Title
Unsupervised algorithm for the segmentation of three-dimensional magnetic resonance brain images
Abstract
This paper presents a multiple resolution algorithm for the segmentation of three-dimensional magnetic resonance (MR) images. The algorithm consists in the unsupervised segmentation of the MR volume into regions of different statistical behavior. Firstly, an unsupervised merging algorithm estimates a block segmentation of the volume while determining the region number and the parameters of those regions This estimation is computed by minimizing a global information criterion Next, the small regions are eliminated using statistic criteria Finally, the segmentation is performed using the neighboring relationships between voxels via Hidden Markov Random Fields and a Multiple Resolution Iterated Conditional Mode algorithm. Some results on volumetric brain MR images are presented and discuted.
Year
DOI
Venue
2001
10.1109/ICIP.2001.958306
ICIP
Keywords
Field
DocType
Markov processes,biomedical MRI,brain,image resolution,image segmentation,iterative methods,medical image processing,minimisation,random processes,unsupervised learning,3D magnetic resonance brain images,MR volume,MRI,block segmentation,global information criterion minimization,hidden Markov random fields,image segmentation,multiple resolution algorithm,multiple resolution iterated conditional mode algorithm,region number,region parameters estimation,statistic criteria,statistical behavior,unsupervised algorithm,unsupervised merging algorithm,unsupervised segmentation,volumetric brain MR images,voxels
Voxel,Scale-space segmentation,Computer science,Segmentation-based object categorization,Image segmentation,Unsupervised learning,Artificial intelligence,Computer vision,Pattern recognition,Segmentation,Algorithm,Hidden Markov model,Image resolution
Conference
Volume
Citations 
PageRank 
3
0
0.34
References 
Authors
2
4
Name
Order
Citations
PageRank
Anne-Sophie Capelle-Laize1193.63
Olivier Alata211819.81
Christine Fernandez-Maloigne317035.22
J. C. Ferrie430.85