公开(公告)号：US11769237B2

公开(公告)日：2023-09-26

申请号：US18001295

申请日：2021-01-30

Applicant: HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Xuming Zhang ,  Shaozhuang Ye

IPC: G06T5/50 ,  G16H30/40 ,  G06T3/40 ,  G06T3/60 ,  G06T5/20 ,  G06V10/80 ,  G06V10/771

CPC classification number: G06T5/50 ,  G06T3/40 ,  G06T3/60 ,  G06T5/20 ,  G06V10/771 ,  G06V10/806 ,  G16H30/40 ,  G06T2207/20081 ,  G06T2207/20221

Abstract: A multimodal medical image fusion method based on a DARTS network is provided. Feature extraction is performed on a multimodal medical image by using a differentiable architecture search (DARTS) network. The network performs learning by using the gradient of network weight as a loss function in a search phase. A network architecture most suitable for a current dataset is selected from different convolution operations and connections between different nodes, so that features extracted by the network have richer details. In addition, a plurality of indicators that can represent image grayscale information, correlation, detail information, structural features, and image contrast are used as a network loss function, so that the effective fusion of medical images can be implemented in an unsupervised learning way without a gold standard.