An Advanced Application for Lung Cancer Prediction using Deep Learning and CT Scan Images

Lung cancer ranks as major causes of mortality across the world particularly due to challenges in early detection stemming from its subtle symptoms. Detecting lung cancer in its initial stages significantly enhances survival rates. Computed Tomography (CT) imaging plays a pivotal role in this regard, aiding in timely diagnosis. To address this, a Computer-Aided System utilizing advanced DL Algorithms is being developed. This system, divided into segmentation, extraction of features, and classification phases, aims to accurately diagnose lung nodules from CT scanned images. Deep learning techniques, including for extraction of features using RNN-LSTM for nodule classification, are employed to achieve optimal accuracy. Lung cancer's detection challenge necessitates a robust Computer aided system for diagnosis. It integrates Deep Learning Algorithms for precise diagnosis from CT scans.