[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124089-en":3,"doc-seo-124089-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124089,687197207639,"Asher","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Machine Learning Based Tool for Automated Sperm Cell Tracking and Sperm Bundle Detection","Study presents a machine learning-based method for automated detection and tracking of sperm cells in microscopic video recordings, enabling reconstruction of individual cell trajectories and analysis of sperm bundle dynamics. The pipeline first identifies sperm cells across consecutive frames, then applies a classification algorithm to separate solitary sperm cells, adjacent cell clusters, and cohesive sperm bundles, addressing gaps in prior approaches. Movement is quantified using conventional velocity metrics including VSL, VAP, and VCL for both cells and bundles. The resulting tool improves accuracy and efficiency for studying sperm motility and aggregation in reproductive biology and fertility research.","Machine Learning Based Tool for Automated Sperm Cell Tracking and Sperm Bundle Detection  \nJakub Horenin1 , Veronika Magdanz2, Islam S. M. Khalil3 , Anke Klingner4, Alexander Kovalenko1, and Miroslav ˇCepek 1(B)  \n1 Faculty of Information Technology, Czech Technical University in Prague, Prague,  \nCzech Republic  \n[cepekmir@fit.cvut.cz](cepekmir@fit.cvut.cz)  \n2 Department of Systems Design Engineering, Waterloo Institute for  \nNanotechnology, University of Waterloo, Waterloo, Canada  \n3 Department of Biomechanical Engineering, University of Twente, Twente,  \nThe Netherlands  \n4 Department of Physics, German University in Cairo, Cairo, Egypt  \nAbstract. This study introduces a novel machine learning-based methodology for automated detection and tracking of sperm cells within microscopic video recordings, aiming to elucidate the dynamics and motion patterns of individual sperm cells as well as sperm cell bundles. At first, the method identifies sperm cells across successive frames within a video sequence, facilitating the reconstruction of each cell’s trajectory over time. Subsequently, we introduce a classification algorithm that distinguishes between solitary sperm cells, clusters of adjacent cells, and cohesive sperm cell bundles, addressing a gap in existing methodologies. Finally, we employ three conventional metrics for velocity assessment: Straight Line Velocity (VSL) and Average Path Velocity (VAP) and Curvilinear velocity (VCL), to quantify the movement speed of both individual sperm cells and bundles. The approach represents a significant advancement in the automated analysis of sperm motility and aggregation phenomena, providing a robust tool for researchers to study sperm behavior with enhanced accuracy and efficiency. The integration of machine learning techniques in sperm cell detection and tracking offers promising insights into reproductive biology and fertility studies. [https://gitlab](https://gitlab).fi[t.cvut.cz/horenjak/sperm](t.cvut.cz/horenjak/sperm cell)[ ](t.cvut.cz/horenjak/sperm cell)[cell](t.cvut.cz/horenjak/sperm cell) tracking app [https://](https://)  \napps.datalab.fi[t.cvut.cz/sperm](t.cvut.cz/sperm tracking/)[ ](t.cvut.cz/sperm tracking/)[tracking/](t.cvut.cz/sperm tracking/)  \nKeywords: Sperm Cell Tracking · Motion Dynamics · Bundle  \nFormation · Bundle Detection · Kalman Filter  \nSupplementary Information The online version contains supplementary material available at [https://doi.org/10.1007/978-3-031-70381-2](https://doi.org/10.1007/978-3-031-70381-2) 2.  \n􀀂c The Author(s), under exclusive license to Springer Nature Switzerland AG 2024  \nA. Bifet et al. (Eds.): ECML PKDD 2024, LNAI 14950, pp. 19–32, 2024 .  \n[https://doi.org/10.1007/978-3-031-70381-2](https://doi.org/10.1007/978-3-031-70381-2_2)[_](https://doi.org/10.1007/978-3-031-70381-2_2)[2](https://doi.org/10.1007/978-3-031-70381-2_2)  \n20 J. Horenin et al.  \n1 Introduction  \nAdvanced machine learning techniques in the era of data abundance offer numerous advantages across various fields. However, for almost any sort of efficient decision-making process or predictive analysis, the quality of data remains crucial. Due to its peculiar characteristics and complexity, biological data, including microscopic images and recorded videos, stand apart from data encountered in daily life like images of common objects, text, or music. Particularly, video recordings of motile sperm cells is a good example to expose biological data complexity. Due to the nature of video recording with a microscope, the data often appear to be noisy, containing artifacts and/or blurred objects. Certain attributes of the video, that are of interest to biologists are not labeled, therefore for many tasks, a straightforward approach such as supervised learning can’tbe applied. On the other hand, labeling of these data is extremely demanding, as it requires domain expert knowledge and some of the events that need tobe labeled are extremely rare. Even though, numerous computer-assisted","cbCairVtgiXNVEgu","https://ap.wps.com/l/cbCairVtgiXNVEgu","pdf",1201412,1,14,"English","en",105,"# Abstract\n# Introduction\n## Challenges of biological video data\n## Importance of sperm bundle detection\n## Links to microrobots and collective behavior\n## Proposed method and tool overview","[{\"question\":\"How does the tool track sperm cells in microscopic videos?\",\"answer\":\"It identifies sperm cells across successive frames and reconstructs each cell’s trajectory over time.\"},{\"question\":\"What types of sperm groupings does the classification algorithm distinguish?\",\"answer\":\"It separates solitary sperm cells, clusters of adjacent cells, and cohesive sperm cell bundles.\"},{\"question\":\"Which metrics are used to quantify sperm movement speed?\",\"answer\":\"The method uses Straight Line Velocity (VSL), Average Path Velocity (VAP), and Curvilinear velocity (VCL) for both individual cells and bundles.\"}]","Machine Learning Based Tool for Automated Sperm Cell Tracking and Sperm Bundle Detection | PDF",1785820267,35,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-based-tool-for-automated-sperm-cell-tracking-and-sperm-bundle-detection","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-based-tool-for-automated-sperm-cell-tracking-and-sperm-bundle-detection/124089/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"How does the tool track sperm cells in microscopic videos?","Question",{"text":75,"@type":76},"It identifies sperm cells across successive frames and reconstructs each cell’s trajectory over time.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What types of sperm groupings does the classification algorithm distinguish?",{"text":80,"@type":76},"It separates solitary sperm cells, clusters of adjacent cells, and cohesive sperm cell bundles.",{"name":82,"@type":73,"acceptedAnswer":83},"Which metrics are used to quantify sperm movement speed?",{"text":84,"@type":76},"The method uses Straight Line Velocity (VSL), Average Path Velocity (VAP), and Curvilinear velocity (VCL) for both individual cells and bundles.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]