Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: The VESSEL12 study

Autor: Pim A. de Jong, Raúl San José Estépar, Marius Staring, Valery Naranjo, Daniel Jimenez-Carretero, Christina Stöcker, Mathias Prokop, Maciej Orkisz, Catalin Fetita, Christophe Lefevre, Arantza Campo, Changyan Xiao, Bram van Ginneken, Karteek Popuri, Wenzhe Xue, Erik Smistad, Dennis Bosboom, Andres Santos, Michael Pienn, Carlos Ortiz-de-Solorzano, Michael Helmberger, Martin Urschler, James C. Ross, Kamuran A. Kadipasaoglu, Dana Cobzas, Devrim Unay, Rina D. Rudyanto, Hans Meine, Ryan Kiros, Eva M. van Rikxoort, Frank Lindseth, Markus Hüllebrand, Berend C. Stoel, Maria J. Ledesma-Carbayo, Amir Hossein Foruzan, Sjoerd Kerkstra, George R. Washko, Arrate Muñoz-Barrutia, Pierre Yves Brillet, Xiangjun Zhu, Anna Fabijańska, Ilkay Oksuz, Fernando L opez Mir, Eliseo Villanueva, Anne C. Elster, Juan Carlos Prieto, Marcela Hernández Hoyos, Jianming Liang

Publikováno v: Medical Image Analysis
Medical Image Analysis, Elsevier, 2014, 18 (7), pp.1217-1232
Medical Image Analysis, 18, 1217-1232
Medical Image Analysis, 18, pp. 1217-1232
Medical Image Analysis, 18(7), 1217-1232
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Contains fulltext : 137671.pdf (Publisher’s version ) (Open Access) The {VESSEL12} ({VES}sel {SE}mentation in the {L}ung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography ({C

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b72783300002656bb2017bcb303b26b9
https://hdl.handle.net/2066/137671