Reducing radiation dose in C-arm Cone-beam CT (CBCT) image-guided interventional procedures is of great importance. However, reducing radiation dose may increase noise magnitude and generate noise streaks in the reconstructed image. Several approaches, ranging from simple to highly complex methods, have been proposed in an attempt to reduce noise and mitigate artifacts caused by low detector counts. These approaches include apodizing the ramp kernel used before backprojection, using an adaptive trimmed mean filter based on local flux information, employing penalized-likelihood approaches or edge-preserving filters for sinogram smoothing, incorporating statistical models into the so-called model based iterative reconstruction framework, and more. This work presents a simple yet powerful scheme for low signal correction in low dose CBCT by applying local anisotropic diffusion filtration to the raw detector data prior to the logarithmic transform. It was found that low signal correction efficiently reduced noise magnitude and noise streaks without considerably sacrificing spatial resolution. Yet caution must be taken when selecting the parameters used for low signal correction so that no spurious information is enhanced and noise streaks are effectively reduced.
Daniel Gomez-Cardona, John Hayes, Ran Zhang, Ke Li, Juan Pablo Cruz-Bastida, and Guang-Hong Chen, "Low signal correction scheme for low dose CBCT: the good, the bad, and the ugly," Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101320Z (Presented at SPIE Medical Imaging: February 15, 2017; Published: 9 March 2017); https://doi.org/10.1117/12.2255531.
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