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Leveraging 3D Information in Unsupervised Brain MRI Segmentation
Learning is performed using a multicentric dataset of healthy brain MRIs, and segmentation performances are estimated on White-Matter Hyperintensities and tumors lesions.
Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust
Deep neural networks have become the gold-standard approach for the automated segmentation of 3D medical images.
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
The full acceptance of Deep Learning (DL) models in the clinical field is rather low with respect to the quantity of high-performing solutions reported in the literature.
Improving Uncertainty-based Out-of-Distribution Detection for Medical Image Segmentation
In this work, we evaluate various uncertainty frameworks to detect OOD inputs in the context of Multiple Sclerosis lesions segmentation.
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