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
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;
Conference_Titel :
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6919-2
DOI :
10.1109/FUZZY.2010.5584178