Segmentation of MR Image Based on Maximum A Posterior

Abstract

Brain MR image segmentation takes an important role in research and clinical application. Statistical method is effective in the segmentation, which is usually based on maximum a posterior (MAP). The key of MAP method is to estimate a prior probability of the segmentation. Multilevel logistic (MLL) model has been used in practice for the estimation. To farther improve the performance of the segmentation, a weighted MLL (WMLL) model is proposed in this paper. The simulated results show that the WMLL model is effective.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA412374

Entities

People

  • Fangli Liu
  • Si Gao
  • Xiangyu Gao

Organizations

  • Tsinghua University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Biomedical Engineering
  • Classification
  • Computations
  • Computer Vision
  • Electrical Engineering
  • Engineering
  • Gaussian Noise
  • Gaussian Processes
  • Genetic Algorithms
  • Image Segmentation
  • Intensity
  • Noise
  • Probability
  • Probability Distributions
  • Random Variables

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Computer Vision.
  • Military/Explosive Ordnance Disposal (EOD) Technology