{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T19:26:12Z","timestamp":1771356372424,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1013955","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T00:00:00Z","timestamp":1771286400000}}],"reference-count":41,"publisher":"Public Library of Science (PLoS)","issue":"2","license":[{"start":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T00:00:00Z","timestamp":1770681600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100009633","name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","doi-asserted-by":"publisher","award":["R01HD110170"],"award-info":[{"award-number":["R01HD110170"]}],"id":[{"id":"10.13039\/100009633","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012851","name":"Thomas Harriot College of Arts and Sciences, East Carolina University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100012851","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100019661","name":"Division of Research, Economic Development and Engagement, East Carolina University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100019661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Since the 1980s, semi-automated sperm motility analysis of phase contrast microscopy videos has been used to measure and categorize sperm motility patterns. Motility categories are determined from various kinematic parameters such as Curvilinear Velocity (VCL) and Beat Cross Frequency (BCF). These measures ultimately rely on the quality of the tracking for each individual sperm in the microscopy video. However, common approaches to sperm tracking require sample dilution and shortening the time window of observation (less than 1 to 2 seconds) to avoid tracking errors that occur when sperm cross paths. The post-ejaculatory lifespan of sperm can exceed several hours to days in some species, and long-term adaptive changes in motility pattern may be an important distinguishing factor for predictive modeling of sperm fertilizing competence. Improving the predictive value of computer assisted semen analysis will require accurate tracking of sperm trajectories over physiologically-relevant time scales and at the high cell densities typically found in semen. In this work, we identify a framework for accurately assessing the quality of sperm trajectory tracking that is independent of standard motility measures. We utilize cell tracking metrics adapted from the more common task of tracking adherent somatic cells and propose modifications based on the unique challenges of sperm video-microscopy. We also provide a small dataset of microscopy videos that includes 340 labeled sperm trajectories to allow for future comparisons and developments. Finally, we demonstrate that variations in configuration can lead to as much as a 30% improvement on metrics, showcasing their effectiveness at analyzing tracking quality.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1013955","type":"journal-article","created":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T18:43:38Z","timestamp":1770749018000},"page":"e1013955","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["A framework for evaluating predicted sperm trajectories in crowded microscopy videos"],"prefix":"10.1371","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1278-2965","authenticated-orcid":true,"given":"David","family":"Hart","sequence":"first","affiliation":[]},{"given":"Kylie","family":"Cashwell","sequence":"additional","affiliation":[]},{"given":"Anita","family":"Bhandari","sequence":"additional","affiliation":[]},{"given":"Jayath","family":"Premasinghe","sequence":"additional","affiliation":[]},{"given":"Cameron","family":"Schmidt","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2026,2,10]]},"reference":[{"issue":"6","key":"pcbi.1013955.ref001","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1071\/RD17420","article-title":"CASA: tracking the past and plotting the future","volume":"30","author":"MT Gallagher","year":"2018","journal-title":"Reprod Fertil Dev."},{"issue":"1","key":"pcbi.1013955.ref002","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1006691","article-title":"OpenCASA: a new open-source and scalable tool for sperm quality analysis","volume":"15","author":"C Alquezar-Baeta","year":"2019","journal-title":"PLoS Comput Biol."},{"issue":"10","key":"pcbi.1013955.ref003","doi-asserted-by":"crossref","first-page":"860","DOI":"10.1002\/mrd.22663","article-title":"Chang\u2019s meaning of capacitation: a molecular perspective","volume":"83","author":"MG Gervasi","year":"2016","journal-title":"Mol Reprod Dev."},{"issue":"6","key":"pcbi.1013955.ref004","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1093\/humupd\/dmn029","article-title":"Control of hyperactivation in sperm","volume":"14","author":"SS Suarez","year":"2008","journal-title":"Hum Reprod Update."},{"key":"pcbi.1013955.ref005","volume-title":"WHO laboratory manual for the examination and processing of human semen","author":"WH Organization","year":"2021"},{"issue":"24","key":"pcbi.1013955.ref006","doi-asserted-by":"crossref","first-page":"248401","DOI":"10.1103\/PhysRevLett.130.248401","article-title":"Biphasic chemokinesis of mammalian sperm","volume":"130","author":"M Zaferani","year":"2023","journal-title":"Phys Rev Lett."},{"key":"pcbi.1013955.ref007","first-page":"2025","article-title":"Sperm hyperactivation drives a circling-and-wandering migration strategy","author":"M Zaferani","year":"2025","journal-title":"bioRxiv."},{"issue":"4","key":"pcbi.1013955.ref008","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1012865","article-title":"Modeling diffusive search by non-adaptive sperm: Empirical and computational insights","volume":"21","author":"BM Brisard","year":"2025","journal-title":"PLoS Comput Biol."},{"issue":"5","key":"pcbi.1013955.ref009","doi-asserted-by":"crossref","first-page":"539","DOI":"10.3390\/e27050539","article-title":"A two-state random walk model of sperm search on confined domains","volume":"27","author":"M Bier","year":"2025","journal-title":"Entropy (Basel)."},{"issue":"1","key":"pcbi.1013955.ref010","doi-asserted-by":"crossref","first-page":"10","DOI":"10.3390\/cells8010010","article-title":"SpermQ\u2013A simple analysis software to comprehensively study flagellar beating and sperm steering","volume":"8","author":"JN Hansen","year":"2018","journal-title":"Cells."},{"key":"pcbi.1013955.ref011","doi-asserted-by":"crossref","unstructured":"Fujii T, Nakagawa H, Takeshima T, Yumura Y, Hamagami T. Automated sperm assessment framework and neural network specialized for sperm video recognition. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV). 2024. p. 7675\u201384.","DOI":"10.1109\/WACV57701.2024.00750"},{"issue":"7","key":"pcbi.1013955.ref012","doi-asserted-by":"crossref","first-page":"1010","DOI":"10.1038\/s41592-023-01879-y","article-title":"The cell tracking challenge: 10 years of objective benchmarking","volume":"20","author":"M Ma\u0161ka","year":"2023","journal-title":"Nat Methods."},{"issue":"4","key":"pcbi.1013955.ref013","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1007\/s11263-020-01393-0","article-title":"MOTChallenge: a benchmark for single-camera multiple target tracking","volume":"129","author":"P Dendorfer","year":"2020","journal-title":"Int J Comput Vis."},{"key":"pcbi.1013955.ref014","doi-asserted-by":"crossref","unstructured":"Bragantini J, Lange M, Royer L. 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