A model-based hematopoietic stem cell tracker

A better understanding of cell behavior is very important in drug and disease research. Cell size, shape, and motility may play a key role in stem-cell specialization or cancer development. However the traditional method of inferring these values manually is such an onerous task that automated methods of cell tracking and segmentation are in high demand. Image cytometry is a practical approach to measure and extract cell properties from large volumes of microscopic cell images. As an important application of image cytometry, this paper presents a probabilistic model based cell tracking method to locate and associate HSCs in phase contrast microscopic images. The proposed cell tracker has been successfully applied to track HSCs based on the most probable identified cell locations and probabilistic data association.