A Method for Simulating Mammograms

Abstract

This project is to facilitate research in digital mammography and related technologies, in particular computer aided diagnosis and image processing. A major limitation to the rapid development and subsequent clinical implementation of these technologies is the lack of a standardized set of mammograms to be used in development and evaluation. We are developing a method to produce simulated mammograms. The method relies on a model of image formation that takes into account the absorption of x-rays in the phosphor, subsequent conversion to light and the scattering of the light before escaping the phosphor. The model also takes into account the finite thickness of the phosphor, the divergence of the x-ray beam, scattered radiation, and noise due to film granularity and from the film digitizer. Almost all the components of the model are completed and computer code is being written. We are now testing the model using x-ray phantoms. We are comparing simulated images created based on a high quality film radiograph to an image acquired using a mammographic screen-film system. The resolution properties of the simulated image closely match that of a real image, but the noise properties differ. We are in the process of determining why there is a difference.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2002
Accession Number
ADA410853

Entities

People

  • Robert Nishikawa

Organizations

  • University of Chicago

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Analog To Digital Converters
  • Biomedical Research
  • Breast Cancer
  • Computer Programs
  • Computer Simulations
  • Computer-Aided Diagnosis
  • Computers
  • Detectors
  • Electronic Mail
  • Image Processing
  • Information Operations
  • Mastectomy
  • Phosphors
  • Simulations
  • Standards
  • Test And Evaluation
  • X Rays

Fields of Study

  • Medicine
  • Physics

Readers

  • Aerospace Test and Evaluation
  • Materials Science and Engineering.
  • Oncology and Biomarker-Based Cancer Detection.