面向断层医学图像的三维重建与关键技术研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
医学图像数据(如计算机断层扫描(CT)数据及核磁共振图像(MRI)数据)的可视化技术经过二十多年的发展如今已经作为医学图像处理中研究的热点问题之一。三维重建是医学图像可视化的最直观的方法。要实现医学图像的三维重建,首先就要对图像数据进行处理,以便从中提取出感兴趣的器官、组织或病变体的外轮廓,从而实现这些被提取出的器官、组织或病变体的三维重建,重建出模型,达到辅助治疗、手术规划、教学模型和假肢设计等目的。在医疗诊断和外科手术策划中,应用逆向工程技术生成病人组织的三维数字模型,进而利用快速成型技术制作手术模型,医生在此基础上进行诊断及手术,能有效地提高诊断和手术水平,缩短时间,节省费用,提高手术的安全性。本文的核心研究问题是断层医学图像的三维重建。
     本文首先回顾了逆向工程和医学图像的三维重建的研究背景,并对断层数据的采集方法做了说明。介绍了数字图像处理、医学图像重建和CAD模型的转换方法和研究现状。本文以此为背景,主要对断层医学图像上的轮廓线的提取和曲面的几何重建及其相关技术进行了研究和实现,主要包括断层图像的图像增强和降噪处理,边缘检测和轮廓线提取,曲面重建算法和三维表面模型转换,以及曲面重建过程中的轮廓匹配和分支问题的解决方法。
     针对医学图像对比度低、噪声较大、灰度缓慢变化的特点,本文首先利用灰度均衡算法进行预处理,以提高图像的对比度,然后利用中值滤波保持边缘信息的平滑效果和小波变换良好的局部化特性和其固有的多尺度特性,通过中值滤波和小波变换结合的方法对图像进行增强处理。实验表明该算法取得了较好的效果,而且可以处理低质量或边缘模糊的医学图像。
     边缘轮廓提取是三维重建的一个主要的前期处理过程。利用Canny算子和边界跟踪在提取单像素轮廓方面有较好的效果,具体针对医学图像边缘轮廓提取的特点,提出了一种利用迭代的改进Canny边缘检测和边界跟踪来提取图像的轮廓线的方法,提取出单像素和连续封闭的边缘轮廓。
     文中第四章介绍了文中曲面重建的理论基础——B样条曲线曲面的知识。介绍了曲线曲面的定义、性质、正算和反算方法。文中接着对轮廓线表面重建方法——基于B样条曲面的表面重建进行了研究。首先分析了型值点获取中的主要关键技术,包括特征点的选取和采样点的确立。依据曲率特征首先提取各层特征点,对其重采样使每行(列)获得统一的采样点数。再对采样点插值得到非均匀双三次B样条曲面。最后,在一定控制精度下对曲面依据距离特征进行节点插入,通过最小二乘逼近法算出新的控制顶点,从而得到误差在容许范围内的逼近曲面。根据断层轮廓的特点,本算法综合运用了周期B样条和非周期B样条,讨论了封闭曲面和非封闭曲面的计算方法。另外插值和逼近的结合应用使该算法考虑到了曲面重建的精度,减少了计算量。除此之外,文中还对重建表面模型向CAD实体模型的转换过程进行了研究。
     文中接着研究了复杂曲面重建中遇到的两类关键技术问题——轮廓匹配和分支问题。文中给出了多轮廓曲面重建和含有复杂嵌套问题的多轮廓曲面重建时的匹配方法:通过建立轮廓树,确定轮廓的内外属性以及轮廓之间的相互嵌套关系,并缩小轮廓匹配的搜索范围;在轮廓树的基础上,利用阈值半径寻找轮廓,确定相邻切片上轮廓的对应关系。另外本文对分支问题可能遇到的情况和解决方法进行了研究。利用加权补分法,进行母轮廓分割,并结合中间层的插入,解决分支问题,从而进行曲面重构。
At present,image data visualization,especially visualization of medical image (such as computed tomography(CT) and magnetic resonance imaging(MRI)),has become one of the hotspots of image processing research after more than two decades development.Three-dimensional(3D) reconstruction is the most intuitive method of the medical image visualization.In order to achieve 3D reconstruction of the medical images,we must process images first.So we can detect the contours of the interested templates,organize and pathological area easily.Then,we can achieve the 3D reconstruction of the extracted organs,tissues or body lesions,and get the purpose of adjuvant therapy,surgical planning,teaching model and prosthetic design. In medical diagosis and surgical planning,3D figure model of the sick organization is generated by the application of reverse engineering.Further,operation model is producted by the use of rapid prototyping technology.On the basis of the model, doctor achieves diagosis and surgery,which effectively improve the level of diagnosis and surgery,shorten the time,save the cost,and improve the safety of surgery.The center issue of this thesis is the 3D reconstruction of medical slice-images.
