Towards Automated Bioimage Analysis: From Features to Semantics

B. S. Manjunath, B. Sumengen, Z. Bi, J. Byun, M. El-Saban, D. Fedorov, N. Vu
Center for Bio-Image Informatics
Department of Electrical and Computer Engineering
University of California, Santa Barbara, CA 93106-9560


Recent advances in bio-molecular imaging have afforded biologists a more thorough understanding of cellular functions in complex tissue structures. For example, high resolution fluorescence images of the retina reveal details about tissue restructuring during detachment experiments. Time sequence imagery of microtubules provides insight into subcellular dynamics in response to cancer treatment drugs. However, technological progress is accompanied by a rapid proliferation of image data. Traditional analysis methods, namely manual measurements and qualitative assessments, become time consuming and are often nonreproducible. Computer vision tools can efficiently analyze these vast amounts of data with promising results. This paper provides an overview of several challenges faced in bioimage processing and our recent progress in addressing these issues.
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B. S. Manjunath, B. Sumengen, Z. Bi, J. Byun, M. El-Saban, D. Fedorov and N. Vu,
IEEE International Symposium on Biomedical Imaging (ISBI), pp. 255-258, Crystal City, CA, Apr. 2006.
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