公开(公告)号：US20230047647A1

公开(公告)日：2023-02-16

申请号：US17889189

申请日：2022-08-16

Applicant: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY

Inventor： Hairong ZHENG ,  Xin LIU ,  Na ZHANG ,  Zhanli HU ,  Qihang CHEN ,  Dong LIANG ,  Yongfeng YANG

IPC: G06V10/774 ,  A61B5/055 ,  G06V10/42 ,  G06T11/00

Abstract: Methods and apparatuses for training a magnetic resonance imaging model, electronic devices and computer readable storage media are provided. A method may include: acquiring a magnetic resonance image data set; constructing a ring deep neural network to be trained; inputting an under-sampled magnetic resonance image and a full-sampled magnetic resonance image respectively to two neural networks included in the ring deep neural network, to generate respective simulated magnetic resonance images; inputting a first simulated full-sampled magnetic resonance image and the full-sampled magnetic resonance image to a pre-constructed first simulated magnetic resonance image class discrimination model, to obtain a first discrimination result indicating whether or not the first simulated full-sampled magnetic resonance image is of a simulated magnetic resonance image class; and adjusting a network parameter of the ring deep neural network based on a preset loss function, to obtain a trained magnetic resonance imaging model.