18 March 2015 CBCT reconstruction via a penalty combining total variation and its higher-degree term
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Abstract
Penalized weighted least-squares (PWLS) iterative algorithm with a total variation penalty (PWLS-TV) has shown potential to improve cone-beam CT (CBCT) image quality, particularly in suppressing noise and preserving edges. However, it sometimes suffers from the well-known staircase effect, which produces piece-wise constant areas in images. In order to remove the staircase effect, there is an increasing interest in replacing TV by higher-order derivative operations such as Hessian. Unfortunately, Hessian tends to blur the edges in the reconstruction results. In this study, we proposed a new penalty, namely the TV-H penalty, which combines the TV penalty and the Hessian penalty for CBCT reconstruction. The TV-H penalty retains some of the most favorable properties of the TV penalty like suppressing noise and preserving edges and has a better ability in preserving the structures of gradual intensity transition in images. The penalized weighted least-squares (PWLS) criterion with the majorization-minimization (MM) approach was used to minimize the objective function. Two simulated digital phantoms were used to compare the performance of TV, Hessian penalty and TV-H penalties. Our experiments indicated that the TV-H penalty outperformed the TV penalty and the Hessian penalty.
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Nanbo Sun, Nanbo Sun, Tao Sun, Tao Sun, Jing Wang, Jing Wang, Shan Tan, Shan Tan, } "CBCT reconstruction via a penalty combining total variation and its higher-degree term", Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94123T (18 March 2015); doi: 10.1117/12.2082445; https://doi.org/10.1117/12.2082445
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