IP Library Granted Patent US 9,008,405
Granted Patent B2
US 9,008,405 · App. 14/484,112 · Granted Apr 14, 2015

Methods and systems for assessing image quality in modeling of patient anatomic or blood flow characteristics

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Quick Facts
Patent No.
US 9,008,405
App. No.
14/484,112
Granted
Apr 14, 2015
Kind
B2
Abstract

Systems and methods are disclosed for assessing the quality of medical images of at least a portion of a patient's anatomy, using a computer system. One method includes receiving one or more images of at least a portion of the patient's anatomy; determining, using a processor of the computer system, one or more image properties of the received images; performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient's anatomy based on the received images; obtaining an identification of one or more image characteristics associated with an anatomic feature of the patient's anatomy based on the anatomic localization or modeling; and calculating, using a processor of the computer system, an image quality score based on the one or more image properties and the one or more image characteristics.

Claims (62)

1. A method for assessing the quality of medical images of at least a portion of a patient's anatomy, using a computer system, the method comprising:

receiving one or more images of at least a portion of the patient's anatomy;

determining, using a processor of the computer system, one or more global image properties of the received images;

performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient's anatomy based on the received images;

obtaining, for a selected one of the received images, an identification of one or more local image characteristics of the selected one of the received images, where the one or more local image characteristics are associated with an anatomic feature of the patient's anatomy based on the anatomic localization or modeling; and

calculating, using a processor of the computer system, either a global quality assessment of the received images or a local quality assessment of the selected one of the received images, based on one or both of the one or more image properties or the one or more local image characteristics.

2. The method of claim 1 , wherein the one or more local image characteristics are identified based on inputs received from a user.

3. The method of claim 1 , wherein the one or more local image characteristics are identified using a processor of the computer system.

4. The method of claim 1 , wherein the one or more local image characteristics include one or more of: a local contrast level, a local noise level, a misregistration, a misalignment, a local motion anomaly, a local blurring anomaly, a partial volume effect, a blooming effect, and an artifact.

5. The method of claim 1 , wherein the one or more image properties include one or more of: an image resolution, a medical anatomy slice thickness, a number of scanner slices, a medication parameter, and a patient characteristic.

6. The method of claim 1 , further comprising:

calculating a local score in relation to each of the one or more local image characteristics; and

calculating the local quality assessment further based on the local scores calculated for each of the one or more local image characteristics.

7. The method of claim 1 , further comprising:

generating an anatomic model of at least a portion of the patient's anatomy based on the anatomic localization or modeling;

predicting a local uncertainty value of the anatomic model based on the one or more image properties and the one or more local image characteristics;

computing a confidence interval of a simulated blood flow calculation based on the predicted local uncertainty value; and

calculating a total uncertainty value for the anatomic model as a quantitative metric of image quality of the one or more images.

8. The method of claim 1 , further comprising:

generating an anatomic model of at least a portion of the patient's anatomy based on the anatomic localization or modeling;

creating a computational model of a blood flow characteristic based on the anatomic model; and

determining a blood flow characteristic within the patient's anatomy based on the anatomic model and the computational model of the blood flow characteristic of the patient's vasculature.

9. The method of claim 1 , wherein the patient's anatomy includes a portion of the patient's vasculature, the method further comprising:

creating a computational model of a blood flow characteristic based on the anatomic localization or modeling; and

determining a location of a functionally significant narrowing in a vessel of the patient's vasculature based on the determined blood flow characteristic.

10. The method of claim 9 , wherein:

the blood flow characteristic is a fractional flow reserve value;

the fractional flow reserve indicates a ratio between a pressure in a first location and a pressure at a second location in the patient's vasculature; and

the fractional flow reserve is determined at a plurality of locations in the patient's vasculature.

11. A system for assessing the quality of medical images of at least a portion of a patient's anatomy, the system comprising:

a digital storage device storing instructions for assessing the quality of medical images of at least a portion of a patient's anatomy; and

a processor configured to execute the instructions to perform a method including:

receiving one or more images of at least a portion of the patient's anatomy;

determining, using a processor of the computer system, one or more global image properties of the received images;

performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient's anatomy based on the received images;

obtaining, for a selected one of the received images, an identification of one or more local image characteristics of the selected one of the received images, where the one or more image characteristics are associated with an anatomic feature of the patient's anatomy based on the anatomic localization or modeling; and

calculating, using a processor of the computer system, either a global quality assessment for the received images collectively or a local quality assessment for the selected one of the received images, based on the one or more image properties and the one or more image characteristics.

