臺灣博碩士論文加值系統

本文提出一種新型自適應閥值等位函數法(New Adaptive Threshold Level Set)，以Fuzzy C-Means 演算法自動計算閥值，此方法是從Active Contours Without Edges改良而成的主動式輪廓線模型，應用在腦部MR影像的白質和灰質區域之自動化分割。由實驗結果顯示本文所提出之等位函數法能自動分割134張橫切面MR腦部影像白質和灰質區域部分，實驗分割結果以表面成像法(surface rendering)完成腦部灰質表面3D影像之重建。

In the paper proposes a New Adaptive Threshold Level Set Model. The model is based on the methodology of Active Contours Without Edges . The proposed method is then applied to the segmentation of gray matter in brain MR images. There are two threshold values, lower threshold and upper threshold, to be decided for locating the contours of the gray matter of the brain MR images. The threshold values are determined by Fuzzy C-Means Algorithm. By combining segmentation of 134 planar MR brain gray images. A three-dimensional model of the brain gray matter has been successfully constructed.

目錄
頁數
摘要…………………………………………………………………………i
ABSTRACT………………………………………………………………ii
致謝………………………………………………………………………iii
目錄……………………………………………………………………iv
表目錄……………………………………………………………………vii
圖目錄……………………………………………………………………viii
第一章 緒論……………………………………………………………1
1.1 研究背景………………………………………………………1
1.2 研究動機與目的………………………………………………2
1.3 方法與材料……………………………………………………4
1.4 論文大綱………………………………………………………5
第二章 影像前處理……………………………………………………6
2.1 數學形態學……………………………………………………6
2.2 二元形態學…………………………………………………8
2.2.1 數學形態學基本運算………………………………9
2.3 Skull Stripping之步驟…………………………………………14
2.3.1 去頭殼之步驟圖示…………………………………………17
2.4 大腦前處理之實驗結果………………………………………19
第三章 主動式輪廓線模型……………………………………………20
3.1 幾何式主動輪廓線模型………………………………………22
3.2 Active Contours Without Edges之理論………………………25
第四章 新型自適應閥值等位函數法…………………………………32
4.1 新型自適應閥值等位函數法之理論………………………32
4.2 閥值的自動選取……………………………………………40
4.2.1 Fuzzy C-Means分群法……………………………………41
4.2.2 Fuzzy C-Means 演算法之介紹……………………………44
4.2.3 Fuzzy C-Means演算法之實驗結果………………………46
4.3 閥值取得之方法…………………………………………47
4.3.1 FCM與分群數目之決定……………………………………47
4.4 實驗結果………………………………………………50
4.4.1 實驗分割結果比較………………………………………52
4.4.2 影像分割之精確性………………………………………56
4.4.3 影像分割之精確性結果與討論……………………………57
第五章 三維立體成像…………………………………………………61
5.1 成像法概述…………………………………………………61
5.1.1 體積成像法………………………………………………62
5.1.2 表面成像法………………………………………………63
5.2 成像工具……………………………………………………65
第六章 總結與未來展望………………………………………………67
6.1 總結……………………………………………………………67
6.2 未來展望………………………………………………………68
附錄A 軟體介紹………………………………………………………69
A.1 Amira………………………………………………………69
附錄B 方程式之推導…………………………………………………72
B.1 Minkowsky addition之推導………………………………72
B.2 Euler-Lagarange方程式推導………………………………75
B.3 curvature之推導……………………………………………77
參考文獻………………………………………………………………78

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