{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T13:10:10Z","timestamp":1791378610563,"version":"4.3.2"},"reference-count":64,"publisher":"The Royal Society","issue":"233","license":[{"start":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T00:00:00Z","timestamp":1764720000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T00:00:00Z","timestamp":1764720000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Single-cell analysis enables the extraction of detailed information from individual cells that bulk analysis cannot provide. Convolutional neural networks (CNNs) hold great potential in overcoming the challenges deriving from single-cell tracking, providing a powerful framework for automated and high-throughput analysis. In this field, sperm analysis for male infertility assessment finds its application. Indeed, evaluating sperm quality indicators of motility and morphology is essential for this purpose, although the gold standard analysis still relies on manual assessment. Here, we propose an automated, label-free method for sperm rolling detection and analysis based on CNNs. Brightfield image sequences of swimming sperm are captured with the same magnification for both motility and morphology analysis. This workflow is based on sperm head detection, identifying\u2014for the first time\u2014the three-dimensional configuration assumed during the motion. Following steps of tracking and segmentation enable the simultaneous extraction of kinematic and morphometric parameters from the head contour across frame sequences, providing additional information related to sperm rolling. The approach successfully captures motion changes, demonstrating its ability to perform advanced sperm characterization. Correlating kinematics and morphology at the single-cell level, the proposed method enhances insights into motility and provides more accurate sperm characterization.<\/jats:p>","DOI":"10.1098\/rsif.2025.0160","type":"journal-article","created":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T20:02:43Z","timestamp":1764878563000},"source":"Crossref","is-referenced-by-count":1,"title":["Single-cell three-dimensional tracking by means of neural networks for sperm rolling classification"],"prefix":"10.1098","volume":"22","author":[{"given":"Claudia","family":"De Clemente","sequence":"first","affiliation":[{"name":"University of Naples Federico II 1 , ,","place":["Naples, Italy"],"department":["Interdisciplinary Research Centre on Biomaterials (CRIB) and Department of Chemical, Materials and Production Engineering (DICMAPI)"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1170-3425","authenticated-orcid":false,"given":"Maria Isabella","family":"Maremonti","sequence":"additional","affiliation":[{"name":"University of Naples Federico II 1 , ,","place":["Naples, Italy"],"department":["Interdisciplinary Research Centre on Biomaterials (CRIB) and Department of Chemical, Materials and Production Engineering (DICMAPI)"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Dannhauser","sequence":"additional","affiliation":[{"name":"University of Naples Federico II 1 , ,","place":["Naples, Italy"],"department":["Interdisciplinary Research Centre on Biomaterials (CRIB) and Department of Chemical, Materials and Production Engineering (DICMAPI)"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paolo Antonio","family":"Netti","sequence":"additional","affiliation":[{"name":"University of Naples Federico II 1 , ,","place":["Naples, Italy"],"department":["Interdisciplinary Research Centre on Biomaterials (CRIB) and Department of Chemical, Materials and Production Engineering (DICMAPI)"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5436-3857","authenticated-orcid":false,"given":"Filippo","family":"Causa","sequence":"additional","affiliation":[{"name":"University of Naples Federico II 1 , ,","place":["Naples, Italy"],"department":["Interdisciplinary Research Centre on Biomaterials (CRIB) and Department of Chemical, Materials and Production Engineering (DICMAPI)"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"175","published-online":{"date-parts":[[2025,12,3]]},"reference":[{"key":"2026030423475881800_R1","doi-asserted-by":"crossref","DOI":"10.3390\/cells9091993","article-title":"Single-cell analysis","volume":"9","author":"Santra","year":"2020","journal-title":"Cells"},{"key":"2026030423475881800_R2","doi-asserted-by":"crossref","DOI":"10.3390\/ijms19103143","article-title":"Current trends of microfluidic single-cell technologies","volume":"19","author":"Shinde","year":"2018","journal-title":"Int. J. Mol. Sci."