Pushing the limits of low-cost ultra-low-field MRI by dual-acquisition deep learning 3D superresolution

Recent development of ultra-low-field (ULF) MRI presents opportunities for low-power, shielding-free, and portable clinical applications at a fraction of the cost. However, its performance remains limited by poor image quality. Here, a computational approach is formulated to advance ULF MR brain ima...

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Veröffentlicht in:	Magnetic resonance in medicine 2023-08, Vol.90 (2), p.400-416
Hauptverfasser:	Lau, Vick, Xiao, Linfang, Zhao, Yujiao, Su, Shi, Ding, Ye, Man, Christopher, Wang, Xunda, Tsang, Anderson, Cao, Peng, Lau, Gary K K, Leung, Gilberto K K, Leong, Alex T L, Wu, Ed X
Format:	Artikel
Sprache:	eng
Schlagworte:	Brain Brain - diagnostic imaging Computational neuroscience Deep Learning Feature extraction Humans Image enhancement Image quality Image reconstruction Imaging, Three-Dimensional - methods Income Magnetic resonance imaging Magnetic Resonance Imaging - methods Medical imaging Neuroimaging Neuroimaging - methods Reproducibility of Results Spatial discrimination Spatial resolution Three dimensional models
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