Automated detection of lung lesions in computed tomography images using image processing techniques and intelligent system / Mohd Firdaus Abdullah

Lung cancer is a common cause of death among people throughout the world. Lung cancer detection can be done in several ways, such as Radiography, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). Based on this method CT is suitable for lung cancer detection, that offers a lower cost, short imaging time and widespread availability. Early detection of lung lesion is important for clinical analysis on effective prevention planning by medical authorities to reduce the number of mortalities. Lesion identification on CT images manually identified by experienced radiologists commonly uses visual score. However, the manual method is timeconsuming, tedious, labour-intensive and intervisibility. Recently, research on fully automated lung lesion identification that aims to overcome the problems of manual delineation has attracted a lot of attention.