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:
Nov. 08, 2022

Filed:

Nov. 30, 2020
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 ...
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); G06T 7/00 (2017.01); 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 system for automatically predicting a physiological parameter based on images of vessel. The method includes receiving the images of a vessel acquired by an imaging device. The method further includes determining a sequence of temporal features at a sequence of positions on a centerline of the vessel based on the images of the vessel, and determining a sequence of structure-related features at the sequence of positions on the centerline of the vessel. The method also includes fusing the sequence of structure-related features and the sequence of temporal features at the sequence of positions respectively. The method additionally includes determining the physiological parameter for the vessel at the sequence of positions, by using a sequence-to-sequence neural network configured to capture sequential dependencies among the sequence of fused features.


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