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arXiv 2018年

作者： Batabyal, Tamal Department of Electrical and Computer Engineering Virginia Image and Video Analysis Laboratory University of Virginia United States Charlottesville VA22904 United States

In the study of neurons, morphology influences function. The complexity in the structure of neurons poses a challenge in the identification and analysis of similar and dissimilar neuronal cells. Existing methodologies carry out structural and geometrical simplifications, which substantially change the morphological statistics. Using digitally-reconstructed neurons, we extend the work of Path2Path as ElasticPath2Path, which seamlessly integrates the graph-theoretic and differentialgeometric frameworks. By decomposing a neuron into a set of paths, we derive graph metrics, which are path concurrence and path hierarchy. Next, we model each path as an elastic string to compute the geodesic distance between the paths of a pair of neurons. Later, we formulate the problem of finding the distance between two neurons as a path assignment problem with a cost function combining the graph metrics and the geodesic deformation of paths. ElasticPath2Path is shown to have superior performance over the state of the art. Copyright © 2018, The Authors. All rights reserved.

关键词： Neurons

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Functional aspects of meningeal lymphatics in ageing and Alzheimer's disease (vol 560, pg 185, 2018)

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NATURE 2018年第7734期564卷 E7-E7页

作者： Da Mesquita, Sandro Louveau, Antoine Vaccari, Andrea Smirnov, Igor Cornelison, R. Chase Kingsmore, Kathryn M. Contarino, Christian Onengut-Gumuscu, Suna Farber, Emily Raper, Daniel Viar, Kenneth E. Powell, Romie D. Baker, Wendy Dabhi, Nisha Bai, Robin Cao, Rui Hu, Song Rich, Stephen S. Munson, Jennifer M. Lopes, M. Beatriz Overall, Christopher C. Acton, Scott T. Kipnis, Jonathan Center for Brain Immunology and Glia (BIG) University of Virginia Charlottesville USA Department of Neuroscience University of Virginia Charlottesville USA Virginia Image and Video Analysis Laboratory Department of Electrical and Computer Engineering University of Virginia Charlottesville USA Department of Biomedical Engineering University of Virginia Charlottesville USA Department of Mathematics University of Trento Povo Italy Center for Public Health Genomics University of Virginia Charlottesville USA Department of Neurosurgery University of Virginia Health System Charlottesville USA Department of Biomedical Engineering and Mechanics College of Engineering Virginia Tech Blacksburg USA Department of Pathology University of Virginia Charlottesville USA

Change history: In this Article, Extended Data Fig. 9 was appearing as Fig. 2 in the HTML, and in Fig. 2, the panel labels 'n' and 'o' overlapped the figure; these errors have been corrected online.

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A statistical approach for shadow detection using spatio-temporal contexts

A statistical approach for shadow detection using spatio-tem...

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IEEE International Conference on image Processing

作者： Yiyang Liu Don Adjeroh Video and Image Processing Laboratory Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV USA Video and Image Processing Laboratory Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV USA

Background subtraction is an important step used to segment moving regions in surveillance videos. However, cast shadows are often falsely labeled as foreground objects, which may severely degrade the accuracy of object localization and detection. Effective shadow detection is necessary for accurate foreground segmentation, especially for outdoor scenes. Based on the characteristics of shadows, such as luminance reduction, chromaticity invariance and texture invariance, we introduce a nonparametric framework for modeling surface behavior under cast shadows. To each pixel, we assign a potential shadow value with a confidence weight, indicating the probability that the pixel location is an actual shadow point. Given an observed RGB value for a pixel in a new frame, we use its recent spatio-temporal context to compute an expected shadow RGB value. The similarity between the observed and the expected shadow RGB values determines whether a pixel position is a true shadow. Experimental results show the performance of the proposed method on a suite of standard indoor and outdoor video sequences.

关键词： Pixel Light sources Color Lighting video sequences Context Histograms

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Deconvolutional speckle reducing anisotropic diffusion

Deconvolutional speckle reducing anisotropic diffusion

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IEEE International Conference on image Processing

作者： S.T. Acton Virginia Image and Video Analysis C.L. Brown Department of Electrical & Computer Engineering Department of Biomedical Engineering University of Virginia Charlottesville VA USA

In order to propel the analysis of medical ultrasound imagery from qualitative observation to quantitative measurement, the obstacles of distortion from speckle and from blurring due to the point spread function must be overcome. A recent partial differential equation (PDE) based enhancement technique has improved the ability to segment ultrasound images and to detect salient edges. However, this diffusion method often distorts the size of image features and may in fact efface subtle features. This paper proposes a new PDE that combines the enhancement of speckle reducing anisotropic diffusion (SRAD) with the mechanism of deconvolution. The resulting method, called deconvolutional speckle reducing anisotropic diffusion (DeSpeRADo), surpasses the edge localization ability of SRAD while yielding lower error in terms of area estimation and improved detection of fine features. A comparative study employs 100 experiments to contrast the quantification enabled by adaptive filtering, inverse filtering, diffusion and the new DeSpeRADo technique.

关键词： Speckle Anisotropic magnetoresistance image edge detection Ultrasonic imaging Adaptive filters Propulsion image analysis Biomedical imaging Distortion measurement Ultrasonic variables measurement

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A DCT based gradient vector flow snake for object boundary detection

A DCT based gradient vector flow snake for object boundary d...

