Efficient and fully automatic segmentation of the lungs in CT volumes

Müller, Henning (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Dicente Cid, Yashin (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Jiménez del Toro, Oscar Alfonso (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Depeursinge, Adrien (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis))

The segmentation of lung volumes constitutes the first step for most computer-aided systems for lung diseases. CT (Computed Tomography) is the most common imaging technique used by these systems, so fast and accurate methods are needed to for allow early and reliable analysis. In this paper, an efficient and fully automatic method for the segmentation of the lung volumes in CT is presented. This method deals with the initial segmentation of the respiratory system, the posterior extraction of the air tracks, and the final identification of the tow lungs with 3 novel approaches. The system relies only on anatomical assumptions and was evaluated in the context of the VISCERAL Anatomy3 Challenge, achieving one of the best results.


Mots-clés:
Type de conférence:
full paper
Faculté:
Economie et Services
Ecole:
HEG-VS
Institut:
Institut Informatique de gestion
Classification:
Informatique
Adresse bibliogr.:
New York, USA, 16-19 April 2015
Date:
New York, USA
16-19 April 2015
2015
Pagination:
5 p.
Publié dans
Workshop proceedings of the VISCERAL Anatomy3 organ Segmentation Challenge co-located with IEEE 12th International Symposium on Biomedical Imaging (ISBI) 2015
Numérotation (vol. no.):
1390
ISSN:
1613-0073
Le document apparaît dans:



 Notice créée le 2015-11-15, modifiée le 2018-12-11

Fichiers:
Télécharger le document
PDF

Évaluer ce document:

Rate this document:
1
2
3
 
(Pas encore évalué)