Variational level-set with gaussian shape model for cell segmentation

Authors:
A. Gelas;K. Mosaliganti;A. Gouaillard;L. Souhait;R. Noche;N. Obholzer;S. G. Megason
Affiliations:
Department of Systems Biology, Harvard Medical School, Boston, MA;Department of Systems Biology, Harvard Medical School, Boston, MA;Department of Systems Biology, Harvard Medical School, Boston, MA;Department of Systems Biology, Harvard Medical School, Boston, MA;Department of Systems Biology, Harvard Medical School, Boston, MA;Department of Systems Biology, Harvard Medical School, Boston, MA;Department of Systems Biology, Harvard Medical School, Boston, MA
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 3
Cited 1

A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model

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Abstract

In analysis of microscopy based images, a major challenge lies in splitting apart cells that appear to overlap because they are too densely packed. This task is complicated by the physics of the image acquisition that causes large variations in pixel intensities. Each image typically contains thousands of cells with each cell having a different orientation, size and intensity histogram. In this paper, a spatial intensity model of a nucleus is incorporated into [1] to aid cell segmentation from microscopy datasets. An energy functional is defined and with it the spatial intensity distribution of a nuclei is modeled as a Gaussian distribution with constant intensity background. Experimental results on a variety of microscopic data validate its effectiveness.