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Artificial intelligence for neuro MRI acquisition: a review.
Yang, Hongjia; Wang, Guanhua; Li, Ziyu; Li, Haoxiang; Zheng, Jialan; Hu, Yuxin; Cao, Xiaozhi; Liao, Congyu; Ye, Huihui; Tian, Qiyuan.
Afiliação
  • Yang H; School of Biomedical Engineering, Tsinghua University, Beijing, China.
  • Wang G; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
  • Li Z; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
  • Li H; School of Biomedical Engineering, Tsinghua University, Beijing, China.
  • Zheng J; School of Biomedical Engineering, Tsinghua University, Beijing, China.
  • Hu Y; Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
  • Cao X; Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
  • Liao C; Department of Radiology, Stanford University, Stanford, CA, USA.
  • Ye H; Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
  • Tian Q; Department of Radiology, Stanford University, Stanford, CA, USA.
MAGMA ; 37(3): 383-396, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38922525
ABSTRACT
OBJECT To review recent advances of artificial intelligence (AI) in enhancing the efficiency and throughput of the MRI acquisition workflow in neuroimaging, including planning, sequence design, and correction of acquisition artifacts. MATERIALS AND

METHODS:

A comprehensive analysis was conducted on recent AI-based methods in neuro MRI acquisition. The study focused on key technological advances, their impact on clinical practice, and potential risks associated with these methods.

RESULTS:

The findings indicate that AI-based algorithms have a substantial positive impact on the MRI acquisition process, improving both efficiency and throughput. Specific algorithms were identified as particularly effective in optimizing acquisition steps, with reported improvements in workflow efficiency.

DISCUSSION:

The review highlights the transformative potential of AI in neuro MRI acquisition, emphasizing the technological advances and clinical benefits. However, it also discusses potential risks and challenges, suggesting areas for future research to mitigate these concerns and further enhance AI integration in MRI acquisition.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Processamento de Imagem Assistida por Computador / Inteligência Artificial / Imageamento por Ressonância Magnética / Neuroimagem Limite: Humans Idioma: En Revista: MAGMA / Magma Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Processamento de Imagem Assistida por Computador / Inteligência Artificial / Imageamento por Ressonância Magnética / Neuroimagem Limite: Humans Idioma: En Revista: MAGMA / Magma Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China