PICSL Multi-Atlas Segmentation Tool This package contains source code for joint label fusion [1] and corrective learning [2], which were applied in MICCAI 2012 Grand Challenge on Multi-Atlas Labeling and finished in the first place. This software is provided for research purpose only under the GNU General Public License. Joint label fusion is for combining candidate segmentations produced by registering and warping multiple atlases for a target image. Corrective learning can be applied to further reduce systematic errors produced by joint label fusion (see [2] for detail). In general, corrective learning can be applied to correct systematic errors produced by other segmentation methods as well. If you use this software to produce results for a publication, please cite the following paper(s) accordingly. [1] H. Wang, J. W. Suh, S. Das, J. Pluta, C. Craige, P. Yushkevich, "Multi-atlas segmentation with joint label fusion," IEEE Trans. on Pattern Analysis and Machine Intelligence, 35(3), 611-623, 2013 [2] H. Wang, S. R. Das, J. W. Suh, M. Altinay, J. Pluta, C. Craige, B. B. Avants, and P. A. Yushkevich, "A Learning-Based Wrapper Method to Correct Systematic Errors in Automatic Image Segmentation: Consistently Improved Performance in Hippocampus, Cortex and Brain," Neuroimage, vol. 55, iss. 3, pp. 968-985, 2011. INSTRUCTIONS FOR COMPILING THE CODE A cmake file is provided to facilitate compiling the code. The user needs to set up configurations for compiling. To do so, go to the folder of the software package. Then type ccmake . to setup the enviroment. After this is done, type make to complie and build the executable files. Our program uses ITK's I/O functions to handle image input and output. Hence, it requries prebuilt ITK. The following three executable files will be built, jointfusion : joint label fusion bl : learning classifiers for correcting systematic errors sa : apply the learned classifiers to correct systematic segmentation errors on testing images Type each command to see details on how to use them. 09/04/2012 Hongzhi Wang wanghongzhi78@gmail.com
dzenanz/PICSL_MALF
Updated code from project https://www.nitrc.org/projects/picsl_malf/ Imported from: https://www.nitrc.org/frs/?group_id=634
C++