BRIC GNU General Public License (GPL) Yes University of North Carolina at Chapel Hill NITRC MARS (Multi-Atlas Robust Segmentation) Yes Minjeong Kim MARS (Multi-Atlas Robust Segmentation) provides the automatic solutions for efficent segmentation/labeling anatomcial structures from medical images. Specifically, this software has integrated several state-of-the-art multi-atlas based segmentation methods, such as majority voting, local weighted voting, and non-local patch based segmentation methods. More importantly, we also included our recently-developed joint sparse patch based segmentation method in this software. Compared with convention methods, our method has the following advantages: (1) add sparsity constraint to suppress the influence of misleading patches; (2) reduce the joint risk of two patches jointly making the same segmentation errors, and (3) use iterative framework to correct the possible mis-segmentations. This software package was developed in the IDEA group at UNC-Chapel Hill ( http://bric.unc.edu/ideagroup). Wu et. al., "A generative probability model of joint label fusion for multi-atlas based brain segmentation", MIA, 2013. 2014-5-15 MARS_V1.0 user's manual (corrected) 2014-5-15 MARS_V1.0 user's manual 2014-5-15 MARS_V1.0_MAC_OS_X_10.9 2014-5-15 MARS_V1.0_LINUX64 2014-5-15 MARS_V1.0_WIN64 2014-5-01 TestData 2014-5-01 MARS_V1.0 MARS (Multi-Atlas Robust Segmentation) CT, Alzheimer Disease, MR, Computational Neuroscience, GNU General Public License (GPL) http://www.nitrc.org/projects/mars/, http://www.nitrc.org/projects/mars/ mjkim@med.unc.edu