臺灣博碩士論文加值系統

本研究成功開發出具有線性度、穩定度之可於開放環境中使用的居家健檢系統，利用免疫反應呈色作為檢測標的並以本系統量化其結果。本研究中使用所開發之應用程式與伺服器連接、拍攝免疫反應呈色結果與本研究所開發的比色板並上傳至伺服器以達到雲端運算的功能，並接收運算結果存入應用程式中的資料庫記錄日期與濃度，以供使用者未來瀏覽使用。為確認本研究所開發的居家健檢系統能於不同偏光環境、對焦距離、光強度、不同手機下有相似的線性度，本研究同時開發一可量化環境的模擬環境系統作為輔助系統以供測試居家健檢系統時使用。
本研究中的居家健檢系統其應用程式使用於Android作業系統以Android Studio IDE使用Java程式語言開發，使用的網頁伺服器為XAMPP，並以PHP做資料傳輸與管理。伺服器中的影像處理程式以Visual Studio IDE做為開發環境，整合HSV色彩空間之概念、OpenCV開源程式庫與Nvidia所開發的CUDA架構以C/C++撰寫。
在模擬環境系統中的測試，本研究所開發的居家健檢系統其影像處理程式於開放環境下仍可正確的抑制陰影、環境光與人為操作上的誤差並且正確的得到T線特徵位置。並於偏光、對焦高度與光強度等不同環境變數下其灰階靈敏度測試的曲線決定係數可介於0.978至0.999之間，而於實際糞便潛血檢測劑量量測下其曲線決定係數可達0.956，且可良好的分辨0 ng/mL與50 ng/mL。

This thesis presents a health care system with fast, portability, stability, and low cost for fecal occult blood tests (FOB) to replace the traditional health checkup. The inspection is based on immunochromatographic assay which is widely applied to many fields of clinical diagnosis. In combination with immunochromatographic strip and home health checkup System, the patient is able to detect and calculate the concentration of the sample. Furthermore, the patient can browse the diagnostic records, view the trend and have a health checkup in any place by the application. The system software integrate HSV image processing, cloud computing, Compute Unified Device Architecture (CUDA) acceleration, Android application and server management. Compare with traditional health checkup, to operate the home health checkup system, the only additional hardware is a stage with color palette made by cardboard and the user’s mobile device. To confirm the system with confirmation experiments, we also build a support system which is use to simulate the difference environment. After the test, we found that the home health checkup system is strong enough to operate correctly in most of the condition in daily routine and it is able to present an agile, high sensitive and steady performance with low economical cost.

摘要 I
Extended Abstract III
誌謝 IX
目錄 X
圖目錄 XV
表目錄 XX
縮寫表 XXIII
第一章 緒論 1
1-1 研究背景 1
1-2 大腸癌的檢測方式簡介 3
1-3 免疫分析法 5
1-3-1 免疫分析基本理論 5
1-3-2 抗原與抗體定義 5
1-3-3 抗原與抗體結合力 7
1-4側流層析免疫反應試紙 8
1-5 文獻回顧 11
1-5-1 影像判讀簡介 11
1-5-2 膠體金奈米粒子灰階判讀 12
1-5-3 動態陰影偵測 14
1-6 研究動機與目的 17
1-7 章節架構 18
第二章 系統設計與製作 20
2-1 系統流程 20
2-2 主系統硬體 22
2-2-1 硬體設計之理念 22
2-2-2 比色板設計與製作 22
2-2-3 載台設計與製作 23
2-3 應用程式與伺服器 25
2-3-1 應用程式與伺服器架構圖 25
2-3-2 應用程式 25
2-3-3 伺服器架設 26
2-4 影像處理程式 27
2-4-1 影像處理前言 27
2-4-2 座標校正 29
2-4-3 定義校正色塊邊界 32
2-4-4 色彩空間距離差 38
2-4-5 C線位置抓取 42
2-4-6 T線位置抓取 43
2-4-7 T線實際灰階 45
2-4-8 零濃度獨立判讀 47
2-4-9 GPU運算加速 49
2-4-10 影像處理結論 50
2-5 模擬環境系統 52
2-5-1 模擬環境系統架構 52
2-5-2 黑箱設計 53
2-5-3 人機介面與溝通 55
2-5-4 LED與電路設計 56
2-5-5 BH1750光照模塊 58
2-5-6 模擬環境系統程式撰寫 59
2-6 色階線性度測試卡匣 61
第三章 儀器與設備 62
3-1 智慧手機 62
3-2 伺服器儀器 62
3-2-1 伺服器軟體 62
3-2-2 伺服器電腦配備 62
3-3 雷射雕刻機 64
3-4 模擬環境系統之儀器與設備 65
3-4-1 微處理器 65
3-4-2 光照度感測器 66
3-4-3 LED光源 66
3-4-4 觸碰螢幕 67
3-5 實驗藥品 68
第四章 線性度實驗方法與結果 69
4-1 對焦高度測試實驗與結果 69
4-2 光強度測試實驗與結果 76
4-3 偏光實驗與結果 83
4-3-1 偏光測試實驗簡介 83
4-3-2 上偏光測試實驗與結果 84
4-3-3 側偏光測試實驗 91
4-3-4 下偏光測試實驗 98
4-4 色階線性測試總結 105
4-5 FOB試劑測試與結果 107
第五章 結論與建議 109
5-1 結論 109
5-1 建議 111
參考文獻 112

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