Segmentation of the Striatum Using Data Fusion

Abstract

This article proposes a new segmentation scheme to detect cerebral structures in MRI acquisitions using numerical information contained in the image and expert knowledge brought by a specialist. This process is divided in three steps: first, information contained in the MR image is extracted using a fuzzy clustering algorithm, and theoretical information concerning the structure to segment is modeled using possibility theory. Information fusion is then processed, followed by a decision step ending the structure segmentation. Heads of caudate nuclei and putamens are segmented using this method. Results are promising and validation is performed using both numerical indexes and assessment by an expert. This method can be applied to any cerebral structure in an MR image, provided that it can be described in terms of shape, direction and distance by an expert and that the contrast and resolution of the MRI are sufficient.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA411838

Entities

People

  • Emmanuelle Frenoux
  • Jean-yves Boire
  • Vincent Barra

Organizations

  • University of Auvergne - Clermont I

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Algorithms
  • Automatic
  • Brain
  • Classification
  • Computer Vision
  • Data Fusion
  • Detection
  • Diagnostic Imaging
  • Diseases And Disorders
  • Fuzzy Sets
  • Image Processing
  • Language
  • Microarchitecture
  • Parkinson'S Disease
  • Segmented

Readers

  • Computer Vision.
  • Library and Information Science/ Studies, Southeast Asia Studies, Bibliography of Vietnam and Lao Studies.
  • Neuroscience