US 12,033,323 B2
Method, device and computer-readable medium for automatically classifying coronary lesion according to CAD-RADS classification by a deep neural network
Jean-François Paul, Bourg-la-Reine (FR)
Assigned to SPIMED-AI, Paris (FR)
Appl. No. 17/613,455
Filed by SPIMED-AI, Paris (FR)
PCT Filed May 18, 2020, PCT No. PCT/EP2020/063798
§ 371(c)(1), (2) Date Nov. 22, 2021,
PCT Pub. No. WO2020/234233, PCT Pub. Date Nov. 26, 2020.
Claims priority of application No. 1905408 (FR), filed on May 23, 2019.
Prior Publication US 2022/0215541 A1, Jul. 7, 2022
Int. Cl. G06T 7/00 (2017.01); A61B 6/00 (2024.01); A61B 6/03 (2006.01); A61B 6/50 (2024.01); G06N 3/04 (2023.01); G06N 3/045 (2023.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01)
CPC G06T 7/0012 (2013.01) [A61B 6/032 (2013.01); A61B 6/503 (2013.01); A61B 6/504 (2013.01); A61B 6/507 (2013.01); A61B 6/5217 (2013.01); G06N 3/045 (2023.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/10081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30048 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30101 (2013.01); G06T 2207/30168 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A computer-implemented method for determining the presence of a coronary lesion for a patient, comprising:
receiving at least one curved or stretched multiplanar medical image of computed tomography (X-scanner) of a coronary artery of said patient; and
determining a value according to the CAD-RADS classification (for Coronary Artery Disease-Reporting and Data System value or System of reports and Data) of a coronary lesion on said image or on a portion of said image by using a first trained deep neural network applied directly to the detected images or portions of detected images.