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:
Mar. 02, 2021

Filed:

Jul. 28, 2018
Applicant:

Shenzhen Keya Medical Technology Corporation, Shenzhen, CN;

Inventors:

Bin Ma, Bellevue, WA (US);

Ying Xuan Zhi, Seattle, WA (US);

Xiaoxiao Liu, Bellevue, WA (US);

Xin Wang, Seattle, WA (US);

Youbing Yin, Kenmore, WA (US);

Qi Song, Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G16H 50/50 (2018.01); A61B 5/0275 (2006.01); A61B 5/026 (2006.01); A61B 6/00 (2006.01); A61B 6/03 (2006.01); A61B 5/02 (2006.01);
U.S. Cl.
CPC ...
G16H 50/50 (2018.01); A61B 5/0261 (2013.01); A61B 5/0263 (2013.01); A61B 5/0275 (2013.01); A61B 6/504 (2013.01); A61B 6/5217 (2013.01); A61B 5/02007 (2013.01); A61B 6/032 (2013.01); A61B 6/481 (2013.01); G06T 7/0012 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30048 (2013.01); G06T 2207/30104 (2013.01);
Abstract

The present disclosure is directed to a method and device for automatically predicting FFR based on images of vessel. The method for automatically predicting FFR based on images of a vessel. The method comprises a step of receiving the images of a vessel acquired by an imaging device. Then, a sequence of flow speeds at a sequence of positions on a centerline of the vessel is acquired by a processor. A sequence of first features at the sequence of positions on a centerline of the vessel are acquired by the processor, by fusing structure-related features and flow speeds and using a convolutional neural network. Then, a sequence of FFR at the sequence of positions is determined by the processor through using a sequence-to-sequence neural network on the basis of the sequence of first features.


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