Automatic Exposure Control Device for Digital Mammography

Abstract

The broad, long-term objective of this IDEA proposal is to achieve optimized image quality for DM within acceptable limits of radiation exposure by developing innovative approaches for controlling DM exposures. These approaches entail using the digital detector and an artificial neural network to control mammographic exposures. This project's specific aims are: (1) to use short, low dose pre-exposures of the breast to create "intelligent" regions of interest that determine the exposure parameters for the fully exposed image; and (2) to use an artificial neural network to select exposure parameters (mAs, kVp, and beam filtration) based on "intelligent decisions" that optimize signal-to-noise (SNR) as a function of mean glandular dose.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2001
Accession Number
ADA403655

Entities

People

  • Laurie L. Fajardo

Organizations

  • Johns Hopkins University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Automatic
  • Carcinoma
  • Data Acquisition
  • Detectors
  • Figure Of Merit
  • Filtration
  • Mammography
  • Materials
  • Neural Networks
  • North America
  • Power Spectra
  • Radiation
  • Spectra
  • Square Roots
  • Three Dimensional
  • X Rays

Fields of Study

  • Physics

Readers

  • Distributed Systems and Data Platform Development
  • Image Processing and Computer Vision.
  • Toxicology/Environmental Toxicology

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks