Tissue level segmentation and tracking of biological structures in microscopic images based on density maps

Authors:
K. Mosaliganti;A. Gelas;A. Gouaillard;S. Megason
Affiliations:
Harvard Medical School, Department of Systems Biology, Boston, MA;Harvard Medical School, Department of Systems Biology, Boston, MA;Harvard Medical School, Department of Systems Biology, Boston, MA;Harvard Medical School, Department of Systems Biology, Boston, MA
Venue:
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Year:
2009

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Abstract

During embryogenesis, cells coordinate to form geometric arrangements. These arrangements are initially noticed as stereotypic clumps of cells that further divide to form a rigorous structure with a high density of cells. In this work, we explore density-based segmentation and tracking of cellular structures as observed in microscopy images. Using a new modified form of the Mumford-Shah energy functional, we derived a variational level-set for density-based segmentation. The novelty of the work lies in evolving an initialized contour that represents a salient structure on density maps to automatically generate novel cell structures upon convergence. We validate our methods and show results on confocal ear images of the zebrafish embryo.