Automated Area Beam Equalization Mammography for Improved Imaging of Dense Breasts

Abstract

In mammography, thick or dense breast regions persistently suffer from reduced contrast-to-noise ratio (CNR) because of degraded contrast from large scatter intensities and relatively high noise. Area x-ray beam equalization can improve image quality by increasing the x-ray exposure to underpenetrated regions without increasing the exposure to the breast regions. Optimal equalization parameters with respect to image quality and patient dose were determined through computer simulations and validated with experimental observations on a step phantom and an anthropomorphic breast phantom. Three parameters important in equalization digital mammography were considered: attenuator material (Z = 13-92), beam energy (22-34 kVp) and equalization level. A Mo/Mo digital mammography system was used for image acquisition. A prototype 16 x 16 piston driven equalization system was used for preparing patient-specific equalization masks. Simulation studies showed that a molybdenum attenuator and an equalization level of 20 were optimal for improving contrast, CNR and figure of merit (FOM = CNR2/dose). Experimental measurements using these parameters showed significant improvements in contrast, CNR and FOM. Moreover, equalized images of a breast phantom showed improved image quality. These results indicate that area beam equalization can improve image quality in digital mammography.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2005
Accession Number
ADA449715

Entities

People

  • Sabee Molloi

Organizations

  • University of California, Irvine

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Air Gaps
  • Angiography
  • Brushless Dc Motors
  • Computer Simulations
  • Detection
  • Detectors
  • Dynamic Range
  • Electronic Components
  • Films
  • Filtration
  • Geometry
  • Materials
  • Measurement
  • Quantum Noise
  • Radiography
  • Simulations
  • X Rays

Fields of Study

  • Medicine
  • Physics

Readers

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  • Oncology and Biomarker-Based Cancer Detection.
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