Our objective of this study is to accurately segment and classify carotid atherosclerotic plaque components in a completely automated manner, based on multi-weighted MRI. Specifically, we segmented each pixel using a two-module neural network model. Furthermore, we generated segmentation uncertainty maps with a Bayesian method to evaluate the inherent uncertainty of this segmentation task.
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