Enhancement of breast CADx with unlabeled dataa)

Abstract

Unlabeled medical image data are abundant, yet the process of converting them into a labeled (“truth‐known”) database is time and resource expensive and fraught with ethical and logistics issues. The authors propose a dual‐stage CADx scheme in which both labeled and unlabeled (truth‐known and “truth‐unknown”) data are used. This study is an initial exploration of the potential for leveraging unlabeled data toward enhancing breast CADx.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 20, 2010
Source ID
10.1118/1.3455704

Entities

People

  • Andrew R. Jamieson
  • Karen Drukker
  • Lorenzo L. Pesce
  • Maryellen Lissak Giger

Organizations

  • National Institutes of Health
  • United States Army Medical Research and Development Command
  • United States Department of Defense
  • United States Department of Energy

Tags

Fields of Study

  • Computer science

Readers

  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Graph Algorithms and Convex Optimization.
  • Systems Analysis and Design