A topological approach to positron emission particle tracking for finding multiple particles in high noise environments
Abstract Positron emission particle tracking (PEPT) is an advanced imaging technique that accurately tracks the three-dimensional spatial coordinates of a radioactively-labelled particle with sub-millimetre and sub-millisecond precision. By detecting back-to-back 511 keV gamma rays from positron-ele...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-97175-0 |
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| author | Jack A. Sykes Andrei L. Nicuşan Dominik Werner Matthew T. Herald Daniel Weston Tzany Kokalova Wheldon Christopher R. K. Windows-Yule |
| author_facet | Jack A. Sykes Andrei L. Nicuşan Dominik Werner Matthew T. Herald Daniel Weston Tzany Kokalova Wheldon Christopher R. K. Windows-Yule |
| author_sort | Jack A. Sykes |
| collection | DOAJ |
| description | Abstract Positron emission particle tracking (PEPT) is an advanced imaging technique that accurately tracks the three-dimensional spatial coordinates of a radioactively-labelled particle with sub-millimetre and sub-millisecond precision. By detecting back-to-back 511 keV gamma rays from positron-electron annihilation coincidence events, PEPT can locate particles within highly dense, opaque systems such as fluidised beds, rotating drums, and mills. Despite the progress made in enhancing the precision and accuracy of PEPT, simultaneous multiple particle tracking remains a significant challenge, particularly in high-noise environments. This paper introduces T-PEPT, a novel algorithm that leverages topological data analysis-a relatively new field of applied mathematics that explores the underlying ’shape’ of data through techniques like persistence homology. By creating simplicial complexes and applying persistence homology to PEPT point data, T-PEPT demonstrates highly effective performance in multiple-particle tracking, especially in scenarios with high noise. When benchmarked against existing PEPT algorithms using a widely recognised standard framework, T-PEPT consistently maintains sub-millimetre spatial and sub-millisecond temporal precision in nearly all cases, demonstrating its robustness and accuracy. For Data availability for T-PEPT, please use the GitHub repository: https://github.com/uob-positron-imaging-centre/pept . |
| format | Article |
| id | doaj-art-70cb08e560f9488b83aa4e86adf785f5 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-70cb08e560f9488b83aa4e86adf785f52025-08-20T02:24:29ZengNature PortfolioScientific Reports2045-23222025-04-0115111010.1038/s41598-025-97175-0A topological approach to positron emission particle tracking for finding multiple particles in high noise environmentsJack A. Sykes0Andrei L. Nicuşan1Dominik Werner2Matthew T. Herald3Daniel Weston4Tzany Kokalova Wheldon5Christopher R. K. Windows-Yule6School of Physics and Astronomy, University of BirminghamSchool of Chemical Engineering, University of BirminghamSchool of Chemical Engineering, University of BirminghamSchool of Chemical Engineering, University of BirminghamSchool of Chemical Engineering, University of BirminghamSchool of Physics and Astronomy, University of BirminghamSchool of Chemical Engineering, University of BirminghamAbstract Positron emission particle tracking (PEPT) is an advanced imaging technique that accurately tracks the three-dimensional spatial coordinates of a radioactively-labelled particle with sub-millimetre and sub-millisecond precision. By detecting back-to-back 511 keV gamma rays from positron-electron annihilation coincidence events, PEPT can locate particles within highly dense, opaque systems such as fluidised beds, rotating drums, and mills. Despite the progress made in enhancing the precision and accuracy of PEPT, simultaneous multiple particle tracking remains a significant challenge, particularly in high-noise environments. This paper introduces T-PEPT, a novel algorithm that leverages topological data analysis-a relatively new field of applied mathematics that explores the underlying ’shape’ of data through techniques like persistence homology. By creating simplicial complexes and applying persistence homology to PEPT point data, T-PEPT demonstrates highly effective performance in multiple-particle tracking, especially in scenarios with high noise. When benchmarked against existing PEPT algorithms using a widely recognised standard framework, T-PEPT consistently maintains sub-millimetre spatial and sub-millisecond temporal precision in nearly all cases, demonstrating its robustness and accuracy. For Data availability for T-PEPT, please use the GitHub repository: https://github.com/uob-positron-imaging-centre/pept .https://doi.org/10.1038/s41598-025-97175-0 |
| spellingShingle | Jack A. Sykes Andrei L. Nicuşan Dominik Werner Matthew T. Herald Daniel Weston Tzany Kokalova Wheldon Christopher R. K. Windows-Yule A topological approach to positron emission particle tracking for finding multiple particles in high noise environments Scientific Reports |
| title | A topological approach to positron emission particle tracking for finding multiple particles in high noise environments |
| title_full | A topological approach to positron emission particle tracking for finding multiple particles in high noise environments |
| title_fullStr | A topological approach to positron emission particle tracking for finding multiple particles in high noise environments |
| title_full_unstemmed | A topological approach to positron emission particle tracking for finding multiple particles in high noise environments |
| title_short | A topological approach to positron emission particle tracking for finding multiple particles in high noise environments |
| title_sort | topological approach to positron emission particle tracking for finding multiple particles in high noise environments |
| url | https://doi.org/10.1038/s41598-025-97175-0 |
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