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		<isbn>85-244-0103-6</isbn>
		<citationkey>MascarenhasSantCruv:1996:UsMAEs</citationkey>
		<title>The use of MAP estimation techniques in the tomographic reconstruction of Poisson noise corrupted images</title>
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		<year>1996</year>
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		<author>Mascarenhas, Nelson Delfino d'Ávila,</author>
		<author>Santos, Saulo Savio Leite,</author>
		<author>Cruvinel, Paulo Estevão,</author>
		<editor>Velho, Luiz,</editor>
		<editor>Albuquerque, Arnaldo de,</editor>
		<editor>Lotufo, Roberto A.,</editor>
		<conferencename>Simpósio Brasileiro de Computação Gráfica e Processamento de Imagens, 9 (SIBGRAPI)</conferencename>
		<conferencelocation>Caxambu, MG, Brazil</conferencelocation>
		<date>29 Oct.-1 Nov. 1996</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<pages>197-204</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>Artigo</tertiarytype>
		<organization>SBC - Sociedade Brasileira de Computação; UFMG - Universidade Federal de Minas Gerais</organization>
		<transferableflag>1</transferableflag>
		<abstract>This work presents new methods for the tomographic reconstruction of images with Poisson noise corrupted projections. The reconstruction method is performed by first filtering the noisy projections under the Maximum a Posteriori criterion and subsequently reconstructing the images through conventional filtering-backprojection methods using the ramp filter. The "a priori" knowledge is incorporated by using several densities, including the Gaussian and densities defined on the non-negative real line. These densities were used to denote the fact that the rates of counting on the projections are non-negative quantities. Experimental results, both simulated and real, indicate that, by using the MAP criterion, it is possible to obtain better performance, as compared to conventional methods of reconstruction, with a very small increase in computational effort.</abstract>
		<type>Aplicações em Medicina</type>
		<language>en</language>
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