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		<citationkey>RebouçasOlivMarqRebo:2016:StDeTh</citationkey>
		<title>Stroke detection through a nonparametric estimation-based level set approach based on the Parzen windows</title>
		<format>On-line</format>
		<year>2016</year>
		<numberoffiles>1</numberoffiles>
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		<author>Rebouças, Elizângela de S.,</author>
		<author>Oliveira, Saulo A. F.,</author>
		<author>Marques, Regis C. P.,</author>
		<author>Rebouças Filho, Pedro P.,</author>
		<affiliation>Instituto Federal de Educação, Ciência e Tecnologia do Ceará</affiliation>
		<affiliation>Instituto Federal de Educação, Ciência e Tecnologia do Ceará</affiliation>
		<affiliation>Instituto Federal de Educação, Ciência e Tecnologia do Ceará</affiliation>
		<affiliation>Instituto Federal de Educação, Ciência e Tecnologia do Ceará</affiliation>
		<editor>Aliaga, Daniel G.,</editor>
		<editor>Davis, Larry S.,</editor>
		<editor>Farias, Ricardo C.,</editor>
		<editor>Fernandes, Leandro A. F.,</editor>
		<editor>Gibson, Stuart J.,</editor>
		<editor>Giraldi, Gilson A.,</editor>
		<editor>Gois, João Paulo,</editor>
		<editor>Maciel, Anderson,</editor>
		<editor>Menotti, David,</editor>
		<editor>Miranda, Paulo A. V.,</editor>
		<editor>Musse, Soraia,</editor>
		<editor>Namikawa, Laercio,</editor>
		<editor>Pamplona, Mauricio,</editor>
		<editor>Papa, João Paulo,</editor>
		<editor>Santos, Jefersson dos,</editor>
		<editor>Schwartz, William Robson,</editor>
		<editor>Thomaz, Carlos E.,</editor>
		<e-mailaddress>pedrosarf@ifce.edu.br</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)</conferencename>
		<conferencelocation>São José dos Campos, SP, Brazil</conferencelocation>
		<date>4-7 Oct. 2016</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Work in Progress</tertiarytype>
		<transferableflag>1</transferableflag>
		<keywords>Medical imaging, stroke, level set, parzen-window.</keywords>
		<abstract>This paper aims to aid stroke medical diagnosis through medical images of the brain. We propose a new approach to segment stroke brain Computerized Tomography (CT) images. The proposed approach uses level set method based on the nonparametric estimation approach via parzen-window. Besides this, by optimizing the criterion function, an optimal global threshold is obtained. The results demonstrated the success of the proposed method, when it was compared with the level set algorithm based on the coherent propagation method, using a ground truth built by a specialist. The results obtained show that the proposed method is better than the method based on coherent propagation. This method is a promising approach to be used in clinical routine diagnosis, since it requires less than 2 seconds for the analysis using a personal computer.</abstract>
		<language>en</language>
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		<usergroup>pedrosarf@ifce.edu.br</usergroup>
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