Lung Cancer Detection Using Convolutional Neural Network
Dhyanendra Jain, Prashant Singh, Amit Kumar Pandey, Mayank Singh, H. B. Singh, Amarjeet Singh
Abstract
Automatic detection of defects and abnormalities in CT scan images has gain lot of importance in the recent times as because of the deteriorating quality of air almost everyone is facing one or the other type of lung related issues thus it is of esteem importance to study the computed tomography (CT) images of the pulmonary nodules to efficiently treat the diseases like lung cancer. The use of machine learning is an efficient way to distribute the work of doctors and process the large amount of data to produce accurate results on the go. Three phases of CT image pre-processing, Deep Learning, and Convolutional Neural Network use make up the diagnosis approach. The pre-processing converts raw data into usable form and deep learning algorithm assigns weight to the data, in the last stage CNN is use to conclude the health status of the lung, i.e. normal or abnormal.