Tissue level segmentation and tracking of biological structures in microscopic images based on density maps
Kishore R. Mosaliganti, Arnaud Gelas, Alexandre Gouaillard, Sean G. Megason · 2009
During embryogenesis, cells coordinate to form geometric arrangements. These arrangements are initially noticed as stereotypical 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.