@book{c2aafbc570b54b9c9e837e36b0a480c7,
title = "On-line lumen centre detection in gastrointestinal and respiratory endoscopy",
abstract = "We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %).",
keywords = "Bronchoscopy, Colonoscopy, Lumen centre detection",
author = "Carles S{\'a}nchez and Jorge Bernal and Debora Gil and S{\'a}nchez, {F. Javier}",
note = "Funding Information: This work was supported by a research grant from Universitat Aut{\'o}noma de Barcelona 471-01- 2/2010 and by Spanish projects , and . ",
year = "2014",
doi = "10.1007/978-3-319-05666-1_5",
language = "English",
isbn = "9783319056654",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}