Challenges in Biological Image Analysis: Blood and Brains
|Event Date:||April 22, 2011|
|Speaker:||Scott T. Acton|
|Speaker Affiliation:||Department of Electrical & Computer Engineering,
University of Virginia
|Sponsor:||Communications, Networking, Signal & Image Processing|
|Contact Name:||Professor Edward Delp
|Open To:||ACCEPTABLE FOR ECE694A
The first part of the talk describes our work in tracking leukocytes (white blood cells) in vivo. Active contour methods are highlighted. Specifically, the Poisson inverse gradient method of contour/surface initialization and the vector field convolution method of contour evolution are presented. Results in leukocyte studies, as well as anatomical studies show the efficacy of these approaches.
The second portion of talk depicts ongoing work in neural image analysis. The knowledge of neuron structure is a central part of the understanding of the brain. Towards this end, development of a library describing the shapes and connectivity of neurons is necessary. Such an atlas is called the neurome. Construction of this library for a range of organisms will require automated image analysis. The talk describes our proposed automatic segmentation method, Tree2Tree, and our proposed neuron matching method, Path2Path. Tree2Tree is a graph based algorithm that extracts the complex shape of the neuron from 3D intensity images of neurons. The challenge lies in computing a consistent estimate of the neuronal branching and connectivity from the low contrast images, characterized by ambiguous edge information and inconsistent brightness patterns. Image processing and analysis methods associated with Tree2Tree, and the path-based matching of Path2Path, will be described. Preliminary results show that the Tree2Tree algorithm segments the neuron with high sensitivity and accuracy and that Path2Path may hold promise in matching neurons based on morphology, hierarchy and spatial position.
Scott T. Acton was born in California and is not very good at basketball. He is Professor of Electrical & Computer Engineering and of Biomedical Engineering at the University of Virginia. He received his M.S. and Ph.D. degrees at the University of Texas at Austin. He received his B.S. degree at Virginia Tech.
Professor Acton’s laboratory at UVA is called VIVA - Virginia Image and Video Analysis. They specialize in biomedical image analysis problems. The research emphasis of VIVA is video tracking and segmentation. Professor Acton has over 200 publications in the image analysis area including the books Biomedical Image Analysis: Tracking and Biomedical Image Analysis: Segmentation. Professor Acton has been at the University of Virginia since 2000. Before that time, he worked in the academic world for Oklahoma State University and in the engineering world for AT&T, Motorola and the Mitre Corporation.