12. The system of claim 11 , wherein the one or more local image characteristics are identified based on inputs received from a user.

13. The system of claim 11 , wherein the one or more local image characteristics are identified using a processor of the computer system.

14. The system of claim 11 , wherein the one or more local image characteristics include one or more of: a local contrast level, a local noise level, a misregistration, a misalignment, a local motion anomaly, a local blurring anomaly, a partial volume effect, a blooming effect, and an artifact.

15. The system of claim 11 , wherein the one or more image properties include one or more of: an image resolution, a medical anatomy slice thickness, a number of scanner slices, a medication parameter, and a patient characteristic.

16. The system of claim 11 , wherein the processor is further configured for:

calculating a local score in relation to each of the one or more local image characteristics; and

calculating the local quality assessment further based on the local scores calculated for each of the one or more local image characteristics.

17. The system of claim 11 , wherein the processor is further configured for:

generating an anatomic model of at least a portion of the patient's anatomy based on the anatomic localization or modeling;

predicting a local uncertainty value of the anatomic model based on the one or more image properties and the one or more local image characteristics;

computing a confidence interval of a simulated blood flow calculation based on the predicted local uncertainty value; and

calculating a total uncertainty value for the anatomic model as a quantitative metric of image quality of the one or more images.

18. The system of claim 11 , wherein the patient's anatomy includes at least a portion of the patient's vasculature, and the processor is further configured for:

generating an anatomic model of at least a portion of the patient's vasculature based on the anatomic localization or modeling;

creating a computational model of a blood flow characteristic based on the anatomic model; and

determining a blood flow characteristic within the patient's vasculature based on the anatomic model and the computational model of the blood flow characteristic of the patient's vasculature.

19. The system of claim 11 , wherein the patient's anatomy includes at least a portion of the patient's vasculature, and wherein the processor is further configured for:

creating a computational model of a blood flow characteristic based on the anatomic localization or modeling; and

determining a location of a functionally significant narrowing in a vessel of the patient's vasculature based on the determined blood flow characteristic.

20. A non-transitory computer readable medium for use on at least one computer system containing computer-executable programming instructions for assessing the quality of medical images of at least a portion of a patient's anatomy, that when executed by the at least one computer system, cause the performance of a method comprising:

receiving one or more images of at least a portion of the patient's anatomy;

determining, using a processor of the computer system, one or more global image properties of the received images;

performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient's anatomy based on the received images;

obtaining, for a selected one of the received images, an identification of one or more local image characteristics of the selected one of the received images, where the one or more local image characteristics are associated with an anatomic feature of the patient's anatomy based on the anatomic localization or modeling; and

calculating, using a processor of the computer system, either a global quality assessment of the received images or a local quality assessment of the selected one of the received images, based on one or both of the one or more image properties or the one or more local image characteristics.

Assignments (5)
RELEASE OF SECURITY INTEREST Recorded Sep 11, 2025
From: HAYFIN SERVICES LLP
To: HEARTFLOW, INC.
Reel/Frame 072876/0775 →
RELEASE OF SECURITY INTEREST Recorded Jun 21, 2024
From: HAYFIN SERVICES LLP
To: HEARTFLOW, INC.
Reel/Frame 067801/0032 →
SECURITY INTEREST Recorded Jun 18, 2024
From: HEARTFLOW, INC.
To: HAYFIN SERVICES LLP
Reel/Frame 067775/0966 →
SECURITY INTEREST Recorded Jan 20, 2021
From: HEARTFLOW, INC.
To: HAYFIN SERVICES LLP
Reel/Frame 055037/0890 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 25, 2017
From: FONTE, TIMOTHY A.; GRADY, LEO J.; WU, ZHONGLE; SCHAAP, MICHIEL; HUNLEY, STANLEY C.; SENGUPTA, SOUMA
To: HEARTFLOW, INC.
Reel/Frame 043682/0534 →