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Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography Using Supervised Learning and a Novel Morphometric Feature Descriptor.

, , and . MICCAI (1), volume 9349 of Lecture Notes in Computer Science, page 621-628. Springer, (2015)

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Optimisation of orthopaedic implant design using statistical shape space analysis based on level sets., , , , , , and . Medical Image Anal., 14 (3): 265-275 (2010)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)Super-Resolution Classification Improves Facial Nerve Segmentation from CBCT Imaging., , , , , , and . CURAC, page 143-144. Der Andere Verlag, (2016)Deep Learning Versus Classical Regression for Brain Tumor Patient Survival Prediction., , , , , , and . BrainLes@MICCAI (2), volume 11384 of Lecture Notes in Computer Science, page 429-440. Springer, (2018)Minimization of Intra-Operative Shaping of Orthopaedic Fixation Plates: A Population-Based Design., , , and . MICCAI (2), volume 6892 of Lecture Notes in Computer Science, page 409-416. Springer, (2011)Do We Really Need that Skip-Connection? Understanding Its Interplay with Task Complexity., , , and . MICCAI (4), volume 14223 of Lecture Notes in Computer Science, page 302-311. Springer, (2023)Reliability of Quantification Estimates in MR Spectroscopy: CNNs vs Traditional Model Fitting., , , , and . MICCAI (8), volume 13438 of Lecture Notes in Computer Science, page 715-724. Springer, (2022)CRF-Based Brain Tumor Segmentation: Alleviating the Shrinking Bias., , , and . BrainLes@MICCAI, volume 10154 of Lecture Notes in Computer Science, page 100-107. (2016)Deep Learning-based Type Identification of Volumetric MRI Sequences., , , , , , and . ICPR, page 5674-5681. IEEE, (2020)Correction tool for Active Shape Model based lumbar muscle segmentation., , , , , , and . EMBC, page 3033-3036. IEEE, (2015)