     In this paper,we begin with an introduction to reverse engineering and 3D reconstruction technique of medical images,and we introduce the collection methods of slice-images data.Then,we introduce the methods and research status of digital image processing,medical image reconstruction and CAD models conversion.We mainly research and implement the methods and related technologies on the extraction of contour lines of medical slice-images and geometric surface reconstruction,which includes image enhancement and noise reduction processing of slice-images,edge detection and contour extraction,surface reconstruction algorithm,and the conversion of 3D model surface.
     According to the low contrast,noise and slow changes of medical images,a gray balance algorithm is used for pre-processing,that can improve image contrast. Then,combining median filtering with wavelet transform to enhance and denoise image.The results show that the algorithm achieves good effects,and can deals with low quality or marginal vague images.
     Contour extraction is one of the main pretreatment process of the 3D reconstruction.Using of improved Canny edge detection and boundary tracking,the paper proposed a image contours extracted method,thus propose a single pixel and closed contours.
     In Chapter 4 of the paper,we introduce the basical theorey of surface reconstruction-the knowledge of B-spline curves and surfaces,and the definition, properties,calculation and backcalculation methods of curves and surfaces.Then, the surface reconstruction method-based on the B-spline surface reconstruction were studied.Fist,the paper analyse the key technologies of data points accessed, including the selection of feature points and the establishment of sampling points. Besides,we extracted feature points based on curvature feature,and resampled feature points in order to get a unification sampling points in each line(column). Then,we interpolated sampling points to get a bi-cubic non-uniform B-spline surface.Finally,we inserted nodes on the surface based on distance feature under the certain control accuracy,and calculated the new control points through the least-squares approximation method,to get approximate surface within the permissible range error.Based on the characteristics of slice contours,we integratively used B-spline cycle and non-cycle B-spline,and discussed how to calculate closed and non-closed surface.In addition,the combination of interpolation and approximation reduces the computational complexity.Finally,the paper studied the conversion process from the surface model to the CAD model.
     Then,the paper studies the two key technical issues of surface reconstruction—matching and branch.First,the paper gives the methods of many surfaces reconstruction and nested surfaces reconstruction:Through the establishment of tree contour,we recognize the in-out features of contours and the outline of the relationship between the contours,and reduce the searching range.Based on tree contour,we find marching contour by use of the threshold radius to determine the correspondence contour on the adjacent sections.Second,the possible problem of branch was studied.Using weight segmentation method,combined with interpolation,we separated the mother contour to solve the branch problem and reconstruct surface.
引文
1.章鲁,衬瑛,顾顺德等,医学图像处理与分析[M].上海科学技术出版社,2006.
    2.Franck,L.,L.Marc,and F.Francis,On the use of entropy power for threshold selection[J].Signal Processing,2004.84:p.1789-1804.
    3.Atkins,M.,S.and B.T.Machiewich,Fully automatic segmentation of the brain in MRI[J].IEEE Transaction on Medical Image,1998.17(1):p.98-107.
    4.Pierre,S.,Morphological image analysis[M].Berlin:Springer Verlag,1998.
    5.Soble,I.,Camera models and machine perception.Stanford AI Memo 121,1970,5.
    6.Sobel,I.,Camera models and machine perception.Stanford AI Memo 121,1970,5.
    7.Hancock,E.R.and J.Xittler,Edge-labeling using dictionary-based Relaxation[J].IEEE Transaction on Pattern Anal.Machine Intell,1990.12(2):p.165181.
    8.Yuan,Y.W.and I.M.Yan,A neural network approach for 3-D face shape reconstruction[C].Proceeding of 2002 International Conference on Machine Learning and Cybernetics,IEEE,2002:p.2073-2077.
    9.Dusan,H.and Z.Damjan,Combined edge detection using wavelet transform and signal registration[J].Image and Vision Computing,2007.25:p.652-662.
