Computer-Aided Diagnosis of Digital Mammograms

Abstract

The long-term goal of our research is to develop computer-aided diagnosis (CAD) techniques for improving the detection and diagnosis of breast cancer. The hypothesis to be tested in the present project is that radiologists' ability to differentiate malignant from benign breast lesions can be improved by integrating radiologists' perceptual expertise in the interpretation of mammograms with the advantages of automated computer classification. This project has 3 objectives: To combine radiologist-extracted Breast Imaging Reporting and Data System (BI-RADS) features with image features extracted by a computer to classify malignant and benign clustered microcalcifications in mammograms. To optimally combine radiologists' diagnosis with the result of computer classification. To optimize computer classification for full-field digital mammograms.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2001
Accession Number
ADA396624

Entities

People

  • Yulei Jiang

Organizations

  • University of Chicago

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Breast Cancer
  • Computational Science
  • Computer-Aided Diagnosis
  • Computers
  • Data Processing
  • Data Science
  • Data Sets
  • Databases
  • Detection
  • Detectors
  • Diagnostic Imaging
  • Equations
  • Experimental Design
  • Feature Extraction
  • Information Processing
  • Information Science
  • Knowledge Management

Fields of Study

  • Medicine
  • Physics

Readers

  • Computer Vision.
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML