Accelerating Brain MR Imaging With Multisequence and Convolutional Neural Networks.

Journal: Brain and behavior
Published Date: Nov 1, 2024

Abstract

PURPOSE: Magnetic resonance imaging (MRI) refers to one of the critical image modalities for diagnosis, whereas its long acquisition time limits its application. In this study, the aim was to investigate whether deep learning-based techniques are capable of using the common information in different MRI sequences to reduce the scan time of the most time-consuming sequences while maintaining the image quality.

Authors

  • Zhanhao Mo
  • He Sui
  • Zhongwen Lv
    Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, China.
  • Xiaoqian Huang
    Department of Biomedical Engineering, Faculty of Environment and Life, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing, 100124, China.
  • Guobin Li
    College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China.
  • Dinggang Shen
    School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.
  • Lin Liu
    Institute of Natural Sciences, MOE-LSC, School of Mathematical Sciences, CMA-Shanghai, SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University; Shanghai Artificial Intelligence Laboratory.
  • Shu Liao

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