Interior Reconstruction from Truncated Projection Data in Cone-beam Computed Tomography

J Digit Imaging. 2023 Feb;36(1):250-258. doi: 10.1007/s10278-022-00695-8. Epub 2022 Aug 29.

Abstract

The interior reconstruction of completely truncated projection data is a frontier research hotspot in cone-beam computed tomography (CBCT) application. It is difficult to find a method with acceptable accuracy and high efficiency to solve it. Based on the simplified algebraic reconstruction technique (S-ART) algorithm and the filtered back projection (FBP) algorithm with the new filter, an efficient and feasible interior reconstruction algorithm is proposed in this paper. The algorithm uses the S-ART algorithm to quickly recover the complete projection data and then uses the new ramp filter which can suppress the high-frequency noise in the projection data to filter the recovered complete projection data. Finally, the interior reconstructed images are obtained by back projection. The computational complexity of the proposed algorithm is close to that of the FBP algorithm for the reconstruction of the whole object, and the reconstructed image quality is acceptable, which provides an effective method for interior reconstruction in CBCT. Simulation results show the effectiveness of the method.

Keywords: CT; Data recovery; FBP algorithm; Interior reconstruction; Truncated projection data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Computer Simulation
  • Cone-Beam Computed Tomography* / methods
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Phantoms, Imaging