An efficient threshold based pulse coupled neural network model for stem cell image segmentation

This paper describes the behavior of regenerative nature of HSc on the basis of culturing conditions. This fast and robust approach has proposed scheme for segmentation process to improve the detection of stem cells. PCNN also yields consistent accurate edge detection by using edge detector. Time lapse experiments on images are complex hence interactive cell segmentation is proposed for efficient analysis of the growth rate on every sample. Based on the parameters set the neurons are synchronized to form the neural network in iterative manner. PCNN also improves the linking co-efficient β by taking the relationship of gray value in each neurons. PCNN technique is implemented to segment the cell boundaries by representing each pixel as neurons to form a neural network based on thresholding. This method performs powerful segmentation based on their intensity and threshold.