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cs.CV2023
On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging
Harry Anthony, Konstantinos Kamnitsas
Implementing neural networks for clinical use in medical applications necessitates the ability for the network to detect when input data differs significantly from the training dat…
eess.IV2023
Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI
Ziyun Liang, Harry Anthony, Felix Wagner +1
Unsupervised anomaly segmentation aims to detect patterns that are distinct from any patterns processed during training, commonly called abnormal or out-of-distribution patterns, w…