A generic approach for cell segmentation based on Gabor filtering and area-constrained ultimate erosion.

Abstract

Nowadays, the demand for segmenting different types of cells imaged by microscopes is increased tremendously. The requirements for the segmentation accuracy are becoming stricter. Because of the great diversity of cells, no traditional methods could segment various types of cells with adequate accuracy. In this paper, we aim to propose a generic approach that is capable of segmenting various types of cells robustly and counting the total number of cells accurately. To this end, we utilize the gradients of cells instead of intensity for cell segmentation because the gradients are less affected by the global intensity variations. To improve the segmentation accuracy, we utilize the Gabor filter to increase the intensity uniformity of the gradient image. To get the optimal segmentation, we utilize the slope difference distribution based threshold selection method to segment the Gabor filtered gradient image. At last, we propose an area-constrained ultimate erosion method to separate the connected cells robustly. Twelve types of cells are used to test the proposed approach in this paper. Experimental results showed that the proposed approach is very promising in meeting the strict accuracy requirements for many applications.