Lung Cancer Detection Using Deep Learning

Lung cancer is a leading cause of cancer-related deaths worldwide.Early detection is critical for effective treatment.This project introduces a state-of-the-art lung cancer detection system that utilizes deep learning technology.It enhances diagnostic accuracy and expedites patient care. I. INTRODUCTIONLung cancer remains a major global health challenge, accounting for a significant number of cancer-related deaths.One of the primary reasons for high mortality is the delayed diagnosis, which limits effective treatment options.Traditional detection methods rely on radiologists interpreting CT scan images, which can be time-consuming and subject to human error.This project proposes an advanced lung cancer detection system powered by deep learning.By utilizing convolutional neural networks (CNNs), the system automates the analysis of lung CT scan images, enhancing diagnostic accuracy and reducing the time required for detection.The web-based interface, developed using Flask, HTML, CSS, and JavaScript, provides an intuitive platform for users to upload images for real-time analysis.The results, including detected anomalies and cancer probability, are displayed on the interface, with an option to download a diagnostic report for further medical consultation.With its ability to provide early and accurate detection, this system aims to assist healthcare professionals in making timely decisions, ultimately improving patient outcomes and survival rates.