口腔磁振影像舌頭構造之自動分割

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姓名

簡村誠(Tsun-Cheng Chien) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

口腔磁振影像舌頭構造之自動分割
(Automatic Segmentation of the Tongue Structure from Human Oral MR Images)

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摘要(中)

本研究的最終目標是利用建構口腔舌頭模型，來研究生理語音構音的機制。因此利用口腔磁振影像分割出舌頭構造所重建的舌頭模型來代表實際的舌頭大小是很重要的步驟，而舌頭磁振影像分割的好壞則關係著重建出來的三維影像準確度。本研究主要目的在節省時間人力成本考量下，對口腔磁振影像自動分割出舌頭構造，並與手動分割出來的結果做比較以瞭解自動分割的準確性。本研究提出結合等位函數法與梯度向量流蛇模型的方法，利用等位函數法做影像自動分割，再用梯度向量流蛇模型做修正舌頭邊緣並平滑化輪廓的步驟。結果顯示本研究一個個案分割的時間約需5.5分鐘，比熟悉舌頭構造操作者手動分割所需22.6分鐘來得快。本研究的準確評估方法是利用相似係數法，結果顯示我們用的方法對大部分切面之平均相似係數都大於0.88 (8位個案，4女、4男)，達到不錯的結果。比較本研究分割與手動分割重建後的三維影像在外形上大致相同只是有些不平整，但從中央矢狀切面來看舌頭內部構造在直覺上沒有差別。

摘要(英)

The long term purpose of this research is to study the physiological articulation mechanism based on a three-dimensional (3D) tongue model that is reconstructed from oral magnetic resonance images (MRI). The accuracy of reconstructed 3D tongue depends on the results of image segmentation of tongue structure from oral MRI data. The main purpose of this study is to automatically segment tongue structure from the oral MRI data not only to save time and efforts for data processing but also to keep the accuracy of automatic segmentation the same as the manual segmentation. This study adopted Level Set (LS) method to segment image automatically and used Gradient Vector Flow Snake (GVFS) method to move the contours toward the tongue boundary and to smooth the segmented contours. The results of our study showed that 5.5 minutes were taken to segment one subject automatically. This is faster than the time needed (22.6 min.) for manual segmentation by a well-trained operator. Similarity index was used to evaluate the accuracy of our segmentation. The results by our method showed average slice similarity index is greater than 0.88 (8 subjects, 4 females, 4 males). This indicates excellent agreement. In addition, the 3D tongue reconstructed from this study is less smooth than by the manual segmentation, and the shape of the 3D tongue reconstructed from this study is approximately similar to the manual segmentation. Finally, the internal structure of the tongue observed from this study from the tongue mid-sagittal slice is visually the same as the manual segmentation.

關鍵字(中)

★ 影像分割
★ 磁振影像
★ 等位函數法
★ 梯度向量流蛇模型
★ 蛇模型

關鍵字(英)

★ Image Segmentation
★ Magnetic Resonance Imaging (MRI)
★ Level Set
★ Gradient Vector Flow Snake
★ Snake

論文目次

中文摘要 . I
Abstract II
致謝 . IV
目錄 . V
圖目錄 VIII
表目錄 XIII
第一章序論 1
1.1 研究動機 1
1.2 文獻探討 2
1.2.1 傳統分割方法 2
1.2.2 蛇模型分割法 6
1.2.3 等位函數法 10
1.3 論文架構 12
第二章等位函數法 14
2.1傳統等位函數法 14
2.1.1 等位函數方程式 16
2.1.2 等位函數的重初始化 18
2.2 不用重初始化的等位函數 19
2.2.1 數值方法 23
2.3 梯度向量流蛇模型 23
2.3.1 數值方法 27
第三章模型參數與方法 29
3.1 磁振影像說明 29
3.2 模型參數 30
3.2.1 等位函數法參數 30
3.2.2 梯度向量流蛇模型參數 34
3.3 研究方法 37
3.3.1 評估方法 44
第四章結果與討論 46
4.1 影像分割結果 46
4.2影像分割結果評估 51
4.3 討論 56
第五章結論與未來展望 67
5.1 結論 67
5.2 未來展望 67
附錄 A 蛇模型能量最小化的Euler equation 69
附錄 B 蛇模型能量最小化的數值方法 72
附錄 C 用來決定參數ν的經驗法則 75
附錄 D 8個案經過修正後的分割、評估、重建的結果 77
參考文獻 101

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指導教授

吳炤民(Chao-Min Wu)

審核日期

2009-2-2

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