    10.Yong,W.,H.Yuanjun,and H.Cal.,Optimal threshold selection algorithm in edge detection based on wavelet transform[J].Image and Vision Computing,2005.23:p.1159-1169.
    11.Ming-Yu,S.and T.Din-Chang,A wavelet-based multiresolution edge detection and tracking[J].Image and Vision Computing,2005.23:p.441-451.
    12.Rivest,J.,Morphological operators on complex signals[J].Processing,2004.84(1):p.133-139.
    13.Jacquin,A.E.,Image coding based on a fractal theory of iterated contractiveimage transformations[J].IEEE Transactions on Image Processing,2002.1(1):p.18-30.
    14.Carr,J.C.,Reconstruction and representation of 3d objects with radial basis functions[C].SIGGRAPH'02 Conference Proceedings,2002:p.736-744.
    15.Kojekine,N.,V.R.Savchenko,and I.Hagiwara,Surface reconstruction based on compactly supported radial basis functions.Kluwer Academic Publishers,Norwell,MA,USA,,2004.
    16.Ohtake,Y.,et al.,Multi-level partition of unity implicit.2003.
    17.Juttler,B.and A.Felis,Least-squares fitting of algebraic spline surfaces[J].Advances in Computational Mathematics,2002.17:p.135-152.
    18.Fleishman,S.,et al.,Progressive point set surfaces[J].ACM Transactions on Computer Graphics,2003.22.
    19.Gill,B.and S.Micha,Piecewise-linear interpolation between polygonal slices[C].In SCG'94:Proceedings of the tenth annual symposium on Computational geometry,1994:p.93-102.
    20.Jianyun,C.,M.Takaharu,and N.Eihachiro,Contour interpolation and surface reconstruction of smooth terrain models[C].In VIS'98:Proceedings of the conference on Visualization "98,1998:p.27-33.
    21.Jones,M.and Chen,A new approach to the construction of surfaces from contour data.Computer Graphics Forum,1994.13(3):p.75-84.
    22.Lorensen,W.E.and H.E.Chine,Marching cubes:A high resolution 3d surface construction algorithm[J].In M.C.Stone,editor,Computer Graphics(SIGGRAPH' 87 Proceedings),1987.21:p.163-170.
    23.Bajaj,C.,E.Coyle,and K.Lin,Arbitrary topology shape reconstruction from planar cross sections[J].Graphical Models and Image Processing,1996.58(6):p.524-543.
    24.Cong,G and B.Parvin,Surface recovery from planar sectional contours[C].ICPR00,2000:p.4106-4109.
    25.Boissonnat,J.D.,Shape Reconstrution from Planar Cross-sections[J].Comp Vis Graph and Image Processing,1988.44(1):p.1-29.
    26.Lin,W.C.,,4 New Surface Interpolation technique for Reconstruction 3D Objects from Serial Cross-sections[J].Comput Vision and Graph Image Proc,1989.48(1):p.124-143.
    27.Keppel,E.,Approximating complex surface by triangulation of contour lines[J].IBM Journal of Research and Development,1975.19:p.2-11.
    28.Fushs,H.,Z.M.Kedem,and S.P.Uselton,Optimal surface reconstruction from planar contours[J].Commun.ACM,1977.20(10):p.693-702.
    29.Ekoule,A.B.,F.C.Peyrin,and C.L.Odet,A triangulation algorithm from arbitrary shaped multiple planar contours[J].ACM Trans.Graph.,1991.10(2):p.182-199.
    30.David,M.,S.Shelley,and S.Kenneth,Surfaces from contours.ACM Trans.Graph.,1992.11(3):p.228-258.
    31.Reinhard,K.,S.Andreas,and S.Wolfgang,Reconstruction and simplification of surfaces from contours[J].Graphical models,2000.62(6):p.429-433.
    32.Boissannat,J.and B.Geiger,Three dimensional reconstruction of complex shape based on the Delaunay triangulation[C].Technical report,INRIA,1992.
    33.谢红,张树生,张定华,杨鹏基,一种基于ICT的工件模型三维重建方法.航空学报,1997.18(5):p.599-602.
    34.谢红,张定华,张树生,杨鹏基,基于/CT和RP&M的计算机辅助产品快速仿制系统研究.西北工业大学学学报,1997.15(4):p.634-638.35.林丽华,卢清萍,颜永年,王素,面向RP的CT图象反求技术.计算机辅助设计与制造,1998.9:p.48-50.
