Sinogram Interpolation Method for Sparse-Angle Tomography

Martti Kalke,Samuli Siltanen

doi:10.4236/am.2014.53043

Abstract

In sparse-angle X-ray tomography reconstruction, where only a small number of projection images are taken around the object, appropriate sinogram interpolation has a significant impact on image quality. A novel sinogram interpolation method is introduced for extreme sparse tomographic reconstruction where only nine measured projection images are available. The sinogram is interpolated by solving characteristics of the so-called warps, which can be considered as approximation sine waves in a limited region. The numerical evidence suggests that this approach gives superior results over standard interpolation methods when the tomographic data are extremely sparse and noisy.

Highlights

Three-dimensional (3D) X-ray imaging is typically needed for measuring the inner structures of a patient
We focus on interpolating new sinogram columns without modifying the measured sinogram columns
We introduce a new approach, called Sinogram Interpolation Technique (SINT) for estimating new sinogram columns between known, measured sinogram columns in the extremely sparse situation of only nine known sinogram columns

Summary

Introduction

Three-dimensional (3D) X-ray imaging is typically needed for measuring the inner structures of a patient. In implant dentistry where damaged or missing teeth are replaced by artificial teeth, a screw hole with accurate depth, angle and diameter is needed for the implant. The hole has to be deep enough to ensure firm attachment, but not too deep as nerves might be damaged. This measurement cannot be based on two-dimensional (2D) images since they represent a distorted projection of the tissue. Another clinical application of 3D X-ray imaging is solving the superposition problem. Since a pixel of a 2D projection image is a sum of attenuation along the path of an X-ray, the overlapping low-contrast tissues are difficult to recognize

Results

Discussion

Conclusion