Paper
13 March 2007 Resolution and noise trade-off analysis for volumetric CT
Author Affiliations +
Abstract
In this study, we investigate the relationship between quantum noise and spatial resolution for volumetric CT. Both theoretical analysis and experiments were performed to investigate their relationship. In theory, quantum noise can be derived from its relationship to dose, in-plane spatial resolution, recon kernel, and signal-to-noise ratio (SNR). In the experiments, by scanning a Teflon sphere phantom, the 3-D MTF was measured from the edge profile along the spherical surface. Cases of different resolutions (and noise levels) were generated by adjusting recon kernel. To reduce bias, the total photon fluxes were matched: 120kVp, 260mA, and 1sec per gantry rotation. In the end, all data sets were reconstructed using modified FDK algorithm under the same condition: FOV=10cm and slice thickness=0.625mm. Finally, we investigated the efficiency of an image-space adaptive smoothing filter as a noise reduction tool and its impact on spatial resolution. The theoretical analysis indicated that the variance of noise is proportional to at least 4th power of the spatial resolution. Our experimental results supported this conclusion by showing the relationship is 4.6th (helical) or 5th (axial) power. Results also showed that, with properly designed image-space smoothing filters, it is feasible to reduce quantum noise (and the power relationship to a lower order) with smaller loss of spatial resolution.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Baojun Li, Swetha Nandyala, Gopal Avinash, and Jiang Hsieh "Resolution and noise trade-off analysis for volumetric CT", Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 65101X (13 March 2007); https://doi.org/10.1117/12.708087
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Spatial resolution

Modulation transfer functions

Optical spheres

Image filtering

Signal to noise ratio

Spherical lenses

Digital filtering

Back to Top