    36.吕维雪,段会龙,三维医学图像可视化及其应用[M].浙江:浙江大学出版社,2001.
    37.王运赣,快速成形技术[M].武汉:华中理工出版社,1999.
    38.Richard,A.R.,Three-Dimensional biomedical imaging principles and practice[M].Boston:John Wiley&Sons Publishers,1998.
    39.Wang,Y.M.and W.X.Lu,Multicriterion decision entropy image reconstruction from projections[J].IEEE Trans.Medical Imaging,1992.11(1):p.70-75.
    40.Nakajima,S.,Three-Dimension Magnetic Resonance lmaging reconstruction for surgical planning and guidance.New York:Thieme Medical Publishers,1999.
    41.黄昶,翁默颖,一种用于提取医学图象边缘的新方法[J].华东师范大学学报(自然科学版),1994.1.
    42.季虎,孙即祥,邵晓芳,毛铃,图象边缘提取方法及展望.计算机工程与应用,2004.14.
    43.何斌等,Visual C++数字图像处理[M].北京-人民邮电出版社,2002.
    44.Ching-Chung,Y.,Image enhancement by modified contrast-stretching manipulation[J].Optics and Laser Technology,2006.38:p.196-201.
    45.Khireddine,A.,K.Benmahammed,and W.Puech,Digital image restoration by Wiener filter in 2D case[J].Advances in Engineering Software,2007.
    46.Kazuhiro,K.,et al.,Spike noise removal in the scanning laser microscopic image of diamond abrasive grain using a wavelet transform[J].Optics Communications,2002.211:p.73-83.
    47.Hong,P.and X.Liangzheng,Exact andf ast algorithm for two-dimensional imagewavelet moments via the projection transform[J].Pattern Recognition,2005.38:p.395-402.
    48.Stanley,O.and I.R.Leonid,Feature-oriented image enhancement using shock filters.SIAM J.NUMER.ANAL,1990.27(4):p.919-940.
    49.Malladi,R.and J.A.Sethian,A unified approach to noise removal,image enhancement,and shaperecovery.IEEE Transactions on Image Processing,1996.5(11):p.1554-1588.
    50.Young,S.C.and R.Krishnapuram,A robust approach to image enhancement based on fuzzy logic[J].IEEE Transactions on Image Processing,1997.6(6):p.808-825.
    51.LEE,J.-D.,Wavelet Transform for 3-D Reconstructions from Series Sectional Medical Images[J].Mathematical and Computer Modelling,1999.30:p.1-13.
    52.Stefano,A.D.,R.Allen,and P.R.White,Noise reduction in spine videofluoroscopic images using the undecimated wavelet transform[J].Computerized Medical Imaging and Graphics,2004.28:p.453-459.
    53.韩裕生,卢伟,刘菡,李从利.基于Db小波与中值滤波的安检图像噪声消除算法[J].CT 理论与应用研究,2005.14(1).
    54.Pillay,P.and A.Bhattacharjee,Application of wavelets to model short-time power system disturbances[J].IEEE Trans.on Power Delivery,1996.11(4):p.2031-2037.
    55.Angrisan,L.,P.Daponte,and M.Apuzzo,A measurement method based on the wavelet transform for power quality analysis[J].IEEE Trans.on Power Delivery,1998.13(4):p.990-998.
    56.Bezdek,J.C.and R.J.Hathaway,Optimization of fuzzy clustering criteria using genetic algorithmiC].FUZZ-IEEE'1994,1994:p.589-594.
    57.Bezdek,J.C.,Pattern recognition with fuzzy objective function algorithm[M].Plenum Press,New York 1981.
    58.Grnaf,C.N.,Validation of the interleved pyramid for the segmentation of 3D vector image[J].Pattern Recognition Letters,1994.15:p.467-475.
    59.林晓梅,李琳娜,牛刚,杨晓红,基于小波边缘检测的图像去噪方法[J].光学精密工程,2004.12(1):p.88-93.
    60.Keim,H.,D.Tucker,and S.G.Mallat,On denosing and best signal representation[J].IEEE Trans.Information Theory,1999.5(7):p.2225-2238.
    61.David,L.D.,De-nosising by sofi-thresholding[J].IEEE Trans.on Information Theory,1995.5.41(3):p.613-627.
    62.Souto,M.,J.Correal,and P.G.Tahoces,Enhancement of chest images by automatic adaptive spatial filtering[J].Journal of Digital Imaging,1992.5(4):p.223-229.
