DocumentCode :
2304696
Title :
A new fuzzy approach to brain tumor segmentation
Author :
Gordillo, Nelly ; Montseny, Eduard ; Sobrevilla, Pilar
Author_Institution :
Dept of Autom. Control (ESAII), Univ. Politec. de Catalunya, Barcelona, Spain
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
In this paper we present a fully automatic and unsupervised brain tumor segmentation method which considers human knowledge. The expert knowledge and the features derived from the MR images are coupled to define heuristic rules aimed to the design of the fuzzy approach. To assess the unsupervised and fully automatic segmentation, intensity-based objective measures are defined, and a new method for obtaining membership functions to suit the MRI data is introduced. The proposed approach is quantitatively comparable to the most accurate existing methods, even though the segmentation is done in 2D.
Keywords :
biomedical MRI; expert systems; fuzzy set theory; image segmentation; medical image processing; tumours; MR images; brain tumor segmentation; expert knowledge; fuzzy approach; human knowledge; membership functions; Feature extraction; Histograms; Image segmentation; Magnetic resonance imaging; Pixel; Skull; Tumors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location :
Barcelona
ISSN :
1098-7584
Print_ISBN :
978-1-4244-6919-2
Type :
conf
DOI :
10.1109/FUZZY.2010.5584178
Filename :
5584178
Link To Document :
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