Method and system for image processing to determine blood flow

1. A computer-implemented system, comprising:

at least one computer readable storage medium configured to store computer executable instructions; and

at least one processor configured to execute the computer executable instructions to perform operations comprising:

receiving cardiac imaging data of a patient;

obtaining a three-dimensional geometric model based on the received cardiac imaging data;

segmenting a coronary tree of the three-dimensional geometric model based on the received cardiac imaging data;

comparing at least one aspect of the segmented coronary tree with an empirical model;

adjusting at least one aspect of a further model, based on the comparing, to generate a patient-specific model;

determining a boundary condition of the patient-specific model based on the received cardiac imaging data; and

computing a fractional flow reserve index based on the boundary condition and the patient-specific model.

2. The system of claim 1 , the operations further comprising:

generating an adjusted coronary tree segmentation from the cardiac imaging data with user interaction based on cardiac imaging data of a patient.

3. The system of claim 1 , the operations further comprising:

updating the boundary condition based on the cardiac imaging data of the patient.

4. The system of claim 3 , the operations further comprising:

determining a set of boundary conditions for a set of predetermined variations in the cardiac imaging data of the patient; and

computing a plurality of fractional flow reserve values based on the set of boundary conditions.

5. The system of claim 1 , the operations further comprising:

receiving data obtained from a patient population;

updating the further model based on the received data; and

computing the fractional flow reserve index based on the updated further model.

6. The system of claim 1 , the operations further comprising:

receiving cardiac imaging data of the patient indicating a presence of diabetes; and

increasing a resistance of a boundary condition for a myocardium wall by adjusting resistance boundary condition in response to the indication of the presence of diabetes.

7. The computer-implemented system of claim 1 , wherein the further model is a reduced-order model.

8. The computer-implemented system of claim 1 , wherein the comparing of at least one aspect of the segmented coronary tree with an empirical model includes comparing a vessel geometry of the segmented coronary tree with a vessel geometry of the empirical model.

9. A non-transitory computer readable storage medium encoded with computer readable instructions which, when executed by a processor, cause the processor to perform a method comprising:

receiving cardiac imaging data of a patient;

generating a three-dimensional geometric model based on the received cardiac imaging data;

segmenting a coronary tree of the three-dimensional geometric model based on the received cardiac imaging data;

comparing at least one aspect of the segmented coronary tree with an empirical model;

adjusting at least one aspect of a further model, based on the comparing, to generate a patient-specific model;

determining a boundary condition of the patient-specific model based on the received cardiac imaging data; and

computing a fractional flow reserve index based on the boundary condition and the patient-specific model.

10. The non-transitory computer readable storage medium of claim 9 , the method further comprising:

generating an adjusted coronary tree segmentation from the cardiac imaging data with user interaction based on cardiac imaging data of a patient.

11. The non-transitory computer readable storage medium of claim 9 , wherein the further model is a reduced-order model.

12. The non-transitory computer readable storage medium of claim 9 , wherein the comparing of at least one aspect of the segmented coronary tree with an empirical model includes comparing a vessel geometry of the segmented coronary tree with a vessel geometry of the empirical model.

13. A method, comprising:

receiving cardiac imaging data of a patient;

generating a three-dimensional geometric model based on the received cardiac imaging data;

segmenting a coronary tree of the three-dimensional geometric model based on the received cardiac imaging data;

comparing at least one aspect of the segmented coronary tree with an empirical model;

adjusting at least one aspect of a further model, based on the comparing, to generate a patient-specific model;

determining a boundary condition of the patient-specific model based on the received cardiac imaging data; and

computing a fractional flow reserve index based on the boundary condition and the patient-specific model.

14. The method of claim 13 , further comprising:

generating an adjusted coronary tree segmentation from the cardiac imaging data with user interaction based on cardiac imaging data of a patient.

15. The method of claim 13 , further comprising:

receiving cardiac imaging data of a patient indicating a presence of diabetes; and

increasing a resistance of a boundary condition for a myocardium wall by adjusting resistance boundary condition in response to the indication of the presence of diabetes.

16. The method of claim 13 , wherein the further model is a reduced-order model.

17. The method of claim 13 , wherein the comparing of at least one aspect of the segmented coronary tree with an empirical model includes comparing a vessel geometry of the segmented coronary tree with a vessel geometry of the empirical model.