臺灣博碩士論文加值系統

由於現今電腦斷層攝影術(Computed tomography，CT)已經相當普及，有鑑於CT影像對骨組織的高顯像能力，絕大多數的骨病變病患在手術前都會進行CT造影。CT影像在院內大多僅被用於二維的病理判讀，但一組序列式CT影像能夠提供病患身體的三維資訊，因此從CT影像能夠進行骨組織的三維模型重建，現今亦有許多研究是針對這個方向在進行。本研究之研究對象是針對CT影像的利用，從多用途之生醫影像軟體平台的建構開始，進行包括序列影像的三維顯示技術、骨組織的分離擷取技術以及骨組織的三維模型重建技術的開發；為了跳脫傳統二維顯示介面，本研究以三維顯示技術為基礎以增加介面的靈活度及直覺性，三維顯示之核心演算法則是以光線投射法及立體渲染法為主；為了能夠分離各個骨組織，本研究改良傳統區域成長法的缺陷，以多區域的概念配合自行開發之演算法進行複數骨組織的分離及擷取；最後的網格化則是採用行進方塊法，並配合本研究之需求略作修改及調整。

Three-dimensional (3D) surface reconstruction from computed tomography (CT) slices has been received more and more attention in preoperative planning as it provides three-dimensional data of the tissue of interest, rather than two-dimensional images . CT has highly developing capability of bone tissue , thus CT images are usually used for bone diseases . This research aims to the usage of CT image , starting from the construction of multipurpose medical imaging software , including 3D display , segmentation of bone tissue and triangulation ; For mobility and intuition , we use ray-casting and volume-rendering to achieve high performance 3D display functions . We improved traditional region-growing algorithm in order to segment bone tissues . And we use improved marching-cubes to triangulate bone tissues .

摘要 I
Abstract II
誌謝 III
目錄 IV
圖目錄 VII
表目錄 XII
第一章 緒論 1
1.1 前言 1
1.2 文獻回顧 2
1.2.1 三維顯示方面 2
1.2.2 骨組織擷取方面 3
1.2.3 網格化方面 5
1.3 研究目的與方法 6
1.3.1 研究目的 6
1.3.1 研究方法 7
1.4 論文架構 8
第二章 三維影像顯示技術 11
2.1 前言 11
2.2 座標轉換 11
2.2.1 影像座標轉換 VDCS -> WCS 12
2.2.2 影像座標轉換 WCS -> VDCS 16
2.2.3 等位面上快速取點 19
2.2.4 座標轉換綜合使用 21
2.2.5 三維線性內插 23
2.2.6 改良前後比較 26
2.3 彩現 26
2.3.1 光衰減 30
2.3.2 塗彩 30
2.3.3 材質染色 33
2.3.4 立體渲染法 33
2.4 立體視覺化技術 37
2.4.1 產生視差影像 37
2.4.2 色彩轉化技術 37
第三章 骨組織擷取 41
3.1 前言 41
3.2 區域成長法 41
3.2.1 輪廓擷取 44
3.2.1.1 四近鄰尋邊 48
3.2.1.2 區域尋邊 50
3.2.2 改良後區域成長法－單一骨組織擷取 52
3.2.3 區域補償 58
3.2.3.1 區域膨脹及收縮 58
3.2.3.2 內部填滿 61
3.2.3.3 區域自動補償 64
3.3 複數骨組織擷取 65
3.3.1 多重區域成長 65
3.3.2 多區域自動成長 68
3.3.3 自動多區域劃分 70
3.3.4 自動多區域合併 73
3.3.5 區域再分割 77
第四章 網格化 79
4.1 前言 79
4.2 Contour based網格化方法 79
4.3 Voxel based網格化方法 80
4.3.1 三維實體貼面法 80
4.3.1.1 網格不合理邊處理 82
4.3.1.2 網格簡化 82
4.3.1.3 網格外型改善 85
4.3.2 行進方塊法 90
4.3.2.1 MC網格拓樸問題 93
4.3.2.2 MC網格數量問題 93
4.3.2.3 MC網格外型問題 97
4.3.2.4 MC網格品質問題 100
4.3.3 三維實體貼面法及MC法比較 104
第五章 範例及驗證 109
5.1 前言 109
5.2 程式介面介紹 109
5.3 三維顯示效能數據測試 109
5.4 骨組織分離範例 114
5.4.1 範例一 116
5.4.2 範例二 116
5.4.3 其他範例－全域分割閾值 118
5.4.4 其他範例－全域分割閾值及區域再分割 123
5.4 CT精確度驗證 132
第六章 結論與未來展望 137
6.1 結論 137
6.2 未來展望 138
參考文獻 141

[1] R. A. Drebin, L. Carpenter and P. Hanrahan, “Volume rendering”, ACM SIGGRAPH Computer Graphics, Vol. 22, No.4, pp. 65-74, 1988.

