Patent ID: 11967004
Assignee: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G  A | IPC A  G

Claim 19:
20. A method of training a neural network to learn a model for reconstructing magnetic resonance (MR) images, the method comprising:
the neural network obtaining a first portion of a MR training dataset, wherein the MR training dataset is associated with a single MR scan and comprises under-sampled MR data associated with an anatomical structure, multiple contrast settings, multiple coils, and multiple segments in a readout direction, and wherein the first portion of the MR training dataset that corresponds to a target contrast and includes data associated with a first subset of the multiple coils and a first segment in the readout direction;
the neural network reconstructing a first MR image of the anatomical structure based on the first portion of the MR training dataset;
the neural network obtaining a second portion of the MR training dataset, wherein the second portion of the MR training dataset is associated with the target contrast and includes data associated with a second subset of the multiple coils and a second segment in the readout direction;
the neural network reconstructing a second MR image of the anatomical structure based on the second portion of the MR training dataset;
the neural network deriving an MR image of the anatomical structure that is associated with the target contrast based at least on the first MR image and the second MR image; and
the neural network adjusting one or more operating parameters based on a difference between the derived MR image and a ground truth MR image.