool enables the user to view the animation of the orbit in two and three-dimensional different telecom metrics at any point on the Mars, namely the global planetary map.

  6. Mapping weak lensing distortions in the Kerr metric

    NASA Astrophysics Data System (ADS)

    Renzini, Arianna I.; Contaldi, Carlo R.; Heavens, Alan

    2017-06-01

    Einstein's theory of General Relativity implies that energy, i.e., matter, curves space-time and thus deforms lightlike geodesics, giving rise to gravitational lensing. This phenomenon is well understood in the case of the Schwarzschild metric and has been accurately described in the past; however, lensing in the Kerr space-time has received less attention in the literature despite potential practical observational applications. In particular, lensing in such space is not expressible as the gradient of a scalar potential and as such is a source of curl-like signatures and an asymmetric shear pattern. In this paper, we develop a differentiable lensing map in the Kerr metric, reworking and extending previous approaches. By using standard tools of weak gravitational lensing, we isolate and quantify the distortion that is uniquely induced by the presence of angular momentum in the metric. We apply this framework to the distortion induced by a Kerr-like foreground object on a distribution of background of sources. We verify that the new unique lensing signature is orders of magnitude below current observational bounds for a range of lens configurations.

  7. A metric linkage disequilibrium map of a human chromosome.

    PubMed

    Tapper, W J; Maniatis, N; Morton, N E; Collins, A

    2003-11-01

    We used LDMAP (Maniatis et al. 2002) to analyse SNP data spanning chromosome 22 (Dawson et al. 2002), to obtain a whole-chromosome metric LD map. The LD map, with map distances analogous to the centiMorgan scale of linkage maps, identifies regions of high LD as plateaus ('blocks') and characterises steps which define the relationship between these regions. From this map we estimate that block regions comprise between 32% and 55% of the euchromatic portion of chromosome 22 and that increasing marker density within steps may increase block coverage. Steps are regions of low LD which correspond to areas of variable recombination intensity. The intensity of recombination is related to the height of the step and thus intense recombination hot-spots can be distinguished from more randomly distributed historical events. The LD maps are more closely related to the high-resolution linkage map (Kong et al. 2002) than average measures of rho with recombination accounting for between 34% and 52% of the variance in patterns of LD (r=0.58 - 0.71, p=0.0001). Step regions are closely correlated with a range of sequence motifs including GT/CA repeats. The LD map identifies holes in which greater marker density is required and defines the optimal SNP spacing for positional cloning, which suggests that some multiple of around 50,000 SNPs will be required to efficiently screen Caucasian genomes. Further analyses which investigate selection of informative SNPs and the effect of SNP allele frequency and marker density will refine this estimate.

  8. Fixed Point Theorems for Generalized α-β-Weakly Contraction Mappings in Metric Spaces and Applications

    PubMed Central

    Latif, Abdul

    2014-01-01

    We extend the notion of generalized weakly contraction mappings due to Choudhury et al. (2011) to generalized α-β-weakly contraction mappings. We show with examples that our new class of mappings is a real generalization of several known classes of mappings. We also establish fixed point results for such mappings in metric spaces. Applying our new results, we obtain fixed point results on ordinary metric spaces, metric spaces endowed with an arbitrary binary relation, and metric spaces endowed with graph. PMID:24895662

  9. Mouse whole-body organ mapping by non-rigid registration approach

    NASA Astrophysics Data System (ADS)

    Xiao, Di; Zahra, David; Bourgeat, Pierrick; Berghofer, Paula; Acosta Tamayo, Oscar; Green, Heather; Gregoire, Marie Claude; Salvado, Olivier

    2011-03-01

    Automatic small animal whole-body organ registration is challenging because of subject's joint structure, posture and position difference and loss of reference features. In this paper, an improved 3D shape context based non-rigid registration method is applied for mouse whole-body skeleton registration and lung registration. A geodesic path based non-rigid registration method is proposed for mouse torso skin registration. Based on the above registration methods, a novel non-rigid registration framework is proposed for mouse whole-body organ mapping from an atlas to new scanned CT data. A preliminary experiment was performed to test the method on lung and skin registration. A whole-body organ mapping was performed on three target data and the selected organs were compared with the manual outlining results. The robust of the method has been demonstrated.

  10. A framework for multi-platform mobile mapping data registration

    NASA Astrophysics Data System (ADS)

    Hassan, Taher Fathy

    Currently, there is an enormous number of Geomatics sensory data available for use in mapping applications. These data are collected from different platforms, using different sensors, and encapsulating different amount of information. The topic of multi-sensor data fusion has received, over the years, a lot of attention by the scientific community for many applications. Multi-sensor data fusion techniques combine data from multiple sensors and related information from associated databases, to achieve improved accuracies and more specific inferences than could be achieved by the use of a single sensor alone. Mobile mapping systems are efficient tools for collecting multi-sensor data that can be used to build and update geographic information systems base maps. The concept of mobile mapping became the mapping standard. Despite the first mobile mapping system was installed on a van, the application has no longer limited to vans. It is now installed on various types of platforms, running in land, sea, and air. Many researchers have proposed different fusion schemes for integrating different sensory data. This fusion process can be broadly classified into pictorial to pictorial, pictorial to non-pictorial, and non pictorial to non-pictorial. Yet, many researchers have investigated different fusion schemes, however there is less amount of attention towards the fusion of airborne and land-based mobile mapping systems' imagery/navigation data. This research introduces a novel data fusion scheme between mobile mapping data, collected from different platforms. The fusion includes both pictorial measurements, in addition to navigation data available from system's navigation component. The fusion is done using generic Bundle Adjustment (BA) engine, which is a generalization of the standard bundle adjustment frameworks. The proposed framework has been adapted to fit the special requirements imposed by the proposed fusion scheme like higher order registration primitives, multi

  11. Gauss-Newton inspired preconditioned optimization in large deformation diffeomorphic metric mapping.

    PubMed

    Hernandez, Monica

    2014-10-21

    In this work, we propose a novel preconditioned optimization method in the paradigm of Large Deformation Diffeomorphic Metric Mapping (LDDMM). The preconditioned update scheme is formulated for the non-stationary and the stationary parameterizations of diffeomorphisms, yielding three different LDDMM methods. The preconditioning matrices are inspired in the Hessian approximation used in Gauss-Newton method. The derivatives are computed using Frechet differentials. Thus, optimization is performed in a Sobolev space, in contrast to optimization in L(2) commonly used in non-rigid registration literature. The proposed LDDMM methods have been evaluated and compared with their respective implementations of gradient descent optimization. Evaluation has been performed using real and simulated images from the Non-rigid Image Registration Evaluation Project (NIREP). The experiments conducted in this work reported that our preconditioned LDDMM methods achieved a performance similar or superior to well-established-in-literature gradient descent non-stationary LDDMM in the great majority of cases. Moreover, preconditioned optimization showed a substantial reduction in the execution time with an affordable increase of the memory usage per iteration. Additional experiments reported that optimization using Frechet differentials should be preferable to optimization using L(2) differentials.

  12. Gauss-Newton inspired preconditioned optimization in large deformation diffeomorphic metric mapping

    NASA Astrophysics Data System (ADS)

    Hernandez, Monica

    2014-10-01

    In this work, we propose a novel preconditioned optimization method in the paradigm of Large Deformation Diffeomorphic Metric Mapping (LDDMM). The preconditioned update scheme is formulated for the non-stationary and the stationary parameterizations of diffeomorphisms, yielding three different LDDMM methods. The preconditioning matrices are inspired in the Hessian approximation used in Gauss-Newton method. The derivatives are computed using Frechet differentials. Thus, optimization is performed in a Sobolev space, in contrast to optimization in L2 commonly used in non-rigid registration literature. The proposed LDDMM methods have been evaluated and compared with their respective implementations of gradient descent optimization. Evaluation has been performed using real and simulated images from the Non-rigid Image Registration Evaluation Project (NIREP). The experiments conducted in this work reported that our preconditioned LDDMM methods achieved a performance similar or superior to well-established-in-literature gradient descent non-stationary LDDMM in the great majority of cases. Moreover, preconditioned optimization showed a substantial reduction in the execution time with an affordable increase of the memory usage per iteration. Additional experiments reported that optimization using Frechet differentials should be preferable to optimization using L2 differentials.

  13. A stochastic approach to estimate the uncertainty of dose mapping caused by uncertainties in b-spline registration

    SciTech Connect

    Hub, Martina; Thieke, Christian; Kessler, Marc L.; Karger, Christian P.

    2012-04-15

    Purpose: In fractionated radiation therapy, image guidance with daily tomographic imaging becomes more and more clinical routine. In principle, this allows for daily computation of the delivered dose and for accumulation of these daily dose distributions to determine the actually delivered total dose to the patient. However, uncertainties in the mapping of the images can translate into errors of the accumulated total dose, depending on the dose gradient. In this work, an approach to estimate the uncertainty of mapping between medical images is proposed that identifies areas bearing a significant risk of inaccurate dose accumulation. Methods: This method accounts for the geometric uncertainty of image registration and the heterogeneity of the dose distribution, which is to be mapped. Its performance is demonstrated in context of dose mapping based on b-spline registration. It is based on evaluation of the sensitivity of dose mapping to variations of the b-spline coefficients combined with evaluation of the sensitivity of the registration metric with respect to the variations of the coefficients. It was evaluated based on patient data that was deformed based on a breathing model, where the ground truth of the deformation, and hence the actual true dose mapping error, is known. Results: The proposed approach has the potential to distinguish areas of the image where dose mapping is likely to be accurate from other areas of the same image, where a larger uncertainty must be expected. Conclusions: An approach to identify areas where dose mapping is likely to be inaccurate was developed and implemented. This method was tested for dose mapping, but it may be applied in context of other mapping tasks as well.

  14. Rice Crop Mapping Using SENTINEL-1A Phenological Metrics

    NASA Astrophysics Data System (ADS)

    Chen, C. F.; Son, N. T.; Chen, C. R.; Chang, L. Y.; Chiang, S. H.

    2016-06-01

    Rice is the most important food crop in Vietnam, providing food more than 90 million people and is considered as an essential source of income for majority of rural populations. Monitoring rice-growing areas is thus important to developing successful strategies for food security in the country. This paper aims to develop an approach for crop acreage estimation from multi-temporal Sentinel-1A data. We processed the data for two main cropping seasons (e.g., winter-spring, summer-autumn) in the Mekong River Delta (MRD), Vietnam through three main steps: (1) data pre-processing, (3) rice classification based on crop phenological metrics, and (4) accuracy assessment of the mapping results. The classification results compared with the ground reference data indicated the overall accuracy of 86.2% and Kappa coefficient of 0.72. These results were reaffirmed by close correlation between the government's rice area statistics for such crops (R2 > 0.95). The values of relative error in area obtained for the winter-spring and summer-autumn were -3.6% and 6.7%, respectively. This study demonstrates the potential application of multi-temporal Sentinel-1A data for rice crop mapping using information of crop phenology in the study region.

  15. Automatic Registration of Wide Area Motion Imagery to Vector Road Maps by Exploiting Vehicle Detections.

    PubMed

    Elliethy, Ahmed; Sharma, Gaurav

    2016-11-01

    To enrich large-scale visual analytics applications enabled by aerial wide area motion imagery (WAMI), we propose a novel methodology for accurately registering a geo-referenced vector roadmap to WAMI by using the locations of detected vehicles and determining a parametric transform that aligns these locations with the network of roads in the roadmap. Specifically, the problem is formulated in a probabilistic framework, explicitly allowing for spurious detections that do not correspond to on-road vehicles. The registration is estimated via the expectation-maximization (EM) algorithm as the planar homography that minimizes the sum of weighted squared distances between the homography-mapped detection locations and the corresponding closest point on the road network, where the weights are estimated posterior probabilities of detections being on-road vehicles. The weighted distance minimization is efficiently performed using the distance transform with the Levenberg-Marquardt nonlinear least-squares minimization procedure, and the fraction of spurious detections is estimated within the EM framework. The proposed method effectively sidesteps the challenges of feature correspondence estimation, applies directly to different imaging modalities, is robust to spurious detections, and is also more appropriate than feature matching for a planar homography. Results over three WAMI data sets captured by both visual and infrared sensors indicate the effectiveness of the proposed methodology: both visual comparison and numerical metrics for the registration accuracy are significantly better for the proposed method as compared with the existing alternatives.

  16. WE-E-213CD-11: A New Automatically Generated Metric for Evaluating the Spatial Precision of Deformable Image Registrations: The Distance Discordance Metric.

    PubMed

    Saleh, Z; Apte, A; Sharp, G; Deasy, J

    2012-06-01

    We propose a new metric called Distance Discordance (DD), which is defined as the distance between two anatomic points from two moving images, which are co-located on some reference image, when deformed onto another reference image. To demonstrate the concept of DD, we created a reference software phantom which contains two objects. The first object (1) consists of a hollow box with a fixed size core and variable wall thickness. The second object (2) consists of a solid box of fixed size and arbitrary location. 7 different variations of the fixed phantom were created. Each phantom was deformed onto every other phantom using two B-Spline DIR algorithms available in Elastix and Plastimatch. Voxels were sampled from the reference phantom [1], which were also deformed from moving phantoms [2…6], and we find the differences in their corresponding location on phantom [7]. Each voxel results in a distribution of DD values, which we call distance discordance histogram (DDH). We also demonstrate this concept in 8 Head & Neck patients. The two image registration algorithms produced two different DD results for the same phantom image set. The mean values of the DDH were slightly lower for Elastix (0-1.28 cm) as compared to the values produced by Plastimatch (0-1.43 cm). The combined DDH for the H&N patients followed a lognormal distribution with a mean of 0.45 cm and std. deviation of 0.42 cm. The proposed distance discordance (DD) metric is an easily interpretable, quantitative tool that can be used to evaluate the effect of inter-patient variability on the goodness of the registration in different parts of the patient anatomy. Therefore, it can be utilized to exclude certain images based on their DDH characteristics. In addition, this metric does not rely on 'ground truth' or the presence of contoured structures. Partially supported by NIH grant R01 CA85181. © 2012 American Association of Physicists in Medicine.

  17. Statistical properties of Jacobian maps and the realization of unbiased large-deformation nonlinear image registration.

    PubMed

    Leow, Alex D; Yanovsky, Igor; Chiang, Ming-Chang; Lee, Agatha D; Klunder, Andrea D; Lu, Allen; Becker, James T; Davis, Simon W; Toga, Arthur W; Thompson, Paul M

    2007-06-01

    Maps of local tissue compression or expansion are often computed by comparing magnetic resonance imaging (MRI) scans using nonlinear image registration. The resulting changes are commonly analyzed using tensor-based morphometry to make inferences about anatomical differences, often based on the Jacobian map, which estimates local tissue gain or loss. Here, we provide rigorous mathematical analyses of the Jacobian maps, and use themto motivate a new numerical method to construct unbiased nonlinear image registration. First, we argue that logarithmic transformation is crucial for analyzing Jacobian values representing morphometric differences. We then examine the statistical distributions of log-Jacobian maps by defining the Kullback-Leibler (KL) distance on material density functions arising in continuum-mechanical models. With this framework, unbiased image registration can be constructed by quantifying the symmetric KL-distance between the identity map and the resulting deformation. Implementation details, addressing the proposed unbiased registration as well as the minimization of symmetric image matching functionals, are then discussed and shown to be applicable to other registration methods, such as inverse consistent registration. In the results section, we test the proposed framework, as well as present an illustrative application mapping detailed 3-D brain changes in sequential magnetic resonance imaging scans of a patient diagnosed with semantic dementia. Using permutation tests, we show that the symmetrization of image registration statistically reduces skewness in the log-Jacobian map.

  18. Detection of time-varying structures by large deformation diffeomorphic metric mapping to aid reading of high-resolution CT images of the lung.

    PubMed

    Sakamoto, Ryo; Mori, Susumu; Miller, Michael I; Okada, Tomohisa; Togashi, Kaori

    2014-01-01

    To evaluate the accuracy of advanced non-linear registration of serial lung Computed Tomography (CT) images using Large Deformation Diffeomorphic Metric Mapping (LDDMM). FIFTEEN CASES OF LUNG CANCER WITH SERIAL LUNG CT IMAGES (INTERVAL: 62.2±26.9 days) were used. After affine transformation, three dimensional, non-linear volume registration was conducted using LDDMM with or without cascading elasticity control. Registration accuracy was evaluated by measuring the displacement of landmarks placed on vessel bifurcations for each lung segment. Subtraction images and Jacobian color maps, calculated from the transformation matrix derived from image warping, were generated, which were used to evaluate time-course changes of the tumors. The average displacement of landmarks was 0.02±0.16 mm and 0.12±0.60 mm for proximal and distal landmarks after LDDMM transformation with cascading elasticity control, which was significantly smaller than 3.11±2.47 mm and 3.99±3.05 mm, respectively, after affine transformation. Emerged or vanished nodules were visualized on subtraction images, and enlarging or shrinking nodules were displayed on Jacobian maps enabled by highly accurate registration of the nodules using LDDMM. However, some residual misalignments were observed, even with non-linear transformation when substantial changes existed between the image pairs. LDDMM provides accurate registration of serial lung CT images, and temporal subtraction images with Jacobian maps help radiologists to find changes in pulmonary nodules.

  19. Digital image registration method based upon binary boundary maps

    NASA Technical Reports Server (NTRS)

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

    1974-01-01

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

  20. Diffeomorphic metric mapping of high angular resolution diffusion imaging based on Riemannian structure of orientation distribution functions.

    PubMed

    Du, Jia; Goh, Alvina; Qiu, Anqi

    2012-05-01

    In this paper, we propose a novel large deformation diffeomorphic registration algorithm to align high angular resolution diffusion images (HARDI) characterized by orientation distribution functions (ODFs). Our proposed algorithm seeks an optimal diffeomorphism of large deformation between two ODF fields in a spatial volume domain and at the same time, locally reorients an ODF in a manner such that it remains consistent with the surrounding anatomical structure. To this end, we first review the Riemannian manifold of ODFs. We then define the reorientation of an ODF when an affine transformation is applied and subsequently, define the diffeomorphic group action to be applied on the ODF based on this reorientation. We incorporate the Riemannian metric of ODFs for quantifying the similarity of two HARDI images into a variational problem defined under the large deformation diffeomorphic metric mapping framework. We finally derive the gradient of the cost function in both Riemannian spaces of diffeomorphisms and the ODFs, and present its numerical implementation. Both synthetic and real brain HARDI data are used to illustrate the performance of our registration algorithm.

  1. TU-A-19A-01: Image Registration I: Deformable Image Registration, Contour Propagation and Dose Mapping: 101 and 201

    SciTech Connect

    Kessler, M

    2014-06-15

    Deformable image registration, contour propagation and dose mapping have become common, possibly essential tools for modern image-guided radiation therapy. Historically, these tools have been largely developed at academic medical centers and used in a rather limited and well controlled fashion. Today these tools are now available to the radiotherapy community at large, both as stand-alone applications and as integrated components of both treatment planning and treatment delivery systems. Unfortunately, the details of how these tools work and their limitations are not generally documented or described by the vendors that provide them. Although “it looks right”, determining that unphysical deformations may have occurred is crucial. Because of this, understanding how and when to use, and not use these tools to support everyday clinical decisions is far from straight forward. The goal of this session will be to present both the theory (basic and advanced) and practical clinical use of deformable image registration, contour propagation and dose mapping. To the extent possible, the “secret sauce” that different vendor use to produce reasonable/acceptable results will be described. A detailed explanation of the possible sources of errors and actual examples of these will be presented. Knowing the underlying principles of the process and understanding the confounding factors will help the practicing medical physicist be better able to make decisions (about making decisions) using these tools available. Learning Objectives: Understand the basic (101) and advanced (201) principles of deformable image registration, contour propagation and dose mapping data mapping. Understand the sources and impact of errors in registration and data mapping and the methods for evaluating the performance of these tools. Understand the clinical use and value of these tools, especially when used as a “black box”.

  2. Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

    SciTech Connect

    Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.; Le Boudic-Jamin, Mathilde; Wohlers, Inken

    2015-10-09

    In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifies up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.

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

    PubMed Central

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

    2013-01-01

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

  4. Fixed Point Results of Locally Contractive Mappings in Ordered Quasi-Partial Metric Spaces

    PubMed Central

    Arshad, Muhammad; Ahmad, Jamshaid

    2013-01-01

    Fixed point results for a self-map satisfying locally contractive conditions on a closed ball in an ordered 0-complete quasi-partial metric space have been established. Instead of monotone mapping, the notion of dominated mappings is applied. We have used weaker metric, weaker contractive conditions, and weaker restrictions to obtain unique fixed points. An example is given which shows that how this result can be used when the corresponding results cannot. Our results generalize, extend, and improve several well-known conventional results. PMID:24062629

  5. Fixed Points of Contractive Mappings in b-Metric-Like Spaces

    PubMed Central

    Hussain, Nawab; Roshan, Jamal Rezaei

    2014-01-01

    We discuss topological structure of b-metric-like spaces and demonstrate a fundamental lemma for the convergence of sequences. As an application we prove certain fixed point results in the setup of such spaces for different types of contractive mappings. Finally, some periodic point results in b-metric-like spaces are obtained. Two examples are presented in order to verify the effectiveness and applicability of our main results. PMID:25143980

  6. 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.

  7. Asymptotic behavior and Denjoy-Wolff theorems for Hilbert metric nonexpansive maps

    NASA Astrophysics Data System (ADS)

    Lins, Brian C.

    We study the asymptotic behavior of fixed point free Hilbert metric nonexpansive maps on bounded convex domains. For such maps, we prove that the omega limit sets are contained in a convex subset of the boundary when the domain is either polyhedral or two dimensional. Similar results are obtained for several classes of positive operators defined on closed cones, including linear maps, affine linear maps, max-min operators, and reproduction-decimation operators. We discuss the relationship between these results and other Denjoy-Wolff type theorems. In particular, we investigate the interaction of nonexpansive maps with the horofunction boundary in the Hilbert geometry and in finite dimensional normed spaces.

  8. Metrics, Bayes, and BOGSAT: Recognizing and Assessing Uncertainties in Earthquake Hazard Maps

    NASA Astrophysics Data System (ADS)

    Stein, S. A.; Brooks, E. M.; Spencer, B. D.

    2015-12-01

    Recent damaging earthquakes in areas predicted to be relatively safe illustrate the need to assess how seismic hazard maps perform. At present, there is no agreed way of assessing how well a map performed. The metric implicit in current maps, that during a time interval predicted shaking will be exceeded only at a specific fraction of sites, is useful but permits maps to be nominally successful although they significantly underpredict or overpredict shaking, or nominally unsuccessful but predict shaking well. We explore metrics that measure the effects of overprediction and underprediction. Although no single metric fully characterizes map behavior, using several metrics can provide useful insight for comparing and improving maps. A related question is whether to regard larger-than-expected shaking as a low-probability event allowed by a map, or to revise the map to show increased hazard. Whether and how much to revise a map is complicated, because a new map that better describes the past may or may not better predict the future. The issue is like deciding after a coin has come up heads a number of times whether to continue assuming that the coin is fair and the run is a low-probability event, or to change to a model in which the coin is assumed to be biased. This decision can be addressed using Bayes' Rule, so that how much to change depends on the degree of one's belief in the prior model. Uncertainties are difficult to assess for hazard maps, which require subjective assessments and choices among many poorly known or unknown parameters. However, even rough uncertainty measures for estimates/predictions from such models, sometimes termed BOGSATs (Bunch Of Guys Sitting Around Table) by risk analysts, can give users useful information to make better decisions. We explore the extent of uncertainty via sensitivity experiments on how the predicted hazard depends on model parameters.

  9. Fully automated prostate magnetic resonance imaging and transrectal ultrasound fusion via a probabilistic registration metric

    NASA Astrophysics Data System (ADS)

    Sparks, Rachel; Bloch, B. Nicholas; Feleppa, Ernest; Barratt, Dean; Madabhushi, Anant

    2013-03-01

    In this work, we present a novel, automated, registration method to fuse magnetic resonance imaging (MRI) and transrectal ultrasound (TRUS) images of the prostate. Our methodology consists of: (1) delineating the prostate on MRI, (2) building a probabilistic model of prostate location on TRUS, and (3) aligning the MRI prostate segmentation to the TRUS probabilistic model. TRUS-guided needle biopsy is the current gold standard for prostate cancer (CaP) diagnosis. Up to 40% of CaP lesions appear isoechoic on TRUS, hence TRUS-guided biopsy cannot reliably target CaP lesions and is associated with a high false negative rate. MRI is better able to distinguish CaP from benign prostatic tissue, but requires special equipment and training. MRI-TRUS fusion, whereby MRI is acquired pre-operatively and aligned to TRUS during the biopsy procedure, allows for information from both modalities to be used to help guide the biopsy. The use of MRI and TRUS in combination to guide biopsy at least doubles the yield of positive biopsies. Previous work on MRI-TRUS fusion has involved aligning manually determined fiducials or prostate surfaces to achieve image registration. The accuracy of these methods is dependent on the reader's ability to determine fiducials or prostate surfaces with minimal error, which is a difficult and time-consuming task. Our novel, fully automated MRI-TRUS fusion method represents a significant advance over the current state-of-the-art because it does not require manual intervention after TRUS acquisition. All necessary preprocessing steps (i.e. delineation of the prostate on MRI) can be performed offline prior to the biopsy procedure. We evaluated our method on seven patient studies, with B-mode TRUS and a 1.5 T surface coil MRI. Our method has a root mean square error (RMSE) for expertly selected fiducials (consisting of the urethra, calcifications, and the centroids of CaP nodules) of 3.39 +/- 0.85 mm.

  10. 3D-2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch.

    PubMed

    De Silva, T; Uneri, A; Ketcha, M D; Reaungamornrat, S; Kleinszig, G; Vogt, S; Aygun, N; Lo, S-F; Wolinsky, J-P; Siewerdsen, J H

    2016-04-21

    In image-guided spine surgery, robust three-dimensional to two-dimensional (3D-2D) registration of preoperative computed tomography (CT) and intraoperative radiographs can be challenged by the image content mismatch associated with the presence of surgical instrumentation and implants as well as soft-tissue resection or deformation. This work investigates image similarity metrics in 3D-2D registration offering improved robustness against mismatch, thereby improving performance and reducing or eliminating the need for manual masking. The performance of four gradient-based image similarity metrics (gradient information (GI), gradient correlation (GC), gradient information with linear scaling (GS), and gradient orientation (GO)) with a multi-start optimization strategy was evaluated in an institutional review board-approved retrospective clinical study using 51 preoperative CT images and 115 intraoperative mobile radiographs. Registrations were tested with and without polygonal masks as a function of the number of multistarts employed during optimization. Registration accuracy was evaluated in terms of the projection distance error (PDE) and assessment of failure modes (PDE  >  30 mm) that could impede reliable vertebral level localization. With manual polygonal masking and 200 multistarts, the GC and GO metrics exhibited robust performance with 0% gross failures and median PDE < 6.4 mm (±4.4 mm interquartile range (IQR)) and a median runtime of 84 s (plus upwards of 1-2 min for manual masking). Excluding manual polygonal masks and decreasing the number of multistarts to 50 caused the GC-based registration to fail at a rate of >14%; however, GO maintained robustness with a 0% gross failure rate. Overall, the GI, GC, and GS metrics were susceptible to registration errors associated with content mismatch, but GO provided robust registration (median PDE  =  5.5 mm, 2.6 mm IQR) without manual masking and with an improved runtime (29.3 s). The GO metric improved

  11. 3D-2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch

    NASA Astrophysics Data System (ADS)

    De Silva, T.; Uneri, A.; Ketcha, M. D.; Reaungamornrat, S.; Kleinszig, G.; Vogt, S.; Aygun, N.; Lo, S.-F.; Wolinsky, J.-P.; Siewerdsen, J. H.

    2016-04-01

    In image-guided spine surgery, robust three-dimensional to two-dimensional (3D-2D) registration of preoperative computed tomography (CT) and intraoperative radiographs can be challenged by the image content mismatch associated with the presence of surgical instrumentation and implants as well as soft-tissue resection or deformation. This work investigates image similarity metrics in 3D-2D registration offering improved robustness against mismatch, thereby improving performance and reducing or eliminating the need for manual masking. The performance of four gradient-based image similarity metrics (gradient information (GI), gradient correlation (GC), gradient information with linear scaling (GS), and gradient orientation (GO)) with a multi-start optimization strategy was evaluated in an institutional review board-approved retrospective clinical study using 51 preoperative CT images and 115 intraoperative mobile radiographs. Registrations were tested with and without polygonal masks as a function of the number of multistarts employed during optimization. Registration accuracy was evaluated in terms of the projection distance error (PDE) and assessment of failure modes (PDE  >  30 mm) that could impede reliable vertebral level localization. With manual polygonal masking and 200 multistarts, the GC and GO metrics exhibited robust performance with 0% gross failures and median PDE  <  6.4 mm (±4.4 mm interquartile range (IQR)) and a median runtime of 84 s (plus upwards of 1-2 min for manual masking). Excluding manual polygonal masks and decreasing the number of multistarts to 50 caused the GC-based registration to fail at a rate of  >14% however, GO maintained robustness with a 0% gross failure rate. Overall, the GI, GC, and GS metrics were susceptible to registration errors associated with content mismatch, but GO provided robust registration (median PDE  =  5.5 mm, 2.6 mm IQR) without manual masking and with an improved

  12. 3D–2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch

    PubMed Central

    De Silva, T; Uneri, A; Ketcha, M D; Reaungamornrat, S; Kleinszig, G; Vogt, S; Aygun, N; Lo, S-F; Wolinsky, J-P; Siewerdsen, J H

    2016-01-01

    In image-guided spine surgery, robust three-dimensional to two-dimensional (3D–2D) registration of preoperative computed tomography (CT) and intraoperative radiographs can be challenged by the image content mismatch associated with the presence of surgical instrumentation and implants as well as soft-tissue resection or deformation. This work investigates image similarity metrics in 3D–2D registration offering improved robustness against mismatch, thereby improving performance and reducing or eliminating the need for manual masking. The performance of four gradient-based image similarity metrics (gradient information (GI), gradient correlation (GC), gradient information with linear scaling (GS), and gradient orientation (GO)) with a multi-start optimization strategy was evaluated in an institutional review board-approved retrospective clinical study using 51 preoperative CT images and 115 intraoperative mobile radiographs. Registrations were tested with and without polygonal masks as a function of the number of multistarts employed during optimization. Registration accuracy was evaluated in terms of the projection distance error (PDE) and assessment of failure modes (PDE > 30 mm) that could impede reliable vertebral level localization. With manual polygonal masking and 200 multistarts, the GC and GO metrics exhibited robust performance with 0% gross failures and median PDE < 6.4 mm (±4.4 mm interquartile range (IQR)) and a median runtime of 84 s (plus upwards of 1–2 min for manual masking). Excluding manual polygonal masks and decreasing the number of multistarts to 50 caused the GC-based registration to fail at a rate of >14%; however, GO maintained robustness with a 0% gross failure rate. Overall, the GI, GC, and GS metrics were susceptible to registration errors associated with content mismatch, but GO provided robust registration (median PDE = 5.5 mm, 2.6 mm IQR) without manual masking and with an improved runtime (29.3 s). The GO metric improved the

  13. Computed tomography lung iodine contrast mapping by image registration and subtraction

    NASA Astrophysics Data System (ADS)

    Goatman, Keith; Plakas, Costas; Schuijf, Joanne; Beveridge, Erin; Prokop, Mathias

    2014-03-01

    Pulmonary embolism (PE) is a relatively common and potentially life threatening disease, affecting around 600,000 people annually in the United States alone. Prompt treatment using anticoagulants is effective and saves lives, but unnecessary treatment risks life threatening haemorrhage. The specificity of any diagnostic test for PE is therefore as important as its sensitivity. Computed tomography (CT) angiography is routinely used to diagnose PE. However, there are concerns it may over-report the condition. Additional information about the severity of an occlusion can be obtained from an iodine contrast map that represents tissue perfusion. Such maps tend to be derived from dual-energy CT acquisitions. However, they may also be calculated by subtracting pre- and post-contrast CT scans. Indeed, there are technical advantages to such a subtraction approach, including better contrast-to-noise ratio for the same radiation dose, and bone suppression. However, subtraction relies on accurate image registration. This paper presents a framework for the automatic alignment of pre- and post-contrast lung volumes prior to subtraction. The registration accuracy is evaluated for seven subjects for whom pre- and post-contrast helical CT scans were acquired using a Toshiba Aquilion ONE scanner. One hundred corresponding points were annotated on the pre- and post-contrast scans, distributed throughout the lung volume. Surface-to-surface error distances were also calculated from lung segmentations. Prior to registration the mean Euclidean landmark alignment error was 2.57mm (range 1.43-4.34 mm), and following registration the mean error was 0.54mm (range 0.44-0.64 mm). The mean surface error distance was 1.89mm before registration and 0.47mm after registration. There was a commensurate reduction in visual artefacts following registration. In conclusion, a framework for pre- and post-contrast lung registration has been developed that is sufficiently accurate for lung subtraction

  14. Effect of thematic map misclassification on landscape multi-metric assessment.

    PubMed

    Kleindl, William J; Powell, Scott L; Hauer, F Richard

    2015-06-01

    Advancements in remote sensing and computational tools have increased our awareness of large-scale environmental problems, thereby creating a need for monitoring, assessment, and management at these scales. Over the last decade, several watershed and regional multi-metric indices have been developed to assist decision-makers with planning actions of these scales. However, these tools use remote-sensing products that are subject to land-cover misclassification, and these errors are rarely incorporated in the assessment results. Here, we examined the sensitivity of a landscape-scale multi-metric index (MMI) to error from thematic land-cover misclassification and the implications of this uncertainty for resource management decisions. Through a case study, we used a simplified floodplain MMI assessment tool, whose metrics were derived from Landsat thematic maps, to initially provide results that were naive to thematic misclassification error. Using a Monte Carlo simulation model, we then incorporated map misclassification error into our MMI, resulting in four important conclusions: (1) each metric had a different sensitivity to error; (2) within each metric, the bias between the error-naive metric scores and simulated scores that incorporate potential error varied in magnitude and direction depending on the underlying land cover at each assessment site; (3) collectively, when the metrics were combined into a multi-metric index, the effects were attenuated; and (4) the index bias indicated that our naive assessment model may overestimate floodplain condition of sites with limited human impacts and, to a lesser extent, either over- or underestimated floodplain condition of sites with mixed land use.

  15. Comparison of optimization strategy and similarity metric in atlas-to-subject registration using statistical deformation model

    NASA Astrophysics Data System (ADS)

    Otake, Y.; Murphy, R. J.; Grupp, R. B.; Sato, Y.; Taylor, R. H.; Armand, M.

    2015-03-01

    A robust atlas-to-subject registration using a statistical deformation model (SDM) is presented. The SDM uses statistics of voxel-wise displacement learned from pre-computed deformation vectors of a training dataset. This allows an atlas instance to be directly translated into an intensity volume and compared with a patient's intensity volume. Rigid and nonrigid transformation parameters were simultaneously optimized via the Covariance Matrix Adaptation - Evolutionary Strategy (CMA-ES), with image similarity used as the objective function. The algorithm was tested on CT volumes of the pelvis from 55 female subjects. A performance comparison of the CMA-ES and Nelder-Mead downhill simplex optimization algorithms with the mutual information and normalized cross correlation similarity metrics was conducted. Simulation studies using synthetic subjects were performed, as well as leave-one-out cross validation studies. Both studies suggested that mutual information and CMA-ES achieved the best performance. The leave-one-out test demonstrated 4.13 mm error with respect to the true displacement field, and 26,102 function evaluations in 180 seconds, on average.

  16. A first-generation metric linkage disequilibrium map of bovine chromosome 6.

    PubMed

    Khatkar, Mehar S; Collins, Andrew; Cavanagh, Julie A L; Hawken, Rachel J; Hobbs, Matthew; Zenger, Kyall R; Barris, Wes; McClintock, Alexander E; Thomson, Peter C; Nicholas, Frank W; Raadsma, Herman W

    2006-09-01

    We constructed a metric linkage disequilibrium (LD) map of bovine chromosome 6 (BTA6) on the basis of data from 220 SNPs genotyped on 433 Australian dairy bulls. This metric LD map has distances in LD units (LDUs) that are analogous to centimorgans in linkage maps. The LD map of BTA6 has a total length of 8.9 LDUs. Within the LD map, regions of high LD (represented as blocks) and regions of low LD (steps) are observed, when plotted against the integrated map in kilobases. At the most stringent block definition, namely a set of loci with zero LDU increase over the span of these markers, BTA6 comprises 40 blocks, accounting for 41% of the chromosome. At a slightly lower stringency of block definition (a set of loci covering a maximum of 0.2 LDUs on the LD map), up to 81% of BTA6 is spanned by 46 blocks and with 13 steps that are likely to reflect recombination hot spots. The mean swept radius (the distance over which LD is likely to be useful for mapping) is 13.3 Mb, confirming extensive LD in Holstein-Friesian dairy cattle, which makes such populations ideal for whole-genome association studies.

  17. Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

    DOE PAGES

    Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.; ...

    2015-10-09

    In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

  18. Optimizing disk registration algorithms for nanobeam electron diffraction strain mapping

    DOE PAGES

    Pekin, Thomas C.; Gammer, Christoph; Ciston, Jim; ...

    2017-01-28

    Scanning nanobeam electron diffraction strain mapping is a technique by which the positions of diffracted disks sampled at the nanoscale over a crystalline sample can be used to reconstruct a strain map over a large area. However, it is important that the disk positions are measured accurately, as their positions relative to a reference are directly used to calculate strain. Here in this study, we compare several correlation methods using both simulated and experimental data in order to directly probe susceptibility to measurement error due to non-uniform diffracted disk illumination structure. We found that prefiltering the diffraction patterns with amore » Sobel filter before performing cross correlation or performing a square-root magnitude weighted phase correlation returned the best results when inner disk structure was present. Lastly, we have tested these methods both on simulated datasets, and experimental data from unstrained silicon as well as a twin grain boundary in 304 stainless steel.« less

  19. 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.

  20. Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI

    PubMed Central

    Wang, Sijia; Peterson, Daniel J.; Gatenby, J. C.; Li, Wenbin; Grabowski, Thomas J.; Madhyastha, Tara M.

    2017-01-01

    Correction of echo planar imaging (EPI)-induced distortions (called “unwarping”) improves anatomical fidelity for diffusion magnetic resonance imaging (MRI) and functional imaging investigations. Commonly used unwarping methods require the acquisition of supplementary images during the scanning session. Alternatively, distortions can be corrected by nonlinear registration to a non-EPI acquired structural image. In this study, we compared reliability using two methods of unwarping: (1) nonlinear registration to a structural image using symmetric normalization (SyN) implemented in Advanced Normalization Tools (ANTs); and (2) unwarping using an acquired field map. We performed this comparison in two different test-retest data sets acquired at differing sites (N = 39 and N = 32). In both data sets, nonlinear registration provided higher test-retest reliability of the output fractional anisotropy (FA) maps than field map-based unwarping, even when accounting for the effect of interpolation on the smoothness of the images. In general, field map-based unwarping was preferable if and only if the field maps were acquired optimally. PMID:28270762

  1. Quantization and Analysis of Hippocampal Morphometric Changes Due to Dementia of Alzheimer Type Using Metric Distances Based on Large Deformation Diffeomorphic Metric Mapping

    PubMed Central

    Ceyhan, Elvan; Beg, M. Faisal; Ceritog̃lu, Can; Wang, Lei; Morris, John C.; Csernansky, John G.; Miller, Michael I.; Ratnanather, J. Tilak

    2011-01-01

    The metric distance obtained from the Large Deformation Diffeomorphic Metric Mapping (LDDMM) algorithm is used to quantize changes in morphometry of brain structures due to neuropsychiatric diseases. For illustrative purposes we consider changes in hippocampal morphometry (shape and size) due to very mild dementia of the Alzheimer type (DAT). LDDMM, which was previously used to calculate dense one-to-one correspondence vector fields between hippocampal shapes, measures the morphometric differences with respect to a template hippocampus by assigning metric distances on the space of anatomical images thereby allowing for direct comparison of morphometric differences. We characterize what information the metric distances provide in terms of size and shape given the hippocampal, brain and intracranial volumes. We demonstrate that metric distance is a measure of morphometry (i.e., shape and size) but mostly a measure of shape, while volume is mostly a measure of size. Moreover, we show how metric distances can be used in cross-sectional, longitudinal analysis, as well as left-right asymmetry comparisons, and provide how the metric distances can serve as a discriminative tool using logistic regression. Thus, we show that metric distances with respect to a template computed via LDDMM can be a powerful tool in detecting differences in shape. PMID:21345652

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

    PubMed

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

    2010-01-01

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

  3. Increasing the power of functional maps of the medial temporal lobe by using large deformation diffeomorphic metric mapping.

    PubMed

    Miller, Michael I; Beg, M Faisal; Ceritoglu, Can; Stark, Craig

    2005-07-05

    The functional magnetic resonance imagery responses of declarative memory tasks in the medial temporal lobe (MTL) are examined by using large deformation diffeomorphic metric mapping (LDDMM) to remove anatomical variations across subjects. LDDMM is used to map the structures of the MTL in multiple subjects into extrinsic atlas coordinates; these same diffeomorphic mappings are used to transfer the corresponding functional data activation to the same extrinsic coordinates. The statistical power in the averaged LDDMM mapped signals is significantly increased over conventional Talairach-Tournoux averaging. Activation patterns are highly localized within the MTL. Whereas the present demonstration has been aimed at enhancing alignment within the MTL, this technique is general and can be applied throughout the brain.

  4. Automatic registration of aerial photographs and digitized maps

    NASA Astrophysics Data System (ADS)

    Li, S. Z.; Kittler, Josef; Petrou, Maria

    1993-06-01

    We have developed a method of matching and recognizing aerial road network images based on road network models. The input is a list of line segments of an image obtained from a preprocessing stage, which is usually fragmentary and contains extraneous noisy segments. The output is the correspondences between the image line segments and model line segments. We use attributed relational graphs (ARG) to describe images and models. An ARG consists of a set of nodes, each node representing a line segment, and attributed relations between nodes. The task of matching is to find the best correspondences between the image ARG and the model ARG. The correspondences are found using a relaxation labeling algorithm, which optimizes a criterion of similarity. The algorithm is capable of subgraph matching of an image road structure to a map road model covering an area 10 times larger than the area imaged by the sensor, provided that the image distortion due to perspective imaging geometry has been corrected during preprocessing stages. We present matching experiments and demonstrate the stability of the matching method to extraneous line segments, missing line segments, and errors in scaling.

  5. Fabricating Diminishable Visual Markers for Geometric Registration in Projection Mapping.

    PubMed

    Asayama, HIrotaka; Iwai, Daisuke; Sato, Kosuke

    2017-01-24

    We propose a visual marker embedding method for the pose estimation of a projection surface to correctly map projected images onto the surface. Assuming that the surface is fabricated by a full-color or multi-material three-dimensional (3D) printer, we propose to automatically embed visual markers on the surface with mechanical accuracy. The appearance of the marker is designed such that the marker is detected by infrared cameras even when printed on a non-planar surface while its appearance can be diminished by the projection to be as imperceptible as possible to human observers. The marker placement is optimized using a genetic algorithm to maximize the number of valid viewpoints from which the pose of the object can be estimated correctly using a stereo camera system. We also propose a radiometric compensation technique to quickly diminish the marker appearance. Experimental results confirm that the pose of projection objects are correctly estimated while the appearance of the markers was diminished to an imperceptible level. At the same time, we confirmed the limitations of the current method; only one object can be handled, and pose estimation is not performed at interactive frame rates. Finally, we demonstrate the proposed technique to show that it works successfully for various surface shapes and target textures.

  6. Nonrigid Registration of Brain Tumor Resection MR Images Based on Joint Saliency Map and Keypoint Clustering.

    PubMed

    Gu, Zhijun; Qin, Binjie

    2009-01-01

    This paper proposes a novel global-to-local nonrigid brain MR image registration to compensate for the brain shift and the unmatchable outliers caused by the tumor resection. The mutual information between the corresponding salient structures, which are enhanced by the joint saliency map (JSM), is maximized to achieve a global rigid registration of the two images. Being detected and clustered at the paired contiguous matching areas in the globally registered images, the paired pools of DoG keypoints in combination with the JSM provide a useful cluster-to-cluster correspondence to guide the local control-point correspondence detection and the outlier keypoint rejection. Lastly, a quasi-inverse consistent deformation is smoothly approximated to locally register brain images through the mapping the clustered control points by compact support radial basis functions. The 2D implementation of the method can model the brain shift in brain tumor resection MR images, though the theory holds for the 3D case.

  7. 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

  8. Image Registration for Quantitative Parametric Response Mapping of Cancer Treatment Response1

    PubMed Central

    Boes, Jennifer L; Hoff, Benjamin A; Hylton, Nola; Pickles, Martin D; Turnbull, Lindsay W; Schott, Anne F; Rehemtulla, Alnawaz; Chamberlain, Ryan; Lemasson, Benjamin; Chenevert, Thomas L; Galbán, Craig J; Meyer, Charles R; Ross, Brian D

    2014-01-01

    Imaging biomarkers capable of early quantification of tumor response to therapy would provide an opportunity to individualize patient care. Image registration of longitudinal scans provides a method of detecting treatment associated changes within heterogeneous tumors by monitoring alterations in the quantitative value of individual voxels over time, which is unattainable by traditional volumetric-based histogram methods. The concepts involved in the use of image registration for tracking and quantifying breast cancer treatment response using parametric response mapping (PRM), a voxel-based analysis of diffusion-weighted magnetic resonance imaging (DW-MRI) scans, are presented. Application of PRM to breast tumor response detection is described, wherein robust registration solutions for tracking small changes in water diffusivity in breast tumors during therapy are required. Methodologies that employ simulations are presented for measuring expected statistical accuracy of PRM for response assessment. Test-retest clinical scans are used to yield estimates of system noise to indicate significant changes in voxel-based changes in water diffusivity. Overall, registration-based PRM image analysis provides significant opportunities for voxel-based image analysis to provide the required accuracy for early assessment of response to treatment in breast cancer patients receiving neoadjuvant chemotherapy. PMID:24772213

  9. 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.

  10. Contractive type non-self mappings on metric spaces of hyperbolic type

    NASA Astrophysics Data System (ADS)

    Ciric, Ljubomir B.

    2006-05-01

    Let (X,d) be a metric space of hyperbolic type and K a nonempty closed subset of X. In this paper we study a class of mappings from K into X (not necessarily self-mappings on K), which are defined by the contractive condition (2.1) below, and a class of pairs of mappings from K into X which satisfy the condition (2.28) below. We present fixed point and common fixed point theorems which are generalizations of the corresponding fixed point theorems of Ciric [L.B. Ciric, Quasi-contraction non-self mappings on Banach spaces, Bull. Acad. Serbe Sci. Arts 23 (1998) 25-31; L.B. Ciric, J.S. Ume, M.S. Khan, H.K.T. Pathak, On some non-self mappings, Math. Nachr. 251 (2003) 28-33], Rhoades [B.E. Rhoades, A fixed point theorem for some non-self mappings, Math. Japon. 23 (1978) 457-459] and many other authors. Some examples are presented to show that our results are genuine generalizations of known results from this area.