[2] M. Levoy, “Display of surfaces from volume data”, IEEE Computer Graphics and Applications, Vol. 8, No. 3, pp. 29-37, 1988.

[3] M. Levoy, ”Efficient ray tracing of volume data”, ACM　Transactions on Graphics, Vol. 9, No. 3, pp. 245-261, 1990.

[4] H. Ray, H. Pfister, D. Silver, and T. Cook, “Ray-casting architectures for volume visualization”, IEEE Transactions Visualization and Computer Graphics, Vol. 5, No. 3, pp. 210-223, 1999.

[5] L. Westover, “Interactive volume rendering”, Proceedings of the 1989 Chapel Hill Workshop on Volume Visualization, pp. 9-16, May 1989.

[6] L. Westover, “Footprint evaluation for volume rendering”, Computer Graphics, vol. 24, No. 4, pp. 367-376, 1990.

[7] P. Lacroute and M. Levoy, “Fast volume rendering using a shear-warp factorization of the viewing transformation”, Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques, pp. 451-458, July 1994.

[8] R. Adams and L. Bischof, "Seeded Region Growing," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, No. 6, pp. 641–647, June 1994.

[9] M. Kass, A. Witkin and D. Terzopoulos, ”Snakes: Active contour models”, International Journal of Computer Vision, Vol. 14, pp. 321–331, 1988.

[10] A. Yezzi, S. Kichenassamy, A. Kumar, P. Olver and A. Tannenbaum, “A geometric snake model for segmentation of medical imagery,” IEEE Transactions Medical Imaging, Vol. 16, No. 2, pp. 199-209, 1997.

[11] L. D. Cohen and I. Cohen , “Finite element methods for active contour models and balloons for 2D and 3D images”. IEEE Transactions Pattern Analysis and Machine Intelligence, Vol. 15, No. 11, pp. 1131–1147, 1993.

[12] H. Tek and B.B. Kimia, “Volumetric segmentation of medical images by three-dimensional bubbles”, Computer Vision and Image Understanding, Vol. 64, No. 2, pp. 246–258, 1997.

[13] S. C. Zhu and A. L. Yuille , “Region competition: unifying snakes, region growing, and Bayes/MDL for multiband image segmentation”, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 18, No. 9 , pp. 884–900, 1996.

[14] T. B. Sebastian, H. Tek, J. J. Crisco, S. W. Wolfe, and B. B. Kimia. “Segmentation of carpal bones from 3D CT images using skeletally coupled deformable models”, MICCAI’98, pp. 1184–1194, 1998.

[15] S. Ganapathy and T. G. Dennehy, ” A new general triangulation method for planar contours”, Proceedings of the 9th Annual Conference on Computer Graphics and Interactive Techniques, pp. 69-75, July 26-30, 1982.

[16] D. Meyers, “Multiresolution tiling,” Computer Graphics Forum, Vol. 13, No. 5, pp. 325-340, 1994.

[17] J Jeong J, K Kim, H Park, H Cho and M Jung, ” B-spline surface approximation to cross-sections using distance maps”, The International Journal of Advanced Manufacturing Technology, Vol. 15, pp. 876-885, 1999

[18] W. E. Lorenson and H. E. Cline, ”Marching cubes: a high resolution 3D surface construction algorithm”, SIGGRAPH ''87 Proceedings, pp. 163-169, 1987.

[19] M. Du¨urst, “Additional reference to ‘Marching Cube’”, Computer Graphics, Vol. 22, pp. 2-3, 1988.

[20] G. Nielson and B. Hamann, “The asymptotic decider: resolving the ambiguity in marching cubes”, 1991 IEEE Proceedings on Visualization, pp. 83-91, 1991.

[21] I. Semenova, V. Savchenko and I. Hagiwara ,”Two techniques to improve mesh quality and preserve surface characteristics”, Proceedings of 13th International Meshing Roundtable, pp 277–288, 2004

[22] I. Semenova, V. Savchenko and I. Hagiwara, ”Improvement of triangular and quadrilateral surface meshes”, Proceedings of the 14th International Conference on Computer Graphics and Vision (GraphiCon’2004), pp. 79–87, 2004