Title
Atlas-based segmentation of brain MR images using least square support vector machines
Abstract
This study presents an automatic model based technique for brain tissue segmentation from cerebral magnetic resonance (MR) images. In this paper, support vector machine (SVM) based classifier, as a new and powerful kind of supervised machine learning with high generalization characteristics, is employed. Here, least-square SVM (LS-SVM) in conjunction with brain probabilistic atlas as a priori information is applied to obtain class probabilities for three tissues of cerebrospinal fluid (CSF), white matter (WM) and grey matter (GM). The entire process of brain segmentation is performed in an iterative procedure, so that the probabilistic maps of brain tissues will be updated at any iteration. The quantitative and qualitative results indicate excellent performance of the applied method.
Year
DOI
Venue
2010
10.1109/IPTA.2010.5586779
IPTA
Keywords
Field
DocType
brain tissue segmentation,atlas,white matter,learning (artificial intelligence),magnetic resonance imaging (mri),automatic model based technique,brain mr image,least squares approximations,least square support vector machine (ls-svm),cerebrospinal fluid,biomedical mri,cerebral magnetic resonance,automated segmentation,brain,supervised machine learning,support vector machine (svm),least square support vector machine,grey matter,support vector machines,atlas based segmentation,support vector machine,magnetic resonance,least square,biomedical imaging,image segmentation,probabilistic logic,least squares support vector machine,magnetic resonance image,learning artificial intelligence,magnetic resonance imaging
Brain segmentation,Computer vision,Pattern recognition,Computer science,Medical imaging,Segmentation,A priori and a posteriori,Support vector machine,Image segmentation,Artificial intelligence,Probabilistic logic,Classifier (linguistics)
Conference
ISSN
ISBN
Citations 
2154-5111
978-1-4244-7247-5
4
PageRank 
References 
Authors
0.45
4
4
Name
Order
Citations
PageRank
Keyvan Kasiri140.45
Kamran Kazemi28112.24
Mohammad Javad Dehghani3234.69
Mohammad Sadegh Helfroush47011.30