Cell segmentation and tracking in phase contrast images using graph cut with asymmetric boundary costs

Abstract: We propose a new robust, effective, and surprisingly simple approach for the segmentation of cells in phase contrast microscopy images. The key feature of our algorithm is that it strongly favors dark-to-bright transitions at the boundaries of the (arbitrarily shaped) segmentation mask. The segmentation mask can be effectively found by a fast min-cut approach. The small but essential difference to standard min-cut based approaches is that our graph contains directed edges with asymmetric edge weights. Combined with a simple region propagation our approach yields better segmentation results on the ISBI Cell Tracking Challenge 2014 dataset than the top ranked methods. We provide an easy-to-use open-source implementation for ImageJ/Fiji and Matlab on our homepage.