Keywords: Quantitative Imaging, Machine Learning/Artificial IntelligenceRapid quantitative magnetic resonance imaging (qMRI) is the trend of MR development and has essential diagnostic value. However, reducing acquisition time will come at the expense of image quality and will also affect the accuracy of quantitative values. Here we propose a method for reconstructing fast low-resolution qMRI images using deep learning, aiming to improve image quality while reducing bias in quantitative values. The research results show that after deep learning, the image quality is comparable to that of conventional high-resolution scanning images, and quantitative values are also more stable.
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