[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121235-en":3,"doc-seo-121235-105":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":20,"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},121235,13056703019404,"Miles","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Advancing Microrobotics for Biomedical Applications through Machine Learning - Assignment of master’s thesis","The thesis assignment investigates how machine learning can advance microrobotics for biomedical use, focusing on biological microrobots in drug-delivery scenarios. It targets understanding and controlling organisms such as sperm cells and MagnetoSperm, improving both detection and external regulation of microrobots including micro-screws in blood. Core research lines include ML-based analysis of sperm-cell dynamics using computer vision and prediction methods, development of efficient object detection and trajectory prediction models, and evaluation of deep symbolic regression to extract governing equations for reliable control.","Title:  \nAssignment of master’s thesis  \nAdvancing Microrobotics for Biomedical Applications through Machine Learning  \nStudent: Bc. Daniil Pastukhov  \nSupervisor: Mgr. Alexander Kovalenko, Ph. D.  \nStudy program: Informatics  \nBranch / specialization: Knowledge Engineering  \nDepartment: Department of Applied Mathematics  \nValidity: until the end of summer semester 2024/2025  \nInstructions  \nCzech Technical University (CTU) and Twente University are collaborating to investigate the potential of machine learning (ML) in advancing micro-robotics, particularly in the context of biological microrobots for drug delivery applications.  \nObjective:  \nThe primary objective of this thesis is to explore the use of ML techniques in understanding and controlling biological microrobots, such as sperm cells and MagnetoSperm, as well as improving the detection and external control of microrobots like micro-screws in the bloodstream.  \nResearch Areas:  \nDynamics of Sperm Cells as Microrobots: The thesis will apply ML techniques, including image processing, object detection, object tracking, next-frame prediction, and symbolic regression, to better comprehend the dynamics of sperm cells for potential microrobot applications in targeted drug delivery.  \nMagnetoSperm Microrobots: The research will extend ML techniques to MagnetoSperm microrobots, sperm cells coated with magnetic nanoparticles controllable via a weak external magnetic field. By analyzing and modeling their behavior, the aim is to develop  \nElectronically approved by Ing. Magda Friedjungová, Ph.D. on 10 May 2023 in Prague.  \naccurate and efficient control methods for improved biomedical applications.  \nDetection of Microscrews and Other Microrobots: The thesis will explore the role of ML in detecting and tracking microrobots like micro-screws within the body, which is essential for their safe and effective use in medical procedures.  \nExternal Control of Microrobots in the Bloodstream: The research will focus on developing ML algorithms for improved external control of microrobots navigating the complex arterial structures within the bloodstream, enhancing precision and safety.  \nTo successfully complete the diploma thesis the following research steps should be  \ntaken:  \n-Conduct a literature review on the fundamentals of computer vision (landmark detection, object detection, object tracking, image augmentation), machine learningbased motion control, and deep symbolic regression;  \n-Preprocess the data obtained from scientific partners;  \n-Train, evaluate, and optimize landmark detection model;  \n-From the obtained landmarks evaluate microswimmers' dynamics;  \n-Train, evaluate, and optimize object detection model;  \n-Train, evaluate, and optimize trajectory prediction model for better navigation in the bloodstream;  \n-Explore the possibilities of deep symbolic regression on the data to extract governing equations;  \nLiterature:  \n-Khalil, Islam SM, et al. \"MagnetoSperm: A microrobot that navigates using weak magnetic fields.\" Applied Physics Letters 104.22 (2014): 223701.  \n-Magdanz, Veronika, et al. \"IRONSperm: Sperm-templated soft magnetic microrobots.\"Science Advances 6.28 (2020): eaba5855 .  \n-Zhang, Kaixuan, et al. \"Locomotion of bovine spermatozoa during the transition from individual cells to bundles.\" Proceedings of the National Academy of Sciences 120.3 (2023): e2211911120 .  \nElectronically approved by Ing. Magda Friedjungová, Ph.D. on 10 May 2023 in Prague.  \nMaster’s thesis  \nAdvancing Microrobotics for Biomedical Applications through Machine Learning  \nBc . Daniil Pastukhov  \nDepartment of Department of Applied Mathematics Supervisor: Mgr. Alexander Kovalenko, Ph.D.  \nJanuary 11, 2024  \nDeclaration  \nI hereby declare that the presented thesis is my own work and that I have cited all sources of information in accordance with the Guideline for adhering to ethical principles when elaborating an academic final thesis.  \nI acknowledge that my thesis is subject to the rights ","cbCaiq5vri0hbiiN","https://ap.wps.com/l/cbCaiq5vri0hbiiN","pdf",7266581,1,55,"English","en",105,"# Objective\n## Research Areas\n## Research Steps\n## Literature\n# Declaration\n## Citation of this thesis","[{\"question\":\"What is the main objective of the master’s thesis?\",\"answer\":\"The thesis explores machine learning techniques for understanding and controlling biological microrobots, improving detection and external control of microrobots in biomedical contexts such as drug delivery and blood navigation.\"},{\"question\":\"Which microrobots and application scenarios are covered?\",\"answer\":\"The work covers sperm cells as microrobots, MagnetoSperm microrobots (sperm coated with magnetic nanoparticles), and microrobots like micro-screws within the bloodstream.\"},{\"question\":\"What research methods and ML tasks will be applied?\",\"answer\":\"The thesis uses computer-vision ML methods such as landmark detection, object detection, object tracking, next-frame/trajectory prediction, and deep symbolic regression to derive governing equations from data.\"}]","Advancing Microrobotics for Biomedical Applications through Machine Learning - 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