April 3, 2024, 4:42 a.m. | Jiacheng Xie, Hua-Chieh Shao, Yunxiang Li, You Zhang

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.01448v1 Announce Type: cross
Abstract: Cone-beam computed tomography (CBCT) is widely used in image-guided radiotherapy. Reconstructing CBCTs from limited-angle acquisitions (LA-CBCT) is highly desired for improved imaging efficiency, dose reduction, and better mechanical clearance. LA-CBCT reconstruction, however, suffers from severe under-sampling artifacts, making it a highly ill-posed inverse problem. Diffusion models can generate data/images by reversing a data-noising process through learned data distributions; and can be incorporated as a denoiser/regularizer in LA-CBCT reconstruction. In this study, we developed a diffusion …

abstract acquisitions arxiv cs.lg diffusion diffusion model efficiency however image imaging making physics.med-ph prior sampling type

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