Applications of Nuclear Magnetic Resonance Imaging

Dear Colleagues,

Nuclear magnetic resonance imaging, commonly called magnetic resonance imaging (MRI), has developed into an indispensable imaging device for medical diagnosis and various research fields since it was introduced in the 1970s. This is due to advances in MRI hardware (e.g., magnet, coils, computer) and software (e.g., pulse sequence, data processing) along with MRI’s unique advantage of providing desired cross-sectional and three-dimensional images with excellent soft-tissue contrast without physical incision or radiation exposure.

MR spectroscopy (MRS; a.k.a. in vivo NMR) has also been benefiting from the advances in MRI hardware for the more accurate and rapid non-invasive extraction of biochemical information from various organs. By combining MRS with the spatial encoding technique in MRI, MR spectroscopic imaging (MRSI; a.k.a. chemical shift imaging (CSI)) provides a unique means of non-invasively mapping multiple metabolites simultaneously over the entire section or volume of a living organ. Given its recent remarkable accomplishments in a variety of different tasks, deep learning has also been applied in MRI and demonstrated its potential in the advancement of MRI techniques, including but not limited to undersampled MRI reconstruction, contrast synthesis, segmentation, diagnosis, and automated scan preparation.  

This Special Issue focuses on the latest developments and applications of nuclear magnetic resonance imaging. We invite researchers to contribute original research or review articles to this Special Issue.

Prof. Dr. Sangdoo Ahn

Prof. Dr. Hyeonjin Kim
Guest Editors

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• nuclear magnetic resonance imaging
• magnetic resonance imaging (MRI)
• MRI hardware
• MRI pulse sequences
• MRI acquisition techniques
• MRI data processing techniques
• MRI applications
• MR spectroscopy techniques
• MR spectroscopy applications
• functional MRI
• artificial intelligence in MRI and MR spectroscopy
• deep-learning-based MRI and MR spectroscopy