CRF Based Brain Tumor Segmentation: Alleviating the Shrinking Bias
This paper extends a previously published brain tumor segmentation method with a dense Conditional Random Field (CRF) Dense CRFs can overcome the shrinking bias inherent to many grid structured CRFs. We focus on illustrating the impact of alleviating the shrinking bias on the performance of CRF based brain tumor segmentation. The proposed segmentation method is evaluated using data from the MICCAI BRATS 2013 2015 data sets (up to 110 patient cases for testing) and compared to a baseline method using a grid structured CRF. Improved segmentation performance for the complete and enhancing tumor was observed with respect to grid structured CRFs.
BrainLes@MICCAI