3D Few-view CT Image Reconstruction with Deep Learning
Huidong Xie, Hongming Shan, Ge Wang
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Few-view CT image reconstruction is an important approach to reduce the ionizing radiation dose associated with X-ray computed tomography (CT). In this paper, we propose a 3D deep-learning-based method for few-view CT image reconstruction from 3D projection data. The proposed method is validated and tested on a publicly available abdominal CT dataset.