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Deep Learning for Magnetic Resonance Fingerprinting: A New Approach for Predicting Quantitative Parameter Values from Time Series.

, , , , , , and . GMDS, volume 243 of Studies in Health Technology and Informatics, page 202-206. IOS Press, (2017)

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Deriving Neural Network Architectures Using Precision Learning: Parallel-to-Fan Beam Conversion., , , , , and . GCPR, volume 11269 of Lecture Notes in Computer Science, page 503-517. Springer, (2018)Disassemblable Fieldwork CT Scanner Using a 3D-printed Calibration Phantom., , , , , and . CoRR, (2020)Estimating the Fundamental Matrix Without Point Correspondences With Application to Transmission Imaging., , , , and . ICCV, page 1072-1081. IEEE, (2019)Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images - A Cross-site Robustness Assessment., , , , , , , , and . BIOIMAGING, page 27-34. SciTePress, (2018)Towards Arbitrary Noise Augmentation - Deep Learning for Sampling from Arbitrary Probability Distributions., , , and . MLMIR@MICCAI, volume 11074 of Lecture Notes in Computer Science, page 129-137. Springer, (2018)Abstract: Some Investigations on Robustness of Deep Learning in Limited Angle Tomography., , , , , and . Bildverarbeitung für die Medizin, page 21. Springer Vieweg, (2019)Deep Learning Fundamentals., , , and . Bildverarbeitung für die Medizin, page 5. Springer Vieweg, (2018)Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images - A Cross-Site Robustness Assessment., , , , , , , , and . CoRR, (2017)Deep Learning Computed Tomography., , , and . MICCAI (3), volume 9902 of Lecture Notes in Computer Science, page 432-440. (2016)Transferability of Deep Learning Algorithms for Malignancy Detection in Confocal Laser Endomicroscopy Images from Different Anatomical Locations of the Upper Gastrointestinal Tract., , , , , , , , and . BIOSTEC (Selected Papers), volume 1024 of Communications in Computer and Information Science, page 67-85. Springer, (2018)