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Spectroscopy imaging in intraoperative MR suite: tissue characterization and optimization of tumor resection.

, , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 9 (4): 551-559 (2014)

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Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss., , , , , , , , , and 1 other author(s). MICCAI (2), volume 11765 of Lecture Notes in Computer Science, page 264-272. Springer, (2019)Scribble-Based Domain Adaptation via Co-segmentation., , , , , , , , , and . MICCAI (1), volume 12261 of Lecture Notes in Computer Science, page 479-489. Springer, (2020)Optimization of Perfusion CT Protocol for Imaging of Extracranial Head and Neck Tumors., , , , and . J. Digital Imaging, 22 (5): 437-448 (2009)Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI., , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 15 (9): 1445-1455 (2020)TISS-net: Brain tumor image synthesis and segmentation using cascaded dual-task networks and error-prediction consistency., , , , , , , , , and 4 other author(s). Neurocomputing, (August 2023)Spectroscopy imaging in intraoperative MR suite: tissue characterization and optimization of tumor resection., , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 9 (4): 551-559 (2014)Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss., , , , , , , , , and . CoRR, (2019)Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status., , , , , , , , , and 19 other author(s). BMC Medical Informatics Decis. Mak., 20 (1): 149 (2020)Towards Safe Deep Learning: Accurately Quantifying Biomarker Uncertainty in Neural Network Predictions., , , , and . MICCAI (1), volume 11070 of Lecture Notes in Computer Science, page 691-699. Springer, (2018)