US 11,832,982 B2
Systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking
James K. Min, Denver, CO (US); James P. Earls, Fairfax Station, VA (US); Hugo Miguel Rodrigues Marques, Lisbon (PT); and Ben Hootnick, New York, NY (US)
Assigned to CLEERLY, INC., Denver, CO (US)
Filed by CLEERLY, INC., Denver, CO (US)
Filed on Dec. 30, 2022, as Appl. No. 18/149,025.
Application 18/149,025 is a continuation of application No. 17/662,734, filed on May 10, 2022.
Application 17/662,734 is a continuation of application No. 17/367,549, filed on Jul. 5, 2021, granted, now 11,367,190, issued on Jun. 21, 2022.
Application 17/367,549 is a continuation of application No. 17/350,836, filed on Jun. 17, 2021.
Application 17/350,836 is a continuation in part of application No. 17/213,966, filed on Mar. 26, 2021, granted, now 11,094,060, issued on Aug. 17, 2021.
Application 17/213,966 is a continuation of application No. 17/142,120, filed on Jan. 5, 2021, granted, now 11,501,436, issued on Nov. 15, 2022.
Claims priority of provisional application 63/201,142, filed on Apr. 14, 2021.
Claims priority of provisional application 63/142,873, filed on Jan. 28, 2021.
Claims priority of provisional application 63/089,790, filed on Oct. 9, 2020.
Claims priority of provisional application 63/077,058, filed on Sep. 11, 2020.
Claims priority of provisional application 63/077,044, filed on Sep. 11, 2020.
Claims priority of provisional application 63/041,252, filed on Jun. 19, 2020.
Claims priority of provisional application 62/958,032, filed on Jan. 7, 2020.
Prior Publication US 2023/0137093 A1, May 4, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 6/00 (2006.01); A61B 8/14 (2006.01); A61B 6/03 (2006.01); A61B 5/00 (2006.01); G06T 7/00 (2017.01); A61B 8/12 (2006.01); A61B 5/055 (2006.01); A61K 49/04 (2006.01); A61B 5/02 (2006.01); G06F 18/10 (2023.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); G06V 10/20 (2022.01); G06V 10/24 (2022.01); G06V 40/14 (2022.01)
CPC A61B 6/481 (2013.01) [A61B 5/0066 (2013.01); A61B 5/0075 (2013.01); A61B 5/02007 (2013.01); A61B 5/055 (2013.01); A61B 5/7267 (2013.01); A61B 5/742 (2013.01); A61B 5/7475 (2013.01); A61B 6/032 (2013.01); A61B 6/037 (2013.01); A61B 6/504 (2013.01); A61B 6/5205 (2013.01); A61B 6/5217 (2013.01); A61B 8/12 (2013.01); A61B 8/14 (2013.01); A61K 49/04 (2013.01); G06F 18/10 (2023.01); G06T 7/0012 (2013.01); G06V 10/20 (2022.01); G06V 10/245 (2022.01); G06V 10/761 (2022.01); G06V 10/764 (2022.01); G06V 40/14 (2022.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10101 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30048 (2013.01); G06T 2207/30101 (2013.01); G06V 10/247 (2022.01)] 30 Claims
OG exemplary drawing
 
1. A computer-implemented method of assessing a risk of coronary artery disease (CAD) for a subject by generating one or more CAD risk scores for the subject based on multi-dimensional information derived from medical image analysis, the method comprising:
accessing, by a computer system, a medical image comprising one or more regions of one or more coronary arteries of a subject;
identifying, by the computer system, one or more segments of coronary arteries within the medical image;
determining, by the computer system, for each of the identified one or more segments of coronary arteries, one or more plaque parameters and one or more vascular parameters, wherein the one or more plaque parameters are determined automatically based at least in part by applying a machine learning algorithm to the accessed medical image, wherein the one or more plaque parameters comprise one or more of plaque volume, plaque composition, plaque attenuation, or plaque location, wherein the one or more vascular parameters comprise one or more of stenosis severity, lumen volume, percentage of coronary blood volume, or percentage of fractional myocardial mass;
generating, by the computer system, for each of the identified one or more segments of coronary arteries a weighted measure of the determined one or more plaque parameters and the one or more vascular parameters;
combining, by the computer system, the generated weighted measure of the determined one or more plaque parameters and the one or more vascular parameters for each of the identified one or more segments of coronary arteries to generate one or more per-vessel, per-vascular territory, or per-subject CAD risk scores; and
generating, by the computer system, a graphical representation of the generated one or more per-vessel, per-vascular territory, or per-subject CAD risk scores for visualizing and quantifying risk of CAD for the subject on one or more of a per-vessel, per-vascular, or per-subject basis, wherein the graphical representation comprises a visual depiction of the one or more regions of the one or more coronary arteries of the subject with graphical indication of one or more vessels or vascular territories based at least in part on the generated one or more per-vessel, per-vascular territory, or per-subject CAD risk scores,
wherein the computer system comprises a computer processor and an electronic storage medium.