US 12,112,471 B2
Systems and methods for multi-label segmentation of cardiac computed tomography and angiography images using deep neural networks
Mario Viti, Paris (FR); Faycal El Hanchi El Amrani, Paris (FR); Nicolas Gogin, Chatenay Malabry (FR); and Celine Pruvot, Buc (FR)
Assigned to GE PRECISION HEALTHCARE LLC, Milwaukee, WI (US)
Filed by GE Precision Healthcare LLC, Milwaukee, WI (US)
Filed on Nov. 22, 2021, as Appl. No. 17/456,145.
Application 17/456,145 is a continuation of application No. 16/653,906, filed on Oct. 15, 2019, granted, now 11,205,264.
Prior Publication US 2022/0084198 A1, Mar. 17, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 7/11 (2017.01); A61B 5/00 (2006.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01); G06T 17/00 (2006.01)
CPC G06T 7/0012 (2013.01) [A61B 5/7264 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06T 7/11 (2017.01); G06T 17/005 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/30048 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30101 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method comprising:
acquiring a 3D cardiac computed tomography and angiography (CCTA) image of a coronary tree;
mapping the 3D CCTA image to a multi-label segmentation map with a trained deep neural network;
generating a plurality of 1D parametric curves for a branch of the coronary tree using the multi-label segmentation map;
determining a location of a lesion in the branch of the coronary tree using the plurality of 1D parametric curves, wherein determining the location of the lesion in the branch of the coronary tree using the plurality of 1D parametric curves comprises determining start and stop points of the lesion in the branch of the coronary tree based on the plurality of 1D parametric curves; and
determining a severity score for the lesion based on the plurality of 1D parametric curves,
wherein generating the plurality of 1D parametric curves for the branch of the coronary tree using the multi-label segmentation map comprises determining values for each of a plurality of pre-defined parameters for each point along a centerline of the branch of the coronary tree, wherein the plurality of pre-defined parameters include one or more of lipid core thickness, vessel wall thickness, lumen radius, and lumen tortuosity.