Method and system for generating multi-task learning-type generative adversarial network for low-dose PET reconstruction

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United States of America Patent

PATENT NO 11756161
SERIAL NO

17340117

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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.

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Patent OwnerAddress
SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY1068 NO 518055 GUANGDONG CITY IN SHENZHEN PROVINCE NANSHAN DISTRICT CITY XILI UNIVERSITY SCHOOL AVENUE SHENZHEN CITY GUANGDONG PROVINCE 518055

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Hu, Zhanli Guangdong, CN 10 5
Liang, Dong Guangdong, CN 117 759
Liu, Xin Guangdong, CN 657 8645
Sun, Hanyu Guangdong, CN 12 7
Yang, Yongfeng Guangdong, CN 10 9
Zhang, Na Guangdong, CN 248 911
Zheng, Hairong Guangdong, CN 60 102

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