A bottom-up approach for labeling of human airway trees

Pechin Lo, Eva M. van Rikxoort, Jonathan Goldin, Fereidoun Abtin, Marleen de Bruijne, Matthew Brown

Abstract

In this paper, an airway labeling algorithm that allows for
gaps between the labeled branches is introduced. A bottom-up approach
for arriving to an optimal set of branches and their associated labels
is used in the proposed method. A K nearest neighbor based appearance
model is used to differentiate the different anatomical branches.
The proposed method was applied on 33 computed tomography scans
of different subjects, where an average of 24 anatomical branches were
correctly detected out of a total of 29 anatomical branches. Additionally
the proposed method was also evaluated on trees with simulated errors,
such as missing branches and having falsely detected branches, where we
showed that such errors have little or no effect on the proposed method.
Original languageEnglish
Title of host publicationThe Fourth International Workshop on Pulmonary Image Analysis
EditorsReinhard Beichel, Marleen de Bruijne, Sven Kabus, Atilla Kiraly, Jan-Martin Kuhnigk, Jamie McClelland, Kensaku Mori, Eva van Rikxoort, Simon Rit
Number of pages12
PublisherCreateSpace
Publication date2011
Pages23-34
ISBN (Print)978-1466200166
Publication statusPublished - 2011
Event4th International Workshop on Pulmonary Image Analysis - Toronto, Canada
Duration: 18 Sept 201118 Sept 2011
Conference number: 4

Conference

Conference4th International Workshop on Pulmonary Image Analysis
Number4
Country/TerritoryCanada
CityToronto
Period18/09/201118/09/2011

Fingerprint

Dive into the research topics of 'A bottom-up approach for labeling of human airway trees'. Together they form a unique fingerprint.

Cite this