Microscopy Image Analysis: Blob Segmentation using Geodesic Active Contours
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/1531
An Insight Toolkit (ITK) processing framework for blob segmentation with applications to microscopy
images is presented in this paper. Our algorithm is a refinement of the work of Mosaliganti et al. [3] for
splitting cell clusters. The basic idea is to incorporate as many cues as possible into developing a suitable
level-set speed function so that an evolving contour exactly segments a cell/nuclei blob. We use image
gradients, distance maps, multiple channel information and a shape model to drive the evolution. The
framework consists of a linear pipeline of 6 new ITK filters which are applied in succession to generate
the segmentation. The filters extract the cell foreground, construct the speed image, find seed points for
evolution and collect cell statistics from the segmentation. We include 2D/3D example code, parameter
settings and show the results generated on confocal images of the zebrafish embryo.
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Categories: Feature extraction, Level sets, Segmentation
Keywords: Microscopy, segmentation, geodesic active contour
Toolkits: ITK
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