DocumentCode :
3212656
Title :
A PSO based method for detection of brain tumors from MRI
Author :
Chandra, Satish ; Bhat, Rajesh ; Singh, Harinder
Author_Institution :
Dept. of CSE&IT, Jaypee Univ. of IT, Waknaghat, India
fYear :
2009
fDate :
9-11 Dec. 2009
Firstpage :
666
Lastpage :
671
Abstract :
Detection of brain tumors from MRI is a time consuming and error-prone task. This is due to the diversity in shape, size and appearance of the tumors. In this paper, we propose a clustering algorithm based on Particle Swarm Optimization (PSO). The algorithm finds the centroids of number of clusters, where each cluster groups together brain tumor patterns, obtained from MR Images. The results obtained for three performance measures are compared with those obtained from Support Vector Machine (SVM) and Ada Boost. The performance analysis shows that qualitative results obtained from the proposed model are comparable with those obtained by SVM. However, to obtain better results from the proposed algorithm we need to carefully select the different values of PSO control parameters.
Keywords :
biomedical MRI; brain; medical image processing; particle swarm optimisation; pattern clustering; support vector machines; tumours; Ada Boost; biomedical MRI; brain tumor detection; brain tumor patterns; centroids; clustering algorithm; particle swarm optimization; support vector machine; Biomedical imaging; Clustering algorithms; Image edge detection; Image segmentation; Magnetic resonance imaging; Medical diagnostic imaging; Neoplasms; Particle swarm optimization; Shape; Support vector machines; AdaBoost; Clustering; MRI; Partcle Swarm Optimization; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4244-5053-4
Type :
conf
DOI :
10.1109/NABIC.2009.5393455
Filename :
5393455
Link To Document :
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