Applying deformable templates for cell image segmentation

摘要

This paper presents an automatic method, based on the deformable template approach, for cell image segmentation under severe noise conditions. We define a new methodology, dividing the process into three parts: (1) obtain evidence from the image about the location of the cells; (2) use this evidence to calculate an elliptical approximation of these locations; (3) refine cell boundaries using locally deforming models. We have designed a new algorithm to locate cells and propose an energy function to be used together with a stochastic deformable template model. Experimental results show that this approach for segmenting cell images is both fast and robust, and that this methodology may be used for automatic classification as part of a computer-aided medical decision making technique.