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Found 2 papers, 2 papers with code
On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging
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 data, with the aim of preventing unreliable predictions.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI
Furthermore, we combine image translation with a masked conditional diffusion model, which attempts to `imagine' what tissue exists under a masked area, further exposing unknown patterns as the generative model fails to recreate them.
