Prediction and Classification of Aerosol Deposition in Lung Using CT Scan Images

Interstitial lung disease (ILD) is a set of chronic lung disorders that are essential for establishing treatment since the decisions are based on human research with the use of non-imaging methodologies. These disorders include asthma, pneumoconiosis, and infections in the respiratory tract. The buildup of particles in the lungs is the fundamental factor in the development of many diseases. Algorithms for pattern recognition are utilized in order to correctly detect and categorize the disease. Within the scope of this study is a discussion on the application of CT scan pictures to the categorization and prediction of various lung diseases. The use of a support vector machine (SVM) classifier to differentiate between a normal CT scan and an aberrant CT scan results in an increase in diagnostic precision. When projecting a three-dimensional image of a region of interest, certain parameters, including reflection coefficients, mass density, and tissue impedance, are taken into consideration (ROI).