擴散磁振造影用在活體組織中來觀測水分子的擴散狀況，藉此來區別、定量不同組織特性的區域。擴散峰值造影因而被提出來觀察在組織中受限制的情形，也就是解釋在高B值時曲線趨近於平緩的現象。在非線性擬和中，如何選擇一個好的初始值是一個蠻重要的議題。在本篇研究中，我們希望可以找到一個好的初始值範圍、方法來進行擴散峰值造影的非線性擬和。並且在研究中我們提出事先擬和找D初始值的方法會使得所有數值點擬和完全。進而，為了找尋最有效率的K初始值我們進行了時間分析。在本篇研究中，我們發現在大D、小K值下的數據的擬和精準度、準確度不佳。最後，我們探討了擬和成功與失敗條件下的D、K值差距，並且在老鼠腦中會在哪些區域。

Diffusion MRI is a noninvasive MR imaging technique that allows in vivo
characterization and quantification of the molecular water diffusion in tissues. Diffusion kurtosis imaging (DKI) model has been used to describe the restricted diffusion condition in tissue, which showed elevated intensities from the estimation of conventional monoexponential diffusion model in high b-value. And it is essential for processing non-linear fitting procedure by setting a good initial guess value. Few studies were investigated on the initial guess value and it is aimed in our study to get stable fitting DKI initial guess value. Pre-fitting D method was proposed to get a robust fitting result, and some of the fixed initial D guess value also did that. Further, it was performed time analysis to find the fastest initial K guess value. At low SNR, the accuracy and precision of pre-fitting was hampered in the large D, small k data which is non-restriction environment in brain. Moreover, it was explored the failed manual chosen initial D guess value caused error estimation amount and map those region in brain.

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