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Decoupling Axial and Radial Tissue Heterogeneity in Diffusion Compartment Imaging.

, , , , , , and . IPMI, volume 10265 of Lecture Notes in Computer Science, page 440-452. Springer, (2017)

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A Fully Bayesian Inference Framework for Population Studies of the Brain Microstructure., , , , and . MICCAI (1), volume 8673 of Lecture Notes in Computer Science, page 25-32. Springer, (2014)Accelerated High Spatial Resolution Diffusion-Weighted Imaging., , , , , and . IPMI, volume 9123 of Lecture Notes in Computer Science, page 69-81. Springer, (2015)Exclusive Independent Probability Estimation using Deep 3D Fully Convolutional DenseNets: Application to IsoIntense Infant Brain MRI Segmentation., , , and . MIDL, volume 102 of Proceedings of Machine Learning Research, page 260-272. PMLR, (2019)Decoupling Axial and Radial Tissue Heterogeneity in Diffusion Compartment Imaging., , , , , , and . IPMI, volume 10265 of Lecture Notes in Computer Science, page 440-452. Springer, (2017)The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)., , , , , , , , , and 66 other author(s). CoRR, (2024)Interpolating multi-fiber models by Gaussian mixture simplification., , , , , and . ISBI, page 928-931. IEEE, (2012)Characterizing the DIstribution of Anisotropic MicrO-structural eNvironments with Diffusion-Weighted Imaging (DIAMOND)., , , , , , and . MICCAI (3), volume 8151 of Lecture Notes in Computer Science, page 518-526. Springer, (2013)BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023., , , , , , , , , and 70 other author(s). CoRR, (2024)Maximum A Posteriori Estimation of Isotropic High-Resolution Volumetric MRI from Orthogonal Thick-Slice Scans., , , , and . MICCAI (2), volume 6362 of Lecture Notes in Computer Science, page 109-116. Springer, (2010)Learning to Detect Brain Lesions from Noisy Annotations., , , , , , , , , and . ISBI, page 1910-1914. IEEE, (2020)