CT artifact correction for sparse and truncated projection data using generative adversarial networks.
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DOI: 10.1002/mp.14504
Abstract: PURPOSE CT-image reconstruction using truncated or sparsely acquired projection data to reduce radiation dose, iodine volume, and patient motion artifacts has been widely investigated. To continue these efforts, we investigated the use of machine-learning based… read more here.
Keywords: reconstruction; correction; projection data; sparse truncated ... See more keywords