Improved particle filter algorithm combined with culture algorithm for collision Caenorhabditis elegans tracking
Abstract In order to address the issue of tracking errors of collision Caenorhabditis elegans, this research proposes an improved particle filter tracking method integrated with cultural algorithm. The particle filter algorithm is enhanced through the integration of the sine cosine algorithm, thereb...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-87970-0 |
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| author | Taoyuan Yu Xiping Xu Yuanpeng Li Ning Zhang Naiyu Zhang Xiaohui Wang |
| author_facet | Taoyuan Yu Xiping Xu Yuanpeng Li Ning Zhang Naiyu Zhang Xiaohui Wang |
| author_sort | Taoyuan Yu |
| collection | DOAJ |
| description | Abstract In order to address the issue of tracking errors of collision Caenorhabditis elegans, this research proposes an improved particle filter tracking method integrated with cultural algorithm. The particle filter algorithm is enhanced through the integration of the sine cosine algorithm, thereby facilitating uninterrupted tracking of the target C. elegans. Furthermore, the cultural algorithm is employed to facilitate recognition of the target C. elegans following a collision. In addition, this method integrates the concepts of down-sample and marking to reduce the average processing time of the image. Ultimately, the experiment was conducted on two strains of C. elegans of six ages. The experimental results demonstrate that the proposed method can accurately identify the target worm in the post-collision stage. The proposed method has the potential to be utilized in the field of worm tracking, offering a novel method into the acquisition of collision C. elegans behavior. |
| format | Article |
| id | doaj-art-c22c92f0ed8040849fe2d45fae463863 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-c22c92f0ed8040849fe2d45fae4638632025-01-26T12:28:04ZengNature PortfolioScientific Reports2045-23222025-01-0115111410.1038/s41598-025-87970-0Improved particle filter algorithm combined with culture algorithm for collision Caenorhabditis elegans trackingTaoyuan Yu0Xiping Xu1Yuanpeng Li2Ning Zhang3Naiyu Zhang4Xiaohui Wang5School of Optoelectronic Engineering, Changchun University of Science and TechnologySchool of Optoelectronic Engineering, Changchun University of Science and TechnologyLaboratory of Chemical Biology, Changchun Institute of Applied Chemistry, Chinese Academy of SciencesSchool of Optoelectronic Engineering, Changchun University of Science and TechnologySchool of Optoelectronic Engineering, Changchun University of Science and TechnologyLaboratory of Chemical Biology, Changchun Institute of Applied Chemistry, Chinese Academy of SciencesAbstract In order to address the issue of tracking errors of collision Caenorhabditis elegans, this research proposes an improved particle filter tracking method integrated with cultural algorithm. The particle filter algorithm is enhanced through the integration of the sine cosine algorithm, thereby facilitating uninterrupted tracking of the target C. elegans. Furthermore, the cultural algorithm is employed to facilitate recognition of the target C. elegans following a collision. In addition, this method integrates the concepts of down-sample and marking to reduce the average processing time of the image. Ultimately, the experiment was conducted on two strains of C. elegans of six ages. The experimental results demonstrate that the proposed method can accurately identify the target worm in the post-collision stage. The proposed method has the potential to be utilized in the field of worm tracking, offering a novel method into the acquisition of collision C. elegans behavior.https://doi.org/10.1038/s41598-025-87970-0Collision C. Elegans trackingParticle filterSine cosine algorithmCultural algorithmVisual object tracking |
| spellingShingle | Taoyuan Yu Xiping Xu Yuanpeng Li Ning Zhang Naiyu Zhang Xiaohui Wang Improved particle filter algorithm combined with culture algorithm for collision Caenorhabditis elegans tracking Scientific Reports Collision C. Elegans tracking Particle filter Sine cosine algorithm Cultural algorithm Visual object tracking |
| title | Improved particle filter algorithm combined with culture algorithm for collision Caenorhabditis elegans tracking |
| title_full | Improved particle filter algorithm combined with culture algorithm for collision Caenorhabditis elegans tracking |
| title_fullStr | Improved particle filter algorithm combined with culture algorithm for collision Caenorhabditis elegans tracking |
| title_full_unstemmed | Improved particle filter algorithm combined with culture algorithm for collision Caenorhabditis elegans tracking |
| title_short | Improved particle filter algorithm combined with culture algorithm for collision Caenorhabditis elegans tracking |
| title_sort | improved particle filter algorithm combined with culture algorithm for collision caenorhabditis elegans tracking |
| topic | Collision C. Elegans tracking Particle filter Sine cosine algorithm Cultural algorithm Visual object tracking |
| url | https://doi.org/10.1038/s41598-025-87970-0 |
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