Method for combining automated detections from medical images with observed detections of a human interpreter

• US 6,650,766 B1
• Filed: 10/25/2002
• Issued: 11/18/2003
• Est. Priority Date: 08/28/1997
• Status: Expired due to Fees

• Current Assignee: iCAD Incorporated
• Original Assignee: Qualia Computing Inc. (iCAD Incorporated)
• Inventors: Rosenstengel, John E., Broussard, Randy P., Ochoa, Edward M., Hoffmeister, Jeffrey W., Rathbun, Thomas F., Rogers, Steven K., Amburn, Philip, DeSimio, Martin P., Berkey, Telford S.
• Primary Examiner(s): Johns, Andrew W.
• Application Number:
  US10/280,237
• Time in Patent Office: 389 Days
• Field of Search: 382/128, 382/132, 382/309, 382/311, 128/920, 128/922, 378/37, 706/924
• US Class Current: 382/132
• CPC Class Codes: A61B 6/502 for diagnosis of breast, i.e. mammography
• CPC Class Codes: B25J 15/04 with provision for the remote detachment or exchange of the head or parts thereof
• CPC Class Codes: B29C 2791/006 Using vacuum
• CPC Class Codes: B29C 2791/007 Using fluid under pressure
• CPC Class Codes: B29C 49/0021 using moulds or mould parts movable in a closed path, e.g. mounted on movable endless supports
• CPC Class Codes: B29L 2023/18 Pleated or corrugated hoses
• CPC Class Codes: G06F 18/41 Interactive pattern learning with a human teacher
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06V 10/28 Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
• CPC Class Codes: G06V 10/443 by matching or filtering
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images
• CPC Class Codes: Y10S 128/922 including image analysis

Abstract

A method and system for detecting and displaying clustered microcalcifications in a digital mammogram, wherein a single digital mammogram is first automatically cropped to a breast area sub-image which is then processed by means of an optimized Difference of Gaussians filter to enhance the appearance of potential microcalcifications in the sub-image. The potential microcalcifications are thresholded, clusters are detected, features are computed for the detected clusters, and the clusters are classified as either suspicious or not suspicious by means of a neural network. Thresholding is preferably by sloping local thresholding, but may also be performed by global and dual-local thresholding. The locations in the original digital mammogram of the suspicious detected clustered microcalcifications are indicated. Parameters for use in the detection and thresholding portions of the system are computer-optimized by means of a genetic algorithm. The results of the system are optimally combined with a radiologist'"'"'s observation of the original mammogram by combining the observations with the results, after the radiologist has first accepted or rejected individual detections reported by the system.

Claims

1. A method for incorporating the output detections of a computer-aided detection system for detecting suspicious regions in a medical image with observed detections of a human interpreter of the same medical image without reducing sensitivity, comprising the steps of:

obtaining said observed detections to form a first set of detections;

obtaining said output detections to form a second set of detections wherein said output detections are displayed in a printed image;

accepting some output detections in said second set to form a third set of detections;

combining said first set and said third set to form a fourth set of detections; and

providing an output based on said fourth set of detections.

2. The method of claim 1 wherein said some output detections accepted from said second set are selected according to their likelihood of warranting further examination.

3. The method of claim 1 wherein said suspicious regions comprises microcalcifications.

4. The method of claim 1 wherein said output detections are obtained from said computer-aided detection system by a method comprising the steps of:

filtering a digital representation of said medical image to produce a second digital representation in which the appearance of microcalcifications is enhanced;

globally thresholding said second digital representation to locate a set of globally bright pixels;

locally thresholding said second digital representation to locate a set of locally bright pixels; and

generating a third digital representation of those pixels which are common to both said sets of bright pixels.

5. The method of claim 1 wherein said step of forming a fourth set of detections comprises forming a union of said first and third sets of detections.

6. The method of claim 1 wherein said output comprises a visual representation of said medical image with indicia appearing therein indicating the locations of suspicious regions therein.

7. A method for incorporating the output detections of a computer-aided detection system for detecting suspicious regions in a medical image with observed detections of a human interpreter of the same medical image without reducing sensitivity, comprising the steps of:

obtaining said observed detections to form a first set of detections;

obtaining said output detections to form a second set of detections wherein said output detections are displayed on a monitor;

accepting some output detections in said second set to form a third set of detections;

combining said first set and said third set to form a fourth set of detections; and

providing an output based on said fourth set of detections.

8. The method of claim 7 wherein said some output detections accepted from said second set are selected according to their likelihood of warranting further examination.

9. The method of claim 7 wherein said suspicious regions comprises microcalcifications.

10. The method of claim 7 wherein said output detections are obtained from said computer-aided detection system by a method comprising the steps of:

filtering a digital representation of said medical image to produce a second digital representation in which the appearance of microcalcifications is enhanced;

globally thresholding said second digital representation to locate a set of globally bright pixels;

locally thresholding said second digital representation to locate a set of locally bright pixels; and

generating a third digital representation of those pixels which are common to both said sets of bright pixels.

11. The method of claim 7 wherein said step of forming a fourth set of detections comprises forming a union of said first and third sets of detections.

12. The method of claim 7 wherein said output comprises a visual representation of said medical image with indicia appearing therein indicating the locations of suspicious regions therein.