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Nanchang University
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ClinReadNet achieves unprecedented accuracy in low-dose abdominal CT image quality assessment by mirroring the nuanced reading strategies of radiologists.
FSS-Net achieves an impressive 96.46% Dice score for carotid artery segmentation, showcasing remarkable robustness against noise and low contrast.
Achieve state-of-the-art brain tumor segmentation even with missing MRI data by explicitly disentangling anatomical features from modality-specific biases using causality.
