Title
Comparison and Evaluation of Segmentation Techniques for Subcortical Structures in Brain MRI
Abstract
The automation of segmentation of medical images is an active research area. However, there has been criticism of the standard of evaluation of methods. We have comprehensively evaluated four novel methods of automatically segmenting subcortical structures using volumetric, spatial overlap and distance-based measures. Two of the methods are atlas-based --- classifier fusion and labelling (CFL) and expectation-maximisation segmentation using a dynamic brain atlas (EMS), and two model-based --- profile active appearance models (PAM) and Bayesian appearance models (BAM). Each method was applied to the segmentation of 18 subcortical structures in 270 subjects from a diverse pool varying in age, disease, sex and image acquisition parameters. Our results showed that all four methods perform on par with recently published methods. CFL performed significantly better than the other three methods according to all three classes of metrics.
Year
DOI
Venue
2008
10.1007/978-3-540-85988-8_49
MICCAI
Keywords
Field
DocType
active appearance model
Classifier fusion,Computer vision,Brain atlas,Scale-space segmentation,Brain mri,Pattern recognition,Segmentation,Computer science,Active appearance model,Artificial intelligence,Bayesian probability
Conference
Volume
Issue
ISSN
11
Pt 1
0302-9743
Citations 
PageRank 
References 
24
1.47
5
Authors
10
Name
Order
Citations
PageRank
Kolawole O. Babalola1745.06
Brian Patenaude248824.18
paul aljabar3118171.30
Julia A Schnabel41978151.49
David N. Kennedy5241.47
William R Crum644832.49
Stephen M. Smith7241.47
Timothy F. Cootes84358579.15
Mark Jenkinson93676225.91
Daniel Rueckert109338637.58