傳統的神經追蹤方法著重於追蹤單一神經元，因此在彩虹腦技術產生的含有多神經與色彩的影像中較不適用。在本篇論文中，我們提出了在不同色彩通道上以自動的方式找尋神經元細胞核並且以形態學與三維空間中利用事先設定的前後景資訊做透明度分析的方法追蹤其突觸，最後需再透過人工給定閥值來切割出單一神經的半自動化系統。本篇論文的想法是基於生物學家手動切割神經時的流程來設計，先根據神經元細胞核與突觸在形狀上巨大的差異來定位出細胞核的位置，再以其灰階值和三維空間中點與點之間的相連性做為追蹤突觸的根據。而在神經突觸相互纏繞的部分，我們將通常使用於二維空間的透明度分析方法拓展到了三維空間之中，並且取得了一些不錯的成果，在結果章節中展示出一些克服的結果與詳細的狀況說明。

Due to dozens of colorized neuron fibers spreading densely in a very intricate structure, it is difficult to trace them by using existing algorithms designed for monochrome single-neuron images and also time-consuming to label them manually. We propose a neuron segmentation system on Drosophila Brainbow image stack. The idea follows the steps of manually, that is, the system is designed to imitate the way biological experts identify different neurons. Besides, because the “color information” of Brainbow imagery is a composite signal coming from those captured by different band-pass filters, it is straightforward to consider each channel independently. On the other hand, according to the considerable morphological differences between cell bodies and neuron fibers, some three-dimensional morphological processing methods could also be applied. Based on the location and the fluorescence intensity of each cell body, we can trace and segment each neuron by considering the similarities among adjacent voxels. The proposed system can provide segmentation results semi-automatically, and thus it would be useful for biologists in identifying the neural-circuits.

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