Abstract
In 3D cancer cell spheroids, particularly in vitro co-culture techniques there is an urgent need in vivid under standing of the interaction of cancer cells with the counter stromal cells. Fluorescence imaging and confocal microscopy techniques will aid in imaging the cells, and it is required an easiest and fast approach in identifying the interactions in multiple confocal planes. To achieve this, image segmentation techniques were employed. The image dataset under consideration can be differentiated based on pixel intensities (color). In the proposed technique firstly, the blurring effect is removed. Further the binarization of image is done using Ostu's global thresholding technique. Separation of colon cancer and fibroblast cells is obtained by applying color-based segmentation technique. After the separation of cells, a novel cell counting technique is applied to obtain the cell ratios. The results present the scattering pattern of cells from the core to the peripheral region. It intends to burgeon techniques for image enhancement, segmentation and cell counting which would render momentous help in automated analysis of colon cancer cells and provide pithy insights into the lesions occurring at cellular level.