LUNG CANCER DETECTION AND CLASSIFICATION SYSTEM USING WGAN

The future scope of lung cancer detection using CT images is very promising due to rapid advancements in medical imaging, artificial intelligence, and data science. In the coming years, AI-based automated diagnosis systems will become more accurate and widely adopted, helping doctors detect lung cancer at very early stages with minimal human intervention. Techniques such as deep learning and convolutional neural networks (CNNs) will improve the identification of small nodules that are often missed in traditional analysis.Another important direction is the development of real-time detection systems, where CT scan results can be analyzed instantly, reducing diagnosis time and enabling faster treatment decisions. Integration with cloud computing and telemedicine will allow remote areas to access advanced diagnostic tools, improving healthcare accessibility. Additionally, 3D image reconstruction and radiomics will provide detailed tumor characterization, helping in personalized treatment planning.There is also growing research in combining CT imaging with genomic data and clinical information, leading to precision medicine approaches tailored to individual patients.