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Abstract #4345

A deep learning network for low-field MRI denoising using group sparsity information and a Noise2Noise method

Yuan Lian1, Xinyu Ye1, Hai Luo2, Ziyue Wu2, and Hua Guo1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Marvel Stone Healthcare Co., Ltd., Wuxi, China


Owing to hardware advancements, interest in low-field MRI system has increased recently. However, the imaging quality of low-field MRI is limited due to intrinsic low signal to noise ratio (SNR). Here we propose a deep-learning model to jointly denoise multi-contrast images using Noise2Noise training strategy. Our method can promote the SNRs of multi-contrast low-field images, and experiments show the effectiveness of the proposed strategy.

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