Single-Pulse Dual-Energy Mammography Using a Binary Screen Coupled to Dual CCD Cameras

Abstract

Mammographic screening for breast cancer currently represents a women's best chance for surviving breast cancer. Nevertheless, for women with dense breasts, mammography by itself may not be as efficient as other imaging strategies. Dual energy mammography is a technique in which the complicated structure of the normal, dense breast can be eliminated mathematically in the image, thereby highlighting the remaining microcalcification structures that may be present and are early tell-tale signs of possible breast cancer. This grant focused on optimizing (maximizing image quality while minimizing radiation dose) the dual energy mammography technique using computer simulation and "Monte Carlo" techniques. In addition, a dual energy mammography system was built and its performance was measured. The research identified the best x-ray spectra that should be used for dual energy mammography acquisition. The research also indicated that single pulse, dual detector dual energy acquisition should be avoided, and rather dual x-ray pulse (switched kVp) approaches using a single detector should be used. Several databases were produced by this effort. These tools, which include a comprehensive attenuation coefficient library, four spectral models, and tables for generating breast dose, should be useful for other investigators seeking to further improve the sensitivity of mammography screening.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1999
Accession Number
ADA376128

Entities

People

  • John M. Boone

Organizations

  • University of California

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computational Science
  • Computer Programs
  • Computers
  • Databases
  • Detection
  • Detectors
  • Diagnostic Imaging
  • Diffraction
  • Digital Images
  • Electronic Mail
  • Health Services
  • Information Science
  • Measurement
  • Medical Personnel
  • Monte Carlo Method
  • Optics
  • Radiography

Fields of Study

  • Medicine
  • Physics

Readers

  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.
  • Oncology and Biomarker-Based Cancer Detection.