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研究生:張書源
研究生(外文):Su-Yuan Chang
論文名稱:血管偵測與顯示系統
論文名稱(外文):Blood vessel detection and display system
指導教授:鍾國亮鍾國亮引用關係陳秋華陳秋華引用關係
指導教授(外文):Kuo-Liang ChungChyou-Hwa Chen
口試委員:鍾國亮陳秋華
口試日期:2011-06-23
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:資訊工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:中文
論文頁數:31
中文關鍵詞:血管攝影黑塞矩陣特徵根多尺度空間醫學影像
外文關鍵詞:blood vessel photographyhessian matrixeigenvaluemulti-scale spacemedical image
相關次數:
  • 被引用被引用:0
  • 點閱點閱:182
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在本論文中,我們發展出一套在缺少背景圖的情況下的血管偵測方法。我們的方法首先透過改良式的區域式直方圖等化法提高數位減法攝影圖的影像對比。之後透過自動化黑塞矩陣為基礎的血管增強遮罩給予每個像素一個適當的血管信任程度,以解決數位減法攝影圖高雜訊問題。最後利用血管信任程度於影像中找出血管的位置。由實驗結果可看出,所提出之方法可以偵測大多數主要的血管,亦可準確地偵測到部分微血管。
In this thesis, we develop a vessel detection method without
background image. In the proposed method, we first exploit the
improved sub-block histogram equalization to enhance the contrast of the image produced by digital subtraction angiography. To reduce the noise in the digital subtraction image, we can assign an appropriate vesselness to each pixel in the image by using the Hessian-based vessel enhancement filters. Finally, according to the assigned vesselness of each pixel, the vessel regions of an image can be detected. By experimenting on some test images, the results demonstrate that the proposed method can detect most principal vessels as well as some capillaries.
圖 索 引
表 索 引
第一章 緒 論
1.1 醫學影像簡介
1.2 血管攝影影像簡介
1.3 血管偵測簡介
第二章 背 景 介 紹
2.1 對比增強
2.2 血管偵測
2.2.1 黑塞矩陣(Hessian Matrix)
2.2.2 尺度空間表示法
2.2.3 黑塞矩陣特徵根的評估
2.2.4 二次偏微分的正規化
2.2.5 選擇合適的特徵描述
第三章 研 究 方 法
3.1 前處理
3.2 植基於黑塞矩陣的自動化血管增強遮罩
3.3 偵測血管
第四章 使 用 者 介 面
第五章 實 驗 結 果
5.1 前處理
5.2 血管增強遮罩
5.3 偵測血管
第六章 結 論
參 考 文 獻
[1] [Online] 醫學影像-維基百科 Available:http://zh.wikipedia.org/wiki/%E9%86%AB%E5%AD%B8%E5%BD%B1%E5%83%8F
[2] [Online] 陸坤池, 周鈺峰, 施威名, 許智鈞, 簡隆至, 許博仁, X-ray影像系統介紹 Available:http://bmeimage.be.cycu.edu.tw/Lab/database/X-RAY/X-ray.html
[3] [Online] 國醫中心放射診斷部 電腦斷層掃瞄 Available:
http://wwwu.tsgh.ndmctsgh.edu.tw/TM/mywebs/fang_she/mysite13/CT注意事項.htm
[4] [Online] 核磁共振-維基百科 Available:
http://zh.wikipedia.org/wiki/%E6%A0%B8%E7%A3%81%E5%85% B1%E6%8C%AF
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[9] M. J. R. Fatemi, S. M. Mirhassani and B. Yousefi, “Vessel segmentation in x-ray angiographic images using hessian-based vesselness filter and wavelet based image fusion,” IEEE International Conference on Information Technology and Applications in Biomedicine, pp. 1-5, 2010.
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[12] S.R. Aylward, E. Bullit, “Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction,” IEEE Transactions on Medical Imaging, vol. 21, pp. 61-75, 2002.
[13] 鍾國亮教授, 影像處理與電腦視覺, 東華書局, 台北, 第四版, 2008.
[14] J. Y. Kim, L S. Kim, and S. H. Hwang, “An advanced contrast enhancement using partially overlapped sub-block histogram equalization,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, pp.475-484, 2001.
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[16] F. Y. Shin, S. Cheng, “Automatic seeded region growing for color image segmentation,” Image and Vision Computing, vol.23, pp.877-886, 2005
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