Detection Systems in Lung Cancer and Imaging

This book focuses on major trends and challenges in the detection of   lung cancer, presenting work aimed at identifying new techniques and   their use in biomedical analysis. This volume covers recent  advancements  in lung cancer and imaging detection and classification,  examining the  main applications of computer aided diagnosis relating to  lung cancer:  lung nodule segmentation, lung nodule classification, and  Big Data in  lung cancer. Ideal for academics working in lung cancer,  data-mining,  machine learning, deep learning and reinforcement  learning, as well as  industry professionals working in the areas of  healthcare, lung cancer  imaging, machine learning, deep learning and  reinforcement learning,  this edited collection comprises an essential  reference for researchers  at the forefront of the field, and provides a  high-level entry point for  more advanced students.