UC Riverside

Blebbing is an important biological indicator in determining the health of human embryonic stem cells (hESC). Especially, areas of a bleb sequence in a video are often used to distinguish two cell blebbing behaviors in hESC: dynamic and apoptotic blebbings. This paper analyzes various segmentation methods for bleb extraction in hESC videos and introduces a bio-inspired score function to improve the performance in bleb extraction. Full bleb formation consists of bleb expansion and retraction. Blebs change their size and image properties dynamically in both processes and between frames. Therefore, adaptive parameters are needed for each segmentation method. A score function derived from the change of bleb area and orientation between consecutive frames is proposed which provides adaptive parameters for bleb extraction in videos. In comparison to manual analysis, the proposed method provides an automated fast and accurate approach for bleb sequence extraction.