M
Margarete Ortner
Researcher at Telecom SudParis
Publications - 8
Citations - 310
Margarete Ortner is an academic researcher from Telecom SudParis. The author has contributed to research in topics: Segmentation & Airway. The author has an hindex of 5, co-authored 8 publications receiving 251 citations.
Papers
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Journal ArticleDOI
Extraction of Airways From CT (EXACT'09)
Pechin Lo,Bram van Ginneken,Joseph M. Reinhardt,Tarunashree Yavarna,Pim A. de Jong,Benjamin Irving,Catalin Fetita,Margarete Ortner,Romulo Pinho,Jan Sijbers,Marco Feuerstein,Anna Fabijańska,Christian Bauer,Reinhard Beichel,Carlos S. Mendoza,Rafael Wiemker,Jaesung Lee,Anthony P. Reeves,Silvia Born,Oliver Weinheimer,Eva M. van Rikxoort,Juerg Tschirren,Ken Mori,Benjamin L. Odry,David P. Naidich,Ieneke J. C. Hartmann,Eric A. Hoffman,Mathias Prokop,Jesper Holst Pedersen,Marleen de Bruijne +29 more
TL;DR: A fusion scheme that obtained superior results is presented, demonstrating that there is complementary information provided by the different algorithms and there is still room for further improvements in airway segmentation algorithms.
A morphological-aggregative approach for 3D segmentation of pulmonary airways from generic MSCT acquisitions
TL;DR: A generic and automated 3D airway segmentation approach able to deal with a large spectrum of MSCT protocols by exploiting a combined morphologicalaggregative methodology is developed.
Proceedings ArticleDOI
Airway shape assessment with visual feed-back in asthma and obstructive diseases
Catalin Fetita,Margarete Ortner,Pierre-Yves Brillet,Pierre-Yves Brillet,Yahya Ould Hmeidi,Francoise Preteux +5 more
TL;DR: A fullyautomated airway shape assessment approach based on the 3D segmentation of the airway lumen from MSCT data, evaluated on a MSCT database including twelve patients with severe or moderate persistent asthma, or severe COPD, by analyzing segmental and subsegmental bronchi of the right lung.
Journal ArticleDOI
Volumetric quantification of airway wall in CT via collision-free active surface model: application to asthma assessment.
TL;DR: The volumetric segmentation of the airway wall from CT data is addressed by exploiting a patient-specific surface active model and allows the quantification of the tissue thickness based on a locally-defined measure sensitive to even small surface irregularities.
Book ChapterDOI
3D vector flow guided segmentation of airway wall in MSCT
TL;DR: In this article, a 3D automated approach for airway wall segmentation and quantification in MSCT based on a patient-specific deformable model is developed, which is explicitly defined as a triangular surface mesh at the level of the airway lumen segmented from the MSCT data.