膝關節軟骨MRI影像之邊界辨識與三維模型重建探討

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陳勁誠(Jin-Cheng Chen) 查詢紙本館藏

畢業系所

機械工程學系

論文名稱

膝關節軟骨MRI影像之邊界辨識與三維模型重建探討
(Image Segmentation and Three-Dimensional Surface Reconstruction of Knee Cartilage for MRI Images)

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摘要(中)

影像物件分割技術可以將器官或組織的輪廓描述出來，可以針對這些區域做特徵的分析，提供醫師或研究人員做為他們診斷或研究時的依據，本研究的主要目標是使用退化性膝關節炎患者的核磁共振影像作為研究對象，然而，在實際運用於醫學影像上的分析，則會產生重大的缺陷與情形（如雜訊敏感度、過度分割、邊界模糊或非均質區域的影響），我們使用影像濾波器進行前置處理，並依據Chan-Vese模式的等階集合法做影像分割，透過區域限制與分層區域限制進行最佳化，將影像序列中關節軟骨予以分割並提供相關的量化資訊（厚薄度和體積資訊）提供給臨床醫師作為術前評估，另一方面透過三維重建的技術也提供病患觀看實際患部受損情形，增加醫師與病患之間雙向的溝通。

摘要(英)

The image segmentation technology can describe the contours of the organ or the structures. It can make the analysis of the characteristic to these areas, and offer to a doctor or the researchers in order to diagnose or study basis. The main target of this research is the use of degenerative knee Magnetic resonance imaging of patients as research subjects. However, when applied to medical image analysis, it has important drawbacks (ex:sensitivity to noise, over-segmentation, fuzzy boundary or the impact of non-homogeneous regions). We use the image pre-processing filter, and Chan-Vese model based Level set method of image segmentation, through the regional limitations and restrictions on the best stratification of the region. Image sequence will be divided in the articular cartilage and provide relevant quantitative information (thickness and volume of information) available to clinicians as a preoperative evaluation. On the other hand, through the three-dimensional reconstruction of the technology also provides patients with damage to watch the actual affected area where increase between physicians and patients with two-way communication.

關鍵字(中)

★ 影像分割
★ 等階集合法
★ 主動輪廓模型
★ 膝關節軟骨

關鍵字(英)

★ Active contour model
★ Level set Method
★ Image segmentation
★ Knee cartilage

論文目次

摘要 I
ABSTRACT II
誌謝 III
目錄 IV
圖目錄 VII
表目錄 X
第一章緒論 1
1.1 前言 1
1.2 文獻回顧 2
1.3 研究目的與方法 5
1.3.1 研究目的 5
1.3.2 研究方法 6
1.4 論文架構 11
第二章磁振造影與膝關節炎之簡介 13
2.1前言 13
2.2磁振造影術簡介 13
2.2.1磁振造影原理 13
2.2.2磁振造影之醫學應用 14
2.2.3磁振成像的優點 16
2.3 膝關節介紹 17
2.4 退化性膝關節炎 18
2.4.1 退化性膝關節炎病理變化 18
2.4.2 退化性膝關節炎的成因 20
2.4.3 退化性膝關節炎的症狀 21
第三章影像前處理 25
3.1 前言 25
3.2 雜訊模型 26
3.3 常見的影像濾波器 27
3.3.1 線性濾波器 29
3.3.2 非線性濾波器 33
3.4影像品質指標 34
3.4.1 絕對性客觀的影像品質指標 35
3.4.2 相對性客觀的影像品質指標 36
3.5 實驗分析與討論 38
3.5.1 實驗結果 39
3.5.2 適應性的參數 49
第四章等階集合法 56
4.1前言 56
4.2隱函數 57
4.2.1 一維空間中分界點 57
4.2.2二維空間中分界曲線 57
4.2.3 幾何工具 59
4.3 符號距離函數 63
4.3.1 距離函數 63
4.3.2 符號距離函數 64
4.3.3 距離轉換 64
4.4 等階集合法之運動形式 64
4.4.1依外力速度場作用而運動 66
4.4.2 依平均曲率作用而運動 67
4.5 重新初始化 68
第五章 MRI影像之區域辨識 70
5.1 前言 70
5.2 定義重建區域 70
5.3 邊界辨識之方法 72
5.3.1 Chan-Vese模型 75
5.3.2 Mumford-Shah函數 76
5.3.3 Level set公式化 78
5.4 區域限制擴充 83
5.4.1 區域限制 84
5.4.2 分層區域限制 85
第六章 MRI膝關節軟骨重建與量化分析 91
6.1 前言 91
6.2 三維軟骨重建 91
6.3軟骨區域選取之量化分析 93
6.3.1 測試條件設定 96
6.3.2 二維輪廓擷取探討 96
6.3.3 三維輪廓點擷取分析 103
6.3.4 量化資訊 111
第七章結論與未來展望 113
7.1 結論 113
7.2 未來展望 115
參考文獻 117

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指導教授

賴景義(Jiing-Yih Lai)

審核日期

2009-6-30

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