為了協助神經學家觀察神經系統的運作機制，量化單一神經元之細胞形態資訊是必需的，然而市面上所流通的商用套裝軟體不易改良成具有特定功能需求的，這將可能造成使用者操作上的不便以及提升了軟體的操作複雜度，因此本研究實現了一個自動化的三維形態資訊擷取軟體以量化雙光子神經顯微影像之細胞形態資訊。本論文修改了區域成長演算法以實現ROI影像分割及神經顯微影像之細胞形態量化功能並且驗證之，使用這套程式軟體可以幫助使用者獲取量化的神經細胞形態資訊，例如神經本體的體積、神經細胞的分支數目以及神經細胞的分支長度，雖然實驗結果還需要再做進一步的驗證，但是所有的神經細胞顯微影像皆可在相同規則條件下量化，這將可以提供相對量化答案給使用者作分析。藉由使用這套系統軟體，量化神經細胞形態資訊所產生的耗時問題及可靠性問題皆可得到改善。

There is a need to extract neuronal morphological information of individual neuron to assist neuroscientists for understanding the mechanism of neuronal physiology. However, almost all commercially available software packages are not easy to be modified for some specific application and may possibly make the operation complicated. Thus, an automated three-dimensional morphological information extraction software is developed in this study to quantify two-photon microscopic neuronal images. In this study, a modified region-growing method for segmenting the ROI and quantifying the morphological information of individual neuron is developed and demonstrated. With the help of proposed system, the morphological information such as the volume of soma, the number of branching, and the length of branching can be obtained for quantitative analysis. Although further validation needs to be done, the relative quantification of neuronal morphological information may be good for reference. The problems of time-consuming and reliability in neuronal image analysis may be such alleviated.

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