利用心臟磁共振影像觀察心臟疾病是近年來廣泛使用的臨床技術，其中又以心肌胞外比容 (extracellular volume fraction, ECV) 映像較為矚目，因其在心肌缺血、瀰漫型心肌纖維化等心臟疾病上皆能清楚地呈現出病灶。心肌胞外比容是透過注射顯影劑前後的T1參數變化量搭配血球容積比計算而得，因此注射顯影劑前後的影像位置必須完全一致且T1參數的計算也必須非常精確，但這在實際造影中幾乎無法實現，必須仰賴影像形變對位的後處理來修正像素位移，由於注射顯影劑前後的影像有明顯的對比度差異，不利於影像形變對位，因此本研究提出應用在心臟短軸切面的左心室自動切割法來增加影像形變對位的準確度，以及多起始T1值猜測來降低T1計算的錯誤率。本研究提出的方法確實大幅提升了T1參數計算與影像對位的準確性，進而改善心肌胞外比容映像的準確度，且左心室自動切割法也有助於自動化的量化估計與臨床應用。

Amount clinical cardiovascular magnetic resonance (CMR) imaging techniques, extracellular volume fraction (ECV) has drawn much attention due to its applications on the focal of myocardial infraction, diffuse myocardial fibrosis and other heart diseases. ECV is estimated by the difference of T1 values between pre- and post- administrations of contrast agent and hematocrit. Accurate T1 estimation and deformable image registration are both crucial for ECV mapping. However, the changes of image contrasts between contrast administrations is a challenge for image registration. In this thesis, we propose a registration method with automatic left-ventricle walls segmentation and multiple initial T1 values. Compared to previous methods, this proposed method prominently reduced the errors of T1 fitting and significantly improve the overlap rate between pre and post contrast images as well as the accuracy of the ECV mapping. In addition, the segmentation results are helpful for ECV quantization and clinical applications.

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