Mammogram Screening by Automated Followup: A Feasibility Study

Abstract

This report addresses the problem of image registration in eases where pixel-to-pixel correspondence can't be established. Specifically, the interest is in images containing 3-D elastic and nonstructured objects whose appearance varies with acquisition parameters. The work is motivated by the problem of mammogram screening based on comparison between mammograms of the same patient acquired in different screenings. Misregistration between temporally spaced screenings arises from minor differences in 3-D positioning and compression, as well as, normal changes in tissue that are function of time. The objective is to identify corresponding regions in two images, similarly to what is done by medical experts. The locations of the regions are determined based on the locations of identifiable landmark points, and each corresponding region's extent is determined by characteristics of the older mammogram. An image pair is covered with overlapping circular regions without gaps and the proposed algorithm provides for further splitting of larger regions. In order to gain an insight into the problem of mammogram misregistration, the work has been extended into problem of mammogram simulation. The developed simulation algorithms encompass the problems of modeling breast tissue, compression and X- ray image acquisition.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2000
Accession Number
ADA406200

Entities

People

  • Dragana Brzakovi

Organizations

  • Lehigh University

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Acquisition
  • Adipose Tissue
  • Algorithms
  • Compression
  • Computer Science
  • Connective Tissue
  • Detection
  • Digital Images
  • Elastic Properties
  • Geometry
  • Image Processing
  • Image Registration
  • Shape
  • Simulations
  • Three Dimensional
  • Two Dimensional
  • X Rays

Fields of Study

  • Medicine
  • Physics

Readers

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

Technology Areas

  • Space
  • Space - Space Objects