The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 28, 2021

Filed:

Jun. 24, 2020
Applicant:

Shenzhen Institutes of Advanced Technology, Shenzhen, CN;

Inventors:

Hairong Zheng, Shenzhen, CN;

Xin Liu, Shenzhen, CN;

Na Zhang, Shenzhen, CN;

Zhanli Hu, Shenzhen, CN;

Dong Liang, Shenzhen, CN;

Yongfeng Yang, Shenzhen, CN;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 7/00 (2017.01); G16H 30/40 (2018.01); G06K 9/62 (2006.01); G06N 3/08 (2006.01); G06T 11/00 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06K 9/6256 (2013.01); G06K 9/6267 (2013.01); G06N 3/08 (2013.01); G06T 11/003 (2013.01); G16H 30/40 (2018.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30101 (2013.01);
Abstract

A method of processing plaques in magnetic resonance imaging of vessel wall include: step Straining a generative adversarial network and a capsule neural network to obtain a trained generator network and a trained capsule neural network; and step Scascade-connecting the trained generator network with the capsule neural network into a system to recognize and classify plaques in magnetic resonance imaging of vessel wall. In one aspect, the capsule neural network has more abundant vascular plaques characteristic information represented by vector; in another aspect, when the trained generator network and the capsule neural network are cascaded into the system to recognize and classify the plaques in magnetic resonance imaging of vessel wall, an accuracy of recognition and classification may be greatly improved. A device for processing the method as well as a computer for implementing are also disclosed.


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