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In conventional computed tomography (CT) reconstruction, a non-negativity constraint on the image values is often included. Such constraint reduces the feasible set in a constrained optimization problem and often results in faster search. In basis-material-based spectral CT reconstruction, the physical grounding for the non-negativity constraint of basis image values is no longer present. It is either...
Statistical iterative reconstruction (SIR) algorithms have shown advantages over the conventional filtered back-projection method for low-dose computed tomography (CT) reconstruction. For the SIR algorithms, the regularization term plays a critical role on determining the performance. One commonly used regularization is the quadratic-form Gaussian Markov random field (MRF), which penalizes differences...
Many studies have reported that the volume-weighting technique has advantages over the ray-tracing method in re-projection modality and the linear interpolation in back-projection operation for three-dimensional (3D) X-ray computed tomography (CT) imaging. However, the calculation of the intersecting volumes requires a high arithmetic complexity and can be difficult to implement practically. In this...
Previous works have demonstrated that the low-dose CT images could be reconstructed by minimizing the total variation (TV) or adaptive weighted total variation (AwTV) of the desired images incorporate data fidelity term. However, due to the piecewise constant assumption of TV model, the reconstructed images are frequently reported to suffer from the undesired patchy artifacts or stair-case effects...
Ray-driven technique is very important for computed tomography (CT) image reconstruction. It has been reported that the weighting factor in ray-driven technique can be obtained by calculating the intersection length (distance-weighting) or area (area-weighting) of a projection line or strip with an image pixel. Recently, we presented a method which considers the intersection volume as weighting factor...
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