A Multi-Rate State Observer for Visual Tracking of Magnetic Micro-Agents using 2D Slow Medical Imaging Modalities

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dc.contributor.authorKaya, Mert
dc.contributor.authorDenasi, Alper
dc.contributor.authorScheggi, Stefano
dc.contributor.authorAgbahca, Erdem
dc.contributor.authorYoon, ChangKyu
dc.contributor.authorGracias, David H.
dc.contributor.authorMisra, Sarthak
dc.date.accessioned2020-03-26T19:52:42Z
dc.date.available2020-03-26T19:52:42Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.description25th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) -- OCT 01-05, 2018 -- Madrid, SPAINen_US
dc.description.abstractMinimally invasive surgery can benefit greatly from utilizing micro-agents. These miniaturized agents need to be clearly visualized and precisely controlled to ensure the success of the surgery. Since medical imaging modalities suffer from low acquisition rate, multi-rate sampling methods can be used to estimate the intersample states of micro-agents. Hence, the sampling rate of the controller can be virtually increased even if the position data is acquired using a slow medical imaging modality. This study presents multi-rate Luenberger and Kalman state estimators for visual tracking of microagents. The micro-agents are tracked using sum of squared differences and normalized cross correlation based visual tracking. Further, the outputs of the two methods are merged to minimize the tracking error and prevent tracking failures. During the experiments, the micro-agents with different geometrical shapes and sizes are imaged using a 2D ultrasound machine and a microscope, and manipulated using electromagnetic coils. The multi-rate state estimation accuracy is measured using a high speed camera. The precision of the tracking and multi-rate state estimation are verified experimentally under challenging conditions. For this purpose, an elliptical shaped magnetic micro-agent with a length of 48 pixels is used. Maximum absolute error in x and y axes are 2:273 and 2:432 pixels for an 8 -fold increase of the sample rate (25 frames per second), respectively. During the experiments, it was observed that the micro-agents could be tracked more reliably using normalized cross correlation based visual tracking and intersample states could be estimated more accurately using Kalman state estimator. Experimental results show that the proposed method could be used to track micro-agents in medical imaging modalities and estimate system states at intermediate time instants in real-time.en_US
dc.description.sponsorshipIEEE Robot & Automat Soc, IEEE Ind Elect Soc, Robot Soc Japan, Soc Instrument & Control Engineers, New Technol Fdn, IEEE, Adept MobileRobots, Willow Garage, Aldebaran Robot, Natl Instruments, Reflexxes GmbH, Schunk Intec S L U, Univ Carlos III Madrid, BOSCH, JD COM, Pal Robot, KUKA, Santander, Squirrel AI Learning, Baidu, Generat Robots, KINOVA Robot, Ouster, Univ Pablo Olavide Sevilla, Rapyuta Robot, SICK, TOYOTA, UP, Amazon, ARGO, Built Robot, Disney Res, Easy Mile, Hitachi, Robot, Khalifa Univ, Magazino, MathWorks, New Dexterity, Schunk, nuTonomy, PILZ, Prophesee, Rootnik, Saga Robot, Shadow, Soft Bank Robot, Anyverse, GalTech, Generat Robot, IEEE CAA Journal Automatica Sinica, Sci Robot, AAAS, TERASen_US
dc.description.sponsorshipEuropean Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation programmeEuropean Research Council (ERC) [638428]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [RO1EB017742]en_US
dc.description.sponsorshipM. Kaya, A. Denasi, S. Scheggi, and S. Misra are affiliated with the Surgical Robotics Laboratory, Department of Biomechanical Engineering, University of Twente, The Netherlands. M. Kaya, A. Denasi and S. Misra are also affiliated with the Department of Biomedical Engineering, University of Groningen and University Medical Centre Groningen, The Netherlands. Erdem Agbahca is affiliated with Department of Computer Engineering, Faculty of Technology, Selcuk University, Turkey. ChangKyu Yoon and D.H. Gracias are with the Department of Materials Science and Engineering, The Johns Hopkins University, USA. D.H. Gracias is also affiliated with the Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, USA. This project (ROBOTAR) has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation programme (Grant Agreement #638428). We also acknowledge support in part from the National Institutes of Health under Award RO1EB017742. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.en_US
dc.identifier.endpage5393en_US
dc.identifier.isbn978-1-5386-8094-0
dc.identifier.issn2153-0858en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage5386en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/36251
dc.identifier.wosWOS:000458872704132en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)en_US
dc.relation.ispartofseriesIEEE International Conference on Intelligent Robots and Systems
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleA Multi-Rate State Observer for Visual Tracking of Magnetic Micro-Agents using 2D Slow Medical Imaging Modalitiesen_US
dc.typeConference Objecten_US

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