The CAD Method for Microcalcification Detection: Independent of Sensor and Resolution
Annual summary rept. 1 Jul 2001-30 Jun 2002
UNIVERSITY OF SOUTH FLORIDA TAMPA
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The aims of this work are to explore the feasibility of developing a new class of computer assisted diagnostic CAD methods for microcalification cluster MCC detection for breast cancer screening using digital mammography. The objectives are to achieve a improved CAD performance that is significantly more robust for large image databases, and b an adaptive CAD method that is independent of the digital sensor resolution and gray scale characteristics for the first time. This report includes 3 sections, I. Summary of the work in first year, which includes data base collection and truth file establishment for different sensors, preprocessing for breast area segmentation, and basic algorithm design and optimization, 2 Summary of the work in second year, which includes algorithm design and modular optimization for enhancement, segmentation, feature extraction and classification. 3. Whole system optimization and evaluation, which includes a design, optimization and evaluation of a successful MCCs detection system.
- Medicine and Medical Research