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Uncertainty quantification in brain tumor segmentation using CRFs and random perturbation models.

, , , , , , and . ISBI, page 428-431. IEEE, (2016)

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Personalized Radiotherapy Planning for Glioma Using Multimodal Bayesian Model Calibration., , , , , , , , , and 4 other author(s). CoRR, (2018)Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge., , , , , , , , , and 41 other author(s). CoRR, (2018)Uncertainty quantification in brain tumor segmentation using CRFs and random perturbation models., , , , , , and . ISBI, page 428-431. IEEE, (2016)Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian Inference., , , , , , , , , and 4 other author(s). IEEE Trans. Medical Imaging, 38 (8): 1875-1884 (2019)Multi-modal Multi-temporal Brain Tumor Segmentation, Growth Analysis and Texture-based Classification (Multispektrale, multitemporale Bildanalyse zur Segmentierung, Wachstumsanalyse und Klassifizierung von Gerhirntumoren). Technical University of Munich, Germany, (2019)Multi-modal Image Classification Using Low-Dimensional Texture Features for Genomic Brain Tumor Recognition., , , , , , , and . GRAIL/MFCA/MICGen@MICCAI, volume 10551 of Lecture Notes in Computer Science, page 201-209. Springer, (2017)From Large to Small Organ Segmentation in CT Using Regional Context., , , and . MLMI@MICCAI, volume 10541 of Lecture Notes in Computer Science, page 1-9. Springer, (2017)