Computer-aided diagnostic system kinds and pulmonary nodule detection efficacy

This paper summarizes the literature on computer-aided detection (CAD) systems used to identify and diagnose lung nodules in images obtained with computed tomography (CT) scanners. The importance of developing such lies fact that process manually detecting is painstaking sequential work for radiologists, as it takes a long time. Moreover, pulmonary have multiple appearances shapes, large number slices generated by scanner creates great difficulty accurately locating nodules. handcraft can be caused messing some spicily when these nodules' diameter less than 10 mm. So, CAD system an essential assistant radiologist this case nodule detection, contributed reducing time consumption detection; moreover, applied more accuracy field. objective follow up current previous cancer diagnosis. dealt group specialized field quickly showed methods them. It emphasis based deep learning involving neural convolution networks.