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用于芯片实验室微流体监测的实时机器视觉现场可编程门阵列实现

Real-time machine vision FPGA implementation for microfluidic monitoring on Lab-on-Chips.

作者信息

Sotiropoulou Calliope-Louisa, Voudouris Liberis, Gentsos Christos, Demiris Athanasios M, Vassiliadis Nikolaos, Nikolaidis Spyridon

出版信息

IEEE Trans Biomed Circuits Syst. 2014 Apr;8(2):268-77. doi: 10.1109/TBCAS.2013.2260338.

DOI:10.1109/TBCAS.2013.2260338
PMID:24875286
Abstract

A machine vision implementation on a field-programmable gate array (FPGA) device for real-time microfluidic monitoring on Lab-On-Chips is presented in this paper. The machine vision system is designed to follow continuous or plug flows, for which the menisci of the fluids are always visible. The system discriminates between the front or "head" of the flow and the back or "tail" and is able to follow flows with a maximum speed of 20 mm/sec in circular channels of a diameter of 200 μm (corresponding to approx. 60 μl/sec ). It is designed to be part of a complete Point-of-Care system, which will be portable and operate in non-ideal laboratory conditions. Thus, it is able to cope with noise due to lighting conditions and small LoC displacements during the experiment execution. The machine vision system can be used for a variety of LoC devices, without the need for fiducial markers (such as redundancy patterns) for its operation. The underlying application requirements called for a complete hardware implementation. The architecture uses a variety of techniques to improve performance and minimize memory access requirements. The system input is 8 bit grayscale uncompressed video of up to 1 Mpixel resolution. The system uses an operating frequency of 170 Mhz and achieves a computational time of 13.97 ms (worst case), which leads to a throughput of 71.6 fps for 1 Mpixel video resolution.

摘要

本文介绍了一种在现场可编程门阵列(FPGA)设备上实现的机器视觉系统,用于对芯片实验室(Lab-On-Chips)进行实时微流体监测。该机器视觉系统旨在跟踪连续流或塞状流,在这种情况下,流体的弯月面始终可见。该系统能够区分流的前端或“头部”与后端或“尾部”,并且能够在直径为200μm的圆形通道中以最高20mm/秒的速度跟踪流(对应于约60μl/秒)。它被设计为完整的即时护理系统的一部分,该系统将是便携式的,并能在非理想的实验室条件下运行。因此,它能够应对实验执行过程中由于光照条件和芯片实验室的微小位移而产生的噪声。该机器视觉系统可用于各种芯片实验室设备,其运行无需基准标记(如冗余图案)。潜在的应用需求要求进行完整的硬件实现。该架构采用了多种技术来提高性能并最小化内存访问需求。系统输入是分辨率高达1兆像素的8位灰度未压缩视频。该系统使用170MHz的工作频率,在最坏情况下实现了13.97ms的计算时间,这导致1兆像素视频分辨率下的吞吐量为71.6帧/秒。

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