Filtering False Detections of Small Multiple Sclerosis Lesions using Fuzzy Regional Analysis

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/11501

dc.contributor	Universitat Politècnica de Catalunya. Departament de Matemàtica Aplicada II
dc.contributor	Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.author	Aymerich Martínez, Francisco Javier
dc.contributor.author	Sobrevilla Frisón, Pilar
dc.contributor.author	Montseny Masip, Eduard
dc.contributor.author	Rovira, Àlex
dc.date	2010
dc.identifier.citation	Aymerich, F.X. [et al.]. Filtering False Detections of Small Multiple Sclerosis Lesions using Fuzzy Regional Analysis. A: IEEE International Conference on Fuzzy Systems. "2010 IEEE International Conference on Fuzzy Systems". Barcelona: 2010, p. 1471-1478.
dc.identifier.citation	978-1-4244-6920-8
dc.identifier.uri	http://hdl.handle.net/2117/11501
dc.language.iso	eng
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Àrees temàtiques de la UPC::Ciències de la salut::Medicina::Diagnòstic per la imatge
dc.subject	Àrees temàtiques de la UPC::Ciències de la salut::Medicina
dc.subject	Multiple sclerosis
dc.subject	Esclerosi múltiple -- Diagnòstic
dc.subject	Esclerosi múltiple
dc.title	Filtering False Detections of Small Multiple Sclerosis Lesions using Fuzzy Regional Analysis
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	This paper introduces a method to filter false detections of small multiple sclerosis lesions in magnetic resonance images based on the analysis of regional features. The proposed method considers as starting point the results of an earlier work in which, through the use of fuzzy rules, the image pixels showing hyperintensity were detected. The regional analysis of the results obtained at previous work allows extracting some features with differentiation capability between small multiple sclerosis lesions and false detections. These features are introduced as restrictions for obtaining a new and improved fuzzy membership function associated with the presence of hyperintensity in these images. Results show an important reduction of the number of false detections preserving the small multiple sclerosis lesions previously detected.

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