Digital Mammography: Computer-Aided Breast Cancer Diagnosis
This study is ongoing, but not recruiting participants.
Information provided by (Responsible Party):
Heang-Ping Chan Ph.D, University of Michigan
First received: August 7, 2008
Last updated: July 25, 2017
Last verified: July 2017
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.
Procedure: digital mammography
||Intervention Model: Single Group Assignment
Masking: None (Open Label)
Primary Purpose: Diagnostic
||Digital Mammography: Computer-Aided Breast Cancer Diagnosis
Primary Outcome Measures:
- 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. ]
| Estimated Enrollment:
| Study Start Date:
| Estimated Study Completion Date:
| Estimated Primary Completion Date:
||August 2017 (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.
|Ages Eligible for Study:
||18 Years to 80 Years (Adult, Senior)
|Sexes Eligible for Study:
|Accepts Healthy Volunteers:
- Females who have been scheduled for mammographic exams.
- Females who have been recommended for work-up or biopsy due to a suspicious finding on their mammogram.
- Females who can give informed consent.
- No subject under 18 years of age
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Please refer to this study by its ClinicalTrials.gov identifier: NCT00732433
|University of Michigan Health System
|Ann Arbor, Michigan, United States, 48109 |
University of Michigan
||Heang-Ping Chan, Ph.D.
||University of Michigan
||Heang-Ping Chan Ph.D, Principal Investigator, University of Michigan
History of Changes
|Other Study ID Numbers:
|Study First Received:
||August 7, 2008
||July 25, 2017
Additional relevant MeSH terms:
ClinicalTrials.gov processed this record on August 22, 2017
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