},{"key":"2026030423475881800_R3","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/S0092-8674(00)81280-5","article-title":"Cell migration: a physically integrated molecular process","volume":"84","author":"Lauffenburger","year":"1996","journal-title":"Cell"},{"key":"2026030423475881800_R4","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1038\/nrc.2018.15","article-title":"Cell motility in cancer invasion and metastasis: insights from simple model organisms","volume":"18","author":"Stuelten","year":"2018","journal-title":"Nat. Rev. Cancer"},{"key":"2026030423475881800_R5","doi-asserted-by":"crossref","first-page":"29","DOI":"10.2147\/IJGM.S241099","article-title":"Some of the factors involved in male infertility: a prospective review","volume":"13","author":"Babakhanzadeh","year":"2020","journal-title":"Int. J. Gen. Med."},{"key":"2026030423475881800_R6","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pmed.1001356","article-title":"National, regional, and global trends in infertility prevalence since 1990: a systematic analysis of 277 health surveys","volume":"9","author":"Mascarenhas","year":"2012","journal-title":"PLoS Med."},{"key":"2026030423475881800_R7","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.68693","article-title":"Rolling controls sperm navigation in response to the dynamic rheological properties of the environment","volume":"10","author":"Zaferani","year":"2021","journal-title":"eLife"},{"key":"2026030423475881800_R8","doi-asserted-by":"crossref","DOI":"10.1098\/rsif.2020.0525","article-title":"Flagellar kinematics reveals the role of environment in shaping sperm motility","volume":"17","author":"Guasto","year":"2020","journal-title":"J. R. Soc. Interface"},{"key":"2026030423475881800_R9","article-title":"Swimming by spinning: spinning-top type rotations regularize sperm swimming into persistently progressive paths in 3D","volume":"12","author":"Ren","year":"2025","journal-title":"Adv. Sci"},{"key":"2026030423475881800_R10","volume-title":"WHO laboratory manual for the examination and processing of human semen","author":"Sexual and Reproductive Health and Research (SRH)","year":"2021","edition":"6th"},{"key":"2026030423475881800_R11","doi-asserted-by":"crossref","first-page":"3069","DOI":"10.21037\/tau-21-276","article-title":"The validity and reliability of computer-aided semen analyzers in performing semen analysis: a systematic review","volume":"10","author":"Finelli","year":"2021","journal-title":"Transl. Androl. Urol."},{"key":"2026030423475881800_R12","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1111\/and.12093","article-title":"Computer-aided sperm analysis: past, present and future","volume":"46","author":"Lu","year":"2014","journal-title":"Andrologia"},{"key":"2026030423475881800_R13","doi-asserted-by":"crossref","DOI":"10.1140\/epje\/s10189-021-00076-z","article-title":"Reconstruction of the three-dimensional beat pattern underlying swimming behaviors of sperm","volume":"44","author":"Gong","year":"2021","journal-title":"Eur. Phys. J. E"},{"key":"2026030423475881800_R14","doi-asserted-by":"crossref","first-page":"102524","DOI":"10.1016\/j.xcrp.2025.102524","article-title":"Superhelix flow structures drive sperm locomotion","volume":"6","author":"Akbaridoust","year":"2025","journal-title":"Cell Rep. Phys. Sci."},{"key":"2026030423475881800_R15","doi-asserted-by":"crossref","DOI":"10.1002\/jcla.24794","article-title":"Effects of six kinds of sperm staining methods on human sperm size and evaluation of their staining effects","volume":"36","author":"Xu","year":"2022","journal-title":"J. Clin. Lab. Anal."