IP Library › Granted Patent US 12,731,672
Granted Patent B2
US 12,731,672 · App. 17/411,473 · Granted Sep 8, 2026

Medical image processing apparatus, system, and method

Inventors: Takuya Sakaguchi (Utsunomiya, JP); Kazumasa Arakita (Utsunomiya, JP); Hideaki Ishii (Nasushiobara, JP); Takahiko Nishioka (Otawara, JP)
Assignee: CANON KABUSHIKI KAISHA
G16H30/40G16H30/20G16H50/30
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,731,672
App. No.
17/411,473
Granted
Sep 8, 2026
Kind
B2
Abstract

A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to acquire a first parameter pertaining to a force at a coronary artery of a subject and a second parameter pertaining to at least one of a shape, character, and fluid resistance related to the coronary artery. The processing circuitry is configured to set, for at least either the first parameter or the second parameter, a weighting factor associated with an anatomical position of the coronary artery. The processing circuitry is configured to calculate, on the basis of the first parameter, the second parameter, and the weighting factor, an index pertaining to a risk on the subject.

Claims (36)

1 . A medical image processing apparatus comprising:

processing circuitry configured to:

acquire a first parameter pertaining to a fractional flow reserve of a coronary artery of a subject and a second parameter pertaining to at least one of a shape, character, and fluid resistance related to the coronary artery;

set a weighting factor for the coronary artery, wherein a heavier value is set for the weighting factor at a proximal side than the weighting factor at a distal side; and

calculate, based on the first parameter, the second parameter, and the weighting factor, an index pertaining to a condition of the subject.

2 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to acquire, as the first parameter, a pertaining to the fractional flow reserve acquired based on an image of the coronary artery of the subject.

3 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to reset the weighting factor to a weighting factor proportional to an area of a short axis cross section of the coronary artery.

4 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to reset the weighting factor to a weighting factor proportional to an area or volume of perfusion by the coronary artery.

5 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to reset the weighting factor to a weighting factor that differs per branch of the coronary artery.

6 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to:

further acquire a third parameter pertaining to a myocardium of the subject; and

calculate, based on the first parameter, the second parameter, the weighting factor, and the third parameter, an index pertaining to a condition of the subject.

7 . The medical image processing apparatus according to claim 6 , wherein the processing circuitry is configured to further set, for the third parameter, weighting associated with an anatomical position of the myocardium.

8 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to:

further acquire a fourth parameter pertaining to a force generated by a pulsation of a myocardium of the subject; and

further use the fourth parameter to calculate an index pertaining to a condition of the subject.

9 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to cause an image of spatial distribution of the index to be displayed.

10 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to cause a map to be displayed, the map reflecting a value of the first parameter and a value of the second parameter included in the index.

11 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to calculate, as an index pertaining to a condition of the subject, an index pertaining to a risk on the subject.

12 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to calculate, as an index pertaining to a condition of the subject, an index pertaining to benefits for the subject.

13 . A medical image processing system comprising:

the medical image processing apparatus according to claim 1 ; and

a medical information display apparatus.

14 . The medical image processing apparatus according to claim 1 , wherein the fractional flow reserve is calculated at two or more different positions along a longitudinal axis of the coronary artery.

15 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to cause a display to display the first parameter, the second parameter, and the weighting factor.

16 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to reset the weighting factor to a weighting factor pertaining to an area of a short axis cross section of the coronary artery.

17 . The medical image processing apparatus according to claim 1 , wherein the processing circuitry is configured to reset the weighting factor to a weighting factor pertaining to an area or volume of perfusion by the coronary artery.

18 . A medical image processing apparatus comprising:

processing circuitry configured to:

acquire a first parameter pertaining to a fractional flow reserve of a coronary artery of a subject and a second parameter pertaining to a myocardium or a pulsation of the myocardium of the subject;

set a weighting factor for the coronary artery, wherein a heavier value is set for the weighting factor at a proximal side than the weighting factor at a distal side; and

calculate, based on the first parameter, the second parameter, and the weighting factor, an index pertaining to a condition of the subject.

19 . A medical image processing method comprising:

acquiring a first parameter pertaining to a fractional flow reserve of a coronary artery of a subject and a second parameter pertaining to at least one of a shape, character, and fluid resistance related to the coronary artery;

set a weighting factor for the coronary artery, wherein a heavier value is set for the weighting factor at a proximal side than the weighting factor at a distal side; and

calculating, based on the first parameter, the second parameter, and the weighting factor, an index pertaining to a condition of the subject.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 1, 2026
From: CANON MEDICAL SYSTEMS CORPORATION
To: CANON KABUSHIKI KAISHA
Reel/Frame 075315/0598 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 10, 2021
From: SAKAGUCHI, TAKUYA; ARAKITA, KAZUMASA; ISHII, HIDEAKI; NISHIOKA, TAKAHIKO
To: CANON MEDICAL SYSTEMS CORPORATION
Reel/Frame 058072/0121 →
Priority Claims (1)
JP 2020-141793 · Aug 25, 2020 · national
Continuity (1)
Related Publication 20220068468A1 · Mar 3, 2022
References Cited (17)
US 12207961B2 · Liu · 2025 [cited by examiner]
US 20100312090A1 · Kerwin · 2010 [cited by examiner]
US 20110218427A1 · Kitamura · 2011 [cited by examiner]
US 20150228115A1 · Wakai et al. · 2015 [cited by applicant]
US 20170065484A1 · Addison · 2017 [cited by examiner]
US 20170245821A1 · Itu · 2017 [cited by examiner]
US 20180020998A1 · Wakai et al. · 2018 [cited by applicant]
US 20180085170A1 · Gopinath · 2018 [cited by examiner]
US 20180357767A1 · Arakita · 2018 [cited by examiner]
US 20200205745A1 · Khosousi · 2020 [cited by examiner]
JP 2008534071A · 2008 [cited by applicant]
JP 6495037B2 · 2019 [cited by applicant]
WO WO2006102511A2 · 2006 [cited by applicant]
Bishop, “Pattern Recognition and Machine Learning”, Springer, (p. 225-290) 2006, 758 pages. [cited by applicant]
Schuijf et al., “Fractional Flow Reserve and Myocardial Perfusion by Computed Tomography: a Guide to Clinical Application”, European Society of Cardiology, http://doi.org/10.1093/ehjcl/jex240_2018, 9 pages. [cited by applicant]
Kate et al. “Fast CT-FFR Analysis Method for the Coronary Artery Based on 4D-CT Image Analysis and Structural and Fluid Analysis”, Proceedings of the ASME 2015 International Mechanical Engineering Congress and Expositio… [cited by applicant]
Hirohata et al., “A Novel CT-FFR Method for the Coronary Artery Based on 4D-CT Image Analysis and Structural and Fluid Analysis”, Proc. of SPIE vol. 9412, 2015, 15 pages. [cited by applicant]