Method and apparatus for knowledge based diagnostic imaging

• US 20050010098A1
• Filed: 03/26/2004
• Published: 01/13/2005
• Est. Priority Date: 04/11/2003
• Status: Abandoned Application

• Current Assignee: GE Medical Systems Global Technology Company LLC (GE Healthcare Technologies, Inc.)
• Original Assignee: GE Medical Systems Global Technology Company LLC (GE Healthcare Technologies, Inc.)
• Inventors: Frigstad, Sigmund, Olstad, Bjorn
• Application Number:
  US10/810,132
• Publication Number:
  US 20050010098A1
• Time in Patent Office: Days
• US Class Current: 600/407
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 6/00 Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment instruments measuring radiation intensity for application in the field of nuclear medicine, e.g. in vivo counting, G01T1/161; apparatus for taking X-ray photographs G03B42/02
• CPC Class Codes: A61B 6/541 involving acquisition triggered by a physiological signal
• CPC Class Codes: A61B 6/56 Details of data transmission or power supply, e.g. use of slip rings
• CPC Class Codes: A61B 6/563 involving image data transmission via a network
• CPC Class Codes: A61B 8/00 Diagnosis using ultrasonic, sonic or infrasonic waves imaging of objects using sonar G01S15/00
• CPC Class Codes: A61B 8/08 Detecting organic movements or changes, e.g. tumours, cysts, swellings A61B8/02 - A61B8/06 take precedence
• CPC Class Codes: A61B 8/483 involving the acquisition of a 3D volume of data
• CPC Class Codes: A61B 8/543 involving acquisition triggered by a physiological signal
• CPC Class Codes: A61B 8/56 Details of data transmission or power supply
• CPC Class Codes: A61B 8/565 involving data transmission via a network
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

A knowledge based diagnostic imaging system, comprising diagnostic equipment for analyzing a patient to obtain a new patient data set containing at least one of MR data, CT data, ultrasound data, x-ray data, SPECT data and PET data. The diagnostic equipment automatically analyzes the new patient data set with respect to a physiologic parameter of the patient to obtain a patient value for said physiologic parameter. A database containing past patient data sets for previously analyzed patients. The past patient data sets contain data indicative of the physiologic parameter with respect to previously analyzed patients. A network interconnects the diagnostic equipment and the database to support access to the past patient data sets.

Claims

1. A knowledge-based diagnostic imaging system, comprising:

diagnostic equipment for analyzing a patient to obtain a new patient data set containing at least one of MR data, CT data, ultrasound data, x-ray data, SPECT data and PET data, said diagnostic equipment automatically analyzing said new patient data set;

a database containing past patient data sets for previously analyzed patients, said past patient data sets containing data indicative of physiologic parameters with respect to previously analyzed patients;

a network for interconnecting said diagnostic equipment and said database to support access to said past patient data sets; and

a controller for accessing said database based on said new patient data set.

2. The knowledge-based diagnostic imaging system of claim 1, wherein said diagnostic equipment is an ultrasound system and said new patient data set contains at least one ultrasound image.

3. The knowledge-based diagnostic imaging system of claim 1, wherein said physiologic parameter is for the myocardium and said controller accesses said database based on at least one of an AV-plane, tissue velocity, systolic transition, myocardium period length, hypertrophy, diastolic point, heart size and heart shape.

4. The knowledge-based diagnostic imaging system of claim 1, wherein said controller accesses said database based on at least one of contraction patterns and velocity profiles of the myocardium of the previously analyzed patients.

5. The knowledge-based diagnostic imaging system of claim 1, wherein said diagnostic equipment highlights abnormalities in an image generated from said new patent data set.

6. The knowledge-based diagnostic imaging system of claim 1, wherein said diagnostic equipment compares new and past patient data sets to determine whether additional information is needed.

7. The knowledge-based diagnostic imaging system of claim 1, wherein said controller compares at least one of said past patient data sets to said new patient data set.

8. The knowledge-based diagnostic imaging system of claim 1, wherein said diagnostic equipment includes an ultrasound machine for generating a new patient image from said new patient data set and for identifying said physiologic parameter based on said new patient image.

9. The knowledge-based diagnostic imaging system of claim 1, wherein said diagnostic equipment automatically measures values for said physiologic parameter from said new patient data set.

10. The knowledge-based diagnostic imaging system of claim 1, wherein said new and past patient data sets represent new and past patient images, respectively, said controller identifying matches between said new and past patient images.

11. The knowledge-based diagnostic imaging system of claim 1, said controller further comprising a processor located separate and remote from said diagnostic equipment, said processor comparing said new patient data set to said past patient data sets to identify matches.

12. A method for providing knowledge-based diagnostic imaging, comprising:

analyzing a patient to obtain a new patient data set containing at least one of MR data, CT data, ultrasound data, x-ray data, SPECT data and PET data;

automatically analyzing said new patient data set;

accessing past patient data sets for previously analyzed patients, said past patient data sets containing stored patient values indicative of said physiologic parameter with respect to previously analyzed patients; and

analyzing said past patient data sets of previously analyzed patients based on said new patient data set.

13. The method of claim 12, wherein said analyzing the patient includes obtaining ultrasound images of the patient as said new patient data set.

14. The method of claim 12, wherein said automatically analyzing said new patient data set includes measuring at least one of an AV-plane, tissue velocity, systolic transition, myocardium period length, hypertrophy, diastolic point, heart size and heart shape.

15. The method of claim 12, wherein said past patient data sets contain at least one of contraction patterns and velocity profiles of the myocardium of the previously analyzed patients.

16. The method of claim 12, wherein said analyzing the patient includes comparing said new patient data set to at least one of said past patient data sets.

17. The method of claim 12, wherein said analyzing the patient includes generating a new patient image from said new patient data set and said automatically analyzing includes identifying said physiologic parameter from said new patient image.

18. The method of claim 12, wherein said automatically analyzing includes measuring values for said physiologic parameter from a patient image.

19. The method of claim 12, further comprising highlighting abnormalities in an image generated from said new patient data set.

20. The method of claim 12, further comprising comparing new and past patient data sets and determining whether additional information is needed based on said comparison.

21. A network comprising:

diagnostic equipment for analyzing a patient to obtain new patient images based on at least one of MR data, CT data, ultrasound data, x-ray data, SPECT data and PET data, said diagnostic equipment automatically analyzing a said new patient images;

a database containing past patient images for previously analyzed patients; and

an interconnection between said diagnostic equipment and said database, said database providing past patient images for previously analyzed patients; and

a controller for accessing said past patient images based on said new patient images.

22. The network of claim 21, wherein said diagnostic equipment includes an ultrasound machine.

23. The network of claim 21, wherein said physiologic parameter is for the myocardium and includes at least one of an AV-plane, tissue velocity, systolic transition, myocardium period length, hypertrophy, diastolic point, heart size and heart shape.

24. The network of claim 21, wherein said past patient images contain at least one of contraction patterns and velocity profiles of the myocardium of the previously analyzed patients.

25. The network of claim 21, wherein said diagnostic equipment is located at a primary health care site.

26. The network of claim 21, wherein said diagnostic equipment determines where said physiologic parameter for the new patient is abnormal.

27. The network of claim 21, wherein said diagnostic equipment highlights, in said new patient image, an abnormality.

28. The network of claim 21, wherein said diagnostic equipment determines whether additional information is needed from an operator after comparing said new patient image to said past patient images.