4 October 2016 Optimized x-ray source scanning trajectories for iterative reconstruction in high cone-angle tomography
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Abstract
With the GPU computing becoming main-stream, iterative tomographic reconstruction (IR) is becoming a com- putationally viable alternative to traditional single-shot analytical methods such as filtered back-projection. IR liberates one from the continuous X-ray source trajectories required for analytical reconstruction. We present a family of novel X-ray source trajectories for large-angle CBCT. These discrete (sparsely sampled) trajectories optimally fill the space of possible source locations by maximising the degree of mutually independent information. They satisfy a discrete equivalent of Tuy’s sufficiency condition and allow high cone-angle (high-flux) tomog- raphy. The highly isotropic nature of the trajectory has several advantages: (1) The average source distance is approximately constant throughout the reconstruction volume, thus avoiding the differential-magnification artefacts that plague high cone-angle helical computed tomography; (2) Reduced streaking artifacts due to e.g. X-ray beam-hardening; (3) Misalignment and component motion manifests as blur in the tomogram rather than double-edges, which is easier to automatically correct; (4) An approximately shift-invariant point-spread-function which enables filtering as a pre-conditioner to speed IR convergence. We describe these space-filling trajectories and demonstrate their above-mentioned properties compared with a traditional helical trajectories.
Conference Presentation
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Andrew M. Kingston, Glenn R. Myers, Shane J. Latham, Heyang Li, Jan P. Veldkamp, Adrian P. Sheppard, "Optimized x-ray source scanning trajectories for iterative reconstruction in high cone-angle tomography", Proc. SPIE 9967, Developments in X-Ray Tomography X, 996712 (4 October 2016); doi: 10.1117/12.2238297; https://doi.org/10.1117/12.2238297
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