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3 January 2025 A transformer-based framework for non-Cartesian MRI reconstruction
Wuzheng Ji, Ze Zhang, Huiyuan Tan, Wenhui Yang, Hui Wang, Xin Liu, Qiuliang Wang
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Proceedings Volume 13442, Fifth International Conference on Signal Processing and Computer Science (SPCS 2024); 134421F (2025) https://doi.org/10.1117/12.3052951
Event: Fifth International Conference on Signal Processing and Computer Science (SPCS 2024), 2024, Kaifeng, China
Abstract
Non-Cartesian reconstruction is a crucial technique for accelerating MRI. However, traditional non-Cartesian reconstruction algorithms often result in suboptimal image quality. Recently, deep neural networks have emerged as powerful tools for MRI reconstruction, yet their application to non-Cartesian acquisitions remains underexplored. Transformer-based approaches have shown impressive performance in image super-resolution, prompting us to explore their potential in this domain. To tackle these challenges, this paper introduces a novel framework that combines non-Cartesian image reconstruction techniques with a Transformer-based network. The proposed framework comprises non-uniform Fourier transform, image feature extraction, and image reconstruction modules. To assess the effectiveness of our approach, we performed experiments using the single-coil knee dataset from fastMRI. Compared to other methods, our proposed approach demonstrated a 2.024 dB improvement in PSNR and a 0.117 increase in SSIM under a 4x accelerated radial undersampling condition.
(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Wuzheng Ji, Ze Zhang, Huiyuan Tan, Wenhui Yang, Hui Wang, Xin Liu, and Qiuliang Wang "A transformer-based framework for non-Cartesian MRI reconstruction", Proc. SPIE 13442, Fifth International Conference on Signal Processing and Computer Science (SPCS 2024), 134421F (3 January 2025); https://doi.org/10.1117/12.3052951
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KEYWORDS
Image restoration
Magnetic resonance imaging
Image processing
Medical image reconstruction
Neural networks
Feature extraction
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