Method and system for automatically generating a disease severity index

• US 20070081707A1
• Filed: 09/20/2006
• Published: 04/12/2007
• Est. Priority Date: 09/29/2005
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Sirohey, Saad, Bembenek, Tamanna, Avinash, Gopal
• Granted Patent: US 7,929,737 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 70/60 relating to pathologies
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Methods and systems for automatically generating a severity index for images of anatomical features of a patient are provided. In an exemplary embodiment, an image of an anatomical feature of a patient is compared with a normal, standardized image of the same anatomical feature. Based on this comparison, a deviation image for the anatomical feature is generated that represents the degree and manner the acquired image deviates from normal for that anatomical feature. The deviation image is automatically pattern matched against multiple images of known disease severity for the anatomical feature. Based on the automated pattern match, a known disease severity, such as in the form of a severity index, is provided as corresponding anatomical feature for the patient.

Claims

1. A method to create a normative categorical score of medical diagnostic images, the method comprising:

accessing image data of at least one specific anatomical region, the anatomical image data being consistent with an indication of functional information in reference to at least one tracer in the anatomical region at the time of the imaging;

determining deviation data from the anatomical image data and from normative standardized anatomical image data based on one or more subject specific factors; and

automatically assigning a severity index to each of the deviation data for each respective anatomical region, wherein each severity index is assigned based on the disease severity deviation images for the respective anatomical region that is automatically matched with each respective deviation data.

2. The method of claim 1, comprising generating a combined severity score from a plurality of severity indices in reference to a rules-based process.

3. The method of claim 2, wherein generating the combined severity score comprises summing the plurality of severity indices in reference to a rules-based process.

4. The method of claim 1, wherein the one or more subject-specific factors comprise at least one of an age of the subject or a sex of the subject.

5. The method of claim 1, comprising acquiring the image data of at least one specific anatomical region using one of magnetic resonance imaging, positron emission tomography, computed tomography, single photon emission computed tomography, ultrasound or optical imaging.

6. The method of claim 1, wherein determining deviation data comprises comparing the image data of at least one specific anatomical region with normative standardized image data for the respective at least one specific anatomical region in reference to the at least one tracer in the anatomical region at the time of the imaging.

7. The method of claim 1, wherein the at least one specific anatomical region comprises at least a portion of a brain.

8. The method of claim 1, wherein the at least one tracer comprises a radioactive tracer.

9. The method of claim 1, wherein automatically matching comprises automatically selecting one or more features within the deviation data for comparison to a set of disease severity deviation images categorized into a degree of severity for each of the at least one anatomical region.

10. The method of claim 1, wherein automatically matching comprises automatically classifying one or more features within the deviation data based on a comparison to a set of disease severity deviation images categorized into a degree of severity for each of the at least one anatomical region.

11. One or more tangible, machine readable media, comprising code executable to perform the acts of:

accessing image data of at least one specific anatomical region, the anatomical image data being consistent with an indication of functional information in reference to at least one tracer in the anatomical region at the time of the imaging;

determining deviation data from the anatomical image data and from normative standardized anatomical image data based on one or more subject specific factors; and

automatically assigning a severity index to each of the deviation data for each respective anatomical region, wherein each severity index is assigned based on the disease severity deviation images for the respective anatomical region that is automatically matched with each respective deviation data.

12. The one or more tangible, machine readable media of claim 11, further comprising code executable to perform the acts of:

generating a combined severity score from a plurality of severity indices in reference to a rules-based process.

13. The one or more tangible, machine readable media of claim 12, wherein the code executable to generate the combined severity score sums the plurality of severity indices in reference to a rules-based process.

14. The one or more tangible, machine readable media of claim 11, wherein the one or more subject-specific factors comprise at least one of an age of the subject or a sex of the subject.

15. The one or more tangible, machine readable media of claim 11, further comprising code executable to perform the acts of:

acquiring the image data of at least one specific anatomical region using one of magnetic resonance imaging, positron emission tomography, computed tomography, single photon emission computed tomography, ultrasound or optical imaging.

16. The one or more tangible, machine readable media of claim 11, wherein the code executable to determine deviation data compares the image data of at least one specific anatomical region with normative standardized image data for the respective at least one specific anatomical region in reference to the at least one tracer in the anatomical region at the time of the imaging.

17. The one or more tangible, machine readable media of claim 11, wherein the at least one specific anatomical region comprises at least a portion of a brain.

18. The one or more tangible, machine readable media of claim 11, wherein the at least one tracer comprises a radioactive tracer.

19. The one or more tangible, machine readable media of claim 11, wherein the code executable to match selects one or more features within the deviation data for comparison to a set of disease severity deviation images categorized into a degree of severity for each of the at least one anatomical region.

20. The one or more tangible, machine readable media of claim 11, wherein the code executable to match classifies one or more features within the deviation data based on a comparison to a set of disease severity deviation images categorized into a degree of severity for each of the at least one anatomical region.

22. The method of claim 20, wherein automatically generating the severity indices comprises automatically matching a deviation image for each patient image with a respective reference image of a set of reference images, wherein each reference image has an associated disease severity.

21. A method for automatically generating a severity score, comprising:

automatically generating a severity index for each of a plurality of patient images; and

automatically deriving a severity score based on the plurality of severity indexes.