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Microscopy Image Analysis: Blob Segmentation using Geodesic Active Contours

Mosaliganti, kishore, gelas, arnaud, gouaillard, alexandre, Megason, Sean
Singapore Agency for Science Technology and Research
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/1531
New: Prefer using the following doi: https://doi.org/10.54294/8est51
Published in The Insight Journal - 2009 January - June.
Submitted by Alexandre Gouaillard on 2009-03-11 09:21:54.

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.