  11. Three-dimensional quantitative assessment of ablation margins based on registration of pre- and post-procedural MRI and distance map

    PubMed Central

    Tani, Soichiro; Tatli, Servet; Hata, Nobuhiko; Garcia-Rojas, Xavier; Olubiyi, Olutayo I.; Silverman, Stuart G.; Tokuda, Junichi

    2016-01-01

    Purpose Contrast-enhanced MR images are widely used to confirm the adequacy of ablation margin after liver ablation for early prediction of local recurrence. However, quantitative assessment of the ablation margin by comparing pre- and post-procedural images remains challenging. We developed and tested a novel method for three-dimensional quantitative assessment of ablation margin based on non-rigid image registration and 3D distance map. Methods Our method was tested with pre- and post-procedural MR images acquired in 21 patients who underwent image-guided percutaneous liver ablation. The two images were co-registered using non-rigid intensity-based registration. After the tumor and ablation volumes were segmented, target volume coverage, percent of tumor coverage, and Dice Similarity Coefficient were calculated as metrics representing overall adequacy of ablation. In addition, 3D distance map around the tumor was computed and superimposed on the ablation volume to identify the area with insufficient margins. For patients with local recurrences, the follow-up images were registered to the post-procedural image. Three-D minimum distance between the recurrence and the areas with insufficient margins were quantified. Results The percent tumor coverage for all non-recurrent cases was 100%. Five cases had tumor recurrences, and the 3D distance map revealed insufficient tumor coverage or a 0-millimeter margin. It also showed that two recurrences were remote to the insufficient margin. Conclusions Non-rigid registration and 3D distance map allows us to quantitatively evaluate the adequacy of the ablation margin after percutaneous liver ablation. The method may be useful to predict local recurrences immediately following ablation procedure. PMID:27038962

  12. 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.

  13. Existence of common fixed point and best proximity point for generalized nonexpansive type maps in convex metric space.

    PubMed

    Rathee, Savita; Dhingra, Kusum; Kumar, Anil

    2016-01-01

    Here, we extend the notion of (E.A.) property in a convex metric space defined by Kumar and Rathee (Fixed Point Theory Appl 1-14, 2014) by introducing a new class of self-maps which satisfies the common property (E.A.) in the context of convex metric space and ensure the existence of common fixed point for this newly introduced class of self-maps. Also, we guarantee the existence of common best proximity points for this class of maps satisfying generalized non-expansive type condition. We furnish an example in support of the proved results.

  14. aMAP is a validated pipeline for registration and segmentation of high-resolution mouse brain data

    PubMed Central

    Niedworok, Christian J.; Brown, Alexander P. Y.; Jorge Cardoso, M.; Osten, Pavel; Ourselin, Sebastien; Modat, Marc; Margrie, Troy W.

    2016-01-01

    The validation of automated image registration and segmentation is crucial for accurate and reliable mapping of brain connectivity and function in three-dimensional (3D) data sets. While validation standards are necessarily high and routinely met in the clinical arena, they have to date been lacking for high-resolution microscopy data sets obtained from the rodent brain. Here we present a tool for optimized automated mouse atlas propagation (aMAP) based on clinical registration software (NiftyReg) for anatomical segmentation of high-resolution 3D fluorescence images of the adult mouse brain. We empirically evaluate aMAP as a method for registration and subsequent segmentation by validating it against the performance of expert human raters. This study therefore establishes a benchmark standard for mapping the molecular function and cellular connectivity of the rodent brain. PMID:27384127

  15. Comparison of interferometric and stereo-radargrammetric 3D metrics in mapping of forest resources

    NASA Astrophysics Data System (ADS)

    Karila, K.; Karjalainen, M.; Yu, X.; Vastaranta, M.; Holopainen, M.; Hyyppa, J.

    2015-04-01

    Accurate forest resources maps are needed in diverse applications ranging from the local forest management to the global climate change research. In particular, it is important to have tools to map changes in forest resources, which helps us to understand the significance of the forest biomass changes in the global carbon cycle. In the task of mapping changes in forest resources for wide areas, Earth Observing satellites could play the key role. In 2013, an EU/FP7-Space funded project "Advanced_SAR" was started with the main objective to develop novel forest resources mapping methods based on the fusion of satellite based 3D measurements and in-situ field measurements of forests. During the summer 2014, an extensive field surveying campaign was carried out in the Evo test site, Southern Finland. Forest inventory attributes of mean tree height, basal area, mean stem diameter, stem volume, and biomass, were determined for 91 test plots having the size of 32 by 32 meters (1024 m2). Simultaneously, a comprehensive set of satellite and airborne data was collected. Satellite data also included a set of TanDEM-X (TDX) and TerraSAR-X (TSX) X-band synthetic aperture radar (SAR) images, suitable for interferometric and stereo-radargrammetric processing to extract 3D elevation data representing the forest canopy. In the present study, we compared the accuracy of TDX InSAR and TSX stereo-radargrammetric derived 3D metrics in forest inventory attribute prediction. First, 3D data were extracted from TDX and TSX images. Then, 3D data were processed as elevations above the ground surface (forest canopy height values) using an accurate Digital Terrain Model (DTM) based on airborne laser scanning survey. Finally, 3D metrics were calculated from the canopy height values for each test plot and the 3D metrics were compared with the field reference data. The Random Forest method was used in the forest inventory attributes prediction. Based on the results InSAR showed slightly better

  16. Lung iodine mapping by subtraction with image registration allowing for tissue sliding

    NASA Astrophysics Data System (ADS)

    Mohr, Brian; Brink, Monique; Oostveen, Luuk J.; Schuijf, Joanne D.; Prokop, Mathias

    2016-03-01

    Pulmonary embolism is a fairly common and serious entity, so rapid diagnosis and treatment has a significant impact on morbidity and mortality rates. Iodine maps representing tissue perfusion enhancement are commonly generated by dual-energy CT acquisitions to provide information about the effect of the embolism on pulmonary perfusion. Alternatively, the iodine map can be generated by subtracting pre- from post-contrast CT scans as previously reported. Although accurate image registration is essential, subtraction has the advantage of a higher signal-to-noise ratio and suppression of bone. This paper presents an improvement over the previously reported registration algorithm. Significantly, allowance for sliding motion at tissue boundaries is included in the regularization. Pre- and post-contrast helical CT scans were acquired for thirty subjects using a Toshiba Aquilion ONE scanner. Ten of these subjects were designated for algorithm development, while the remaining twenty were reserved for qualitative clinical evaluation. Quantitative evaluation was performed against the previously reported method and using publicly available data for comparison against other methods. Comparison of 100 landmarks in seven datasets shows no change in the mean Euclidean error of 0.48 mm, compared to the previous method. Evaluation in the publicly available DIR-Lab data with 300 annotations results in a mean Euclidean error of 1.17 mm in the ten 4DCT cases and 3.37 mm in the ten COPDGene cases. Clinical evaluation on a sliding scale from 1 (excellent) to 5 (non-diagnostic) indicates a slight, but non-significant, improvement in registration adequacy from 3.1 to 2.9.

  17. Motion Correction for Myocardial T1 Mapping using Image Registration with Synthetic Image Estimation

    PubMed Central

    Xue, Hui; Shah, Saurabh; Greiser, Andreas; Guetter, Christoph; Littmann, Arne; Jolly, Marie-Pierre; Arai, Andrew E; Zuehlsdorff, Sven; Guehring, Jens; Kellman, Peter

    2013-01-01

    Quantification of myocardial T1 relaxation has potential value in the diagnosis of both ischemic and non-ischemic cardiomyopathies. Image acquisition using the Modified Look-Locker Inversion Recovery technique is clinically feasible for T1 mapping. However, respiratory motion limits its applicability and degrades the accuracy of T1 estimation. The robust registration of acquired inversion recovery images is particularly challenging due to the large changes in image contrast, especially for those images acquired near the signal null point of the inversion recovery and other inversion times for which there is little tissue contrast. In this paper, we propose a novel motion correction algorithm. This approach is based on estimating synthetic images presenting contrast changes similar to the acquired images. The estimation of synthetic images is formulated as a variational energy minimization problem. Validation on a consecutive patient data cohort shows that this strategy can perform robust non-rigid registration to align inversion recovery images experiencing significant motion and lead to suppression of motion induced artifacts in the T1 map. PMID:22135227

  18. Nonrigid Registration of Brain Tumor Resection MR Images Based on Joint Saliency Map and Keypoint Clustering

    PubMed Central

    Gu, Zhijun; Qin, Binjie

    2009-01-01

    This paper proposes a novel global-to-local nonrigid brain MR image registration to compensate for the brain shift and the unmatchable outliers caused by the tumor resection. The mutual information between the corresponding salient structures, which are enhanced by the joint saliency map (JSM), is maximized to achieve a global rigid registration of the two images. Being detected and clustered at the paired contiguous matching areas in the globally registered images, the paired pools of DoG keypoints in combination with the JSM provide a useful cluster-to-cluster correspondence to guide the local control-point correspondence detection and the outlier keypoint rejection. Lastly, a quasi-inverse consistent deformation is smoothly approximated to locally register brain images through the mapping the clustered control points by compact support radial basis functions. The 2D implementation of the method can model the brain shift in brain tumor resection MR images, though the theory holds for the 3D case. PMID:22303173

  19. Landmark constrained genus-one surface Teichmüller map applied to surface registration in medical imaging.

    PubMed

    Lam, Ka Chun; Gu, Xianfeng; Lui, Lok Ming

    2015-10-01

    We address the registration problem of genus-one surfaces (such as vertebrae bones) with prescribed landmark constraints. The high-genus topology of the surfaces makes it challenging to obtain a unique and bijective surface mapping that matches landmarks consistently. This work proposes to tackle this registration problem using a special class of quasi-conformal maps called Teichmüller maps (T-Maps). A landmark constrained T-Map is the unique mapping between genus-1 surfaces that minimizes the maximal conformality distortion while matching the prescribed feature landmarks. Existence and uniqueness of the landmark constrained T-Map are theoretically guaranteed. This work presents an iterative algorithm to compute the T-Map. The main idea is to represent the set of diffeomorphism using the Beltrami coefficients (BC). The BC is iteratively adjusted to an optimal one, which corresponds to our desired T-Map that matches the prescribed landmarks and satisfies the periodic boundary condition on the universal covering space. Numerical experiments demonstrate the effectiveness of our proposed algorithm. The method has also been applied to register vertebrae bones with prescribed landmark points and curves, which gives accurate surface registrations.

  20. Multi-manifold diffeomorphic metric mapping for aligning cortical hemispheric surfaces.

    PubMed

    Zhong, Jidan; Qiu, Anqi

    2010-01-01

    Cortical surface-based analysis has been widely used in anatomical and functional studies because it is geometrically appropriate for the cortex. One of the main challenges in the cortical surface-based analysis is to optimize the alignment of the cortical hemispheric surfaces across individuals. In this paper, we introduce a multi-manifold large deformation diffeomorphic metric mapping (MM-LDDMM) algorithm that allows simultaneously carrying the cortical hemispheric surface and its sulcal curves from one to the other through a flow of diffeomorphisms. We present an algorithm based on recent derivation of a law of momentum conservation for the geodesics of diffeomorphic flow. Once a template is fixed, the space of initial momentum becomes an appropriate space for studying shape via geodesic flow since the flow at any point on curves and surfaces along the geodesic is completely determined by the momentum at the origin. We solve for trajectories (geodesics) of the kinetic energy by computing its variation with respect to the initial momentum and by applying a gradient descent scheme. The MM-LDDMM algorithm optimizes the initial momenta encoding the anatomical variation of each individual relative to a common coordinate system in a linear space, which provides a natural scheme for shape deformation average and template (or atlas) generation. We applied the MM-LDDMM algorithm for constructing the templates for the cortical surface and 14 sulcal curves of each hemisphere using a group of 40 subjects. The estimated template shape reflects regions which are highly variable across these subjects. Compared with existing single-manifold LDDMM algorithms, such as the LDDMM-curve mapping and the LDDMM-surface mapping, the MM-LDDMM mapping provides better results in terms of surface to surface distances in five predefined regions.

  1. Effects of registration error on parametric response map analysis: a simulation study using liver CT-perfusion images

    NASA Astrophysics Data System (ADS)

    Lausch, A.; Jensen, N. K. G.; Chen, J.; Lee, T. Y.; Lock, M.; Wong, E.

    2014-03-01

    Purpose: To investigate the effects of registration error (RE) on parametric response map (PRM) analysis of pre and post-radiotherapy (RT) functional images. Methods: Arterial blood flow maps (ABF) were generated from the CT-perfusion scans of 5 patients with hepatocellular carcinoma. ABF values within each patient map were modified to produce seven new ABF maps simulating 7 distinct post-RT functional change scenarios. Ground truth PRMs were generated for each patient by comparing the simulated and original ABF maps. Each simulated ABF map was then deformed by different magnitudes of realistic respiratory motion in order to simulate RE. PRMs were generated for each of the deformed maps and then compared to the ground truth PRMs to produce estimates of RE-induced misclassification. Main findings: The percentage of voxels misclassified as decreasing, no change, and increasing, increased with RE For all patients, increasing RE was observed to increase the number of high post-RT ABF voxels associated with low pre-RT ABF voxels and vice versa. 3 mm of average tumour RE resulted in 18-45% tumour voxel misclassification rates. Conclusions: RE induced misclassification posed challenges for PRM analysis in the liver where registration accuracy tends to be lower. Quantitative understanding of the sensitivity of the PRM method to registration error is required if PRMs are to be used to guide radiation therapy dose painting techniques.

  2. Diffeomorphic metric surface mapping in subregion of the superior temporal gyrus.

    PubMed

    Vaillant, Marc; Qiu, Anqi; Glaunès, Joan; Miller, Michael I

    2007-02-01

    This paper describes the application of large deformation diffeomorphic metric mapping to cortical surfaces based on the shape and geometric properties of subregions of the superior temporal gyrus in the human brain. The anatomical surfaces of the cortex are represented as triangulated meshes. The diffeomorphic matching algorithm is implemented by defining a norm between the triangulated meshes, based on the algorithms of Vaillant and Glaunès. The diffeomorphic correspondence is defined as a flow of the extrinsic three dimensional coordinates containing the cortical surface that registers the initial and target geometry by minimizing the norm. The methods are demonstrated in 40 high-resolution MRI cortical surfaces of planum temporale (PT) constructed from subsets of the superior temporal gyrus (STG). The effectiveness of the algorithm is demonstrated via the Euclidean positional distance, distance of normal vectors, and curvature before and after the surface matching as well as the comparison with a landmark matching algorithm. The results demonstrate that both the positional and shape variability of the anatomical configurations are being represented by the diffeomorphic maps.

  3. Diffeomorphic Image Registration of Diffusion MRI Using Spherical Harmonics

    PubMed Central

    Geng, Xiujuan; Ross, Thomas J.; Gu, Hong; Shin, Wanyong; Zhan, Wang; Chao, Yi-Ping; Lin, Ching-Po; Schuff, Norbert; Yang, Yihong

    2013-01-01

    Non-rigid registration of diffusion MRI is crucial for group analyses and building white matter and fiber tract atlases. Most current diffusion MRI registration techniques are limited to the alignment of diffusion tensor imaging (DTI) data. We propose a novel diffeomorphic registration method for high angular resolution diffusion images by mapping their orientation distribution functions (ODFs). ODFs can be reconstructed using q-ball imaging (QBI) techniques and represented by spherical harmonics (SHs) to resolve intra-voxel fiber crossings. The registration is based on optimizing a diffeomorphic demons cost function. Unlike scalar images, deforming ODF maps requires ODF reorientation to maintain its consistency with the local fiber orientations. Our method simultaneously reorients the ODFs by computing a Wigner rotation matrix at each voxel, and applies it to the SH coefficients during registration. Rotation of the coefficients avoids the estimation of principal directions, which has no analytical solution and is time consuming. The proposed method was validated on both simulated and real data sets with various metrics, which include the distance between the estimated and simulated transformation fields, the standard deviation of the general fractional anisotropy and the directional consistency of the deformed and reference images. The registration performance using SHs with different maximum orders were compared using these metrics. Results show that the diffeomorphic registration improved the affine alignment, and registration using SHs with higher order SHs further improved the registration accuracy by reducing the shape difference and improving the directional consistency of the registered and reference ODF maps. PMID:21134814

  4. Diffeomorphic image registration of diffusion MRI using spherical harmonics.

    PubMed

    Geng, Xiujuan; Ross, Thomas J; Gu, Hong; Shin, Wanyong; Zhan, Wang; Chao, Yi-Ping; Lin, Ching-Po; Schuff, Norbert; Yang, Yihong

    2011-03-01

    Nonrigid registration of diffusion magnetic resonance imaging (MRI) is crucial for group analyses and building white matter and fiber tract atlases. Most current diffusion MRI registration techniques are limited to the alignment of diffusion tensor imaging (DTI) data. We propose a novel diffeomorphic registration method for high angular resolution diffusion images by mapping their orientation distribution functions (ODFs). ODFs can be reconstructed using q-ball imaging (QBI) techniques and represented by spherical harmonics (SHs) to resolve intra-voxel fiber crossings. The registration is based on optimizing a diffeomorphic demons cost function. Unlike scalar images, deforming ODF maps requires ODF reorientation to maintain its consistency with the local fiber orientations. Our method simultaneously reorients the ODFs by computing a Wigner rotation matrix at each voxel, and applies it to the SH coefficients during registration. Rotation of the coefficients avoids the estimation of principal directions, which has no analytical solution and is time consuming. The proposed method was validated on both simulated and real data sets with various metrics, which include the distance between the estimated and simulated transformation fields, the standard deviation of the general fractional anisotropy and the directional consistency of the deformed and reference images. The registration performance using SHs with different maximum orders were compared using these metrics. Results show that the diffeomorphic registration improved the affine alignment, and registration using SHs with higher order SHs further improved the registration accuracy by reducing the shape difference and improving the directional consistency of the registered and reference ODF maps.

  5. Hamiltonian Map to Conformal Modification of Spacetime Metric: Kaluza-Klein and TeVeS

    NASA Astrophysics Data System (ADS)

    Horwitz, Lawrence; Gershon, Avi; Schiffer, Marcelo

    2011-01-01

    It has been shown that the orbits of motion for a wide class of non-relativistic Hamiltonian systems can be described as geodesic flows on a manifold and an associated dual by means of a conformal map. This method can be applied to a four dimensional manifold of orbits in spacetime associated with a relativistic system. We show that a relativistic Hamiltonian which generates Einstein geodesics, with the addition of a world scalar field, can be put into correspondence in this way with another Hamiltonian with conformally modified metric. Such a construction could account for part of the requirements of Bekenstein for achieving the MOND theory of Milgrom in the post-Newtonian limit. The constraints on the MOND theory imposed by the galactic rotation curves, through this correspondence, would then imply constraints on the structure of the world scalar field. We then use the fact that a Hamiltonian with vector gauge fields results, through such a conformal map, in a Kaluza-Klein type theory, and indicate how the TeVeS structure of Bekenstein and Saunders can be put into this framework. We exhibit a class of infinitesimal gauge transformations on the gauge fields {mathcal{U}}_{μ}(x) which preserve the Bekenstein-Sanders condition {mathcal{U}}_{μ}{mathcal{U}}^{μ}=-1. The underlying quantum structure giving rise to these gauge fields is a Hilbert bundle, and the gauge transformations induce a non-commutative behavior to the fields, i.e. they become of Yang-Mills type. Working in the infinitesimal gauge neighborhood of the initial Abelian theory we show that in the Abelian limit the Yang-Mills field equations provide residual nonlinear terms which may avoid the caustic singularity found by Contaldi et al.

  6. Time Sequence Diffeomorphic Metric Mapping and Parallel Transport Track Time-Dependent Shape Changes

    PubMed Central

    Qiu, Anqi; Albert, Marilyn; Younes, Laurent; Miller, Michael I.

    2009-01-01

    Serial MRI human brain scans have facilitated the detection of brain development and of the earliest signs of neuropsychiatric and neurodegenerative diseases, monitoring disease progression, and resolving drug effects in clinical trials for preventing or slowing the rate of brain degeneration. To track anatomical shape changes in serial images, we introduce new point-based time sequence large deformation diffeomorphic metric mapping (TS-LDDMM) to infer the time flow of within-subject geometric shape changes that carry known observations through a period. Its Euler-Lagrange equation is generalized for anatomies whose shapes are characterized by point sets, such as landmarks, curves, and surfaces. The time-dependent momentum obtained from the TS-LDDMM encodes within-subject shape changes. For the purpose of across-subject shape comparison, we then propose a diffeomorphic analysis framework to translate within-subject deformation in a global template without incorporating across-subject anatomical variations via parallel transport technique. The analysis involves the retraction of the within-subject timedependent momentum along the TS-LDDMM trajectory from each time to the baseline, the translation of the momentum in a global template, and the reconstruction of the TS-LDDMM trajectory starting from the global template. PMID:19041947

  7. A large deformation diffeomorphic metric mapping solution for diffusion spectrum imaging datasets.

    PubMed

    Hsu, Yung-Chin; Hsu, Ching-Han; Tseng, Wen-Yih Isaac

    2012-11-01

    Spatial transformation for diffusion spectrum imaging (DSI) is an important step for group analyses of DSI datasets. In this study, we developed a transformation method for DSI datasets under the framework of large deformation diffeomorphic metric mapping (LDDMM), which is termed LDDMM-DSI. The proposed method made use of the fact that a DSI dataset is 6D, and generalized the original 2D/3D LDDMM algorithm to the 6D case with some modifications made for the DSI datasets. In this manner, the conventional reorientation problem that arises from transforming diffusion-weighted datasets was avoided by making the DSI datasets capable of being freely deformed in the q-space. The algorithm treated the data-matching task as a variational problem under the LDDMM framework and sought optimal velocity fields from which the generated transformations were diffeomorphic and the transformation curve was a geodesic. The mathematical materials and numerical implementation are detailed in the paper, and experiments were performed to analyze the proposed method on real brain DSI datasets. The results showed that the method was capable of registering different DSI datasets in both global structural shapes and local diffusion profiles. In conclusion, the proposed method can facilitate group analyses of DSI datasets and the generation of a DSI template. Copyright © 2012 Elsevier Inc. All rights reserved.

  8. Diffeomorphic metric mapping of hybrid diffusion imaging based on BFOR signal basis.

    PubMed

    Du, Jia; Hosseinbor, A Pasha; Chung, Moo K; Bendlin, Barbara B; Suryawanshi, Gaurav; Suryawanshi, Gaurav; Qiu, Anqi

    2013-01-01

    In this paper, we propose a large deformation diffeomorphic metric mapping algorithm to align multiple b-value diffusion weighted imaging (mDWI) data, specifically acquired via hybrid diffusion imaging (HYDI), denoted as LDDMM-HYDI. We adopt the work given in Hosseinbor et al. (2012) and represent the q-space diffusion signal with the Bessel Fourier orientation reconstruction (BFOR) signal basis. The BFOR framework provides the representation of mDWI in the q-space and thus reduces memory requirement. In addition, since the BFOR signal basis is orthonormal, the L2 norm that quantifies the differences in q-space signals of any two mDWI datasets can be easily computed as the sum of the squared differences in the BFOR expansion coefficients. In this work, we show that the reorientation of the q-space signal due to spatial transformation can be easily defined on the BFOR signal basis. We incorporate the BFOR signal basis into the LDDMM framework and derive the gradient descent algorithm for LDDMM-HYDI with explicit orientation optimization. Using real HYDI datasets, we show that it is important to consider the variation of mDWI reorientation due to a small change in diffeomorphic transformation in the LDDMM-HYDI optimization.

  9. Diffeomorphic Metric Mapping and Probabilistic Atlas Generation of Hybrid Diffusion Imaging based on BFOR Signal Basis

    PubMed Central

    Du, Jia; Hosseinbor, A. Pasha; Chung, Moo K.; Bendlin, Barbara B.; Suryawanshi, Gaurav; Alexander, Andrew L.; Qiu, Anqi

    2015-01-01

    We first propose a large deformation diffeomorphic metric mapping algorithm to align multiple b-value diffusion weighted imaging (mDWI) data, specifically acquired via hybrid diffusion imaging (HYDI).We denote this algorithm as LDDMM-HYDI. We then propose a Bayesian probabilistic model for estimating the white matter atlas from HYDIs. We adopt the work given in Hosseinbor et al. (2012) and represent the q-space diffusion signal with the Bessel Fourier orientation reconstruction (BFOR) signal basis. The BFOR framework provides the representation of mDWI in the q-space and the analytic form of the emsemble average propagator (EAP) reconstructure, as well as reduces memory requirement. In addition, since the BFOR signal basis is orthonormal, the L2 norm that quantifies the differences in the q-space signals of any two mDWI datasets can be easily computed as the sum of the squared differences in the BFOR expansion coefficients. In this work, we show that the reorientation of the q-space signal due to spatial transformation can be easily defined on the BFOR signal basis. We incorporate the BFOR signal basis into the LDDMM framework and derive the gradient descent algorithm for LDDMM-HYDI with explicit orientation optimization. Additionally, we extend the previous Bayesian atlas estimation framework for scalar-valued images to HYDIs and derive the expectation-maximization algorithm for solving the HYDI atlas estimation problem. Using real HYDI datasets, we show the Bayesian model generates the white matter atlas with anatomical details. Moreover, we show that it is important to consider the variation of mDWI reorientation due to a small change in diffeomorphic transformation in the LDDMM-HYDI optimization and to incorporate the full information of HYDI for aligning mDWI. Finally, we show that the LDDMM-HYDI outperforms the LDDMM algorithm with diffusion tensors generated from each shell of HYDI. PMID:24972378

  10. Automated, foot-bone registration using subdivision-embedded atlases for spatial mapping of bone mineral density.

    PubMed

    Liu, Lu; Commean, Paul K; Hildebolt, Charles; Sinacore, Dave; Prior, Fred; Carson, James P; Kakadiaris, Ioannis; Ju, Tao

    2013-06-01

    We present an atlas-based registration method for bones segmented from quantitative computed tomography (QCT) scans, with the goal of mapping their interior bone mineral densities (BMDs) volumetrically. We introduce a new type of deformable atlas, called subdivision-embedded atlas, which consists of a control grid represented as a tetrahedral subdivision mesh and a template bone surface embedded within the grid. Compared to a typical lattice-based deformation grid, the subdivision control grid possesses a relatively small degree of freedom tailored to the shape of the bone, which allows efficient fitting onto subjects. Compared with previous subdivision atlases, the novelty of our atlas lies in the addition of the embedded template surface, which further increases the accuracy of the fitting. Using this new atlas representation, we developed an efficient and fully automated pipeline for registering atlases of 12 tarsal and metatarsal bones to a segmented QCT scan of a human foot. Our evaluation shows that the mapping of BMD enabled by the registration is consistent for bones in repeated scans, and the regional BMD automatically computed from the mapping is not significantly different from expert annotations. The results suggest that our improved subdivision-based registration method is a reliable, efficient way to replace manual labor for measuring regional BMD in foot bones in QCT scans.

  11. METRIC model for the estimation and mapping of evapotranspiration in a super intensive olive orchard in Southern Portugal

    NASA Astrophysics Data System (ADS)

    Pôças, Isabel; Nogueira, António; Paço, Teresa A.; Sousa, Adélia; Valente, Fernanda; Silvestre, José; Andrade, José A.; Santos, Francisco L.; Pereira, Luís S.; Allen, Richard G.

    2013-04-01

    Satellite-based surface energy balance models have been successfully applied to estimate and map evapotranspiration (ET). The METRICtm model, Mapping EvapoTranspiration at high Resolution using Internalized Calibration, is one of such models. METRIC has been widely used over an extensive range of vegetation types and applications, mostly focusing annual crops. In the current study, the single-layer-blended METRIC model was applied to Landsat5 TM and Landsat7 ETM+ images to produce estimates of evapotranspiration (ET) in a super intensive olive orchard in Southern Portugal. In sparse woody canopies as in olive orchards, some adjustments in METRIC application related to the estimation of vegetation temperature and of momentum roughness length and sensible heat flux (H) for tall vegetation must be considered. To minimize biases in H estimates due to uncertainties in the definition of momentum roughness length, the Perrier function based on leaf area index and tree canopy architecture, associated with an adjusted estimation of crop height, was used to obtain momentum roughness length estimates. Additionally, to minimize the biases in surface temperature simulations, due to soil and shadow effects, the computation of radiometric temperature considered a three-source condition, where Ts=fcTc+fshadowTshadow+fsunlitTsunlit. As such, the surface temperature (Ts), derived from the thermal band of the Landsat images, integrates the temperature of the canopy (Tc), the temperature of the shaded ground surface (Tshadow), and the temperature of the sunlit ground surface (Tsunlit), according to the relative fraction of vegetation (fc), shadow (fshadow) and sunlit (fsunlit) ground surface, respectively. As the sunlit canopies are the primary source of energy exchange, the effective temperature for the canopy was estimated by solving the three-source condition equation for Tc. To evaluate METRIC performance to estimate ET over the olive grove, several parameters derived from the

  12. Diffeomorphic metric mapping and probabilistic atlas generation of hybrid diffusion imaging based on BFOR signal basis.

    PubMed

    Du, Jia; Hosseinbor, A Pasha; Chung, Moo K; Bendlin, Barbara B; Suryawanshi, Gaurav; Alexander, Andrew L; Qiu, Anqi

    2014-10-01

    We first propose a large deformation diffeomorphic metric mapping algorithm to align multiple b-value diffusion weighted imaging (mDWI) data, specifically acquired via hybrid diffusion imaging (HYDI). We denote this algorithm as LDDMM-HYDI. We then propose a Bayesian probabilistic model for estimating the white matter atlas from HYDIs. We adopt the work given in Hosseinbor et al. (2013) and represent the q-space diffusion signal with the Bessel Fourier orientation reconstruction (BFOR) signal basis. The BFOR framework provides the representation of mDWI in the q-space and the analytic form of the emsemble average propagator (EAP) reconstruction, as well as reduces memory requirement. In addition, since the BFOR signal basis is orthonormal, the L(2) norm that quantifies the differences in the q-space signals of any two mDWI datasets can be easily computed as the sum of the squared differences in the BFOR expansion coefficients. In this work, we show that the reorientation of the q-space signal due to spatial transformation can be easily defined on the BFOR signal basis. We incorporate the BFOR signal basis into the LDDMM framework and derive the gradient descent algorithm for LDDMM-HYDI with explicit orientation optimization. Additionally, we extend the previous Bayesian atlas estimation framework for scalar-valued images to HYDIs and derive the expectation-maximization algorithm for solving the HYDI atlas estimation problem. Using real HYDI datasets, we show that the Bayesian model generates the white matter atlas with anatomical details. Moreover, we show that it is important to consider the variation of mDWI reorientation due to a small change in diffeomorphic transformation in the LDDMM-HYDI optimization and to incorporate the full information of HYDI for aligning mDWI. Finally, we show that the LDDMM-HYDI outperforms the LDDMM algorithm with diffusion tensors generated from each shell of HYDI. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights

  13. Nonrigid registration of multiple sclerosis brain images using lesion inpainting for morphometry or lesion mapping.

    PubMed

    Sdika, Michaël; Pelletier, Daniel

    2009-04-01

    Morphometric studies of medical images often include a nonrigid registration step from a subject to a common reference. The presence of white matter multiple sclerosis lesions will distort and bias the output of the registration. In this article, we present a method to remove this bias by filling such lesions to make the brain look like a healthy brain before the registration. We finally propose a dedicated method to fill the lesions and present numerical results showing that our method outperforms current state of the art method. 2008 Wiley-Liss, Inc.

  14. Efficient Inverse Isoparametric Mapping Algorithm for Whole-Body Computed Tomography Registration Using Deformations Predicted by Nonlinear Finite Element Modeling

    PubMed Central

    Li, Mao; Wittek, Adam; Miller, Karol

    2014-01-01

    Biomechanical modeling methods can be used to predict deformations for medical image registration and particularly, they are very effective for whole-body computed tomography (CT) image registration because differences between the source and target images caused by complex articulated motions and soft tissues deformations are very large. The biomechanics-based image registration method needs to deform the source images using the deformation field predicted by finite element models (FEMs). In practice, the global and local coordinate systems are used in finite element analysis. This involves the transformation of coordinates from the global coordinate system to the local coordinate system when calculating the global coordinates of image voxels for warping images. In this paper, we present an efficient numerical inverse isoparametric mapping algorithm to calculate the local coordinates of arbitrary points within the eight-noded hexahedral finite element. Verification of the algorithm for a nonparallelepiped hexahedral element confirms its accuracy, fast convergence, and efficiency. The algorithm's application in warping of the whole-body CT using the deformation field predicted by means of a biomechanical FEM confirms its reliability in the context of whole-body CT registration. PMID:24828796

  15. Facile and high spatial resolution ratio-metric luminescence thermal mapping in microfluidics by near infrared excited upconversion nanoparticles

    NASA Astrophysics Data System (ADS)

    Wang, Yu; Cao, Wenbin; Li, Shunbo; Wen, Weijia

    2016-02-01

    A local area temperature monitor is important for precise control of chemical and biological processes in microfluidics. In this work, we developed a facile method to realize micron spatial resolution of temperature mapping in a microfluidic channel quickly and cost effectively. Based on the temperature dependent fluorescence emission of NaYF4:Yb3+, Er3+ upconversion nanoparticles (UCNPs) under near-infrared irradiation, ratio-metric imaging of UCNPs doped polydimethylsiloxane can map detailed temperature distribution in the channel. Unlike some reported strategies that utilize temperature sensitive organic dye (such as Rhodamine) to achieve thermal sensing, our method is highly chemically inert and physically stable without any performance degradation in long term operation. Moreover, this method can be easily scaled up or down, since the spatial and temperature resolution is determined by an optical imaging system. Our method supplied a simple and efficient solution for temperature mapping on a heterogeneous surface where usage of an infrared thermal camera was limited.

  16. Adaptive Registration of Varying Contrast-Weighted Images for Improved Tissue Characterization (ARCTIC): Application to T1 Mapping

    PubMed Central

    Roujol, Sébastien; Foppa, Murilo; Weingartner, Sebastian; Manning, Warren J.; Nezafat, Reza

    2014-01-01

    Purpose To propose and evaluate a novel non-rigid image registration approach for improved myocardial T1 mapping. Methods Myocardial motion is estimated as global affine motion refined by a novel local non-rigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient (DSC) and the myocardial boundary error (MBE) in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion”. Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-non diagnostic/severe motion artifact, 4-excellent/no motion artifact). Results Increased DSC (0.78±0.14 to 0.87±0.03, p<0.001), reduced MBE (1.29±0.72mm to 0.84±0.20mm, p<0.001), improved overall T1 map quality (2.86±1.04 to 3.49±0.77, p<0.001), and reduced T1 map motion artifacts (2.51±0.84 to 3.61±0.64, p<0.001) were obtained after motion correction of “with motion” data (~56% of data). Conclusion The proposed non-rigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. PMID:24798588

  17. Improving parenchyma segmentation by simultaneous estimation of tissue property T1 map and group-wise registration of inversion recovery MR breast images.

    PubMed

    Xing, Ye; Xue, Zhong; Englander, Sarah; Schnall, Mitchell; Shen, Dinggang

    2008-01-01

    The parenchyma tissue in the breast has a strong relation with predictive biomarkers of breast cancer. To better segment parenchyma, we perform segmentation on estimated tissue property T1 map. To improve the estimation of tissue property (T1) which is the basis for parenchyma segmentation, we present an integrated algorithm for simultaneous T1 map estimation, T1 map based parenchyma segmentation and group-wise registration on series of inversion recovery magnetic resonance (MR) breast images. The advantage of using this integrated algorithm is that the simultaneous T1 map estimation (E-step) and group-wise registration (R-step) could benefit each other and jointly improve parenchyma segmentation. In particular, in E-step, T1 map based segmentation could help perform an edge-preserving smoothing on the tentatively estimated noisy T1 map, and could also help provide tissue probability maps to be robustly registered in R-step. Meanwhile, the improved estimation of T1 map could help segment parenchyma in a more accurate way. In R-step, for robust registration, the group-wise registration is performed on the tissue probability maps produced in E-step, rather than the original inversion recovery MR images, since tissue probability maps are the intrinsic tissue property which is invariant to the use of different imaging parameters. The better alignment of images achieved in R-step can help improve T1 map estimation and indirectly the T1 map based parenchyma segmentation. By iteratively performing E-step and R-step, we can simultaneously obtain better results for T1 map estimation, T1 map based segmentation, group-wise registration, and finally parenchyma segmentation.

  18. Combining Anatomical Manifold Information via Diffeomorphic Metric Mappings for Studying Cortical Thinning of the Cingulate Gyrus in Schizophrenia

    PubMed Central

    Qiu, Anqi; Younes, Laurent; Wang, Lei; Ratnanather, J. Tilak; Gillepsie, Sarah K.; Kaplan, Gillian; Csernansky, John; Miller, Michael I.

    2015-01-01

    Spatial normalization is a crucial step in assessing patterns of neuroanatomical structure and function associated with health and disease. Errors that occur during spatial normalization can influence hypothesis testing due to the dimensionalities of mapping algorithms and anatomical manifolds (landmarks, curves, surfaces, volumes) used to drive the mapping algorithms. The primary aim of this paper is to improve statistical inference using multiple anatomical manifolds and Large Deformation Diffeomorphic Metric Mapping (LDDMM) algorithms. We propose that combining information generated by the various manifolds and algorithms improves the reliability of hypothesis testing. We used this unified approach to assess variation in the thickness of the cingulate gyrus in subjects with schizophrenia and healthy comparison subjects. Three different LDDMM algorithms for mapping landmarks, curves and triangulated meshes were used to transform thickness maps of the cingulate surfaces into an atlas coordinate system. We then tested for group differences by combining the information from the three types of anatomical manifolds and LDDMM mapping algorithms. The unified approach provided reliable statistical results and eliminated ambiguous results due to surface mismatches. Subjects with schizophrenia had non-uniform cortical thinning over the left and right cingulate gyri, especially in the anterior portion, as compared to healthy comparison subjects. PMID:17613251

  19. Investigation of boresight offsets and co-registration of HiRISE and CTX imagery for precision Mars topographic mapping

    NASA Astrophysics Data System (ADS)

    Wang, Yiran; Wu, Bo

    2017-05-01

    Images from two sensors, the High-Resolution Imaging Science Experiment (HiRISE) and the Context Camera (CTX), both on board the Mars Reconnaissance Orbiter, were used to generate Digital Elevation Models (DEMs) of the Martian surface. However, the DEMs generated from the images acquired by these two sensors show discrepancies for various reasons, such as variations in the boresight alignment between the two sensors while flying in the complex environment of space. This paper presents a systematic investigation of the discrepancies between the DEMs generated from the HiRISE and CTX images and further the boresight offsets between the HiRISE and CTX sensors. A bundle adjustment approach is presented for the co-registration of HiRISE and CTX images. The experimental analyses were carried out using eight sets of HiRISE and CTX images collected from different regions. The results indicate that the systematic offsets between the DEMs derived from HiRISE and CTX images reach several hundred meters in object space and dozens of pixels in image space along the north-east direction. After co-registration, the offsets were reduced to about 10 m in object space and to sub-pixel level in image space. From the co-registration results, relatively consistent angular boresight offsets were found, which deviated from the default values. The findings are significant for the synergistic use of HiRISE and CTX images for precision Mars topographic mapping.

  20. Feasibility and validation of registration of three-dimensional left atrial models derived from computed tomography with a noncontact cardiac mapping system.

    PubMed

    Sra, Jasbir; Krum, David; Hare, John; Okerlund, Darin; Thompson, Helen; Vass, Melissa; Schweitzer, Jeff; Olson, Eric; Foley, W Dennis; Akhtar, Masood

    2005-01-01

    The purpose of this study was to determine the feasibility and assess the validity of registering three-dimensional (3D) models from computed tomographic (CT) images using a cardiac mapping system. Registration of 3D anatomic models with an interventional system could help identify and navigate mapping and ablation catheters over a complex structure such as the left atrium (LA). ECG-gated, contrast-enhanced cardiac CT imaging was performed in 14 patients with atrial fibrillation. Segmentation was used to create 3D models of the LA. The 3D models were registered with the mapping system using a series of fiducial points. Registration was accomplished retrospectively in the first 10 patients, and catheter navigation was visualized from recorded data. In the final four patients, registration was accomplished in real time during electrophysiologic study. The mapping catheter position, as it was navigated inside the LA, was applied to the registered model in real time. For the validation study, temporary pacing leads were implanted in the LA of 10 dogs. Following this, CT scanning, segmentation, LA model importation, and registration was described previously. After registration, a mapping catheter was positioned at the site of each buried lead according to the registered model with no fluoroscopic guidance. A radiofrequency lesion was created at this location, and the dog was sacrificed, the heart removed and stained, and the distance between the buried lead and the lesion measured. During the feasibility study, the location of the catheter in the registered model correlated with fluoroscopy, angiography, and intracardiac electrograms. LA endocardial potentials during sinus rhythm and any premature atrial contractions also were successfully delineated over the registered models. In the validation study, the mean target registration error was 2.0 +/- 3.6 mm. Registration of CT-derived 3D models of the LA using a cardiac mapping system is feasible and accurate.

  1. Spatial mapping of metals in tissue-sections using combination of mass-spectrometry and histology through image registration

    NASA Astrophysics Data System (ADS)

    Anyz, Jiri; Vyslouzilova, Lenka; Vaculovic, Tomas; Tvrdonova, Michaela; Kanicky, Viktor; Haase, Hajo; Horak, Vratislav; Stepankova, Olga; Heger, Zbynek; Adam, Vojtech

    2017-01-01

    We describe a new procedure for the parallel mapping of selected metals in histologically characterized tissue samples. Mapping is achieved via image registration of digital data obtained from two neighbouring cryosections by scanning the first as a histological sample and subjecting the second to laser ablation inductively coupled plasma mass spectrometry. This computer supported procedure enables determination of the distribution and content of metals of interest directly in the chosen histological zones and represents a substantial improvement over the standard approach, which determines these values in tissue homogenates or whole tissue sections. The potential of the described procedure was demonstrated in a pilot study that analysed Zn and Cu levels in successive development stages of pig melanoma tissue using MeLiM (Melanoma-bearing-Libechov-Minipig) model. We anticipate that the procedure could be useful for a complex understanding of the role that the spatial distribution of metals plays within tissues affected by pathological states including cancer.

  2. Spatial mapping of metals in tissue-sections using combination of mass-spectrometry and histology through image registration

    PubMed Central

    Anyz, Jiri; Vyslouzilova, Lenka; Vaculovic, Tomas; Tvrdonova, Michaela; Kanicky, Viktor; Haase, Hajo; Horak, Vratislav; Stepankova, Olga; Heger, Zbynek; Adam, Vojtech

    2017-01-01

    We describe a new procedure for the parallel mapping of selected metals in histologically characterized tissue samples. Mapping is achieved via image registration of digital data obtained from two neighbouring cryosections by scanning the first as a histological sample and subjecting the second to laser ablation inductively coupled plasma mass spectrometry. This computer supported procedure enables determination of the distribution and content of metals of interest directly in the chosen histological zones and represents a substantial improvement over the standard approach, which determines these values in tissue homogenates or whole tissue sections. The potential of the described procedure was demonstrated in a pilot study that analysed Zn and Cu levels in successive development stages of pig melanoma tissue using MeLiM (Melanoma-bearing-Libechov-Minipig) model. We anticipate that the procedure could be useful for a complex understanding of the role that the spatial distribution of metals plays within tissues affected by pathological states including cancer. PMID:28071735

  3. Group-wise diffeomorphic diffusion tensor image registration.

    PubMed

    Geng, Xiujuan; Gu, Hong; Shin, Wanyong; Ross, Thomas J; Yang, Yihong

    2010-01-01

    We propose an unbiased group-wise diffeomorphic registration technique to normalize a group of diffusion tensor (DT) images. Our method uses an implicit reference group-wise registration framework to avoid bias caused by reference selection. Log-Euclidean metrics on diffusion tensors are used for the tensor interpolation and computation of the similarity cost functions. The overall energy function is constructed by a diffeomorphic demons approach. The tensor reorientation is performed and implicitly optimized during the registration procedure. The performance of the proposed method is compared with reference-based diffusion tensor imaging (DTI) registration methods. The registered DTI images have smaller shape differences in terms of reduced variance of the fractional anisotropy maps and more consistent tensor orientations. We demonstrate that fiber tract atlas construction can benefit from the group-wise registration by producing fiber bundles with higher overlaps.

  4. Quantifying and Mapping Habitat-Based Biodiversity Metrics Within an Ecosystem Services Framework

    EPA Science Inventory

    Ecosystem services have become a key issue of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have become strategic national interests for integrating ecology with econom...

  5. A National Approach for Mapping and Quantifying Habitat-based Biodiversity Metrics Across Multiple Spatial Scales

    EPA Science Inventory

    Ecosystem services, i.e., "services provided to humans from natural systems," have become a key issue of this century in resource management, conservation planning, and environmental decision analysis. Mapping and quantifying ecosystem services have become strategic national inte...

  6. A National Approach to Quantify and Map Biodiversity Conservation Metrics within an Ecosystem Services Framework

    EPA Science Inventory

    Ecosystem services, i.e., "services provided to humans from natural systems," have become a key issue of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have be...

  7. A National Approach to Quantify and Map Biodiversity Conservation Metrics within an Ecosystem Services Framework

    EPA Science Inventory

    Ecosystem services, i.e., "services provided to humans from natural systems," have become a key issue of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have be...

  8. Quantifying and Mapping Habitat-Based Biodiversity Metrics Within an Ecosystem Services Framework

    EPA Science Inventory

    Ecosystem services have become a key issue of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have become strategic national interests for integrating ecology with econom...

  9. A National Approach for Mapping and Quantifying Habitat-based Biodiversity Metrics Across Multiple Spatial Scales

    EPA Science Inventory

    Ecosystem services, i.e., "services provided to humans from natural systems," have become a key issue of this century in resource management, conservation planning, and environmental decision analysis. Mapping and quantifying ecosystem services have become strategic national inte...

  10. Facile and high spatial resolution ratio-metric luminescence thermal mapping in microfluidics by near infrared excited upconversion nanoparticles

    SciTech Connect

    Wang, Yu; Li, Shunbo; Wen, Weijia

    2016-02-01

    A local area temperature monitor is important for precise control of chemical and biological processes in microfluidics. In this work, we developed a facile method to realize micron spatial resolution of temperature mapping in a microfluidic channel quickly and cost effectively. Based on the temperature dependent fluorescence emission of NaYF{sub 4}:Yb{sup 3+}, Er{sup 3+} upconversion nanoparticles (UCNPs) under near-infrared irradiation, ratio-metric imaging of UCNPs doped polydimethylsiloxane can map detailed temperature distribution in the channel. Unlike some reported strategies that utilize temperature sensitive organic dye (such as Rhodamine) to achieve thermal sensing, our method is highly chemically inert and physically stable without any performance degradation in long term operation. Moreover, this method can be easily scaled up or down, since the spatial and temperature resolution is determined by an optical imaging system. Our method supplied a simple and efficient solution for temperature mapping on a heterogeneous surface where usage of an infrared thermal camera was limited.

