Systems and Methods for Automated Diagnosis and Decision Support for Breast Imaging

• US 20100121178A1
• Filed: 11/18/2009
• Published: 05/13/2010
• Est. Priority Date: 06/25/2003
• Status: Abandoned Application

• Current Assignee: Glenn Fung, Murat Dundar, Rao R. Bharat, Sriram Krishnan
• Original Assignee: Glenn Fung, Murat Dundar, Rao R. Bharat, Sriram Krishnan
• Inventors: Fung, Glenn, Krishnan, Sriram, Rao, R. Bharat, Dundar, Murat
• Application Number:
  US12/621,363
• Publication Number:
  US 20100121178A1
• Time in Patent Office: Days
• US Class Current: 600/411
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/10116 X-ray image
• CPC Class Codes: G06T 2207/20084 Artificial neural networks [ANN]
• CPC Class Codes: G06T 2207/30068 Mammography; Breast
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics
• CPC Class Codes: Y10S 128/922 including image analysis
• CPC Class Codes: Y10S 128/923 by comparison of patient data to other data
• CPC Class Codes: Y10S 128/924 using artificial intelligence

Abstract

CAD (computer-aided diagnosis) systems and applications for breast imaging are provided, which implement methods to automatically extract and analyze features from a collection of patient information (including image data and/or non-image data) of a subject patient, to provide decision support for various aspects of physician workflow including, for example, automated diagnosis of breast cancer other automated decision support functions that enable decision support for, e.g., screening and staging for breast cancer. The CAD systems implement machine-learning techniques that use a set of training data obtained (learned) from a database of labeled patient cases in one or more relevant clinical domains and/or expert interpretations of such data to enable the CAD systems to “learn” to analyze patient data and make proper diagnostic assessments and decisions for assisting physician workflow.

Claims

1. A system for providing automatic diagnosis and decision support, comprising:

an image acquisition device for obtaining information from image data of a subject patient;

a phase spotting unit for receiving non-image data records of the subject patient, extracting an unstructured free-text source from the non-image data records, and identifying phrases of interest from the free-text source;

a rules database including a list of rules for providing inferences drawn from the identified phrases of interest; and

an automatic diagnosis unit for providing diagnosis using the information from the image data and the inferences drawn from the identified phrases of interest.

2. The system of claim 1, wherein the image data includes a breast of the subject patient and the automatic diagnosis unit provides diagnosis pertaining to abnormal breast tissue.

3. The system of claim 1, further comprising a patient management module for recommending therapies to the patient based on the provided diagnosis.

4. The system of claim 1, wherein the image data is ultrasound image data and wherein the automatic diagnosis unit automatically extracts one or more features from the ultrasound data in providing diagnosis.

5. The system of claim 1, wherein the image data is acquired using an ultrasound medical imaging device.

6. The system of claim 5, wherein the ultrasound medical imaging device is a three-dimensional ultrasound.

7. The system of claim 1 wherein the automatic diagnosis unit is a computer aided diagnosis system.

8. The system of claim 1, wherein the image data is acquired using an X-ray mammography scanner, an MRI scanner, an ultrasound imager or a combination thereof.

9. A method for providing automatic diagnosis and decision support, comprising:

obtaining information from image data of a subject patient;

receiving non-image data records of the subject patient, extracting an unstructured free-text source from the non-image data records, and identifying phrases of interest from the free-text source;

referencing a rules database to provide inferences drawn from the identified phrases of interest; and

automatically providing diagnosis using the information from the image data and the inferences drawn from the identified phrases of interest,

where in the above steps are performed using a computer assisted diagnosis system.

10. The method of claim 9, wherein the image data includes a breast of the subject patient and the automatic diagnosis comprises diagnosis pertaining to abnormal breast tissue.

11. The method of claim 9, wherein one or more therapies are recommended to the patient based on the provided diagnosis.

12. The method of claim 11, wherein the recommending of the one or more therapies is influenced using user criteria provided through a user interface.

13. The method of claim 11, wherein the recommending of the one or more therapies is influenced clinical knowledge provided through a clinical knowledge database.

14. The method of claim 11, wherein the recommending of the one or more therapies utilizes an interactive diagnostic workflow assistance module.

15. The method of claim 9, wherein automatically providing the diagnosis is influenced by user criteria provided through a user interface.

16. The method of claim 9, wherein automatically providing the diagnosis is influenced by clinical knowledge provided through a clinical knowledge database.

17. The method of claim 9, wherein automatically providing the diagnosis utilizes an interactive diagnostic workflow assistance module.

18. A method for providing automatic diagnosis and decision support, comprising:

obtaining information from image data of a subject patient;

receiving non-image data records of the subject patient, extracting an unstructured free-text source from the non-image data records, and identifying phrases of interest from the free-text source;

automatically providing diagnosis using the information from the image data and the identified phrases of interest; and

recommending one or more therapies based on the provided diagnosis and user criteria,

where in the above steps are performed using a computer assisted diagnosis system.

19. The method of claim 18, wherein the image data includes a breast of the subject patient and the automatic diagnosis comprises diagnosis pertaining to abnormal breast tissue.

20. The method of claim 18, wherein the image data is ultrasound image data, X-ray mammography image data, MRI data, or a combination thereof.