@inproceedings{3f0f912889fb4f07a7aa17e00b426410,
title = "Crohn's disease segmentation from MRI using learned image priors",
abstract = "We use a Field of Experts (FoE) model to segment abdominal regions from MRI affected with Crohns Disease (CD). FoE learns a prior model of diseased and normal bowel, and background non-bowel tissues from manually annotated training images. Unlike current approaches, FoE does not rely on hand designed features but learns the most discriminative features (in the form of filters) for different classes. FoE filter responses are integrated into a Random forest (RF) model that outputs probability maps for the test image and finally segments the diseased region. Experimental results show our method achieves significantly better performance than existing methods.",
keywords = "Crohns Disease, Fields of Experts, Graph cuts, Random Forests, Segmentation",
author = "Dwarikanath Mahapatra and Peter Schuffler and Frans Vos and Buhmann, {Joachim M.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 ; Conference date: 16-04-2015 Through 19-04-2015",
year = "2015",
month = jul,
day = "21",
doi = "10.1109/ISBI.2015.7163951",
language = "English",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "625--628",
booktitle = "2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015",
}