},{"key":"2026030423475881800_R16","doi-asserted-by":"crossref","first-page":"1473","DOI":"10.15517\/rbt.v67i6.35151","article-title":"Sperm kinematics and morphometric subpopulations analysis with CASA systems: a review","volume":"67","author":"Valverde Abarca","year":"2019","journal-title":"Rev. Biol. 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An opportunity for low- and middle-income countries","volume":"13","author":"Onofre","year":"2021","journal-title":"Facts Views Vis. Obgyn."},{"key":"2026030423475881800_R20","doi-asserted-by":"crossref","first-page":"189","DOI":"10.22358\/jafs\/127691\/2020","article-title":"The application of computer-assisted semen analysis (CASA) technology to optimise semen evaluation. A review","volume":"29","author":"Valverde","year":"2020","journal-title":"J. Anim. Feed Sci."},{"key":"2026030423475881800_R21","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1111\/j.2042-3306.2011.00523.x","article-title":"Influence of counting chamber type on CASA outcomes of equine semen analysis","volume":"44","author":"Hoogewijs","year":"2012","journal-title":"Equine Vet. 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(doi:10.1109\/SIBGRAPI55357.2022.9991745)","DOI":"10.1109\/SIBGRAPI55357.2022.9991745"},{"key":"2026030423475881800_R30","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.compbiomed.2019.04.030","article-title":"A novel deep learning method for automatic assessment of human sperm images","volume":"109","author":"Javadi","year":"2019","journal-title":"Comput. Biol. Med."},{"key":"2026030423475881800_R31","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2019.103342","article-title":"Deep learning for the classification of human sperm","volume":"111","author":"Riordon","year":"2019","journal-title":"Comput. Biol. 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Lett."},{"key":"2026030423475881800_R41","doi-asserted-by":"crossref","unstructured":"Melendez\n              R\n            , CastanonCB, Medina-RodriguezR. 2021Sperm cell segmentation in digital micrographs based on convolutional neural networks using U-net architecture. InIEEE 34th Int. Symp. on Computer-Based Medical Systems, Aveiro, Portugal, 7\u20139 June 2021, pp. 91\u201396. (doi:10.1109\/CBMS52027.2021.00084)","DOI":"10.1109\/CBMS52027.2021.00084"},{"key":"2026030423475881800_R42","first-page":"1133","article-title":"Deep learning-based classification and segmentation of sperm head and flagellum for image-based flow cytometry","volume":"27","author":"Hern\u00e1ndez-Herrera","year":"2023","journal-title":"Comput. Sist."},{"key":"2026030423475881800_R43","doi-asserted-by":"crossref","first-page":"1767","DOI":"10.1017\/S1431927622012132","article-title":"Fast noninvasive morphometric characterization of free human sperms using deep learning","volume":"28","author":"Liu","year":"2022","journal-title":"Microsc. Microanal."},{"key":"2026030423475881800_R44","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.csbj.2024.02.025","article-title":"Multidimensional morphological analysis of live sperm based on multiple-target tracking","volume":"24","author":"Yang","year":"2024","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"2026030423475881800_R45","doi-asserted-by":"crossref","DOI":"10.1002\/aisy.202100200","article-title":"Simultaneous morphology, motility, and fragmentation analysis of live individual sperm cells for male fertility evaluation","volume":"4","author":"Ben-Yehuda","year":"2022","journal-title":"Adv. Intell. 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(https:\/\/arxiv.org\/abs\/1609.04747)","author":"Ruder","year":"2016"},{"key":"2026030423475881800_R50","doi-asserted-by":"crossref","DOI":"10.1155\/2008\/246309","article-title":"Evaluating multiple object tracking performance: the CLEAR MOT metrics","volume":"2008","author":"Bernardin","year":"2008","journal-title":"EURASIP J. Image Video Process."},{"key":"2026030423475881800_R51","article-title":"U-Net: convolutional networks for biomedical image segmentation. (https:\/\/arxiv.org\/abs\/1505.04597)","author":"Ronneberger","year":"2015"},{"key":"2026030423475881800_R52","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.neunet.2019.08.025","article-title":"MultiResUNet: rethinking the U-Net architecture for multimodal biomedical image segmentation","volume":"121","author":"Ibtehaz","year":"2020","journal-title":"Neural Netw."