Hardware acceleration of an image processing system for dielectrophoretic loading of single neurons inside micro-wells of microelectrode arrays
Conference item
Authors | Zhai, Xiaojun, Jaber, Fadi, Bensaali, Faycal and Mishra, Arti |
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Abstract | This 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. |
Keywords | Microelectrode array; Computer architecture; Image processing; Microprocessors |
Year | 2015 |
Journal | Proceedings of the 17th UKSim-AMSS International Conference on Modelling and Simulation (UKSim) |
Publisher | IEEE |
Digital Object Identifier (DOI) | https://doi.org/10.1109/UKSim.2015.28 |
Web address (URL) | http://hdl.handle.net/10545/620813 |
hdl:10545/620813 | |
ISBN | 9781479987139 |
File | File Access Level Open |
Publication dates | 25 Mar 2015 |
Publication process dates | |
Deposited | 11 Nov 2016, 16:14 |
Contributors | University of Derby |
https://repository.derby.ac.uk/item/9533v/hardware-acceleration-of-an-image-processing-system-for-dielectrophoretic-loading-of-single-neurons-inside-micro-wells-of-microelectrode-arrays
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