Chapter 5 - Neural network for lung cancer diagnosis

Abstract

Lung cancer is the most common malignant tumor in the world, which also has the highest mortality rate. In contrast to the steady increase in survival for most type of cancers, lung cancer progresses slowly. Generally, a 5-year survival rate for lung cancer patients is 16%, and if the lung cancer is diagnosed at an early stage, it reaches 52%. Therefore, early detection of lung cancer is essential in order to prolong the lives of patients. The results of the neural network diagnosis method for lung cancer are in good agreement with the known data, and they have a high accuracy rate. The diagnosis can be made accurately, which is conducive to the early detection and treatment of lung cancer, especially for lung cancer patients. This paper summarizes the application of neural networks with the diagnosis of lung cancer, which includes the detection of lung nodules, the segmentation of lung tumors, and the classification of lung nodules. This paper also introduces the technical route for a lung cancer diagnosis in detail. It starts with the detection of lung nodules that cause lung cancer, detects an area, segments it, and then classifies the types of lung nodules.