Dynamic Edge Tracing for 2D Image Segmentation

Abstract

A novel segmentation technique which may be useful for two dimensional (2D) magnetic resonance (MR) image segmentation is presented. The technique utilizes a dynamic target tracking algorithm and a Kalman filter and permits edges to be followed in the presence of intensity variation similar to that found in MR images. Segmentation of two synthetic test images, one with intensity nonuniformity and one without, is performed. Fuzzy c-means clustering with pixel intensity features is used to segment the same test images for qualitative comparison.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA412095

Entities

People

  • D. J. Withey
  • W. Pedrycz
  • Z. J. Koles

Organizations

  • University of Alberta

Tags

Communities of Interest

  • Biomedical
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Acquisition
  • Aircrafts
  • Algorithms
  • Automatic
  • Automatic Tracking
  • Biomedical Engineering
  • Change Detection
  • Covariance
  • Data Association
  • Engineering
  • Filters
  • Image Segmentation
  • Kalman Filters
  • Magnetic Resonance
  • Target Tracking
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Physics

Readers

  • Computer Vision.