Filtered Back Projection Algorithm for Computed Tomography (CT) Reconstruction

The Filtered Back Projection algorithm serves as a fundamental reconstruction technique in Computed Tomography (CT) systems. This algorithm transforms a series of projection data into high-quality cross-sectional images through filtering and backprojection operations. In practical implementation, the process typically involves applying a convolution filter (such as Ram-Lak or Shepp-Logan filters) to raw projection data before performing backprojection using interpolation methods like linear or nearest-neighbor approaches. The algorithm's core function computes the inverse Radon transform by integrating filtered projections across all angles, which can be optimized through parallel computing techniques for medical imaging applications including diagnostic procedures and treatment planning. Continuous research focuses on improving reconstruction accuracy and computational efficiency through advanced filtering techniques and GPU-accelerated implementations, making it an indispensable component in modern CT technology.