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Artificial intelligence in multiparametric magnetic resonance imaging: A review.

Publication ,  Journal Article
Li, C; Li, W; Liu, C; Zheng, H; Cai, J; Wang, S
Published in: Med Phys
October 2022

Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the clinical workflow for the diagnosis and treatment planning of various diseases. Machine learning-based artificial intelligence (AI) methods, especially those adopting the deep learning technique, have been extensively employed to perform mpMRI image classification, segmentation, registration, detection, reconstruction, and super-resolution. The current availabilities of increasing computational power and fast-improving AI algorithms have empowered numerous computer-based systems for applying mpMRI to disease diagnosis, imaging-guided radiotherapy, patient risk and overall survival time prediction, and the development of advanced quantitative imaging technology for magnetic resonance fingerprinting. However, the wide application of these developed systems in the clinic is still limited by a number of factors, including robustness, reliability, and interpretability. This survey aims to provide an overview for new researchers in the field as well as radiologists with the hope that they can understand the general concepts, main application scenarios, and remaining challenges of AI in mpMRI.

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Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

October 2022

Volume

49

Issue

10

Start / End Page

e1024 / e1054

Location

United States

Related Subject Headings

  • Reproducibility of Results
  • Nuclear Medicine & Medical Imaging
  • Magnetic Resonance Spectroscopy
  • Magnetic Resonance Imaging
  • Machine Learning
  • Humans
  • Artificial Intelligence
  • 5105 Medical and biological physics
  • 4003 Biomedical engineering
  • 1112 Oncology and Carcinogenesis
 

Citation

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MLA
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Li, C., Li, W., Liu, C., Zheng, H., Cai, J., & Wang, S. (2022). Artificial intelligence in multiparametric magnetic resonance imaging: A review. Med Phys, 49(10), e1024–e1054. https://doi.org/10.1002/mp.15936
Li, Cheng, Wen Li, Chenyang Liu, Hairong Zheng, Jing Cai, and Shanshan Wang. “Artificial intelligence in multiparametric magnetic resonance imaging: A review.Med Phys 49, no. 10 (October 2022): e1024–54. https://doi.org/10.1002/mp.15936.
Li C, Li W, Liu C, Zheng H, Cai J, Wang S. Artificial intelligence in multiparametric magnetic resonance imaging: A review. Med Phys. 2022 Oct;49(10):e1024–54.
Li, Cheng, et al. “Artificial intelligence in multiparametric magnetic resonance imaging: A review.Med Phys, vol. 49, no. 10, Oct. 2022, pp. e1024–54. Pubmed, doi:10.1002/mp.15936.
Li C, Li W, Liu C, Zheng H, Cai J, Wang S. Artificial intelligence in multiparametric magnetic resonance imaging: A review. Med Phys. 2022 Oct;49(10):e1024–e1054.

Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

October 2022

Volume

49

Issue

10

Start / End Page

e1024 / e1054

Location

United States

Related Subject Headings

  • Reproducibility of Results
  • Nuclear Medicine & Medical Imaging
  • Magnetic Resonance Spectroscopy
  • Magnetic Resonance Imaging
  • Machine Learning
  • Humans
  • Artificial Intelligence
  • 5105 Medical and biological physics
  • 4003 Biomedical engineering
  • 1112 Oncology and Carcinogenesis