Constrained watershed method to infer morphology of mammalian cells in microscopic images.

Precise information about the size, shape, temporal dynamics, and spatial distribution of cells is beneficial for the understanding of cell behavior and may play a key role in drug development, regenerative medicine, and disease research. The traditional method of manual observation and measurement of cells from microscopic images is tedious, expensive, and time consuming. Thus, automated methods are in high demand, especially given the increasing quantity of cell data being collected. In this article, an automated method to measure cell morphology from microscopic images is proposed to outline the boundaries of individual hematopoietic stem cells (HSCs). The proposed method outlines the cell regions using a constrained watershed method which is derived as an inverse problem. The experimental results generated by applying the proposed method to different HSC image sequences showed robust performance to detect and segment individual and dividing cells. The performance of the proposed method for individual cell segmentation for single frame high-resolution images was more than 97%, and decreased slightly to 90% for low-resolution multiframe stitched images.