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:
Apr. 07, 2020

Filed:

May. 25, 2018
Applicant:

Sun Yat-sen University, Guangzhou, Guangdong, CN;

Inventors:

Liang Lin, Guangdong, CN;

Qingxing Cao, Guangdong, CN;

Qing Wang, Guangdong, CN;

Bo Jiang, Guangdong, CN;

Assignee:

SUN YAT-SEN UNIVERSITY, Guangzhou, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 7/00 (2017.01); G06K 9/32 (2006.01); G06T 7/62 (2017.01); G06T 7/70 (2017.01); A61B 8/08 (2006.01); A61B 8/00 (2006.01); G06K 9/34 (2006.01); G06K 9/46 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0014 (2013.01); A61B 8/085 (2013.01); A61B 8/469 (2013.01); A61B 8/5223 (2013.01); G06K 9/3233 (2013.01); G06K 9/3241 (2013.01); G06K 9/346 (2013.01); G06K 9/4604 (2013.01); G06K 9/4671 (2013.01); G06K 9/6227 (2013.01); G06K 9/6257 (2013.01); G06K 9/6276 (2013.01); G06K 9/6289 (2013.01); G06T 7/0016 (2013.01); G06T 7/62 (2017.01); G06T 7/70 (2017.01); A61B 8/481 (2013.01); G06K 2209/05 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20072 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30056 (2013.01); G06T 2207/30096 (2013.01);
Abstract

The disclosure relates to a method for automatically recognizing liver tumor types in ultrasound images. The method specifically comprises: using a plurality of Regions of Interest (ROIs) to represent a CEUS image; different lesions are distinguished by the performance and changes of the ROI in time and space; representing a space-time relationship between ROIs by establishing a model in time and space at the same time; and determining, by the model, a relatively appropriate ROI and relevant parameters of the model according to existing CEUS lesion samples by means of an iterative learning method. After giving a sample, an appropriate ROI can be determined and a reference diagnosis for the lesion can be given by removing part of inappropriate ROIs in advance and by means of a rapid search method.


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