    63.Maack,I.and U.Neitzel,Optimized image processing for routine digital radiography[M].Berlin:Springer Verlag,1991:p.109-114.
    64.Ko,S.J.,Y.H.Lee,and M.K.Prasad,Detailed-preserving weighted median filters[C].Proceedings of 1988 Conference:Information Science and System,1988.3:p.769-774.
    65.Loupas,T.,W.N.McDicken,and P.L.Allan,An adaptive weighted median filter for speckle suppression in medical ultrasonic images[J].IEEE Trans.Circuits Sysem,1989.1(36):p.345-356.
    66.Ko,S.J.and Y.H.Lee,Center weighted median filters and their applications to image enhancement[J].IEEE Trans.Circuits Sysem,1991.15(9):p.984-993.
    67.Eng,H.L.and K.K.Ma,Noise adaptive so.R-switching median filter[J].IEEE Trans.Image Processing,2001.10(2):p.1534-1547.
    68.Zioa,D.and S.Tabbone,A multi-scale edge detector[J].Pattern Recognition,1993.26(9):p.1305-1314.
    69.Brown,M.A.,K.T.Blackwell,and H.G.Khalak,Multi-scale edge detection and feature binding:an integrated approach[J].Pattern Recognition,1998.31(10):p.1479-1490.
    70.Hall,L.O.,et al.,A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain[J].IEEE Trans.Neural Networks,1992.3(5):p.672-681.
    71.Lin,J.-S.,K.-S.Cheng,and C.-W.Mao,A fuzzy hopfield neural network for medical image segmentation[J].IEEE Trans.Neural Networks,1996.43(4):p.2389-2398.
    72.Lim,Y.W.and S.U.Lee,On the color image segmentation algorithm based on the thresholding and the fuzzy c-means techniques[J].Pattern Recognition,1990.23(9):p.935-952.
    73.Ron,S.,Integrated methodology for segmentation of large optical satellite images in land applications of remote sensing.Luxembourg,Italy,1995.
    74.Zugaj,D.and V.Lattuati,A new approach of color images segmentation based on fusing region and edge segmentation outputs[J].Pattern Recognition,1998.31(2):p.105-113.
    75.Pavlidis,T.and Y.T.Liow,Integrating region growing and edge detection[J].IEEE Trans.Pattern Analysis and Machine Intelligence,1990.12(3):p.225-233.
    76.Roberts,L.G.,Machine perception of three-dimensional solids.Optical and Electrooptical Information Processing,MIT Press,1965:p.159-197.
    77.Prewit,J.M.S.,Picture processing and psychopictorics[M].Academic Press,New York,1970.
    78.Marr,D.and E.H ildreth,Theory of edge detection[M].Proc.R.Soc.,London,1980:p.187-217.
    79.Canny,J.F.,A computational approach to edge detection[J].IEEE Trans.on PAMI,1995.8(6):p.679-698.
    80.Bomana,M.,et al.,3-D segmentation of MR images of the head for 3-D display[J].IEEE Trans.On Medical Imaging,1990.9:p.177-183.
    81.Bergholro,F.,Edge focusing[J].IEEE Trans,Pattern Analysis and Machine Intelligence,1987.9(9):p.726-741.
    82.Michael,H.and F.Wilkinaon,Optimizing Edge Detectors for Robust Automatic Threshold Selection:Coping with Edge Curvature and Noise[J].Graphical Models and Image Processing,1998.60:p.385-401.
    83.Bhabatosh,C.,K.K.Malay,and Y.V.Padmaja,A Multi-Scale Morphologic Edge Detector[J].Pattern Recognition,1998.3I(10):p.1469-1478.
    84.Bnnk,A.B.,Gray level thresholding of images using a correlation criterioa[J].Pattern Recognition Letters,1989.9:p.335-341.
    85.Tremeau,A.and N.Borel,A region growing and merging algorithm to color segmentation[J].Pattern Recognition,1997.30:p.1191-1203.
    86.Sandor,T.,D.Metcalf,and Y.J.Krno,Segmentation of brain CT images using the concept of region growing[J].J.Biomed.Comput.,1991.29:p.133-147.
    87.Adams,R.and L.Bischof,Seeded region growing[J].IEEE Trans.Pattern Analysis and Machine Intelligence,1994.16:p.641-647.
