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检索条件"机构=Computer Vision and Image Analysis"

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Visualization of High Dimensional Data using an Automated 3D Star Co-ordinate System

Visualization of High Dimensional Data using an Automated 3D...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： J.S. Shaik M. Yeasin Computer Vision Pattern and Image Analysis Laboratory Electrical and Computer Engineering University of Memphis Memphis TN USA

This paper presents a 3D star coordinate-based visualization technique for exploratory data analysis. To improve the data visualization and reveal the hidden patterns in complex high dimensional data sets, first the 2D star coordinate system is extended to the 3D star coordinate system. An autonomous procedure is defined to find the best configuration for the 3D star coordinate system based on cluster validation measures. To illustrate the efficacy of the proposed techniques, empirical analysis were conducted on a number of synthetic (Five dimensional Gaussian distribution with three classes) and real (Fisher's IRIS, Leukemia, Gastric cancer and Petroleum datasets) databases. Empirical analyses shows that automated 3D star coordinate system helps in better visualization of the complex high dimensional data when compared to 2D star coordinate system and also other projection-based visualization techniques. Also the automated configuration for 3D star coordinate system reveals the hidden patterns in the complex datasets without human intervention.

关键词： Data visualization Data analysis Data mining Visual databases Humans computer vision image analysis Laboratories Coordinate measuring machines Gaussian distribution

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A Progressive Framework for Two-Way Clustering Using Adaptive Subspace Iteration for Functionally Classifying Genes

A Progressive Framework for Two-Way Clustering Using Adaptiv...

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International Joint Conference on Neural Networks (IJCNN)

作者： J.S. Shaik M. Yeasin Computer Vision Pattern and Image Analysis Laboratory Department of Electrical and Computer Engineering University of Memphis Memphis TN USA

This paper presents an adaptive subspace based two-way clustering of microarray data. To analyze the data at various scales a "Progressive" framework is introduced. The goals are to functionally classify genes and also to find differentially expressed genes in microarray expression profiles. Empirical analysis on Colon Cancer dataset shows that ASI performs favorably in grouping genes with similar functions and finding genes that may have been involved in the formation of colon cancer. It was also observed that the proposed algorithm is robust against ordering of samples and yield results consistent with ground truth information.

关键词： Clustering algorithms Cancer Colon Data analysis Robustness Biological tissues Proteins computer vision image analysis Performance analysis

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Functionally Classifying Genes from Microarray Data Using Linear and Non-linear Data Projection

Functionally Classifying Genes from Microarray Data Using Li...

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ACS/IEEE International Conference on computer Systems and Applications

作者： J. Shaik M. Yeasin Computer Vision Pattern and Image Analysis (CVPIA) laboratory Department of Electrical and Computer Engineering University Of Memphis Memphis TN USA

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Fully-automated analysis of muscle fiber images with combined region and edge-based active contours

Fully-automated analysis of muscle fiber images with combine...

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Workshops Bildverarbeitung fur die Medizin: Algorithmen Systeme Anwendungen, BVM 2006 - Workshop on image Processing for Medicine: Algorithms - Systems - Applications, BVM 2006

作者： Brox, Thomas Kim, Yoo-Jin Weickert, Joachim Feiden, Wolfgang Computer Vision and Pattern Recognition Group University of Bonn Romerstr. 164 53117 Bonn Germany Institute of Neuropathology Saarland University 66421 Homburg/Saar Germany Math. Image Analysis Group Saarland University 66041 Saarbrücken Germany

ISBN: (纸本)9783540321361

This paper presents a new approach to automated muscle fiber analysis based on segmenting myofibers with combined region and edge-based active contours. It provides reliable and fully-automated processing, thus, enabling time-saving batch processing of the entire biopsy sample stemming from routinely HE-stained cryostat sections. The method combines color, texture, and edge cues in a level set based active contour model succeeded by a refinement with morphological filters. Falsepositive segmentations as compared to former methods are minimized. A quantitative comparison between manual and automated analysis of muscle fibers images did not reveal any significant differences. We gratefully acknowledge partial funding by the DFG.

关键词： Batch data processing

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Performance Evaluation of Subspace-based Algorithm in Selecting Differentially Expressed Genes and Classification of Tissue Types from Microarray Data

Performance Evaluation of Subspace-based Algorithm in Select...

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International Joint Conference on Neural Networks (IJCNN)

作者： J.S. Shaik M. Yeasin Computational Vision Pattern and Image Analysis Laboratory Department of Electrical and Computer Engineering University of Memphis Memphis TN USA

This paper presents the implementation and evaluation of subspace-based clustering algorithm for robust selection of differentially expressed genes as well as the classification of tissue types from microarray data. The performance of the proposed algorithm is compared against other well known clustering algorithms and the quality of clusters is evaluated using a number of cluster validation indices. Empirical analyses on a number of synthetic and real microarray data sets suggest that the proposed subspace-based algorithm is robust in selecting differentially expressed genes and performs significantly better compared to popular clustering algorithms in selecting differentially expressed genes and classifying different tissue types.

