An Effective Mitosis Recognition and Segmentation Tool for Stem Cell Exploration

Stem cells, on regenerative medicine, has enormous potential and impact, lead to the rapidly growing interest for tools to analyze and characterize the behaviors of these cells invitro in an automated and high throughput fashion. Measurement of the proliferative behaviors of cells invitro is important to many biomedical applications for the measurement of the accurate counting and localization of occurrences of mitosis, or cell division, in a cell culture. In this paper, the performance analysis of clustering for segmenting the mitosis detection is proposed. It is possible to manually identify incidents of mitosis because mitotic cells in culture tend to exhibit intensified surrounding halos under phase contrast illumination. This halo artifact is eliminated by using Diffusion corona filter. Using this method of segmentation precision of 97.1% is obtained which is 1.3% higher when compared with the semi Markov process of segmentation.