Analytical reconstruction algorithm for multiple source-translation computed tomography (mSTCT)

Abstract

Micro-CT is a widely used technique to provide high-resolution images of morphological structures for diverse objects; however, the trade-off between magnification and field-of-view (FOV) impedes high-resolution imaging for large objects. Recently, we have developed a multiple X-ray source translation micro-CT (mSTCT)—where we can freely adjust FOV at a given magnification—to alleviate this conflict. In this paper, we report an analytical algorithm to address truncated projections, redundant data, and geometry errors in STCT reconstruction. We deal with the truncated projections by introducing virtual projections; handle the redundant data by developing a new weighting strategy; mitigate the geometry errors by modifying projection geometry. We conduct both numerical and physical experiments to validate the feasibility of our algorithm, which demonstrates our proposed algorithm is effective for mSTCT reconstruction.