Forskning ved Københavns Universitet - Københavns Universitet


A bottom-up approach for labeling of human airway trees

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

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.
TitelThe Fourth International Workshop on Pulmonary Image Analysis
RedaktørerReinhard Beichel, Marleen de Bruijne, Sven Kabus, Atilla Kiraly, Jan-Martin Kuhnigk, Jamie McClelland, Kensaku Mori, Eva van Rikxoort, Simon Rit
Antal sider12
ISBN (Trykt)978-1466200166
StatusUdgivet - 2011
Begivenhed4th International Workshop on Pulmonary Image Analysis - Toronto, Canada
Varighed: 18 sep. 201118 sep. 2011
Konferencens nummer: 4


Konference4th International Workshop on Pulmonary Image Analysis

ID: 33950690