Advances of deep learning in electrical impedance tomography image

HIGHLIGHTS

  • who: December and collaborators from the Shenzhen University, China have published the research: Advances of deep learning in electrical impedance tomography image, in the Journal: (JOURNAL)
  • what: In this review, the authors systematically analyzed the application and development of deep learning technology in EIT image reconstruction from three aspects: neural_network reconstruction directly from EIT measurement data, traditional algorithm and deep learning joint reconstruction, and multiple network hybrid reconstruction.
  • how: Following that work they proposed a structure-aware two-branch network (SADB-Net) that fuses information together by two feature extractors and the results . . .

     

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