公开(公告)号：US20230316549A1

公开(公告)日：2023-10-05

申请号：US17997693

申请日：2021-04-13

Applicant: Huazhong University of Science and Technology

Inventor： Xuming ZHANG ,  Xingxing ZHU

IPC: G06T7/33 ,  G06T5/20 ,  G06V10/44 ,  G06V10/74 ,  G16H30/20

CPC classification number: G06T7/337 ,  G06T5/20 ,  G06T7/344 ,  G06V10/454 ,  G06V10/761 ,  G16H30/20 ,  G06T2207/20081

Abstract: Disclosed are a method for establishing a non-rigid multi-modal medical image registration model and an application thereof, which pertain to the field of medical image registration. The method comprises: establishing a generative adversarial network GAN_dr, wherein a generator G_dr is used to generate a deformation recovered structural representations, and a discriminator D_dr is used to determine whether the structural representations generated by G_dr has effectively recovered deformations; performing calculation with respect to structural representations of a reference image, a floating image, and an actual registered image in each sample in a medical dataset, and using a calculation result to train GAN_dr; establishing a generative adversarial network GAN_ie, wherein a generator G_ie uses the structural representations as an input to estimate a registered image, and a discriminator D_ie is used to determine whether the estimated registered image is consistent with the actual registered image; using the trained G_dr to generate the deformation recovered structural representations corresponding to each sample in the medical dataset, and training GAN_ie; and after connecting the trained G_ie to G_dr, obtaining the registration model. The present invention can achieve fast and accurate matching of medical images.