由於近年來科技的進步，複雜的醫療影像處理、重構和立體成像都可以在即時的時間內完成運算。本論文利用目前現有的方法並發展出與登錄的演算法。其中追蹤演算法可以由核磁共振影像將人體複雜的膽道重建出來，而登錄演算法可以由電腦斷層影像與核磁共振影像中分別擷取出脊椎骨與椎神經並且將這些組織融合在一起提供了醫生在診療上的參考依據。

本論文首先提出一個追蹤整個核磁共振影像膽道結構的方法，接著提出一個電腦斷層與核磁共振脊髓影像登錄與融合的演算法；膽道追蹤演算法將分為四個步驟：第一個步驟將整個肝臟結構由核磁共振的立體影像資料分割出來並且用B-spline 的方式將其肝臟結構整個封閉並且將邊緣平滑化。第二步驟將膽道由整個肝臟資料中分割出來，由於核磁共振膽道造影的影像中膽道的灰階值較周圍肝臟的灰階值高，因此利用區域成長法將可以把膽道結構分割出來，而其停止條件為完全搜尋整個立體肝臟結構。第三步驟利用第二步驟分割出的膽道資料進行自動的三維追蹤重建，這三維追蹤演算法會建立出每一個膽道分支的表面座標與中心軸座標資料最後將整個膽道結構資料完整的紀錄下來。最後一個步驟利用重建的膽道座標資料將其結構立體成像。雖然此演算法較傳統的方式耗時，但它提供了清楚的膽道立體組織結構和量化的結構資料等資訊有助於醫師在做肝臟診療參考。

登錄與融合演算法-醫療上的診斷可以利用不同的影像資料獲取不同性質的疾病資訊。在各種不同方式擷取的影像資料型態進行三維的登錄與融合是有其必要性，因為登錄多種影像資料不只提供相互關聯的診療資訊外，並且協助外科治療與放射治療所需的影像資料。本研究將針對電腦斷層掃描影像與核磁共振影像這兩種影像特徵進行登錄融合。由於電腦斷層攝影在骨骼結構上有較好之顯示能力，而核磁共振造影則是在組織方面有不錯的顯示效果，由於兩種醫療影像所提供之資訊是互補的，若能經過一些影像前處理，突顯出個別之特徵後，再經由登錄對位方式合併成新的影像互相結合兩種不同成像方法之優點，如此必定能輔助醫師在疾病的診斷觀察上提供較精確之判斷結果。所以此演算法包含了電腦斷層與核磁共振影像前處理、電腦斷層與核磁共振影像分割，三維登錄與融合且此法不需要外部標記並且最後能夠成功的將脊髓骨與椎神經同時立體顯示出來提供了下背痛的診斷依據。

Due to the advancement of computer science in recent year, the processing of complex medical image, reconstruction, and rendering can almost be finished in real time.

In this thesis, firstly an algorithm for reconstructing Magnetic Resonance Cholangiography (MRC) biliary structure is proposed. Then the process for registration and fusion of the MR and CT images of the spinal are developed. For the proposed tracking algorithm, the processing of MRC data can be divided into four phases. In the first phase, the region of interest (ROI) containing the liver and biliary ducts is extracted from the original volume data based on human anatomy by B-spline curve. The second phase involves segmenting the biliary ducts from the region identified in the previous phase. Because the image of biliary portion is brighter than the liver, the segmentation is started by choosing the brightest pixel in the ROI as the seed for 3D region growing. This procedure could be executed many times, depending on the provided stopping condition. In the third phase, the segmented biliary duct regions are traced to construct the biliary tree. An automated 3D tracking algorithm is proposed for this phase. This 3D tracking algorithm estimates the coordinates of the points along the medial axis of each biliary duct branch. The cross sections associated with the points along the medial axis are also calculated approximately during the tracking process. The biliary tree data structure is constructed in this phase. The biliary tree is reconstructed and rendered in the last phase. Although the proposed algorithm takes a longer time compared with the conventional approach, the reconstructed biliary tree 3D structure can provide more clearly image. A concise representation for the biliary tree can be achieved with the proposed method and provide both quantitative and structural information for clinical reference.

Medical diagnosis can benefit from the complementary information in different modality images. Multi-modal image registration and fusion is an essential task in numerous three-dimensional medical image-processing applications. Registered images are not only providing more correlative information to aid in diagnosis, but also assisting with the planning and monitoring of both surgery and radiotherapy. This research is directed at registering different images captured from Computed Tomography (CT) and Magnetic Resonance (MR) imaging devices, respectively, to acquire more thorough information for disease diagnosis. Because MR bone model segmentation is difficult, this research used a 3D model obtained from CT images. This model accomplishes image registration by optimizing the gradient information accumulated around the bony boundary areas with respect to the 3D model. This system involves pre-processing, 2D segmentation, 3D registration, fusion and sub-system rendering. This method provides desired image operation, robustness verification, and multi-modality spinal image registration accuracy. The proposed system is useful in observing the foramen and nerve root. Because the registration can be performed without external markers, a better choice for clinical usage is provided for lumbar spine diagnosis.

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