Fuzzy approach to grade gliomas using susceptibility-weighted images. A preliminary study

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/131137

dc.contributor	Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor	Universitat Politècnica de Catalunya. BIOART - BIOsignal Analysis for Rehabilitation and Therapy
dc.contributor.author	Aymerich Martínez, Francisco Javier
dc.contributor.author	Auger, Cristina
dc.contributor.author	García, Julio
dc.contributor.author	Martínez Sáez, Elena
dc.contributor.author	Martínez Ricarte, Francisco
dc.contributor.author	Corral, Juan Francisco
dc.contributor.author	Rovira, Alex
dc.date	2018
dc.identifier.citation	Aymerich, F.X. [et al.]. Fuzzy approach to grade gliomas using susceptibility-weighted images. A preliminary study. A: IEEE World Congress on Computational Intelligence. "2018 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2018: Rio de Janeiro, Brazil, July 8-13, 2018". Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1-6.
dc.identifier.citation	978-1-5090-6020-7
dc.identifier.citation	10.1109/FUZZ-IEEE.2018.8491475
dc.identifier.uri	http://hdl.handle.net/2117/131137
dc.language.iso	eng
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation	https://ieeexplore.ieee.org/document/8491475
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Ciències de la salut
dc.subject	Magnetic resonance imaging
dc.subject	Diagnostic imaging
dc.subject	Imatgeria per ressonància magnètica
dc.subject	Tumors -- Diagnòstic
dc.subject	Imatgeria per al diagnòstic
dc.title	Fuzzy approach to grade gliomas using susceptibility-weighted images. A preliminary study
dc.type	info:eu-repo/semantics/submittedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	This paper describes a method to grade gliomas examined by magnetic resonance imaging. It is a preliminary study focused only on the features extracted from susceptibility-weighted images. The proposed method involves fusion of classifiers based on decision trees designed using fuzzy techniques. The favorable results indicate that the fuzzy approach may be of particular value for grading gliomas.

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