Performance and Analysis of Ground-Glass Pattern Detection in Lung Disease based on High-Resolution Computed Tomography

Background/Aim: The aim of this work is to perform and analyze the Ground glass pattern Detection in Lung Disease based on High Resolution Computed Tomography (HRCT). Methods: The algorithm incorporates Gabor filter bank which is based on frequency spectrum analysis of image. Gabor filter banks assist in the frequency extraction process. This method when applied to HRCT images will help doctors to extract more information than from the CT images. This method is accomplished in three steps: Extraction of Preliminary mask formation, Extraction of Peripheral mask formation and finally post processing. By applying these methods, higher sensitivity and selectivity may be attained with fast processing time. In the post processing, binary noise removal technique is applied to remove noise from the detection mask. Findings: While interpreting the HRCT images we have to consider the blood being distributed to the dependent portions of the lungs. On the basis of the ground glass opacities, the bleeding site is determined as the area having more attenuation. In homogeneous attenuation, the bleeding site is determined as the upper lobes. Therefore, the bleeding site was thus determined keeping all the abnormalities (mass or clot or lesion) in mind. Application: The HRCT has also been used to guide and to provide information regarding an optimum site for open lung surgery. HRCT provides additional useful information to the CXR and directly influence the clinical management of pediatric patients with pulmonary disease, especially in detecting post-infection or post bone marrow transplant sequelae, bronchiectasis and in evaluating patients with nonspecific CXR findings.