  11. Correction of B0-Susceptibility Induced Distortion in Diffusion-weighted Images Using Large-Deformation Diffeomorphic Metric Mapping

    PubMed Central

    Huang, Hao; Ceritoglu, Can; Li, Xin; Qiu, Anqi; Miller, Michael I.; van Zijl, Peter C.M.; Mori, Susumu

    2008-01-01

    Geometric distortion caused by B0-inhomogeneity is one of the most important problems for diffusion weighted images (DWI) using single shot, echo planar imaging (SS-EPI). In this study, large-Deformation, Diffeomorphic Metric Mapping (LDDMM) algorithm has been tested for the correction of geometric distortion in diffusion tensor images (DTI). Based on data from nine normal subjects, the amount of distortion caused by B0-susceptibility in the 3T magnet was characterized. The distortion quality was validated by manually placing landmarks in the target and DTI images before and after distortion correction. The distortion was found to be up to 15 millimeters in the population-averaged map and could be more than 20 millimeters in individual images. Both qualitative demonstration and quantitative statistical results suggest that the highly elastic geometric distortion caused by spatial inhomogeneity of the B0 field in DTI using SS-EPI can be effectively corrected by LDDMM. This postprocessing method is especially useful for correcting existent DTI data without phase maps. PMID:18499384

  12. Nonexistence of stable F-stationary maps of a functional related to pullback metrics.

    PubMed

    Li, Jing; Liu, Fang; Zhao, Peibiao

    2017-01-01

    Let [Formula: see text] be a compact convex hypersurface in [Formula: see text]. In this paper, we prove that if the principal curvatures [Formula: see text] of [Formula: see text] satisfy [Formula: see text] and [Formula: see text], then there exists no nonconstant stable F-stationary map between M and a compact Riemannian manifold when (6) or (7) holds.

  13. Selected annotated bibliographies for image mapping : geometric registration, resampling, contrast enhancement, spatial filtering, and color calibration

    USGS Publications Warehouse

    Quirk, B.K.

    1985-01-01

    Many articles have been published in the image processing areas associated with image mapping, but no document has combined these references in a single publication. Image mapping is a new and dynamic field and a baseline document reviewing past research in the image processing areas associated with it needs to be provided. A collection of annotated bibliographies provides a source for that background information.

  14. Registration of a rice gene mapping population of Lemont X Jasmine 85 recombinant inbred lines

    USDA-ARS?s Scientific Manuscript database

    A mapping population developed from a cross of rice (Oryza sativa L.) tropical japonica cultivar ‘Lemont’ and indica cultivar ‘Jasmine 85’ was developed to facilitate genetic studies for important agronomic traits. The indica- and japonica-based rice recombinant inbred line (RIL) mapping population ...

  15. Registration of the Ki14 × B73 recombinant inbred mapping population of maize

    USDA-ARS?s Scientific Manuscript database

    The Ohio Agricultural Research and Development Center released Ki14 × B73 (KB) maize (Zea mays L.) mapping population, a set of 119 recombinant inbred lines (RILs), in March 2007. The mapping population was derived from a biparental cross between inbreds Ki14 (NCRPIS accession Ames 27259) and B73 (...

  16. Definition of the metric on the space clos{sub ∅}(X) of closed subsets of a metric space X and properties of mappings with values in clos{sub ∅}(R{sup n})

    SciTech Connect

    Zhukovskii, E S; Panasenko, E A

    2014-09-30

    The paper is concerned with the extension of tests for superpositional measurability, Filippov's implicit function lemma and the Scorza Dragoni property to set-valued (and, as a corollary, to single-valued) mappings that fail to satisfy the Carathéodory conditions (the upper Carathéodory conditions) and are not continuous (upper semicontinuous) in the phase variable. The corresponding results depend on the introduction of the space clos{sub ∅}(X) of all closed subsets (including the empty set) of an arbitrary metric space X; a metric on clos{sub ∅}(X) is proposed; the space clos{sub ∅}(X) is shown to be complete whenever the original space X is; a criterion for convergence of a sequence is put forward; mappings with values in clos{sub ∅}(X) are studied. Some results on set-valued mappings satisfying the Carathéodory conditions and having compact values in R{sup n} are shown to hold for mappings with values in clos{sub ∅}(R{sup n}), measurable in the first argument, and continuous in the proposed metric in the second argument. Bibliography: 22 titles.

  17. Mapping the functional connectome in traumatic brain injury: What can graph metrics tell us?

    PubMed

    Caeyenberghs, Karen; Verhelst, Helena; Clemente, Adam; Wilson, Peter H

    2016-12-03

    Traumatic brain injury (TBI) is associated with cognitive and motor deficits, and poses a significant personal, societal, and economic burden. One mechanism by which TBI is thought to affect cognition and behavior is through changes in functional connectivity. Graph theory is a powerful framework for quantifying topological features of neuroimaging-derived functional networks. The objective of this paper is to review studies examining functional connectivity in TBI with an emphasis on graph theoretical analysis that is proving to be valuable in uncovering network abnormalities in this condition. We review studies that have examined TBI-related alterations in different properties of the functional brain network, including global integration, segregation, centrality and resilience. We focus on functional data using task-related fMRI or resting-state fMRI in patients with TBI of different severity and recovery phase, and consider how graph metrics may inform rehabilitation and enhance efficacy. Moreover, we outline some methodological challenges associated with the examination of functional connectivity in patients with brain injury, including the sample size, parcellation scheme used, node definition and subgroup analyses. The findings suggest that TBI is associated with hyperconnectivity and a suboptimal global integration, characterized by increased connectivity degree and strength and reduced efficiency of functional networks. This altered functional connectivity, also evident in other clinical populations, is attributable to diffuse white matter pathology and reductions in gray and white matter volume. These functional alterations are implicated in post-concussional symptoms, posttraumatic stress and neurocognitive dysfunction after TBI. Finally, the effects of focal lesions have been found to depend critically on topological position and their role in the network. Graph theory is a unique and powerful tool for exploring functional connectivity in brain

  18. Combined lineage mapping and gene expression profiling of embryonic brain patterning using ultrashort pulse microscopy and image registration

    NASA Astrophysics Data System (ADS)

    Gibbs, Holly C.; Dodson, Colin R.; Bai, Yuqiang; Lekven, Arne C.; Yeh, Alvin T.

    2014-12-01

    During embryogenesis, presumptive brain compartments are patterned by dynamic networks of gene expression. The spatiotemporal dynamics of these networks, however, have not been characterized with sufficient resolution for us to understand the regulatory logic resulting in morphogenetic cellular behaviors that give the brain its shape. We have developed a new, integrated approach using ultrashort pulse microscopy [a high-resolution, two-photon fluorescence (2PF)-optical coherence microscopy (OCM) platform using 10-fs pulses] and image registration to study brain patterning and morphogenesis in zebrafish embryos. As a demonstration, we used time-lapse 2PF to capture midbrain-hindbrain boundary morphogenesis and a wnt1 lineage map from embryos during brain segmentation. We then performed in situ hybridization to deposit NBT/BCIP, where wnt1 remained actively expressed, and reimaged the embryos with combined 2PF-OCM. When we merged these datasets using morphological landmark registration, we found that the mechanism of boundary formation differs along the dorsoventral axis. Dorsally, boundary sharpening is dominated by changes in gene expression, while ventrally, sharpening may be accomplished by lineage sorting. We conclude that the integrated visualization of lineage reporter and gene expression domains simultaneously with brain morphology will be useful for understanding how changes in gene expression give rise to proper brain compartmentalization and structure.

  19. Registration of the KS4895 x Jackson mapping population (AR93705)

    USDA-ARS?s Scientific Manuscript database

    AR93705 (Reg. no. MP-_, NSL ______) is a soybean [Glycine max (L.) Merr.] mapping population developed by the University of Arkansas Experiment Station. The population consists of 15 F3- and 76 F5-derived recombinant inbred lines (RILs) from a cross between KS4895 (PI595081) and Jackson (PI548657). ...

  20. Registration of the MN98550/MN99394 Wheat Recombinant Inbred Mapping Population

    USDA-ARS?s Scientific Manuscript database

    A mapping population was developed from the two hard red spring wheat (Triticum aestivum L.) breeding lines MN98550 and MN99394 at the University of Minnesota. This population has 139 F6:8 recombinant inbred lines (RILs) and was assigned the USDA-ARS Germplasm Resources Information Network (GRIN) ac...

  1. Registration of USG 3209/Jaypee Wheat Recombinant Inbred Line Mapping Population

    USDA-ARS?s Scientific Manuscript database

    ‘USG 3209’/‘Jaypee’ (Reg. No. MP-3, NSL 465777 MAP), is a soft red winter wheat (Triticum aestivum L.) recombinant inbred line (RIL) population developed by Virginia Polytechnic Institute and State University and submitted to the USDA–ARS National Small Grains Germplasm Research Facility in Aberdeen...

  2. Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation

    PubMed Central

    2012-01-01

    The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models. Where risks are heterogeneous across population groups or space or dependent on transmission between individuals, spatial data on human population distributions and demographic structures are required to estimate infectious disease risks, burdens, and dynamics. The disease impact in terms of morbidity, mortality, and speed of spread varies substantially with demographic profiles, so that identifying the most exposed or affected populations becomes a key aspect of planning and targeting interventions. Subnational breakdowns of population counts by age and sex are routinely collected during national censuses and maintained in finer detail within microcensus data. Moreover, demographic and health surveys continue to collect representative and contemporary samples from clusters of communities in low-income countries where census data may be less detailed and not collected regularly. Together, these freely available datasets form a rich resource for quantifying and understanding the spatial variations in the sizes and distributions of those most at risk of disease in low income regions, yet at present, they remain unconnected data scattered across national statistical offices and websites. In this paper we discuss the deficiencies of existing spatial population datasets

  3. Automatic Registration of Scanned Satellite Imagery with a Digital Map Data Base.

    DTIC Science & Technology

    1980-11-01

    believe that it makes sense to support human analysis of digital ima- ges by automation and to incorporate an available map into this process. There...of reseau points (ROOS, 1975). The associative, complex mental interpretation of an ima- ge by the human expert will hardly ever be matched by the...by a human interpreter. A topological data structure will thus be required. It is straight-forward to define a set of functions to be satis- fied by

  4. Diffeomorphic registration using geodesic shooting and Gauss–Newton optimisation

    PubMed Central

    Ashburner, John; Friston, Karl J.

    2011-01-01

    This paper presents a nonlinear image registration algorithm based on the setting of Large Deformation Diffeomorphic Metric Mapping (LDDMM), but with a more efficient optimisation scheme — both in terms of memory required and the number of iterations required to reach convergence. Rather than perform a variational optimisation on a series of velocity fields, the algorithm is formulated to use a geodesic shooting procedure, so that only an initial velocity is estimated. A Gauss–Newton optimisation strategy is used to achieve faster convergence. The algorithm was evaluated using freely available manually labelled datasets, and found to compare favourably with other inter-subject registration algorithms evaluated using the same data. PMID:21216294

  5. FreeSurfer-Initiated Fully-Automated Subcortical Brain Segmentation in MRI Using Large Deformation Diffeomorphic Metric Mapping

    PubMed Central

    Khan, Ali R.; Wang, Lei

    2010-01-01

    Fully-automated brain segmentation methods have not been widely adopted for clinical use because of issues related to reliability, accuracy, and limitations of delineation protocol. By combining the probabilistic-based FreeSurfer (FS) method with the Large Deformation Diffeomorphic Metric Mapping (LDDMM) based label propagation method, we are able to increase reliability and accuracy, and allow for flexibility in template choice. Our method uses the automated FreeSurfer subcortical labeling to provide a coarse to fine introduction of information in the LDDMM template-based segmentation resulting in a fully-automated subcortical brain segmentation method (FS+LDDMM). One major advantage of the FS+LDDMM-based approach is that the automatically generated segmentations generated are inherently smooth, thus subsequent steps in shape analysis can directly follow without manual post-processing or loss of detail. We have evaluated our new FS+LDDMM method on several databases containing a total of 50 subjects with different pathologies, scan sequences and manual delineation protocols for labeling the basal ganglia, thalamus, and hippocampus. In healthy controls we report Dice overlap measures of 0.81, 0.83, 0.74, 0.86 and 0.75 for the right caudate nucleus, putamen, pallidum, thalamus and hippocampus respectively. We also find statistically significant improvement of accuracy in FS+LDDMM over FreeSurfer for the caudate nucleus and putamen of Huntington’s disease and Tourette’s syndrome subjects, and the right hippocampus of Schizophrenia subjects. PMID:18455931

  6. An augmented parametric response map with consideration of image registration error: towards guidance of locally adaptive radiotherapy

    NASA Astrophysics Data System (ADS)

    Lausch, Anthony; Chen, Jeff; Ward, Aaron D.; Gaede, Stewart; Lee, Ting-Yim; Wong, Eugene

    2014-11-01

    Parametric response map (PRM) analysis is a voxel-wise technique for predicting overall treatment outcome, which shows promise as a tool for guiding personalized locally adaptive radiotherapy (RT). However, image registration error (IRE) introduces uncertainty into this analysis which may limit its use for guiding RT. Here we extend the PRM method to include an IRE-related PRM analysis confidence interval and also incorporate multiple graded classification thresholds to facilitate visualization. A Gaussian IRE model was used to compute an expected value and confidence interval for PRM analysis. The augmented PRM (A-PRM) was evaluated using CT-perfusion functional image data from patients treated with RT for glioma and hepatocellular carcinoma. Known rigid IREs were simulated by applying one thousand different rigid transformations to each image set. PRM and A-PRM analyses of the transformed images were then compared to analyses of the original images (ground truth) in order to investigate the two methods in the presence of controlled IRE. The A-PRM was shown to help visualize and quantify IRE-related analysis uncertainty. The use of multiple graded classification thresholds also provided additional contextual information which could be useful for visually identifying adaptive RT targets (e.g. sub-volume boosts). The A-PRM should facilitate reliable PRM guided adaptive RT by allowing the user to identify if a patient’s unique IRE-related PRM analysis uncertainty has the potential to influence target delineation.

  7. Advanced Tie Feature Matching for the Registration of Mobile Mapping Imaging Data and Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Jende, P.; Peter, M.; Gerke, M.; Vosselman, G.

    2016-06-01

    Mobile Mapping's ability to acquire high-resolution ground data is opposing unreliable localisation capabilities of satellite-based positioning systems in urban areas. Buildings shape canyons impeding a direct line-of-sight to navigation satellites resulting in a deficiency to accurately estimate the mobile platform's position. Consequently, acquired data products' positioning quality is considerably diminished. This issue has been widely addressed in the literature and research projects. However, a consistent compliance of sub-decimetre accuracy as well as a correction of errors in height remain unsolved. We propose a novel approach to enhance Mobile Mapping (MM) image orientation based on the utilisation of highly accurate orientation parameters derived from aerial imagery. In addition to that, the diminished exterior orientation parameters of the MM platform will be utilised as they enable the application of accurate matching techniques needed to derive reliable tie information. This tie information will then be used within an adjustment solution to correct affected MM data. This paper presents an advanced feature matching procedure as a prerequisite to the aforementioned orientation update. MM data is ortho-projected to gain a higher resemblance to aerial nadir data simplifying the images' geometry for matching. By utilising MM exterior orientation parameters, search windows may be used in conjunction with a selective keypoint detection and template matching. Originating from different sensor systems, however, difficulties arise with respect to changes in illumination, radiometry and a different original perspective. To respond to these challenges for feature detection, the procedure relies on detecting keypoints in only one image. Initial tests indicate a considerable improvement in comparison to classic detector/descriptor approaches in this particular matching scenario. This method leads to a significant reduction of outliers due to the limited availability

  8. The EnviroAtlas ‐ Developing a National Approach to Quantify and Map Metrics within an Ecosystem Services Framework. Subfocus: Multi‐scale Biodiversity Conservation Metrics

    EPA Science Inventory

    Ecosystem services, i.e., "services provided to humans from natural systems," have become a key issue of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have become stra...

  9. The EnviroAtlas ‐ Developing a National Approach to Quantify and Map Metrics within an Ecosystem Services Framework. Subfocus: Multi‐scale Biodiversity Conservation Metrics

    EPA Science Inventory

    Ecosystem services, i.e., "services provided to humans from natural systems," have become a key issue of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have become stra...

  10. The Insight ToolKit image registration framework

    PubMed Central

    Avants, Brian B.; Tustison, Nicholas J.; Stauffer, Michael; Song, Gang; Wu, Baohua; Gee, James C.

    2014-01-01

    Publicly available scientific resources help establish evaluation standards, provide a platform for teaching and improve reproducibility. Version 4 of the Insight ToolKit (ITK4) seeks to establish new standards in publicly available image registration methodology. ITK4 makes several advances in comparison to previous versions of ITK. ITK4 supports both multivariate images and objective functions; it also unifies high-dimensional (deformation field) and low-dimensional (affine) transformations with metrics that are reusable across transform types and with composite transforms that allow arbitrary series of geometric mappings to be chained together seamlessly. Metrics and optimizers take advantage of multi-core resources, when available. Furthermore, ITK4 reduces the parameter optimization burden via principled heuristics that automatically set scaling across disparate parameter types (rotations vs. translations). A related approach also constrains steps sizes for gradient-based optimizers. The result is that tuning for different metrics and/or image pairs is rarely necessary allowing the researcher to more easily focus on design/comparison of registration strategies. In total, the ITK4 contribution is intended as a structure to support reproducible research practices, will provide a more extensive foundation against which to evaluate new work in image registration and also enable application level programmers a broad suite of tools on which to build. Finally, we contextualize this work with a reference registration evaluation study with application to pediatric brain labeling.1 PMID:24817849

  11. Metric Madness

    ERIC Educational Resources Information Center

    Kroon, Cindy D.

    2007-01-01

    Created for a Metric Day activity, Metric Madness is a board game for two to four players. Students review and practice metric vocabulary, measurement, and calculations by playing the game. Playing time is approximately twenty to thirty minutes.

  12. Semi-automated registration-based anatomical labelling, voxel based morphometry and cortical thickness mapping of the mouse brain.

    PubMed

    Pagani, Marco; Damiano, Mario; Galbusera, Alberto; Tsaftaris, Sotirios A; Gozzi, Alessandro

    2016-07-15

    Morphoanatomical MRI methods have recently begun to be applied in the mouse. However, substantial differences in the anatomical organisation of human and rodent brain prevent a straightforward extension of clinical neuroimaging tools to mouse brain imaging. As a result, the vast majority of the published approaches rely on tailored routines that address single morphoanatomical readouts and typically lack a sufficiently-detailed description of the complex workflow required to process images and quantify structural alterations. Here we provide a detailed description of semi-automated registration-based procedures for voxel based morphometry, cortical thickness estimation and automated anatomical labelling of the mouse brain. The approach relies on the sequential use of advanced image processing tools offered by ANTs, a flexible open source toolkit freely available to the scientific community. To illustrate our procedures, we described their application to quantify morphological alterations in socially-impaired BTBR mice with respect to normosocial C57BL/6J controls, a comparison recently described by us and other research groups. We show that the approach can reliably detect both focal and large-scale grey matter alterations using complementary readouts. No detailed operational workflows for mouse imaging are available for direct comparison with our methods. However, empirical assessment of the mapped inter-strain differences is in good agreement with the findings of other groups using analogous approaches. The detailed operational workflows described here are expected to help the implementation of rodent morphoanatomical methods by non-expert users, and ultimately promote the use of these tools across the preclinical neuroimaging community. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Non-rigid image registration under non-deterministic deformation bounds

    NASA Astrophysics Data System (ADS)

    Ge, Qian; Lokare, Namita; Lobaton, Edgar

    2015-01-01

    Image registration aims to identify the mapping between corresponding locations in an anatomic structure. Most traditional approaches solve this problem by minimizing some error metric. However, they do not quantify the uncertainty behind their estimates and the feasibility of other solutions. In this work, it is assumed that two images of the same anatomic structure are related via a Lipschitz non-rigid deformation (the registration map). An approach for identifying point correspondences with zero false-negative rate and high precision is introduced under this assumption. This methodology is then extended to registration of regions in an image which is posed as a graph matching problem with geometric constraints. The outcome of this approach is a homeomorphism with uncertainty bounds characterizing its accuracy over the entire image domain. The method is tested by applying deformation maps to the LPBA40 dataset.

  14. Quicksilver: Fast predictive image registration - A deep learning approach.

    PubMed

    Yang, Xiao; Kwitt, Roland; Styner, Martin; Niethammer, Marc

    2017-07-11

    This paper introduces Quicksilver, a fast deformable image registration method. Quicksilver registration for image-pairs works by patch-wise prediction of a deformation model based directly on image appearance. A deep encoder-decoder network is used as the prediction model. While the prediction strategy is general, we focus on predictions for the Large Deformation Diffeomorphic Metric Mapping (LDDMM) model. Specifically, we predict the momentum-parameterization of LDDMM, which facilitates a patch-wise prediction strategy while maintaining the theoretical properties of LDDMM, such as guaranteed diffeomorphic mappings for sufficiently strong regularization. We also provide a probabilistic version of our prediction network which can be sampled during the testing time to calculate uncertainties in the predicted deformations. Finally, we introduce a new correction network which greatly increases the prediction accuracy of an already existing prediction network. We show experimental results for uni-modal atlas-to-image as well as uni-/multi-modal image-to-image registrations. These experiments demonstrate that our method accurately predicts registrations obtained by numerical optimization, is very fast, achieves state-of-the-art registration results on four standard validation datasets, and can jointly learn an image similarity measure. Quicksilver is freely available as an open-source software. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Rectification and Registration of Remotely Sensed Data.

    DTIC Science & Technology

    2014-09-26

    intelligence Image registration Resampling Mapping Change detection Geometrical distortions Multisensor Signal processing Synthetic aperture radar...rectification and registration of images generated by onboard sensors. Accurate registration is a key requirement for detecting changes (in position...or "unwarping" of the image data before registration and information extraction, in the form of geometric and radiometric corrections and data

  16. SU-E-J-113: Effects of Deformable Registration On First-Order Texture Maps Calculated From Thoracic Lung CT Scans

    SciTech Connect

    Smith, C; Cunliffe, A; Al-Hallaq, H; Armato, S

    2015-06-15

    Purpose: To determine the stability of eight first-order texture features following the deformable registration of serial computed tomography (CT) scans. Methods: CT scans at two different time points from 10 patients deemed to have no lung abnormalities by a radiologist were collected. Following lung segmentation using an in-house program, texture maps were calculated from 32×32-pixel regions of interest centered at every pixel in the lungs. The texture feature value of the ROI was assigned to the center pixel of the ROI in the corresponding location of the texture map. Pixels in the square ROI not contained within the segmented lung were not included in the calculation. To quantify the agreement between ROI texture features in corresponding pixels of the baseline and follow-up texture maps, the Fraunhofer MEVIS EMPIRE10 deformable registration algorithm was used to register the baseline and follow-up scans. Bland-Altman analysis was used to compare registered scan pairs by computing normalized bias (nBias), defined as the feature value change normalized to the mean feature value, and normalized range of agreement (nRoA), defined as the range spanned by the 95% limits of agreement normalized to the mean feature value. Results: Each patient’s scans contained between 6.8–15.4 million ROIs. All of the first-order features investigated were found to have an nBias value less than 0.04% and an nRoA less than 19%, indicating that the variability introduced by deformable registration was low. Conclusion: The eight first-order features investigated were found to be registration stable. Changes in CT texture maps could allow for temporal-spatial evaluation of the evolution of lung abnormalities relating to a variety of diseases on a patient-by-patient basis. SGA and HA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology. Research reported in this publication was supported by the National Institute Of General

  17. Yield Mapping for Different Crops in Sudano-Sahelian Smallholder Farming Systems: Results Based on Metric Worldview and Decametric SPOT-5 Take5 Time Series

    NASA Astrophysics Data System (ADS)

    Blaes, X.; Lambert, M.-J.; Chome, G.; Traore, P. S.; de By, R. A.; Defourny, P.

    2016-08-01

    Efficient yield mapping in Sudano-Sahelian Africa, characterized by a very heterogeneous landscape, is crucial to help ensure food security and decrease smallholder farmers' vulnerability. Thanks to an unprecedented in-situ data and HR and VHR remote sensing time series collected in the Koutiala district (in south-eastern Mali), the yield and some key factors of yield estimation were estimated. A crop-specific biomass map was derived with a mean absolute error of 20% using metric WorldView and 25% using decametric SPOT-5 TAKE5 image time series. The very high intra- and inter-field heterogeneity was captured efficiently. The presence of trees in the fields led to a general overestimation of yields, while the mixed pixels at the field borders introduced noise in the biomass predictions.

  18. Color Metric.

    ERIC Educational Resources Information Center

    Illinois State Office of Education, Springfield.

    This booklet was designed to convey metric information in pictoral form. The use of pictures in the coloring book enables the more mature person to grasp the metric message instantly, whereas the younger person, while coloring the picture, will be exposed to the metric information long enough to make the proper associations. Sheets of the booklet…

  19. Color Metric.

    ERIC Educational Resources Information Center

    Illinois State Office of Education, Springfield.

    This booklet was designed to convey metric information in pictoral form. The use of pictures in the coloring book enables the more mature person to grasp the metric message instantly, whereas the younger person, while coloring the picture, will be exposed to the metric information long enough to make the proper associations. Sheets of the booklet…

  20. Automated landmark-guided deformable image registration.

    PubMed

    Kearney, Vasant; Chen, Susie; Gu, Xuejun; Chiu, Tsuicheng; Liu, Honghuan; Jiang, Lan; Wang, Jing; Yordy, John; Nedzi, Lucien; Mao, Weihua

    2015-01-07

    The purpose of this work is to develop an automated landmark-guided deformable image registration (LDIR) algorithm between the planning CT and daily cone-beam CT (CBCT) with low image quality. This method uses an automated landmark generation algorithm in conjunction with a local small volume gradient matching search engine to map corresponding landmarks between the CBCT and the planning CT. The landmarks act as stabilizing control points in the following Demons deformable image registration. LDIR is implemented on graphics processing units (GPUs) for parallel computation to achieve ultra fast calculation. The accuracy of the LDIR algorithm has been evaluated on a synthetic case in the presence of different noise levels and data of six head and neck cancer patients. The results indicate that LDIR performed better than rigid registration, Demons, and intensity corrected Demons for all similarity metrics used. In conclusion, LDIR achieves high accuracy in the presence of multimodality intensity mismatch and CBCT noise contamination, while simultaneously preserving high computational efficiency.

  1. Automated landmark-guided deformable image registration

    NASA Astrophysics Data System (ADS)

    Kearney, Vasant; Chen, Susie; Gu, Xuejun; Chiu, Tsuicheng; Liu, Honghuan; Jiang, Lan; Wang, Jing; Yordy, John; Nedzi, Lucien; Mao, Weihua

    2015-01-01

    The purpose of this work is to develop an automated landmark-guided deformable image registration (LDIR) algorithm between the planning CT and daily cone-beam CT (CBCT) with low image quality. This method uses an automated landmark generation algorithm in conjunction with a local small volume gradient matching search engine to map corresponding landmarks between the CBCT and the planning CT. The landmarks act as stabilizing control points in the following Demons deformable image registration. LDIR is implemented on graphics processing units (GPUs) for parallel computation to achieve ultra fast calculation. The accuracy of the LDIR algorithm has been evaluated on a synthetic case in the presence of different noise levels and data of six head and neck cancer patients. The results indicate that LDIR performed better than rigid registration, Demons, and intensity corrected Demons for all similarity metrics used. In conclusion, LDIR achieves high accuracy in the presence of multimodality intensity mismatch and CBCT noise contamination, while simultaneously preserving high computational efficiency.

  2. Registration of Magnetic Resonance Image Series for Knee Articular Cartilage Analysis

    PubMed Central

    Urish, Kenneth L.; Williams, Ashley A.; Durkin, John R.

    2013-01-01

    Objective: Although conventional radiography is used to assess osteoarthritis in a clinical setting, it has limitations, including an inability to stage early cartilage degeneration. There is a growing interest in using quantitative magnetic resonance imaging to identify degenerative changes in articular cartilage, including the large multicentered study, the Osteoarthritis Initiative (OAI). There is a demand for suitable image registration and segmentation software to complete this analysis. The objective of this study was to develop and validate the open source software, ImageK, that registers 3 T MRI T2 mapping and double echo steady state (DESS) knee MRI sequences acquired in the OAI protocol. Methods: A C++ library, the insight toolkit, was used to develop open source software to register DESS and T2 mapping image MRI sequences using Mattes’s Multimodality Mutual information metric. Results: Registration was assessed using three separate methods. A checkerboard layout demonstrated acceptable visual alignment. Fiducial markers placed in cadaveric knees measured a registration error of 0.85 voxels. Measuring the local variation in Mattes’s Mutual Information metric in the local area of the registered solution showed precision within 1 pixel. In this group, the registered solution required a transform of 56 voxels in translation and 1 degree of rotation. Conclusion: The software we have developed, ImageK, provides free, open source image analysis software that registers DESS and T2 mapping sequences of knee articular cartilage within 1 voxel accuracy. This image registration software facilitates quantitative MRI analyses of knee articular cartilage. PMID:23997865

  3. Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: Application to normal elderly and Alzheimer’s disease participants

    PubMed Central

    Oishi, Kenichi; Faria, Andreia; Jiang, Hangyi; Li, Xin; Akhter, Kazi; Zhang, Jiangyang; Hsu, John T.; Miller, Michael I.; van Zijl, Peter C.M.; Albert, Marilyn; Lyketsos, Constantine G.; Woods, Roger; Toga, Arthur W.; Pike, G. Bruce; Rosa-Neto, Pedro; Evans, Alan; Mazziotta, John; Mori, Susumu

    2010-01-01

    The purpose of this paper is to establish single-participant white matter atlases based on diffusion tensor imaging. As one of the applications of the atlas, automated brain segmentation was performed and the accuracy was measured using Large Deformation Diffeomorphic Metric Mapping (LDDMM). High-quality diffusion tensor imaging (DTI) data from a single-participant were B0-distortion-corrected and transformed to the ICBM-152 atlas or to Talairach coordinates. The deep white matter structures, which have been previously well documented and clearly identified by DTI, were manually segmented. The superficial white matter areas beneath the cortex were defined, based on a population-averaged white matter probability map. The white matter was parcellated into 176 regions based on the anatomical labeling in the ICBM-DTI-81 atlas. The automated parcellation was achieved by warping this parcellation map to normal controls and to Alzheimer’s disease patients with severe anatomical atrophy. The parcellation accuracy was measured by a kappa analysis between the automated and manual parcellation at 11 anatomical regions. The kappa values were 0.70 for both normal controls and patients while the inter-rater reproducibility was 0.81 (controls) and 0.82 (patients), suggesting “almost perfect” agreement. A power analysis suggested that the proposed method is suitable for detecting FA and size abnormalities of the white matter in clinical studies. PMID:19385016

  4. Registration of a rice gene-mapping population consisting of 'TeQing'-into-'Lemont' backcross introgression lines

    USDA-ARS?s Scientific Manuscript database

    A new rice (Oryza sativa L.) mapping population consisting of 123 'TeQing'-into-'Lemont' backcross introgression lines (TILs) (Reg. No. MP-5, NSL 477436 MAP) was developed by the USDA-ARS Rice Research Unit at the Texas A&M University System AgriLife Research and Extension Center at Beaumont, TX, in...

  5. Temporal Subtraction of Serial CT Images with Large Deformation Diffeomorphic Metric Mapping in the Identification of Bone Metastases.

    PubMed

    Sakamoto, Ryo; Yakami, Masahiro; Fujimoto, Koji; Nakagomi, Keita; Kubo, Takeshi; Emoto, Yutaka; Akasaka, Thai; Aoyama, Gakuto; Yamamoto, Hiroyuki; Miller, Michael I; Mori, Susumu; Togashi, Kaori

    2017-07-03

    Purpose To determine the improvement of radiologist efficiency and performance in the detection of bone metastases at serial follow-up computed tomography (CT) by using a temporal subtraction (TS) technique based on an advanced nonrigid image registration algorithm. Materials and Methods This retrospective study was approved by the institutional review board, and informed consent was waived. CT image pairs (previous and current scans of the torso) in 60 patients with cancer (primary lesion location: prostate, n = 14; breast, n = 16; lung, n = 20; liver, n = 10) were included. These consisted of 30 positive cases with a total of 65 bone metastases depicted only on current images and confirmed by two radiologists who had access to additional imaging examinations and clinical courses and 30 matched negative control cases (no bone metastases). Previous CT images were semiautomatically registered to current CT images by the algorithm, and TS images were created. Seven radiologists independently interpreted CT image pairs to identify newly developed bone metastases without and with TS images with an interval of at least 30 days. Jackknife free-response receiver operating characteristics (JAFROC) analysis was conducted to assess observer performance. Reading time was recorded, and usefulness was evaluated with subjective scores of 1-5, with 5 being extremely useful and 1 being useless. Significance of these values was tested with the Wilcoxon signed-rank test. Results The subtraction images depicted various types of bone metastases (osteolytic, n = 28; osteoblastic, n = 26; mixed osteolytic and blastic, n = 11) as temporal changes. The average reading time was significantly reduced (384.3 vs 286.8 seconds; Wilcoxon signed rank test, P = .028). The average figure-of-merit value increased from 0.758 to 0.835; however, this difference was not significant (JAFROC analysis, P = .092). The subjective usefulness survey response showed a median score of 5 for use of the technique

  6. User Registration in EOSDIS

    NASA Astrophysics Data System (ADS)

    Murphy, K. J.; Mitchell, A. E.

    2009-12-01

    Throughout the lifetime of EOSDIS the topic of user registration has received varied attention. Initially, for example, users ordering data from the Earth Science Data Gateway were required to register for delivery of media orders, to check order status and save profile information for future interactions. As EOSDIS embraced evolution of its data systems, the mostly centralized search and order system was replaced with a more diverse set of interfaces allowing (mostly) anonymous online access to data, tools and services. The changes to EOSDIS were embraced by users but the anonymous nature of the interaction made it more difficult to characterize users, capture metrics and provide customized services that benefit users. Additionally, new tools and interfaces have been developed without a centralized registration system. Currently a patchwork of independent registration systems exists throughout EOSDIS for ordering data and interacting with online tools and services. Each requires a separate username and password that must be managed by users. A consolidation of registration systems presents an opportunity to improve not only the user experience through tool customization and simplification of password management, but the understanding of users. This work discusses the options for implementing a common user registration for the EOSDIS, anticipated benefits and pitfalls.

  7. Fully Automatic Feature-Based Registration of Mobile Mapping and Aerial Nadir Images for Enabling the Adjustment of Mobile Platform Locations in Gnss-Denied Urban Environments

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

    Mobile Mapping (MM) has gained significant importance in the realm of high-resolution data acquisition techniques. MM is able to record georeferenced street-level data in a continuous (laser scanners) and/or discrete (cameras) fashion. MM's georeferencing relies on a conjunction of Global Navigation Satellite Systems (GNSS), Inertial Measurement Units (IMU) and optionally on odometry sensors. While this technique does not pose a problem for absolute positioning in open areas, its reliability and accuracy may be diminished in urban areas where high-rise buildings and other tall objects can obstruct the direct line-of-sight between the satellite and the receiver unit. Consequently, multipath measurements or complete signal outages impede the MM platform's localisation and may affect the accurate georeferencing of collected data. This paper presents a technique to recover correct orientation parameters for MM imaging platforms by utilising aerial images as an external georeferencing source. This is achieved by a fully automatic registration strategy which takes into account the overall differences between aerial and MM data, such as scale, illumination, perspective and content. Based on these correspondences, MM data can be verified and/or corrected by using an adjustment solution. The registration strategy is discussed and results in a success rate of about 95 %.

  8. Forensic Metrics

    ERIC Educational Resources Information Center

    Bort, Nancy

    2005-01-01

    One of the most important review topics the author teaches in middle school is the use of metric measurement for problem solving and inquiry. For many years, she had students measuring various objects around the room using the tools of metric measurement. She dutifully taught hypothesizing, data collecting, and drawing conclusions. It was…

  9. Primary Metrics.

    ERIC Educational Resources Information Center

    Otto, Karen; And Others

    These 55 activity cards were created to help teachers implement a unit on metric measurement. They were designed for students aged 5 to 10, but could be used with older students. Cards are color-coded in terms of activities on basic metric terms, prefixes, length, and other measures. Both individual and small-group games and ideas are included.…

  10. Mastering Metrics

    ERIC Educational Resources Information Center

    Parrot, Annette M.

    2005-01-01

    By the time students reach a middle school science course, they are expected to make measurements using the metric system. However, most are not practiced in its use, as their experience in metrics is often limited to one unit they were taught in elementary school. This lack of knowledge is not wholly the fault of formal education. Although the…

  11. Mastering Metrics

    ERIC Educational Resources Information Center

    Parrot, Annette M.

    2005-01-01

    By the time students reach a middle school science course, they are expected to make measurements using the metric system. However, most are not practiced in its use, as their experience in metrics is often limited to one unit they were taught in elementary school. This lack of knowledge is not wholly the fault of formal education. Although the…

  12. Forensic Metrics

    ERIC Educational Resources Information Center

    Bort, Nancy

    2005-01-01

    One of the most important review topics the author teaches in middle school is the use of metric measurement for problem solving and inquiry. For many years, she had students measuring various objects around the room using the tools of metric measurement. She dutifully taught hypothesizing, data collecting, and drawing conclusions. It was…

  13. Lessons Learned From Large-Scale Evapotranspiration and Root Zone Soil Moisture Mapping Using Ground Measurements (meteorological, LAS, EC) and Remote Sensing (METRIC)

    NASA Astrophysics Data System (ADS)

    Hendrickx, J. M. H.; Allen, R. G.; Myint, S. W.; Ogden, F. L.

    2015-12-01

    Large scale mapping of evapotranspiration and root zone soil moisture is only possible when satellite images are used. The spatial resolution of this imagery typically depends on its temporal resolution or the satellite overpass time. For example, the Landsat satellite acquires images at 30 m resolution every 16 days while the MODIS satellite acquires images at 250 m resolution every day. In this study we deal with optical/thermal imagery that is impacted by cloudiness contrary to radar imagery that penetrates through clouds. Due to cloudiness, the temporal resolution of Landsat drops from 16 days to about one clear sky Landsat image per month in the southwestern USA and about one every ten years in the humid tropics of Panama. Only by launching additional satellites can the temporal resolution be improved. Since this is too costly, an alternative is found by using ground measurements with high temporal resolution (from minutes to days) but poor spatial resolution. The challenge for large-scale evapotranspiration and root zone soil moisture mapping is to construct a layer stack consisting of N time layers covering the period of interest each containing M pixels covering the region of interest. We will present examples of the Phoenix Active Management Area in AZ (14,600 km2), Green River Basin in WY (44,000 km2), the Kishwaukee Watershed in IL (3,150 km2), the area covered by Landsat Path 28/Row 35 in OK (30,000 km2) and the Agua Salud Watershed in Panama (200 km2). In these regions we used Landsat or MODIS imagery for mapping evapotranspiration and root zone soil moisture by the algorithm Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) together with meteorological measurements and sometimes either Large Aperture Scintillometers (LAS) or Eddy Covariance (EC). We conclude with lessons learned for future large-scale hydrological studies.

  14. The Potential of Spaceborne Remote Sensing for Deriving Canopy Structure Metrics and Informing Biodiversity and Habitat Mapping

    NASA Astrophysics Data System (ADS)

    Goetz, S. J.; Dubayah, R.

    2016-12-01

    Research on characterization of canopy structure with remote sensing has exploded as airborne data sets have become more widely available to the biodiversity science and habitat management communities. While these advances are important in the context of increasing pressure on both habitat and wildlife, airborne data acquisitions are necessarily limited in geographic scope and thus in their general applicability to biome-scale biodiversity research initiatives, including international programs striving to implement the United Nations Convention on Biological Diversity (CBD) and the associated Aichi Biodiversity Targets. The lack of systematic metrics of canopy structure across large geographic domains also makes it difficult to implement the CBD Strategic Plan systematically across nations, as outlined in National Biodiversity Strategies and Action Plans. The Group on Earth Observations, Biodiversity Observation Network (GEO BON) has proposed a set of Essential Biodiversity Variables (EBVs) that could be used as a global-scale basis for biodiversity monitoring, but several of those EBVs are still limited by the availability of data on habitat 3D structure. Those limitations will be overcome in the near future with a suite of satellite missions that will provide an unprecedented level of active remote sensing measurements useful for deriving structure information, including Tandem-X, ICESat-2, BIOMASS and the Global Ecosystem Dynamics Investigation (GEDI). We will provide a brief overview of the rapid advance of measurements of canopy structure and the applications that have evolved in recent years in terms of 3D habitat characterization, species-specific habitat utilization, and the potential of these new space-based measurements. In this talk we will focus primarily on GEDI, a lidar mission to be installed on the International Space Station that is optimized for retrieving 3D canopy structure. GEDI and the other new missions will provide long-desired consistent

  15. Performance metrics for state-of-the-art airborne magnetic and electromagnetic systems for mapping and detection of unexploded ordnance

    NASA Astrophysics Data System (ADS)

    Doll, William E.; Bell, David T.; Gamey, T. Jeffrey; Beard, Les P.; Sheehan, Jacob R.; Norton, Jeannemarie

    2010-04-01

    Over the past decade, notable progress has been made in the performance of airborne geophysical systems for mapping and detection of unexploded ordnance in terrestrial and shallow marine environments. For magnetometer systems, the most significant improvements include development of denser magnetometer arrays and vertical gradiometer configurations. In prototype analyses and recent Environmental Security Technology Certification Program (ESTCP) assessments using new production systems the greatest sensitivity has been achieved with a vertical gradiometer configuration, despite model-based survey design results which suggest that dense total-field arrays would be superior. As effective as magnetometer systems have proven to be at many sites, they are inadequate at sites where basalts and other ferrous geologic formations or soils produce anomalies that approach or exceed those of target ordnance items. Additionally, magnetometer systems are ineffective where detection of non-ferrous ordnance items is of primary concern. Recent completion of the Battelle TEM-8 airborne time-domain electromagnetic system represents the culmination of nearly nine years of assessment and development of airborne electromagnetic systems for UXO mapping and detection. A recent ESTCP demonstration of this system in New Mexico showed that it was able to detect 99% of blind-seeded ordnance items, 81mm and larger, and that it could be used to map in detail a bombing target on a basalt flow where previous airborne magnetometer surveys had failed. The probability of detection for the TEM-8 in the blind-seeded study area was better than that reported for a dense-array total-field magnetometer demonstration of the same blind-seeded site, and the TEM-8 system successfully detected these items with less than half as many anomaly picks as the dense-array total-field magnetometer system.

  16. MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery

    NASA Astrophysics Data System (ADS)

    Reaungamornrat, S.; De Silva, T.; Uneri, A.; Wolinsky, J.-P.; Khanna, A. J.; Kleinszig, G.; Vogt, S.; Prince, J. L.; Siewerdsen, J. H.

    2016-03-01

    Purpose: Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. Method: The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. Result: The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. Conclusions: A modality-independent deformable registration method has been developed to estimate a

  17. MIND Demons for MR-to-CT Deformable Image Registration In Image-Guided Spine Surgery

    PubMed Central

    Reaungamornrat, S.; De Silva, T.; Uneri, A.; Wolinsky, J.-P.; Khanna, A. J.; Kleinszig, G.; Vogt, S.; Prince, J. L.; Siewerdsen, J. H.

    2016-01-01

    Purpose Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. Method The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. Result The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. Conclusions A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The

  18. MIND Demons for MR-to-CT Deformable Image Registration In Image-Guided Spine Surgery.

    PubMed

    Reaungamornrat, S; De Silva, T; Uneri, A; Wolinsky, J-P; Khanna, A J; Kleinszig, G; Vogt, S; Prince, J L; Siewerdsen, J H

    2016-02-27

    Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The method yields registration

  19. Edible Metrics.

    ERIC Educational Resources Information Center

    Mecca, Christyna E.

    1998-01-01

    Presents an exercise that introduces students to scientific measurements using only metric units. At the conclusion of the exercise, students eat the experiment. Requires dried refried beans, crackers or chips, and dried instant powder for lemonade. (DDR)

  20. Think Metric

    USGS Publications Warehouse

    ,

    1978-01-01

    The International System of Units, as the metric system is officially called, provides for a single "language" to describe weights and measures over the world. We in the United States together with the people of Brunei, Burma, and Yemen are the only ones who have not put this convenient system into effect. In the passage of the Metric Conversion Act of 1975, Congress determined that we also will adopt it, but the transition will be voluntary.

  1. Automated hexahedral meshing of anatomic structures using deformable registration.

    PubMed

    Grosland, Nicole M; Bafna, Ritesh; Magnotta, Vincent A

    2009-02-01

    This work introduces a novel method of automating the process of patient-specific finite element (FE) model development using a mapped mesh technique. The objective is to map a predefined mesh (template) of high quality directly onto a new bony surface (target) definition, thereby yielding a similar mesh with minimal user interaction. To bring the template mesh into correspondence with the target surface, a deformable registration technique based on the FE method has been adopted. The procedure has been made hierarchical allowing several levels of mesh refinement to be used, thus reducing the time required to achieve a solution. Our initial efforts have focused on the phalanx bones of the human hand. Mesh quality metrics, such as element volume and distortion were evaluated. Furthermore, the distance between the target surface and the final mapped mesh were measured. The results have satisfactorily proven the applicability of the proposed method.

  2. Registration of the IS3620C/BTx623 recombinant inbred mapping population of sorghum (Sorghum bicolor L. [Moench.])

    USDA-ARS?s Scientific Manuscript database

    The BTx623 x IS3620C sorghum [Sorghum bicolor (L.) Moench.] mapping population (Reg. No. _______, NSL ____, [represented as BTx623/IS3620C]), is a set of 430 F7 to F9 recombinant inbred lines [RILs](USDA-ARS Germplasm Information Network (GRIN) PI 658758 through PI 659060 and PI 659144 through PI 65...