},{"key":"2026030423475881800_R53","first-page":"626","volume-title":"Medical image computing and computer assisted intervention","author":"Goos","year":"2024"},{"key":"2026030423475881800_R54","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1007\/978-3-319-67558-9_28","volume-title":"Deep learning in medical image analysis and multimodal learning for clinical decision support","author":"Sudre","year":"2017"},{"key":"2026030423475881800_R55","first-page":"740","volume-title":"Computer vision","author":"Lin","year":"2014"},{"key":"2026030423475881800_R56","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.compbiomed.2019.04.032","article-title":"Automatic segmentation of sperm\u2019s parts in microscopic images of human semen smears using concatenated learning approaches","volume":"109","author":"Movahed","year":"2019","journal-title":"Comput. Biol. Med."},{"key":"2026030423475881800_R57","doi-asserted-by":"crossref","first-page":"108172","DOI":"10.1016\/j.bspc.2025.108172","article-title":"A multi-sperm dynamic tracking algorithm based on interactive motion model","volume":"110","author":"Jiao","year":"2025","journal-title":"Biomed. Signal Process. Control"},{"key":"2026030423475881800_R58","doi-asserted-by":"crossref","DOI":"10.1002\/aisy.202500115","article-title":"Hi-LabSpermTracking: a novel and high-quality sperm tracking dataset with an advanced ensemble detection and tracking approach for real-world clinical scenarios","author":"Aktas","year":"2025","journal-title":"Adv. Intell. Syst."},{"key":"2026030423475881800_R59","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1242\/jeb.163.1.15","article-title":"Rotational movement of a spermatozoon around its long axis","volume":"163","author":"Ishijima","year":"1992","journal-title":"J. Exp. Biol."},{"key":"2026030423475881800_R60","first-page":"508","volume-title":"Revista cient\u00edfica, vol. XVII","author":"Rubio-Guill\u00e9n","year":"2007"},{"key":"2026030423475881800_R61","doi-asserted-by":"crossref","first-page":"840","DOI":"10.4103\/1008-682X.186877","article-title":"A comparative study of the morphometry of sperm head components in cattle, sheep, and pigs with a computer-assisted fluorescence method","volume":"18","author":"Y\u00e1niz","year":"2016","journal-title":"Asian J. Androl."},{"key":"2026030423475881800_R62","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.anireprosci.2013.04.002","article-title":"A comparative study of sperm morphometric subpopulations in cattle, goat, sheep and pigs using a computer-assisted fluorescence method (CASMA-F)","volume":"139","author":"Vicente-Fiel","year":"2013","journal-title":"Anim. Reprod. Sci."},{"key":"2026030423475881800_R63","article-title":"Single-cell 3D tracking by means of neural networks for sperm rolling classification. Figshare.","author":"De Clemente","year":"2025"},{"key":"2026030423475881800_R64","article-title":"Supplementary material from: Single-Cell 3D tracking by means of Neural Networks for automated sperm classification. Figshare.","author":"De Clemente","year":"2025"}],"container-title":["Journal of the Royal Society Interface"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/royalsocietypublishing.org\/rsif\/article-pdf\/doi\/10.1098\/rsif.2025.0160\/4405046\/rsif.2025.0160.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/royalsocietypublishing.org\/rsif\/article-pdf\/doi\/10.1098\/rsif.2025.0160\/4405046\/rsif.2025.0160.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T04:48:28Z","timestamp":1772686108000},"score":1,"resource":{"primary":{"URL":"https:\/\/royalsocietypublishing.org\/rsif\/article\/22\/233\/20250160\/363286\/Single-cell-three-dimensional-tracking-by-means-of"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,3]]},"references-count":64,"journal-issue":{"issue":"233","published-print":{"date-parts":[[2025,12,3]]}},"URL":"https:\/\/doi.org\/10.1098\/rsif.2025.0160","relation":{},"ISSN":["1742-5662"],"issn-type":[{"value":"1742-5662","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,3]]},"article-number":"20250160"}}