US 12,131,477 B2
Computer learning assisted blood flow imaging
Aaron So, Ontario (CA)
Assigned to London Health Sciences Centre Research Inc., London (CA)
Filed by London Health Sciences Centre Research Inc., London (CA)
Filed on Apr. 3, 2024, as Appl. No. 18/626,293.
Claims priority of provisional application 63/493,927, filed on Apr. 3, 2023.
Prior Publication US 2024/0331159 A1, Oct. 3, 2024
Int. Cl. G06T 7/00 (2017.01); G06T 7/246 (2017.01); G16H 50/30 (2018.01)
CPC G06T 7/0016 (2013.01) [G06T 7/248 (2017.01); G16H 50/30 (2018.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30104 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer implemented method for blood flow imaging comprising:
obtaining CT or MRI image data comprising a plurality of corresponding images capturing at least a portion of one or both an increase phase and a decline phase of a contrast agent in a cardiovasculature of interest;
extracting a first image feature of a measured time-enhancement curve from the CT or MRI image data;
providing the first image feature and at least one non-image feature to a machine learning model to generate a predicted value of an area under a simulated time-enhancement curve of the contrast agent within the cardiovasculature of interest, the predicted value simulating a second set of image acquisition parameters that are different than a first set of image acquisition parameters used to acquire the CT or MRI image data;
converting the predicted value of area under the simulated time-enhancement curve to a total sum of contrast agent concentration time product in the cardiovasculature of interest;
determining a blood flow characteristic in the cardiovasculature of interest based on a ratio of mass of the contrast agent in the cardiovasculature of interest to a total sum of contrast agent concentration time product in the cardiovasculature of interest.