Hardware acceleration of an image processing system for dielectrophoretic loading of single neurons inside micro-wells of microelectrode arrays
AffiliationUniversity of Derby
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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.
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 March
JournalProceedings of the 17th UKSim-AMSS International Conference on Modelling and Simulation (UKSim)
TypeMeetings and Proceedings