創傷性腦部損傷及其相關疾病是世界各地主要健康問題之一。基於生物醫學的目的，生物醫學家選擇斑馬魚作為模式生物，以了解腦部損傷前後之生理特徵與修復機制其相應於血管新生和血管修復的變化，進而將此生物醫學相關性推論至人類系統，以提供創傷性腦部損傷患者有效的治療方式。在本論文中，我們提出一個應用於斑馬魚腦血管封閉循環系統中的量化評估之三維影像分析系統，分析其中對於血管新生和重塑有意義的資訊，並加以量化以描述其相對於腦損傷與修復機制的情形，最後提供趨勢圖表以利於生物醫學家的研究與觀察。

　　應用於斑馬魚腦血管系統之三維共聚焦影像序列，本論文提出的三維影像分析系統可以分為三個部分，自動定位架構、斑馬魚腦血管提取架構、斑馬魚腦血管分析架構，以量化斑馬魚腦血管系統中對於血管新生和重塑有意義的訊息。首先，此系統結合高帽轉換，高增幅濾波器和型態學觀點之雙閾值法，從原始血管三維影像序列中去除染色滲液和其連續共聚焦影像重疊的部分以提取整個血管脈絡。更進一步地，此系統演算法將血管增生分析融合物件檢測與追蹤技術的概念，進而追蹤每一個有意義的特徵，例如：血管分支點和骨幹，以計數血管分支點數量和推算血管長度，並量化這些有意義的參數以提供血管新生和修復的趨勢圖表。根據實驗結果，本系統所提取的血管分支點和血管線段資訊可以確實地描述完整的斑馬魚腦血管系統，且本系統所提供的量化數據和趨勢圖表則可以貼切地意味著斑馬魚腦血管系統的增長趨勢和修復情形。

　　總括而言，我們提出一個新的整合系統以增強原始三維共聚焦顯微影像序列中的斑馬魚腦血管系統之信號，進而提取其整個血管脈絡，並分析其中的血管特徵以量化其有意義的參數，進一步利用斑馬魚腦血管系統的時移影像集產生可視化視頻，以達到協助生物醫學家有效地評估神經血管損傷情形並追蹤其再生癒合的過程。

Trauma brain injury and its related diseases are the major health problem around the world. For biomedical purpose, biomedical scientists select the zebrafish as a model organism, and they want to understand the corresponding changes of angiogenesis and vascular remodeling between brain lesion and reconstruction. Thereby they could extrapolate the biomedical correlations from the zebrafish model to the human model to provide an effective treatment for trauma brain injury patients.

In this thesis, a three-dimensional image analysis system for quantitative assessment of angiogenesis and vascular remodeling in a closed circulatory system of the zebrafish brain is presented to provide the meaningful information for observation and research by biomedical scientists. The proposed system is composed of three parts such as the proposed automatic positioning scheme, the proposed zebrafish brain vascular extraction scheme and the proposed zebrafish brain vascular analysis scheme to quantify the meaningful angiogenesis information from the three-dimensional confocal imaging sequence of the zebrafish brain vascular system.

At first, the proposed system combines the top-hat transformation, high-boost filter and morphological double-thresholding to extract the whole vasculatures and remove the dye effusion and the repeated vasculatures in the consecutive images. Furthermore, the proposed algorithm has integrated the object tracking and detection algorithm with the angiogenesis analysis for tracking every meaningful feature such as the vascular branch points and lengths, and then quantifies these meaningful parameters to provide trend graphs of the angiogenesis and vascular remodeling. According to experimental results, the vascular branch points and lengths extracted by the proposed system can indeed describe the complete information of the whole zebrafish brain vascular system, and the quantitative data provided by the proposed system can imply pertinently the growth trend and the remodeling tend.

In conclusion, we provide a new integrated system to enhance the signals of the zebrafish brain vascular system from a three-dimensional original microscopic image sequence, extract its whole vasculatures, analyze its vascular features, quantify its meaningful parameters and utilize the time-lapse images of the zebrafish brain vascular system to generate a visualization video which could help biomedical researchers to effectively assess the neurovascular damage and to track the regenerative healing process.

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