Automated Spot Mammography for Improved Imaging of Dense Breasts

Abstract

We are developing an automated stereo spot mammography technique to improve imaging of lesions within dense breast tissue. During the third year of this project, our work was devoted primarily to developing: 1) software for an improved observer study to compare regions in mammograms that are selected by radiologists and the computer for spot imaging; and 2) software and hardware to implement the automated spot collimation component of the auto stereo spot technique. Based on radiologists' evaluations of the software used in our observer study performed during the second year of this project, we wrote new algorithms to display digitized mammograms at 200 micrometers and 400 micrometers resolution, which are 4 and 2 x better resolution than the 800 micrometers resolution employed previously. The new programs also allowed the radiologists to trace regions for spot imaging at either or both of these resolutions. In addition, we applied our CAD group's analysis techniques to the images so we could compare the regions selected by the computer with those selected by the radiologists. The spot collimation hardware was built and software was written to select spot regions and automatically move the collimator blades to restrict the x-ray beam to those regions. A phantom study was performed to verify proper auto-spot collimation.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2002
Accession Number
ADA410675

Entities

People

  • Mitchell M. Goodsitt

Organizations

  • University of Michigan

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Biomedical Research
  • Collimators
  • Computer Programs
  • Computers
  • Detection
  • Detectors
  • Diagnostic Imaging
  • Health Services
  • Imaging Techniques
  • Mammography
  • Medical Personnel
  • Three Dimensional
  • Tomography
  • Visualizations
  • X Rays

Fields of Study

  • Medicine
  • Physics

Readers

  • Image Processing and Computer Vision.
  • Oncology and Biomarker-Based Cancer Detection.
  • Systems Analysis and Design