<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Conference Proceedings">
		<site>sibgrapi.sid.inpe.br 802</site>
		<holdercode>{ibi 8JMKD3MGPEW34M/46T9EHH}</holdercode>
		<identifier>8JMKD3MGPBW4/35TE3AS</identifier>
		<repository>sid.inpe.br/sibgrapi@80/2009/08.25.18.40</repository>
		<lastupdate>2009:08.25.18.40.08 sid.inpe.br/banon/2001/03.30.15.38 administrator</lastupdate>
		<metadatarepository>sid.inpe.br/sibgrapi@80/2009/08.25.18.40.10</metadatarepository>
		<metadatalastupdate>2022:07.30.04.22.22 sid.inpe.br/banon/2001/03.30.15.38 administrator {D 2009}</metadatalastupdate>
		<doi>10.1109/SIBGRAPI.2009.41</doi>
		<citationkey>LaraMenoFariAraú:2009:SeMeSe</citationkey>
		<title>A Semi-Automatic Method for Segmentation of the Coronary Artery Tree from Angiography</title>
		<format>Printed, On-line.</format>
		<year>2009</year>
		<numberoffiles>1</numberoffiles>
		<size>5437 KiB</size>
		<author>Lara, Daniel S. D.,</author>
		<author>Menotti, David,</author>
		<author>Faria, Alexandre W. C.,</author>
		<author>Araújo, Arnaldo de Albuquerque,</author>
		<editor>Nonato, Luis Gustavo,</editor>
		<editor>Scharcanski, Jacob,</editor>
		<e-mailaddress>daniel_diogo@hotmail.com</e-mailaddress>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 22 (SIBGRAPI)</conferencename>
		<conferencelocation>Rio de Janeiro, RJ, Brazil</conferencelocation>
		<date>11-14 Oct. 2009</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>Image Segmentation, Coronary Artery Tree, Angiography.</keywords>
		<abstract>Nowadays, medical diagnostics using images has a considerable importance in many areas of  medicine.  It promotes and makes easier the acquisition,  transmission and analysis of medical images. The  use of digital images for diseases evaluations or  diagnostics is still growing up and new application modalities are always appearing. This paper presents  a methodology for a  semi-automatic segmentation of the coronary artery tree in 2D X-Ray  angiographies. It combines a region growing  algorithm and a differential geometry approach. The  proposed segmentation method identifies about 90% of the main coronary artery tree.</abstract>
		<language>en</language>
		<targetfile>2009-sibgrapi-angio_submitted.pdf</targetfile>
		<usergroup>daniel_diogo@hotmail.com</usergroup>
		<visibility>shown</visibility>
		<mirrorrepository>sid.inpe.br/banon/2001/03.30.15.38.24</mirrorrepository>
		<nexthigherunit>8JMKD3MGPEW34M/46SJQ2S</nexthigherunit>
		<nexthigherunit>8JMKD3MGPEW34M/4742MCS</nexthigherunit>
		<citingitemlist>sid.inpe.br/sibgrapi/2022/05.14.19.43 3</citingitemlist>
		<hostcollection>sid.inpe.br/banon/2001/03.30.15.38</hostcollection>
		<lasthostcollection>sid.inpe.br/banon/2001/03.30.15.38</lasthostcollection>
		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/sibgrapi@80/2009/08.25.18.40</url>
	</metadata>
</metadatalist>