Counting Sertoli Cells in Thin Testicular Tissue

This book develops a novel system to model the tubular structure in thin sections of testicular tissue and count the Sertoli cells. A three-phase method is proposed to model the tubular structure in microscopic images of the tissue; the model is deployed to detect the cells. In the first phase, the germ-mass, which represents the inside layer of tubules, are detected. All cells are detected by radial symmetry transform and then the graph cut algorithm is used to separate the germ cells. Each region covered by a compact set of germ cells is considered as the germ-mass. In the second phase, all bright areas in the image are detected and used to adjust the germ-mass regions. In this phase level-set and shape morphology are used for germ-mass detection. In the last phase, all edges that are line-like are identified and straight lines are fitted to the edges. The lines are later connected to compensate for the broken parts of the tubules' boundaries. At the end, the system is applied to detect the Sertoli cells.

Autorentext

Currently, Rahim is PhD student at Strasbourg University, France working on 3D people tracking. Rahim has a M.S. computer science from Uppsala University, Sweden, and M.S. of Artificial Intelligence from Isfahan University, Iran.He worked as lecturer at Azad university of Boukan between 2009 and 2010. He is a member of Iranian Fuzzy System Society.