  3. Geodesic active fields--a geometric framework for image registration.

    PubMed

    Zosso, Dominique; Bresson, Xavier; Thiran, Jean-Philippe

    2011-05-01

    In this paper we present a novel geometric framework called geodesic active fields for general image registration. In image registration, one looks for the underlying deformation field that best maps one image onto another. This is a classic ill-posed inverse problem, which is usually solved by adding a regularization term. Here, we propose a multiplicative coupling between the registration term and the regularization term, which turns out to be equivalent to embed the deformation field in a weighted minimal surface problem. Then, the deformation field is driven by a minimization flow toward a harmonic map corresponding to the solution of the registration problem. This proposed approach for registration shares close similarities with the well-known geodesic active contours model in image segmentation, where the segmentation term (the edge detector function) is coupled with the regularization term (the length functional) via multiplication as well. As a matter of fact, our proposed geometric model is actually the exact mathematical generalization to vector fields of the weighted length problem for curves and surfaces introduced by Caselles-Kimmel-Sapiro. The energy of the deformation field is measured with the Polyakov energy weighted by a suitable image distance, borrowed from standard registration models. We investigate three different weighting functions, the squared error and the approximated absolute error for monomodal images, and the local joint entropy for multimodal images. As compared to specialized state-of-the-art methods tailored for specific applications, our geometric framework involves important contributions. Firstly, our general formulation for registration works on any parametrizable, smooth and differentiable surface, including nonflat and multiscale images. In the latter case, multiscale images are registered at all scales simultaneously, and the relations between space and scale are intrinsically being accounted for. Second, this method is, to

  4. Mapping of dose distribution from IMRT onto MRI-guided high dose rate brachytherapy using deformable image registration for cervical cancer treatments: preliminary study with commercially available software

    PubMed Central

    Huq, M. Saiful; Houser, Chris; Beriwal, Sushil; Michalski, Dariusz

    2014-01-01

    Purpose For patients undergoing external beam radiation therapy (EBRT) and brachytherapy, recommendations for target doses and constraints are based on calculation of the equivalent dose in 2 Gy fractions (EQD2) from each phase. At present, the EBRT dose distribution is assumed to be uniform throughout the pelvis. We performed a preliminary study to determine whether deformable dose distribution mapping from the EBRT onto magnetic resonance (MR) images for the brachytherapy would yield differences in doses for organs at risk (OARs) and high-risk clinical target volume (HR-CTV). Material and methods Nine cervical cancer patients were treated to a total dose of 45 Gy in 25 fractions using intensity-modulated radiation therapy (IMRT), followed by MRI-based 3D high dose rate (HDR) brachytherapy. Retrospectively, the IMRT planning CT images were fused with the MR image for each fraction of brachytherapy using deformable image registration. The deformed IMRT dose onto MR images were converted to EQD2 and compared to the uniform dose assumption. Results For all patients, the EQD2 from the EBRT phase was significantly higher with deformable registration than with the conventional uniform dose distribution assumption. The mean EQD2 ± SD for HR-CTV D90 was 45.7 ± 0.7 Gy vs. 44.3 Gy for deformable vs. uniform dose distribution, respectively (p < 0.001). The dose to 2 cc of the bladder, rectum, and sigmoid was 46.4 ± 1.2 Gy, 46.2 ± 1.0 Gy, and 48.0 ± 2.5 Gy, respectively with deformable dose distribution, and was significantly higher than with uniform dose distribution (43.2 Gy for all OAR, p < 0.001). Conclusions This study reveals that deformed EBRT dose distribution to HR-CTV and OARs in MR images for brachytherapy is technically feasible, and achieves differences compared to a uniform dose distribution. Therefore, the assumption that EBRT contributes the same dose value may need to be carefully investigated further based on deformable image registration. PMID:25097559

  5. The application of iterative closest point (ICP) registration to improve 3D terrain mapping estimates using the flash 3D ladar system

    NASA Astrophysics Data System (ADS)

    Woods, Jack; Armstrong, Ernest E.; Armbruster, Walter; Richmond, Richard

    2010-04-01

    The primary purpose of this research was to develop an effective means of creating a 3D terrain map image (point-cloud) in GPS denied regions from a sequence of co-bore sighted visible and 3D LIDAR images. Both the visible and 3D LADAR cameras were hard mounted to a vehicle. The vehicle was then driven around the streets of an abandoned village used as a training facility by the German Army and imagery was collected. The visible and 3D LADAR images were then fused and 3D registration performed using a variation of the Iterative Closest Point (ICP) algorithm. The ICP algorithm is widely used for various spatial and geometric alignment of 3D imagery producing a set of rotation and translation transformations between two 3D images. ICP rotation and translation information obtain from registering the fused visible and 3D LADAR imagery was then used to calculate the x-y plane, range and intensity (xyzi) coordinates of various structures (building, vehicles, trees etc.) along the driven path. The xyzi coordinates information was then combined to create a 3D terrain map (point-cloud). In this paper, we describe the development and application of 3D imaging techniques (most specifically the ICP algorithm) used to improve spatial, range and intensity estimates of imagery collected during urban terrain mapping using a co-bore sighted, commercially available digital video camera with focal plan of 640×480 pixels and a 3D FLASH LADAR. Various representations of the reconstructed point-clouds for the drive through data will also be presented.

  6. Image Registration Through The Exploitation Of Perspective Invariant Graphs

    NASA Astrophysics Data System (ADS)

    Gilmore, John F.

    1983-10-01

    This paper describes two new techniques of image registration as applied to scenes consisting of natural terrain. The first technique is a syntactic pattern recognition approach which combines the spatial relationships of a point pattern with point classifications to accurately perform image registration. In this approach, a preprocessor analyzes each image in order to identify points of interest and to classify these points based on statistical features. A classified graph possessing perspective invariant properties is created and is converted into a classification-based grammar string. A local match analysis is performed and the best global match is con-structed. A probability-of-match metric is computed in order to evaluate match confidence. The second technique described is an isomorphic graph matching approach called Mean Neighbors (MN). A MN graph is constructed from a given point pattern taking into account the elliptical projections of real world scenes onto a two dimensional surface. This approach exploits the spatial relationships of the given points of interest but neglects the point classifications used in syntactic processing. A projective, perspective invariant graph is constructed for both the reference and sensed images and a mapping of the coincidence edges occurs. A probability of match metric is used to evaluate the confidence of the best mapping.

  7. Finite-Dimensional Lie Algebras for Fast Diffeomorphic Image Registration.

    PubMed

    Zhang, Miaomiao; Fletcher, P Thomas

    2015-01-01

    This paper presents a fast geodesic shooting algorithm for diffeomorphic image registration. We first introduce a novel finite-dimensional Lie algebra structure on the space of bandlimited velocity fields. We then show that this space can effectively represent initial velocities for diffeomorphic image registration at much lower dimensions than typically used, with little to no loss in registration accuracy. We then leverage the fact that the geodesic evolution equations, as well as the adjoint Jacobi field equations needed for gradient descent methods, can be computed entirely in this finite-dimensional Lie algebra. The result is a geodesic shooting method for large deformation metric mapping (LDDMM) that is dramatically faster and less memory intensive than state-of-the-art methods. We demonstrate the effectiveness of our model to register 3D brain images and compare its registration accuracy, run-time, and memory consumption with leading LDDMM methods. We also show how our algorithm breaks through the prohibitive time and memory requirements of diffeomorphic atlas building.

  8. Image Segmentation, Registration, Compression, and Matching

    NASA Technical Reports Server (NTRS)

    Yadegar, Jacob; Wei, Hai; Yadegar, Joseph; Ray, Nilanjan; Zabuawala, Sakina

    2011-01-01

    A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity

  9. Automatic registration of misaligned CT attenuation correction maps in Rb-82 PET/CT improves detection of angiographically significant coronary artery disease.

    PubMed

    Slomka, Piotr J; Diaz-Zamudio, Mariana; Dey, Damini; Motwani, Manish; Brodov, Yafim; Choi, David; Hayes, Sean; Thomson, Louise; Friedman, John; Germano, Guido; Berman, Daniel

    2015-12-01

    We aimed to evaluate the utility of fully automated software registration intended to improve CT attenuation correction (CTAC) map misalignments during cardiac (82)Rb PET/CT myocardial perfusion imaging (MPI). 171 consecutive patients (108 males, mean age 69 years), undergoing both rest-stress (82)Rb PET/CT MPI and invasive coronary angiography within 6 months (mean 14 days, range 0-170), were studied. List mode data were automatically processed in batch mode to generate transaxial attenuation corrected slices with four different CTAC alignment correction strategies: (i) no alignment correction (NONE); (ii) manual correction (MANUAL); (iii) automated 6-parameter rigid correction (AUTO); and (iv) targeted use of automated correction only where PET-CTAC alignment was initially judged as incorrect on either stress or rest scan (AUTO for misalignment only). Initial and final registration quality was graded (1-3) by an experienced radiologist (1: satisfactory alignment (<2 mm misalignment), 2: slight misalignment (2-5 mm in any direction), or 3: poor (>5 mm misalignment in any direction). Total perfusion deficit (TPD) and ischemic TPD (ITPD) were computed automatically, and their diagnostic accuracy to detect significant coronary artery disease with each realignment technique was assessed using receiver operating characteristic analysis. The diagnostic accuracy of ITPD, expressed as area under curve, was .81 ± .03 with no alignment correction (NONE), .83 ± .03 with MANUAL correction, .85 ± .03 with AUTO correction (P < .05 vs. NONE and MANUAL), and .87 ± .03 with the targeted use of AUTO correction (P < .05 vs. NONE, MANUAL and AUTO). Both manual and software corrections increased the percentage of cases with satisfactory PET-CTAC map alignment (P < .05 for all) at rest (from 55% for NONE to 80% for MANUAL and 92% for AUTO) and at stress (from 51% for NONE to 78% for MANUAL and 84% for AUTO). The diagnostic accuracy of (82)Rb PET/CT MPI with automated rigid

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

    NASA Astrophysics Data System (ADS)

    Ye, Y.

    2017-09-01

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

  11. Nonlinear functional connectivity network recovery in the human brain with mutual connectivity analysis (MCA): convergent cross-mapping and non-metric clustering

    NASA Astrophysics Data System (ADS)

    Wismüller, Axel; Abidin, Anas Z.; D'Souza, Adora M.; Wang, Xixi; Hobbs, Susan K.; Leistritz, Lutz; Nagarajan, Mahesh B.

    2015-03-01

    We explore a computational framework for functional connectivity analysis in resting-state functional MRI (fMRI) data acquired from the human brain for recovering the underlying network structure and understanding causality between network components. Termed mutual connectivity analysis (MCA), this framework involves two steps, the first of which is to evaluate the pair-wise cross-prediction performance between fMRI pixel time series within the brain. In a second step, the underlying network structure is subsequently recovered from the affinity matrix using non-metric network clustering approaches, such as the so-called Louvain method. Finally, we use convergent cross-mapping (CCM) to study causality between different network components. We demonstrate our MCA framework in the problem of recovering the motor cortex network associated with hand movement from resting state fMRI data. Results are compared with a ground truth of active motor cortex regions as identified by a task-based fMRI sequence involving a finger-tapping stimulation experiment. Our results regarding causation between regions of the motor cortex revealed a significant directional variability and were not readily interpretable in a consistent manner across subjects. However, our results on whole-slice fMRI analysis demonstrate that MCA-based model-free recovery of regions associated with the primary motor cortex and supplementary motor area are in close agreement with localization of similar regions achieved with a task-based fMRI acquisition. Thus, we conclude that our MCA methodology can extract and visualize valuable information concerning the underlying network structure between different regions of the brain in resting state fMRI.

  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. Automatic Masking for Robust 3D-2D Image Registration in Image-Guided Spine Surgery

    PubMed Central

    Ketcha, M. D.; De Silva, T.; Uneri, A.; Kleinszig, G.; Vogt, S.; Wolinsky, J.-P.; Siewerdsen, J. H.

    2016-01-01

    During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies. PMID:27335531

  15. Automatic Masking for Robust 3D-2D Image Registration in Image-Guided Spine Surgery.

    PubMed

    Ketcha, M D; De Silva, T; Uneri, A; Kleinszig, G; Vogt, S; Wolinsky, J-P; Siewerdsen, J H

    During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.

  16. Automatic masking for robust 3D-2D image registration in image-guided spine surgery

    NASA Astrophysics Data System (ADS)

    Ketcha, M. D.; De Silva, T.; Uneri, A.; Kleinszig, G.; Vogt, S.; Wolinsky, J.-P.; Siewerdsen, J. H.

    2016-03-01

    During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.

  17. Laplacian eigenmaps for multimodal groupwise image registration

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  18. Medial Demons Registration Localizes The Degree of Genetic Influence Over Subcortical Shape Variability: An N= 1480 Meta-Analysis.

    PubMed

    Gutman, Boris A; Jahanshad, Neda; Ching, Christopher R K; Wang, Yalin; Kochunov, Peter V; Nichols, Thomas E; Thompson, Paul M

    2015-04-01

    We present a multi-cohort shape heritability study, extending the fast spherical demons registration to subcortical shapes via medial modeling. A multi-channel demons registration based on vector spherical harmonics is applied to medial and curvature features, while controlling for metric distortion. We registered and compared seven subcortical structures of 1480 twins and siblings from the Queensland Twin Imaging Study and Human Connectome Project: Thalamus, Caudate, Putamen, Pallidum, Hippocampus, Amygdala, and Nucleus Accumbens. Radial distance and tensor-based morphometry (TBM) features were found to be highly heritable throughout the entire basal ganglia and limbic system. Surface maps reveal subtle variation in heritability across functionally distinct parts of each structure. Medial Demons reveals more significantly heritable regions than two previously described surface registration methods. This approach may help to prioritize features and measures for genome-wide association studies.

  19. Medial Demons Registration Localizes The Degree of Genetic Influence Over Subcortical Shape Variability: An N= 1480 Meta-Analysis

    PubMed Central

    Gutman, Boris A.; Jahanshad, Neda; Ching, Christopher R.K.; Wang, Yalin; Kochunov, Peter V.; Nichols, Thomas E.; Thompson, Paul M.

    2015-01-01

    We present a multi-cohort shape heritability study, extending the fast spherical demons registration to subcortical shapes via medial modeling. A multi-channel demons registration based on vector spherical harmonics is applied to medial and curvature features, while controlling for metric distortion. We registered and compared seven subcortical structures of 1480 twins and siblings from the Queensland Twin Imaging Study and Human Connectome Project: Thalamus, Caudate, Putamen, Pallidum, Hippocampus, Amygdala, and Nucleus Accumbens. Radial distance and tensor-based morphometry (TBM) features were found to be highly heritable throughout the entire basal ganglia and limbic system. Surface maps reveal subtle variation in heritability across functionally distinct parts of each structure. Medial Demons reveals more significantly heritable regions than two previously described surface registration methods. This approach may help to prioritize features and measures for genome-wide association studies. PMID:26413211

  20. Biodiversity Metrics

    EPA Science Inventory

    Ecosystem services, i.e., "services provided to humans from natural systems," have become a key focus of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have become strat...

  1. Biodiversity Metrics

    EPA Science Inventory

    Ecosystem services, i.e., "services provided to humans from natural systems," have become a key focus of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have become strat...

  2. Narrow band deformable registration of prostate magnetic resonance imaging, magnetic resonance spectroscopic imaging, and computed tomography studies

    SciTech Connect

    Schreibmann, Eduard; Xing Lei . E-mail: lei@reyes.stanford.edu

    2005-06-01

    Purpose: Endorectal (ER) coil-based magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI) is often used to obtain anatomic and metabolic images of the prostate and to accurately identify and assess the intraprostatic lesions. Recent advancements in high-field (3 Tesla or above) MR techniques affords significantly enhanced signal-to-noise ratio and makes it possible to obtain high-quality MRI data. In reality, the use of rigid or inflatable endorectal probes deforms the shape of the prostate gland, and the images so obtained are not directly usable in radiation therapy planning. The purpose of this work is to apply a narrow band deformable registration model to faithfully map the acquired information from the ER-based MRI/MRSI onto treatment planning computed tomography (CT) images. Methods and Materials: A narrow band registration, which is a hybrid method combining the advantages of pixel-based and distance-based registration techniques, was used to directly register ER-based MRI/MRSI with CT. The normalized correlation between the two input images for registration was used as the metric, and the calculation was restricted to those points contained in the narrow bands around the user-delineated structures. The narrow band method is inherently efficient because of the use of a priori information of the meaningful contour data. The registration was performed in two steps. First, the two input images were grossly aligned using a rigid registration. The detailed mapping was then modeled by free form deformations based on B-spline. The limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS), which is known for its superior performance in dealing with high-dimensionality problems, was implemented to optimize the metric function. The convergence behavior of the algorithm was studied by self-registering an MR image with 100 randomly initiated relative positions. To evaluate the performance of the algorithm, an MR image was

  3. Registration of interferometric SAR images

    NASA Technical Reports Server (NTRS)

    Lin, Qian; Vesecky, John F.; Zebker, Howard A.

    1992-01-01

    Interferometric synthetic aperture radar (INSAR) is a new way of performing topography mapping. Among the factors critical to mapping accuracy is the registration of the complex SAR images from repeated orbits. A new algorithm for registering interferometric SAR images is presented. A new figure of merit, the average fluctuation function of the phase difference image, is proposed to evaluate the fringe pattern quality. The process of adjusting the registration parameters according to the fringe pattern quality is optimized through a downhill simplex minimization algorithm. The results of applying the proposed algorithm to register two pairs of Seasat SAR images with a short baseline (75 m) and a long baseline (500 m) are shown. It is found that the average fluctuation function is a very stable measure of fringe pattern quality allowing very accurate registration.

  4. Make It Metric.

    ERIC Educational Resources Information Center

    Camilli, Thomas

    Measurement is perhaps the most frequently used form of mathematics. This book presents activities for learning about the metric system designed for upper intermediate and junior high levels. Discussions include: why metrics, history of metrics, changing to a metric world, teaching tips, and formulas. Activities presented are: metrics all around…

  5. Imbedding Locally Euclidean and Conformally Euclidean Metrics

    NASA Astrophysics Data System (ADS)

    Aleksandrov, V. A.

    1992-02-01

    The possibility of imbedding n-dimensional locally Euclidean metrics in the large in Rn is studied by means of the global inverse function theorem in the forms suggested by Hadamard, John, Levy and Plastock. The imbeddability of conformally Euclidean metrics is studied by means of a theorem of Zorich on the removability of an isolated singularity of a locally quasiconformal mapping.

  6. Image Registration: A Necessary Evil

    NASA Technical Reports Server (NTRS)

    Bell, James; McLachlan, Blair; Hermstad, Dexter; Trosin, Jeff; George, Michael W. (Technical Monitor)

    1995-01-01

    Registration of test and reference images is a key component of nearly all PSP data reduction techniques. This is done to ensure that a test image pixel viewing a particular point on the model is ratioed by the reference image pixel which views the same point. Typically registration is needed to account for model motion due to differing airloads when the wind-off and wind-on images are taken. Registration is also necessary when two cameras are used for simultaneous acquisition of data from a dual-frequency paint. This presentation will discuss the advantages and disadvantages of several different image registration techniques. In order to do so, it is necessary to propose both an accuracy requirement for image registration and a means for measuring the accuracy of a particular technique. High contrast regions in the unregistered images are most sensitive to registration errors, and it is proposed that these regions be used to establish the error limits for registration. Once this is done, the actual registration error can be determined by locating corresponding points on the test and reference images, and determining how well a particular registration technique matches them. An example of this procedure is shown for three transforms used to register images of a semispan model. Thirty control points were located on the model. A subset of the points were used to determine the coefficients of each registration transform, and the error with which each transform aligned the remaining points was determined. The results indicate the general superiority of a third-order polynomial over other candidate transforms, as well as showing how registration accuracy varies with number of control points. Finally, it is proposed that image registration may eventually be done away with completely. As more accurate image resection techniques and more detailed model surface grids become available, it will be possible to map raw image data onto the model surface accurately. Intensity

  7. An automatic MRI/SPECT registration algorithm using image intensity and anatomical feature as matching characters: application on the evaluation of Parkinson's disease.

    PubMed

    Lee, Jiann-Der; Huang, Chung-Hsien; Weng, Yi-Hsin; Lin, Kun-Ju; Chen, Chin-Tu

    2007-05-01

    Single-photon emission computed tomography (SPECT) of dopamine transporters with (99m)Tc-TRODAT-1 has recently been proposed to offer valuable information in assessing the functionality of dopaminergic systems. Magnetic resonance imaging (MRI) and SPECT imaging are important in the noninvasive examination of dopamine concentration in vivo. Therefore, this investigation presents an automated MRI/SPECT image registration algorithm based on a new similarity metric. This similarity metric combines anatomical features that are characterized by specific binding, the mean count per voxel in putamens and caudate nuclei, and the distribution of image intensity that is characterized by normalized mutual information (NMI). A preprocess, a novel two-cluster SPECT normalization algorithm, is also presented for MRI/SPECT registration. Clinical MRI/SPECT data from 18 healthy subjects and 13 Parkinson's disease (PD) patients are involved to validate the performance of the proposed algorithms. An appropriate color map, such as "rainbow," for image display enables the two-cluster SPECT normalization algorithm to provide clinically meaningful visual contrast. The proposed registration scheme reduces target registration error from >7 mm for conventional registration algorithm based on NMI to approximately 4 mm. The error in the specific/nonspecific (99m)Tc-TRODAT-1 binding ratio, which is employed as a quantitative measure of TRODAT receptor binding, is also reduced from 0.45+/-0.22 to 0.08+/-0.06 among healthy subjects and from 0.28+/-0.18 to 0.12+/-0.09 among PD patients.

  8. "Nonparametric Local Smoothing" is not image registration.

    PubMed

    Rohlfing, Torsten; Avants, Brian

    2012-11-01

    Image registration is one of the most important and universally useful computational tasks in biomedical image analysis. A recent article by Xing & Qiu (IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(10):2081-2092, 2011) is based on an inappropriately narrow conceptualization of the image registration problem as the task of making two images look alike, which disregards whether the established spatial correspondence is plausible. The authors propose a new algorithm, Nonparametric Local Smoothing (NLS) for image registration, but use image similarities alone as a measure of registration performance, although these measures do not relate reliably to the realism of the correspondence map. Using data obtained from its authors, we show experimentally that the method proposed by Xing & Qiu is not an effective registration algorithm. While it optimizes image similarity, it does not compute accurate, interpretable transformations. Even judged by image similarity alone, the proposed method is consistently outperformed by a simple pixel permutation algorithm, which is known by design not to compute valid registrations. This study has demonstrated that the NLS algorithm proposed recently for image registration, and published in one of the most respected journals in computer science, is not, in fact, an effective registration method at all. Our results also emphasize the general need to apply registration evaluation criteria that are sensitive to whether correspondences are accurate and mappings between images are physically interpretable. These goals cannot be achieved by simply reporting image similarities.

  9. 32 CFR 263.4 - Registration of vehicles.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 2 2011-07-01 2011-07-01 false Registration of vehicles. 263.4 Section 263.4...) MISCELLANEOUS TRAFFIC AND VEHICLE CONTROL ON CERTAIN DEFENSE MAPPING AGENCY SITES § 263.4 Registration of...) Temporary registration for a specified period of time will be permitted for temporarily hired, detailed,...

  10. NASA metrication activities

    NASA Technical Reports Server (NTRS)

    Vlannes, P. N.

    1978-01-01

    NASA's organization and policy for metrification, history from 1964, NASA participation in Federal agency activities, interaction with nongovernmental metrication organizations, and the proposed metrication assessment study are reviewed.

  11. Science as Knowledge, Practice, and Map Making: The Challenge of Defining Metrics for Evaluating and Improving DOE-Funded Basic Experimental Science

    SciTech Connect

    Bodnarczuk, M.

    1993-03-01

    Industrial R&D laboratories have been surprisingly successful in developing performance objectives and metrics that convincingly show that planning, management, and improvement techniques can be value-added to the actual output of R&D organizations. In this paper, I will discuss the more difficult case of developing analogous constructs for DOE-funded non-nuclear, non-weapons basic research, or as I will refer to it - basic experimental science. Unlike most industrial R&D or the bulk of applied science performed at the National Renewable Energy Laboratory (NREL), the purpose of basic experimental science is producing new knowledge (usually published in professional journals) that has no immediate application to the first link (the R) of a planned R&D chain. Consequently, performance objectives and metrics are far more difficult to define. My claim is that if one can successfully define metrics for evaluating and improving DOE-funded basic experimental science (which is the most difficult case), then defining such constructs for DOE-funded applied science should be much less problematic. With the publication of the DOE Standard - Implementation Guide for Quality Assurance Programs for Basic and Applied Research (DOE-ER-STD-6001-92) and the development of a conceptual framework for integrating all the DOE orders, we need to move aggressively toward the threefold next phase: (1) focusing the management elements found in DOE-ER-STD-6001-92 on the main output of national laboratories - the experimental science itself; (2) developing clearer definitions of basic experimental science as practice not just knowledge; and (3) understanding the relationship between the metrics that scientists use for evaluating the performance of DOE-funded basic experimental science, the management elements of DOE-ER-STD-6001-92, and the notion of continuous improvement.

  12. ACIR: automatic cochlea image registration

    NASA Astrophysics Data System (ADS)

    Al-Dhamari, Ibraheem; Bauer, Sabine; Paulus, Dietrich; Lissek, Friedrich; Jacob, Roland

    2017-02-01

    Efficient Cochlear Implant (CI) surgery requires prior knowledge of the cochlea's size and its characteristics. This information helps to select suitable implants for different patients. To get these measurements, a segmentation method of cochlea medical images is needed. An important pre-processing step for good cochlea segmentation involves efficient image registration. The cochlea's small size and complex structure, in addition to the different resolutions and head positions during imaging, reveals a big challenge for the automated registration of the different image modalities. In this paper, an Automatic Cochlea Image Registration (ACIR) method for multi- modal human cochlea images is proposed. This method is based on using small areas that have clear structures from both input images instead of registering the complete image. It uses the Adaptive Stochastic Gradient Descent Optimizer (ASGD) and Mattes's Mutual Information metric (MMI) to estimate 3D rigid transform parameters. The use of state of the art medical image registration optimizers published over the last two years are studied and compared quantitatively using the standard Dice Similarity Coefficient (DSC). ACIR requires only 4.86 seconds on average to align cochlea images automatically and to put all the modalities in the same spatial locations without human interference. The source code is based on the tool elastix and is provided for free as a 3D Slicer plugin. Another contribution of this work is a proposed public cochlea standard dataset which can be downloaded for free from a public XNAT server.

  13. On optimal fuzzy best proximity coincidence points of fuzzy order preserving proximal Ψ(σ, α)-lower-bounding asymptotically contractive mappings in non-Archimedean fuzzy metric spaces.

    PubMed

    De la Sen, Manuel; Abbas, Mujahid; Saleem, Naeem

    2016-01-01

    This paper discusses some convergence properties in fuzzy ordered proximal approaches defined by [Formula: see text]-sequences of pairs, where [Formula: see text] is a surjective self-mapping and [Formula: see text] where Aand Bare nonempty subsets of and abstract nonempty set X and [Formula: see text] is a partially ordered non-Archimedean fuzzy metric space which is endowed with a fuzzy metric M, a triangular norm * and an ordering [Formula: see text] The fuzzy set M takes values in a sequence or set [Formula: see text] where the elements of the so-called switching rule [Formula: see text] are defined from [Formula: see text] to a subset of [Formula: see text] Such a switching rule selects a particular realization of M at the nth iteration and it is parameterized by a growth evolution sequence [Formula: see text] and a sequence or set [Formula: see text] which belongs to the so-called [Formula: see text]-lower-bounding mappings which are defined from [0, 1] to [0, 1]. Some application examples concerning discrete systems under switching rules and best approximation solvability of algebraic equations are discussed.

  14. Biomechanical model as a registration tool for image-guided neurosurgery: evaluation against BSpline registration

    PubMed Central

    Mostayed, Ahmed; Garlapati, Revanth Reddy; Joldes, Grand Roman; Wittek, Adam; Roy, Aditi; Kikinis, Ron; Warfield, Simon K.; Miller, Karol

    2013-01-01

    In this paper we evaluate the accuracy of warping of neuro-images using brain deformation predicted by means of a patient-specific biomechanical model against registration using a BSpline-based free form deformation algorithm. Unlike the Bspline algorithm, biomechanics-based registration does not require an intra-operative MR image which is very expensive and cumbersome to acquire. Only sparse intra-operative data on the brain surface is sufficient to compute deformation for the whole brain. In this contribution the deformation fields obtained from both methods are qualitatively compared and overlaps of Canny edges extracted from the images are examined. We define an edge based Hausdorff distance metric to quantitatively evaluate the accuracy of registration for these two algorithms. The qualitative and quantitative evaluations indicate that our biomechanics-based registration algorithm, despite using much less input data, has at least as high registration accuracy as that of the BSpline algorithm. PMID:23771299

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

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

  16. Generalized Ulam-Hyers Stability, Well-Posedness, and Limit Shadowing of Fixed Point Problems for α-β-Contraction Mapping in Metric Spaces

    PubMed Central

    2014-01-01

    We study the generalized Ulam-Hyers stability, the well-posedness, and the limit shadowing of the fixed point problem for new type of generalized contraction mapping, the so-called α-β-contraction mapping. Our results in this paper are generalized and unify several results in the literature as the result of Geraghty (1973) and the Banach contraction principle. PMID:24592174

  17. Cortical Correspondence via Sulcal Curve-Constrained Spherical Registration with Application to Macaque Studies.

    PubMed

    Lyu, Ilwoo; Kim, Sun Hyung; Seong, Joon-Kyung; Yoo, Sang Wook; Evans, Alan C; Shi, Yundi; Sanchez, Mar; Niethammer, Marc; Styner, Martin

    2013-03-13

    In this work, we present a novel cortical correspondence method with application to the macaque brain. The correspondence method is based on sulcal curve constraints on a spherical deformable registration using spherical harmonics to parameterize the spherical deformation. Starting from structural MR images, we first apply existing preprocessing steps: brain tissue segmentation using the Automatic Brain Classification tool (ABC), as well as cortical surface reconstruction and spherical parametrization of the cortical surface via Constrained Laplacian-based Automated Segmentation with Proximities (CLASP). Then, initial correspondence between two cortical surfaces is automatically determined by a curve labeling method using sulcal landmarks extracted along sulcal fundic regions. Since the initial correspondence is limited to sulcal regions, we use spherical harmonics to extrapolate and regularize this correspondence to the entire cortical surface. To further improve the correspondence, we compute a spherical registration that optimizes the spherical harmonic parameterized deformation using a metric that incorporates the error over the sulcal landmarks as well as the normalized cross correlation of sulcal depth maps over the whole cortical surface. For evaluation, a normal 18-months-old macaque brain (for both left and right hemispheres) was matched to a prior macaque brain template with 9 manually labeled, major sulcal curves. The results show successful registration using the proposed registration approach. Evaluation results for optimal parameter settings are presented as well.

  18. Mapping.

    ERIC Educational Resources Information Center

    Kinney, Douglas M.; McIntosh, Willard L.

    1979-01-01

    The area of geological mapping in the United States in 1978 increased greatly over that reported in 1977; state geological maps were added for California, Idaho, Nevada, and Alaska last year. (Author/BB)

  19. A factor analysis of landscape pattern and structure metrics

    Treesearch

    Kurt H. Riitters; R.V. O' Neill; C.T. Hunsaker; James D. Wickham; D.H. Yankee; S.P. Timmins; K.B. Jones; B.L. Jackson

    1995-01-01

    Fifty-five metrics of landscape pattern and structure were calculated for 85 maps of land use and land cover. A multivariate factor analysis was used to identify the common axes (or dimensions) of pattern and structure which were measured by a reduced set of 26 metrics. The first six factors explained about 87% of the variation in the 26 landscape metrics. These...

  20. 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.

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

    PubMed

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

    2015-03-01

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

  2. Fluid Registration of Diffusion Tensor Images Using Information Theory

    PubMed Central

    Chiang, Ming-Chang; Leow, Alex D.; Klunder, Andrea D.; Dutton, Rebecca A.; Barysheva, Marina; Rose, Stephen E.; McMahon, Katie L.; de Zubicaray, Greig I.; Toga, Arthur W.; Thompson, Paul M.

    2008-01-01

    We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data. PMID:18390342

  3. DR-TAMAS: Diffeomorphic Registration for Tensor Accurate Alignment of Anatomical Structures.

    PubMed

    Irfanoglu, M Okan; Nayak, Amritha; Jenkins, Jeffrey; Hutchinson, Elizabeth B; Sadeghi, Neda; Thomas, Cibu P; Pierpaoli, Carlo

    2016-05-15

    In this work, we propose DR-TAMAS (Diffeomorphic Registration for Tensor Accurate alignMent of Anatomical Structures), a novel framework for intersubject registration of Diffusion Tensor Imaging (DTI) data sets. This framework is optimized for brain data and its main goal is to achieve an accurate alignment of all brain structures, including white matter (WM), gray matter (GM), and spaces containing cerebrospinal fluid (CSF). Currently most DTI-based spatial normalization algorithms emphasize alignment of anisotropic structures. While some diffusion-derived metrics, such as diffusion anisotropy and tensor eigenvector orientation, are highly informative for proper alignment of WM, other tensor metrics such as the trace or mean diffusivity (MD) are fundamental for a proper alignment of GM and CSF boundaries. Moreover, it is desirable to include information from structural MRI data, e.g., T1-weighted or T2-weighted images, which are usually available together with the diffusion data. The fundamental property of DR-TAMAS is to achieve global anatomical accuracy by incorporating in its cost function the most informative metrics locally. Another important feature of DR-TAMAS is a symmetric time-varying velocity-based transformation model, which enables it to account for potentially large anatomical variability in healthy subjects and patients. The performance of DR-TAMAS is evaluated with several data sets and compared with other widely-used diffeomorphic image registration techniques employing both full tensor information and/or DTI-derived scalar maps. Our results show that the proposed method has excellent overall performance in the entire brain, while being equivalent to the best existing methods in WM. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. DR-TAMAS: Diffeomorphic Registration for Tensor Accurate alignMent of Anatomical Structures

    PubMed Central

    Irfanoglu, M. Okan; Nayak, Amritha; Jenkins, Jeffrey; Hutchinson, Elizabeth B.; Sadeghi, Neda; Thomas, Cibu P.; Pierpaoli, Carlo

    2016-01-01

    In this work, we propose DR-TAMAS (Diffeomorphic Registration for Tensor Accurate alignMent of Anatomical Structures), a novel framework for intersubject registration of Diffusion Tensor Imaging (DTI) data sets. This framework is optimized for brain data and its main goal is to achieve an accurate alignment of all brain structures, including white matter (WM), gray matter (GM), and spaces containing cerebrospinal fluid (CSF). Currently most DTI-based spatial normalization algorithms emphasize alignment of anisotropic structures. While some diffusion-derived metrics, such as diffusion anisotropy and tensor eigenvector orientation, are highly informative for proper alignment of WM, other tensor metrics such as the trace or mean diffusivity (MD) are fundamental for a proper alignment of GM and CSF boundaries. Moreover, it is desirable to include information from structural MRI data, e.g., T1-weighted or T2-weighted images, which are usually available together with the diffusion data. The fundamental property of DR-TAMAS is to achieve global anatomical accuracy by incorporating in its cost function the most informative metrics locally. Another important feature of DR-TAMAS is a symmetric time-varying velocity-based transformation model, which enables it to account for potentially large anatomical variability in healthy subjects and patients. The performance of DR-TAMAS is evaluated with several data sets and compared with other widely-used diffeomorphic image registration techniques employing both full tensor information and/or DTI-derived scalar maps. Our results show that the proposed method has excellent overall performance in the entire brain, while being equivalent to the best existing methods in WM. PMID:26931817

  5. NASA metric transition plan

    NASA Technical Reports Server (NTRS)

    1992-01-01

    NASA science publications have used the metric system of measurement since 1970. Although NASA has maintained a metric use policy since 1979, practical constraints have restricted actual use of metric units. In 1988, an amendment to the Metric Conversion Act of 1975 required the Federal Government to adopt the metric system except where impractical. In response to Public Law 100-418 and Executive Order 12770, NASA revised its metric use policy and developed this Metric Transition Plan. NASA's goal is to use the metric system for program development and functional support activities to the greatest practical extent by the end of 1995. The introduction of the metric system into new flight programs will determine the pace of the metric transition. Transition of institutional capabilities and support functions will be phased to enable use of the metric system in flight program development and operations. Externally oriented elements of this plan will introduce and actively support use of the metric system in education, public information, and small business programs. The plan also establishes a procedure for evaluating and approving waivers and exceptions to the required use of the metric system for new programs. Coordination with other Federal agencies and departments (through the Interagency Council on Metric Policy) and industry (directly and through professional societies and interest groups) will identify sources of external support and minimize duplication of effort.

  6. NASA metric transition plan

    NASA Astrophysics Data System (ADS)

    NASA science publications have used the metric system of measurement since 1970. Although NASA has maintained a metric use policy since 1979, practical constraints have restricted actual use of metric units. In 1988, an amendment to the Metric Conversion Act of 1975 required the Federal Government to adopt the metric system except where impractical. In response to Public Law 100-418 and Executive Order 12770, NASA revised its metric use policy and developed this Metric Transition Plan. NASA's goal is to use the metric system for program development and functional support activities to the greatest practical extent by the end of 1995. The introduction of the metric system into new flight programs will determine the pace of the metric transition. Transition of institutional capabilities and support functions will be phased to enable use of the metric system in flight program development and operations. Externally oriented elements of this plan will introduce and actively support use of the metric system in education, public information, and small business programs. The plan also establishes a procedure for evaluating and approving waivers and exceptions to the required use of the metric system for new programs. Coordination with other Federal agencies and departments (through the Interagency Council on Metric Policy) and industry (directly and through professional societies and interest groups) will identify sources of external support and minimize duplication of effort.

  7. Performance metrics for evaluating system suitability in liquid chromatography--Mass spectrometry peptide mass mapping of protein therapeutics and monoclonal antibodies.

    PubMed

    Zhou, Mowei; Gucinski, Ashley C; Boyne, Michael T

    2015-01-01

    The use of liquid chromatography--mass spectrometry (LC-MS) for the characterization of proteins can provide a plethora of information related to their structure, including amino acid sequence determination and analysis of posttranslational modifications. The variety of LC-MS based applications has led to the use of LC-MS characterization of therapeutic proteins and monoclonal antibodies as an integral part of the regulatory approval process. However, the improper use of an LC-MS system, related to intrinsic instrument limitations, improper tuning parameters, or poorly optimized methods may result in the production of low quality data. Improper system performance may arise from subtle changes in operating conditions that limit the ability to detect low abundance species. To address this issue, we systematically evaluated LC-MS/MS operating parameters to identify a set of metrics that can be used in a workflow to determine if a system is suitable for its intended purpose. Development of this workflow utilized a bovine serum albumin (BSA) digest standard spiked with synthetic peptides present at 0.1% to 100% of the BSA digest peptide concentration to simulate the detection of low abundance species using a traditional bottom-up workflow and data-dependent MS(2) acquisition. BSA sequence coverage, a commonly used indicator for instrument performance did not effectively identify settings that led to limited dynamic range or poorer absolute mass accuracy on 2 separate LC-MS systems. Additional metrics focusing on the detection limit and sensitivity for peptide identification were determined to be necessary to establish system suitability for protein therapeutic characterization by LC-MS.

  8. Performance metrics for evaluating system suitability in liquid chromatography—Mass spectrometry peptide mass mapping of protein therapeutics and monoclonal antibodies

    PubMed Central

    Zhou, Mowei; Gucinski, Ashley C; Boyne, Michael T

    2015-01-01

    The use of liquid chromatography – mass spectrometry (LC-MS) for the characterization of proteins can provide a plethora of information related to their structure, including amino acid sequence determination and analysis of posttranslational modifications. The variety of LC-MS based applications has led to the use of LC-MS characterization of therapeutic proteins and monoclonal antibodies as an integral part of the regulatory approval process. However, the improper use of an LC-MS system, related to intrinsic instrument limitations, improper tuning parameters, or poorly optimized methods may result in the production of low quality data. Improper system performance may arise from subtle changes in operating conditions that limit the ability to detect low abundance species. To address this issue, we systematically evaluated LC-MS/MS operating parameters to identify a set of metrics that can be used in a workflow to determine if a system is suitable for its intended purpose. Development of this workflow utilized a bovine serum albumin (BSA) digest standard spiked with synthetic peptides present at 0.1% to 100% of the BSA digest peptide concentration to simulate the detection of low abundance species using a traditional bottom-up workflow and data-dependent MS2 acquisition. BSA sequence coverage, a commonly used indicator for instrument performance did not effectively identify settings that led to limited dynamic range or poorer absolute mass accuracy on 2 separate LC-MS systems. Additional metrics focusing on the detection limit and sensitivity for peptide identification were determined to be necessary to establish system suitability for protein therapeutic characterization by LC-MS. PMID:26218711

  9. Endoluminal surface registration for CT colonography using haustral fold matching☆

    PubMed Central

    Hampshire, Thomas; Roth, Holger R.; Helbren, Emma; Plumb, Andrew; Boone, Darren; Slabaugh, Greg; Halligan, Steve; Hawkes, David J.

    2013-01-01

    Computed Tomographic (CT) colonography is a technique used for the detection of bowel cancer or potentially precancerous polyps. The procedure is performed routinely with the patient both prone and supine to differentiate fixed colonic pathology from mobile faecal residue. Matching corresponding locations is difficult and time consuming for radiologists due to colonic deformations that occur during patient repositioning. We propose a novel method to establish correspondence between the two acquisitions automatically. The problem is first simplified by detecting haustral folds using a graph cut method applied to a curvature-based metric applied to a surface mesh generated from segmentation of the colonic lumen. A virtual camera is used to create a set of images that provide a metric for matching pairs of folds between the prone and supine acquisitions. Image patches are generated at the fold positions using depth map renderings of the endoluminal surface and optimised by performing a virtual camera registration over a restricted set of degrees of freedom. The intensity difference between image pairs, along with additional neighbourhood information to enforce geometric constraints over a 2D parameterisation of the 3D space, are used as unary and pair-wise costs respectively, and included in a Markov Random Field (MRF) model to estimate the maximum a posteriori fold labelling assignment. The method achieved fold matching accuracy of 96.0% and 96.1% in patient cases with and without local colonic collapse. Moreover, it improved upon an existing surface-based registration algorithm by providing an initialisation. The set of landmark correspondences is used to non-rigidly transform a 2D source image derived from a conformal mapping process on the 3D endoluminal surface mesh. This achieves full surface correspondence between prone and supine views and can be further refined with an intensity based registration showing a statistically significant improvement (p < 0

  10. Endoluminal surface registration for CT colonography using haustral fold matching.

    PubMed

    Hampshire, Thomas; Roth, Holger R; Helbren, Emma; Plumb, Andrew; Boone, Darren; Slabaugh, Greg; Halligan, Steve; Hawkes, David J

    2013-12-01

    Computed Tomographic (CT) colonography is a technique used for the detection of bowel cancer or potentially precancerous polyps. The procedure is performed routinely with the patient both prone and supine to differentiate fixed colonic pathology from mobile faecal residue. Matching corresponding locations is difficult and time consuming for radiologists due to colonic deformations that occur during patient repositioning. We propose a novel method to establish correspondence between the two acquisitions automatically. The problem is first simplified by detecting haustral folds using a graph cut method applied to a curvature-based metric applied to a surface mesh generated from segmentation of the colonic lumen. A virtual camera is used to create a set of images that provide a metric for matching pairs of folds between the prone and supine acquisitions. Image patches are generated at the fold positions using depth map renderings of the endoluminal surface and optimised by performing a virtual camera registration over a restricted set of degrees of freedom. The intensity difference between image pairs, along with additional neighbourhood information to enforce geometric constraints over a 2D parameterisation of the 3D space, are used as unary and pair-wise costs respectively, and included in a Markov Random Field (MRF) model to estimate the maximum a posteriori fold labelling assignment. The method achieved fold matching accuracy of 96.0% and 96.1% in patient cases with and without local colonic collapse. Moreover, it improved upon an existing surface-based registration algorithm by providing an initialisation. The set of landmark correspondences is used to non-rigidly transform a 2D source image derived from a conformal mapping process on the 3D endoluminal surface mesh. This achieves full surface correspondence between prone and supine views and can be further refined with an intensity based registration showing a statistically significant improvement (p<0.001), and

  11. Semantic Metrics for Object Oriented Design

    NASA Technical Reports Server (NTRS)

    Etzkorn, Lethe

    2003-01-01

    The purpose of this proposal is to research a new suite of object-oriented (OO) software metrics, called semantic metrics, that have the potential to help software engineers identify fragile, low quality code sections much earlier in the development cycle than is possible with traditional OO metrics. With earlier and better Fault detection, software maintenance will be less time consuming and expensive, and software reusability will be improved. Because it is less costly to correct faults found earlier than to correct faults found later in the software lifecycle, the overall cost of software development will be reduced. Semantic metrics can be derived from the knowledge base of a program understanding system. A program understanding system is designed to understand a software module. Once understanding is complete, the knowledge-base contains digested information about the software module. Various semantic metrics can be collected on the knowledge base. This new kind of metric measures domain complexity, or the relationship of the software to its application domain, rather than implementation complexity, which is what traditional software metrics measure. A semantic metric will thus map much more closely to qualities humans are interested in, such as cohesion and maintainability, than is possible using traditional metrics, that are calculated using only syntactic aspects of software.

  12. Semantic Metrics for Object Oriented Design

    NASA Technical Reports Server (NTRS)

    Etzkorn, Lethe

    2003-01-01

    The purpose of this proposal is to research a new suite of object-oriented (OO) software metrics, called semantic metrics, that have the potential to help software engineers identify fragile, low quality code sections much earlier in the development cycle than is possible with traditional OO metrics. With earlier and better Fault detection, software maintenance will be less time consuming and expensive, and software reusability will be improved. Because it is less costly to correct faults found earlier than to correct faults found later in the software lifecycle, the overall cost of software development will be reduced. Semantic metrics can be derived from the knowledge base of a program understanding system. A program understanding system is designed to understand a software module. Once understanding is complete, the knowledge-base contains digested information about the software module. Various semantic metrics can be collected on the knowledge base. This new kind of metric measures domain complexity, or the relationship of the software to its application domain, rather than implementation complexity, which is what traditional software metrics measure. A semantic metric will thus map much more closely to qualities humans are interested in, such as cohesion and maintainability, than is possible using traditional metrics, that are calculated using only syntactic aspects of software.

  13. SU-E-J-122: The CBCT Dose Calculation Using a Patient Specific CBCT Number to Mass Density Conversion Curve Based On a Novel Image Registration and Organ Mapping Method in Head-And-Neck Radiation Therapy

    SciTech Connect

    Zhou, J; Lasio, G; Chen, S; Zhang, B; Langen, K; Prado, K; D’Souza, W; Yi, B; Huang, J

    2015-06-15

    Purpose: To develop a CBCT HU correction method using a patient specific HU to mass density conversion curve based on a novel image registration and organ mapping method for head-and-neck radiation therapy. Methods: There are three steps to generate a patient specific CBCT HU to mass density conversion curve. First, we developed a novel robust image registration method based on sparseness analysis to register the planning CT (PCT) and the CBCT. Second, a novel organ mapping method was developed to transfer the organs at risk (OAR) contours from the PCT to the CBCT and corresponding mean HU values of each OAR were measured in both the PCT and CBCT volumes. Third, a set of PCT and CBCT HU to mass density conversion curves were created based on the mean HU values of OARs and the corresponding mass density of the OAR in the PCT. Then, we compared our proposed conversion curve with the traditional Catphan phantom based CBCT HU to mass density calibration curve. Both curves were input into the treatment planning system (TPS) for dose calculation. Last, the PTV and OAR doses, DVH and dose distributions of CBCT plans are compared to the original treatment plan. Results: One head-and-neck cases which contained a pair of PCT and CBCT was used. The dose differences between the PCT and CBCT plans using the proposed method are −1.33% for the mean PTV, 0.06% for PTV D95%, and −0.56% for the left neck. The dose differences between plans of PCT and CBCT corrected using the CATPhan based method are −4.39% for mean PTV, 4.07% for PTV D95%, and −2.01% for the left neck. Conclusion: The proposed CBCT HU correction method achieves better agreement with the original treatment plan compared to the traditional CATPhan based calibration method.

  14. Moving to Metric.

    ERIC Educational Resources Information Center

    North Carolina State Dept. of Public Instruction, Raleigh.

    This booklet, designed to help the consumer prepare for the change to the metric system, discusses the following related topics: simplicity and universality of the metric system, weather, shopping, textiles, cooking, and driving. (MP)

  15. Metrication for the Manager.

    ERIC Educational Resources Information Center

    Benedict, John T.

