A narrow-band level-set method with dynamic velocity for neural stem cell cluster segmentation

Abstract

Neural Stem Cells (NSCs) have a remarkable capacity to proliferate and differentiate to other cell types. This ability to differentiate to desirable phenotypes has motivated clinical interests, hence the interest here to segment Neural Stem Cell (NSC) clusters to locate the NSC clusters over time in a sequence of frames, and in turn to perform NSC cluster motion analysis. However the manual segmentation of such data is a tedious task. Thus, due to the increasing amount of cell data being collected, automated cell segmentation methods are highly desired. In this paper a novel level set based segmentation method is proposed to accomplish this segmentation. The method is initialization insensitive, making it an appropriate solution for automated segmentation systems. The proposed segmentation method has been successfully applied to NSC cluster segmentation. © Springer-Verlag Berlin Heidelberg 2005.