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研究生:何易展
研究生(外文):Yi-Chan Ho
論文名稱:細胞顯微影像之分割、追蹤與運動分析
論文名稱(外文):Cell Segmentation, Tracking and MotionAnalysis from Microscopic Image Sequence
指導教授:孫永年孫永年引用關係
指導教授(外文):Yung-Nien Sun
學位類別:碩士
校院名稱:國立成功大學
系所名稱:資訊工程學系碩博士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:83
中文關鍵詞:運動分析追蹤顯微影像細胞影像分割
外文關鍵詞:Level SetSnakeMicroscopic ImageMotion AnalysisCell SegmentationFast Geodesic Active Contours
相關次數:
  • 被引用被引用:22
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  • 下載下載:183
  • 收藏至我的研究室書目清單書目收藏:0
在醫學研究中,細胞的觀察是主要的基本程序。除了一般肉眼的觀察外,醫學專家希望藉由影像處理協助他們仔細評估細胞顯微影像,以找出各種病理現象或其成因。在一般的顯微鏡底下,細胞幾乎是透明看不見的,若要觀察細胞的結構,則必須替細胞進行染色的程序。然而,細胞一經染色便會死亡,所以無法長時間觀察細胞的變化。一種叫做Phase Contrast的成像技術成為替代方案,其原理是利用物體間不同的折射率所造成的對比效果。

欲觀察細胞在影像序列中的連續變化,可以藉由影像分割(image segmentation)的方式,找出細胞在對應影像中的邊緣。在本論文中,我們使用變異數影像分割配合FGAC(Fast Geodesic Active Contours)的方法自動偵測細胞邊緣,FGAC承襲了Snake與Level-Set的精神,可自動進行單一或多個之邊緣萃取,其對於細胞顯微影像的分割有不錯的效果。在細胞運動分析方面,依據影像分割所獲得的輪廓,我們可以將細胞的輪廓運動區分為平移、旋轉、形變及分裂。其中形變的運動可用最小方均根方法求出Affine的轉換參數,而細胞的分裂運動則可由觀察輪廓形狀的變化得知。此外,觀察整體細胞的運動趨勢也是所要探討的問題之一。觀察者透過圖形使用者介面,可以執行細胞影像分割及追蹤的功能,並且依據使用者的訴求,即時獲得細胞輪廓及各種運動的各項運動參數。
The observation of cells is one of the essential processes in fundamental medical study. In order to find each pathological phenomenon or its reason that causes diseases, medical experts make use of image processing to assess cell microscopic images in detail. Cells are almost transparent and cannot be seen under normal microscopes. Generally, they have to be stained if we want to observe the structure of them. However, the cells will be killed after being stained. In this situation, we can’t observe the activities of cells during a long period of time. An imaging technique called phase contrast imaging is the alternative approach. The principle of phase contrast is to use the different refractive indexes that cause the contrast effect.
We can observe the consecutive motion of cell activities in image sequence by using image segmentation method to detect the variations of the corresponding cell boundaries. In this thesis, we use the variance map along with the Fast Geodesic Active Contours (FGAC) method to find the boundaries of cells automatically. FGAC inherits the spirit of both Snake and Level-Set methods. It can extract boundaries from multiple cells automatically and acquire fine segmentation results from a sequence of cell microscopic images. To speak of cell motion analysis, we can classify the cell motion into classes based on image segmentation result. These classes are commonly the translation, rotation, deformation and cytokinesis. We use the least-mean-square method to compute the affine parameters and use the resulting parameters to represent the deformation motion. Besides, cytoknesis can be known by observing the variation of contours of cells. In addition, we also study the motion trend of the entire group of cells. Through using the graphic user interface, user can segment and track the observed cell or cells. Meanwhile, the boundaries of the observed cells can be defined and the corresponding motion parameters are computed in real time.
中文摘要 ……………………………………………………………………………. i
英文摘要 …………………………………………………………………………… ii
目錄 ………………………………………………………………………………… iii
圖目錄 ………………………………………………………………………… v
表目錄 …………………………………………………………………………… viii
第一章. 序論 …………………………………………………………………... 1
1.1 研究動機 ………………………………………………………… 1
1.2 相關文獻 …………….…………………………….…………….. 2
1.3 章節提要 ………………………………………………………… 4
第二章. 細胞影像之分割…………………………………………….………… 6
2.1 細胞之結構與成像 ……………………………………………… 6
2.2 細胞位置及初始輪廓之偵測 …..……………………….……… 10
2.2.1 變異數影像 ……………………………..………………… 10
2.2.2 臨界值選取 ………………………………….…………… 13
2.2.3 邊界描繪…………………………………….…………… 16
2.3 影像分割 ……………………………………….………………. 19
2.3.1 Active Contour Model簡介 …………..…………………. 19
2.3.2 Level-Set方法 ………………………..…………………. 25
2.3.3 Fast Geodesic Active Contours方法 …..……………… 28
2.3.4 邊界定義 ……………………………..…………………. 41
第三章. 細胞之運動分析………………………………………….…………… 43
3.1 單細胞之運動分析-平移與旋轉………………………………… 43
3.2 細胞形變運動分析………………………….…………………… 48
3.3 細胞分裂 ………………………………………….……………. 57
3.4 整體細胞運動之觀察與統計 ………………….……………. 60
第四章. 系統概述及實驗結果 ……………………………………………… 62
4.1系統概述 …………………………………………………….…. 62
4.2 合成影像實驗 ……………………………………………….… 63
4.3 上皮細胞影像實驗 …………………………………………… 65
第五章. 結論及未來展望 …………………………………………………… 78
5.1 結論 …………………………………………………………… 78
5.2 未來展望 ………………………………….…………………… 79
■ 參考文獻 ……………………………………………………………………… 80
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