    The scope of this book covers metrication management. It was created to fill the middle management need for condensed, authoritative information about the metrication process and was conceived as a working tool and a prime reference source. Written from a management point of view, it touches on virtually all aspects of metrication and highlights…

  16. Autonomous Exploration Using an Information Gain Metric

    DTIC Science & Technology

    2016-03-01

    explore and map the unknown area. Exploration frontiers can be described as areas that lie on the boundary between known and unknown space . This...ARL-TR-7638 ● MAR 2016 US Army Research Laboratory Autonomous Exploration Using an Information Gain Metric by Nicholas C Fung...Laboratory Autonomous Exploration Using an Information Gain Metric by Nicholas C Fung, Jason M Gregory, and John G Rogers Computational and

  17. Registration Review Process

    EPA Pesticide Factsheets

    EPA will review each registered pesticide at least every 15 years to determine whether it continues to meet the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) standard for registration. There are currently 745 registration review cases.

  18. Pesticide Registration Information System

    EPA Pesticide Factsheets

    PRISM provides an integrated, web portal for all pesticide related data, communications, registrations and transactions for OPP and its stakeholders, partners and customers. PRISM supports Strategic Goal 4 by automating pesticide registration processes.

  19. MAPS

    Atmospheric Science Data Center

    2014-07-03

    ... Measurement of Air Pollution from Satellites (MAPS) data were collected during Space Shuttle flights in 1981, ... Facts Correlative Data  - CDIAC - Spring & Fall 1994 - Field and Aircraft Campaigns SCAR-B Block:  ...

  20. Registration of multi-view apical 3D echocardiography images

    NASA Astrophysics Data System (ADS)

    Mulder, H. W.; van Stralen, M.; van der Zwaan, H. B.; Leung, K. Y. E.; Bosch, J. G.; Pluim, J. P. W.

    2011-03-01

    Real-time three-dimensional echocardiography (RT3DE) is a non-invasive method to visualize the heart. Disadvantageously, it suffers from non-uniform image quality and a limited field of view. Image quality can be improved by fusion of multiple echocardiography images. Successful registration of the images is essential for prosperous fusion. Therefore, this study examines the performance of different methods for intrasubject registration of multi-view apical RT3DE images. A total of 14 data sets was annotated by two observers who indicated the position of the apex and four points on the mitral valve ring. These annotations were used to evaluate registration. Multi-view end-diastolic (ED) as well as end-systolic (ES) images were rigidly registered in a multi-resolution strategy. The performance of single-frame and multi-frame registration was examined. Multi-frame registration optimizes the metric for several time frames simultaneously. Furthermore, the suitability of mutual information (MI) as similarity measure was compared to normalized cross-correlation (NCC). For initialization of the registration, a transformation that describes the probe movement was obtained by manually registering five representative data sets. It was found that multi-frame registration can improve registration results with respect to single-frame registration. Additionally, NCC outperformed MI as similarity measure. If NCC was optimized in a multi-frame registration strategy including ED and ES time frames, the performance of the automatic method was comparable to that of manual registration. In conclusion, automatic registration of RT3DE images performs as good as manual registration. As registration precedes image fusion, this method can contribute to improved quality of echocardiography images.

  1. Multiple Kernel Point Set Registration.

    PubMed

    Nguyen, Thanh Minh; Wu, Q M Jonathan

    2015-12-22

    The finite Gaussian mixture model with kernel correlation is a flexible tool that has recently received attention for point set registration. While there are many algorithms for point set registration presented in the literature, an important issue arising from these studies concerns the mapping of data with nonlinear relationships and the ability to select a suitable kernel. Kernel selection is crucial for effective point set registration. We focus here on multiple kernel point set registration. We make several contributions in this paper. First, each observation is modeled using the Student's t-distribution, which is heavily tailed and more robust than the Gaussian distribution. Second, by automatically adjusting the kernel weights, the proposed method allows us to prune the ineffective kernels. This makes the choice of kernels less crucial. After parameter learning, the kernel saliencies of the irrelevant kernels go to zero. Thus, the choice of kernels is less crucial and it is easy to include other kinds of kernels. Finally, we show empirically that our model outperforms state-of-the-art methods recently proposed in the literature.

  2. Multiple Kernel Point Set Registration.

    PubMed

    Nguyen, Thanh Minh; Wu, Q M Jonathan

    2016-06-01

    The finite Gaussian mixture model with kernel correlation is a flexible tool that has recently received attention for point set registration. While there are many algorithms for point set registration presented in the literature, an important issue arising from these studies concerns the mapping of data with nonlinear relationships and the ability to select a suitable kernel. Kernel selection is crucial for effective point set registration. We focus here on multiple kernel point set registration. We make several contributions in this paper. First, each observation is modeled using the Student's t-distribution, which is heavily tailed and more robust than the Gaussian distribution. Second, by automatically adjusting the kernel weights, the proposed method allows us to prune the ineffective kernels. This makes the choice of kernels less crucial. After parameter learning, the kernel saliencies of the irrelevant kernels go to zero. Thus, the choice of kernels is less crucial and it is easy to include other kinds of kernels. Finally, we show empirically that our model outperforms state-of-the-art methods recently proposed in the literature.

  3. 3D-2D registration for surgical guidance: effect of projection view angles on registration accuracy.

    PubMed

    Uneri, A; Otake, Y; Wang, A S; Kleinszig, G; Vogt, S; Khanna, A J; Siewerdsen, J H

    2014-01-20

    An algorithm for intensity-based 3D-2D registration of CT and x-ray projections is evaluated, specifically using single- or dual-projection views to provide 3D localization. The registration framework employs the gradient information similarity metric and covariance matrix adaptation evolution strategy to solve for the patient pose in six degrees of freedom. Registration performance was evaluated in an anthropomorphic phantom and cadaver, using C-arm projection views acquired at angular separation, Δθ, ranging from ∼0°-180° at variable C-arm magnification. Registration accuracy was assessed in terms of 2D projection distance error and 3D target registration error (TRE) and compared to that of an electromagnetic (EM) tracker. The results indicate that angular separation as small as Δθ ∼10°-20° achieved TRE <2 mm with 95% confidence, comparable or superior to that of the EM tracker. The method allows direct registration of preoperative CT and planning data to intraoperative fluoroscopy, providing 3D localization free from conventional limitations associated with external fiducial markers, stereotactic frames, trackers and manual registration.

  4. 3D-2D registration for surgical guidance: effect of projection view angles on registration accuracy

    NASA Astrophysics Data System (ADS)

    Uneri, A.; Otake, Y.; Wang, A. S.; Kleinszig, G.; Vogt, S.; Khanna, A. J.; Siewerdsen, J. H.

    2014-01-01

    An algorithm for intensity-based 3D-2D registration of CT and x-ray projections is evaluated, specifically using single- or dual-projection views to provide 3D localization. The registration framework employs the gradient information similarity metric and covariance matrix adaptation evolution strategy to solve for the patient pose in six degrees of freedom. Registration performance was evaluated in an anthropomorphic phantom and cadaver, using C-arm projection views acquired at angular separation, Δθ, ranging from ˜0°-180° at variable C-arm magnification. Registration accuracy was assessed in terms of 2D projection distance error and 3D target registration error (TRE) and compared to that of an electromagnetic (EM) tracker. The results indicate that angular separation as small as Δθ ˜10°-20° achieved TRE <2 mm with 95% confidence, comparable or superior to that of the EM tracker. The method allows direct registration of preoperative CT and planning data to intraoperative fluoroscopy, providing 3D localization free from conventional limitations associated with external fiducial markers, stereotactic frames, trackers and manual registration.

  5. 3D–2D registration for surgical guidance: effect of projection view angles on registration accuracy

    PubMed Central

    Uneri, A; Otake, Y; Wang, A S; Kleinszig, G; Vogt, S; Khanna, A J; Siewerdsen, J H

    2016-01-01

    An algorithm for intensity-based 3D–2D registration of CT and x-ray projections is evaluated, specifically using single- or dual-projection views to provide 3D localization. The registration framework employs the gradient information similarity metric and covariance matrix adaptation evolution strategy to solve for the patient pose in six degrees of freedom. Registration performance was evaluated in an anthropomorphic phantom and cadaver, using C-arm projection views acquired at angular separation, Δθ, ranging from ~0°–180° at variable C-arm magnification. Registration accuracy was assessed in terms of 2D projection distance error and 3D target registration error (TRE) and compared to that of an electromagnetic (EM) tracker. The results indicate that angular separation as small as Δθ ~10°–20° achieved TRE <2 mm with 95% confidence, comparable or superior to that of the EM tracker. The method allows direct registration of preoperative CT and planning data to intraoperative fluoroscopy, providing 3D localization free from conventional limitations associated with external fiducial markers, stereotactic frames, trackers and manual registration. PMID:24351769

  6. Undergraduate Cross Registration.

    ERIC Educational Resources Information Center

    Grupe, Fritz H.

    This report discusses various aspects of undergraduate cross-registration procedures, including the dimensions, values, roles and functions, basic assumptions, and facilitating and encouragment of cross-registration. Dimensions of cross-registration encompass financial exchange, eligibility, program limitations, type of grade and credit; extent of…

  7. Algebraic mesh quality metrics

    SciTech Connect

    KNUPP,PATRICK

    2000-04-24

    Quality metrics for structured and unstructured mesh generation are placed within an algebraic framework to form a mathematical theory of mesh quality metrics. The theory, based on the Jacobian and related matrices, provides a means of constructing, classifying, and evaluating mesh quality metrics. The Jacobian matrix is factored into geometrically meaningful parts. A nodally-invariant Jacobian matrix can be defined for simplicial elements using a weight matrix derived from the Jacobian matrix of an ideal reference element. Scale and orientation-invariant algebraic mesh quality metrics are defined. the singular value decomposition is used to study relationships between metrics. Equivalence of the element condition number and mean ratio metrics is proved. Condition number is shown to measure the distance of an element to the set of degenerate elements. Algebraic measures for skew, length ratio, shape, volume, and orientation are defined abstractly, with specific examples given. Combined metrics for shape and volume, shape-volume-orientation are algebraically defined and examples of such metrics are given. Algebraic mesh quality metrics are extended to non-simplical elements. A series of numerical tests verify the theoretical properties of the metrics defined.

  8. About Using the Metric System.

    ERIC Educational Resources Information Center

    Illinois State Office of Education, Springfield.

    This booklet contains a brief introduction to the use of the metric system. Topics covered include: (1) what is the metric system; (2) how to think metric; (3) some advantages of the metric system; (4) basics of the metric system; (5) how to measure length, area, volume, mass and temperature the metric way; (6) some simple calculations using…

  9. SU-E-J-100: The Combination of Deformable Image Registration and Regions-Of-Interest Mapping Technique to Accomplish Accurate Dose Calculation On Cone Beam Computed Tomography for Esophageal Cancer

    SciTech Connect

    Huang, B-T; Lu, J-Y

    2015-06-15

    Purpose: We introduce a new method combined with the deformable image registration (DIR) and regions-of-interest mapping (ROIM) technique to accurately calculate dose on daily CBCT for esophageal cancer. Methods: Patients suffered from esophageal cancer were enrolled in the study. Prescription was set to 66 Gy/30 F and 54 Gy/30 F to the primary tumor (PTV66) and subclinical disease (PTV54) . Planning CT (pCT) were segmented into 8 substructures in terms of their differences in physical density, such as gross target volume (GTV), venae cava superior (SVC), aorta, heart, spinal cord, lung, muscle and bones. The pCT and its substructures were transferred to the MIM software to readout their mean HU values. Afterwards, a deformable planning CT to daily KV-CBCT image registration method was then utilized to acquire a new structure set on CBCT. The newly generated structures on CBCT were then transferred back to the treatment planning system (TPS) and its HU information were overridden manually with mean HU values obtained from pCT. Finally, the treatment plan was projected onto the CBCT images with the same beam arrangements and monitor units (MUs) to accomplish dose calculation. Planning target volume (PTV) and organs at risk (OARs) from both of the pCT and CBCT were compared to evaluate the dose calculation accuracy. Results: It was found that the dose distribution in the CBCT showed little differences compared to the pCT, regardless of whether PTV or OARs were concerned. Specifically, dose variation in GTV, PTV54, PTV66, SVC, lung and heart were within 0.1%. The maximum dose variation was presented in the spinal cord, which was up to 2.7% dose difference. Conclusion: The proposed method combined with DIR and ROIM technique to accurately calculate dose distribution on CBCT for esophageal cancer is feasible.

  10. Topics in Metric Approximation

    NASA Astrophysics Data System (ADS)

    Leeb, William Edward

    This thesis develops effective approximations of certain metrics that occur frequently in pure and applied mathematics. We show that distances that often arise in applications, such as the Earth Mover's Distance between two probability measures, can be approximated by easily computed formulas for a wide variety of ground distances. We develop simple and easily computed characterizations both of norms measuring a function's regularity -- such as the Lipschitz norm -- and of their duals. We are particularly concerned with the tensor product of metric spaces, where the natural notion of regularity is not the Lipschitz condition but the mixed Lipschitz condition. A theme that runs throughout this thesis is that snowflake metrics (metrics raised to a power less than 1) are often better-behaved than ordinary metrics. For example, we show that snowflake metrics on finite spaces can be approximated by the average of tree metrics with a distortion bounded by intrinsic geometric characteristics of the space and not the number of points. Many of the metrics for which we characterize the Lipschitz space and its dual are snowflake metrics. We also present applications of the characterization of certain regularity norms to the problem of recovering a matrix that has been corrupted by noise. We are able to achieve an optimal rate of recovery for certain families of matrices by exploiting the relationship between mixed-variable regularity conditions and the decay of a function's coefficients in a certain orthonormal basis.

  11. Piecewise-diffeomorphic image registration: application to the motion estimation between 3D CT lung images with sliding conditions.

    PubMed

    Risser, Laurent; Vialard, François-Xavier; Baluwala, Habib Y; Schnabel, Julia A

    2013-02-01

    In this paper, we propose a new strategy for modelling sliding conditions when registering 3D images in a piecewise-diffeomorphic framework. More specifically, our main contribution is the development of a mathematical formalism to perform Large Deformation Diffeomorphic Metric Mapping registration with sliding conditions. We also show how to adapt this formalism to the LogDemons diffeomorphic registration framework. We finally show how to apply this strategy to estimate the respiratory motion between 3D CT pulmonary images. Quantitative tests are performed on 2D and 3D synthetic images, as well as on real 3D lung images from the MICCAI EMPIRE10 challenge. Results show that our strategy estimates accurate mappings of entire 3D thoracic image volumes that exhibit a sliding motion, as opposed to conventional registration methods which are not capable of capturing discontinuous deformations at the thoracic cage boundary. They also show that although the deformations are not smooth across the location of sliding conditions, they are almost always invertible in the whole image domain. This would be helpful for radiotherapy planning and delivery. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

  12. Bayesian technique for image classifying registration.

    PubMed

    Hachama, Mohamed; Desolneux, Agnès; Richard, Frédéric J P

    2012-09-01

    In this paper, we address a complex image registration issue arising while the dependencies between intensities of images to be registered are not spatially homogeneous. Such a situation is frequently encountered in medical imaging when a pathology present in one of the images modifies locally intensity dependencies observed on normal tissues. Usual image registration models, which are based on a single global intensity similarity criterion, fail to register such images, as they are blind to local deviations of intensity dependencies. Such a limitation is also encountered in contrast-enhanced images where there exist multiple pixel classes having different properties of contrast agent absorption. In this paper, we propose a new model in which the similarity criterion is adapted locally to images by classification of image intensity dependencies. Defined in a Bayesian framework, the similarity criterion is a mixture of probability distributions describing dependencies on two classes. The model also includes a class map which locates pixels of the two classes and weighs the two mixture components. The registration problem is formulated both as an energy minimization problem and as a maximum a posteriori estimation problem. It is solved using a gradient descent algorithm. In the problem formulation and resolution, the image deformation and the class map are estimated simultaneously, leading to an original combination of registration and classification that we call image classifying registration. Whenever sufficient information about class location is available in applications, the registration can also be performed on its own by fixing a given class map. Finally, we illustrate the interest of our model on two real applications from medical imaging: template-based segmentation of contrast-enhanced images and lesion detection in mammograms. We also conduct an evaluation of our model on simulated medical data and show its ability to take into account spatial variations

  13. 32 CFR 263.4 - Registration of vehicles.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 32 National Defense 2 2012-07-01 2012-07-01 false Registration of vehicles. 263.4 Section 263.4...) MISCELLANEOUS TRAFFIC AND VEHICLE CONTROL ON CERTAIN DEFENSE MAPPING AGENCY SITES § 263.4 Registration of vehicles. (a) Newly assigned or employed individuals who intend to operate a privately-owned vehicle at...

  14. 32 CFR 263.4 - Registration of vehicles.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 32 National Defense 2 2014-07-01 2014-07-01 false Registration of vehicles. 263.4 Section 263.4...) MISCELLANEOUS TRAFFIC AND VEHICLE CONTROL ON CERTAIN DEFENSE MAPPING AGENCY SITES § 263.4 Registration of vehicles. (a) Newly assigned or employed individuals who intend to operate a privately-owned vehicle at...

  15. 32 CFR 263.4 - Registration of vehicles.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 2 2010-07-01 2010-07-01 false Registration of vehicles. 263.4 Section 263.4...) MISCELLANEOUS TRAFFIC AND VEHICLE CONTROL ON CERTAIN DEFENSE MAPPING AGENCY SITES § 263.4 Registration of vehicles. (a) Newly assigned or employed individuals who intend to operate a privately-owned vehicle at...

  16. Invariant metrics, contractions and nonlinear matrix equations

    NASA Astrophysics Data System (ADS)

    Lee, Hosoo; Lim, Yongdo

    2008-04-01

    In this paper we consider the semigroup generated by the self-maps on the open convex cone of positive definite matrices of translations, congruence transformations and matrix inversion that includes symplectic Hamiltonians and show that every member of the semigroup contracts any invariant metric distance inherited from a symmetric gauge function. This extends the results of Bougerol for the Riemannian metric and of Liverani-Wojtkowski for the Thompson part metric. A uniform upper bound of the Lipschitz contraction constant for a member of the semigroup is given in terms of the minimum eigenvalues of its determining matrices. We apply this result to a variety of nonlinear equations including Stein and Riccati equations for uniqueness and existence of positive definite solutions and find a new convergence analysis of iterative algorithms for the positive definite solution depending only on the least contraction coefficient for the invariant metric from the spectral norm.

  17. Research on land registration procedure ontology of China

    NASA Astrophysics Data System (ADS)

    Zhao, Zhongjun; Du, Qingyun; Zhang, Weiwei; Liu, Tao

    2009-10-01

    Land registration is public act which is to record the state-owned land use right, collective land ownership, collective land use right and land mortgage, servitude, as well as other land rights required the registration according to laws and regulations onto land registering books. Land registration is one of the important government affairs , so it is very important to standardize, optimize and humanize the process of land registration. The management works of organization are realized through a variety of workflows. Process knowledge is in essence a kind of methodology knowledge and a system which including the core and the relational knowledge. In this paper, the ontology is introduced into the field of land registration and management, trying to optimize the flow of land registration, to promote the automation-building and intelligent Service of land registration affairs, to provide humanized and intelligent service for multi-types of users . This paper tries to build land registration procedure ontology by defining the land registration procedure ontology's key concepts which represent the kinds of processes of land registration and mapping the kinds of processes to OWL-S. The land registration procedure ontology shall be the start and the basis of the Web service.

  18. Metrics for Blueprint Reading.

    ERIC Educational Resources Information Center

    Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.

    Designed to meet the job-related metric measurement needs of blueprint reading students, this instructional package is one of eight for the manufacturing occupations cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational terminology, measurement…

  19. Metrics for Food Distribution.

    ERIC Educational Resources Information Center

    Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.

    Designed to meet the job-related metric measurement needs of students interested in food distribution, this instructional package is one of five for the marketing and distribution cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational…

  20. Metrics for Transportation.

    ERIC Educational Resources Information Center

    Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.

    Designed to meet the job-related metric measurement needs of students interested in transportation, this instructional package is one of five for the marketing and distribution cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational terminology,…

  1. Surveillance Metrics Sensitivity Study

    SciTech Connect

    Bierbaum, R; Hamada, M; Robertson, A

    2011-11-01

    In September of 2009, a Tri-Lab team was formed to develop a set of metrics relating to the NNSA nuclear weapon surveillance program. The purpose of the metrics was to develop a more quantitative and/or qualitative metric(s) describing the results of realized or non-realized surveillance activities on our confidence in reporting reliability and assessing the stockpile. As a part of this effort, a statistical sub-team investigated various techniques and developed a complementary set of statistical metrics that could serve as a foundation for characterizing aspects of meeting the surveillance program objectives. The metrics are a combination of tolerance limit calculations and power calculations, intending to answer level-of-confidence type questions with respect to the ability to detect certain undesirable behaviors (catastrophic defects, margin insufficiency defects, and deviations from a model). Note that the metrics are not intended to gauge product performance but instead the adequacy of surveillance. This report gives a short description of four metrics types that were explored and the results of a sensitivity study conducted to investigate their behavior for various inputs. The results of the sensitivity study can be used to set the risk parameters that specify the level of stockpile problem that the surveillance program should be addressing.

  2. Surveillance metrics sensitivity study.

    SciTech Connect

    Hamada, Michael S.; Bierbaum, Rene Lynn; Robertson, Alix A.

    2011-09-01

    In September of 2009, a Tri-Lab team was formed to develop a set of metrics relating to the NNSA nuclear weapon surveillance program. The purpose of the metrics was to develop a more quantitative and/or qualitative metric(s) describing the results of realized or non-realized surveillance activities on our confidence in reporting reliability and assessing the stockpile. As a part of this effort, a statistical sub-team investigated various techniques and developed a complementary set of statistical metrics that could serve as a foundation for characterizing aspects of meeting the surveillance program objectives. The metrics are a combination of tolerance limit calculations and power calculations, intending to answer level-of-confidence type questions with respect to the ability to detect certain undesirable behaviors (catastrophic defects, margin insufficiency defects, and deviations from a model). Note that the metrics are not intended to gauge product performance but instead the adequacy of surveillance. This report gives a short description of four metrics types that were explored and the results of a sensitivity study conducted to investigate their behavior for various inputs. The results of the sensitivity study can be used to set the risk parameters that specify the level of stockpile problem that the surveillance program should be addressing.

  3. Arbitrary Metrics in Psychology

    ERIC Educational Resources Information Center

    Blanton, Hart; Jaccard, James

    2006-01-01

    Many psychological tests have arbitrary metrics but are appropriate for testing psychological theories. Metric arbitrariness is a concern, however, when researchers wish to draw inferences about the true, absolute standing of a group or individual on the latent psychological dimension being measured. The authors illustrate this in the context of 2…

  4. Metric Education Evaluation Package.

    ERIC Educational Resources Information Center

    Kansky, Bob; And Others

    This document was developed out of a need for a complete, carefully designed set of evaluation instruments and procedures that might be applied in metric inservice programs across the nation. Components of this package were prepared in such a way as to permit local adaptation to the evaluation of a broad spectrum of metric education activities.…

  5. Metrics for Cosmetology.

    ERIC Educational Resources Information Center

    Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.

    Designed to meet the job-related metric measurement needs of cosmetology students, this instructional package on cosmetology is part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational terminology, measurement terms, and tools currently in use. Each of the…

  6. Metrics for Aviation Electronics.

    ERIC Educational Resources Information Center

    Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.

    Designed to meet the job-related metric measurement needs of aviation electronics students, this instructional package is one of four for the transportation occupations cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational terminology,…

  7. Arbitrary Metrics in Psychology

    ERIC Educational Resources Information Center

    Blanton, Hart; Jaccard, James

    2006-01-01

    Many psychological tests have arbitrary metrics but are appropriate for testing psychological theories. Metric arbitrariness is a concern, however, when researchers wish to draw inferences about the true, absolute standing of a group or individual on the latent psychological dimension being measured. The authors illustrate this in the context of 2…

  8. Metrics for Dental Assistants.

    ERIC Educational Resources Information Center

    Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.

    Designed to meet the job-related metric measurement needs of students interested in becoming dental assistants, this instructional package is one of five for the health occupations cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational…

  9. A Measured Metric Statement.

    ERIC Educational Resources Information Center

    Gaughan, Edward D.; Wisner, Robert J.

    1981-01-01

    A middle-road approach towards adopting the instruction of the metric system is presented. The realities of our cultural, economic, and political processes are taken into account and a 100 percent metric curriculum is viewed as unrealistic and anachronistic. (MP)

  10. Metrics for Fire Service.

    ERIC Educational Resources Information Center

    Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.

    Designed to meet the job-related metric measurement needs of students interested in fire science education, this instructional package is one of two for the public service occupations cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational…

  11. Supporting registration decisions during 3D medical volume reconstructions

    NASA Astrophysics Data System (ADS)

    Bajcsy, Peter; Lee, Sang-Chul; Clutter, David

    2006-03-01

    We propose a methodology for making optimal registration decisions during 3D volume reconstruction in terms of (a) anticipated accuracy of aligned images, (b) uncertainty of obtained results during the registration process, (c) algorithmic repeatability of alignment procedure, and (d) computational requirements. We researched and developed a web-enabled, web services based, data-driven, registration decision support system. The registration decisions include (1) image spatial size (image sub-area or entire image), (2) transformation model (e.g., rigid, affine or elastic), (3) invariant registration feature (intensity, morphology or a sequential combination of the two), (4) automation level (manual, semi-automated, or fully-automated), (5) evaluations of registration results (multiple metrics and methods for establishing ground truth), and (6) assessment of resources (computational resources and human expertise, geographically local or distributed). Our goal is to provide mechanisms for evaluating the tradeoffs of each registration decision in terms of the aforementioned impacts. First, we present a medical registration methodology for making registration decisions that lead to registration results with well-understood accuracy, uncertainty, consistency and computational complexity characteristics. Second, we have built software tools that enable geographically distributed researchers to optimize their data-driven registration decisions by using web services and supercomputing resources. The support developed for registration decisions about 3D volume reconstruction is available to the general community with the access to the NCSA supercomputing resources. We illustrate performance by considering 3D volume reconstruction of blood vessels in histological sections of uveal melanoma from serial fluorescent labeled paraffin sections labeled with antibodies to CD34 and laminin. The specimens are studied by fluorescence confocal laser scanning microscopy (CLSM) images.

  12. The Science News Metrics

    NASA Astrophysics Data System (ADS)

    Christian, Carol A.; Davidson, Greg

    2006-01-01

    Scientists, observatories, academic institutions and funding agencies persistently review the usefulness and productivity of investment in scientific research. The Science News Metrics was created over 10 years ago to review NASA's performance in this arena. The metric has been useful for many years as one facet in measuring the scientific discovery productivity of NASA-funded missions. The metric is computed independently of the agency and has been compiled in a consistent manner. Examination of the metric yields year-by-year insight into NASA science successes in a world wide context. The metric has shown that NASA's contribution to worldwide top science news stories has been approximately 5% overall with the Hubble Space Telescope dominating the performance.

  13. Image Registration Workshop Proceedings

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline (Editor)

    1997-01-01

    Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research.

  14. An image registration pipeline for analysis of transsynaptic tracing in mice

    NASA Astrophysics Data System (ADS)

    Kutten, Kwame S.; Eacker, Stephen M.; Dawson, Valina L.; Dawson, Ted M.; Ratnanather, Tilak; Miller, Michael I.

    2016-03-01

    Parkinson's Disease (PD) is a movement disorder characterized by the loss of dopamine neurons in the substantia nigra pars compacta (SNpc) and norepinephrine neurons in the locus coeruleus (LC). To further understand the pathophysiology of PD, the input neurons of the SNpc and LC will be transsynapticly traced in mice using a fluorescent recombinant rabies virus (RbV) and imaged using serial two-photon tomography (STP). A mapping between these images and a brain atlas must be found to accurately determine the locations of input neurons in the brain. Therefore a registration pipeline to align the Allen Reference Atlas (ARA) to these types of images was developed. In the preprocessing step, a brain mask was generated from the transsynaptic tracing images using simple morphological operators. The masks were then registered to the ARA using Large Deformation Diffeomorphic Metric Mapping (LDDMM), an algorithm specialized for calculating anatomically realistic transforms between images. The pipeline was then tested on an STP scan of a mouse brain labeled by an adeno-associated virus (AAV). Based on qualitative evaluation of the registration results, the pipeline was found to be sufficient for use with transsynaptic RbV tracing.

  15. 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.

  16. Registration and rectification needs of geology

    NASA Technical Reports Server (NTRS)

    Chavez, P. S., Jr.

    1982-01-01

    Geologic applications of remotely sensed imaging encompass five areas of interest. The five areas include: (1) enhancement and analysis of individual images; (2) work with small area mosaics of imagery which have been map projection rectified to individual quadrangles; (3) development of large area mosaics of multiple images for several counties or states; (4) registration of multitemporal images; and (5) data integration from several sensors and map sources. Examples for each of these types of applications are summarized.

  17. Image quality metrics applied to digital pathology

    NASA Astrophysics Data System (ADS)

    Jiménez, Ana; Bueno, Gloria; Cristóbal, Gabriel; Déniz, Oscar; Toomey, David; Conway, Catherine

    2016-04-01

    Several full-reference and blind metrics from literature have been tested on a set of digitized pathology slides under different known distortion conditions. Those ones showing the most uniform behavior are presented in this paper. Also, an algorithm that provides a blur map of the whole slide images (WSIs) has been implemented based on one of such methods.

  18. Evaluation of Thematic Mapper interband registration and noise characteristics

    NASA Technical Reports Server (NTRS)

    Wrigley, R. C.; Hlavka, C. A.; Card, D. H.; Buis, J. S.

    1985-01-01

    It is pointed out that the Thematic Mapper (TM) instruments aboard the Landsat-4 and Landsat-5 spacecraft have provided the first digital imagery of the earth's surface with a resolution sufficient to distinguish cultural features easily. The present paper provides a description of the results of studies designed to investigate the band-to-band registration, geodetic registration to a map base, and periodic noise. In the eight TM scenes analyzed, the band-to-band registration accuracy was high even before correction, and the correction for the shift between focal planes brought all bands into registration according to tight specifications.

  19. Holographic Spherically Symmetric Metrics

    NASA Astrophysics Data System (ADS)

    Petri, Michael

    The holographic principle (HP) conjectures, that the maximum number of degrees of freedom of any realistic physical system is proportional to the system's boundary area. The HP has its roots in the study of black holes. It has recently been applied to cosmological solutions. In this article we apply the HP to spherically symmetric static space-times. We find that any regular spherically symmetric object saturating the HP is subject to tight constraints on the (interior) metric, energy-density, temperature and entropy-density. Whenever gravity can be described by a metric theory, gravity is macroscopically scale invariant and the laws of thermodynamics hold locally and globally, the (interior) metric of a regular holographic object is uniquely determined up to a constant factor and the interior matter-state must follow well defined scaling relations. When the metric theory of gravity is general relativity, the interior matter has an overall string equation of state (EOS) and a unique total energy-density. Thus the holographic metric derived in this article can serve as simple interior 4D realization of Mathur's string fuzzball proposal. Some properties of the holographic metric and its possible experimental verification are discussed. The geodesics of the holographic metric describe an isotropically expanding (or contracting) universe with a nearly homogeneous matter-distribution within the local Hubble volume. Due to the overall string EOS the active gravitational mass-density is zero, resulting in a coasting expansion with Ht = 1, which is compatible with the recent GRB-data.

  20. Registration in neurosurgery and neuroradiotherapy applications.

    PubMed

    Cuchet, E; Knoplioch, J; Dormont, D; Marsault, C

    1995-01-01

    Because of the high level of accuracy needed in neurosurgery, many computer-assisted surgery (CAS) and augmented reality techniques have been developed in this field. A common issue with all of these techniques is registration between preoperative three-dimensional images (computed tomography and magnetic resonance imaging) and the patient in the operating room. We present, in the first part of this paper, a survey of the latest CAS technologies, using fully automatic registration without fiducial landmarks. All of the registration algorithms described are based on minimization of a cost function. We then describe our approach. Our cost function is simply the mean square error (MSE), minimized by the iterative closest point algorithm (ICP). Because the weak point of the ICP algorithm is the closest point computational cost, we precalculate it by a "closest point map," inspired from classical distance map. We finally perturb the found solution to eliminate local minima close to the global minimum. This paper summarizes the various methods presented. We study the shape of the different cost functions and show that there is no need for a complex cost function. MSE has sufficiently good convergence properties to reach a position very close to the global minimum. We also demonstrate the influence of a final perturbation of the found solution to improve registration. Finally, we test the registration on different regions of the patient's head.

  1. “Nonparametric Local Smoothing” is not image registration

    PubMed Central

    2012-01-01

    Background Image registration is one of the most important and universally useful computational tasks in biomedical image analysis. A recent article by Xing & Qiu (IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(10):2081–2092, 2011) is based on an inappropriately narrow conceptualization of the image registration problem as the task of making two images look alike, which disregards whether the established spatial correspondence is plausible. The authors propose a new algorithm, Nonparametric Local Smoothing (NLS) for image registration, but use image similarities alone as a measure of registration performance, although these measures do not relate reliably to the realism of the correspondence map. Results Using data obtained from its authors, we show experimentally that the method proposed by Xing & Qiu is not an effective registration algorithm. While it optimizes image similarity, it does not compute accurate, interpretable transformations. Even judged by image similarity alone, the proposed method is consistently outperformed by a simple pixel permutation algorithm, which is known by design not to compute valid registrations. Conclusions This study has demonstrated that the NLS algorithm proposed recently for image registration, and published in one of the most respected journals in computer science, is not, in fact, an effective registration method at all. Our results also emphasize the general need to apply registration evaluation criteria that are sensitive to whether correspondences are accurate and mappings between images are physically interpretable. These goals cannot be achieved by simply reporting image similarities. PMID:23116330

  2. Accuracy of cancer registration.

    PubMed Central

    West, R R

    1976-01-01

    In South Wales cancer registration is done principally by means of the Hospital Activity Analysis. Altogether 1460 hospital records of cancer patients (19% of the 1972 registrations received by May 1973) were studied and the principal items of information required for cancer registrations by the Office of Population Censuses and Surveys were copied and subsequently compared with the corresponding registrations at the Welsh Hospital Board's cancer bureau. Differences between these 're-registrations' and the original registrations were analysed item by item. There were 234 registrations with errors in the diagnostic summary (although 110 of these would cause misclassification only under the fourth digit of the ICD code), 164 with errors in date of birth (36 of which would cause classification in the wrong WHO age group) and 198 with errors in the date of registration (112 of which were wrongly ascribed to the year 1972). Error and omission rates were particularly high for NHS number, occupation, place of birth, and histology. PMID:974439

  3. DRAMMS: deformable registration via attribute matching and mutual-saliency weighting.

    PubMed

    Ou, Yangming; Davatzikos, Christos

    2009-01-01

    A general-purpose deformable registration algorithm referred to as "DRAMMS" is presented in this paper. DRAMMS adds to the literature of registration methods that bridge between the traditional voxel-wise methods and landmark/feature-based methods. In particular, DRAMMS extracts Gabor attributes at each voxel and selects the optimal components, so that they form a highly distinctive morphological signature reflecting the anatomical context around each voxel in a multi-scale and multi-resolution fashion. Compared with intensity or mutual-information based methods, the high-dimensional optimal Gabor attributes render different anatomical regions relatively distinctively identifiable and therefore help establish more accurate and reliable correspondence. Moreover, the optimal Gabor attribute vector is constructed in a way that generalizes well, i.e., it can be applied to different registration tasks, regardless of the image contents under registration. A second characteristic of DRAMMS is that it is based on a cost function that weights different voxel pairs according to a metric referred to as "mutual-saliency", which reflects the uniqueness (reliability) of anatomical correspondences implied by the tentative transformation. As a result, image voxels do not contribute equally to the optimization process, as in most voxel-wise methods, or in a binary selection fashion, as in most landmark/feature-based methods. Instead, they contribute according to a continuously-valued mutual-saliency map, which is dynamically updated during the algorithm's evolution. The general applicability and accuracy of DRAMMS are demonstrated by experiments in simulated images, inter-subject images, single-/multi-modality images, and longitudinal images, from human and mouse brains, breast, heart, and prostate.

  4. 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.

  5. User Registration Systems for Distributed Systems

    NASA Astrophysics Data System (ADS)

    Murphy, K. J.; Cechini, M.; Pilone, D.; Mitchell, A.

    2010-12-01

    As NASA’s Earth Observing System Data and Information System (EOSDIS) systems have evolved over the years, most of the EOSDIS data are now available to users via anonymous on-line access. Although the changes have improved the dissemination efficiency of earth science data, the anonymous access has made it difficult to characterize users, capture metrics on the value of EOSDIS and provide customized services that benefit users. As the number of web-based applications continues to grow, data centers and application providers have implemented their own user registration systems and provided new tools and interfaces for their registered users. This has led to the creation of independent registration systems for accessing data and interacting with online tools and services. The user profile information maintained at each of these registration systems is not consistent and the registration enforcement varies by system as well. This problem is in no way unique to EOSDIS and represents a general challenge to the distributed computing community. In a study done in 2007(http://www2007.org/papers/paper620.pd), the average user has approximately 7 passwords for about 25 accounts and enters a password 8 times a day. These numbers have only increased in the last three years. To try and address this, a number of solutions have been offered including Single Sign-On solutions using a common backend like Microsoft Active Directory or an LDAP server, trust based identity providers like OpenID, and various forms of authorization delegation like OAuth or SAML/XACML. This talk discusses the differences between authentication and authorization, the state of the more popular user registration solutions available for distributed use, and some of the technical and policy drivers that need to be considered when incorporating a user registration system into your application.

  6. TIMER: Tensor Image Morphing for Elastic Registration

    PubMed Central

    Yap, Pew-Thian; Wu, Guorong; Zhu, Hongtu; Lin, Weili; Shen, Dinggang

    2009-01-01

    We propose a novel diffusion tensor imaging (DTI) registration algorithm, called Tensor Image Morphing for Elastic Registration (TIMER), which leverages the hierarchical guidance of regional distributions and local boundaries, both extracted directly from the tensors. Currently available DTI registration methods generally extract tensor scalar features from each tensor to construct scalar maps. Subsequently, regional integration and other operations such as edge detection are performed to extract more features to guide the registration. However, there are two major limitations with these approaches. First, the computed regional features might not reflect the actual regional tensor distributions. Second, by the same token, gradient maps calculated from the tensor-derived scalar feature maps might not represent the actual tissue tensor boundaries. To overcome these limitations, we propose a new approach which extracts regional and edge information directly from a tensor neighborhood. Regional tensor distribution information, such as mean and variance, is computed in a multiscale fashion directly from the tensors by taking into account the voxel neighborhood of different sizes, and hence capturing tensor information at different scales, which in turn can be employed to hierarchically guide the registration. Such multiscale scheme can help alleviate the problem of local minimum and is also more robust to noise since one can better determine the statistical properties of each voxel by taking into account the properties of its surrounding. Also incorporated in our method is edge information extracted directly from the tensors, which is crucial to facilitate registration of tissue boundaries. Experiments involving real subjects, simulated subjects, fiber tracking, and atrophy detection indicate that TIMER performs better than the other methods in comparison (Yang et al., 2008a; Zhang et al., 2006). PMID:19398022

  7. TIMER: tensor image morphing for elastic registration.

    PubMed

    Yap, Pew-Thian; Wu, Guorong; Zhu, Hongtu; Lin, Weili; Shen, Dinggang

    2009-08-15

    We propose a novel diffusion tensor imaging (DTI) registration algorithm, called Tensor Image Morphing for Elastic Registration (TIMER), which leverages the hierarchical guidance of regional distributions and local boundaries, both extracted directly from the tensors. Currently available DTI registration methods generally extract tensor scalar features from each tensor to construct scalar maps. Subsequently, regional integration and other operations such as edge detection are performed to extract more features to guide the registration. However, there are two major limitations with these approaches. First, the computed regional features might not reflect the actual regional tensor distributions. Second, by the same token, gradient maps calculated from the tensor-derived scalar feature maps might not represent the actual tissue tensor boundaries. To overcome these limitations, we propose a new approach which extracts regional and edge information directly from a tensor neighborhood. Regional tensor distribution information, such as mean and variance, is computed in a multiscale fashion directly from the tensors by taking into account the voxel neighborhood of different sizes, and hence capturing tensor information at different scales, which in turn can be employed to hierarchically guide the registration. Such multiscale scheme can help alleviate the problem of local minimum and is also more robust to noise since one can better determine the statistical properties of each voxel by taking into account the properties of its surrounding. Also incorporated in our method is edge information extracted directly from the tensors, which is crucial to facilitate registration of tissue boundaries. Experiments involving real subjects, simulated subjects, fiber tracking, and atrophy detection indicate that TIMER performs better than the other methods (Yang et al., 2008; Zhang et al., 2006).

  8. Sustainability Indicators and Metrics

    EPA Science Inventory

    Sustainability is about preserving human existence. Indicators and metrics are absolutely necessary to provide at least a semi-quantitative assessment of progress towards or away from sustainability. Otherwise, it becomes impossible to objectively assess whether progress is bei...

  9. An Arithmetic Metric

    ERIC Educational Resources Information Center

    Dominici, Diego

    2011-01-01

    This work introduces a distance between natural numbers not based on their position on the real line but on their arithmetic properties. We prove some metric properties of this distance and consider a possible extension.

  10. General Motors Goes Metric

    ERIC Educational Resources Information Center

    Webb, Ted

    1976-01-01

    Describes the program to convert to the metric system all of General Motors Corporation products. Steps include establishing policy regarding employee-owned tools, setting up training plans, and making arrangements with suppliers. (MF)

  11. Sustainability Indicators and Metrics

    EPA Science Inventory

    Sustainability is about preserving human existence. Indicators and metrics are absolutely necessary to provide at least a semi-quantitative assessment of progress towards or away from sustainability. Otherwise, it becomes impossible to objectively assess whether progress is bei...

  12. An Arithmetic Metric

    ERIC Educational Resources Information Center

    Dominici, Diego

    2011-01-01

    This work introduces a distance between natural numbers not based on their position on the real line but on their arithmetic properties. We prove some metric properties of this distance and consider a possible extension.

  13. A metric for success

    NASA Astrophysics Data System (ADS)

    Carver, Gary P.

    1994-05-01

    The federal agencies are working with industry to ease adoption of the metric system. The goal is to help U.S. industry compete more successfully in the global marketplace, increase exports, and create new jobs. The strategy is to use federal procurement, financial assistance, and other business-related activities to encourage voluntary conversion. Based upon the positive experiences of firms and industries that have converted, federal agencies have concluded that metric use will yield long-term benefits that are beyond any one-time costs or inconveniences. It may be time for additional steps to move the Nation out of its dual-system comfort zone and continue to progress toward metrication. This report includes 'Metric Highlights in U.S. History'.

  14. Enterprise Sustainment Metrics

    DTIC Science & Technology

    The Air Force sustainment enterprise does not have metrics that . . . adequately measure key sustainment parameters, according to the 2011 National...Research Council of the National Academies study, Examination of the U.S. Air Force’s Aircraft Sustainment Needs in the Future and Its Strategy to Meet...standardized and do not contribute to the overall assessment of the sustainment enterprise. This paper explores the development of a single metric

  15. Registration of 4D time-series of cardiac images with multichannel Diffeomorphic Demons.

    PubMed

    Peyrat, Jean-Marc; Delingette, Hervé; Sermesant, Maxime; Pennec, Xavier; Xu, Chenyang; Ayache, Nicholas

    2008-01-01

    In this paper, we propose a generic framework for intersubject non-linear registration of 4D time-series images. In this framework, spatio-temporal registration is defined by mapping trajectories of physical points as opposed to spatial registration that solely aims at mapping homologous points. First, we determine the trajectories we want to register in each sequence using a motion tracking algorithm based on the Diffeomorphic Demons algorithm. Then, we perform simultaneously pairwise registrations of corresponding time-points with the constraint to map the same physical points over time. We show this trajectory registration can be formulated as a multichannel registration of 3D images. We solve it using the Diffeomorphic Demons algorithm extended to vector-valued 3D images. This framework is applied to the inter-subject non-linear registration of 4D cardiac CT sequences.

  16. MRI signal intensity based B-spline nonrigid registration for pre- and intraoperative imaging during prostate brachytherapy.

    PubMed

    Oguro, Sota; Tokuda, Junichi; Elhawary, Haytham; Haker, Steven; Kikinis, Ron; Tempany, Clare M C; Hata, Nobuhiko

    2009-11-01

    To apply an intensity-based nonrigid registration algorithm to MRI-guided prostate brachytherapy clinical data and to assess its accuracy. A nonrigid registration of preoperative MRI to intraoperative MRI images was carried out in 16 cases using a Basis-Spline algorithm in a retrospective manner. The registration was assessed qualitatively by experts' visual inspection and quantitatively by measuring the Dice similarity coefficient (DSC) for total gland (TG), central gland (CG), and peripheral zone (PZ), the mutual information (MI) metric, and the fiducial registration error (FRE) between corresponding anatomical landmarks for both the nonrigid and a rigid registration method. All 16 cases were successfully registered in less than 5 min. After the nonrigid registration, DSC values for TG, CG, PZ were 0.91, 0.89, 0.79, respectively, the MI metric was -0.19 +/- 0.07 and FRE presented a value of 2.3 +/- 1.8 mm. All the metrics were significantly better than in the case of rigid registration, as determined by one-sided t-tests. The intensity-based nonrigid registration method using clinical data was demonstrated to be feasible and showed statistically improved metrics when compare to only rigid registration. The method is a valuable tool to integrate pre- and intraoperative images for brachytherapy.

  17. MRI Signal Intensity Based B-Spline Nonrigid Registration for Pre- and Intraoperative Imaging During Prostate Brachytherapy

    PubMed Central

    Oguro, Sota; Tokuda, Junichi; Elhawary, Haytham; Haker, Steven; Kikinis, Ron; Tempany, Clare M.C.; Hata, Nobuhiko

    2009-01-01

    Purpose To apply an intensity-based nonrigid registration algorithm to MRI-guided prostate brachytherapy clinical data and to assess its accuracy. Materials and Methods A nonrigid registration of preoperative MRI to intraoperative MRI images was carried out in 16 cases using a Basis-Spline algorithm in a retrospective manner. The registration was assessed qualitatively by experts’ visual inspection and quantitatively by measuring the Dice similarity coefficient (DSC) for total gland (TG), central gland (CG), and peripheral zone (PZ), the mutual information (MI) metric, and the fiducial registration error (FRE) between corresponding anatomical landmarks for both the nonrigid and a rigid registration method. Results All 16 cases were successfully registered in less than 5 min. After the nonrigid registration, DSC values for TG, CG, PZ were 0.91, 0.89, 0.79, respectively, the MI metric was −0.19 ± 0.07 and FRE presented a value of 2.3 ± 1.8 mm. All the metrics were significantly better than in the case of rigid registration, as determined by one-sided t-tests. Conclusion The intensity-based nonrigid registration method using clinical data was demonstrated to be feasible and showed statistically improved metrics when compare to only rigid registration. The method is a valuable tool to integrate pre- and intraoperative images for brachytherapy. PMID:19856437

  18. Reproducibility of graph metrics in FMRI networks.

    PubMed

    Telesford, Qawi K; Morgan, Ashley R; Hayasaka, Satoru; Simpson, Sean L; Barret, William; Kraft, Robert A; Mozolic, Jennifer L; Laurienti, Paul J

    2010-01-01

    The reliability of graph metrics calculated in network analysis is essential to the interpretation of complex network organization. These graph metrics are used to deduce the small-world properties in networks. In this study, we investigated the test-retest reliability of graph metrics from functional magnetic resonance imaging data collected for two runs in 45 healthy older adults. Graph metrics were calculated on data for both runs and compared using intraclass correlation coefficient (ICC) statistics and Bland-Altman (BA) plots. ICC scores describe the level of absolute agreement between two measurements and provide a measure of reproducibility. For mean graph metrics, ICC scores were high for clustering coefficient (ICC = 0.86), global efficiency (ICC = 0.83), path length (ICC = 0.79), and local efficiency (ICC = 0.75); the ICC score for degree was found to be low (ICC = 0.29). ICC scores were also used to generate reproducibility maps in brain space to test voxel-wise reproducibility for unsmoothed and smoothed data. Reproducibility was uniform across the brain for global efficiency and path length, but was only high in network hubs for clustering coefficient, local efficiency, and degree. BA plots were used to test the measurement repeatability of all graph metrics. All graph metrics fell within the limits for repeatability. Together, these results suggest that with exception of degree, mean graph metrics are reproducible and suitable for clinical studies. Further exploration is warranted to better understand reproducibility across the brain on a voxel-wise basis.

