臺灣博碩士論文加值系統

癌症在過去十年蟬聯人類十大死因之首，世界各國為了找出癌症的根治之法，紛紛投入治療癌症的實驗。由於癌細胞必須倚賴生物血管中的氧氣及養分才能存活，於是實驗樣本大多採用小型動物為主(例如: 兔子、白老鼠…等)，在其體內置入癌細胞令其感染，之後再將實驗藥物注入其體內，觀察血管的變化，以決定該實驗藥物是否對癌細胞真正有效。近幾年由於動物樣本的成本逐漸增加，而且實驗的過程必須將動物進行解剖，行為上十分不人道，實驗之後動物的後續處理流程也非常麻煩。然而受精雞蛋中的雞胚胎成長速度較快，價格也較低廉，因此容易快速地觀察到實驗結果。雞胚胎也同時具有血管構造，十分適合代替動物樣本。
由於樣本數量眾多，醫護人員在檢視反應結果時，常常需要耗費大量的時間以及人力來判斷結果好壞。因此本篇提出一種利用影像處理技術來輔助判斷實驗後雞胚胎的結果，節省醫護人員的時間精力。此技術可分為兩個部分 : 蛋黃與非蛋黃區域的分割以及蛋黃區域之血管切割。首先，本篇利用R、G、B三種灰階圖間的相互輔助，使蛋黃與非蛋黃區域間對比拉開，再利用Local Cross Thresholding 將兩者分離。之後針對蛋黃區域中的血管使用Run-Length讓血管更明顯，接著依然使用Local Cross Thresholding 將血管從蛋黃區域中切割出來。由於切割出來的血管會伴隨著雜訊相連，因此使用Opening將血管和雜訊切開，並利用細線化、區域標籤等方法將雜訊去除，萃取出血管區域。
實驗結果以Box Counting Dimension (簡稱BCD)判斷的血管的密度，並分別計算Ground Truth、本篇方法以及人工肉眼判斷血管方法的BCD值，BCD值與Ground Truth的BCD值接近者即表示結果較佳。實驗結果顯示:本篇方法的BCD值較接近Ground Truth，故表示本篇方法比人工肉眼判斷血管方法有較佳的結果。

Cancer has been the leading first of - first ten causes of death in humans in the past ten years. Many researchers have invested in the cancer experiments in order to find the cure for cancer. Because cancer cells have to rely on oxygen and nutrients in biological vessel to survive, researchers usually need small animals for experimental sample (for example: rabbits, mouses, etc ….), put cancer cells into the small animals’ bodies to make them infected, inject the experimental drug and observe the changes in blood vessels to determine whether the experimental drug against cancer effectively. In recent years, the cost of animal samples becomes increase. Moreover, the animals must be dissected in the experiments, The processing of animal experiments is very troublesome. However, the chicken chorioallantoic membrane grows faster, the price is cheaper, and it is easy to observe the results immediately. Chicken chorioallantoic membrane which has vascular structure is suited to replace other animal samples.
Due to the large quantity of samples, the researchers needs to takes a lot of time on viewing the results of the reaction to judge good or bad results. Therefore we proposed a technology to determine the results of the chicken chorioallantoic membrane. This technology can be divided into two parts: non-yolk and yolk region segmentation and vessel segmentation in yolk region.
In the first part, we use R, G, B three kinds of gray scale to let the boundary between non-yolk and yolk region more obvious. Then, Local Cross Thresholding is used to segment non-yolk and yolk region. In the second part, Run-Length is used to make blood vessels in the yolk region more obvious and Local Cross Thresholding is used to segment vessels in yolk region. Because there is noise after blood vessels were segmented, we use Opening to divide them, and Thinning and Region Labeling to remove the noise.
We use Box Counting Dimension (BCD) to determine the density of blood vessels. Then, BCD values of Ground Truth, propose methods and artificial blood vessels judgment method are calculated. According to the experimental results, BCD values of the proposed method are close to those of Ground Truth. The proposed method has better results.

Table of Contents
摘要.....................i
Abstract.................ii
Table of Contents........iv
List of Tables...........v
List of Figure...........vi
Chapter 1 Introduction....1
Chapter 2 Related Work....6
2.1. Region Labeling......6
2.2 Mathematical Morphology....10
2.2.1 Dilation & Erosion.......10
2.2.2 Thinning.................12
2.3 Run-Length.................13
2.4. BCD (Box Counting Dimension).....14
Chapter 3 Vessel BCD Method........16
3.1 The Segmentation of Yolk Area and Non-Yolk Area 16
3.2 Separating Vessels in Yolk Area..........21
Chapter 4 Experimental Result................28
4.1 The Result of Segmentation of Vessels in Yolk Area .............................................28
4.2 The Result and Comparison of BCD Value....31
Chapter 5 Conclusion.......34
Reference..................36

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