Textural feature based cell segmentation method for isolating Chinese hamster ovary cells

Abstract

Analysis of cellular behavior is signif icant for studying cell cycle and detecting anti cancer drugs.Isolating individual cells in confocal microscopic images of non stained live cell cultures is very difficult process. Because these images do not have adequate textural variations and the cell s are often overlap in consecutive focal planes. Manual cell segmentation requires massive labor and it is a time consuming process. This paper describes a automated cell segmentation method for localizing the individual cells of Chinese hamster ovary cell culture. K means clustering method is used to extract the cellular regions from the background. Subsequently, level set method is used to determine the boundaries of individual cells. The result indicates the significance of the proposed method as it appr oximates the boundaries of cells, which are placed very close r or overlapped in each other.