Tomographic Reconstruction under Unknown Angles

Tomographic reconstruction is a multidimensional inverse problem to reconstruct a specific system from finite number of projections. We estimate the optimal number of projections needed when projection angles are unknown

  • Compared SART, SIRT, FBP, SGD algorithms for tomographic reconstruction under known angle setting
  • Experimented with Graph Laplacian and Spherical LLE methods to reconstruct projections under unknown angles
  • Evaluated robustness under noise and random shifts to obtain optimal results with minimum projections