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Automated Nomenclature Labeling of the Bronchial Tree in 3D-CT Lung Images
Book chapter   Open access   Peer reviewed

Automated Nomenclature Labeling of the Bronchial Tree in 3D-CT Lung Images

Hiroko Kitaoka, Yongsup Park, Juerg Tschirren, Joseph Reinhardt, Milan Sonka, Goeffrey McLennan and Eric A Hoffman
Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002, pp.1-11
Lecture Notes in Computer Science, Springer Berlin Heidelberg
10/10/2002
DOI: 10.1007/3-540-45787-9_1
url
https://doi.org/10.1007/3-540-45787-9_1View
Published (Version of record) Open Access

Abstract

A nomenclature labeling algorithm for the human bronchial tree down to sub-lobar segments is proposed, as a means of inter and intra subject comparisons for the evaluation of lung structure and function. The algorithm is a weighted maximum clique search of an association graph between a reference tree and an object tree. The adjacency between nodes in the association graph is defined so as to reflect the consistency between the bronchial name in the reference tree and the node connectivity in the object tree. Nodes in the association graph are weighted according to the similarity between two tree nodes in the respective trees. This algorithm is robust to various branching patterns and false branches that arise during segmentation processing. Experiments have been performed for nine airway trees extracted automatically from clinical 3D-CT data, where approximately 250 branches were contained. Of these, 95 % were accurately named.
 Bronchial Tree Left Lower Lobe Object Tree Reference Tree Segmental Node

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