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研究生:溫竣傑
研究生(外文):WEN, JUN-JIE
論文名稱:結合六軸機械手臂與細胞影像分析應用於繼代培養自動化之研究
論文名稱(外文):Using a Six-axis Robotic Arm and Cell Image Analysis System for Subculture Automation
指導教授:連啓翔
指導教授(外文):LIEN, CHI-HSIANG
口試委員:徐祖安張家源徐偉軒連啓翔
口試委員(外文):SYU, ZU-ANJHANG, JIA-YUANSYU, WEI-SYUANLIEN, CHI-HSIANG
口試日期:2019-03-07
學位類別:碩士
校院名稱:國立聯合大學
系所名稱:機械工程學系碩士班
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:中文
論文頁數:140
中文關鍵詞:細胞培養繼代培養自動化六軸機械手臂形態學影像分析分形維數差分盒計數法
外文關鍵詞:Cell cultureSubcultureAutomationSix-axis robot armMorphological image processingFractal dimensionDifferential box-counting method
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隨著生醫技術的發展,為了取得大量且穩定的細胞以滿足在藥物、疾病等研究時的需求,因此本研究利用一六軸機械手臂,結合影像分析技術與自製的電動移液吸管等周邊設備,完成貼附型細胞培養環節中的繼代培養動作之相關建置。藉由此自動化系統可以達到以下三個優點:1)降低人力與時間成本,可令實驗室成員專注於設計實驗與實驗結果部分,較無需為培養細胞而勞心費神;2)可設定時間區間以隨時觀測細胞生長狀況,當滿足繼代培養條件時自動進行繼代培養程序,以保持實驗的穩定性與一致性;3)藉由高自由度之六軸機械手臂建立的自動化系統,可完成所有繼代培養所需之動作並且可降低汙染風險和增進細胞品質控制。此外,本研究針對細胞影像分析部分,主要是利用相位差縮時顯微鏡連續拍攝三種不同初始濃度之HaCaT Cell貼附型細胞,任一種濃度每經三小時進行記錄並長達三天,透過形態學分析細胞面積與差分盒計數法(DBC)皆可建立細胞生長曲線並清楚分辨不同初始濃度的成長情形,其中與人工問卷分析結果比對,當分形維數達2.4時為較佳的繼代培養時機。
In the advancement of biomedical technology, it is important to make large amounts of the experimental cells with keeping the same quality for medicine or disease research. In this paper, we have developed an automated system to subculture process of HaCaT Cells. This system is consisting of a six-axis robot arm and other homemade module devices such as electric pipettes, involving the cell image analysis technology.
This automated system improves three advantages in subculture process. First, this system provides benefits of reducing labor costs and saving time to focus on designing experimental results rather than nurturing cells. Second, the experimental data quality is consistency and accuracy because of tracking the cell growth condition automatically. Finally, all operation movements of the subculture process were accomplished by only one six-axis robot arm. Simultaneously, using the automation system could minimize the risk of contamination and improves the better quality of cell populations.
The user operation interface in our system was built up using C++ and OpenCV. The HaCaT cell growth images with three different initial concentrations were detected by the phase-contrast time-lapse microscope. In the observation time with 72 hours, the images were recorded every three hours for each concentration.
In addition, we determined the cell confluency and calculated the fractal dimension of the cell images by differential box counting (DBC) to establish them growth curve. The results indicated we could clearly track the state of the growth cell at the different initial conditions. And also we show that the fractal dimension is 2.4 for an appropriate subculture timing based on those experiments.
摘要 I
Abstract II
誌謝 IV
目錄 V
圖目錄 VII
表目錄 XII
第一章 緒論 1
1-1 前言 1
1-2 文獻回顧 3
1-2-1 細胞培養自動化系統 4
1-2-2 細胞影像之匯合度 6
1-2-3 細胞影像分析方法 8
1-2-4 分形維數 12
1-3 研究動機與目的 14
1-4 研究流程規劃及架構 15
第二章 理論建立 17
2-1 細胞影像處理方法 17
2-1-1 影像前處理 19
2-1-2 二值化方法 25
2-1-3 形態學操作 29
2-2 分形理論 33
2-2-1 分形簡介 33
2-2-2 分形維數計算方法 37
2-2-3 差分盒計數(DBC)方法與其改良 41
第三章 實驗步驟與方法 43
3-1 實驗器材設計與製作 43
3-1-1 上銀六軸機械手臂RA605-710 43
3-1-2 電動夾爪XEG-64 45
3-1-3 治具設計 45
3-1-4 細胞培養周邊設備和影像來源 54
3-2 實驗步驟 62
3-2-1 系統架構圖 62
3-2-2 系統初始化設定 66
3-2-3 影像載入與選擇感興趣區域 66
3-2-4 影像處理過程 67
3-2-5 分形維數計算 69
第四章 結果與討論 71
4-1 六軸機械手臂運動探討與各動作之影片縮圖 71
4-2 細胞影像分析結果探討 93
4-2-1 形態學影像處理結果 93
4-2-2 細胞影像之差分盒維數計算結果 97
4-2-3 程式與人員之細胞覆蓋率觀測結果校正 99
4-2-4 單顆細胞平均像素面積與細胞影像濃度計算 102
4-3 離心機內影像校正結果探討 110
4-3-1 離心機內影像之圓心驗證方法 112
4-3-2 離心機校正馬達旋轉角度與時間關係 114
4-3-3 校正馬達旋轉至正確位置所需之旋轉角度計算 115
第五章 結論與未來展望 117
第六章 參考文獻 118

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