{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/robust-and-highly-performant-ring-detection","title":"Robust and highly performant ring detection algorithm for 3d particle tracking using 2d microscope imaging","arxiv_id":"1310.1371","date":"2013-10-02","proceeding":null,"authors":["Eldad Afik"],"abstract":"Three-dimensional particle tracking is an essential tool in studying dynamics\nunder the microscope, namely, fluid dynamics in microfluidic devices, bacteria\ntaxis, cellular trafficking. The 3d position can be determined using 2d imaging\nalone by measuring the diffraction rings generated by an out-of-focus\nfluorescent particle, imaged on a single camera. Here I present a ring\ndetection algorithm exhibiting a high detection rate, which is robust to the\nchallenges arising from ring occlusion, inclusions and overlaps, and allows\nresolving particles even when near to each other. It is capable of real time\nanalysis thanks to its high performance and low memory footprint. The proposed\nalgorithm, an offspring of the circle Hough transform, addresses the need to\nefficiently trace the trajectories of many particles concurrently, when their\nnumber in not necessarily fixed, by solving a classification problem, and\novercomes the challenges of finding local maxima in the complex parameter space\nwhich results from ring clusters and noise. Several algorithmic concepts\nintroduced here can be advantageous in other cases, particularly when dealing\nwith noisy and sparse data. The implementation is based on open-source and\ncross-platform software packages only, making it easy to distribute and modify.\nIt is implemented in a microfluidic experiment allowing real-time\nmulti-particle tracking at 70 Hz, achieving a detection rate which exceeds 94%\nand only 1% false-detection.","url_abs":"http://arxiv.org/abs/1310.1371v3","url_pdf":"http://arxiv.org/pdf/1310.1371v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"robust-and-highly-performant-ring-detection","repo_url":"https://github.com/eldad-a/ridge-directed-ring-detector","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}