We present a computational approach for fast approximation of nonlinear tomographic reconstruction methods by filtered backprojection (FBP) methods. Algebraic reconstruction algorithms are the methods of choice in a wide range of tomographic applications, yet they require significant computation time, restricting their usefulness. We build upon recent work on the approximation of linear algebraic reconstruction methods and extend the approach to the approximation of nonlinear reconstruction methods which are common in practice. We demonstrate that if a blueprint image is available that is sufficiently similar to the scanned object, our approach can compute reconstructions that approximate iterative nonlinear methods, yet have the same speed as FBP.
Additional Metadata
Keywords CT reconstruction, Matrices, Sensors, Tomography, Radon transform, Reconstruction algorithms, Expectation maximization algorithms
THEME Life Sciences (theme 5)
Publisher SPIE and IS&T
Persistent URL dx.doi.org/10.1117/1.JEI.24.1.013026
Journal Journal of Electronic Imaging
Project Mathematical Aspects of Discrete Tomography
Citation
Plantagie, L, & Batenburg, K.J. (2015). Algebraic filter approach for fast approximation of nonlinear tomographic reconstruction methods . Journal of Electronic Imaging, 24(1). doi:10.1117/1.JEI.24.1.013026