Keywords: Segmentation, Brain, Uncertainty
Segmentation is crucial in analysing volumes of brain tissue compartments in studies of healthy development and pathological changes. Probabilistic segmentation is widely used, but the choice of threshold on probability maps has large effects on the resulting tissue volumes, and there is no consensus on optimal choice of such threshold. This work presents a way to minimise this effect by quantifying the uncertainty using Shannon entropy. Entropy map contains information about uncertainties in each individual voxel and this can be used to inform about uncertainty in MRI-based tissue segmentation.
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