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A Supervised Learning Based Approach to Detect Crohn's Disease in Abdominal MR Volumes.

, , , , and . Abdominal Imaging, volume 7601 of Lecture Notes in Computer Science, page 97-106. Springer, (2012)

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Automatic Detection and Segmentation of Crohn's Disease Tissues From Abdominal MRI., , , , , , , and . IEEE Trans. Med. Imaging, 32 (12): 2332-2347 (2013)Semi-Supervised and Active Learning for Automatic Segmentation of Crohn's Disease., , , , and . MICCAI (2), volume 8150 of Lecture Notes in Computer Science, page 214-221. Springer, (2013)Combining Multiple Expert Annotations Using Semi-supervised Learning and Graph Cuts for Crohn's Disease Segmentation., , , , , , , , , and 1 other author(s). ABDI@MICCAI, volume 8676 of Lecture Notes in Computer Science, page 139-147. Springer, (2014)Crohn's disease tissue segmentation from abdominal MRI using semantic information and graph cuts., , , , and . ISBI, page 358-361. (2013)Expiration-Phase Template-Based Motion Correction of Free-Breathing Abdominal Dynamic Contrast Enhanced MRI., , , , , , , , and . IEEE Trans. Biomed. Engineering, 62 (4): 1215-1225 (2015)A Supervised Learning Based Approach to Detect Crohn's Disease in Abdominal MR Volumes., , , , and . Abdominal Imaging, volume 7601 of Lecture Notes in Computer Science, page 97-106. Springer, (2012)Computational modeling for assessment of IBD: To be or not to be?, , , , , , , , , and 2 other author(s). EMBC, page 3974-3977. IEEE, (2012)Active learning based segmentation of Crohn's disease using principles of visual saliency., , , , , , , and . ISBI, page 226-229. IEEE, (2014)Image Registration Based on Autocorrelation of Local Structure., , , , , and . IEEE Trans. Med. Imaging, 35 (1): 63-75 (2016)A Model Development Pipeline for Crohn's Disease Severity Assessment from Magnetic Resonance Images., , , , , , , , , and . Abdominal Imaging, volume 8198 of Lecture Notes in Computer Science, page 1-10. Springer, (2013)