Development of a Computer-Aided Diagnosis System for Early Detection of Masses Using Retrospectively Detected Cancers on Prior Mammograms

Abstract

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY) 01-06-20072. REPORT TYPE (From -To) Annual DATES COVERED PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBERUniversity of Michigan Ann Arbor, MI 48109-1274 SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S) U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 SPONSOR/MONITOR'S REPORT NUMBER(S) DISTRIBUTION / AVAILABILITY STATEMENTApproved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES -Original contains colored plates: ALL DTIC reproductions will be in black and white. ABSTRACTThe goal of this project is to develop a computer-aided diagnosis (CAD) system for mass detection using advanced computer vision techniques that will be trained with retrospectively detected cancers on prior mammograms. The new CAD system will be combined with our existing CAD system. When fully developed, the new dual CAD system should increase the sensitivity of detecting cancers at the early stage without compromising the sensitivity for other cancers.During this project year, we have performed the following tasks: (1) continue to collect the data sets of digitized film mammograms for testing our CAD system, (2) investigation of a bilateral approach to reduce the false positives (FPs) on single CAD system, (3) develop image processing techniques for improvement of mass detection on prior mammograms, and (4) continue to develop a two-view information fusion method to improve the performance of single CAD system. In summary, we have investigated a number of areas in CAD of mammographic masses and evaluated the new techniques for mass detection on mammograms. We have made progress in three of the tasks proposed in the project. We have found that our new computer-vision techniques can improve the performance of the CAD systems. We will continue the development of the CAD system in the coming years. SUBJECT TERMSBreast cancer, mammography, CAD (4) IntroductionRecent clinical studies have proved that computer-aided diagnosis (CAD) systems are helpful for improving cancer detection by radio...