Algorithm Selection for Intracellular Image Segmentation Based on Region Similarity

This paper deals with the problem of intracellular image segmentation. Our goal is to propose an algorithm selection framework that has the potential to be general enough to be used for a variety of intracellular image segmentation tasks. With this framework, an optimal algorithm suited to each segmentation task can be selected automatically by our proposed evaluation criteria derived from region similarity of image features and boundary shape. Furthermore, using our framework, we can rank different algorithms, as well as define each algorithm's parameters. We tested our prototype framework on confocal microscope images and showed that application of these criteria gave highly accurate segmentation results without missing any biologically important image characteristics.