click here to download project abstract/base paper
ABSTRACT
Embark on a critical journey in medical diagnostics with our pioneering project, “Detection of Lung Cancer through Computed Tomographic Images using Deep Learning.” This abstract extends an insightful invitation to students eager to explore the convergence of cutting-edge technology and healthcare, unraveling the potential of deep learning in the early detection of lung cancer through advanced image analysis.
In this project, we navigate the intricate realm of medical imaging, employing deep learning methodologies to analyze computed tomographic (CT) images for signs of lung cancer. Students will be introduced to the fundamental concepts of convolutional neural networks (CNNs), image preprocessing, and the application of deep learning algorithms, gaining a comprehensive understanding of the pivotal role technology plays in enhancing medical diagnostics.
This abstract provides a glimpse into the core principles of our project, showcasing how deep learning enables accurate and timely detection of lung cancer from CT scans. Through hands-on exploration, students will gain valuable insights into the challenges and innovations within medical imaging, empowering them to contribute to the evolution of intelligent systems for early disease diagnosis.
