Article

Deep learning-based ultrasound transducer induced CT metal artifact reduction using generative adversarial networks for ultrasound-guided cardiac radioablation

2023-03-29

Abstract excerpt

<title>Abstract</title> In US-guided cardiac radioablation, a possible workflow includes simultaneous US and planning CT acquisitions, which can result in US transducer-induced metal artifacts on the planning CT scans. To reduce the impact of these artifacts, a metal artifact reduction (MAR) algorithm has been developed based on a deep learning Generative Adversarial Network (CycleGAN) called Cycle-MAR, and co...

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Literature Corpus work: be9da857-c3a9-55db-8c04-43a0533b6dbc
DOI: 10.21203/rs.3.rs-2713705/v1

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