A microfluidic analyzer system and a cell detection algorithm were developed to analyze biomedical fluids. The obtained microfluidic device is based on the integration of dif- ferent fluidic systems: the SensoNor glass/silicon/glass multilayer microchip and ThinXXS plastic slide. A hydrodynamic focuser was designed to sort and analyze cells/particles in a 100μm wide channel. The advantages of this Lab-On-a-Chip (LOC) structure are the easy interfaceability with electrodes and optical systems, biocompatibility and ability of optical analysis and morphologic recognition. The proposed CNN-based (Cellular Neural Network) algorithm is real-time and scalable. This constructed microfluidic and optical system is able to analyze and measure any biological liquid, which contain less than 10μm size particles or cells, and count the number of morphologically well-separated different el- ements in the focused liquid flow using real-time image processing algorithms.
An integrated LOC hydrodynamic focuser with a CNN-based camera system for cell counting application / A. Laki; I. Rattalino; F. Corinto; K. Ivan; D. Demarchi; P. Civera. - ELETTRONICO. - 1(2011), pp. 301-304. ((Intervento presentato al convegno Biomedical Circuits and Systems Conference (BioCAS) tenutosi a San Diego (USA) nel 10-12 November 2011 [10.1109/BioCAS.2011.6107787].
Titolo: | An integrated LOC hydrodynamic focuser with a CNN-based camera system for cell counting application | |
Autori: | ||
Data di pubblicazione: | 2011 | |
Abstract: | A microfluidic analyzer system and a cell detection algorithm were developed to analyze biomedica...l fluids. The obtained microfluidic device is based on the integration of dif- ferent fluidic systems: the SensoNor glass/silicon/glass multilayer microchip and ThinXXS plastic slide. A hydrodynamic focuser was designed to sort and analyze cells/particles in a 100μm wide channel. The advantages of this Lab-On-a-Chip (LOC) structure are the easy interfaceability with electrodes and optical systems, biocompatibility and ability of optical analysis and morphologic recognition. The proposed CNN-based (Cellular Neural Network) algorithm is real-time and scalable. This constructed microfluidic and optical system is able to analyze and measure any biological liquid, which contain less than 10μm size particles or cells, and count the number of morphologically well-separated different el- ements in the focused liquid flow using real-time image processing algorithms. | |
ISBN: | 9781457714689 | |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/11583/2498907