- 學位論文
結合封閉不可壓縮黏性流體模型與互資訊知識從事醫學影像之對位
Medical image registration using a closed incompressible viscous fluid model with mutual information
摘要
影像對位對於在醫學上的研究或在醫療診斷用途上是相當重要的。其為對多張影像處理，並將個別的資訊顯示在對位後的影像。影像對位的方法相當多種，本論文敘述物理模型類中的黏性流體方法。利用黏性流體模型的數值方法包含有不易求解的非線性偏微分方程式。在本論文中，我們利用封閉不可壓縮之黏性流場的數值方法來求解影像對位中的速度場與位移場，並利用互資訊的概念使得對位效果更加精確。我們使用了大量不同的核磁共振影像來評估此一新方法。從實驗結果中可得知，本論文所提出的方法可有效解決影像對位的問題，且對位結果也相當的準確，在與光流場模型做比較後得知，本篇論文所提出的方法在相關係數的評估上，呈現較精確的結果。我們相信，本研究之方法在各種不同的醫學影像對位應用中，具有相當的潛能。
並列摘要
Image registration is very important for a wide variety of medical image applications. It provides lots of image information for medical personnel to judge and analyze the anatomical structures and lesions. There are many image registration method being proposed. This thesis describes a non-rigid viscous model which involves a complicated, nonlinear partial differential equation. We propose to use the closed two-dimensional incompressible viscous flow model to solve the partial differential equation, We also incorporate the knowledge of mutual information into the model, from which the velocity and displacement fields are obtained. A wide variety of magnetic resonance images were used to evaluate this new method. Experimental results indicate that the proposed method successfully performed registration and provided good accuracy. Comparing to the optical-flow model, our method produced higher correlation coefficient scores. We believe that our algorithm is of potential in a wide variety of medical image registration applications.