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Coil2Coil: Self-supervised MR image denoising using phased-array coil images. (arXiv:2208.07552v1 [eess.IV])
Aug. 17, 2022, 1:10 a.m. | Juhyung Park, Dongwon Park, Hyeong-Geol Shin, Eun-Jung Choi, Hongjun An, Minjun Kim, Dongmyung Shin, Se Young Chun, Jongho Lee
cs.LG updates on arXiv.org arxiv.org
Denoising of magnetic resonance images is beneficial in improving the quality
of low signal-to-noise ratio images. Recently, denoising using deep neural
networks has demonstrated promising results. Most of these networks, however,
utilize supervised learning, which requires large training images of
noise-corrupted and clean image pairs. Obtaining training images, particularly
clean images, is expensive and time-consuming. Hence, methods such as
Noise2Noise (N2N) that require only pairs of noise-corrupted images have been
developed to reduce the burden of obtaining training datasets. In …
More from arxiv.org / cs.LG updates on arXiv.org
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