Iterative thresholding for segmentation of cells from noisy images

Abstract

We introduce an iterative thresholding algorithm for the segmentation of cells from noisy cell images. The thresholding image, which is initially a constant, changes iteratively with both the previous segmentation and image local activity. Experimental results for both synthesized and real cell images are provided to demonstrate the performance of the algorithm.