Design and Implementation of Computed Tomography Reconstruction System Using Neural Radiance Fields Techniques

Surgery in modern medicine is renowned for its meticulous precision and emphasis on safety, requiring intricate procedures.However, ongoing concerns about radiation exposure during these surgical procedures remain a significant challenge.Continued efforts are being made to minimize radiation exposure, primarily focusing on ensuring the safety of patients and medical personnel.However, these efforts face additional hurdles, including wearing additional protective equipment.Given these challenges, this paper presents a pioneering software-based approach to mitigate radiation exposure issues.The proposed methodology introduces the Neural Radiance Field (NeRF) and a novel loss function to facilitate the reconstruction of three-dimensional CT scans from partial multi-view two-dimensional digitally reconstructed radiographs (DRRs).By employing a novel approach that implicitly learns the radiation attenuation equations within the model, this method aims to provide a comprehensive solution.The proposed approach's evaluation includes quantitative and qualitative assessments using head, abdomen, and feet datasets.The 3D reconstruction method outlined in this thesis is anticipated to serve as a transformative technological intervention, promoting improvements in safety protocols and operational efficiencies within the medical field.