关键词： Clustering algorithms Robustness Algorithm design and analysis Data analysis Partitioning algorithms computer vision image analysis Performance analysis Biomedical imaging Diseases

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Flowing crossfade of endoscopic images for the generation of a mosaic 1

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Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2005 - Workshop on image Processing for Medicine: Algorithms - Systems - Applications, BVM 2005

作者： Wald, Diana Reeff, Mireille Székely, Gabor Cattin, Philippe Paulus, Dietrich Medical Image Analysis and Visualization Group Computer Vision Laboratory Swiss Federal Institute of Technology Sternwartstr. 7 CH-8092 Zurich Switzerland Institut für Computervisualistik Universitätsstr. 1 D-56070 Koblenz Germany

ISBN: (数字)9783540264316

ISBN: (纸本)3540250522

Im Beitrag wird ein neues Verfahren zum fließenden Überblenden von Endoskopiebildern vorgestellt. Spezielles Augenmerk wird dabei auf die Erhaltung von feinsten Details in den Aufnahmen und einen guten visuellen Gesamteindruck gelegt. Die Bilder werden zunächst in ihrer Intensität angeglichen. Die Überlappungsbereiche werden anschließend mit dem neuen Verfahren überblendet.

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Bit-rate allocation control and quality improvement for color channels in HMVQ image compression

Bit-rate allocation control and quality improvement for colo...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Jiangling Guo P. Shrivastava K. Kepley Shuyu Yang S. Mitra B. Nutter Department of Electrical and Computer Engineering Computer Vision and Image Analysis Laboratory Texas Tech University USA Computer Vision and Image Analysis Lab Department of Electrical and Computer Engineering Texas Tech University USA

Medical images usually require higher fidelity than commonly used natural images, especially with respect to detail preservation. Color medical images also require a higher degree of color preservation. In this paper, we present the extension of the novel gray-scale image compression technique, hybrid multi-scale vector quantization (HMVQ) to color image compression. Limitations of common color image compression methods in controlling bit-rate allocation for color channels are discussed, and the ability of HMVQ in overcoming such limitations while improving the color quality is demonstrated.

关键词： image coding Biomedical imaging Medical diagnostic imaging Entropy image color analysis Gray-scale Pixel image storage Transform coding Quantization

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An automated, segmentation-based, rigid registration system for Cervigram/spl trade/ images utilizing simple clustering and active contour techniques

An automated, segmentation-based, rigid registration system ...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： P. King S. Mitra B. Nutter Computer Vision and Image Analysis Lab Department of Electrical and Computer Engineering Texas Tech University Lubbock TX USA

In this article, a technique for the automated registration of Cervigram/spl trade/ images will be introduced. The motivation for the development of such a technique is warranted by the fact that registration is often a first step to other, more sophisticated, algorithms useful in medical applications. Such algorithms are typically processes developed for the tracking and monitoring of patient health. The registration described in this article is segmentation-based and utilizes a combination of clustering- and active contour-based methodologies. The clustering algorithm is used to obtain an initial contour that will subsequently serve as initialization for an active contour. The active contour, in conjunction with various internal and external forces, should converge to a more precise segmentation of the region of interest which, in this application, is the cervix. Once the segmentations are completed, more traditional registration techniques, such as those of Fourier or correlation-based techniques, may be used to register the segmented images with more accuracy as the adverse effects stemming from the highly variable background features are no longer a source of error. For illustration purposes, the results from two patients are demonstrated at the end of this article.

关键词： image segmentation Active contours computer vision Clustering algorithms Cervical cancer image analysis image converters Biomedical imaging image color analysis Medical services

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Using real shadows to create virtual ones

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13th Scandinavian Conference on image analysis, SCIA 2003

作者： Madsen, Claus B. Laboratory of Computer Vision and Image Analysis Aalborg University Aalborg EastDK-9220 Denmark

ISBN: (纸本)3540406018

In Augmented Reality (AR) real imagery is superimposed by computer graphics renderings of virtual objects. This paper addresses the problem of creating the illusion that the virtual objects cast credible shadows in the real scenario. A step towards this is to be able to detect shadow regions in images of natural scenes, and this paper describes an approach to such shadow detection. The shadow detection can distinguish between directly lit areas, penumbra (half-shadow) areas, and umbra (full shadow) areas. Furthermore, it is demonstrated how virtual shadows can be created which appear very similar to the real shadows. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Augmented reality

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Combining the advantages of local and global optic flow methods

Combining the advantages of local and global optic flow meth...

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24th Symposium of the German Pattern Recognition Association, DAGM 2002

作者： Bruhn, Andres Weickert, Joachim Schnorr, Christoph Mathematical Image Analysis Group Faculty of Mathematics and Computer Science Saarland University 66041 Saarbrücken Germany Computer Vision Graphics and Pattern Recognition Group Department of Mathematics and Computer Science University of Mannheim 68131 Mannheim Germany

ISBN: (纸本)354044209X

Differential methods are frequently used techniques for optic flow computations. They can be classified into local methods such as the Lucas-Kanade technique or Bigün's structure tensor method, and into global methods such as the Horn-Schunck approach and its modifications. Local methods are known to be more robust under noise, while global techniques yield 100% dense flow fields. No clear attempts to combine the advantages of these two classes of methods have been made in the literature so far. This problem is addressed in our paper. First we juxtapose the role of smoothing processes that are required in local and global differential methods for optic flow computation. This discussion motivates us to introduce and evaluate a novel method that combines the advantages of local and global approaches: It yields dense flow fields that are robust against noise. Finally experiments with different sequences are performed demonstrating its excellent results. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Flow fields

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