  19. Active registration models

    NASA Astrophysics Data System (ADS)

    Marstal, Kasper; Klein, Stefan

    2017-02-01

    We present the Active Registration Model (ARM) that couples medical image registration with regularization using a statistical model of intensity. Inspired by Active Appearance Models (AAMs), the statistical model is embedded in the registration procedure as a regularization term that penalize differences between a target image and a synthesized model reconstruction of that image. We demonstrate that the method generalizes AAMs to 3D images, many different transformation models, and many different gradient descent optimization methods. The method is validated on magnetic resonance images of human brains.

  20. Discrimination of dementia with Lewy bodies from Alzheimer's disease using voxel-based morphometry of white matter by statistical parametric mapping 8 plus diffeomorphic anatomic registration through exponentiated Lie algebra.

    PubMed

    Nakatsuka, Tomoya; Imabayashi, Etsuko; Matsuda, Hiroshi; Sakakibara, Ryuji; Inaoka, Tsutomu; Terada, Hitoshi

    2013-05-01

    The purpose of this study was to identify brain atrophy specific for dementia with Lewy bodies (DLB) and to evaluate the discriminatory performance of this specific atrophy between DLB and Alzheimer's disease (AD). We retrospectively reviewed 60 DLB and 30 AD patients who had undergone 3D T1-weighted MRI. We randomly divided the DLB patients into two equal groups (A and B). First, we obtained a target volume of interest (VOI) for DLB-specific atrophy using correlation analysis of the percentage rate of significant whole white matter (WM) atrophy calculated using the Voxel-based Specific Regional Analysis System for Alzheimer's Disease (VSRAD) based on statistical parametric mapping 8 (SPM8) plus diffeomorphic anatomic registration through exponentiated Lie algebra, with segmented WM images in group A. We then evaluated the usefulness of this target VOI for discriminating the remaining 30 DLB patients in group B from the 30 AD patients. Z score values in this target VOI obtained from VSRAD were used as the determinant in receiver operating characteristic (ROC) analysis. Specific target VOIs for DLB were determined in the right-side dominant dorsal midbrain, right-side dominant dorsal pons, and bilateral cerebellum. ROC analysis revealed that the target VOI limited to the midbrain exhibited the highest area under the ROC curves of 0.75. DLB patients showed specific atrophy in the midbrain, pons, and cerebellum. Midbrain atrophy demonstrated the highest power for discriminating DLB and AD. This approach may be useful for determining the contributions of DLB and AD pathologies to the dementia syndrome.

  1. Towards a physics on fractals: Differential vector calculus in three-dimensional continuum with fractal metric

    NASA Astrophysics Data System (ADS)

    Balankin, Alexander S.; Bory-Reyes, Juan; Shapiro, Michael

    2016-02-01

    One way to deal with physical problems on nowhere differentiable fractals is the mapping of these problems into the corresponding problems for continuum with a proper fractal metric. On this way different definitions of the fractal metric were suggested to account for the essential fractal features. In this work we develop the metric differential vector calculus in a three-dimensional continuum with a non-Euclidean metric. The metric differential forms and Laplacian are introduced, fundamental identities for metric differential operators are established and integral theorems are proved by employing the metric version of the quaternionic analysis for the Moisil-Teodoresco operator, which has been introduced and partially developed in this paper. The relations between the metric and conventional operators are revealed. It should be emphasized that the metric vector calculus developed in this work provides a comprehensive mathematical formalism for the continuum with any suitable definition of fractal metric. This offers a novel tool to study physics on fractals.

  2. Registration Review Schedules

    EPA Pesticide Factsheets

    This schedule indicates plans for completion of risk assessments, proposed interim decisions and interim decisions for pesticides in the Registration Review program, EPA reviews all registered pesticides at least every 15 years as required by FIFRA.

  3. CSPP CDX Registration Guide

    EPA Pesticide Factsheets

    CDX allows users submitting data to the EPA to register for the specific program of interest. This Guide describes the registration process and information requirements associated with Submissions for the Chemical Safety and Pesticide Programs (CSPP).

  4. Lesson 6: Registration

    EPA Pesticide Factsheets

    Lesson 6 provides checklist items 1 through 4 are grouped under the Registration Process, where users establish their accounts in the system. This process typically requires users to provide information about them.

  5. Registration of Enlist Duo

    EPA Pesticide Factsheets

    EPA is proposing to amend the registration of Enlist Duo to allow use on GE cotton in the original 15 states and extend the use of Enlist Duo on GE corn, soybean and cotton to an additional 19 states.

  6. Fault Management Metrics

    NASA Technical Reports Server (NTRS)

    Johnson, Stephen B.; Ghoshal, Sudipto; Haste, Deepak; Moore, Craig

    2017-01-01

    This paper describes the theory and considerations in the application of metrics to measure the effectiveness of fault management. Fault management refers here to the operational aspect of system health management, and as such is considered as a meta-control loop that operates to preserve or maximize the system's ability to achieve its goals in the face of current or prospective failure. As a suite of control loops, the metrics to estimate and measure the effectiveness of fault management are similar to those of classical control loops in being divided into two major classes: state estimation, and state control. State estimation metrics can be classified into lower-level subdivisions for detection coverage, detection effectiveness, fault isolation and fault identification (diagnostics), and failure prognosis. State control metrics can be classified into response determination effectiveness and response effectiveness. These metrics are applied to each and every fault management control loop in the system, for each failure to which they apply, and probabilistically summed to determine the effectiveness of these fault management control loops to preserve the relevant system goals that they are intended to protect.

  7. Successful Experiences in Teaching Metric.

    ERIC Educational Resources Information Center

    Odom, Jeffrey V., Ed.

    In this publication are presentations on specific experiences in teaching metrics, made at a National Bureau of Standards conference. Ideas of value to teachers and administrators are described in reports on: SI units of measure; principles and practices of teaching metric; metric and the school librarian; teaching metric through television and…

  8. Changing to the Metric System.

    ERIC Educational Resources Information Center

    Chambers, Donald L.; Dowling, Kenneth W.

    This report examines educational aspects of the conversion to the metric system of measurement in the United States. Statements of positions on metrication and basic mathematical skills are given from various groups. Base units, symbols, prefixes, and style of the metric system are outlined. Guidelines for teaching metric concepts are given,…

  9. Using Metrics in Industrial Arts.

    ERIC Educational Resources Information Center

    Bame, E. Allen

    This metric supplement is intended as a guide to aid the industrial arts teacher in incorporating metrics in the classroom. A list of student objectives for measurement skills is followed by an overview of the history of measurement, an argument for change to the metric system in the United States, and a discussion of metric basics (common terms).…

  10. Cyber threat metrics.

    SciTech Connect

    Frye, Jason Neal; Veitch, Cynthia K.; Mateski, Mark Elliot; Michalski, John T.; Harris, James Mark; Trevino, Cassandra M.; Maruoka, Scott

    2012-03-01

    Threats are generally much easier to list than to describe, and much easier to describe than to measure. As a result, many organizations list threats. Fewer describe them in useful terms, and still fewer measure them in meaningful ways. This is particularly true in the dynamic and nebulous domain of cyber threats - a domain that tends to resist easy measurement and, in some cases, appears to defy any measurement. We believe the problem is tractable. In this report we describe threat metrics and models for characterizing threats consistently and unambiguously. The purpose of this report is to support the Operational Threat Assessment (OTA) phase of risk and vulnerability assessment. To this end, we focus on the task of characterizing cyber threats using consistent threat metrics and models. In particular, we address threat metrics and models for describing malicious cyber threats to US FCEB agencies and systems.

  11. Automatic registration and mosaicking of conservation images

    NASA Astrophysics Data System (ADS)

    Conover, Damon M.; Delaney, John K.; Loew, Murray H.

    2013-05-01

    As high-resolution conservation images, acquired using various imaging modalities, become more widely available, it is increasingly important to achieve accurate registration between the images. Accurate registration allows information unavailable in any one image to be compiled from several images and then used to provide a better understanding of how a painting was constructed. We have developed an algorithm that solves several important conservation problems: 1) registration and mosaicking of multiple X-ray films, ultraviolet images, and infrared reflectograms to a color reference image at high spatial-resolution (200 to 500 dpi) of paintings (both panel and canvas) and of works on paper, 2) registration of the images within visible and infrared multispectral reflectance and luminescence image cubes, and 3) mosaicking of hyperspectral image cubes (400 to 2500 nm). The registration/mosaicking algorithm corrects for several kinds of distortion, small rotation and scale errors, and keystone effects between the images. Thus images acquired with different cameras, illumination, and geometries can be registered/mosaicked. This automatic algorithm for registering/mosaicking multimodal conservation images is expected to be a valuable tool for conservators attempting to answer questions regarding the creation and preservation history of paintings. For example, an analysis of the reflectance spectra obtained from the sub-pixel registered multispectral image cubes can be used to separate, map, and identify artist materials in situ. And, by comparing the corresponding images in the X-ray, visible, and infrared regions, conservators can obtain a deeper understanding of compositional changes.

  12. Large deformation diffeomorphic registration of diffusion-weighted imaging data.

    PubMed

    Zhang, Pei; Niethammer, Marc; Shen, Dinggang; Yap, Pew-Thian

    2014-12-01

    Registration plays an important role in group analysis of diffusion-weighted imaging (DWI) data. It can be used to build a reference anatomy for investigating structural variation or tracking changes in white matter. Unlike traditional scalar image registration where spatial alignment is the only focus, registration of DWI data requires both spatial alignment of structures and reorientation of local signal profiles. As such, DWI registration is much more complex and challenging than scalar image registration. Although a variety of algorithms has been proposed to tackle the problem, most of them are restricted by the diffusion model used for registration, making it difficult to fit to the registered data a different model. In this paper we describe a method that allows any diffusion model to be fitted after registration for subsequent multifaceted analysis. This is achieved by directly aligning DWI data using a large deformation diffeomorphic registration framework. Our algorithm seeks the optimal coordinate mapping by simultaneously considering structural alignment, local signal profile reorientation, and deformation regularization. Our algorithm also incorporates a multi-kernel strategy to concurrently register anatomical structures at different scales. We demonstrate the efficacy of our approach using in vivo data and report detailed qualitative and quantitative results in comparison with several different registration strategies. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Large deformation diffeomorphic registration of diffusion-weighted imaging data

    PubMed Central

    Zhang, Pei; Niethammer, Marc; Shen, Dinggang; Yap, Pew-Thian

    2014-01-01

    Registration plays an important role in group analysis of diffusion-weighted imaging (DWI) data. It can be used to build a reference anatomy for investigating structural variation or tracking changes in white matter. Unlike traditional scalar image registration where spatial alignment is the only focus, registration of DWI data requires both spatial alignment of structures and reorientation of local signal profiles. As such, DWI registration is much more complex and challenging than scalar image registration. Although a variety of algorithms has been proposed to tackle the problem, most of them are restricted by the zdiffusion model used for registration, making it difficult to fit to the registered data a different model. In this paper we describe a method that allows any diffusion model to be fitted after registration for subsequent multifaceted analysis. This is achieved by directly aligning DWI data using a large deformation diffeomorphic registration framework. Our algorithm seeks the optimal coordinate mapping by simultaneously considering structural alignment, local signal profile reorientation, and deformation regularization. Our algorithm also incorporates a multi-kernel strategy to concurrently register anatomical structures at different scales. We demonstrate the efficacy of our approach using in vivo data and report detailed qualitative and quantitative results in comparison with several different registration strategies. PMID:25106710

  14. Measurable Control System Security through Ideal Driven Technical Metrics

    SciTech Connect

    Miles McQueen; Wayne Boyer; Sean McBride; Marie Farrar; Zachary Tudor

    2008-01-01

    The Department of Homeland Security National Cyber Security Division supported development of a small set of security ideals as a framework to establish measurable control systems security. Based on these ideals, a draft set of proposed technical metrics was developed to allow control systems owner-operators to track improvements or degradations in their individual control systems security posture. The technical metrics development effort included review and evaluation of over thirty metrics-related documents. On the bases of complexity, ambiguity, or misleading and distorting effects the metrics identified during the reviews were determined to be weaker than necessary to aid defense against the myriad threats posed by cyber-terrorism to human safety, as well as to economic prosperity. Using the results of our metrics review and the set of security ideals as a starting point for metrics development, we identified thirteen potential technical metrics - with at least one metric supporting each ideal. Two case study applications of the ideals and thirteen metrics to control systems were then performed to establish potential difficulties in applying both the ideals and the metrics. The case studies resulted in no changes to the ideals, and only a few deletions and refinements to the thirteen potential metrics. This led to a final proposed set of ten core technical metrics. To further validate the security ideals, the modifications made to the original thirteen potential metrics, and the final proposed set of ten core metrics, seven separate control systems security assessments performed over the past three years were reviewed for findings and recommended mitigations. These findings and mitigations were then mapped to the security ideals and metrics to assess gaps in their coverage. The mappings indicated that there are no gaps in the security ideals and that the ten core technical metrics provide significant coverage of standard security issues with 87% coverage. Based

  15. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic product...

  16. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic product...

  17. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic product...

  18. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic product...

  19. 21 CFR 710.8 - Misbranding by reference to registration or to registration number.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... HUMAN SERVICES (CONTINUED) COSMETICS VOLUNTARY REGISTRATION OF COSMETIC PRODUCT ESTABLISHMENTS § 710.8 Misbranding by reference to registration or to registration number. Registration of a cosmetic product...

  20. Overview of metrics and their correlation patterns for multiple-metric topology analysis on heterogeneous graph ensembles

    NASA Astrophysics Data System (ADS)

    Bounova, Gergana; de Weck, Olivier

    2012-01-01

    This study is an overview of network topology metrics and a computational approach to analyzing graph topology via multiple-metric analysis on graph ensembles. The paper cautions against studying single metrics or combining disparate graph ensembles from different domains to extract global patterns. This is because there often exists considerable diversity among graphs that share any given topology metric, patterns vary depending on the underlying graph construction model, and many real data sets are not actual statistical ensembles. As real data examples, we present five airline ensembles, comprising temporal snapshots of networks of similar topology. Wikipedia language networks are shown as an example of a nontemporal ensemble. General patterns in metric correlations, as well as exceptions, are discussed by representing the data sets via hierarchically clustered correlation heat maps. Most topology metrics are not independent and their correlation patterns vary across ensembles. In general, density-related metrics and graph distance-based metrics cluster and the two groups are orthogonal to each other. Metrics based on degree-degree correlations have the highest variance across ensembles and cluster the different data sets on par with principal component analysis. Namely, the degree correlation, the s metric, their elasticities, and the rich club moments appear to be most useful in distinguishing topologies.

  1. Overview of metrics and their correlation patterns for multiple-metric topology analysis on heterogeneous graph ensembles.

    PubMed

    Bounova, Gergana; de Weck, Olivier

    2012-01-01

    This study is an overview of network topology metrics and a computational approach to analyzing graph topology via multiple-metric analysis on graph ensembles. The paper cautions against studying single metrics or combining disparate graph ensembles from different domains to extract global patterns. This is because there often exists considerable diversity among graphs that share any given topology metric, patterns vary depending on the underlying graph construction model, and many real data sets are not actual statistical ensembles. As real data examples, we present five airline ensembles, comprising temporal snapshots of networks of similar topology. Wikipedia language networks are shown as an example of a nontemporal ensemble. General patterns in metric correlations, as well as exceptions, are discussed by representing the data sets via hierarchically clustered correlation heat maps. Most topology metrics are not independent and their correlation patterns vary across ensembles. In general, density-related metrics and graph distance-based metrics cluster and the two groups are orthogonal to each other. Metrics based on degree-degree correlations have the highest variance across ensembles and cluster the different data sets on par with principal component analysis. Namely, the degree correlation, the s metric, their elasticities, and the rich club moments appear to be most useful in distinguishing topologies.

  2. Simultaneous fine and coarse diffeomorphic registration: application to atrophy measurement in Alzheimer's disease.

    PubMed

    Risser, Laurent; Vialard, François-Xavier; Wolz, Robin; Holm, Darryl D; Rueckert, Daniel

    2010-01-01

    In this paper, we present a fine and coarse approach for the multiscale registration of 3D medical images using Large Deformation Diffeomorphic Metric Mapping (LDDMM). This approach has particularly interesting properties since it estimates large, smooth and invertible optimal deformations having a rich descriptive power for the quantification of temporal changes in the images. First, we show the importance of the smoothing kernel and its influence on the final solution. We then propose a new strategy for the spatial regularization of the deformations, which uses simultaneously fine and coarse smoothing kernels. We have evaluated the approach on both 2D synthetic images as well as on 3D MR longitudinal images out of the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Results highlight the regularizing properties of our approach for the registration of complex shapes. More importantly, the results also demonstrate its ability to measure shape variations at several scales simultaneously while keeping the desirable properties of LDDMM. This opens new perspectives for clinical applications.

  3. Metrics of Scholarly Impact

    ERIC Educational Resources Information Center

    Cacioppo, John T.; Cacioppo, Stephanie

    2012-01-01

    Ruscio and colleagues (Ruscio, Seaman, D'Oriano, Stremlo, & Mahalchik, this issue) provide a thoughtful empirical analysis of 22 different measures of individual scholarly impact. The simplest metric is number of publications, which Simonton (1997) found to be a reasonable predictor of career trajectories. Although the assessment of the scholarly…

  4. Adaptable edge quality metric

    NASA Astrophysics Data System (ADS)

    Strickland, Robin N.; Chang, Dunkai K.

    1990-09-01

    A new quality metric for evaluating edges detected by digital image processing algorithms is presented. The metric is a weighted sum of measures of edge continuity smoothness thinness localization detection and noisiness. Through a training process we can design weights which optimize the metric for different users and applications. We have used the metric to compare the results of ten edge detectors when applied to edges degraded by varying degrees of blur and varying degrees and types of noise. As expected the more optimum Difference-of-Gaussians (DOG) and Haralick methods outperform the simpler gradient detectors. At high signal-to-noise (SNR) ratios Haralick''s method is the best choice although it exhibits a sudden drop in performance at lower SNRs. The DOG filter''s performance degrades almost linearly with SNR and maintains a reasonably high level at lower SNRs. The same relative performances are observed as blur is varied. For most of the detectors tested performance drops with increasing noise correlation. Noise correlated in the same direction as the edge is the most destructive of the noise types tested.

  5. Metrical Phonology and SLA.

    ERIC Educational Resources Information Center

    Tice, Bradley S.

    Metrical phonology, a linguistic process of phonological stress assessment and diagrammatic simplification of sentence and word stress, is discussed as it is found in the English language with the intention that it may be used in second language instruction. Stress is defined by its physical and acoustical correlates, and the principles of…

  6. Metrics and Sports.

    ERIC Educational Resources Information Center

    National Collegiate Athletic Association, Shawnee Mission, KS.

    Designed as a guide to aid the National Collegiate Athletic Association membership and others who must relate measurement of distances, weights, and volumes to athletic activity, this document presents diagrams of performance areas with measurements delineated in both imperial and metric terms. Illustrations are given for baseball, basketball,…

  7. Engineering performance metrics

    NASA Astrophysics Data System (ADS)

    Delozier, R.; Snyder, N.

    1993-03-01

    Implementation of a Total Quality Management (TQM) approach to engineering work required the development of a system of metrics which would serve as a meaningful management tool for evaluating effectiveness in accomplishing project objectives and in achieving improved customer satisfaction. A team effort was chartered with the goal of developing a system of engineering performance metrics which would measure customer satisfaction, quality, cost effectiveness, and timeliness. The approach to developing this system involved normal systems design phases including, conceptual design, detailed design, implementation, and integration. The lessons teamed from this effort will be explored in this paper. These lessons learned may provide a starting point for other large engineering organizations seeking to institute a performance measurement system accomplishing project objectives and in achieving improved customer satisfaction. To facilitate this effort, a team was chartered to assist in the development of the metrics system. This team, consisting of customers and Engineering staff members, was utilized to ensure that the needs and views of the customers were considered in the development of performance measurements. The development of a system of metrics is no different than the development of any type of system. It includes the steps of defining performance measurement requirements, measurement process conceptual design, performance measurement and reporting system detailed design, and system implementation and integration.

  8. Arbitrary Metrics Redux

    ERIC Educational Resources Information Center

    Blanton, Hart; Jaccard, James

    2006-01-01

    Reducing the arbitrariness of a metric is distinct from the pursuit of validity, rational zero points, data transformations, standardization, and the types of statistical procedures one uses to analyze interval-level versus ordinal-level data. A variety of theoretical, methodological, and statistical tools can assist researchers who wish to make…

  9. Metrics of Scholarly Impact

    ERIC Educational Resources Information Center

    Cacioppo, John T.; Cacioppo, Stephanie

    2012-01-01

    Ruscio and colleagues (Ruscio, Seaman, D'Oriano, Stremlo, & Mahalchik, this issue) provide a thoughtful empirical analysis of 22 different measures of individual scholarly impact. The simplest metric is number of publications, which Simonton (1997) found to be a reasonable predictor of career trajectories. Although the assessment of the scholarly…

  10. Software Quality Metrics

    DTIC Science & Technology

    1991-07-01

    March 1979, pp. 121-128. Gorla, Narasimhaiah, Alan C. Benander, and Barbara A. Benander, "Debugging Effort Estimation Using Software Metrics", IEEE...Society, IEEE Guide for the Use of IEEE Standard Dictionary of Measures to Produce Reliable Software, IEEE Std 982.2-1988, June 1989. Jones, Capers

  11. Software Quality Assurance Metrics

    NASA Technical Reports Server (NTRS)

    McRae, Kalindra A.

    2004-01-01

    Software Quality Assurance (SQA) is a planned and systematic set of activities that ensures conformance of software life cycle processes and products conform to requirements, standards and procedures. In software development, software quality means meeting requirements and a degree of excellence and refinement of a project or product. Software Quality is a set of attributes of a software product by which its quality is described and evaluated. The set of attributes includes functionality, reliability, usability, efficiency, maintainability, and portability. Software Metrics help us understand the technical process that is used to develop a product. The process is measured to improve it and the product is measured to increase quality throughout the life cycle of software. Software Metrics are measurements of the quality of software. Software is measured to indicate the quality of the product, to assess the productivity of the people who produce the product, to assess the benefits derived from new software engineering methods and tools, to form a baseline for estimation, and to help justify requests for new tools or additional training. Any part of the software development can be measured. If Software Metrics are implemented in software development, it can save time, money, and allow the organization to identify the caused of defects which have the greatest effect on software development. The summer of 2004, I worked with Cynthia Calhoun and Frank Robinson in the Software Assurance/Risk Management department. My task was to research and collect, compile, and analyze SQA Metrics that have been used in other projects that are not currently being used by the SA team and report them to the Software Assurance team to see if any metrics can be implemented in their software assurance life cycle process.

  12. Software Quality Assurance Metrics

    NASA Technical Reports Server (NTRS)

    McRae, Kalindra A.

    2004-01-01

    Software Quality Assurance (SQA) is a planned and systematic set of activities that ensures conformance of software life cycle processes and products conform to requirements, standards and procedures. In software development, software quality means meeting requirements and a degree of excellence and refinement of a project or product. Software Quality is a set of attributes of a software product by which its quality is described and evaluated. The set of attributes includes functionality, reliability, usability, efficiency, maintainability, and portability. Software Metrics help us understand the technical process that is used to develop a product. The process is measured to improve it and the product is measured to increase quality throughout the life cycle of software. Software Metrics are measurements of the quality of software. Software is measured to indicate the quality of the product, to assess the productivity of the people who produce the product, to assess the benefits derived from new software engineering methods and tools, to form a baseline for estimation, and to help justify requests for new tools or additional training. Any part of the software development can be measured. If Software Metrics are implemented in software development, it can save time, money, and allow the organization to identify the caused of defects which have the greatest effect on software development. The summer of 2004, I worked with Cynthia Calhoun and Frank Robinson in the Software Assurance/Risk Management department. My task was to research and collect, compile, and analyze SQA Metrics that have been used in other projects that are not currently being used by the SA team and report them to the Software Assurance team to see if any metrics can be implemented in their software assurance life cycle process.

  13. EVALUATION OF REGISTRATION, COMPRESSION AND CLASSIFICATION ALGORITHMS

    NASA Technical Reports Server (NTRS)

    Jayroe, R. R.

    1994-01-01

    Several types of algorithms are generally used to process digital imagery such as Landsat data. The most commonly used algorithms perform the task of registration, compression, and classification. Because there are different techniques available for performing registration, compression, and classification, imagery data users need a rationale for selecting a particular approach to meet their particular needs. This collection of registration, compression, and classification algorithms was developed so that different approaches could be evaluated and the best approach for a particular application determined. Routines are included for six registration algorithms, six compression algorithms, and two classification algorithms. The package also includes routines for evaluating the effects of processing on the image data. This collection of routines should be useful to anyone using or developing image processing software. Registration of image data involves the geometrical alteration of the imagery. Registration routines available in the evaluation package include image magnification, mapping functions, partitioning, map overlay, and data interpolation. The compression of image data involves reducing the volume of data needed for a given image. Compression routines available in the package include adaptive differential pulse code modulation, two-dimensional transforms, clustering, vector reduction, and picture segmentation. Classification of image data involves analyzing the uncompressed or compressed image data to produce inventories and maps of areas of similar spectral properties within a scene. The classification routines available include a sequential linear technique and a maximum likelihood technique. The choice of the appropriate evaluation criteria is quite important in evaluating the image processing functions. The user is therefore given a choice of evaluation criteria with which to investigate the available image processing functions. All of the available

  14. EVALUATION OF REGISTRATION, COMPRESSION AND CLASSIFICATION ALGORITHMS

    NASA Technical Reports Server (NTRS)

    Jayroe, R. R.

    1994-01-01

    Several types of algorithms are generally used to process digital imagery such as Landsat data. The most commonly used algorithms perform the task of registration, compression, and classification. Because there are different techniques available for performing registration, compression, and classification, imagery data users need a rationale for selecting a particular approach to meet their particular needs. This collection of registration, compression, and classification algorithms was developed so that different approaches could be evaluated and the best approach for a particular application determined. Routines are included for six registration algorithms, six compression algorithms, and two classification algorithms. The package also includes routines for evaluating the effects of processing on the image data. This collection of routines should be useful to anyone using or developing image processing software. Registration of image data involves the geometrical alteration of the imagery. Registration routines available in the evaluation package include image magnification, mapping functions, partitioning, map overlay, and data interpolation. The compression of image data involves reducing the volume of data needed for a given image. Compression routines available in the package include adaptive differential pulse code modulation, two-dimensional transforms, clustering, vector reduction, and picture segmentation. Classification of image data involves analyzing the uncompressed or compressed image data to produce inventories and maps of areas of similar spectral properties within a scene. The classification routines available include a sequential linear technique and a maximum likelihood technique. The choice of the appropriate evaluation criteria is quite important in evaluating the image processing functions. The user is therefore given a choice of evaluation criteria with which to investigate the available image processing functions. All of the available

  15. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Registration number. 47.15 Section 47.15... REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft registration must place a U.S. registration number (registration mark) on the Aircraft Registration Application, AC...

  16. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Registration number. 47.15 Section 47.15... REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft registration must place a U.S. registration number (registration mark) on the Aircraft Registration Application, AC...

  17. 14 CFR 47.15 - Registration number.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Registration number. 47.15 Section 47.15... REGISTRATION General § 47.15 Registration number. (a) Number required. An applicant for aircraft registration must place a U.S. registration number (registration mark) on the Aircraft Registration Application,...

  18. Towards an intercomparison of automated registration algorithms for multiple source remote sensing data

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; Xia, Wei; Chettri, Samir; El-Ghazawi, Tarek; Kaymaz, Emre; Lerner, Bao-Ting; Mareboyana, Manohar; Netanyahu, Nathan; Pierce, John; Raghavan, Srini; hide

    1997-01-01

    The first step in the integration of multiple data is registration, either relative image-to-image registration or absolute geo-registration, to a map or a fixed coordinate system. As the need for automating registration techniques is recognized, we feel that there is a need to survey all the registration methods which may be applicable to Earth and space science problems and to evaluate their performances on a large variety of existing remote sensing data as well as on simulated data of soon-to-be-flown instruments. In this paper we will describe: 1) the operational toolbox which we are developing and which will consist in some of the most important registration techniques; and 2) the quantitative intercomparison of the different methods, which will allow a user to select the desired registration technique based on this evaluation and the visualization of the registration results.

  19. Towards an intercomparison of automated registration algorithms for multiple source remote sensing data

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; Xia, Wei; Chettri, Samir; El-Ghazawi, Tarek; Kaymaz, Emre; Lerner, Bao-Ting; Mareboyana, Manohar; Netanyahu, Nathan; Pierce, John; Raghavan, Srini; Tilton, James C.; Campbell, William J.; Cromp, Robert F.

    1997-01-01

    The first step in the integration of multiple data is registration, either relative image-to-image registration or absolute geo-registration, to a map or a fixed coordinate system. As the need for automating registration techniques is recognized, we feel that there is a need to survey all the registration methods which may be applicable to Earth and space science problems and to evaluate their performances on a large variety of existing remote sensing data as well as on simulated data of soon-to-be-flown instruments. In this paper we will describe: 1) the operational toolbox which we are developing and which will consist in some of the most important registration techniques; and 2) the quantitative intercomparison of the different methods, which will allow a user to select the desired registration technique based on this evaluation and the visualization of the registration results.

  20. Corneal topography matching by iterative registration.

    PubMed

    Wang, Junjie; Elsheikh, Ahmed; Davey, Pinakin G; Wang, Weizhuo; Bao, Fangjun; Mottershead, John E

    2014-11-01

    Videokeratography is used for the measurement of corneal topography in overlapping portions (or maps) which must later be joined together to form the overall topography of the cornea. The separate portions are measured from different viewpoints and therefore must be brought together by registration of measurement points in the regions of overlap. The central map is generally the most accurate, but all maps are measured with uncertainty that increases towards the periphery. It becomes the reference (or static) map, and the peripheral (or dynamic) maps must then be transformed by rotation and translation so that the overlapping portions are matched. The process known as registration, of determining the necessary transformation, is a well-understood procedure in image analysis and has been applied in several areas of science and engineering. In this article, direct search optimisation using the Nelder-Mead algorithm and several variants of the iterative closest/corresponding point routine are explained and applied to simulated and real clinical data. The measurement points on the static and dynamic maps are generally different so that it becomes necessary to interpolate, which is done using a truncated series of Zernike polynomials. The point-to-plane iterative closest/corresponding point variant has the advantage of releasing certain optimisation constraints that lead to persistent registration and alignment errors when other approaches are used. The point-to-plane iterative closest/corresponding point routine is found to be robust to measurement noise, insensitive to starting values of the transformation parameters and produces high-quality results when using real clinical data.

  1. Image registration by parts

    NASA Technical Reports Server (NTRS)

    Chalermwat, Prachya; El-Ghazawi, Tarek; LeMoigne, Jacqueline

    1997-01-01

    In spite of the large number of different image registration techniques, most of these techniques use the correlation operation to match spatial image characteristics. Correlation is known to be one of the most computationally intensive operations and its computational needs grow rapidly with the increase in the image sizes. In this article, we show that, in many cases, it might be sufficient to determine image transformations by considering only one or several parts of the image rather than the entire image, which could result in substantial computational savings. This paper introduces the concept of registration by parts and investigates its viability. It describes alternative techniques for such image registration by parts and presents early empirical results that address the underlying trade-offs.

  2. Analysis of subpixel registration

    NASA Technical Reports Server (NTRS)

    Berenstein, C. A.; Kanal, L. N.; Lavine, D.; Olson, E. C.; Slud, E.

    1984-01-01

    The area of subpixel accuracy in image registration and edge detection was studied. Two main directions of research were pursued, edge detection and matching based on the digital geometry of edges, and random field models for probablistic analysis of registration error. In the edge detection approach, error bounds and error probabilities were computed using theoretical models. Algorithms were developed and tests on simulated imagery. The methods appear promising for high accuracy edge position estimation and registration, though further refinement of the procedures is required. Using random field models, a statistical measure of the quality of the cross correlation peak as an estimate of the offset between a sensed and a reference image was developed. Simulations were performed to determine the validity of this estimte with real imagery and to study the results of interpolating digital correlation functions to estimate the translation offset to subpixel accuracy.

  3. Towards operational multisensor registration

    NASA Technical Reports Server (NTRS)

    Rignot, Eric J. M.; Kwok, Ronald; Curlander, John C.

    1991-01-01

    To use data from a number of different remote sensors in a synergistic manner, a multidimensional analysis of the data is necessary. However, prior to this analysis, processing to correct for the systematic geometric distortion characteristic of each sensor is required. Furthermore, the registration process must be fully automated to handle a large volume of data and high data rates. A conceptual approach towards an operational multisensor registration algorithm is presented. The performance requirements of the algorithm are first formulated given the spatially, temporally, and spectrally varying factors that influence the image characteristics and the science requirements of various applications. Several registration techniques that fit within the structure of this algorithm are also presented. Their performance was evaluated using a multisensor test data set assembled from LANDSAT TM, SEASAT, SIR-B, Thermal Infrared Multispectral Scanner (TIMS), and SPOT sensors.

  4. Minimum of a functional in a metric space and fixed points

    NASA Astrophysics Data System (ADS)

    Arutyunov, A. V.; Gel'Man, B. D.

    2009-07-01

    The existence of minimizers is examined for a function defined on a metric space. Theorems are proved that assert the existence of minimizers, and examples of the functions for which these theorems are valid are given. Then, these theorems are applied to proving theorems on fixed points of univalent and multivalued mappings of metric spaces. Finally, coincident points of two mappings are examined.

  5. Developing image processing meta-algorithms with data mining of multiple metrics.

    PubMed

    Leung, Kelvin; Cunha, Alexandre; Toga, A W; Parker, D Stott

    2014-01-01

    People often use multiple metrics in image processing, but here we take a novel approach of mining the values of batteries of metrics on image processing results. We present a case for extending image processing methods to incorporate automated mining of multiple image metric values. Here by a metric we mean any image similarity or distance measure, and in this paper we consider intensity-based and statistical image measures and focus on registration as an image processing problem. We show how it is possible to develop meta-algorithms that evaluate different image processing results with a number of different metrics and mine the results in an automated fashion so as to select the best results. We show that the mining of multiple metrics offers a variety of potential benefits for many image processing problems, including improved robustness and validation.

  6. Developing Image Processing Meta-Algorithms with Data Mining of Multiple Metrics

    PubMed Central

    Cunha, Alexandre; Toga, A. W.; Parker, D. Stott

    2014-01-01

    People often use multiple metrics in image processing, but here we take a novel approach of mining the values of batteries of metrics on image processing results. We present a case for extending image processing methods to incorporate automated mining of multiple image metric values. Here by a metric we mean any image similarity or distance measure, and in this paper we consider intensity-based and statistical image measures and focus on registration as an image processing problem. We show how it is possible to develop meta-algorithms that evaluate different image processing results with a number of different metrics and mine the results in an automated fashion so as to select the best results. We show that the mining of multiple metrics offers a variety of potential benefits for many image processing problems, including improved robustness and validation. PMID:24653748

  7. MR to CT Registration of Brains using Image Synthesis.

    PubMed

    Roy, Snehashis; Carass, Aaron; Jog, Amod; Prince, Jerry L; Lee, Junghoon

    2014-03-21

    Computed tomography (CT) is the standard imaging modality for patient dose calculation for radiation therapy. Magnetic resonance (MR) imaging (MRI) is used along with CT to identify brain structures due to its superior soft tissue contrast. Registration of MR and CT is necessary for accurate delineation of the tumor and other structures, and is critical in radiotherapy planning. Mutual information (MI) or its variants are typically used as a similarity metric to register MRI to CT. However, unlike CT, MRI intensity does not have an accepted calibrated intensity scale. Therefore, MI-based MR-CT registration may vary from scan to scan as MI depends on the joint histogram of the images. In this paper, we propose a fully automatic framework for MR-CT registration by synthesizing a synthetic CT image from MRI using a co-registered pair of MR and CT images as an atlas. Patches of the subject MRI are matched to the atlas and the synthetic CT patches are estimated in a probabilistic framework. The synthetic CT is registered to the original CT using a deformable registration and the computed deformation is applied to the MRI. In contrast to most existing methods, we do not need any manual intervention such as picking landmarks or regions of interests. The proposed method was validated on ten brain cancer patient cases, showing 25% improvement in MI and correlation between MR and CT images after registration compared to state-of-the-art registration methods.

  8. MR to CT registration of brains using image synthesis

    NASA Astrophysics Data System (ADS)

    Roy, Snehashis; Carass, Aaron; Jog, Amod; Prince, Jerry L.; Lee, Junghoon

    2014-03-01

    Computed tomography (CT) is the preferred imaging modality for patient dose calculation for radiation therapy. Magnetic resonance (MR) imaging (MRI) is used along with CT to identify brain structures due to its superior soft tissue contrast. Registration of MR and CT is necessary for accurate delineation of the tumor and other structures, and is critical in radiotherapy planning. Mutual information (MI) or its variants are typically used as a similarity metric to register MRI to CT. However, unlike CT, MRI intensity does not have an accepted calibrated intensity scale. Therefore, MI-based MR-CT registration may vary from scan to scan as MI depends on the joint histogram of the images. In this paper, we propose a fully automatic framework for MR-CT registration by synthesizing a synthetic CT image from MRI using a co-registered pair of MR and CT images as an atlas. Patches of the subject MRI are matched to the atlas and the synthetic CT patches are estimated in a probabilistic framework. The synthetic CT is registered to the original CT using a deformable registration and the computed deformation is applied to the MRI. In contrast to most existing methods, we do not need any manual intervention such as picking landmarks or regions of interests. The proposed method was validated on ten brain cancer patient cases, showing 25% improvement in MI and correlation between MR and CT images after registration compared to state-of-the-art registration methods.

  9. Metric Measurement and Instructional Television

    ERIC Educational Resources Information Center

    Meiring, Steven P.

    1977-01-01

    The television series "MeasureMetric," an instructional series introducing length, area, volume, mass, and temperature measurement in metric settings, is described. Guidelines are given for using the series as a complete learning unit. (JT)

  10. Quality Metrics in Endoscopy

    PubMed Central

    Gurudu, Suryakanth R.

    2013-01-01

    Endoscopy has evolved in the past 4 decades to become an important tool in the diagnosis and management of many digestive diseases. Greater focus on endoscopic quality has highlighted the need to ensure competency among endoscopists. A joint task force of the American College of Gastroenterology and the American Society for Gastrointestinal Endoscopy has proposed several quality metrics to establish competence and help define areas of continuous quality improvement. These metrics represent quality in endoscopy pertinent to pre-, intra-, and postprocedural periods. Quality in endoscopy is a dynamic and multidimensional process that requires continuous monitoring of several indicators and benchmarking with local and national standards. Institutions and practices should have a process in place for credentialing endoscopists and for the assessment of competence regarding individual endoscopic procedures. PMID:24711767

  11. The Kerr metric

    NASA Astrophysics Data System (ADS)

    Teukolsky, Saul A.

    2015-06-01

    This review describes the events leading up to the discovery of the Kerr metric in 1963 and the enormous impact the discovery has had in the subsequent 50 years. The review discusses the Penrose process, the four laws of black hole mechanics, uniqueness of the solution, and the no-hair theorems. It also includes Kerr perturbation theory and its application to black hole stability and quasi-normal modes. The Kerr metric's importance in the astrophysics of quasars and accreting stellar-mass black hole systems is detailed. A theme of the review is the ‘miraculous’ nature of the solution, both in describing in a simple analytic formula the most general rotating black hole, and in having unexpected mathematical properties that make many calculations tractable. Also included is a pedagogical derivation of the solution suitable for a first course in general relativity.

  12. 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.

  13. Performance Metrics for Commercial Buildings

    SciTech Connect

    Fowler, Kimberly M.; Wang, Na; Romero, Rachel L.; Deru, Michael P.

    2010-09-30

    Commercial building owners and operators have requested a standard set of key performance metrics to provide a systematic way to evaluate the performance of their buildings. The performance metrics included in this document provide standard metrics for the energy, water, operations and maintenance, indoor environmental quality, purchasing, waste and recycling and transportation impact of their building. The metrics can be used for comparative performance analysis between existing buildings and industry standards to clarify the impact of sustainably designed and operated buildings.

  14. Aquatic Acoustic Metrics Interface

    SciTech Connect

    2012-12-18

    Fishes and marine mammals may suffer a range of potential effects from exposure to intense underwater sound generated by anthropogenic activities such as pile driving, shipping, sonars, and underwater blasting. Several underwater sound recording (USR) devices have been built to acquire samples of the underwater sound generated by anthropogenic activities. Software becomes indispensable for processing and analyzing the audio files recorded by these USRs. The new Aquatic Acoustic Metrics Interface Utility Software (AAMI) is specifically designed for analysis of underwater sound recordings to provide data in metrics that facilitate evaluation of the potential impacts of the sound on aquatic animals. In addition to the basic functions, such as loading and editing audio files recorded by USRs and batch processing of sound files, the software utilizes recording system calibration data to compute important parameters in physical units. The software also facilitates comparison of the noise sound sample metrics with biological measures such as audiograms of the sensitivity of aquatic animals to the sound, integrating various components into a single analytical frame.

  15. Metrics for Energy Resilience

    SciTech Connect

    Paul E. Roege; Zachary A. Collier; James Mancillas; John A. McDonagh; Igor Linkov

    2014-09-01

    Energy lies at the backbone of any advanced society and constitutes an essential prerequisite for economic growth, social order and national defense. However there is an Achilles heel to today?s energy and technology relationship; namely a precarious intimacy between energy and the fiscal, social, and technical systems it supports. Recently, widespread and persistent disruptions in energy systems have highlighted the extent of this dependence and the vulnerability of increasingly optimized systems to changing conditions. Resilience is an emerging concept that offers to reconcile considerations of performance under dynamic environments and across multiple time frames by supplementing traditionally static system performance measures to consider behaviors under changing conditions and complex interactions among physical, information and human domains. This paper identifies metrics useful to implement guidance for energy-related planning, design, investment, and operation. Recommendations are presented using a matrix format to provide a structured and comprehensive framework of metrics relevant to a system?s energy resilience. The study synthesizes previously proposed metrics and emergent resilience literature to provide a multi-dimensional model intended for use by leaders and practitioners as they transform our energy posture from one of stasis and reaction to one that is proactive and which fosters sustainable growth.

  16. EnviroAtlas - Metrics for Durham, NC

    EPA Pesticide Factsheets

    These EnviroAtlas web services support research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas ). The layers in these web services depict ecosystem services at the census block group level for the community of Durham, North Carolina. These layers illustrate the ecosystems and natural resources that are associated with clean air (https://enviroatlas.epa.gov/arcgis/rest/services/Communities/ESC_DNC_CleanAir/MapServer); clean and plentiful water (https://enviroatlas.epa.gov/arcgis/rest/services/Communities/ESC_DNC_CleanPlentifulWater/MapServer); natural hazard mitigation (https://enviroatlas.epa.gov/arcgis/rest/services/Communities/ESC_DNC_NaturalHazardMitigation/MapServer); climate stabilization (https://enviroatlas.epa.gov/arcgis/rest/services/Communities/ESC_DNC_ClimateStabilization/MapServer); food, fuel, and materials; recreation, culture, and aesthetics (https://enviroatlas.epa.gov/arcgis/rest/services/Communities/ESC_DNC_RecreationCultureAesthetics/MapServer); and biodiversity conservation (https://enviroatlas.epa.gov/arcgis/rest/services/Communities/ESC_DNC_BiodiversityConservation/MapServer) , and factors that place stress on those resources. EnviroAtlas allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the conterminous United States as well as detailed metrics for select communities. Additional descriptive information about each attribut

  17. Some References on Metric Information.

    ERIC Educational Resources Information Center

    National Bureau of Standards (DOC), Washington, DC.

    This resource work lists metric information published by the U.S. Government and the American National Standards Institute. Also organizations marketing metric materials for education are given. A short table of conversions is included as is a listing of basic metric facts for everyday living. (LS)

  18. Metrication, American Style. Fastback 41.

    ERIC Educational Resources Information Center

    Izzi, John

    The purpose of this pamphlet is to provide a starting point of information on the metric system for any concerned or interested reader. The material is organized into five brief chapters: Man and Measurement; Learning the Metric System; Progress Report: Education; Recommended Sources; and Metrication, American Style. Appendixes include an…

  19. Say "Yes" to Metric Measure.

    ERIC Educational Resources Information Center

    Monroe, Eula Ewing; Nelson, Marvin N.

    2000-01-01

    Provides a brief history of the metric system. Discusses the infrequent use of the metric measurement system in the United States, why conversion from the customary system to the metric system is difficult, and the need for change. (Contains 14 resources.) (ASK)

  20. Metrication in a global environment

    NASA Technical Reports Server (NTRS)

    Aberg, J.

    1994-01-01

    A brief history about the development of the metric system of measurement is given. The need for the U.S. to implement the 'SI' metric system in the international markets, especially in the aerospace and general trade, is discussed. Development of metric implementation and experiences locally, nationally, and internationally are included.

  1. Metric Education Plan for Virginia.

    ERIC Educational Resources Information Center

    Virginia State Dept. of Education, Richmond. Div. of Secondary Education.

    This comprehensive document is the result of statewide planning for the implementation of metric education in Virginia schools. An introduction discusses the rationale, needs, and continuing objectives for metric education. An organizational structure for metric education in Virginia is outlined. Guidelines for administrative planning are…

  2. Metric Education for Adult Learners.

    ERIC Educational Resources Information Center

    Goetsch, David L.

