Digital Mammography: Computer-Aided Breast Cancer Diagnosis
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.
Allocation: Non-Randomized, Intervention Model: Single Group Assignment, Masking: Open Label, Primary Purpose: Diagnostic
Using computer aided programs to assist in detection and characterization of breast lesions in digital mammography.
Research scan will be completed at the time of scheduled clinical visit.
Heang-Ping Chan, Ph.D.
University of Michigan
United States: Institutional Review Board
|University of Michigan Health System||Ann Arbor, Michigan|