Multi-Scale Wavelet Domain Residual Learning for Limited-Angle CT Reconstruction

Jawook Gu; Jong Chul Ye

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arXiv · 1703.01382

Multi-Scale Wavelet Domain Residual Learning for Limited-Angle CT Reconstruction

Jawook Gu·Jong Chul Ye

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Abstract

Limited-angle computed tomography (CT) is often used in clinical applications such as C-arm CT for interventional imaging. However, CT images from limited angles suffers from heavy artifacts due to incomplete projection data. Existing iterative methods require extensive calculations but can not deliver satisfactory results. Based on the observation that the artifacts from limited angles have some directional property and are globally distributed, we propose a novel multi-scale wavelet domain residual learning architecture, which compensates for the artifacts. Experiments have shown that the proposed method effectively eliminates artifacts, thereby preserving edge and global structures of the image.

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BibTeX RIS

Jawook Gu, Jong Chul Ye. 2017-03-04. Multi-Scale Wavelet Domain Residual Learning for Limited-Angle CT Reconstruction. https://arxiv.org/abs/1703.01382

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