Weighted Filtered Back-Projection for Source Translation Computed Tomography Reconstruction
Jie Chen, Haijun Yu, Song Ni, Chuanjiang Liu, Wenjie Ge, Yixing Huang, Fenglin Liu
Abstract
Micro-computed tomography (micro-CT) is an indispensable tool to provide attenuation-based, high-resolution 3D images in scientific research. However, its current available configuration limits the size of objects that can be imaged. Previously, we have proposed a multiple source translation computed tomography (mSTCT) imaging geometry to extend the field-of-view of micro-CT, and developed a corresponding reconstruction algorithm called virtual projection-based filtered back-projection (V-FBP). V-FBP achieves high-resolution reconstructions when the source is densely sampled but fails if the source is coarsely sampled. In this paper, to achieve high-resolution reconstruction at a low source sampling rate, we propose a full-scan multiple-STCT (F-mSTCT) scanning configuration, which allows for a simple and effective weighting function to deal with data redundancy and truncation simultaneously. Based on this concept, we develop a weighted FBP (W-FBP) algorithm. The numerical and physical experiments demonstrate that W-FBP is able to reconstruct high-resolution images at a low source sampling rate, and can reduce 1/2-3/4 projections compared with V-FBP at the same resolution.