Segmentation of Neuronal-Cell Images from Stained Fields and Monomodal Histograms

Information from images taken of cells being grown in culture with oxidative agents allows life science researchers to compare changes in neurons from the Zellweger mice to those from normal mice. Image segmentation is the major and first step for the study of these different types of processes in cells. In this paper we develop an innovative strategy for the segmentation of neuronal-cell images which are subjected to stains and whose histograms are monomodal. Such nontrival images make it a challenging task for many existing image segmentation methods. We show that the proposed method is an effective and simple procedure for the subsequent quantitative analysis of neuronal images