Abstract
Abstract
In automated manufacturing and safety inspection, there is a
high demand for fast computed tomography (CT) scanning and image
reconstruction. Currently, faster scanning can be achieved by
reducing the X-ray exposure time within sparse view CT. The faster
scanning strategy introduces significant streak artefacts and noise
during the sampling process. Consequently, streak artefacts and
noise need to be simultaneously suppressed, which is poses a
challenge for existing reconstruction methods. This paper presents a
fast iterative reconstruction algorithm that can simultaneously
suppress both streak artefacts and noise. This method can not only
reconstruct high-fidelity images from rapidly acquired projection
data, but also has a faster reconstruction speed than the existing
iterative reconstruction algorithms. First, we present a high-order
multi-directional total variation (HOM-TV) method that specifically
focuses on preserving edge details of the image. Then, we present a
fast iterative reconstruction model by incorporating HOM-TV and
non-local means into the objective function. Finally, the
effectiveness of the presented reconstruction model is validated by
simulation and real experiments. The faster scanning method can
complete the scan in only 5 seconds, and the structural similarity
index (SSIM) of the CT image reconstructed by our method is 0.9755,
which is higher than 0.0175 of the Fast Null Space Reconstruction
(FNSR) algorithm. The peak signal-to-noise ratio (PSNR) index is
1.656, which is higher than that of the contrast algorithm. In terms
of reconstruction time, our algorithm can achieve reconstruction in
as little as 36 seconds, outperforming the baseline algorithms.