This book investigates the critical role of detection systems in identifying and classifying lung cancer, particularly through advanced imaging techniques. It presents recent advancements in lung cancer detection and classification, focusing on the primary applications of computer-aided diagnosis. The work examines lung nodule segmentation, lung nodule classification, and the impact of Big Data in lung cancer analysis, aiming to identify new techniques and their use in biomedical analysis.

This volume is positioned as a technical exploration of cutting-edge methods in lung cancer detection. The focus on computer-aided diagnosis and Big Data suggests a readership of researchers and medical professionals interested in the computational aspects of oncology. The presentation of specific applications like nodule segmentation and classification indicates a practical, data-driven approach to the subject matter.