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Spatial analysis of gene localization using fluorescent in-situ hybridization (FISH) labeling is potentially a new method for early cancer detection. Current methodology relies heavily upon accurate segmentation of cell nuclei and FISH signals in tissue sections. While automatic FISH signal detection is a relatively simpler task, accurate nuclei segmentation is still a manual process which is fairly...
Communications between cells in large part drive tissue development and function, as well as disease-related processes such as tumorigenesis. Understanding the mechanistic bases of these processes necessitates quantifying specific molecules in adjacent cells or cell nuclei of intact tissue. However, a major restriction on such analyses is the lack of an efficient method that correctly segments each...
We present a highly robust, semi-automatic algorithm for segmenting individual, fluorescence-labeled, whole cells or cell nuclei (objects) from 3D confocal microscope images of tissue. The core of the algorithm is an extension of dynamic programming that finds the surface as a series of overlapping ribbons, where the mean intensity per unit area within each ribbon is a global maximum. Consequently,...
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