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Self-supervision for medical image classification: state-of-the-art performance with ~100 labeled training samples per class., , , и . CoRR, (2023)3d-SMRnet: Achieving a new quality of MPI system matrix recovery by deep learning., , , , , и . CoRR, (2019)Skin Lesion Classification Using CNNs With Patch-Based Attention and Diagnosis-Guided Loss Weighting., , , , , , , и . IEEE Trans. Biomed. Eng., 67 (2): 495-503 (2020)Multi-scale fully convolutional neural networks for histopathology image segmentation: From nuclear aberrations to the global tissue architecture., , , , , , и . Medical Image Anal., (2021)Reservoir Computing for Jurkat T-cell Segmentation in High Resolution Live Cell Ca2+ Fluorescence Microscopy., , , и . ISBI, стр. 1587-1591. IEEE, (2020)Extending Tempcyclegan for Virtual Augmentation of Gastrointestinal Endoscopy Training Simulators., , , , , и . Bildverarbeitung für die Medizin, стр. 3-8. Springer, (2023)Abstract: Reduktion der Kalibrierungszeit für die Magnetpartikelbildgebung mittels Deep Learning., , , , , и . Bildverarbeitung für die Medizin, стр. 337. Springer, (2021)Time Matters: Handling Spatio-Temporal Perfusion Information for Automated TICI Scoring., , , , , и . MICCAI (6), том 12266 из Lecture Notes in Computer Science, стр. 86-96. Springer, (2020)Widening the Focus: Biomedical Image Segmentation Challenges and the Underestimated Role of Patch Sampling and Inference Strategies., , , и . MICCAI (4), том 12264 из Lecture Notes in Computer Science, стр. 289-298. Springer, (2020)3d-SMRnet: Achieving a New Quality of MPI System Matrix Recovery by Deep Learning., , , , , и . MICCAI (2), том 12262 из Lecture Notes in Computer Science, стр. 74-82. Springer, (2020)