FULL-MODAL MEDICAL IMAGE SEQUENCE GROUPING METHOD BASED ON DEEP LEARNING SIGN STRUCTURE

WIPO Patent Application WO/2022/077858

A1

A full-modal medical image sequence grouping method based on a deep learning sign structure. The method comprises: acquiring medical image information; performing information extraction on the acquired medical image information; establishing a full-modal deep learning AI sequence matching system; performing sequence matching processing; transmitting processed medical image sequences to a display unit in groups; and the display unit displaying full-modal medical image sequences in groups. A deep learning neural network is used, human skeletons are precisely identified and segmented into relatively fixed local regions according to precise CT and MR anatomy information of a human body, precise human body position segmentation is performed using specified skeleton parts, precise positioning is performed according to a CT or MR image in dual modalities of a molecular image, the CT or MR image is converted to a corresponding layer of a full-modal image, and automatic and precise registration and display is performed, such that diagnosis errors caused by a technical level difference are reduced, and the working efficiency of physicians is also improved.

SHI HONGCHENG (CN)
CHEN SHUGUANG (CN)
HU PENGCHENG (CN)
LIU GUOBING (CN)
GU YUCAN (CN)
YU HAOJUN (CN)

PCT/CN2021/081413

April 21, 2022

March 18, 2021

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ZHONGSHAN HOSPITAL OF FUDAN UNIV (CN)

G06N3/08; G06T7/33

CN112308888A	2021-02-02
CN108701370A	2018-10-23
CN109285200A	2019-01-29
US20200134883A1	2020-04-30

SHANGHAI KESHENG INTELLECTUAL PROPERTY AGENCY LTD. (CN)

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