本研究是以美國國家衛生研究院(NIH)主導的可視人體計畫(Visible Human Project)所釋出的高解析度死刑犯人體切片影像為藍本，並透過本實驗室自行發展的3D醫學影像系統(3D Builder)去繪製出切片影像上的各種不同器官之輪廓線，而於完成輪廓線的繪製後必須要能對每條輪廓線作命名處理以正確的區分其所代表的人體器官，但若是使用人工的方法對每條輪廓線逐一的作命名，將會花費大量的人力及時間，因此系統必須要能在最少的人員介入及最短的時間花費之下完成命名的工作，當然命名完成後必須要有一些機制確認結果，若有不正確的情況發生則要提供功能讓使用者進行修改，而於輪廓線命名完成之後，系統需可利用輪廓線的名稱將個別器官組織的3D物件建立出來，但若3D物件的表面過於粗糙、尖銳，則可使用平滑化功能對其表面做處理，且系統也提供虛擬手術功能，讓使用者可切開3D器官組織物件，如此使用者即可清楚地看到剖開人體後的情況，以模擬手術情境。

This research uses high resolution human body slice images for image segmentation research. In the system we develop, the contour of every single organ or tissue can be segmented automatically or semi-automatically. After the contours are segmented, we have to name those contours in order to know what organ or tissue it represents. This is a very time consuming work. Therefore, the 3DBuilder system we developed tries to name the contours with a minimum human involvement. The system provides some inspection mechanisms to check whether the names of the contours are correct. If not, the system provides some tools to correct them automatically. After naming contours, the system reconstructs 3D Objects of these contours. If the surfaces of the 3D objects are too rough, the system smoothes them automatically. The system also provides virtual cut operations on 3D Objects. Therefore user can see what is inside the 3D Object clearly.

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