Automatic Segmentation of the Encephalic Parenchyma Using Fuzzy Techniques

Abstract

This work shows an automatic, fast and reproducible algorithm to segment the encephalic parenchyma in magnetic resonance (MR) images. The algorithm has been implemented following a rule-based schema in which a fuzzy analysis of MR images information has been introduced to deal with the vagueness associated to the images. The obtention of a fuzzy result helps to determine the accuracy of the classification. The evaluation of the results is based on the use of quality indexes, which allow the comparison with previous works.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA412491

Entities

People

  • A. Rovira
  • E. Montseny
  • F. X. Aymerich
  • J. Gili
  • P. Sobrevilla

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Arachnoid
  • Automatic
  • Brain
  • Central Nervous System
  • Classification
  • Computer Vision
  • Fuzzy Sets
  • Magnetic Resonance
  • Magnetic Resonance Imaging
  • Nervous System
  • Numbers
  • Probability
  • Probability Density Functions
  • Reproducibility
  • Test Sets
  • Visual Inspection

Readers

  • Artificial Intelligence
  • Computer Vision.
  • Systems Analysis and Design