    1978-01-01

    The metric education program developed at Okaloosa-Walton Junior College, Niceville, Florida, for students and the community in general consists of three components: a metric measurement course; multimedia labor for independent study; and metric signs located throughout the campus. Instructional approaches for adult students are noted. (MF)

  3. Earth Science Imagery Registration

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; Morisette, Jeffrey; Cole-Rhodes, Arlene; Johnson, Kisha; Netanyahu, Nathan S.; Eastman, Roger; Stone, Harold; Zavorin, Ilya

    2003-01-01

    The study of global environmental changes involves the comparison, fusion, and integration of multiple types of remotely-sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, as well as for the validation of new instruments or for new data analysis. Furthermore, future multiple satellite missions will include many different sensors carried on separate platforms, and the amount of remote sensing data to be combined is increasing tremendously. For all of these applications, the first required step is fast and automatic image registration, and as this need for automating registration techniques is being recognized, it becomes necessary to survey all the registration methods which may be applicable to Earth and space science problems and to evaluate their performances on a large variety of existing remote sensing data as well as on simulated data of soon-to-be-flown instruments. In this paper we present one of the first steps toward such an exhaustive quantitative evaluation. First, the different components of image registration algorithms are reviewed, and different choices for each of these components are described. Then, the results of the evaluation of the corresponding algorithms combining these components are presented o n several datasets. The algorithms are based on gray levels or wavelet features and compute rigid transformations (including scale, rotation, and shifts). Test datasets include synthetic data as well as data acquired over several EOS Land Validation Core Sites with the IKONOS and the Landsat-7 sensors.

  4. Registration Priorities: A Report.

    ERIC Educational Resources Information Center

    Walters, Judy E.

    In May 1993, the California Community Colleges' Board of Governors adopted systemwide guidelines recommending student registration priorities to help address current discrepancies between available resources and courses and the colleges' open-door mission. This report describes the guidelines and results of a study conducted to determine their…

  5. Distributed Continuous Registration.

    ERIC Educational Resources Information Center

    Myers, Donald L.

    1981-01-01

    The development, implementation, and features of Northern Colorado's continuous registration system are described. The system is an online distributed processing system, written in COBOL for an IBM Series I under the CPS operating system. Course selection, permit to enroll, and drop/add forms are provided. (Author/MLW)

  6. Distributed Continuous Registration.

    ERIC Educational Resources Information Center

    Myers, Donald L.

    1981-01-01

    The development, implementation, and features of Northern Colorado's continuous registration system are described. The system is an online distributed processing system, written in COBOL for an IBM Series I under the CPS operating system. Course selection, permit to enroll, and drop/add forms are provided. (Author/MLW)

  7. Registration Study. Research Note.

    ERIC Educational Resources Information Center

    Baratta, Mary Kathryne

    During spring 1977 registration, 3,255 or 45% of Moraine Valley Community College (MVCC) registering students responded to a scheduling preferences and problems questionnaire covering enrollment status, curriculum load, program preference, ability to obtain courses, schedule conflicts, preferred times for class offerings, actual scheduling of…

  8. CUNY's Voter Registration System.

    ERIC Educational Resources Information Center

    Hershenson, Jay; And Others

    This collection of items including public testimony by the Vice Chancellor, Jay Hershenson, a formal resolution, a press release, and brochures, documents the City University of New York's (CUNY) unique voter registration system, "CUNY Project Vote". As the press release describes it, Project Vote is the nation's largest student voter…

  9. Suspension of Registrations under FIFRA

    EPA Pesticide Factsheets

    Under FIFRA Section 3(c)(2)(B), this generally halts further distribution and sale of the suspended pesticide product by the registrant. Find suspension listings by product name, active ingredient, registrant name, date, and contact information.

  10. Implications of Metric Choice for Common Applications of Readmission Metrics

    PubMed Central

    Davies, Sheryl; Saynina, Olga; Schultz, Ellen; McDonald, Kathryn M; Baker, Laurence C

    2013-01-01

    Objective. To quantify the differential impact on hospital performance of three readmission metrics: all-cause readmission (ACR), 3M Potential Preventable Readmission (PPR), and Centers for Medicare and Medicaid 30-day readmission (CMS). Data Sources. 2000–2009 California Office of Statewide Health Planning and Development Patient Discharge Data Nonpublic file. Study Design. We calculated 30-day readmission rates using three metrics, for three disease groups: heart failure (HF), acute myocardial infarction (AMI), and pneumonia. Using each metric, we calculated the absolute change and correlation between performance; the percent of hospitals remaining in extreme deciles and level of agreement; and differences in longitudinal performance. Principal Findings. Average hospital rates for HF patients and the CMS metric were generally higher than for other conditions and metrics. Correlations between the ACR and CMS metrics were highest (r = 0.67–0.84). Rates calculated using the PPR and either ACR or CMS metrics were moderately correlated (r = 0.50–0.67). Between 47 and 75 percent of hospitals in an extreme decile according to one metric remained when using a different metric. Correlations among metrics were modest when measuring hospital longitudinal change. Conclusions. Different approaches to computing readmissions can produce different hospital rankings and impact pay-for-performance. Careful consideration should be placed on readmission metric choice for these applications. PMID:23742056

  11. Regional manifold learning for deformable registration of brain MR images.

    PubMed

    Ye, Dong Hye; Hamm, Jihun; Kwon, Dongjin; Davatzikos, Christos; Pohl, Kilian M

    2012-01-01

    We propose a method for deformable registration based on learning the manifolds of individual brain regions. Recent publications on registration of medical images advocate the use of manifold learning in order to confine the search space to anatomically plausible deformations. Existing methods construct manifolds based on a single metric over the entire image domain thus frequently miss regional brain variations. We address this issue by first learning manifolds for specific regions and then computing region-specific deformations from these manifolds. We then determine deformations for the entire image domain by learning the global manifold in such a way that it preserves the region-specific deformations. We evaluate the accuracy of our method by applying it to the LPBA40 dataset and measuring the overlap of the deformed segmentations. The result shows significant improvement in registration accuracy on cortex regions compared to other state of the art methods.

  12. New GPU optimizations for intensity-based registration

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

  13. Point set registration: coherent point drift.

    PubMed

    Myronenko, Andriy; Song, Xubo

    2010-12-01

    Point set registration is a key component in many computer vision tasks. The goal of point set registration is to assign correspondences between two sets of points and to recover the transformation that maps one point set to the other. Multiple factors, including an unknown nonrigid spatial transformation, large dimensionality of point set, noise, and outliers, make the point set registration a challenging problem. We introduce a probabilistic method, called the Coherent Point Drift (CPD) algorithm, for both rigid and nonrigid point set registration. We consider the alignment of two point sets as a probability density estimation problem. We fit the Gaussian mixture model (GMM) centroids (representing the first point set) to the data (the second point set) by maximizing the likelihood. We force the GMM centroids to move coherently as a group to preserve the topological structure of the point sets. In the rigid case, we impose the coherence constraint by reparameterization of GMM centroid locations with rigid parameters and derive a closed form solution of the maximization step of the EM algorithm in arbitrary dimensions. In the nonrigid case, we impose the coherence constraint by regularizing the displacement field and using the variational calculus to derive the optimal transformation. We also introduce a fast algorithm that reduces the method computation complexity to linear. We test the CPD algorithm for both rigid and nonrigid transformations in the presence of noise, outliers, and missing points, where CPD shows accurate results and outperforms current state-of-the-art methods.

  14. Comparative Study of Two Automatic Registration Algorithms

    NASA Astrophysics Data System (ADS)

    Grant, D.; Bethel, J.; Crawford, M.

    2013-10-01

    The Iterative Closest Point (ICP) algorithm is prevalent for the automatic fine registration of overlapping pairs of terrestrial laser scanning (TLS) data. This method along with its vast number of variants, obtains the least squares parameters that are necessary to align the TLS data by minimizing some distance metric between the scans. The ICP algorithm uses a "model-data" concept in which the scans obtain differential treatment in the registration process depending on whether they were assigned to be the "model" or "data". For each of the "data" points, corresponding points from the "model" are sought. Another concept of "symmetric correspondence" was proposed in the Point-to-Plane (P2P) algorithm, where both scans are treated equally in the registration process. The P2P method establishes correspondences on both scans and minimizes the point-to-plane distances between the scans by simultaneously considering the stochastic properties of both scans. This paper studies both the ICP and P2P algorithms in terms of their consistency in registration parameters for pairs of TLS data. The question being investigated in this paper is, should scan A be registered to scan B, will the parameters be the same if scan B were registered to scan A? Experiments were conducted with eight pairs of real TLS data which were registered by the two algorithms in the forward (scan A to scan B) and backward (scan B to scan A) modes and the results were compared. The P2P algorithm was found to be more consistent than the ICP algorithm. The differences in registration accuracy between the forward and backward modes were negligible when using the P2P algorithm (mean difference of 0.03 mm). However, the ICP had a mean difference of 4.26 mm. Each scan was also transformed by the forward and backward parameters of the two algorithms and the misclosure computed. The mean misclosure for the P2P algorithm was 0.80 mm while that for the ICP algorithm was 5.39 mm. The conclusion from this study is

  15. Adaptive Metric Learning for Saliency Detection.

    PubMed

    Li, Shuang; Lu, Huchuan; Lin, Zhe; Shen, Xiaohui; Price, Brian

    2015-11-01

    In this paper, we propose a novel adaptive metric learning algorithm (AML) for visual saliency detection. A key observation is that the saliency of a superpixel can be estimated by the distance from the most certain foreground and background seeds. Instead of measuring distance on the Euclidean space, we present a learning method based on two complementary Mahalanobis distance metrics: 1) generic metric learning (GML) and 2) specific metric learning (SML). GML aims at the global distribution of the whole training set, while SML considers the specific structure of a single image. Considering that multiple similarity measures from different views may enhance the relevant information and alleviate the irrelevant one, we try to fuse the GML and SML together and experimentally find the combining result does work well. Different from the most existing methods which are directly based on low-level features, we devise a superpixelwise Fisher vector coding approach to better distinguish salient objects from the background. We also propose an accurate seeds selection mechanism and exploit contextual and multiscale information when constructing the final saliency map. Experimental results on various image sets show that the proposed AML performs favorably against the state-of-the-arts.

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

    PubMed Central

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

    2015-01-01

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

  17. 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.

  18. Avoiding stair-step artifacts in image registration for GOES-R navigation and registration assessment

    NASA Astrophysics Data System (ADS)

    Grycewicz, Thomas J.; Tan, Bin; Isaacson, Peter J.; De Luccia, Frank J.; Dellomo, John

    2016-09-01

    In developing software for independent verification and validation (IV and V) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite - R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

  19. Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

    NASA Technical Reports Server (NTRS)

    Grycewicz, Thomas J.; Tan, Bin; Isaacson, Peter J.; De Luccia, Frank J.; Dellomo, John

    2016-01-01

    In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

  20. The hidden KPI registration accuracy.

    PubMed

    Shorrosh, Paul

    2011-09-01

    Determining the registration accuracy rate is fundamental to improving revenue cycle key performance indicators. A registration quality assurance (QA) process allows errors to be corrected before bills are sent and helps registrars learn from their mistakes. Tools are available to help patient access staff who perform registration QA manually.

  1. Off-Campus Registration Procedures.

    ERIC Educational Resources Information Center

    Maas, Michael L.

    Registration is one of the more critical functions that a college staff encounters each semester. To have a smooth, efficient, college-wide registration, it is essential that all segments of the college be aware of registration procedures as well as data control operations. This packet was designed to acquaint interested parties with the…

  2. Consistency of magnetoencephalographic functional connectivity and network reconstruction using a template versus native MRI for co-registration.

    PubMed

    Douw, Linda; Nieboer, Dagmar; Stam, Cornelis J; Tewarie, Prejaas; Hillebrand, Arjan

    2017-10-08

    Studies using functional connectivity and network analyses based on magnetoencephalography (MEG) with source localization are rapidly emerging in neuroscientific literature. However, these analyses currently depend on the availability of costly and sometimes burdensome individual MR scans for co-registration. We evaluated the consistency of these measures when using a template MRI, instead of native MRI, for the analysis of functional connectivity and network topology. Seventeen healthy participants underwent resting-state eyes-closed MEG and anatomical MRI. These data were projected into source space using an atlas-based peak voxel and a centroid beamforming approach either using (1) participants' native MRIs or (2) the Montreal Neurological Institute's template. For both methods, time series were reconstructed from 78 cortical atlas regions. Relative power was determined in six classical frequency bands per region and globally averaged. Functional connectivity (phase lag index) between each pair of regions was calculated. The adjacency matrices were then used to reconstruct functional networks, of which regional and global metrics were determined. Intraclass correlation coefficients were calculated and Bland-Altman plots were made to quantify the consistency and potential bias of the use of template versus native MRI. Co-registration with the template yielded largely consistent relative power, connectivity, and network estimates compared to native MRI. These findings indicate that there is no (systematic) bias or inconsistency between template and native MRI co-registration of MEG. They open up possibilities for retrospective and prospective analyses to MEG datasets in the general population that have no native MRIs available. Hum Brain Mapp, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  3. Registration Documents for Enlist Duo Herbicide (2014)

    EPA Pesticide Factsheets

    See details of the registration of Enlist Duo in 2014, including the notification to the registrant, the details of the assessment and registration decision, and the response to public comment on the proposed registration.

  4. Random Kähler metrics

    NASA Astrophysics Data System (ADS)

    Ferrari, Frank; Klevtsov, Semyon; Zelditch, Steve

    2013-04-01

    The purpose of this article is to propose a new method to define and calculate path integrals over metrics on a Kähler manifold. The main idea is to use finite dimensional spaces of Bergman metrics, as an approximation to the full space of Kähler metrics. We use the theory of large deviations to decide when a sequence of probability measures on the spaces of Bergman metrics tends to a limit measure on the space of all Kähler metrics. Several examples are considered.

  5. Optical metrics and projective equivalence

    SciTech Connect

    Casey, Stephen; Dunajski, Maciej; Gibbons, Gary; Warnick, Claude

    2011-04-15

    Trajectories of light rays in a static spacetime are described by unparametrized geodesics of the Riemannian optical metric associated with the Lorentzian spacetime metric. We investigate the uniqueness of this structure and demonstrate that two different observers, moving relative to one another, who both see the Universe as static may determine the geometry of the light rays differently. More specifically, we classify Lorentzian metrics admitting more than one hyper-surface orthogonal timelike Killing vector and analyze the projective equivalence of the resulting optical metrics. These metrics are shown to be projectively equivalent up to diffeomorphism if the static Killing vectors generate a group SL(2,R), but not projectively equivalent in general. We also consider the cosmological C metrics in Einstein-Maxwell theory and demonstrate that optical metrics corresponding to different values of the cosmological constant are projectively equivalent.

  6. Comparing Resource Adequacy Metrics

    SciTech Connect

    Ibanez, Eduardo; Milligan, Michael

    2014-11-13

    As the penetration of variable generation (wind and solar) increases around the world, there is an accompanying growing interest and importance in accurately assessing the contribution that these resources can make toward planning reserve. This contribution, also known as the capacity credit or capacity value of the resource, is best quantified by using a probabilistic measure of overall resource adequacy. In recognizing the variable nature of these renewable resources, there has been interest in exploring the use of reliability metrics other than loss of load expectation. In this paper, we undertake some comparisons using data from the Western Electricity Coordinating Council in the western United States.

  7. SI (Metric) handbook

    NASA Technical Reports Server (NTRS)

    Artusa, Elisa A.

    1994-01-01

    This guide provides information for an understanding of SI units, symbols, and prefixes; style and usage in documentation in both the US and in the international business community; conversion techniques; limits, fits, and tolerance data; and drawing and technical writing guidelines. Also provided is information of SI usage for specialized applications like data processing and computer programming, science, engineering, and construction. Related information in the appendixes include legislative documents, historical and biographical data, a list of metric documentation, rules for determining significant digits and rounding, conversion factors, shorthand notation, and a unit index.

  8. Degenerate metric phase boundaries

    NASA Astrophysics Data System (ADS)

    Bengtsson, I.; Jacobson, T.

    1997-11-01

    The structure of boundaries between degenerate and non-degenerate solutions of Ashtekar's canonical reformulation of Einstein's equations is studied. Several examples are given of such `phase boundaries' in which the metric is degenerate on one side of a null hypersurface and non-degenerate on the other side. These include portions of flat space, Schwarzschild and plane-wave solutions joined to degenerate regions. In the last case, the wave collides with a planar phase boundary and continues on with the same curvature but degenerate triad, while the phase boundary continues in the opposite direction. We conjecture that degenerate phase boundaries are always null.

  9. Distance Metric Tracking

    DTIC Science & Technology

    2016-03-02

    520, 2004. 16 [12] E.C. Hall and R.M. Willett. Online convex optimization in dynamic environ- ments. Selected Topics in Signal Processing, IEEE Journal...Conference on Machine Learning, pages 1160–1167. ACM, 2008. [25] Eric P Xing, Michael I Jordan, Stuart Russell, and Andrew Y Ng. Distance metric...whereBψ is any Bregman divergence and ηt is the learning rate parameter. From ( Hall & Willett, 2015) we have: Theorem 1. G` = max θ∈Θ,`∈L ‖∇f(θ)‖ φmax = 1

  10. Metrics for Multiagent Systems

    NASA Astrophysics Data System (ADS)

    Lass, Robert N.; Sultanik, Evan A.; Regli, William C.

    A Multiagent System (MAS) is a software paradigm for building large scale intelligent distributed systems. Increasingly these systems are being deployed on handheld computing devices that rely on non-traditional communications mediums such as mobile ad hoc networks and satellite links. These systems present new challenges for computer scientists in describing system performance and analyzing competing systems. This chapter surveys existing metrics that can be used to describe MASs and related components. A framework for analyzing MASs is provided and an example of how this framework might be employed is given for the domain of distributed constraint reasoning.

  11. SI (Metric) handbook

    NASA Astrophysics Data System (ADS)

    Artusa, Elisa A.

    1994-03-01

    This guide provides information for an understanding of SI units, symbols, and prefixes; style and usage in documentation in both the US and in the international business community; conversion techniques; limits, fits, and tolerance data; and drawing and technical writing guidelines. Also provided is information of SI usage for specialized applications like data processing and computer programming, science, engineering, and construction. Related information in the appendixes include legislative documents, historical and biographical data, a list of metric documentation, rules for determining significant digits and rounding, conversion factors, shorthand notation, and a unit index.

  12. Validating Software Metrics

    DTIC Science & Technology

    1990-09-30

    validation test: Spearman Rank Correlation and Wald - Wolfowitz Runs Test (test for randomness) (5,8]. For example, if a complexity metric is claimed to be... error count (E). Validity Criteria Select values of V, B, A, and P. The values of V, B, A, and P, used in the example are .7, .7, 20%, and 80...Procedures with no errors Average rank of first group = 85.2419 based on 31 values . Average rank of second group = 45.5 based on 81 values . Large sample test

  13. Sustainable chemistry metrics.

    PubMed

    Calvo-Flores, Francisco García

    2009-01-01

    Green chemistry has developed mathematical parameters to describe the sustainability of chemical reactions and processes, in order to quantify their environmental impact. These parameters are related to mass and energy magnitudes, and enable analyses and numerical diagnoses of chemical reactions. The environmental impact factor (E factor), atom economy, and reaction mass efficiency have been the most influential metrics, and they are interconnected by mathematical equations. The ecodesign concept must also be considered for complex industrial syntheses, as a part of the sustainability of manufacturing processes. The aim of this Concept article is to identify the main parameters for evaluating undesirable environmental consequences.

  14. PROFESSIONAL REGISTRATION OF GOVERNMENT ENGINEERS.

    USGS Publications Warehouse

    Buchanan, Thomas J.

    1985-01-01

    The American Society of Civil Engineers views professional registration as an appropriate requirement for engineers, including those in government. The National Society of Professional Engineers makes registration a requirement for the grade of member and full privileges in the society. Some Federal agencies require engineering registration for certain positions in their agencies. Engineers in government service should consider the value of engineering registration to themselves and to their agencies and take pride in their professions and in their own capabilities by becoming registered engineers. They should also take steps to encourage their agencies to give more attention to engineering registration.

  15. 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.

  16. 14 CFR 47.43 - Invalid registration.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Invalid registration. 47.43 Section 47.43... REGISTRATION Certificates of Aircraft Registration § 47.43 Invalid registration. (a) The registration of an...) compliance with 49 U.S.C. 44101-44104. (b) If the registration of an aircraft is invalid under paragraph...

  17. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 6 2011-07-01 2011-07-01 false Registration. 1615.1 Section 1615.1 National... REGISTRATION § 1615.1 Registration. (a) Registration under selective service law consists of: (1) Completing a registration card or other method of registration prescribed by the Director of Selective Service by a...

  18. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Registration. 1615.1 Section 1615.1 National... REGISTRATION § 1615.1 Registration. (a) Registration under selective service law consists of: (1) Completing a registration card or other method of registration prescribed by the Director of Selective Service by a...

  19. 14 CFR 47.43 - Invalid registration.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Invalid registration. 47.43 Section 47.43... REGISTRATION Certificates of Aircraft Registration § 47.43 Invalid registration. (a) The registration of an...) compliance with 49 U.S.C. 44101-44104. (b) If the registration of an aircraft is invalid under paragraph...

  20. 14 CFR 47.43 - Invalid registration.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Invalid registration. 47.43 Section 47.43... REGISTRATION Certificates of Aircraft Registration § 47.43 Invalid registration. (a) The registration of an...) compliance with 49 U.S.C. 44101-44104. (b) If the registration of an aircraft is invalid under paragraph...

  1. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 32 National Defense 6 2014-07-01 2014-07-01 false Registration. 1615.1 Section 1615.1 National... REGISTRATION § 1615.1 Registration. (a) Registration under selective service law consists of: (1) Completing a registration card or other method of registration prescribed by the Director of Selective Service by a...

  2. 32 CFR 1615.1 - Registration.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 32 National Defense 6 2012-07-01 2012-07-01 false Registration. 1615.1 Section 1615.1 National... REGISTRATION § 1615.1 Registration. (a) Registration under selective service law consists of: (1) Completing a registration card or other method of registration prescribed by the Director of Selective Service by a...

  3. Incorporating visual attention models into video quality metrics

    NASA Astrophysics Data System (ADS)

    Akamine, Welington Y. L.; Farias, Mylène C. Q.

    2014-01-01

    A recent development in the area of image and video quality consists of trying to incorporate aspects of visual attention in the design of visual quality metrics, mostly using the assumption that visual distortions appearing in less salient areas might be less visible and, therefore, less annoying. This research area is still in its infancy and results obtained by different groups are not yet conclusive. Among the works that have reported some improvement, most use subjective saliency maps, i.e. saliency maps generated from eye-tracking data obtained experimentally. Besides, most works address the image quality problem, not focusing on how to incorporate visual attention into video signals. In this work, we investigate the benefits of incorporating saliency maps obtained with visual attention. In particular, we compare the performance of four full-reference video quality metrics with their modified versions, which had saliency maps incorporated to the algorithm. For comparison proposes, we have used a database of subjective salience maps.

  4. Photogrammetric Processing of Apollo 15 Metric Camera Oblique Images

    NASA Astrophysics Data System (ADS)

    Edmundson, K. L.; Alexandrov, O.; Archinal, B. A.; Becker, K. J.; Becker, T. L.; Kirk, R. L.; Moratto, Z. M.; Nefian, A. V.; Richie, J. O.; Robinson, M. S.

    2016-06-01

    The integrated photogrammetric mapping system flown on the last three Apollo lunar missions (15, 16, and 17) in the early 1970s incorporated a Metric (mapping) Camera, a high-resolution Panoramic Camera, and a star camera and laser altimeter to provide support data. In an ongoing collaboration, the U.S. Geological Survey's Astrogeology Science Center, the Intelligent Robotics Group of the NASA Ames Research Center, and Arizona State University are working to achieve the most complete cartographic development of Apollo mapping system data into versatile digital map products. These will enable a variety of scientific/engineering uses of the data including mission planning, geologic mapping, geophysical process modelling, slope dependent correction of spectral data, and change detection. Here we describe efforts to control the oblique images acquired from the Apollo 15 Metric Camera.

  5. Asymmetric Image-Template Registration

    PubMed Central

    Sabuncu, Mert R.; Yeo, B.T. Thomas; Van Leemput, Koen; Vercauteren, Tom; Golland, Polina

    2010-01-01

    A natural requirement in pairwise image registration is that the resulting deformation is independent of the order of the images. This constraint is typically achieved via a symmetric cost function and has been shown to reduce the effects of local optima. Consequently, symmetric registration has been successfully applied to pairwise image registration as well as the spatial alignment of individual images with a template. However, recent work has shown that the relationship between an image and a template is fundamentally asymmetric. In this paper, we develop a method that reconciles the practical advantages of symmetric registration with the asymmetric nature of image-template registration by adding a simple correction factor to the symmetric cost function. We instantiate our model within a log-domain diffeomorphic registration framework. Our experiments show exploiting the asymmetry in image-template registration improves alignment in the image coordinates. PMID:20426033

  6. Early Warning Look Ahead Metrics: The Percent Milestone Backlog Metric

    NASA Technical Reports Server (NTRS)

    Shinn, Stephen A.; Anderson, Timothy P.

    2017-01-01

    All complex development projects experience delays and corresponding backlogs of their project control milestones during their acquisition lifecycles. NASA Goddard Space Flight Center (GSFC) Flight Projects Directorate (FPD) teamed with The Aerospace Corporation (Aerospace) to develop a collection of Early Warning Look Ahead metrics that would provide GSFC leadership with some independent indication of the programmatic health of GSFC flight projects. As part of the collection of Early Warning Look Ahead metrics, the Percent Milestone Backlog metric is particularly revealing, and has utility as a stand-alone execution performance monitoring tool. This paper describes the purpose, development methodology, and utility of the Percent Milestone Backlog metric. The other four Early Warning Look Ahead metrics are also briefly discussed. Finally, an example of the use of the Percent Milestone Backlog metric in providing actionable insight is described, along with examples of its potential use in other commodities.

  7. Exploring Metric Symmetry

    SciTech Connect

    Zwart, P.H.; Grosse-Kunstleve, R.W.; Adams, P.D.

    2006-07-31

    Relatively minor perturbations to a crystal structure can in some cases result in apparently large changes in symmetry. Changes in space group or even lattice can be induced by heavy metal or halide soaking (Dauter et al, 2001), flash freezing (Skrzypczak-Jankun et al, 1996), and Se-Met substitution (Poulsen et al, 2001). Relations between various space groups and lattices can provide insight in the underlying structural causes for the symmetry or lattice transformations. Furthermore, these relations can be useful in understanding twinning and how to efficiently solve two different but related crystal structures. Although (pseudo) symmetric properties of a certain combination of unit cell parameters and a space group are immediately obvious (such as a pseudo four-fold axis if a is approximately equal to b in an orthorhombic space group), other relations (e.g. Lehtio, et al, 2005) that are less obvious might be crucial to the understanding and detection of certain idiosyncrasies of experimental data. We have developed a set of tools that allows straightforward exploration of possible metric symmetry relations given unit cell parameters and a space group. The new iotbx.explore{_}metric{_}symmetry command produces an overview of the various relations between several possible point groups for a given lattice. Methods for finding relations between a pair of unit cells are also available. The tools described in this newsletter are part of the CCTBX libraries, which are included in the latest (versions July 2006 and up) PHENIX and CCI Apps distributions.

  8. Spacecraft camera image registration

    NASA Technical Reports Server (NTRS)

    Kamel, Ahmed A. (Inventor); Graul, Donald W. (Inventor); Chan, Fred N. T. (Inventor); Gamble, Donald W. (Inventor)

    1987-01-01

    A system for achieving spacecraft camera (1, 2) image registration comprises a portion external to the spacecraft and an image motion compensation system (IMCS) portion onboard the spacecraft. Within the IMCS, a computer (38) calculates an image registration compensation signal (60) which is sent to the scan control loops (84, 88, 94, 98) of the onboard cameras (1, 2). At the location external to the spacecraft, the long-term orbital and attitude perturbations on the spacecraft are modeled. Coefficients (K, A) from this model are periodically sent to the onboard computer (38) by means of a command unit (39). The coefficients (K, A) take into account observations of stars and landmarks made by the spacecraft cameras (1, 2) themselves. The computer (38) takes as inputs the updated coefficients (K, A) plus synchronization information indicating the mirror position (AZ, EL) of each of the spacecraft cameras (1, 2), operating mode, and starting and stopping status of the scan lines generated by these cameras (1, 2), and generates in response thereto the image registration compensation signal (60). The sources of periodic thermal errors on the spacecraft are discussed. The system is checked by calculating measurement residuals, the difference between the landmark and star locations predicted at the external location and the landmark and star locations as measured by the spacecraft cameras (1, 2).

  9. Binary 4D seismic history matching, a metric study

    NASA Astrophysics Data System (ADS)

    Chassagne, Romain; Obidegwu, Dennis; Dambrine, Julien; MacBeth, Colin

    2016-11-01

    This paper explores 4D seismic history matching and it specifically focuses on the objective function used during the optimisation with seismic data. The objective function is calculated by using binary maps, where one map is obtained from the observed seismic data and the other is from one realisation of the optimisation algorithm from the simulation model. In order to decide which set of parameters is a relevant update for the simulation model, an efficient way is required to measure how similar these two binary images are, during their evaluation within the objective function. Behind this aspect of quantification of the similarities or dissimilarities lies the metric notion, or the art of measuring distances. Four metrics are proposed with this study, the well-known Hamming distance, two widely used metrics, the Hausdorff distance and Mutual Information and a recent metric, called the Current Measure Metric. These metrics will be tested and compared on different case scenarios, designed in accordance to a real field case (gas exsolution) before being used in the second part of the paper. Despite its simplicity, the Hamming distance gives positive results, but the Current Measure Metric appears to be a more efficient choice to cover a wider range of scenarios, these conclusions remain true when tested on synthetic and real dataset in a history matching exercise. Some practical aspects of binary map processes will be examined through the paper, as it is shown that it is more proper to use a derivative free optimisation algorithm and a proper metric should be more inclined to capture global features than local features.

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

    NASA Astrophysics Data System (ADS)

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

    2005-04-01

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

  11. d-Neighborhood system and generalized F-contraction in dislocated metric space.

    PubMed

    Kumari, P Sumati; Zoto, Kastriot; Panthi, Dinesh

    2015-01-01

    This paper, gives an answer for the Question 1.1 posed by Hitzler (Generalized metrics and topology in logic programming semantics, 2001) by means of "Topological aspects of d-metric space with d-neighborhood system". We have investigated the topological aspects of a d-neighborhood system obtained from dislocated metric space (simply d-metric space) which has got useful applications in the semantic analysis of logic programming. Further more we have generalized the notion of F-contraction in the view of d-metric spaces and investigated the uniqueness of fixed point and coincidence point of such mappings.

  12. 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.

  13. Validating Dose Uncertainty Estimates Produced by AUTODIRECT: An Automated Program to Evaluate Deformable Image Registration Accuracy.

    PubMed

    Kim, Hojin; Chen, Josephine; Phillips, Justin; Pukala, Jason; Yom, Sue S; Kirby, Neil

    2017-01-01

    Deformable image registration is a powerful tool for mapping information, such as radiation therapy dose calculations, from one computed tomography image to another. However, deformable image registration is susceptible to mapping errors. Recently, an automated deformable image registration evaluation of confidence tool was proposed to predict voxel-specific deformable image registration dose mapping errors on a patient-by-patient basis. The purpose of this work is to conduct an extensive analysis of automated deformable image registration evaluation of confidence tool to show its effectiveness in estimating dose mapping errors. The proposed format of automated deformable image registration evaluation of confidence tool utilizes 4 simulated patient deformations (3 B-spline-based deformations and 1 rigid transformation) to predict the uncertainty in a deformable image registration algorithm's performance. This workflow is validated for 2 DIR algorithms (B-spline multipass from Velocity and Plastimatch) with 1 physical and 11 virtual phantoms, which have known ground-truth deformations, and with 3 pairs of real patient lung images, which have several hundred identified landmarks. The true dose mapping error distributions closely followed the Student t distributions predicted by automated deformable image registration evaluation of confidence tool for the validation tests: on average, the automated deformable image registration evaluation of confidence tool-produced confidence levels of 50%, 68%, and 95% contained 48.8%, 66.3%, and 93.8% and 50.1%, 67.6%, and 93.8% of the actual errors from Velocity and Plastimatch, respectively. Despite the sparsity of landmark points, the observed error distribution from the 3 lung patient data sets also followed the expected error distribution. The dose error distributions from automated deformable image registration evaluation of confidence tool also demonstrate good resemblance to the true dose error distributions. Automated

  14. Handbook of aircraft noise metrics

    NASA Technical Reports Server (NTRS)

    Bennett, R. L.; Pearsons, K. S.

    1981-01-01

    Information is presented on 22 noise metrics that are associated with the measurement and prediction of the effects of aircraft noise. Some of the instantaneous frequency weighted sound level measures, such as A-weighted sound level, are used to provide multiple assessment of the aircraft noise level. Other multiple event metrics, such as day-night average sound level, were designed to relate sound levels measured over a period of time to subjective responses in an effort to determine compatible land uses and aid in community planning. The various measures are divided into: (1) instantaneous sound level metrics; (2) duration corrected single event metrics; (3) multiple event metrics; and (4) speech communication metrics. The scope of each measure is examined in terms of its: definition, purpose, background, relationship to other measures, calculation method, example, equipment, references, and standards.

  15. 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).

  16. LCC-Demons: a robust and accurate symmetric diffeomorphic registration algorithm.

    PubMed

    Lorenzi, M; Ayache, N; Frisoni, G B; Pennec, X

    2013-11-01

    Non-linear registration is a key instrument for computational anatomy to study the morphology of organs and tissues. However, in order to be an effective instrument for the clinical practice, registration algorithms must be computationally efficient, accurate and most importantly robust to the multiple biases affecting medical images. In this work we propose a fast and robust registration framework based on the log-Demons diffeomorphic registration algorithm. The transformation is parameterized by stationary velocity fields (SVFs), and the similarity metric implements a symmetric local correlation coefficient (LCC). Moreover, we show how the SVF setting provides a stable and consistent numerical scheme for the computation of the Jacobian determinant and the flux of the deformation across the boundaries of a given region. Thus, it provides a robust evaluation of spatial changes. We tested the LCC-Demons in the inter-subject registration setting, by comparing with state-of-the-art registration algorithms on public available datasets, and in the intra-subject longitudinal registration problem, for the statistically powered measurements of the longitudinal atrophy in Alzheimer's disease. Experimental results show that LCC-Demons is a generic, flexible, efficient and robust algorithm for the accurate non-linear registration of images, which can find several applications in the field of medical imaging. Without any additional optimization, it solves equally well intra & inter-subject registration problems, and compares favorably to state-of-the-art methods. Copyright © 2013 Elsevier Inc. All rights reserved.

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

    PubMed Central

    Wang, Yangping; Wang, Song

    2016-01-01

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

  18. 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.

  19. Ligand efficiency metrics considered harmful

    NASA Astrophysics Data System (ADS)

    Kenny, Peter W.; Leitão, Andrei; Montanari, Carlos A.

    2014-07-01

    Ligand efficiency metrics are used in drug discovery to normalize biological activity or affinity with respect to physicochemical properties such as lipophilicity and molecular size. This Perspective provides an overview of ligand efficiency metrics and summarizes thermodynamics of protein-ligand binding. Different classes of ligand efficiency metric are critically examined and the study concludes with suggestions for alternative ways to account for physicochemical properties when prioritizing and optimizing leads.

  20. Do-It-Yourself Metrics

    ERIC Educational Resources Information Center

    Klubeck, Martin; Langthorne, Michael; Padgett, Don

    2006-01-01

    Something new is on the horizon, and depending on one's role on campus, it might be storm clouds or a cleansing shower. Either way, no matter how hard one tries to avoid it, sooner rather than later he/she will have to deal with metrics. Metrics do not have to cause fear and resistance. Metrics can, and should, be a powerful tool for improvement.…

  1. Chosen Aspects of the Production of the Basic Map Using Uav Imagery

    NASA Astrophysics Data System (ADS)

    Kedzierski, M.; Fryskowska, A.; Wierzbicki, D.; Nerc, P.

    2016-06-01

    For several years there has been an increasing interest in the use of unmanned aerial vehicles in acquiring image data from a low altitude. Considering the cost-effectiveness of the flight time of UAVs vs. conventional airplanes, the use of the former is advantageous when generating large scale accurate ortophotos. Through the development of UAV imagery, we can update large-scale basic maps. These maps are cartographic products which are used for registration, economic, and strategic planning. On the basis of these maps other cartographic maps are produced, for example maps used building planning. The article presents an assessesment of the usefulness of orthophotos based on UAV imagery to upgrade the basic map. In the research a compact, non-metric camera, mounted on a fixed wing powered by an electric motor was used. The tested area covered flat, agricultural and woodland terrains. The processing and analysis of orthorectification were carried out with the INPHO UASMaster programme. Due to the effect of UAV instability on low-altitude imagery, the use of non-metric digital cameras and the low-accuracy GPS-INS sensors, the geometry of images is visibly lower were compared to conventional digital aerial photos (large values of phi and kappa angles). Therefore, typically, low-altitude images require large along- and across-track direction overlap - usually above 70 %. As a result of the research orthoimages were obtained with a resolution of 0.06 meters and a horizontal accuracy of 0.10m. Digitized basic maps were used as the reference data. The accuracy of orthoimages vs. basic maps was estimated based on the study and on the available reference sources. As a result, it was found that the geometric accuracy and interpretative advantages of the final orthoimages allow the updating of basic maps. It is estimated that such an update of basic maps based on UAV imagery reduces processing time by approx. 40%.

  2. The metric system: An introduction

    SciTech Connect

    Lumley, S.M.

    1995-05-01

    On July 13, 1992, Deputy Director Duane Sewell restated the Laboratory`s policy on conversion to the metric system which was established in 1974. Sewell`s memo announced the Laboratory`s intention to continue metric conversion on a reasonable and cost effective basis. Copies of the 1974 and 1992 Administrative Memos are contained in the Appendix. There are three primary reasons behind the Laboratory`s conversion to the metric system. First, Public Law 100-418, passed in 1988, states that by the end of fiscal year 1992 the Federal Government must begin using metric units in grants, procurements, and other business transactions. Second, on July 25, 1991, President George Bush signed Executive Order 12770 which urged Federal agencies to expedite conversion to metric units. Third, the contract between the University of California and the Department of Energy calls for the Laboratory to convert to the metric system. Thus, conversion to the metric system is a legal requirement and a contractual mandate with the University of California. Public Law 100-418 and Executive Order 12770 are discussed in more detail later in this section, but first they examine the reasons behind the nation`s conversion to the metric system. The second part of this report is on applying the metric system.

  3. The metric system: An introduction

    NASA Astrophysics Data System (ADS)

    Lumley, Susan M.

    On 13 Jul. 1992, Deputy Director Duane Sewell restated the Laboratory's policy on conversion to the metric system which was established in 1974. Sewell's memo announced the Laboratory's intention to continue metric conversion on a reasonable and cost effective basis. Copies of the 1974 and 1992 Administrative Memos are contained in the Appendix. There are three primary reasons behind the Laboratory's conversion to the metric system. First, Public Law 100-418, passed in 1988, states that by the end of fiscal year 1992 the Federal Government must begin using metric units in grants, procurements, and other business transactions. Second, on 25 Jul. 1991, President George Bush signed Executive Order 12770 which urged Federal agencies to expedite conversion to metric units. Third, the contract between the University of California and the Department of Energy calls for the Laboratory to convert to the metric system. Thus, conversion to the metric system is a legal requirement and a contractual mandate with the University of California. Public Law 100-418 and Executive Order 12770 are discussed in more detail later in this section, but first they examine the reasons behind the nation's conversion to the metric system. The second part of this report is on applying the metric system.

  4. Implementing the Metric System in Business Occupations. Metric Implementation Guide.

    ERIC Educational Resources Information Center

    Retzer, Kenneth A.; And Others

    Addressed to the business education teacher, this guide is intended to provide appropriate information, viewpoints, and attitudes regarding the metric system and to make suggestions regarding presentation of the material in the classroom. An introductory section on teaching suggestions emphasizes the need for a "think metric" approach made up of…

  5. Implementing the Metric System in Industrial Occupations. Metric Implementation Guide.

    ERIC Educational Resources Information Center

    Retzer, Kenneth A.

    Addressed to the industrial education teacher, this guide is intended to provide appropriate information, viewpoints, and attitudes regarding the metric system and to make suggestions regarding presentation of the material in the classroom. An introductory section on teaching suggestions emphasizes the need for a "think metric" approach made up of…

  6. Implementing the Metric System in Health Occupations. Metric Implementation Guide.

    ERIC Educational Resources Information Center

    Banks, Wilson P.; And Others

    Addressed to the health occupations education teacher, this guide is intended to provide appropriate information, viewpoints, and attitudes regarding the metric system and to make suggestions regarding presentation of the material in the classroom. An introductory section on teaching suggestions emphasizes the need for a "think metric" approach…

  7. Implementing the Metric System in Agricultural Occupations. Metric Implementation Guide.

    ERIC Educational Resources Information Center

    Gilmore, Hal M.; And Others

    Addressed to the agricultural education teacher, this guide is intended to provide appropriate information, viewpoints, and attitudes regarding the metric system and to make suggestions regarding presentation of the material in the classroom. An introductory section on teaching suggestions emphasizes the need for a "think metric" approach made up…

  8. Software metrics: Software quality metrics for distributed systems. [reliability engineering

    NASA Technical Reports Server (NTRS)

    Post, J. V.

    1981-01-01

    Software quality metrics was extended to cover distributed computer systems. Emphasis is placed on studying embedded computer systems and on viewing them within a system life cycle. The hierarchy of quality factors, criteria, and metrics was maintained. New software quality factors were added, including survivability, expandability, and evolvability.

  9. Spin groups of super metrics and a theorem of Rogers

    NASA Astrophysics Data System (ADS)

    Fulp, Ronald

    2017-01-01

    We derive the canonical forms of super Riemannian metrics and the local isometry groups of such metrics. For certain super metrics we also compute the simply connected covering groups of the local isometry groups and interpret these as local spin groups of the super metric. Super metrics define reductions OSg of the relevant frame bundle. When principal bundles S˜g exist with structure group the simply connected covering group G ˜ of the structure group of OSg , representations of G ˜ define vector bundles associated to S˜g whose sections are "spinor fields" associated with the super metric g . Using a generalization of a Theorem of Rogers, which is itself one of the main results of this paper, we show that for super metrics we call body reducible, each such simply connected covering group G ˜ is a super Lie group with a conventional super Lie algebra as its corresponding super Lie algebra. Some of our results were known to DeWitt (1984) using formal Grassmann series and others were known by Rogers using finitely many Grassmann generators and passing to a direct limit. We work exclusively in the category of G∞ supermanifolds with G∞ mappings. Our supernumbers are infinite series of products of Grassmann generators subject to convergence in the ℓ1 norm introduced by Rogers (1980, 2007).

  10. Heuristic approach to image registration

    NASA Astrophysics Data System (ADS)

    Gertner, Izidor; Maslov, Igor V.

    2000-08-01

    Image registration, i.e. correct mapping of images obtained from different sensor readings onto common reference frame, is a critical part of multi-sensor ATR/AOR systems based on readings from different types of sensors. In order to fuse two different sensor readings of the same object, the readings have to be put into a common coordinate system. This task can be formulated as optimization problem in a space of all possible affine transformations of an image. In this paper, a combination of heuristic methods is explored to register gray- scale images. The modification of Genetic Algorithm is used as the first step in global search for optimal transformation. It covers the entire search space with (randomly or heuristically) scattered probe points and helps significantly reduce the search space to a subspace of potentially most successful transformations. Due to its discrete character, however, Genetic Algorithm in general can not converge while coming close to the optimum. Its termination point can be specified either as some predefined number of generations or as achievement of a certain acceptable convergence level. To refine the search, potential optimal subspaces are searched using more delicate and efficient for local search Taboo and Simulated Annealing methods.

  11. Supervised local error estimation for nonlinear image registration using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Eppenhof, Koen A. J.; Pluim, Josien P. W.

    2017-02-01

    Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation of a registration error map for nonlinear image registration. The method is based on a convolutional neural network that estimates the norm of the residual deformation from patches around each pixel in two registered images. This norm is interpreted as the registration error, and is defined for every pixel in the image domain. The network is trained using a set of artificially deformed images. Each training example is a pair of images: the original image, and a random deformation of that image. No manually labeled ground truth error is required. At test time, only the two registered images are required as input. We train and validate the network on registrations in a set of 2D digital subtraction angiography sequences, such that errors up to eight pixels can be estimated. We show that for this range of errors the convolutional network is able to learn the registration error in pairs of 2D registered images at subpixel precision. Finally, we present a proof of principle for the extension to 3D registration problems in chest CTs, showing that the method has the potential to estimate errors in 3D registration problems.

  12. Image registration for luminescent paint applications

    NASA Technical Reports Server (NTRS)

    Bell, James H.; Mclachlan, Blair G.

    1993-01-01

    The use of pressure sensitive luminescent paints is a viable technique for the measurement of surface pressure on wind tunnel models. This technique requires data reduction of images obtained under known as well as test conditions and spatial transformation of the images. A general transform which registers images to subpixel accuracy is presented and the general characteristics of transforms for image registration and their derivation are discussed. Image resection and its applications are described. The mapping of pressure data to the three dimensional model surface for small wind tunnel models to a spatial accuracy of 0.5 percent of the model length is demonstrated.

  13. Assessment of artery dilation by using image registration based on spatial features

    NASA Astrophysics Data System (ADS)

    Oubel, Estanislao; Neemuchwala, Huzefa; Hero, Alfred; Boisrobert, Loic; Laclaustra, Martin; Frangi, Alejandro F.

    2005-04-01

    The use of affine image registration based on normalized mutual information (NMI) has recently been proposed by Frangi et al. as an automatic method for assessing brachial artery flow mediated dilation (FMD) for the characterization of endothelial function. Even though this method solves many problems of previous approaches, there are still some situations that can lead to misregistration between frames, such as the presence of adjacent vessels due to probe movement, muscle fibres or poor image quality. Despite its widespread use as a registration metric and its promising results, MI is not the panacea and can occasionally fail. Previous work has attempted to include spatial information into the image similarity metric. Among these methods the direct estimation of alpha-MI through Minimum Euclidean Graphs allows to include spatial information and it seems suitable to tackle the registration problem in vascular images, where well oriented structures corresponding to vessel walls and muscle fibres are present. The purpose of this work is twofold. Firstly, we aim to evaluate the effect of including spatial information in the performance of the method suggested by Frangi et al. by using alpha-MI of spatial features as similarity metric. Secondly, the application of image registration to long image sequences in which both rigid motion and deformation are present will be used as a benchmark to prove the value of alpha-MI as a similarity metric, and will also allow us to make a comparative study with respect to NMI.

  14. Proceedings of the NASA Workshop on Registration and Rectification

    NASA Technical Reports Server (NTRS)

    Bryant, N. A. (Editor)

    1982-01-01

    Issues associated with the registration and rectification of remotely sensed data. Near and long range applications research tasks and some medium range technology augmentation research areas are recommended. Image sharpness, feature extraction, inter-image mapping, error analysis, and verification methods are addressed.

  15. 32 CFR 263.5 - Inspection of license and registration.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... (CONTINUED) MISCELLANEOUS TRAFFIC AND VEHICLE CONTROL ON CERTAIN DEFENSE MAPPING AGENCY SITES § 263.5 Inspection of license and registration. No person may operate any motor vehicle on the site without a valid, current operator's license, nor may any person, if operating a motor vehicle on the site, refuse to...

