Cancerous lung nodule detection in computed tomography images - Ayman Abu Baker; Yazeed Ghadi (TELKOMNIKA (Telecommunication Computing Electronics and Control), 2020)
Diagnosis the computed tomography images (CT-images) is one of the images that may take a lot of time in diagnosis by the radiologist and may miss some of cancerous nodules in these images. Therefore, in this paper a new novel enhancement and detection cancerous nodule algorithm is proposed to diagnose a CT-images. The novel algorithm is divided into three main stages. In first stage, suspicious regions are enhanced using modified LoG algorithm. Then in stage two, a potential cancerous nodule was detected based on visual appearance in lung. Finally, five texture features analysis algorithm is implemented to reduce number of detected FP regions. This algorithm is evaluated using 60 cases (normal and cancerous cases), and it shows a high sensitivity in detecting the cancerous lung nodules with TP ration 97% and with FP ratio 25 cluster/image.