Computer learning assisted blood flow imaging

A system for blood flow imaging comprising:

• a memory for storing 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;
• a CT or MRI image processing component to extract at least one image feature of a measured time-enhancement curve from the CT or MRI image data;
• a machine learning model to generate a predicted value of an area under a time-enhancement curve of the contrast agent within the cardiovasculature of interest by inputting the at least one image feature and an associated at least one non-image feature to the machine learning model, the machine learning model trained with training inputs of the at least one image feature with the at least one non-image feature, and associated with an area under a time-enhancement curve value as ground truth;
• and a processor executing instructions to communicate with the CT or MRI image processing component and the machine learning model, and convert the predicted value of area under the time-enhancement curve to a time rate of change of contrast agent concentration in the cardiovasculature of interest, and determine 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 the time rate of change of contrast agent concentration in the cardiovasculature of interest.