A texton-based approach for the classification of lung parenchyma in CT images
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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.
Original language | English |
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Title of host publication | Medical Image Computing and Computer-Assisted Intervention - MICCAI 2010 : 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part III |
Editors | Tianzi Jiang, Nassir Navab, Josien P. W. Pluim, Max A. Viergever |
Number of pages | 8 |
Volume | Part III |
Publisher | Springer |
Publication date | 2010 |
Pages | 595-602 |
DOIs | |
Publication status | Published - 2010 |
Event | 13th International Conference on Medical Image Computing and Computer Assisted Intervention - Beijing, China Duration: 20 Sep 2010 → 24 Sep 2010 Conference number: 13 |
Conference
Conference | 13th International Conference on Medical Image Computing and Computer Assisted Intervention |
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Nummer | 13 |
Land | China |
By | Beijing |
Periode | 20/09/2010 → 24/09/2010 |
Series | Lecture notes in computer science |
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Number | 6363 |
ISSN | 0302-9743 |
ID: 19869956