Translator Disclaimer
21 March 2016 Automatic brain tumor segmentation with a fast Mumford-Shah algorithm
Author Affiliations +
We propose a fully-automatic method for brain tumor segmentation that does not require any training phase. Our approach is based on a sequence of segmentations using the Mumford-Shah cartoon model with varying parameters. In order to come up with a very fast implementation, we extend the recent primal-dual algorithm of Strekalovskiy et al. (2014) from the 2D to the medically relevant 3D setting. Moreover, we suggest a new confidence refinement and show that it can increase the precision of our segmentations substantially. Our method is evaluated on 188 data sets with high-grade gliomas and 25 with low-grade gliomas from the BraTS14 database. Within a computation time of only three minutes, we achieve Dice scores that are comparable to state-of-the-art methods.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sabine Müller, Joachim Weickert, and Norbert Graf "Automatic brain tumor segmentation with a fast Mumford-Shah algorithm", Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97842S (21 March 2016);

Back to Top