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:
Jan. 06, 2026

Filed:

Jun. 12, 2023
Applicant:

Shanghai United Imaging Intelligence Co., Ltd., Shanghai, CN;

Inventors:

Shanhui Sun, Cambridge, MA (US);

Zhang Chen, Cambridge, MA (US);

Terrence Chen, Cambridge, MA (US);

Ziyan Wu, Cambridge, MA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 7/246 (2017.01); A61B 5/00 (2006.01); A61B 6/00 (2024.01); A61B 6/46 (2024.01); A61B 8/00 (2006.01); G06N 3/02 (2006.01); G06N 3/0475 (2023.01); G06N 3/088 (2023.01); G06N 3/0895 (2023.01); G06N 3/094 (2023.01); G06N 5/04 (2023.01); G06N 7/02 (2006.01); G06N 20/00 (2019.01); G06T 3/18 (2024.01); G06T 7/00 (2017.01); G06T 7/20 (2017.01); G06T 7/33 (2017.01); G06T 7/73 (2017.01); G06V 10/25 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); H04N 13/20 (2018.01); H04N 19/137 (2014.01); H04N 19/139 (2014.01); H04N 19/513 (2014.01); H04N 19/527 (2014.01); A61B 5/11 (2006.01); A61N 5/10 (2006.01);
U.S. Cl.
CPC ...
G06T 7/251 (2017.01); A61B 5/0004 (2013.01); A61B 5/0044 (2013.01); A61B 5/4857 (2013.01); A61B 5/72 (2013.01); A61B 5/748 (2013.01); A61B 5/7485 (2013.01); A61B 6/469 (2013.01); A61B 6/5217 (2013.01); A61B 8/5207 (2013.01); G06N 3/02 (2013.01); G06N 3/0475 (2023.01); G06N 3/088 (2013.01); G06N 3/0895 (2023.01); G06N 3/094 (2023.01); G06N 5/04 (2013.01); G06N 7/023 (2013.01); G06N 20/00 (2019.01); G06T 3/18 (2024.01); G06T 7/0012 (2013.01); G06T 7/0014 (2013.01); G06T 7/20 (2013.01); G06T 7/248 (2017.01); G06T 7/337 (2017.01); G06T 7/74 (2017.01); G06V 10/25 (2022.01); G06V 10/764 (2022.01); G06V 10/7753 (2022.01); G06V 10/82 (2022.01); H04N 13/20 (2018.05); H04N 19/137 (2014.11); H04N 19/139 (2014.11); H04N 19/513 (2014.11); H04N 19/521 (2014.11); H04N 19/527 (2014.11); A61B 5/1107 (2013.01); A61B 5/7264 (2013.01); A61N 2005/1072 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01); G06T 2207/30048 (2013.01); G06T 2207/30061 (2013.01); G06T 2210/41 (2013.01); G06T 2211/00 (2013.01); G06T 2211/40 (2013.01); G06T 2211/424 (2013.01); G06T 2211/441 (2023.08); G06T 2215/00 (2013.01); G06V 2201/031 (2022.01);
Abstract

A system for physiological motion measurement is provided. The system may acquire a reference image corresponding to a reference motion phase of an ROI and a target image of the ROI corresponding to a target motion phase, wherein the reference motion phase may be different from the target motion phase. The system may identify one or more feature points relating to the ROI from the reference image, and determine a motion field of the feature points from the reference motion phase to the target motion phase using a motion prediction model. An input of the motion prediction model may include at least the reference image and the target image. The system may further determine a physiological condition of the ROI based on the motion field.


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