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Fully Automated and Standardized Segmentation of Adipose Tissue Compartments by Deep Learning in Three-dimensional Whole-body MRI of Epidemiological Cohort Studies.

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Fully Automated and Standardized Segmentation of Adipose Tissue Compartments by Deep Learning in Three-dimensional Whole-body MRI of Epidemiological Cohort Studies., , , , , , , , , and 2 other author(s). CoRR, (2020)Assessment of rodent brain activity using combined 15OH2O-PET and BOLD-fMRI., , , , and . NeuroImage, (2014)Monte-Carlo Analysis for Quality Estimation of Gradient Correction Algorithms in Simultaneous Surface EMG-MRI Measurements using Signal Synthesis and Class Probability., , , and . EMBC, page 690-693. IEEE, (2019)Graphical User Interface for Medical Deep Learning - Application to Magnetic Resonance Imaging., , , , , , , , , and 3 other author(s). APSIPA, page 838-847. IEEE, (2018)Magnetic Field Distribution and Signal Decay in Functional MRI in Very High Fields (up to 9.4 T) Using Monte Carlo Diffusion Modeling., , , and . Int. J. Biomed. Imaging, (2007)A fully automated trabecular bone structural analysis tool based on T2*-weighted magnetic resonance imaging., , , , , , , and . Comput. Medical Imaging Graph., 36 (2): 85-94 (2012)Classification-guided Neural Network-based Correction of Magnetic Resonance-related Gradient Artifact Residuals in Simultaneously Recorded Surface Electromyography., , and . EMBC, page 3632-3635. IEEE, (2022)Identification of radiomic biomarkers in a set of four skeletal muscle groups on Dixon MRI of the NAKO MR study., , , , , , , , , and 7 other author(s). BMC Medical Imaging, 23 (1): 104 (December 2023)Semantic Organ Segmentation in 3D Whole-Body MR Images., , , , , , , , and . ICIP, page 3498-3502. IEEE, (2018)