Digital Mammography: Computer-Aided Breast Cancer Diagnosis
The purpose of this study is to develop computer programs to assist radiologists in finding breast cancer on mammograms and to compare the computer's accuracy of detecting cancers on direct digital and film mammograms.
|Study Design:||Intervention Model: Single Group Assignment
Masking: Open Label
Primary Purpose: Diagnostic
|Official Title:||Digital Mammography: Computer-Aided Breast Cancer Diagnosis|
- Using computer aided programs to assist in detection and characterization of breast lesions in digital mammography. [ Time Frame: Research scan will be completed at the time of scheduled clinical visit. ] [ Designated as safety issue: No ]
|Study Start Date:||June 2000|
|Estimated Study Completion Date:||August 2015|
|Estimated Primary Completion Date:||August 2015 (Final data collection date for primary outcome measure)|
Experimental: digital mammogram
Digital mammography is a non-invasive imaging technique to obtain an x-ray image of the breast.
Two-view digital mammogram of the breast with a lesion that has been recommended for biopsy during the subject's regular clinical care. The digital mammogram is then analyzed by a computer program.
Procedure: digital mammography
Using non-invasive digital mammography with computer aided programs to screen, detect and characterize breast lesions/cancer.
To develop a computer-aided diagnosis (CAD) system for full field digital mammography (FFDM) using advanced computer vision techniques and to evaluate the effects of CAD on interpretation of digital mammograms (DMs). This system will assist radiologists with the four most important areas in mammographic interpretation: (1) detection of masses, (2) classification of masses, (3) detection of microcalcifications, (4) classification of microcalcifications. The proposed approach is distinctly different from previous approaches in that image information from two-view and bilateral mammograms will be fused with that from the single-view mammogram to improve lesion detection and characterization.
Please refer to this study by its ClinicalTrials.gov identifier: NCT00732433
|United States, Michigan|
|University of Michigan Health System|
|Ann Arbor, Michigan, United States, 48109|
|Principal Investigator:||Heang-Ping Chan, Ph.D.||University of Michigan|