公开(公告)号：US20240169610A1

公开(公告)日：2024-05-23

申请号：US18363703

申请日：2023-08-01

Applicant: ZHEJIANG LAB

Inventor： Jingsong LI ,  Yiwei GAO ,  Peijun HU ,  Tianshu ZHOU ,  Yu TIAN

IPC: G06T11/00 ,  G06T3/40 ,  G06T5/00 ,  G16H30/40

CPC classification number: G06T11/006 ,  G06T3/4053 ,  G06T5/002 ,  G06T11/005 ,  G16H30/40 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30004 ,  G06T2207/30168 ,  G06T2211/441

Abstract: The present application discloses a label-free adaptive CT super-resolution reconstruction method, device and system based on a generative network, which comprises the following modules: an acquisition module configured for acquiring low-resolution original CT image data; a preprocessing module configured for performing super-resolution reconstruction on original CT images based on total variation to obtain an initial value; and a super-resolution reconstruction module configured for performing high-resolution reconstruction on the initial value. According to the present application, a parameter fine-tuning method is adopted, and a CT reconstruction network which is not suitable for a certain patient is adjusted into a network which is suitable for the patient's situation on the premise of not using a large number of data sets for training; only the low-resolution CT data of the patient is used in this process, and the corresponding high-resolution CT data is not needed as a label.