Computer-Aided Diagnosis of Breast Cancer: A Multi-Center Demonstrator

Abstract

The long-term goal of this work is to develop a computer aid for the decision for breast biopsy. in this -project, a database of BIRADS reports of mammographic findings was developed from five institutions. The focus has been to gather data from multiple sites in order to verify and whether the artificial neural network computer aid to the diagnosis of breast cancer can be translated between locations. In all, cases were acquired from Duke University, University of North Carolina, University of Maryland, University of Pennsylvania, and Sloan-Kettering Cancer Center. An cases included biopsy proof of the presence or absence of'-malignancy. in testing between institutions, the computer -aid -was found to -be robust with -little -loss of performance when cases from other institutions were used as reference cases. These results indicate the possibility that a centrally trained computer aid could provide assistance for the decision to biopsy. 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.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2000
Accession Number
ADA389660

Entities

People

  • Carey E. Floyd Jr.

Organizations

  • Duke University Hospital

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Breast Cancer
  • Cancer
  • Computer-Aided Diagnosis
  • Computers
  • Data Sets
  • Databases
  • Diagnostic Imaging
  • Engineering
  • Health Services
  • Image Processing
  • Information Systems
  • Neoplasms
  • Neural Networks
  • North America
  • North Carolina
  • Predictive Modeling

Readers

  • Clinical Trial Research.
  • Medical or Health Care Field.
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML