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dc.contributor.authorZhai, Xiaojun
dc.contributor.authorJaber, Fadi
dc.contributor.authorBensaali, Faycal
dc.contributor.authorMishra, Arti
dc.date.accessioned2016-11-11T16:14:24Z
dc.date.available2016-11-11T16:14:24Z
dc.date.issued2015-03-25
dc.identifier.citationZhai, X. et al. (2015) 'Hardware acceleration of an image processing system for dielectrophoretic loading of single neurons inside micro-wells of microelectrode arrays', Proceedings of the 17th UKSim-AMSS International Conference on Modelling and Simulation (UKSim), Cambridge, UK, 25-27 Marchen
dc.identifier.isbn9781479987139
dc.identifier.doi10.1109/UKSim.2015.28
dc.identifier.urihttp://hdl.handle.net/10545/620813
dc.description.abstractThis paper describes an image processing algorithm and its efficient architecture. The proposed architecture is used to process images of microelectrode arrays (MEAs) and micro-wells captured by a microscope camera in a dielectrophoresis (DEP)-based system which consists as well of digital switches for turning the DEP force 'on' or 'off'. The images are processed in order to determine if a neuron has entered any of the micro-wells in which case the corresponding switch turns 'off' the DEP force. This process must be in real-time to avoid more than one cell to be loaded in a micro-well. The proposed architecture has been successfully implemented and tested on a Zynq SoC. Results achieved have shown that the system can process one image in 9 ms which meets the minimum real-time requirements of this DEP system.
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/document/7576603/en
dc.relation.urlhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7575913en
dc.relation.urlhttp://uksim.info/uksim2015/start.pdfen
dc.subjectMicroelectrode arrayen
dc.subjectComputer architectureen
dc.subjectImage processingen
dc.subjectMicroprocessorsen
dc.titleHardware acceleration of an image processing system for dielectrophoretic loading of single neurons inside micro-wells of microelectrode arraysen
dc.typeMeetings and Proceedingsen
dc.contributor.departmentUniversity of Derbyen
dc.identifier.journalProceedings of the 17th UKSim-AMSS International Conference on Modelling and Simulation (UKSim)en
html.description.abstractThis paper describes an image processing algorithm and its efficient architecture. The proposed architecture is used to process images of microelectrode arrays (MEAs) and micro-wells captured by a microscope camera in a dielectrophoresis (DEP)-based system which consists as well of digital switches for turning the DEP force 'on' or 'off'. The images are processed in order to determine if a neuron has entered any of the micro-wells in which case the corresponding switch turns 'off' the DEP force. This process must be in real-time to avoid more than one cell to be loaded in a micro-well. The proposed architecture has been successfully implemented and tested on a Zynq SoC. Results achieved have shown that the system can process one image in 9 ms which meets the minimum real-time requirements of this DEP system.


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