公开(公告)号：US11756161B2

公开(公告)日：2023-09-12

申请号：US17340117

申请日：2021-06-07

Applicant: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY

Inventor： Zhanli Hu ,  Hairong Zheng ,  Na Zhang ,  Xin Liu ,  Dong Liang ,  Yongfeng Yang ,  Hanyu Sun

IPC: G06T5/00 ,  A61B6/03 ,  G06N3/08 ,  G06N3/045

CPC classification number: G06T5/00 ,  A61B6/037 ,  G06N3/045 ,  G06N3/08 ,  G06T2207/10088 ,  G06T2207/10104 ,  G06T2207/20081

Abstract: The present application relates to a method and system for generating multi-task learning-type generative adversarial network for low-dose PET reconstruction, and relates to the field of deep learning. The method includes connecting layers of the encoder with layers of the decoder by skip connection to provide a U-Net type picture generator; generating a group of generative adversarial networks by matching a plurality of picture generators with a plurality of discriminators in one-to-one manner; obtaining a first multi-task learning-type generative adversarial network; designing a joint loss function 1 for improving image quality; and training the first multi-task learning-type generative adversarial network according to the joint loss function 1 in combination with an optimizer to provide a second multi-task learning-type generative adversarial network.