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Regularized 3D Iterative Reconstruction on a Mobile C-ARM CT
Y. Pan, R.T. Whitaker, A. Cheryauka, D. Ferguson. In Proceedings of The First CT Meeting, Salt Lake City, UT, 2010.
3D iterative CT reconstruction is an active research area in medical imaging. Compared with analytic reconstruction methods such as FDK, iterative methods may provide better reconstruction results for incomplete and noisy projection data. The simultaneous algebraic reconstruction technique (SART), one of the most popular iterative reconstruction methods, is applied in the cone-beam geometry for high resolution reconstruction, with the help of graphics hardware (GPU) and total variation (TV) regularization. GPU greatly improves the efficiency of SART, which is computationally intense for CPU, and thus makes it suitable for clinical applications. TV regularization reduces the effects of noise and helps the convergence of SART for noisy data. Experimental results for both synthetic and real data are provided to evaluate the accuracy and efficiency of the proposed framework.
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