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.
Original language | English (US) |
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Title of host publication | Medical Imaging 2015: Physics of Medical Imaging |
Publisher | SPIE |
Volume | 9412 |
ISBN (Electronic) | 9781628415025 |
DOIs | |
State | Published - 2015 |
Event | Medical Imaging 2015: Physics of Medical Imaging - Orlando, United States Duration: Feb 22 2015 → Feb 25 2015 |
Other
Other | Medical Imaging 2015: Physics of Medical Imaging |
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Country/Territory | United States |
City | Orlando |
Period | 2/22/15 → 2/25/15 |
Keywords
- Cone-beam CT
- Hessian norm
- Penalized weighted least-squares
- Total variation
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Electronic, Optical and Magnetic Materials
- Biomaterials
- Radiology Nuclear Medicine and imaging