Space-Filling X-Ray Source Trajectories for Efficient Scanning in Large-Angle Cone-Beam Computed Tomography
| العنوان: | Space-Filling X-Ray Source Trajectories for Efficient Scanning in Large-Angle Cone-Beam Computed Tomography |
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| المؤلفون: | Adrian Sheppard, Shane Latham, Benoit Recur, Andrew Kingston, Heyang Li, Glenn R. Myers |
| المصدر: | IEEE Transactions on Computational Imaging. 4:447-458 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2018. |
| سنة النشر: | 2018 |
| مصطلحات موضوعية: | Physics, Cone beam computed tomography, Tomographic reconstruction, Mathematical analysis, 02 engineering and technology, Iterative reconstruction, Inverse problem, 021001 nanoscience & nanotechnology, 01 natural sciences, Projection (linear algebra), Computer Science Applications, 010309 optics, Computational Mathematics, 0103 physical sciences, Signal Processing, Trajectory, Tomography, 0210 nano-technology, Condition number |
| الوصف: | We present a new family of X-ray source scanning trajectories for large-angle cone-beam computed tomography. Traditional scanning trajectories are described by continuous paths through space, e.g., circles, saddles, or helices, with a large degree of redundant information in adjacent projection images. Here, we consider discrete trajectories as a set of points that uniformly sample the entire space of possible source positions, i.e., a space-filling trajectory (SFT). We numerically demonstrate the advantageous properties of the SFT when compared with circular and helical trajectories as follows: first, the most isotropic sampling of the data, second, optimal level of mutually independent data, and third, an improved condition number of the tomographic inverse problem. The practical implications of these properties in tomography are also illustrated by simulation. We show that the SFT provides greater data acquisition efficiency, and reduced reconstruction artifacts when compared with helical trajectory. It also possesses an effective preconditioner for fast iterative tomographic reconstruction. |
| تدمد: | 2334-0118 2573-0436 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::ad88786d36a5e8d259f57c3dea714cb1 https://doi.org/10.1109/tci.2018.2841202 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........ad88786d36a5e8d259f57c3dea714cb1 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 23340118 25730436 |
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