Image quality improvement through fusion of hybrid bone- and soft-tissue-texture filtering for 3D cone beam CT extremity imaging system
Paper
24 February 2012 Image quality improvement through fusion of hybrid bone- and soft-tissue-texture filtering for 3D cone beam CT extremity imaging system
D. Yang, R. A. Senn, N. Packard, J. Yorkston, D. H. Foos
Author Affiliations +
Abstract
A flat-panel, detector-based cone beam CT system can provide advantages over a fan beam CT system in terms of 3D isotropic spatial resolution. However, as a result of increased X-ray coverage along the rotation axis, there is also an increase in scatter. This can lead to a decrease in low-contrast resolution as well as the appearance of non-uniform artifacts across the reconstructed image. These effects can be minimized with the use of an anti-scatter grid; however, further software corrections are often desirable. Software scatter correction is generally achieved through the subtraction of an estimate of the scatter distribution from the corresponding original projection data in the linear space. While the non-uniform artifacts effect is generally improved, a side effect of this subtractive process can be an undesirable amplification of the apparent noise, which makes the image quality, in terms of contrast-to-noise ratio (CNR), much worse than the images produced by fan beam CT systems. In this work, a novel modified imaging chain has been proposed to apply separate, non-linear noise-reduction algorithms on bone and soft tissues to improve the CNR for soft tissue as well as to maintain a high spatial resolution for the display of boney structures.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
D. Yang, R. A. Senn, N. Packard, J. Yorkston, and D. H. Foos "Image quality improvement through fusion of hybrid bone- and soft-tissue-texture filtering for 3D cone beam CT extremity imaging system", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83143X (24 February 2012); https://doi.org/10.1117/12.911320
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KEYWORDS
Imaging systems

X-ray computed tomography

Tissues

3D image processing

Denoising

Image filtering

Linear filtering

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