• Hardware acceleration of an image processing system for dielectrophoretic loading of single neurons inside micro-wells of microelectrode arrays

      Zhai, Xiaojun; Jaber, Fadi; Bensaali, Faycal; Mishra, Arti; University of Derby (IEEE, 2015-03-25)
      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.