Abstract
In medical and industrial applications of computed tomography (CT) imaging, limited by the scanning environment and the risk of excessive X-ray radiation exposure imposed to the patients, reconstructing high quality CT images from limited projection data has become a hot topic. X-ray imaging in limited scanning angular range is an effective imaging modality to reduce the radiation dose to the patients. As the projection data available in this modality are incomplete, limited-angle CT image reconstruction is actually an ill-posed inverse problem. To solve the problem, image reconstructed by conventional filtered back projection (FBP) algorithm frequently results in conspicuous streak artifacts and gradual changed artifacts nearby edges. Image reconstruction based on total variation minimization (TVM) can significantly reduce streak artifacts in few-view CT, but it suffers from the gradual changed artifacts nearby edges in limited-angle CT. To suppress this kind of artifacts, we develop an image reconstruction algorithm based on ℓ 0 gradient minimization for limited-angle CT in this paper. The ℓ 0-norm of the image gradient is taken as the regularization function in the framework of developed reconstruction model. We transformed the optimization problem into a few optimization sub-problems and then, solved these sub-problems in the manner of alternating iteration. Numerical experiments are performed to validate the efficiency and the feasibility of the developed algorithm. From the statistical analysis results of the performance evaluations peak signal-to-noise ratio (PSNR) and normalized root mean square distance (NRMSD), it shows that there are significant statistical differences between different algorithms from different scanning angular ranges (p<0.0001). From the experimental results, it also indicates that the developed algorithm outperforms classical reconstruction algorithms in suppressing the streak artifacts and the gradual changed artifacts nearby edges simultaneously.
Highlights
As an important nondestructive testing method, computed tomography (CT) shows large-scale applications in many fields such as medical diagnosis, industrial nondestructive testing, etc
To better preserve the edges and suppress the artifacts to limited-angle CT image reconstruction, we developed an alternating iterative reconstruction algorithm for limited-angle CT based on l0 gradient minimization
We tested the developed algorithm for limited-angle tomography using a digital NURBS based cardiac-torso (NCAT) phantom with matrix size 256×256 [35,36,37]
Summary
As an important nondestructive testing method, CT shows large-scale applications in many fields such as medical diagnosis, industrial nondestructive testing, etc. Limited by the scanning environment and the excessive radiation dose imposed to the patients, it is desired that high quality CT images can be reconstructed from low-dose projection data [2,3,4]. It is possible that the effective scanning angular range doesn’t satisfy the condition of short scan [5], i.e., the effective scanning angular range is less than 180° plus fan angle. In this case, significant streak artifacts and gradual changed artifacts nearby edges are present in reconstructed images by conventional FBP algorithm and images are distorted [6]. Especially for dental CT [7,8], C-
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