Gabor texture measure in interstitial lung disease discrimination using high resolution computed tomography thorax images

High rsolution computed tomography (HRCT) thorax imaging is a trusted modality which is widely used in medical institutions to detect respiratory disease, in particular, interstitial lung disease (ILD) detection. Observing the enormous number of slices for single patient is time consuming and consequently may lead to human error. In order to overcome to this problem, developing computer aided diagnostic (CAD) systems will assist radiologists to make correct decision in shorter time when a single case is studied. A prototype CAD system using level 5 slice of HRCT images is proposed in this study with measuring textures derived from Gabor filtered images. Ability of proposed CAD system for pairwise discrimination of ILD, non-ILD and normal lungs is tested with a statistical data analysis procedure.