TD-Net: A Tri-domain network for sparse-view CT reconstruction

• URL: http://arxiv.org/abs/2311.15369v1
• Date: Sun, 26 Nov 2023 17:48:53 GMT
• Title: TD-Net: A Tri-domain network for sparse-view CT reconstruction
• Authors: Xinyuan Wang and Changqing Su and Bo Xiong
• Abstract summary: TD-Net is a pioneering tri-domain approach that unifies sinogram, image, and frequency domain optimizations. It adeptly preserves intricate details, overcoming the prevalent over-smoothing issue. The enhanced capabilities of TD-Net in varied noise scenarios highlight its potential as a breakthrough in medical imaging.
• Score: 16.40734977207315
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Sparse-view CT reconstruction, aimed at reducing X-ray radiation risks, frequently suffers from image quality degradation, manifested as noise and artifacts. Existing post-processing and dual-domain techniques, although effective in radiation reduction, often lead to over-smoothed results, compromising diagnostic clarity. Addressing this, we introduce TD-Net, a pioneering tri-domain approach that unifies sinogram, image, and frequency domain optimizations. By incorporating Frequency Supervision Module(FSM), TD-Net adeptly preserves intricate details, overcoming the prevalent over-smoothing issue. Extensive evaluations demonstrate TD-Net's superior performance in reconstructing high-quality CT images from sparse views, efficiently balancing radiation safety and image fidelity. The enhanced capabilities of TD-Net in varied noise scenarios highlight its potential as a breakthrough in medical imaging.

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