Statistical Textural Features for Classification of Lung Emphysema in CT Images:A comparative study

Verónica Vasconcelos
ISEC – IPC
Portugal

António Marques
ISEC – IPC
Portugal

José Silva
DF – FCTUC
Portugal

João Barroso
UTAD
Portugal

Abstract:
Computed tomography (CT) can contribute to the early detection of lung diseases like emphysema, a chronic and progressive disease. Texture-based methods can be explored to classify regions of interest (ROI’s) into emphysematous areas and normal areas. In this work we evaluated the importance of a set of parameters in the classification of lung CT images, such as the size of the ROIs, the quantization level, and textural features used in classification. A support vector machine was used as classifier. The performance of the designed classifier was evaluated using a 10-fold cross validation method and the results compared based on the sensibility, specificity and overall accuracy.