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		<doi>10.1109/SIBGRAPI.2008.33</doi>
		<citationkey>FavrettoBergFalc:2008:FaAuMe</citationkey>
		<title>A Fast and Automatic Method for 3D Rigid Registration of MR Images of the Human Brain</title>
		<format>Printed, On-line.</format>
		<year>2008</year>
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		<author>Favretto, Fernanda Oliveira,</author>
		<author>Bergo, Felipe Paulo Guazzi,</author>
		<author>Falcão, Alexandre Xavier,</author>
		<affiliation>LIV - Instituto de Computação - Unicamp</affiliation>
		<affiliation>LIV - Instituto de Computação - Unicamp</affiliation>
		<affiliation>LIV - Instituto de Computação - Unicamp</affiliation>
		<editor>Jung, Cláudio Rosito,</editor>
		<editor>Walter, Marcelo,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 21 (SIBGRAPI)</conferencename>
		<conferencelocation>Campo Grande, MS, Brazil</conferencelocation>
		<date>12-15 Oct. 2008</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>Registration, Image Processing, Medical Image Analysis.</keywords>
		<abstract>Image registration is an important problem with several applications in Medical Imaging. Intra-subject rigid registration requires a minimal set of parameters to be computed, and is sufficient for organs with no significant movement or deformation, such as the human brain. Rigid registration has also been used as the first step before inter-subject deformable registration. In this paper we present a fast and automatic method for 3D rigid registration of magnetic resonance images of the human brain. The method combines previous approaches for mid-sagittal plane location and brain segmentation with a greedy-search algorithm to find the best match between source and target images. We evaluated the method on 200 image pairs: 100 without structural abnormalities and 100 with artificially created lesions, such that it was possible to quantify the registration errors. The method achieved very accurate registration within a few seconds.</abstract>
		<language>en</language>
		<targetfile>favretto-registration.pdf</targetfile>
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