  Micro-computed tomography (micro-CT) is a widely used state-of-the-art
instrument employed to study the morphological structures of objects in various
fields. However, its small field-of-view (FOV) cannot meet the pressing demand
for imaging relatively large objects at high spatial resolutions. Recently, we
devised a novel scanning mode called multiple source translation CT (mSTCT)
that effectively enlarges the FOV of the micro-CT and correspondingly developed
a virtual projection-based filtered backprojection (V-FBP) algorithm for
reconstruction. Although V-FBP skillfully solves the truncation problem in
mSTCT, it requires densely sampled projections to arrive at high-resolution
reconstruction, which reduces imaging efficiency. In this paper, we developed
two backprojection-filtration (BPF)-based algorithms for mSTCT, i.e., S-BPF
(derivatives along source) and D-BPF (derivatives along detector). D-BPF can
achieve high-resolution reconstruction with fewer projections than V-FBP and
S-BPF. Through simulated and real experiments conducted in this paper, we
demonstrate that D-BPF can reduce source sampling by 75% compared with V-FBP at
the same spatial resolution, which makes mSTCT more feasible in practice.
Meanwhile, S-BPF can yield more stable results than D-BPF, which is similar to
V-FBP.