  16. Precise FIA plot registration using field and dense LIDAR data

    Treesearch

    Demetrios Gatziolis

    2009-01-01

    Precise registration of forest inventory and analysis (FIA) plots is a prerequisite for an effective fusion of field data with ancillary spatial information, which is an approach commonly employed in the mapping of various forest parameters. Although the adoption of Global Positioning System technology has improved the precision of plot coordinates obtained during...

  17. An approach to automatic blood vessel image registration of microcirculation for blood flow analysis on nude mice.

    PubMed

    Lin, Wen-Chen; Wu, Chih-Chieh; Zhang, Geoffrey; Wu, Tung-Hsin; Lin, Yang-Hsien; Huang, Tzung-Chi; Liu, Ren-Shyan; Lin, Kang-Ping

    2011-04-01

    Image registration is often a required and a time-consuming step in blood flow analysis of large microscopic video sequences in vivo. In order to obtain stable images for blood flow analysis, frame-to-frame image matching as a preprocessing step is a solution to the problem of movement during image acquisition. In this paper, microscopic system analysis without fluorescent labelling is performed to provide precise and continuous quantitative data of blood flow rate in individual microvessels of nude mice. The performance properties of several matching metrics are evaluated through simulated image registrations. An automatic image registration programme based on Powell's optimisation search method with low calculation redundancy was implemented. The matching method by variance of ratio is computationally efficient and improves the registration robustness and accuracy in practical application of microcirculation registration. The presented registration method shows acceptable results in close requisition to analyse red blood cell velocities, confirming the scientific potential of the system in blood flow analysis.

  18. Multimetric indices: How many metrics?

    EPA Science Inventory

    Multimetric indices (MMI’s) often include 5 to 15 metrics, each representing a different attribute of assemblage condition, such as species diversity, tolerant taxa, and nonnative taxa. Is there an optimal number of metrics for MMIs? To explore this question, I created 1000 9-met...

  19. Metrical Phonology: German Sound System.

    ERIC Educational Resources Information Center

    Tice, Bradley S.

    Metrical phonology, a linguistic process of phonological stress assessment and diagrammatic simplification of sentence and word stress, is discussed as it is found in the English and German languages. The objective is to promote use of metrical phonology as a tool for enhancing instruction in stress patterns in words and sentences, particularly in…

  20. Metrics for Soft Goods Merchandising.

    ERIC Educational Resources Information Center

    Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.

    Designed to meet the job-related metric measurement needs of students interested in soft goods merchandising, this instructional package is one of five for the marketing and distribution cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational…

  1. Metrics for Hard Goods Merchandising.

    ERIC Educational Resources Information Center

    Cooper, Gloria S., Ed.; Magisos, Joel H., Ed.

    Designed to meet the job-related metric measurement needs of students interested in hard goods merchandising, this instructional package is one of five for the marketing and distribution cluster, part of a set of 55 packages for metric instruction in different occupations. The package is intended for students who already know the occupational…

  2. Metrication: A Guide for Consumers.

    ERIC Educational Resources Information Center

    Consumer and Corporate Affairs Dept., Ottawa (Ontario).

    The widespread use of the metric system by most of the major industrial powers of the world has prompted the Canadian government to investigate and consider use of the system. This booklet was developed to aid the consuming public in Canada in gaining some knowledge of metrication and how its application would affect their present economy.…

  3. Metrics--Libraries and Librarians

    ERIC Educational Resources Information Center

    Hall, Vivian S.; Anderson, Gregg

    1975-01-01

    The 1975 librarian must determine whether to begin collecting materials on the International System of Measurements (metric system). Librarians are urged to learn and use the metric system, provide displays, and collect materials to better serve their patrons. Bibliography. (Author/LS)

  4. Inching toward the Metric System.

    ERIC Educational Resources Information Center

    Moore, Randy

    1989-01-01

    Provides an overview and description of the metric system. Discusses the evolution of measurement systems and their early cultures, the beginnings of metric measurement, the history of measurement systems in the United States, the International System of Units, its general style and usage, and supplementary units. (RT)

  5. Numerical Calabi-Yau metrics

    NASA Astrophysics Data System (ADS)

    Douglas, Michael R.; Karp, Robert L.; Lukic, Sergio; Reinbacher, René

    2008-03-01

    We develop numerical methods for approximating Ricci flat metrics on Calabi-Yau hypersurfaces in projective spaces. Our approach is based on finding balanced metrics and builds on recent theoretical work by Donaldson. We illustrate our methods in detail for a one parameter family of quintics. We also suggest several ways to extend our results.

  6. How to Teach Metric Now.

    ERIC Educational Resources Information Center

    Worcester Public Schools, MA.

    This curriculum guide for grades K-6 was prepared to assist teachers and students in learning about the metric system. An introductory section presents a brief history of the metric system and the rationale for introducing it into the schools. Instructional objectives and suggested learning activities are presented for each grade level. The…

  7. Metric Activities, Grades K-6.

    ERIC Educational Resources Information Center

    Draper, Bob, Comp.

    This pamphlet presents worksheets for use in fifteen activities or groups of activities designed for teaching the metric system to children in grades K through 6. The approach taken in several of the activities is one of conversion between metric and English units. The majority of the activities concern length, area, volume, and capacity. A…

  8. What About Metric? Revised Edition.

    ERIC Educational Resources Information Center

    Barbrow, Louis E.

    Described are the advantages of using the metric system over the English system. The most common units of both systems are listed and compared. Pictures are used to exhibit use of the metric system in connection with giving prices or sizes of common items. Several examples provide computations of area, total weight of several objects, and volume;…

  9. Conversion to the Metric System

    ERIC Educational Resources Information Center

    Crunkilton, John C.; Lee, Jasper S.

    1974-01-01

    The authors discuss background information about the metric system and explore the effect of metrication of agriculture in areas such as equipment calibration, chemical measurement, and marketing of agricultural products. Suggestions are given for possible leadership roles and approaches that agricultural education might take in converting to the…

  10. Metric Supplement to Technical Drawing.

    ERIC Educational Resources Information Center

    Henschel, Mark

    This manual is intended for use in training persons whose vocations involve technical drawing to use the metric system of measurement. It could be used in a short course designed for that purpose or for individual study. The manual begins with a brief discussion of the rationale for conversion to the metric system. It then provides a…

  11. Metrication: A Guide for Consumers.

    ERIC Educational Resources Information Center

    Consumer and Corporate Affairs Dept., Ottawa (Ontario).

    The widespread use of the metric system by most of the major industrial powers of the world has prompted the Canadian government to investigate and consider use of the system. This booklet was developed to aid the consuming public in Canada in gaining some knowledge of metrication and how its application would affect their present economy.…

  12. Metrication report to the Congress

    NASA Technical Reports Server (NTRS)

    1989-01-01

    The major NASA metrication activity of 1988 concerned the Space Station. Although the metric system was the baseline measurement system for preliminary design studies, solicitations for final design and development of the Space Station Freedom requested use of the inch-pound system because of concerns with cost impact and potential safety hazards. Under that policy, however use of the metric system would be permitted through waivers where its use was appropriate. Late in 1987, several Department of Defense decisions were made to increase commitment to the metric system, thereby broadening the potential base of metric involvement in the U.S. industry. A re-evaluation of Space Station Freedom units of measure policy was, therefore, initiated in January 1988.

  13. 17 CFR 250.1 - Registration.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 17 Commodity and Securities Exchanges 3 2010-04-01 2010-04-01 false Registration. 250.1 Section... AND REGULATIONS, PUBLIC UTILITY HOLDING COMPANY ACT OF 1935 Registration and General Exemptions § 250.1 Registration. (a) Notification of registration. Notifications of registration pursuant to...

  14. 14 CFR 47.43 - Invalid registration.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Invalid registration. 47.43 Section 47.43... REGISTRATION Certificates of Aircraft Registration § 47.43 Invalid registration. Link to an amendment published... registration of an aircraft is invalid if, at the time it is made— (1) The aircraft is registered in a...

  15. 14 CFR 47.43 - Invalid registration.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Invalid registration. 47.43 Section 47.43... REGISTRATION Certificates of Aircraft Registration § 47.43 Invalid registration. Link to an amendment published... registration of an aircraft is invalid if, at the time it is made— (1) The aircraft is registered in a...

  16. 17 CFR 250.1 - Registration.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 17 Commodity and Securities Exchanges 3 2011-04-01 2011-04-01 false Registration. 250.1 Section... AND REGULATIONS, PUBLIC UTILITY HOLDING COMPANY ACT OF 1935 Registration and General Exemptions § 250.1 Registration. (a) Notification of registration. Notifications of registration pursuant to...

  17. 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.

  18. Estimating Landscape Pattern Metrics from a Sample of Land Cover

    EPA Science Inventory

    Although landscape pattern metrics can be computed directly from wall-to-wall land-cover maps, statistical sampling offers a practical alternative when complete coverage land-cover information is unavailable. Partitioning a region into spatial units (“blocks”) to create a samplin...

  19. Estimating Landscape Pattern Metrics from a Sample of Land Cover

    EPA Science Inventory

    Although landscape pattern metrics can be computed directly from wall-to-wall land-cover maps, statistical sampling offers a practical alternative when complete coverage land-cover information is unavailable. Partitioning a region into spatial units (“blocks”) to create a samplin...

  20. Weyl metrics and wormholes

    NASA Astrophysics Data System (ADS)

    Gibbons, Gary W.; Volkov, Mikhail S.

    2017-05-01

    We study solutions obtained via applying dualities and complexifications to the vacuum Weyl metrics generated by massive rods and by point masses. Rescaling them and extending to complex parameter values yields axially symmetric vacuum solutions containing singularities along circles that can be viewed as singular matter sources. These solutions have wormhole topology with several asymptotic regions interconnected by throats and their sources can be viewed as thin rings of negative tension encircling the throats. For a particular value of the ring tension the geometry becomes exactly flat although the topology remains non-trivial, so that the rings literally produce holes in flat space. To create a single ring wormhole of one metre radius one needs a negative energy equivalent to the mass of Jupiter. Further duality transformations dress the rings with the scalar field, either conventional or phantom. This gives rise to large classes of static, axially symmetric solutions, presumably including all previously known solutions for a gravity-coupled massless scalar field, as for example the spherically symmetric Bronnikov-Ellis wormholes with phantom scalar. The multi-wormholes contain infinite struts everywhere at the symmetry axes, apart from solutions with locally flat geometry.

  1. 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

  2. Groupwise registration of MR brain images with tumors

    NASA Astrophysics Data System (ADS)

    Tang, Zhenyu; Wu, Yihong; Fan, Yong

    2017-09-01

    A novel groupwise image registration framework is developed for registering MR brain images with tumors. Our method iteratively estimates a normal-appearance counterpart for each tumor image to be registered and constructs a directed graph (digraph) of normal-appearance images to guide the groupwise image registration. Particularly, our method maps each tumor image to its normal appearance counterpart by identifying and inpainting brain tumor regions with intensity information estimated using a low-rank plus sparse matrix decomposition based image representation technique. The estimated normal-appearance images are groupwisely registered to a group center image guided by a digraph of images so that the total length of ‘image registration paths’ to be the minimum, and then the original tumor images are warped to the group center image using the resulting deformation fields. We have evaluated our method based on both simulated and real MR brain tumor images. The registration results were evaluated with overlap measures of corresponding brain regions and average entropy of image intensity information, and Wilcoxon signed rank tests were adopted to compare different methods with respect to their regional overlap measures. Compared with a groupwise image registration method that is applied to normal-appearance images estimated using the traditional low-rank plus sparse matrix decomposition based image inpainting, our method achieved higher image registration accuracy with statistical significance (p  =  7.02  ×  10-9).

  3. Large deformation diffeomorphic registration of diffusion-weighted images.

    PubMed

    Zhang, Pei; Niethammer, Marc; Shen, Dinggang; Yap, Pew-Thian

    2012-01-01

    Registration of Diffusion-weighted imaging (DWI) data emerges as an important topic in magnetic resonance (MR) image analysis. As existing methods are often designed for specific diffusion models, it is difficult to fit to the registered data different models other than the one used for registration. In this paper we describe a diffeomorphic registration algorithm for DWI data in a large deformation setting. Our method generates spatially normalized DWI data and it is thus possible to fit various diffusion models after registration for comparison purposes. Our algorithm includes (1) a reorientation component, where each diffusion profile (DWI signal as a function on a unit sphere) is decomposed, reoriented and recomposed to form the orientation-corrected DWI profile, and (2) a large deformation diffeomorphic registration component to ensure one-to-one mapping in a large-structural-variation scenario. In addition our algorithm uses a geodesic shooting mechanism to avoid the huge computational resources that are needed to register high-dimensional vector-valued data. We also incorporate into our algorithm a multi-kernel strategy where anatomical structures at different scales are considered simultaneously during registration. We demonstrate the efficacy of our method using in vivo data.

  4. Fast 3D fluid registration of brain magnetic resonance images

    NASA Astrophysics Data System (ADS)

    Leporé, Natasha; Chou, Yi-Yu; Lopez, Oscar L.; Aizenstein, Howard J.; Becker, James T.; Toga, Arthur W.; Thompson, Paul M.

    2008-03-01

    Fluid registration is widely used in medical imaging to track anatomical changes, to correct image distortions, and to integrate multi-modality data. Fluid mappings guarantee that the template image deforms smoothly into the target, without tearing or folding, even when large deformations are required for accurate matching. Here we implemented an intensity-based fluid registration algorithm, accelerated by using a filter designed by Bro-Nielsen and Gramkow. We validated the algorithm on 2D and 3D geometric phantoms using the mean square difference between the final registered image and target as a measure of the accuracy of the registration. In tests on phantom images with different levels of overlap, varying amounts of Gaussian noise, and different intensity gradients, the fluid method outperformed a more commonly used elastic registration method, both in terms of accuracy and in avoiding topological errors during deformation. We also studied the effect of varying the viscosity coefficients in the viscous fluid equation, to optimize registration accuracy. Finally, we applied the fluid registration algorithm to a dataset of 2D binary corpus callosum images and 3D volumetric brain MRIs from 14 healthy individuals to assess its accuracy and robustness.

  5. Groupwise registration of MR brain images with tumors.

    PubMed

    Tang, Zhenyu; Wu, Yihong; Fan, Yong

    2017-08-04

    A novel groupwise image registration framework is developed for registering MR brain images with tumors. Our method iteratively estimates a normal-appearance counterpart for each tumor image to be registered and constructs a directed graph (digraph) of normal-appearance images to guide the groupwise image registration. Particularly, our method maps each tumor image to its normal appearance counterpart by identifying and inpainting brain tumor regions with intensity information estimated using a low-rank plus sparse matrix decomposition based image representation technique. The estimated normal-appearance images are groupwisely registered to a group center image guided by a digraph of images so that the total length of 'image registration paths' to be the minimum, and then the original tumor images are warped to the group center image using the resulting deformation fields. We have evaluated our method based on both simulated and real MR brain tumor images. The registration results were evaluated with overlap measures of corresponding brain regions and average entropy of image intensity information, and Wilcoxon signed rank tests were adopted to compare different methods with respect to their regional overlap measures. Compared with a groupwise image registration method that is applied to normal-appearance images estimated using the traditional low-rank plus sparse matrix decomposition based image inpainting, our method achieved higher image registration accuracy with statistical significance (p  =  7.02  ×  10(-9)).

  6. Rigid and elastic registration for coronary artery IVUS images.

    PubMed

    Sun, Zheng; Bai, Hua; Liu, Bingru

    2016-04-29

    Intravascular ultrasound (IVUS) has been widely used in diagnosis and interventional treatment of cardiac vessel diseases. The coronary artery IVUS images are usually polluted by motion artifacts caused by cardiac motion, pulsatile blood and catheter twist during continuous pullback acquisition. Strategies for rigid and elastic registration of coronary artery IVUS studies are developed to suppress the longitudinal motion and misalignment between successive frames. Rigid registration is performed by searching for the optimal matching for each frame in other cycles based on the cyclic variation of gray-scale features. The image sequence is gated to properly identify the frames in each cardiac phase. Then, elastic registration between frames is achieved through an optimization algorithm based on thin plate spline (TPS) to correct the misalignment of successive slices. Experimental results with in vivo image data shows that the rigid registration performs better than the offline ECG gating. The elastic mapping relation between lumen contours in successive frames is smooth and continuous. The serrated vessel wall borders in longitudinal cuts are smoothed after rigid registration while image segmentation and feature extraction are required. The point-to-point correspondence between lumen contours detected from two matched frames is obtained with elastic registration.

  7. Restricted surface matching: a new registration method for medical images

    NASA Astrophysics Data System (ADS)

    Gong, JianXing; Zamorano, Lucia J.; Jiang, Zhaowei; Nolte, Lutz P.; Diaz, Fernando

    1998-06-01

    Since its introduction to neurological surgery in the early 1980's, computer assisted surgery (CAS) with and without robotics navigation has been applied to several medical fields. The common issue all CAS systems is registration between two pre-operative 3D image modalities (for example, CT/MRI/PET et al) and the 3D image references of the patient in the operative room. In Wayne State University, a new way is introduced for medical image registration, which is different from traditional fiducial point registration and surface registration. We call it restricted surface matching (RSM). The method fast, convenient, accurate and robust. It combines the advantages from two registration methods mentioned before. Because of a penalty function introduced in its cost function, it is called `RSM'. The surface of a 3D image modality is pre-operatively extracted using segmentation techniques, and a distance map is created from such surface. The surface of another 3D reference is presented by a cloud of 3D points. At least three rough landmarks are used to restrict a registration not far away from global minimum. The local minimum issue is solved by use of a restriction for in the cost function and larger number of random starting points. The accuracy of matching is achieved by gradually releasing the restriction and limiting the influence of outliers. It only needs about half a minute to find the global minimum (for 256 X 256 X 56 images) in a SunSparc 10 station.

  8. Cortical sulcal atlas construction using a diffeomorphic mapping approach.

    PubMed

    Joshi, Shantanu H; Cabeen, Ryan P; Sun, Bo; Joshi, Anand A; Gutman, Boris; Zamanyan, Alen; Chakrapani, Shruthi; Dinov, Ivo; Woods, Roger P; Toga, Arthur W

    2010-01-01

    We present a geometric approach for constructing shape atlases of sulcal curves on the human cortex. Sulci and gyri are represented as continuous open curves in R3, and their shapes are studied as elements of an infinite-dimensional sphere. This shape manifold has some nice properties--it is equipped with a Riemannian L2 metric on the tangent space and facilitates computational analyses and correspondences between sulcal shapes. Sulcal mapping is achieved by computing geodesics in the quotient space of shapes modulo rigid rotations and reparameterizations. The resulting sulcal shape atlas is shown to preserve important local geometry inherently present in the sample population. This is demonstrated in our experimental results for deep brain sulci, where we integrate the elastic shape model into surface registration framework for a population of 69 healthy young adult subjects.

  9. Automated robust registration of grossly misregistered whole-slide images with varying stains

    NASA Astrophysics Data System (ADS)

    Litjens, G.; Safferling, K.; Grabe, N.

    2016-03-01

    Cancer diagnosis and pharmaceutical research increasingly depend on the accurate quantification of cancer biomarkers. Identification of biomarkers is usually performed through immunohistochemical staining of cancer sections on glass slides. However, combination of multiple biomarkers from a wide variety of immunohistochemically stained slides is a tedious process in traditional histopathology due to the switching of glass slides and re-identification of regions of interest by pathologists. Digital pathology now allows us to apply image registration algorithms to digitized whole-slides to align the differing immunohistochemical stains automatically. However, registration algorithms need to be robust to changes in color due to differing stains and severe changes in tissue content between slides. In this work we developed a robust registration methodology to allow for fast coarse alignment of multiple immunohistochemical stains to the base hematyoxylin and eosin stained image. We applied HSD color model conversion to obtain a less stain color dependent representation of the whole-slide images. Subsequently, optical density thresholding and connected component analysis were used to identify the relevant regions for registration. Template matching using normalized mutual information was applied to provide initial translation and rotation parameters, after which a cost function-driven affine registration was performed. The algorithm was validated using 40 slides from 10 prostate cancer patients, with landmark registration error as a metric. Median landmark registration error was around 180 microns, which indicates performance is adequate for practical application. None of the registrations failed, indicating the robustness of the algorithm.

  10. Image Navigation and Registration Performance Assessment Evaluation Tools for GOES-R ABI and GLM

    NASA Technical Reports Server (NTRS)

    Houchin, Scott; Porter, Brian; Graybill, Justin; Slingerland, Philip

    2017-01-01

    The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. This paper describes the software design and implementation of IPATS and provides preliminary test results.

  11. Registration Delay and Student Performance

    ERIC Educational Resources Information Center

    Siefken, Jason

    2017-01-01

    Tracking the difference between the time a first-year student is allowed to register for a course and the time he or she does register for a course (a student's registration delay), we notice a negative correlation between registration delay and final grade in a course. The difference between a student who registers within the first two minutes…

  12. METRICS DEVELOPMENT FOR PATENTS.

    PubMed

    Veiga, Daniela Francescato; Ferreira, Lydia Masako

    2015-01-01

    To develop a proposal for metrics for patents to be applied in assessing the postgraduate programs of Medicine III - Capes. From the reading and analysis of the 2013 area documents of all the 48 areas of Capes, a proposal for metrics for patents was developed to be applied in Medicine III programs. Except for the areas Biotechnology, Food Science, Biological Sciences III, Physical Education, Engineering I, III and IV and Interdisciplinary, most areas do not adopt a scoring system for patents. The proposal developed was based on the criteria of Biotechnology, with adaptations. In general, it will be valued, in ascending order, the deposit, the granting and licensing/production. It will also be assigned higher scores to patents registered abroad and whenever there is a participation of students. This proposal can be applied to the item Intellectual Production of the evaluation form, in subsection Technical Production/Patents. The percentage of 10% for academic programs and 40% for Masters Professionals should be maintained. The program will be scored as Very Good when it reaches 400 points or over; Good, between 200 and 399 points; Regular, between 71 and 199 points; Weak up to 70 points; Insufficient, no punctuation. Desenvolver uma proposta de métricas para patentes a serem aplicadas na avaliação dos Programas de Pós-Graduação da Área Medicina III - Capes. A partir da leitura e análise dos documentos de área de 2013 de todas as 48 Áreas da Capes, desenvolveu-se uma proposta de métricas para patentes, a ser aplicada na avaliação dos programas da área. Constatou-se que, com exceção das áreas Biotecnologia, Ciência de Alimentos, Ciências Biológicas III, Educação Física, Engenharias I, III e IV e Interdisciplinar, a maioria não adota sistema de pontuação para patentes. A proposta desenvolvida baseou-se nos critérios da Biotecnologia, com adaptações. De uma forma geral, foi valorizado, em ordem crescente, o depósito, a concessão e o

  13. Quantum correlations for the metric

    NASA Astrophysics Data System (ADS)

    Wetterich, C.

    2017-06-01

    We discuss the correlation function for the metric for homogeneous and isotropic cosmologies. The exact propagator equation determines the correlation function as the inverse of the second functional derivative of the quantum effective action. This formulation relates the metric correlation function employed in quantum gravity computations to cosmological observables as the graviton power spectrum. In the Einstein-Hilbert approximation for the effective action the on-shell graviton correlation function can be obtained equivalently from a product of mode functions which are solutions of the linearized Einstein equations. In contrast, the product of mode functions, often employed in the context of cosmology, does not yield the correlation function for the vector and scalar components of the metric fluctuations. We divide the metric fluctuations into "physical fluctuations," which couple to a conserved energy momentum tensor, and gauge fluctuations. On the subspace of physical metric fluctuations the relation to physical sources becomes invertible, such that the effective action and its relation to correlation functions no longer needs to involve a gauge fixing term. The physical metric fluctuations have a similar status as the Bardeen potentials, while being formulated in a covariant way. We compute the effective action for the physical metric fluctuations for geometries corresponding to realistic cosmologies.

  14. A Dynamic Testing Complexity Metric

    NASA Technical Reports Server (NTRS)

    Voas, Jeffrey

    1991-01-01

    This paper introduces a dynamic metric that is based on the estimated ability of a program to withstand the effects of injected "semantic mutants" during execution by computing the same function as if the semantic mutants had not been injected. Semantic mutants include: (1) syntactic mutants injected into an executing program and (2) randomly selected values injected into an executing program's internal states. The metric is a function of a program, the method used for injecting these two types of mutants, and the program's input distribution; this metric is found through dynamic executions of the program. A program's ability to withstand the effects of injected semantic mutants by computing the same function when executed is then used as a tool for predicting the difficulty that will be incurred during random testing to reveal the existence of faults, i.e., the metric suggests the likelihood that a program will expose the existence of faults during random testing assuming faults were to exist. If the metric is applied to a module rather than to a program, the metric can be used to guide the allocation of testing resources among a program's modules. In this manner the metric acts as a white-box testing tool for determining where to concentrate testing resources. Index Terms: Revealing ability, random testing, input distribution, program, fault, failure.

  15. Variable metric conjugate gradient methods

    SciTech Connect

    Barth, T.; Manteuffel, T.

    1994-07-01

    1.1 Motivation. In this paper we present a framework that includes many well known iterative methods for the solution of nonsymmetric linear systems of equations, Ax = b. Section 2 begins with a brief review of the conjugate gradient method. Next, we describe a broader class of methods, known as projection methods, to which the conjugate gradient (CG) method and most conjugate gradient-like methods belong. The concept of a method having either a fixed or a variable metric is introduced. Methods that have a metric are referred to as either fixed or variable metric methods. Some relationships between projection methods and fixed (variable) metric methods are discussed. The main emphasis of the remainder of this paper is on variable metric methods. In Section 3 we show how the biconjugate gradient (BCG), and the quasi-minimal residual (QMR) methods fit into this framework as variable metric methods. By modifying the underlying Lanczos biorthogonalization process used in the implementation of BCG and QMR, we obtain other variable metric methods. These, we refer to as generalizations of BCG and QMR.

  16. A Metric for Heterotic Moduli

    NASA Astrophysics Data System (ADS)

    Candelas, Philip; de la Ossa, Xenia; McOrist, Jock

    2017-09-01

    Heterotic vacua of string theory are realised, at large radius, by a compact threefold with vanishing first Chern class together with a choice of stable holomorphic vector bundle. These form a wide class of potentially realistic four-dimensional vacua of string theory. Despite all their phenomenological promise, there is little understanding of the metric on the moduli space of these. What is sought is the analogue of special geometry for these vacua. The metric on the moduli space is important in phenomenology as it normalises D-terms and Yukawa couplings. It is also of interest in mathematics, since it generalises the metric, first found by Kobayashi, on the space of gauge field connections, to a more general context. Here we construct this metric, correct to first order in {α^{\\backprime}} , in two ways: first by postulating a metric that is invariant under background gauge transformations of the gauge field, and also by dimensionally reducing heterotic supergravity. These methods agree and the resulting metric is Kähler, as is required by supersymmetry. Checking the metric is Kähler is intricate and the anomaly cancellation equation for the H field plays an essential role. The Kähler potential nevertheless takes a remarkably simple form: it is the Kähler potential of special geometry with the Kähler form replaced by the {α^{\\backprime}} -corrected hermitian form.

  17. GPS Metric Tracking Unit

    NASA Technical Reports Server (NTRS)

    2008-01-01

    As Global Positioning Satellite (GPS) applications become more prevalent for land- and air-based vehicles, GPS applications for space vehicles will also increase. The Applied Technology Directorate of Kennedy Space Center (KSC) has developed a lightweight, low-cost GPS Metric Tracking Unit (GMTU), the first of two steps in developing a lightweight, low-cost Space-Based Tracking and Command Subsystem (STACS) designed to meet Range Safety's link margin and latency requirements for vehicle command and telemetry data. The goals of STACS are to improve Range Safety operations and expand tracking capabilities for space vehicles. STACS will track the vehicle, receive commands, and send telemetry data through the space-based asset, which will dramatically reduce dependence on ground-based assets. The other step was the Low-Cost Tracking and Data Relay Satellite System (TDRSS) Transceiver (LCT2), developed by the Wallops Flight Facility (WFF), which allows the vehicle to communicate with a geosynchronous relay satellite. Although the GMTU and LCT2 were independently implemented and tested, the design collaboration of KSC and WFF engineers allowed GMTU and LCT2 to be integrated into one enclosure, leading to the final STACS. In operation, GMTU needs only a radio frequency (RF) input from a GPS antenna and outputs position and velocity data to the vehicle through a serial or pulse code modulation (PCM) interface. GMTU includes one commercial GPS receiver board and a custom board, the Command and Telemetry Processor (CTP) developed by KSC. The CTP design is based on a field-programmable gate array (FPGA) with embedded processors to support GPS functions.

  18. Automatic registration of satellite imagery

    NASA Technical Reports Server (NTRS)

    Fonseca, Leila M. G.; Costa, Max H. M.; Manjunath, B. S.; Kenney, C.

    1997-01-01

    Image registration is one of the basic image processing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-sensor/multi-spectral images has become an important issue. A wide range of registration techniques has been developed for many different types of applications and data. The objective of this paper is to present an automatic registration algorithm which uses a multiresolution analysis procedure based upon the wavelet transform. The procedure is completely automatic and relies on the grey level information content of the images and their local wavelet transform modulus maxima. The registration algorithm is very simple and easy to apply because it needs basically one parameter. We have obtained very encouraging results on test data sets from the TM and SPOT sensor images of forest, urban and agricultural areas.

  19. Double metric, generalized metric, and α' -deformed double field theory

    NASA Astrophysics Data System (ADS)

    Hohm, Olaf; Zwiebach, Barton

    2016-03-01

    We relate the unconstrained "double metric" of the "α' -geometry" formulation of double field theory to the constrained generalized metric encoding the spacetime metric and b -field. This is achieved by integrating out auxiliary field components of the double metric in an iterative procedure that induces an infinite number of higher-derivative corrections. As an application, we prove that, to first order in α' and to all orders in fields, the deformed gauge transformations are Green-Schwarz-deformed diffeomorphisms. We also prove that to first order in α' the spacetime action encodes precisely the Green-Schwarz deformation with Chern-Simons forms based on the torsionless gravitational connection. This seems to be in tension with suggestions in the literature that T-duality requires a torsionful connection, but we explain that these assertions are ambiguous since actions that use different connections are related by field redefinitions.

  20. Point Set Registration via Particle Filtering and Stochastic Dynamics

    PubMed Central

    Sandhu, Romeil; Dambreville, Samuel; Tannenbaum, Allen

    2013-01-01

    In this paper, we propose a particle filtering approach for the problem of registering two point sets that differ by a rigid body transformation. Typically, registration algorithms compute the transformation parameters by maximizing a metric given an estimate of the correspondence between points across the two sets of interest. This can be viewed as a posterior estimation problem, in which the corresponding distribution can naturally be estimated using a particle filter. In this work, we treat motion as a local variation in pose parameters obtained by running a few iterations of a certain local optimizer. Employing this idea, we introduce stochastic motion dynamics to widen the narrow band of convergence often found in local optimizer approaches for registration. Thus, the novelty of our method is threefold: First, we employ a particle filtering scheme to drive the point set registration process. Second, we present a local optimizer that is motivated by the correlation measure. Third, we increase the robustness of the registration performance by introducing a dynamic model of uncertainty for the transformation parameters. In contrast with other techniques, our approach requires no annealing schedule, which results in a reduction in computational complexity (with respect to particle size) as well as maintains the temporal coherency of the state (no loss of information). Also unlike some alternative approaches for point set registration, we make no geometric assumptions on the two data sets. Experimental results are provided that demonstrate the robustness of the algorithm to initialization, noise, missing structures, and/or differing point densities in each set, on several challenging 2D and 3D registration scenarios. PMID:20558877

  1. Effects of Image Contrast on Functional MRI Image Registration

    PubMed Central

    Gonzalez-Castillo, Javier; Duthie, Kristen N.; Saad, Ziad S.; Chu, Carlton; Bandettini, Peter A.; Luh, Wen-Ming

    2012-01-01

    Lack of tissue contrast and existing inhomogeneous bias fields from multi-channel coils have the potential to degrade the output of registration algorithms; and consequently degrade group analysis and any attempt to accurately localize brain function. Non-invasive ways to improve tissue contrast in fMRI images include the use of low flip angles (FAs) well below the Ernst angle and longer repetition times (TR). Techniques to correct intensity inhomogeneity are also available in most mainstream fMRI data analysis packages; but are not used as part of the pre-processing pipeline in many studies. In this work, we use a combination of real data and simulations to show that simple-to-implement acquisition/pre-processing techniques can significantly improve the outcome of both functional-to-functional and anatomical-to-functional image registrations. We also emphasize the need of tissue contrast on EPI images to be able to appropriately evaluate the quality of the alignment. In particular, we show that the use of low FAs (e.g., θ≤40°), when physiological noise considerations permit such an approach, significantly improves accuracy, consistency and stability of registration for data acquired at relatively short TRs (TR≤2s). Moreover, we also show that the application of bias correction techniques significantly improves alignment both for array-coil data (known to contain high intensity inhomogeneity) as well as birdcage-coil data. Finally, improvements in alignment derived from the use of the first infinite-TR volumes (ITVs) as targets for registration are also demonstrated. For the purpose of quantitatively evaluating the different scenarios, two novel metrics were developed: Mean Voxel Distance (MVD) to evaluate registration consistency, and Deviation of Mean Voxel Distance (dMVD) to evaluate registration stability across successive alignment attempts. PMID:23128074

  2. Public Participation Process for Registration Actions

    EPA Pesticide Factsheets

    Describes the process for registration actions which provides the opportunity for the public to comment on major registration decisions at a point in the registration process when comprehensive information and analysis are available.

  3. Robust Method For Robotic Mapping

    NASA Technical Reports Server (NTRS)

    Kuipers, Benjamin J.; Byun, Yung-Tai

    1992-01-01

    Robot constructs map from experience. Topological model consists of nodes and arcs corresponding to distinctive places and local travel edges linking nearby distinctive places. Model created by linking places and edges. Enables accumulation of metrical information with reduced vulnerability to metrical errors. Applications include robotic sentires, robotic delivery trucks, robotic floor cleaners, and robotic lawnmowers.

  4. Daylight metrics and energy savings

    SciTech Connect

    Mardaljevic, John; Heschong, Lisa; Lee, Eleanor

    2009-12-31

    The drive towards sustainable, low-energy buildings has increased the need for simple, yet accurate methods to evaluate whether a daylit building meets minimum standards for energy and human comfort performance. Current metrics do not account for the temporal and spatial aspects of daylight, nor of occupants comfort or interventions. This paper reviews the historical basis of current compliance methods for achieving daylit buildings, proposes a technical basis for development of better metrics, and provides two case study examples to stimulate dialogue on how metrics can be applied in a practical, real-world context.

  5. Truss Performance and Packaging Metrics

    NASA Technical Reports Server (NTRS)

    Mikulas, Martin M.; Collins, Timothy J.; Doggett, William; Dorsey, John; Watson, Judith

    2006-01-01

    In the present paper a set of performance metrics are derived from first principals to assess the efficiency of competing space truss structural concepts in terms of mass, stiffness, and strength, for designs that are constrained by packaging. The use of these performance metrics provides unique insight into the primary drivers for lowering structural mass and packaging volume as well as enabling quantitative concept performance evaluation and comparison. To demonstrate the use of these performance metrics, data for existing structural concepts are plotted and discussed. Structural performance data is presented for various mechanical deployable concepts, for erectable structures, and for rigidizable structures.

  6. Patient Registration Using Intraoperative Stereovision in Image-guided Open Spinal Surgery

    PubMed Central

    Fan, Xiaoyao; Paulsen, Keith D.; Roberts, David W.; Mirza, Sohail K.; Lollis, S. Scott

    2015-01-01

    Despite its widespread availability and success in open cranial neurosurgery, image-guidance technology remains more limited in use in open spinal procedures, in large part because of patient registration challenges. In this study, we evaluated the feasibility of using intraoperative stereovision (iSV) for accurate, efficient and robust patient registration in open spinal fusion surgery. Geometrical surfaces of exposed vertebrae were first reconstructed from iSV. A classical multi-start registration was then executed between point clouds generated from iSV and preoperative CT (pCT) images of the spine. With two pairs of feature points manually identified to facilitate the registration, an average registration accuracy of 1.43 mm in terms of surface-to-surface distance error was achieved in 8 patient cases using a single iSV image pair sampling 2–3 vertebral segments. The iSV registration error was consistently smaller than the conventional landmark approach for every case (average of 2.02 mm with the same error metric). The large capture ranges (average of 23.8 mm in translation and 46.0 deg in rotation) found in the iSV patient registration suggest the technique may offer sufficient robustness for practical application in the operating room. Although some manual effort was still necessary, the manually-derived inputs for iSV registration only needed to be approximate as opposed to be precise and accurate for the manual efforts required in landmark registration. The total computational cost of the iSV registration was 1.5 min on average, significantly less than the typical ~30 min required for the landmark approach. These findings support the clinical feasibility of iSV to offer accurate, efficient and robust patient registration in open spinal surgery, and therefore, its potential to further increase the adoption of image-guidance in this surgical specialty. PMID:25826802

  7. The distance discordance metric—a novel approach to quantifying spatial uncertainties in intra- and inter-patient deformable image registration

    NASA Astrophysics Data System (ADS)

    Saleh, Ziad H.; Apte, Aditya P.; Sharp, Gregory C.; Shusharina, Nadezhda P.; Wang, Ya; Veeraraghavan, Harini; Thor, Maria; Muren, Ludvig P.; Rao, Shyam S.; Lee, Nancy Y.; Deasy, Joseph O.

    2014-02-01

    Previous methods to estimate the inherent accuracy of deformable image registration (DIR) have typically been performed relative to a known ground truth, such as tracking of anatomic landmarks or known deformations in a physical or virtual phantom. In this study, we propose a new approach to estimate the spatial geometric uncertainty of DIR using statistical sampling techniques that can be applied to the resulting deformation vector fields (DVFs) for a given registration. The proposed DIR performance metric, the distance discordance metric (DDM), is based on the variability in the distance between corresponding voxels from different images, which are co-registered to the same voxel at location (X) in an arbitrarily chosen ‘reference’ image. The DDM value, at location (X) in the reference image, represents the mean dispersion between voxels, when these images are registered to other images in the image set. The method requires at least four registered images to estimate the uncertainty of the DIRs, both for inter- and intra-patient DIR. To validate the proposed method, we generated an image set by deforming a software phantom with known DVFs. The registration error was computed at each voxel in the ‘reference’ phantom and then compared to DDM, inverse consistency error (ICE), and transitivity error (TE) over the entire phantom. The DDM showed a higher Pearson correlation (Rp) with the actual error (Rp ranged from 0.6 to 0.9) in comparison with ICE and TE (Rp ranged from 0.2 to 0.8). In the resulting spatial DDM map, regions with distinct intensity gradients had a lower discordance and therefore, less variability relative to regions with uniform intensity. Subsequently, we applied DDM for intra-patient DIR in an image set of ten longitudinal computed tomography (CT) scans of one prostate cancer patient and for inter-patient DIR in an image set of ten planning CT scans of different head and neck cancer patients. For both intra- and inter-patient DIR, the

  8. ACME, a GIS tool for Automated Cirque Metric Extraction

    NASA Astrophysics Data System (ADS)

    Spagnolo, Matteo; Pellitero, Ramon; Barr, Iestyn D.; Ely, Jeremy C.; Pellicer, Xavier M.; Rea, Brice R.

    2017-02-01

    Regional scale studies of glacial cirque metrics provide key insights on the (palaeo) environment related to the formation of these erosional landforms. The growing availability of high resolution terrain models means that more glacial cirques can be identified and mapped in the future. However, the extraction of their metrics still largely relies on time consuming manual techniques or the combination of, more or less obsolete, GIS tools. In this paper, a newly coded toolbox is provided for the automated, and comparatively quick, extraction of 16 key glacial cirque metrics; including length, width, circularity, planar and 3D area, elevation, slope, aspect, plan closure and hypsometry. The set of tools, named ACME (Automated Cirque Metric Extraction), is coded in Python, runs in one of the most commonly used GIS packages (ArcGIS) and has a user friendly interface. A polygon layer of mapped cirques is required for all metrics, while a Digital Terrain Model and a point layer of cirque threshold midpoints are needed to run some of the tools. Results from ACME are comparable to those from other techniques and can be obtained rapidly, allowing large cirque datasets to be analysed and potentially important regional trends highlighted.

  9. Classifying helicopter gearbox faults using a normalized energy metric

    NASA Astrophysics Data System (ADS)

    Samuel, Paul D.; Pines, Darryll J.

    2001-02-01

    A normalized energy metric is used to classify seeded faults of the OH-58A main transmission. This gearbox comprises a two-stage transmission with an overall reduction of 17.44:1. Loaded gearbox test runs are used to evaluate the sensitivity of a non-stationary fault metric for early fault detection and classification. The non-stationary fault metric consists of a simple normalized energy index developed to account for a redistribution of sideband energy of the dominant mesh frequency and its harmonics in the presence of actual gearbox faults. This index is used to qualitatively assess the presence, type and location of gearbox faults. In this work, elements of the normalized energy metric are assembled into a feature vector to serve as input into a self-organizing Kohonen neural network classifier. This classifier maps vibration features onto a two-dimensional grid. A feedforward back propagation neural network is then used to classify different faults according to how they cluster on the two-dimensional self-organizing map. Gearbox faults of OH-58A main transmission considered in this study include sun gear spalling and spiral bevel gear scoring. Results from the classification suggest that the normalized energy metric is reasonably robust against false alarms for certain geartrain faults.

  10. Correcting image placement errors using registration control (RegC®) technology in the photomask periphery

    NASA Astrophysics Data System (ADS)

    Cohen, Avi; Lange, Falk; Ben-Zvi, Guy; Graitzer, Erez; Vladimir, Dmitriev

    2012-11-01

    The ITRS roadmap specifies wafer overlay control as one of the major tasks for the sub 40 nm nodes in addition to CD control and defect control. Wafer overlay is strongly dependent on mask image placement error (registration errors or Reg errors)1. The specifications for registration or mask placement accuracy are significantly tighter in some of the double patterning techniques (DPT). This puts a heavy challenge on mask manufacturers (mask shops) to comply with advanced node registration specifications. The conventional methods of feeding back the systematic registration error to the E-beam writer and re-writing the mask are becoming difficult, expensive and not sufficient for the advanced nodes especially for double pattering technologies. Six production masks were measured on a standard registration metrology tool and the registration errors were calculated and plotted. Specially developed algorithm along with the RegC Wizard (dedicated software) was used to compute a correction lateral strain field that would minimize the registration errors. This strain field was then implemented in the photomask bulk material using an ultra short pulse laser based system. Finally the post process registration error maps were measured and the resulting residual registration error field with and without scale and orthogonal errors removal was calculated. In this paper we present a robust process flow in the mask shop which leads up to 32% registration 3sigma improvement, bringing some out-of-spec masks into spec, utilizing the RegC® process in the photomask periphery while leaving the exposure field optically unaffected.

  11. Using TRACI for Sustainability Metrics

    EPA Science Inventory

    TRACI, the Tool for the Reduction and Assessment of Chemical and other environmental Impacts, has been developed for sustainability metrics, life cycle impact assessment, and product and process design impact assessment for developing increasingly sustainable products, processes,...

  12. Let's Make Metric Ice Cream

    ERIC Educational Resources Information Center

    Zimmerman, Marianna

    1975-01-01

    Describes a classroom activity which involved sixth grade students in a learning situation including making ice cream, safety procedures in a science laboratory, calibrating a thermometer, using metric units of volume and mass. (EB)

  13. Sizing Up the Metric System.

    ERIC Educational Resources Information Center

    Sherman, Helene J.

    1997-01-01

    Presents estimation as a tool for learning observation and measurement relationships for the metric system. Activities include constructing a meter tape and using mystery boxes to practice volume estimation and measurement. (AIM)

  14. Let's Make Metric Ice Cream

    ERIC Educational Resources Information Center

    Zimmerman, Marianna

    1975-01-01

    Describes a classroom activity which involved sixth grade students in a learning situation including making ice cream, safety procedures in a science laboratory, calibrating a thermometer, using metric units of volume and mass. (EB)

  15. Using TRACI for Sustainability Metrics

    EPA Science Inventory

    TRACI, the Tool for the Reduction and Assessment of Chemical and other environmental Impacts, has been developed for sustainability metrics, life cycle impact assessment, and product and process design impact assessment for developing increasingly sustainable products, processes,...

  16. Outstanding results from one year's activities of the ESA Metric Camera Working Group

    NASA Astrophysics Data System (ADS)

    Togliatti, G.

    1985-06-01

    Results of the Spacelab Metric Camera experiment on STS-9 in photogrammetry: (precision, triangulations, point identification and mapping, orthophotos); thematic interpretations; and geological interpretation are summarized. Performance is fairly satisfactory in topographic mapping and in geological and thematic applications, with shortcomings in features identification, mainly due to poor lighting conditions and absence of image motion compensation. The metric accuracy of the images is very good, and in several cases better than expected.

  17. Testing of the Apollo 15 Metric Camera System.

    NASA Technical Reports Server (NTRS)

    Helmering, R. J.; Alspaugh, D. H.

    1972-01-01

    Description of tests conducted (1) to assess the quality of Apollo 15 Metric Camera System data and (2) to develop production procedures for total block reduction. Three strips of metric photography over the Hadley Rille area were selected for the tests. These photographs were utilized in a series of evaluation tests culminating in an orbitally constrained block triangulation solution. Results show that film deformations up to 25 and 5 microns are present in the mapping and stellar materials, respectively. Stellar reductions can provide mapping camera orientations with an accuracy that is consistent with the accuracies of other parameters in the triangulation solutions. Pointing accuracies of 4 to 10 microns can be expected for the mapping camera materials, depending on variations in resolution caused by changing sun angle conditions.

  18. Metric Selection for Ecosystem Restoration

    DTIC Science & Technology

    2013-06-01

    Conceptual modeling can be used in a situation where there is little funding for monitoring and evaluation planning, and when planning needs to be done...ecosystem restoration monitoring and evaluation programs, compile a list of these previous metrics, and assess and narrow them down based on...and understanding of the system will likely correlate with the benefits gained from monitoring and evaluation . A more appropriate, robust metric

  19. Electromagnetic Metrics of Mental Workload.

    DTIC Science & Technology

    1987-09-01

    D-AiBS 285 ELECTROMAGNETIC METRICS OF MENTAL AdORIKLOAD(U) PURDUE t/, UNIV LAFAYETTE IN EEG SIGNAL PROCESSING LRB RUNON ET AL SEP 87 AFOSR-TR-87-ib.3...ACCESSION NO 61102F 2313 A4 11 TITLE (Include Security Claiwfication) Electromagnetic Metrics of Mental Workload (U) 12 PERSONAL AUTHOR(S) Aunon, J. I...sustained high level of workload can lead to mental exhaustion. Previous research has indicated that heart rate lariability and evoked potentials in

  20. Coverage Metrics for Model Checking

    NASA Technical Reports Server (NTRS)

    Penix, John; Visser, Willem; Norvig, Peter (Technical Monitor)

    2001-01-01

    When using model checking to verify programs in practice, it is not usually possible to achieve complete coverage of the system. In this position paper we describe ongoing research within the Automated Software Engineering group at NASA Ames on the use of test coverage metrics to measure partial coverage and provide heuristic guidance for program model checking. We are specifically interested in applying and developing coverage metrics for concurrent programs that might be used to support certification of next generation avionics software.