Digital Mammography: Development of an Advanced Computer-Aided Diagnosis System for Breast Cancer Detection
Abstract
The goal of the project is to develop computer-aided diagnosis (CAD) methods and systems for mammography using advanced computer vision techniques and image information fusion from multiple mammograms to improve lesion detection and characterization. When tally developed, the CAD system can assist radiologists in mammographic interpretation. During this project year, we have performed the following tasks: (1) collected databases of digital mammograms (DMs) and digitized film mammograms (DFMs) for development of the CAD systems, (2) developed computer vision techniques and a prototype CAD system for detection of microcalcifications on DMs, (3) developed computer vision techniques and a prototype CAD system for detection of masses on DFMs and DMs, (4) explored the feasibility of improving mass detection by CAD on digital breast tomosynthesis mammograms, (5) developed automated pectoral muscle detection method for preprocessing of MLO view mammograms for multiple image analysis, (6) developed a prototype CAD method for classification of malignant and benign masses by fusion of information from mammograms and ultrasound images and investigated the effects of the multi-modality CAD system on radiologists performance. In summary, we have investigated a number of areas in CAD of mammographic lesions and evaluated the new techniques for both DMs and DFMs. We have made progress in the six tasks proposed in the project. We have found that our new computer-vision techniques and two-view information fusion approach can improve the performance of the CAD systems. We will continue the development of the CAD systems for DMs and DFMs in the coming years.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 2005
- Accession Number
- ADA443621
Entities
People
- Heang-Ping Chan
Organizations
- University of Michigan