Computer Aided Breast Cancer Diagnosis.
Abstract
The long range goal of this project is to improve the accuracy and consistency of breast cancer diagnosis by developing a Computer Aided Diagnosis (CAD) system for early prediction of breast cancer from the patients' mammographic findings and medical history. In the third year of this project, we have acquired 200 new cases bring our total case database to over 700. We have further investigated an alternative network architecture for predicting malignancy: (1) a genetic algorithm. A user interface was further developed for more efficient data entry and error checking was employed. The existing mammography data entry database was evaluated for use in the prediction system. These developments were targeted at the first specific aim of the grant: (2) develop an artificial neural network to predict biopsy outcome from mammographic and history findings. In the fourth year, we will focus on the second specific aim: and (3) evaluate the improvement in radiologists' diagnostic performance when the computer diagnostic aid is provided. This implementation of an accurate CAD system will improve sensitivity, specificity, and consistency of breast cancer diagnosis and will provide a significant improvement in long term outcome for breast cancer patients.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 1997
- Accession Number
- ADA346548
Entities
People
- Carey E. Floyd
Organizations
- Duke University Hospital