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Context-dependent enhancements for radiological images

  • B. Plessis
  • M. Goldberg
  • R. Dillon
  • J. Tombaugh
  • J. Robertson
  • G. Bélanger
  • N. Hickey
Article

Abstract

Many techniques have been proposed to enhance radiographic images and each of them may be optimal depending upon the circumstances. However, the problem confronting the radiologist or the physician is which enhancement to use and how to select the parameters when a specific feature is to be emphasized. At the University of Ottawa, our research work is oriented towards automatic context-dependent enhancements. Our approach attempts to match the three phases involved in viewing a radiograph: getting a global impression, analyzing the objects and the local features, and focusing on the image perturbations. In this article, we report on enhancements to support the first two phases in the case of chest radiographs and on the applicability of gray level reversal transformtions.

Keywords

Reverse Mode Lung Field Baseline Image Adaptive Histogram Equalization Telecommunication Research Institute 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© W.B. Saunders Company 1989

Authors and Affiliations

  • B. Plessis
    • 3
    • 1
    • 2
  • M. Goldberg
    • 3
    • 1
    • 2
  • R. Dillon
    • 3
    • 1
    • 2
  • J. Tombaugh
    • 3
    • 1
    • 2
  • J. Robertson
    • 3
    • 1
    • 2
  • G. Bélanger
    • 3
    • 1
    • 2
  • N. Hickey
    • 3
    • 1
    • 2
  1. 1.Department of PsychologyCarleton UniversityCanada
  2. 2.Department of Radiological SciencesOttawa Civic HospitalCanada
  3. 3.Telecommunications Research Institute of OntarioUniversity of Ottawa Medical Communication Research CentreOttawaCanada

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