Investigative Magnetic Resonance Imaging

Korean Society of Magnetic Resonance in Medicine (대한자기공명의과학회)
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Artificial Intelligence in Neuroimaging: Clinical Applications

  • Choi, Kyu Sung (Department of Radiology, Seoul National University Hospital) ;
  • Sunwoo, Leonard (Department of Radiology, Seoul National University Bundang Hospital)
  • Received : 2021.08.03
  • Published : 2022.03.30
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Abstract

Artificial intelligence (AI) powered by deep learning (DL) has shown remarkable progress in image recognition tasks. Over the past decade, AI has proven its feasibility for applications in medical imaging. Various aspects of clinical practice in neuroimaging can be improved with the help of AI. For example, AI can aid in detecting brain metastases, predicting treatment response of brain tumors, generating a parametric map of dynamic contrast-enhanced MRI, and enhancing radiomics research by extracting salient features from input images. In addition, image quality can be improved via AI-based image reconstruction or motion artifact reduction. In this review, we summarize recent clinical applications of DL in various aspects of neuroimaging.

Keywords

Acknowledgement

This research was supported by the SNUBH Research Fund (No. 09-2019-006).

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