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Automatic Artifact Detection Algorithm in Fetal MRI
2022
Frontiers in Artificial Intelligence
Fetal MR imaging is subject to artifacts including motion, chemical shift, and radiofrequency artifacts. Currently, such artifacts are detected by the MRI operator, a process which is subjective, time consuming, and prone to errors. We propose a novel algorithm, RISE-Net, that can consistently, automatically, and objectively detect artifacts in 3D fetal MRI. It makes use of a CNN ensemble approach where the first CNN aims to identify and classify any artifacts in the image, and the second CNN
doi:10.3389/frai.2022.861791
pmid:35783351
pmcid:PMC9244144
fatcat:y5ywqqhxaraitgiblt2qvmayf4