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Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI.

, , , , , , , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109501E. SPIE, (2019)

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Content-based image retrieval utilizing explicit shape descriptors: applications to breast MRI and prostate histopathology., and . Medical Imaging: Image Processing, volume 7962 of SPIE Proceedings, page 79621I. SPIE, (2011)Fully automated prostate magnetic resonance imaging and transrectal ultrasound fusion via a probabilistic registration metric., , , , and . Medical Imaging: Image-Guided Procedures, volume 8671 of SPIE Proceedings, page 86710A. SPIE, (2013)Gleason grading of prostate histology utilizing manifold regularization via statistical shape model of manifolds., and . Medical Imaging: Computer-Aided Diagnosis, volume 8315 of SPIE Proceedings, page 83151J. SPIE, (2012)Spatially aware expectation maximization (SpAEM): application to prostate TRUS segmentation., , , , , and . Medical Imaging: Image Processing, volume 9034 of SPIE Proceedings, page 90343Y. SPIE, (2014)Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS., , and . Medical Image Anal., 17 (2): 219-235 (2013)A high-throughput active contour scheme for segmentation of histopathological imagery., , , and . Medical Image Anal., 15 (6): 851-862 (2011)Aggregated Distance Metric Learning (ADM) for Image Classification in Presence of Limited Training Data., and . MICCAI (3), volume 6893 of Lecture Notes in Computer Science, page 33-40. Springer, (2011)Adaptive Energy Selective Active Contour with Shape Priors for Nuclear Segmentation and Gleason Grading of Prostate Cancer., , , , and . MICCAI (1), volume 6891 of Lecture Notes in Computer Science, page 661-669. Springer, (2011)A Boosting Cascade for Automated Detection of Prostate Cancer from Digitized Histology., , , and . MICCAI (2), volume 4191 of Lecture Notes in Computer Science, page 504-511. Springer, (2006)Consensus-Locally Linear Embedding (C-LLE): Application to Prostate Cancer Detection on Magnetic Resonance Spectroscopy., , and . MICCAI (2), volume 5242 of Lecture Notes in Computer Science, page 330-338. Springer, (2008)