A semi-supervised, multi-sequence U-Net with late fusion and anatomical priors segments carotid vessel walls and plaques in MRI, with bottleneck fusion outperforming early fusion.
Enhancing medical image segmentation: Ground truth optimization through evaluating uncertainty in expert annotations.Mathematics, 11(17):3771, 2023
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Semi-supervised learning and integration of multi-sequence MR-images for carotid vessel wall and plaque segmentation
A semi-supervised, multi-sequence U-Net with late fusion and anatomical priors segments carotid vessel walls and plaques in MRI, with bottleneck fusion outperforming early fusion.