臺灣博碩士論文加值系統

本研究擬開發一套利用電腦斷層影像準確計算大腸直腸癌之小顆(≦8毫米)轉移性肺結節體積，利用前後兩次體積計算其體積倍增時間及生長速率，並提出最佳後續追蹤時間間隔。
第一部分利用影像處理技術於大腸直腸癌之小顆(≦8毫米)轉移性肺結節的電腦斷層影像上，分別定位肺結節區域及計算肺結節體積。首先經由直方圖擴展法與自適應性直方圖等化將電腦斷層影像灰階值調整至0~255並修正過亮及過暗的影像。接著進行肺部提取流程，以K-means進行分群及二値化，搭配形態學做初步肺結節定位，並以黃框標示。接著由醫師進行二次確認，將點選之肺結節影像進行血管連接判斷，血管去除後將整個肺結節像素點全部提取，並計算其中心做為下張影像之種子點，達到整顆肺結節輪廓自動化提取。最後利用等值面提取的Marching cube演算法重建及計算肺結節體積，並利用體積33 及322 的驗證樣本以不同形狀拍攝電腦斷層影像，再分別以一維、二維及本研究方法計算其體積，其平均誤差分別為2%及1%，驗證本研究所求體積可信度。
第二部分為醫學分析，將29位前後兩次大腸直腸癌之小顆轉移性肺結節體積做體積倍增時間與生長速率計算，並與一、二維量測方式所得體積及良性肺結節體積做比較，提出最佳後續追蹤時間間隔為3.2個月。

This study plans to develop a method using computed tomogra-phy (CT) to calculate the pulmonary metastasis lung nodules volume of colorectal cancer accurately. The volume doubling time and growth rate are calculated by two consecutive volumes, and the optimum subse-quent tracking time interval is proposed.
Part I uses image processing techniques to analyze the lung cancer CT to localize the lung nodules region and calculate the lung nodules volume. First, the CT gray level is adjusted by histogram expansion method and adaptive histogram equalization to 0~255. The overly bright and dark images are corrected. The lung extraction process is designed. The K-means is used for clustering and binarization, com-bined with morphological approach to obtain the lung region mask. The lung nodules region is localized, and the lung nodules location is indicated by a yellow frame for lung nodules localizing. Afterwards, the doctor makes confirmation twice. The blood vessel connection is judged according to the selected lung nodules image. All of the lung nodules pixels are extracted after the blood vessels are removed. The center is calculated as the seed of next image, so as to extract the whole lung nodules contour automatically. Finally, the Marching Cube algo-rithm of isosurface extraction is used for reconstructing the lung nod-ules volume and calculation. The CT is taken by using the known volume and the same clay in different shapes. Then the volume is cal-culated by one dimension. Two dimension and the method of this study to validate the reliability of the calculated volume, the mean error is 1%.
Part II is medical analysis. The volume doubling time and growth rate of two consecutive metastatic lung nodules volumes of colorectal cancer of 29 patients are calculated, and compared with the volumes obtained by one-dimensional and two-dimensional measurement methods and propose the optimum subsequent tracking time interval is 3.2 months of the volume of non-metastatic lung nodules.

摘要 I
Abstract II
致謝 IV
目錄 V
圖目錄 VIII
表目錄 X
第1章 緒論 1
1.1 研究背景與動機 1
1.2 文獻回顧 2
1.2.1 醫學影像 2
1.2.2 影像增強理論 3
1.2.3 影像分割理論 5
1.2.4 輪廓提取理論 6
1.3 研究目的 8
1.4 論文架構 8
第2章 醫學影像擷取系統與軟硬體介紹 11
2.1 醫學影像擷取系統 11
2.2 軟硬體介紹 13
第3章 醫學簡介 14
3.1 大腸直腸構造及功能 14
3.2 肺部構造及功能 15
3.3 癌症 15
3.3.1 大腸直腸癌 16
3.3.2 治療方式 16
3.4 肺結節介紹 17
3.4.1 種類 17
3.4.2 大小評估 19
3.4.3 後續治療 21
3.5 樣本採納條件 21
第4章 研究方法與理論 23
4.1 影像空間 23
4.2 前處理 24
4.2.1 直方圖擴展法 24
4.2.2 自適應性直方圖等化 24
4.3 影像分割 26
4.3.1 K-means演算法 27
4.3.2 形態學 29
4.3.3 Stefano法 34
4.3.4 Sobel 35
4.4 三維重建 35
4.5 醫學方法 39
4.5.1 體積倍增時間 39
4.5.2 生長速率 40
第5章 實驗結果與驗證 41
5.1 影像處理流程 41
5.1.1 前處理 42
5.1.2 肺部整體分割 44
5.1.3 肺結節輪廓分割 46
5.1.4 肺結節初步定位 47
5.1.5 自動化肺結節輪廓提取 47
5.1.6 輪廓提取比較 52
5.2 體積修正與計算 52
5.2.1 肺結節像素量修正 52
5.2.2 三維重建 53
5.2.3 體積計算 54
5.2.4 體積驗證 55
5.3 醫學分析 56
第6章 結論 62
參考文獻 64

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