Application of Multi-objective Optimization in 3D Image Reconstruction

3D image reconstruction technology holds significant potential for applications in medical imaging, industrial inspection, and virtual reality, offering more intuitive and precise internal structure visualization.However, due to the complexity of human anatomy and the diversity of medical imaging data, traditional 3D reconstruction methods often struggle to achieve optimal results in terms of reconstruction accuracy, computational efficiency, and structural continuity simultaneously.The application of multi-objective optimization in 3D image reconstruction can comprehensively consider multiple objectives, providing more comprehensive and optimized reconstruction results.However, current research methods still have some deficiencies, primarily neglecting the trade-offs between different objectives and experiencing high computational load and low efficiency when handling complex medical imaging data.This study includes the development of image-target 3D reconstruction algorithms in trajectory space and the establishment and solution of a multiobjective optimization-based 3D image reconstruction model.The research content of this paper aims to improve the quality of reconstruction results and provide more reliable technical support for practical applications, in the hopes of enriching the theoretical foundation of 3D image reconstruction as well as offering new technical approaches for practical applications, having significant theoretical and practical value.