Computer Aided Breast Cancer Diagnosis
Abstract
The long term goal of this work is to develop a computer aid for the decision for breast biopsy. In this project, an artificial neural network was developed to predict the outcome of biopsy from the mammographic features described in the BIRADS lexicon. The focus has been to optimize the performance of the artificial neural network as well as to investigate alternate decision models. Cases were acquired from Duke University, and all cases included biopsy proof of the presence or absence of malignancy. In testing, the computer aid was found to be able to reduce the number of benign lesions that would be biopsied by 40% while missing 2% of the malignancies. Several alternative classifier designs were found to be offer promise as well. The deployment of this system into regional care facilities and into private mammography practices could facilitate transferring the expertise currently present in only a few tertiary care centers to the public at large and to smaller and more rural settings and thus improve access for under-served populations.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2000
- Accession Number
- ADA388926
Entities
People
- Carey E. Floyd
Organizations
- Duke University Hospital