Lung Cancer Detection using Convolutional Neural Networks and Virtual Reality

Early detection is essential for the enhancement of survival rates, as lung cancer is one of the most lethal malignancies worldwide. The latest developments in deep learning and virtual reality (VR) offer exciting opportunities for improving diagnostic precision and patient care. This research presents an innovative method for lung cancer detection that combines Convolutional Neural Networks (CNNs) with virtual reality technologies. The suggested method utilizes the robust image recognition capabilities of CNNs to precisely identify and categorize lung cancer in medical imaging. Concurrently, VR offers an immersive visualization environment, assisting radiologists and clinicians in understanding the spatial distribution and attributes of identified tumors. This integrated strategy seeks to enhance diagnostic efficiency, minimize false positives, and provide a more user-friendly interface for healthcare practitioners.