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cs.CV2024
Self-Supervised Radiograph Anatomical Region Classification -- How Clean Is Your Real-World Data?
Simon Langer, Jessica Ritter, Rickmer Braren +2
Modern deep learning-based clinical imaging workflows rely on accurate labels of the examined anatomical region. Knowing the anatomical region is required to select applicable down…
cs.CV2022
SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for prior-informed assessment of muscle function and pathology
Alexander Mühlberg, Paul Ritter, Simon Langer +11
Deep learning (DL) shows notable success in biomedical studies. However, most DL algorithms work as a black box, exclude biomedical experts, and need extensive data. We introduce t…
cs.CV2022
DeepTechnome: Mitigating Unknown Bias in Deep Learning Based Assessment of CT Images
Simon Langer, Oliver Taubmann, Felix Denzinger +2
Reliably detecting diseases using relevant biological information is crucial for real-world applicability of deep learning techniques in medical imaging. We debias deep learning mo…