Evaluation of Digital Mammography Display.

Abstract

During the first two years we have carried out experiments to evaluate adaptive histogram equalization and intensity windowing applied to mammograms. We found statistically significant improvement in detection of speculations with contrast limited adaptive histogram equalization processing, and found statistically significant improvement in detection of both calcification and masses with intensity windowing. We have also looked at intensity window selection methods based on types of tissue, namely dense breast. The purpose of this research is to experimentally determine the diagnostic accuracy and interpretation speed of digitally acquired mammograms displayed on the best available display methods.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1996
Accession Number
ADA322218

Entities

People

  • Etta Pisano

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Breast Cancer
  • Computer Science
  • Contrast
  • Detection
  • Detectors
  • Diagnostic Imaging
  • Digital Data
  • Digital Images
  • Display Systems
  • Equalization
  • Gray Scale
  • Health Services
  • Image Processing
  • Medical Personnel
  • Neoplasms
  • Standards

Fields of Study

  • Medicine
  • Physics

Readers

  • Oncology and Biomarker-Based Cancer Detection.
  • Radio communications and signal processing.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.