Mammography Information System

• US 20110137132A1
• Filed: 11/23/2010
• Published: 06/09/2011
• Est. Priority Date: 11/24/2009
• Status: Active Grant

• Current Assignee: Penrad Technologies Incorporated (Intelerad Medical Systems Incorporated)
• Original Assignee: Penrad Technologies Incorporated (Intelerad Medical Systems Incorporated)
• Inventors: Gustafson, Gregory A.
• Granted Patent: US 8,799,013 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: A61B 5/06 Devices, other than using radiation, for detecting or locating foreign bodies for removing same A61B17/50 ; determining position of probes within or on the body of the patient
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/4312 Breast evaluation or disorder diagnosis A61B5/0091 takes precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• 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

Abstract

A method and system for analyzing and retrieving tissue abnormality tracking data, providing a tool for a radiologist that includes a report summarizing the statistical frequency of diagnosed patients, both locally and nationally, with tissue region-of-interest classifications similar to the tissue images taken of the anatomy of an individual patient. In one embodiment, a computer aided diagnostic program can suggest region-of-interest attributes and classifications for user review. In one embodiment, user can select a seed area for computer aided diagnostic program analysis, the CAD analysis can suggest region-of-interest attributes and classifications. In yet another embodiment, the region-of-interest abnormality attributes suggested by the computer aided diagnostic program can be stored and compared with the user selected abnormality attributes and classifications. In one embodiment the images are of human breast tissue.

Claims

1. A configurable mammography diagnostic system, comprising:

a plurality of electronic displays, at least one of the plurality of electronic displays configured to display a breast tissue image;

a graphical user interface presented on at least one of the plurality of electronic displays and including;

a breast tissue image on which at least one region of interest in the breast tissue image can be indicated,

a plurality of possible characteristics according to which an automated categorization of a region of interest in the breast tissue image can be indicated, and

a profiler display configured to present statistical information related to a comparison of the automated categorization with the existing categorizations; and

a processing engine including a computer aided diagnosis (CAD) tool configured to identify the at least one region of interest in the breast tissue image, to provide the automated categorization of the region of interest, and to present the automated categorization of the region of interest via the graphical user interface.

2. The system of claim 1, wherein the breast tissue image is selected from the group consisting of an X-ray image, a CT image, an MRI image, an ultrasound image, and a pathology image.

3. The system of claim 1, wherein each of the plurality of breast tissue images is cataloged in the database according to a characteristic of the breast tissue image.

4. The system of claim 1, wherein the plurality of possible characteristics includes an abnormality type, size, and profile.

5. The system of claim 1, wherein the computer aided diagnosis (CAD) tool is further configured to identify the plurality of possible characteristics of an abnormality depicted in the at least one region of interest.

6. The system of claim 1, wherein the computer aided diagnosis (CAD) tool is further configured to identify the at least one region of interest in the breast tissue image based on a user selection of a portion of the breast tissue image within the region of interest depicted in the breast tissue image.

7. The system of claim 1, wherein the computer aided diagnosis (CAD) tool is further configured to identify the at least one region of interest in the breast tissue image based a user selection of a portion the breast tissue image containing the region of interest depicted in the one of the breast tissue image.

8. The system of claim 1, further comprising an interface to receive a manual re-categorization of the region of interest.

9. The system of claim 8, wherein the processing engine is operable to compare the automated categorization and the manual re-categorization of the region of interest.

10. The system of claim 9, wherein an algorithm of the CAD tool is updated based on the comparison of the CAD automated categorization with the manual re-categorization.

11. The system of claim 8, wherein the processing engine is operable to compare the CAD automated categorization with pathological data related to a particular region of interest.

12. A method for managing patient mammography data comprising:

obtaining a plurality of breast tissue images selected from the group consisting of an X-ray image, a CT image, an MRI image, an ultrasound image, and a pathology image;

identifying a region of interest in at least one of the plurality of breast tissue images;

obtaining, from a computer aided diagnosis (CAD) tool, a categorization of a breast tissue abnormality in the region of interest according to an established lexicon;

presenting the categorization of the breast tissue abnormality in the region of interest to a user;

receiving a confirmation of the categorization from the user; and

associating the confirmed categorization with the region of interest.

13. The method of claim 12, further comprising:

receiving a modification of the categorization from the user.

14. The method of claim 12, further comprising:

comparing the confirmed categorization of the region of interest with a database of existing categorizations.

15. The method of claim 14, further comprising:

presenting a diagnostic indicator comprising a number of instances of the categorization within a database of existing categorizations, a number of diagnoses of malignant abnormalities for the categorization among the existing categorizations, and a number of diagnoses of benign abnormalities for the categorization among the existing categorizations.

16. The method of claim 12, further comprising:

updating the diagnostic indicator based on a comparison of the confirmed categorization and the existing categorizations.

17. The method of claim 16, further comprising:

comparing the user categorization with the computer aided diagnosis (CAD) categorization for the same region of interest.

18. The method of claim 14, wherein the database of existing categorizations includes an identified region of interest in each of a plurality of breast tissue images, and wherein each region of interest is associated with one of either a malignant or a benign diagnosis.

19. The method of claim 18, further comprising:

comparing the associated malignant or benign diagnosis of a region of interest in the database with a computer aided diagnosis (CAD) of the one of the plurality of breast tissue images associated with the region of interest.

20. A method for managing patient medical data comprising:

obtaining a plurality of tissue images selected from the group consisting of an X-ray image, a CT image, an MRI image, an ultrasound image, and a pathology image;

storing the plurality of tissue images in an image database having a non-volatile computer readable medium configured to retrievably store the plurality of tissue images;

performing a digital image analysis of the plurality of tissue images;

identifying a region of interest in at least one of the tissue images;

performing a categorization of a tissue abnormality in the region of interest according to an established lexicon with a computer aided diagnosis (CAD) tool;

presenting the categorization of the tissue abnormality in the region of interest to a user; and

presenting the user with statistical information regarding the categorization.

21. The method of claim 20, further comprising:

receiving a modification of the categorization from the user.

22. The method of claim 20, further comprising:

comparing the categorization with a database including a plurality of diagnosed tissue abnormality categorizations.

23. The method of claim 20, wherein the identification of a region of interest in at least one of the tissue images includes a user selection of a portion of one of the tissue images within the region of interest depicted in the one of the tissue images.

24. The method of claim 20, wherein the identification of a region of interest in at least one of the tissue images includes a user selection of a portion of one of the tissue images containing the region of interest depicted in the one of the tissue images.

25. The method of claim 20, wherein the identification of a region of interest in at least one of the tissue images includes identifying a region of interest in at least one of the tissue images based on the digital image analysis.