Noise Mapping and Removal in Complex-Valued Multi-Channel MRI via Optimal Shrinkage of Singular Values
| Autor: | Wei-Tang Chang, Sang Hun Chung, Yong Chen, Yueh Z. Lee, Khoi Minh Huynh, Pew Thian Yap |
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| Rok vydání: | 2022 |
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| Zdroj: | Med Image Comput Comput Assist Interv Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030872304 MICCAI (6) |
| Popis: | In magnetic resonance imaging (MRI), noise is a limiting factor for higher spatial resolution and a major cause of prolonged scan time, owing to the need for repeated scans. Improving the signal-to-noise ratio is therefore key to faster and higher-resolution MRI. Here we propose a method for mapping and reducing noise in MRI by leveraging the inherent redundancy in complex-valued multi-channel MRI data. Our method leverages a provably optimal strategy for shrinking the singular values of a data matrix, allowing it to outperform state-of-the-art methods such as Marchenko-Pastur PCA in noise reduction. Our method reduces the noise floor in brain diffusion MRI by 5-fold and remarkably improves the contrast of spiral lung \(^{19}\)F MRI. Our framework is fast and does not require training and hyper-parameter tuning, therefore providing a convenient means for improving SNR in MRI. |
| Databáze: | OpenAIRE |
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