以嵌入式系統開發表面電漿共振感測器之多執行緒架構的自動化影像分析系統

表面電漿共振 (Surface Plasmon Resonance, SPR) 生物感測器常用於檢測生物及化學分子，具有高靈敏度 (high sensitivity)、即時性 (real-time)、不須事先標定生物分子 (label-free) 等優點，但傳統上幾乎都是使用一般電腦來處理後端的影像分析，其中牽涉到需手動來選取影像中有表面電漿共振反應的區域，既耗時費力又容易造成人為誤差，而無法達到自動化的檢測分析。　　因此本研究透過嵌入式系統 (embedded system) 開發一套自動化影像分析系統，搭配感光耦合元件 (Charge-coupled Device, CCD) 來擷取表面電漿共振之影像，並利用多執行緒 (multi-threading) 架構使影格率 (Frame Per Second, FPS) 增快約 81.4 %，提高了檢測的時間解析度 (temporal resolution)，亦能使影像取樣 (sampling) 時能更均勻 (uniform)，進而增加實驗與檢測結果的準確度。當系統收到影像後，會立即執行已預先寫好的影像切割演算法，自動化找出有表面電漿共振反應的區域，再將反應區域的平均強度數值，透過藍芽傳輸的方式實時 (real-time) 傳給智慧型裝置 (smart device)，以提供使用者即時確認檢測結果的平台。　　而藉由自動化影像切割 (automatic image segmentation) 演算法，可降低處理時間及人為誤差的可能性，實質達到即時性與自動化檢測分析的效果，並能提高實驗結果之準確度，而經過實驗得到的結果可知目前感測器之靈敏度 (sensitivity) 可達到 9.6*10^-6 RIU。而使用嵌入式系統取代傳統電腦亦能大幅縮減後端運算裝置的體積與成本，並且可與前端表面電漿共振生物感測器整合成為一可攜式 (portable) 系統裝置。

關鍵字

表面電漿共振；生物感測器；嵌入式系統；自動化影像切割演算法；多執行緒；藍芽傳輸

並列摘要

Surface plasmon resonance (SPR) biosensors are used to detect biological and chemical molecules. They have serval advantages such as high sensitivity, real-time detection, and label-free. However, backend image analysis traditionally relies on a personal computer to process, and involves manual selection of SPR reactive region. It is time-consuming, liable to cause artificial error, and unable to detect automatically. 　　Therefore, an automatic image analysis system has been proposed by using an embedded system, combing charge-coupled device (CCD) to capture SPR images. The multi-threading architecture of the main program increases FPS by about 81.4 %, which also increases temporal resolution of detection. Moreover, the sampling time interval is more uniform, causing experiment and testing results become more accurate. After received SPR images, the system will immediately execute a pre-defined image segmentation algorithm to find SPR reactive region. And the mean value of intensity in SPR reactive region will be real-time transmitted to the smart device by Bluetooth. It provides users with the platform of checking testing results. 　　The system can reduce processing time and artificial error by using an automatic image segmentation algorithm, providing real-time and automatic detection. It also increases the accuracy of experiments and sensitivity, which reaches 9.6*10^-6 RIU. Replacing the personal computer with an embedded system greatly reduces the volume and cost of the backend computing device. Moreover, it can be integrated with SPR biosensors into a portable device.

並列關鍵字

surface plasmon resonance ； biosensor ； embedded system ； automatic image segmentation algorithm ； multi-threading ； Bluetooth transmission

參考文獻

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以嵌入式系統開發表面電漿共振感測器之多執行緒架構的自動化影像分析系統

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