<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Judit Kanyó</style></author><author><style face="normal" font="default" size="100%">Eörs Máté</style></author><author><style face="normal" font="default" size="100%">Géza Makay</style></author><author><style face="normal" font="default" size="100%">Emese Balogh</style></author><author><style face="normal" font="default" size="100%">Márta Fidrich</style></author><author><style face="normal" font="default" size="100%">Attila Kuba</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Dmitrij Chetverikov</style></author><author><style face="normal" font="default" size="100%">László Czúni</style></author><author><style face="normal" font="default" size="100%">Markus Vincze</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Method for Automatically Segmenting the Spinal Cord and Canal from 3D CT Images</style></title><secondary-title><style face="normal" font="default" size="100%">Joint Hungarian-Austrian conference on image processing and pattern recognition. 5th conference of the Hungarian Association for Image Processing and Pattern Recognition (KÉPAF), 29th workshop of the Austrian Association for Pattern Reco</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">OCG</style></publisher><pub-location><style face="normal" font="default" size="100%">Vienna</style></pub-location><pages><style face="normal" font="default" size="100%">311 - 318</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present two approaches for automatically segmenting thespinal cord/canal from native CT images of the thorax region 
containing the spine. Different strategies are included to 
handle images where only part of the spinal column is visible. 
The algorithms require one seed point given on a slice located 
in the middle region of the spine, and the rest is automatic. 
The spatial extent of the spinal cord/canal is determined 
automatically using anatomical information for segmenting the 
spinal canal while active contours are applied if the spinal 
cord is to be segmented. Both methods work in 2D and use 
propagated information from neighboring slices. They are also 
very rapid in execution, that means an efficient, user-friendly 
workflow. The methods were evaluated by radiologists and were 
found to be useful and met the accuracy and repeatability 
requirements for the particular task.
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