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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 . CoRR, (2020)

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ipA-MedGAN: Inpainting of Arbitrarily Regions in Medical Modalities., , , , , and . CoRR, (2019)Organ-based Age Estimation based on 3D MRI Scans., , , , , , and . CoRR, (2019)Age-Net: An MRI-Based Iterative Framework for Biological Age Estimation., , , , , , , , and . CoRR, (2020)Erweiterung inferenzstatistischer Fähigkeiten modellbasierter Gradient-Boosting Algorithmen (Extending the inferential capabilities of model-based gradient boosting algorithms). University of Erlangen-Nuremberg, Germany, (2019)base-search.net (ftuniverlangen:oai:ub.uni-erlangen.de-opus:11786).Overcoming barriers to data sharing with medical image generation: a comprehensive evaluation., , , , , , and . npj Digit. Medicine, (2021)ipA-MedGAN: Inpainting of Arbitrary Regions in Medical Imaging., , , , , and . ICIP, page 3005-3009. IEEE, (2020)MedGAN: Medical image translation using GANs., , , , , , , and . Comput. Medical Imaging Graph., (2020)Mixture density networks for the indirect estimation of reference intervals., , , , and . BMC Bioinform., 23 (1): 307 (2022)Adaptive step-length selection in gradient boosting for Gaussian location and scale models., , , and . Comput. Stat., 37 (5): 2295-2332 (2022)ImFEATbox: a toolbox for extraction and analysis of medical image features., , , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 13 (12): 1881-1893 (2018)