Self-supervised MRI denoising: leveraging Stein’s unbiased risk estimator and spatially resolved noise maps
Abstract Thermal noise caused by the imaged object is an intrinsic limitation in magnetic resonance imaging (MRI), resulting in an impaired clinical value of the acquisitions. Recently, deep learning (DL)-based denoising methods achieved promising results by extracting complex feature representation...
Main Authors: | , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-12-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-49023-2 |