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		<doi>10.1109/SIBGRA.2004.1352937</doi>
		<citationkey>CamapumSilFreBasFre:2004:SeClSt</citationkey>
		<title>Segmentation of Clinical Structures from Images of the Human Pelvic Area</title>
		<format>On-line</format>
		<year>2004</year>
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		<size>602 KiB</size>
		<author>Camapum, Juliana Fernandes,</author>
		<author>Silva, Alzenir O.,</author>
		<author>Freitas, Alan N.,</author>
		<author>Bassani, Hansenclever de F.,</author>
		<author>Freitas, Flávia Mendes O.,</author>
		<affiliation>Universidade de Brasília, Departamento de Engenharia Elétrica,</affiliation>
		<editor>Albuquerque, Ara?Arnaldo de,</editor>
		<editor>Comba, Jo?Luiz Dihl,</editor>
		<editor>Navazo, Isabel,</editor>
		<editor>Sousa, Ant? Augusto de,</editor>
		<e-mailaddress>juliana@ene.unb.br</e-mailaddress>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 17 (SIBGRAPI) - Ibero-American Symposium on Computer Graphics, 2 (SIACG)</conferencename>
		<conferencelocation>Curitiba, PR, Brazil</conferencelocation>
		<date>17-20 Oct. 2004</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>segmentation, watershed transform, medical image.</keywords>
		<abstract>The radiotherapy treatment planning requires the delineation of the therapy structures that will be submitted to the radiation beams. When executed manually, this delineation is a slow process and can result in human errors due to the amount of X-ray Computed Tomography (CT) images that are analyzed in each radiotherapy planning. This process needs precision, minimizing the radiation on healthy areas, close to the target tissues. A new system for automatic segmentation of images of clinical structures is proposed in this work. The algorithm is based on multi-region growing followed by watershed transform. The main contributions are the method of seed pixels selection and predicate of the multi-region growing algorithm and the segmentation results achieved. The system was tested in 400 images and its efficiency was measured by two different statistical methods, correlation and the t-test. The clinical structures of interest are the rectum, bladder and seminal vesicles.</abstract>
		<language>en</language>
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