Deep learning algorithms for brain disease detection with magnetic induction tomography.

Journal: Medical physics
PMID: 33119126

Abstract

PURPOSE: In order to improve the reconstruction accuracy of magnetic induction tomography (MIT) and achieve fast imaging especially in the detection of cerebral hemorrhage, artificial intelligence algorithms are proposed to improve the accuracy of MIT inverse problem.

Authors

  • Ruijuan Chen
    School of Life Sciences, Tianjin Polytechnic University, 399 Binshui West Street, Xiqing District, Tianjin, 300387, P.R.China.
  • Juan Huang
    State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Nankai University, Tianjin 300071, PR China.
  • Yixiang Song
    School of Life Sciences, Tianjin Polytechnic University, 399 Binshui West Street, Xiqing District, Tianjin, 300387, P.R.China.
  • Bingnan Li
    School of Life Sciences, Tianjin Polytechnic University, 399 Binshui West Street, Xiqing District, Tianjin, 300387, P.R.China.
  • Jinhai Wang
  • Huiquan Wang

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