Noise-resilient approach for deep tomographic imaging

2022/11/22 by Zhen Guo, Zhiguang Liu, Guo, Zhen +7
Engineering · Medicine · Physics and Astronomy · #Advanced X-ray Imaging Techniques #Advanced X-ray and CT Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Medical Imaging Techniques and Applications #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2211.15456

openalex publication_date 2022/11/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We propose a noise-resilient deep reconstruction algorithm for X-ray tomography. Our approach shows strong noise resilience without obtaining noisy training examples. The advantages of our framework may further enable low-photon tomographic imaging.

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