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IEEE Southwest Symposium on image Analysis and Interpretation

作者： Jinshan Tang S.T. Acton Virginia Image and Video Processing (VIVA) Department of Electrical and Computer Engineering University of Virginia Charlottesville VA USA

The paper proposes a new gradient vector flow (GVF) snake based on the discrete cosine transform (DCT) for object boundary detection. In order to develop the DCT GVF snake, for each pixel in the spatial domain, we compute the two dimensional DCT in its local neighborhood. A contrast measure derived from the local DCT coefficients is used to compute the gradient vector flow field, which is employed as the external force to drive the snake to the object edges. The advantage of the DCT GVF snake lies in its robustness to multiplicative noise. The DCT GVF snake is applied to object boundary detection in images with multiplicative noise. Experiments show the boundary detection result obtained by the DCT GVF snake is more accurate than that obtained by the original GVF snake.

关键词： Discrete cosine transforms Object detection image segmentation Active contours Additive noise Force measurement Noise reduction Filters Fluid flow measurement Noise robustness

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Active Contours with Area-Weighted Binary Flows for Segmenting Low SNR imagery

Active Contours with Area-Weighted Binary Flows for Segmenti...

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Proceedings: 2003 International Conference on image Processing, ICIP-2003

作者： Yu, Yongjian Acton, Scott T. Virginia Image and Video Analysis Electrical and Computer Engineering University of Virginia Charlottesville VA 22903

We investigate the detection of region boundaries in low SNR images using region based active contours. In this paper, we first show that the region based active contours models based on the region mean-difference binary flows suffer from two drawbacks when being applied to the detection of low SNR objects: (1) the contours give biased boundary locations if the image is smoothed with a linear filter;(2) the contours detect numerous false boundaries if the image is not prefiltered. Toward this end, we present a model that quantifies the contour location bias. Then, we derive a new region based model to detect the boundaries of objects in low SNR imagery, based on techniques of curve evolution, area-weighted mean-difference binary flows, and level sets. Finally, we present various experimental results to illustrate that the area-weighted technique can overcome the drawbacks of the existing method.

关键词： image analysis

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image retrieval using segmentation

Image retrieval using segmentation

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2003 IEEE Systems and Information engineering Design Symposium, SIEDS 2003

作者： Avula, S.R. Tang, Jinshan Acton, S.T. Virginia Image and Video Analysis Department of Electrical and Computer Engineering University of Virginia United States

ISBN: (纸本)0974455903

A novel algorithm for image retrieval is presented. The basic idea of the new algorithm is that the constituent segments of the images are used to retrieve images within a digital library. image retrieval using segments is distinctive in that the local features of the image are used to retrieve the image instead of the typically utilized global features. In our algorithm, the given image is first segmented into dominant components and then the features of these components are extracted to perform retrieval. The features corresponding to each component are used to calculate the distance between components in the matching process. Each image is ranked based on the component wise distance measure with respect to the query component. One of the advantages of the algorithm is that, for a given retrieval image, the user can select a query segment with which to perform retrieval, thus it can satisfy different needs from different users. © 2003 Univesity of virginia.

关键词： image segmentation

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image retrieval using segmentation

Image retrieval using segmentation

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IEEE Symposium on Systems and Information engineering Design, SIEDS

作者： S.R. Avula Jinshan Tang S.T. Acton Virginia Image and Video AnalysisDeprubnent of Electrical and Computer Engineering University of Virginia USA

关键词： image retrieval image segmentation Gray-scale Information retrieval image databases image storage Content based retrieval Shape Color image converters

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A decentralized image retrieval system for education

A decentralized image retrieval system for education

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2003 IEEE Systems and Information engineering Design Symposium, SIEDS 2003

作者： Tang, Jinshan Acton, S.T. Virginia Image and Video Analysis Department of Electrical and Computer Engineering University of Virginia VA22903 United States

ISBN: (纸本)0974455903

We describe the development of a decentralized image retrieval system for education (DIRECT). With DIRECT, content based image retrieval (CBIR) is a service that will run autonomously;the constituent collections will not need to be modified to accommodate DIRECT. DIRECT applies a consistent CBIR mechanism to the entire system and gives CBIR functionality to collections without effort by the collection providers. Collections that do not have their own CBIR system or are not able to invest in a CBIR system (such as small collections or collections that do not contain a large proportion of images) will gain greater distribution of their holdings via DIRECT's CBIR functionality. The DIRECT service finds the collections in the library and requests the images using the same method that the portal uses to search and request images. DIRECT will perform feature extraction on the images and store the features in its own database. A portal or client application can query DIRECT, and it will use the features of the desired image to search the library for images with the same features. DIRECT will automatically monitor collections in order to keep the DIRECT index up-to-date. © 2003 Univesity of virginia.

关键词： Feature extraction

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A decentralized image retrieval system for education

A decentralized image retrieval system for education

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IEEE Symposium on Systems and Information engineering Design, SIEDS

作者： Jinshan Tang S.T. Acton Image and Video Analysis Department of Electrical and Computer Engineering University of Virginia VA USA

We describe the development of a decentralized image retrieval system for education (DIRECT). With DIRECT, content based image retrieval (CBIR) is a service that will run autonomously; the constituent collections will not need to be modified to accommodate DIRECT. DIRECT applies a consistent CBIR mechanism to the entire system and gives CBIR functionality to collections without effort by the collection providers. Collections that do not have their own CBIR system or are not able to invest in a CBIR system (such as small collections or collections that do not contain a large proportion of images) will gain greater distribution of their holdings via DIRECT's CBIR functionality. The DIRECT service finds the collections in the library and requests the images using the same method that the portal uses to search and request images. DIRECT will perform feature extraction on the images and store the features in its own database. A portal or client application can query DIRECT, and it will use the features of the desired image to search the library for images with the same features. DIRECT will automatically monitor collections in order to keep the DIRECT index up-to-date.

关键词： image retrieval Content based retrieval computer science education image analysis Portals Feature extraction image databases Spatial databases Software libraries Educational programs

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