Automatic Ground Glass Pattern Detection in Lung Disease using Gabor Filter

摘要

This paper proposes an approach for automatic detection of Ground glass pattern, a lung disease, from Computed Tomography (CT) and High Resolution Computed Tomography (HRCT) scans of the lung. The algorithm is based on frequency spectrum analysis of the image using Gabor filter bank. The tasks are completed in three steps: Preliminary mask formation, Peripheral mask formation and finally post processing. By these higher sensitivity and selectivity may be achieved with fast processing time. In the post processing, binary noise removal technique is used to remove noise from the detection mask.