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    題名: 二維凝膠電泳影像中蛋白質點的偵測與分析
    其他題名: Detection and analysis of protein spots in 2D gel electrophoresis image
    作者: 蔡明宏;Tsai, Ming-hung
    貢獻者: 淡江大學資訊工程學系碩士班
    許輝煌;Hsu, Hui-huang
    關鍵詞: 凝膠電泳;蛋白質;型態影像學;分水嶺演算法;影像切割;Electrophoresis;Protein;Morphology;Watershed Algorithm;Image Segmentation
    日期: 2006
    上傳時間: 2010-01-11 06:07:17 (UTC+8)
    摘要: 在蛋白質體學的研究當中,二維凝膠電泳一直扮演著重要的角色,它不僅有效的將蛋白質分離出來,藉由這個方法也可以對蛋白質做定性、定量的研究。以往研究人員必須以人工的方式,將凝膠影像上的蛋白質點圈選出來,不僅研究的速度緩慢,也有可能會發生誤判的情形。有鑑於此,因此開發了這一套處理二維凝膠電泳影像的系統來解決這個問題,在這個系統中,主要是運用了型態影像學上的一些方法,例如我們利用了分水嶺演算法來做影像切割,希望能從複雜的背景中將蛋白質點切割出來;在影像切割這個問題中,分水嶺演算法是常被使用的一個方法,因為它可以很準確的將物件的邊緣切割出來,但是這個方法通常會因為區域極小值過多,而造成過度分割的問題,所以切割出來的結果是很破碎的,這時候就必須利用其他的方法來改善,像是在前處理的部份做雜訊去除,這可以利用一些現成的濾波器就可以完成,另外我們也可以在使用分水嶺演算法做影像切割之前,針對梯度影像上的區域極小值做修正,這個部份我們使用了型態影像學上的影像重建方法,保留了蛋白質上的區域極小值,而將影像上其他的區域極小值修補起來,如此一來做分水嶺切割時就可以避免掉過度分割的問題,產生的物件邊緣也會很完整。運用以上這些方法就可以把凝膠影像上所有的蛋白質點偵測出來;另外也可以針對這些蛋白質點編號,並且計算它們的相關資料,例如面積、位置等等,以利更進一步的分析。此外,我們也將結果跟商業軟體Image Master的結果做比較,證明了我們的結果是具有可信度的。
    2D gel electrophoresis plays an important role in proteomics. It can not only separate protein spots effectively but also identify and quantify the function of proteins. Traditionally, researchers can merely pick protein spots in the gel images with manpower. As a result, the efficiency of the research is critically reduced, and lots of mistakes take place at that time. Therefore, we proposed a system to deal with 2d gel images and to solve this problem. In this system, we mainly use some methods in morphlolgy, for example, we hope to retrieve protein spots from complicated gel images within watershed images segmentation algorithm. When it comes to images segmentation, watershed is the commonest approach, for its ability to segment boundary of spot objects. On the contrary, problems of over segmentation usually occur due to the production of too many local minimums, and this will cause fracture division. As a result, a few pre-processing procedures which can be easily achieved with existing filters should be utilized to improve the effect. By the way, we can also modify local minimums on gradient images before doing images segmentation with images reconstruction technique, that is, local minimums on the protein spots are kept while others are repaired. Therefore, problems of over segmentation can be avoided, and boundary of spots produced are quite complete, too.Using these method, we can detect all of the protein spots in 2D gel images. The system is also able to assign ID numbers to the protein spots and retrieve some annotated information of the spots such as area or location, which can be further analyzed for more researches. Finally, the comparison between the proposed system and another commercial software called Image Master is proceeded, which stands for the reliability of our system.
    顯示於類別:[資訊工程學系暨研究所] 學位論文

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