Ansatte – Københavns Universitet

A texton-based approach for the classification of lung parenchyma in CT images

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Mehrdad J. Gangeh, Lauge Sørensen, Saher B. Shaker, Mohamed S. Kamel, Marleen de Bruijne, Marco Loog

In this paper, a texton-based classification system based on raw pixel representation along with a support vector machine with radial basis function kernel is proposed for the classification of emphysema in computed tomography images of the lung. The proposed approach is tested on 168 annotated regions of interest consisting of normal tissue, centrilobular emphysema, and paraseptal emphysema. The results show the superiority of the proposed approach to common techniques in the literature including moments of the histogram of filter responses based on Gaussian derivatives. The performance of the proposed system, with an accuracy of 96.43%, also slightly improves over a recently proposed approach based on local binary patterns.

OriginalsprogEngelsk
TitelMedical Image Computing and Computer-Assisted Intervention - MICCAI 2010 : 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part III
RedaktørerTianzi Jiang, Nassir Navab, Josien P. W. Pluim, Max A. Viergever
Antal sider8
Vol/bindPart III
ForlagSpringer
Publikationsdato2010
Sider595-602
DOI
StatusUdgivet - 2010
Begivenhed13th International Conference on Medical Image Computing and Computer Assisted Intervention - Beijing, Kina
Varighed: 20 sep. 201024 sep. 2010
Konferencens nummer: 13

Konference

Konference13th International Conference on Medical Image Computing and Computer Assisted Intervention
Nummer13
LandKina
ByBeijing
Periode20/09/201024/09/2010
NavnLecture notes in computer science
Nummer6363
ISSN0302-9743

ID: 19869956