膝關節系統在人體下肢運動中扮演不可或缺的角色，由於它在運動過程中會承受大於體重數倍的壓力，因此膝關節系統容易產生運動傷害或是失去部分功能。欲探討膝關節疾病的成因，了解膝關節內部骨塊的運動是很重要的。在本篇論文裡，我們提出一個膝關節模型為基礎的影像對位系統，將多姿勢核磁共振(MR)影像之三維靜態空間資訊與單平面動態X光(Fluoroscopy)影像之時間資訊結合，以重建立體膝關節之運動。這個系統包含了膝關節模型建立以及模型為基礎的影像對位兩個部份。在模型建立方面，我們從多組不同姿勢的核磁共振影像中，建立一個包含膝蓋內部骨塊的幾何形狀以及關節運動系統的膝關節模型。在影像對位的部份，根據本論文提出的模型為基礎的對位方法，膝關節模型將被對位至動態X光影像序列。在對位的過程中，我們提出一個非對應點刪除的機制，使對位結果能避免陷於不正確的區域解。除此之外，此膝關節模型在對位過程中適當地運用了膝關節的結構限制，使得運動重建的結果變得更為合理可靠。在實驗部分，我們利用動物死體進行對位準確性的驗證。在不同的膝蓋骨塊上，皆獲得了小於1.5公厘(millimeter)之平均距離誤差，顯示我們提出之對位方法具有一定的準確性。此外，我們也將對位的結果利用幾何內插的方式，重建出立體膝關節運動。

The knee joint plays an essential role in human movement. As the knee joint undertakes the pressure much larger than the body weight during motion, it has higher probability to get sport injuries or lose partial functions. To study the causes of knee diseases, understanding the knee motion is very important. In this paper we propose a model-based image registration system, which integrates the spatial information of multi-postural Magnetic Resonance (MR) images with the temporal information from single planar fluoroscopic videos, to reconstruct the three-dimensional (3-D) knee motion. The proposed system is divided into model construction and model-based image registration steps. In the first step, we construct a knee model that consists of bone shapes and articulated joint system based on multi-postural MR images. In the registration step, the constructed model is registered to a sequence of fluoroscopic images by using the proposed model-based image registration method. A non-corresponding point removal mechanism is also designed to avoid the undesired local solutions in the registration process. Moreover, the proposed knee model can provide proper constraints of knee structure in the registration process so that the reconstructed knee motion looks like more reasonable and plausible. In the experiments, the accuracy of the proposed method is validated based on animal cadaver. Very small registration errors (less than 1.5mm) are achieved on each knee bone segment. The 3-D knee motion reconstructed by interpolating the registration results is also demonstrated.

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