Matched view weighting in tilted-plane-based reconstruction algorithms to suppress helical artifacts and optimize noise characteristics.
In multi-slice helical CT, the single-tilted-plane-based reconstruction algorithm has been proposed to combat helical and cone beam artifacts by tilting a reconstruction plane to fit a helical source trajectory optimally. Furthermore, to improve the noise characteristics or dose efficiency of the single-tilted-plane-based reconstruction algorithm, the multi-tilted-plane-based reconstruction algorithm has been proposed, in which the reconstruction plane deviates from the pose globally optimized due to an extra rotation along the 3rd axis. As a result, the capability of suppressing helical and cone beam artifacts in the multi-tilted-plane-based reconstruction algorithm is compromised. A matched view weighting approach is proposed here to optimize the capability of suppressing helical and cone beam artifacts and noise characteristics. A helical body phantom is employed to quantitatively evaluate the imaging performance of the matched view weighting approach, showing that the matched view weighting improves both the helical artifact suppression and noise characteristics or dose efficiency significantly in comparison to the case in which nonmatched view weighting is applied. The matched view weighting approach is of practical importance in the development of multi-slice helical CT, because it maintains the computational structure of fan beam filtered back-projection and demands no extra computational resources.
Tang
Xiangyang
X
Applied Science Laboratory, GE Medical Systems, 3000 North Grandview Boulevard, W-1190, Waukesha, Wisconsin 53188, USA. xiangyang.tang@med.ge.com
D000465:Algorithms; D016477:Artifacts; D006801:Humans; D019047:Phantoms, Imaging; D011786:Quality Control; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012542:Scattering, Radiation; D012680:Sensitivity and Specificity; D013269:Stochastic Processes; D036542:Tomography, Spiral Computed / Q000295:instrumentation / Q000379:methods*