SCRED-Distillation: Improving Low-Dose CT Image Quality via Feature Fusion and Mutual Learning
The substantial noise inherent in low-dose CT (LDCT) significantly impedes diagnostic accuracy. Although deep learning techniques, particularly CNNs, have offered promise for LDCT denoising, their inherent focus on local features and the scarcity of extensive training data can limit their performanc...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11062456/ |
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