Selecting projection views based on error equidistribution for computed tomography
Zhang, Yinghui and Zhao, Xing and Chen, Ke and Li, Hongwei (2025) Selecting projection views based on error equidistribution for computed tomography. Journal of X-Ray Science and Technology. ISSN 1095-9114 (https://doi.org/10.1177/08953996241289267)
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Abstract
Background Nonuniform sampling is a useful technique to optimize the acquisition of projections with a limited budget. Existing methods for selecting important projection views have limitations, such as relying on blueprint images or excessive computing resources. Methods We aim to develop a simple nonuniform sampling method for selecting informative projection views suitable for practical CT applications. The proposed algorithm is inspired by two key observations: projection errors contain angle-specific information, and adding views around error peaks effectively reduces errors and improves reconstruction. Given a budget and an initial view set, the proposed method involves: estimating projection errors based on current set of projection views, adding more projection views based on error equidistribution to smooth out errors, and final image reconstruction based on the new set of projection views. This process can be recursive, and the initial view can be obtained uniformly or from a prior for greater efficiency. Results Comparison with popular view selection algorithms using simulated and real data demonstrates consistently superior performance in identifying optimal views and generating high-quality reconstructions. Notably, the new algorithm performs well in both PSNR and SSIM metrics while being computationally efficient, enhancing its practicality for CT optimization. Conclusions A projection view selection algorithm based on error equidistribution is proposed, offering superior reconstruction quality and efficiency over existing methods. It is ready for real CT applications to optimize dose utilization.
ORCID iDs
Zhang, Yinghui, Zhao, Xing, Chen, Ke
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Item type: Article ID code: 92010 Dates: DateEvent15 January 2025Published15 January 2025Published Online19 September 2024Accepted5 June 2024SubmittedSubjects: Science > Mathematics
Medicine > Biomedical engineering. Electronics. InstrumentationDepartment: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 06 Feb 2025 12:01 Last modified: 06 Feb 2025 12:06 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/92010