從一系列的二維影像重建出其原本的三維模型已經廣泛地應用在各個領域當中，也有很多種不同的方式去呈現三維模型。本論文所針對的重建對象是以輪廓線為主的二維影像，讓使用者能更具體的看到這一些輪廓線實際在人類生活中所代表的真實情況。這些二維的輪廓線可以代表人類的器官，例如：腎臟、肝臟．．．等等，重建這些三維的物件能幫助使用者進一步地去發現出更具有貢獻的研究。
　　在本論文中設計且實作了一套重建三維物件的系統。每一張以輪廓線為主的二維影像上，包含一系列在XY座標上的點集合，這些點集合就是輪廓線。我們可以利用邊緣偵測的方式取得輪廓線資料。除此之外，本系統還提供手動新增輪廓線、編輯輪廓線、刪除輪廓線等相關操作功能，以滿足使用者對輪廓線的操作。
　　在產生輪廓線後，可以依照使用者的需求來設定連結條件，例如：相鄰兩頁面上輪廓線有重疊即建立連結。本系統會利用OpenGL的應用程式介面將兩輪廓線的點建立成三維模型，本系統也可以自動依照連結條件的設定來建立出所有可能的三維物件模型，使用者再依其需求來手動修改（新增連結或刪除連結）建立出來的三維物件，以節省使用者的操作時間。
　　使用者可以載入樹狀架構的器官資料表，並且將三維物件命名為器官資料表內的器官節點。日後使用者即可輕易地分辨出每一個三維物件所代表的器官。

　　To reconstruct the 3D model from a series of 2D images are now in widespread used in every field. There are also many methods to display the 3D model. The reconstruction targets of this thesis are the contour-based 2D images and it will let the user concretely realize how the contours really exist in our life. The contours can be the organs of human being, for example: the kidney, the liver…etc. It is helpful to the user to discover more significant research by reconstructing the 3D objects.
　　In this thesis, we design and implement a 3D reconstruction system. A contour-based image contains a lot of point sets in the Cartesian coordinate system. These point sets are contours. We can get contours by using the method of edge detection. Furthermore, the system provides additional functions, such as adding, editing, deleting contours manually, to fulfill users’ needs.
　　After producing contours, the user can set up connection conditions for constructing 3D model to meet their needs. For instance, contours that overlap of the adjacent slices could establish connections. The system will reconstruct 3D model of points in two contours by using the OpenGL API(Application Programming Interface). More efficiently, the system can also construct every possible 3D models automatically based on the predetermined connection conditions, then the user can modify it manually (adding or deleting connections) according to their needs.
　　The user can load the organ table in tree structure, and name 3D objects by the organ node in the organ table. At a later day the user can easily recognize every 3D object as which organ.

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