在同步輻射光源的持續發展下，同調光繞射顯微術（Coherent Diffraction
Imaging，簡稱 CDI）能夠重建非結晶樣品的結構以供更深入的研究，是一種相當實用的檢測技術。其所使用的重建演算法（Hybrid Input Output Algorithm，簡稱 HIO）由於同時利用了實空間與倒空間的資訊來進行迭代，因此能夠較為精確的重建樣品的結構資訊。
　　本論文分為兩個部分，第一部分是在 Matlab 環境下對 HIO 算法及其優化版本 GHIO 算法進行優化，大幅降低其重建過程所需花費的時間，並以實例說明優化後的版本在相關研究中能提供大量的幫助，讓研究人員更專注於理論的正確性及實驗的技術提升。
　　第二部分是將 HIO 應用於進行三維斷層影像的重建，利用 HIO 算法的特性，我們可以獲得相當精準的重建結果。也透過與其他常用的重建算法（FBP 及 ART）比較，說明 HIO 對於投影角度及數量的缺失，以及實驗過程中的雜訊都有相當高的容忍度，非常適合用於高解析度的 STEM 斷層影像的重建。

With the continuous development of synchrotron radiation sources, Coherent Diffraction Imaging (CDI) has become a practical and valuable technique for reconstructing the structures of non-crystalline samples, enabling deeper research insights. The reconstruction algorithm used in CDI, known as the Hybrid Input Output Algorithm (HIO), leverages both real and reciprocal space information during iterations, resulting in more accurate reconstruction of sample structures.
This paper is divided into two parts. The first part focuses on optimizing the HIO algorithm and its improved version, GHIO, in the Matlab environment, significantly reducing the reconstruction time. Examples demonstrate how the optimized version can offer substantial assistance in related research, allowing researchers to concentrate more on theoretical correctness and experimental enhancements.
In the second part, we apply the HIO algorithm to perform three-dimensional tomographic image reconstruction. Exploiting the characteristics of the HIO algorithm, we achieve highly accurate reconstruction results. Comparisons with other commonly used reconstruction algorithms (FBP and ART) reveal HIO's high tolerance to missing projection angles and quantities, as well as experimental noise, making it particularly suitable for high-resolution STEM tomographic image reconstruction.

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