Abstract: A method and system for computing blood flow in coronary arteries from medical image data disclosed. Patient-specific anatomical measurements of a coronary artery tree are extracted from medical image data of a patient. A reference radius is estimated for each of a plurality of branches in the coronary artery tree from the patient-specific anatomical measurements of the coronary artery tree. A flow rate is calculated based on the reference radius for each of the plurality of branches of the coronary artery tree. A plurality of total flow rate estimates for the coronary artery tree are calculated. Each total flow rate estimate is calculated from the flow rates of branches of particular generation in the coronary artery tree. A total flow rate of the coronary artery tree is calculated based on the plurality of total flow rate estimates. The total flow rate of the coronary artery tree can be used to derive boundary conditions for simulating blood flow in the coronary artery tree.

Abstract: Personalized whole-body circulation calculation is provided. In one embodiment, a combination of models at different scales and machine learning may be used to personalize and calculate the circulation for a particular patient. In another embodiment, imaging, ECG, and pressure data are used to personalize a multi-scale whole body circulation model. Different parameters, such as (but not limited to) time-varying flow rate for the heart, pressure variation for the heart, cardiovascular systemic impedance, and cardiovascular pulmonary impedance, are determined for the patient and used to personalize the model. The model is then used to determine, visualize, or report a diagnostically or therapeutically useful circulation metric for that patient.