Convolution Neural Network Based Lung Cancer Detection with Remote Communication

Abstract

Lung cancer is one of the dangerous and life- threatening disease on the planet. Therefore, computer aided diagnosis (CAD) will assist the doctors to detect the cancerous cells more accurately. Many computer aided techniques make use of image processing and machine learning models. This paper demonstrates a CAD system which utilizes deep convolutional networks for lung cancer detection using CT scan images. The datasets from Kaggle Data Science Bowl 2017 is considered as database to analyse the lung cancer.  The convolution neural network based technique is adapted to classify the cancerous cell. Cascading of such layers improves the accuracy of prediction. During the advanced stage of cancer, the patients are unable to visit the doctors very often due to health conditions. Hence there is a need for IoT infrastructure to be deployed so that the doctors and patients can communicate from the remote places. On identification the result is communicated to the patients through the remote communication.