    88.陈燕新,戚飞虎,基于竞争Hopfield网络的自动聚类图像分割方法[J].模式识别与人工智能,1998.11(2):p.215-221.
    89.Wang,J.P.,Stochastic relaxation on partitions with connnected components and its application on image segmentation[J].IEEE Trans.Pattern Analysis and Machine Intelligence,1998.20(8):p.619-636.
    90.戴剑彬,张大力,图像分析中的松弛标记法[J].中国图像图形学报,1998.3A(2):p.96-99.
    91.Brummer,M.E.,et al.,Automatic detection of brain contours in MRI data sets[C].Proceedings of 12th IPMI'91,1991:p.190-204.
    92.秦绪佳,欧宗瑛,纪风欣,黎华,袁野,医学图象的交互分割及三维表面重建[J].工程图学学报,2001.22(2):p.94-101.
    93.王爱民,沈兰荪,图像分割研究综述[J].测控技术,2000.19(5):p.1-6.
    94.Kass,M.,A.Witkin,and D.S.Terzopoulos,Active contour models[J].International Journal of Computer Vision,1988.1(4):p.321-331.
    95.Amini,A.A.,T.E.Weymouth,and R.C.Jain,Using dynamic programming for solving variational problems in vision[J].IEEE Trans.Pattern Analysis and Machine Intelligence,1990.12(9):p.855-867.
    96.Donna,W.and S.Mubarak,A fast algorithm for active contours and curvature estimation[J].CVGIP:Image Understanding,1992.55(1):p.14-26.
    97.杨枝灵,王开,Hsual C++数字图像获取、处理及实践应用[M].北京-人民邮电出版社,2003.
    98.Pavlidis,T.,Algorithms for Graphics and Image Processing[M].Computer Science Press,Rockville,Maryland,1982:p.143-146.
    99.Yu,X.J.and L.Z.Peng,An algorithm for getting the curve border from a black-white image[J].Journal of Image and Graphics,2002.7A(3).
    100.Kamoun,B.,D.Afungchui,and A.A.Chauvin,A wind turbine blade profile analysis code based on the singularities method[J].Renewable Energy,2005.30(3):p.339-352.
    101.Zenzo,S.D.,L.Cinque,and S.Levialdi,Run-based algorithms for binary image analysis and processing[C].IEEE Transactions on Pattern Analysis and Machine Intelligence,1996.18(1).
    102.Ren,M.W.,J.Y.Yang,and H.sun,Tracing boundary contours in a binary image[J].Image and Vision Computing,2002.20:p.125-131.
    103.Chang,F.and C.J.Chen,A component-labeling algorithm using contour tracing technique[C].Proceedings of the Seventh International Conference on Document Analysis and Recognition(ICDAR'03),2003.
    104.Zingaretti,P.,M.Casparroni,and L.Vecci,Fast chain coding of region boundaries(2003)[C].IEEE Transactions on Pattern Analysis and Machine Intelligence,1998.20(4):p.407-415.
    105.Park,S.C.and B.K.Choi,Boundary extraction algorithm for cutting area detection[J].Computer-Aided Design,2001.33:p.571-579.
    106.汪小鹏,郑津津,双光子加工中加工路径的逐点生成[D].[硕士].合肥:中国科学技术 大学,2007.6.
    107.George,K.K.and A.-N.Rasha,Adaptive reconstruction of bone geometry from serial cross-sections[J].Artificial Intelligence in Engineering,2001.15:p.227-239.
    108.Yang,X.,C.S.C.Albert,and Y.Jian,An active contour model for image segmentation based on elastic interaction[J].Journal of Computational Physics,2006.219:p.455-476.
    109.Christian,K.,et al.,Outlining of the prostate using snakes with shape restrictions based on the wavelet transform(Doctoral Thesis:Dissertation)[J].Pattern Recognition,1999.32:p.1767-1781.
    110.施法中,计算机辅助几何设计与菲均匀有理B样条.高等教育出版社,2001.8:p.211-306.
    111.孙培培,基于切片数据的三维B样条曲面重构[D].[硕士].合肥:中国科学技术大学,2008.6.
    112.邓建松,样条函数—基于Blossoming.中国科学技术大学数学系讲义.
    113.Schoenberg,I.J.,Contribution to data smoothing.Quarterly Appl.Math.,1946.4:p.45-99,112-141.
    114.de Boor,C.,On Calculation with B-splines.J.appox,theory,1972.6.
    115.Cox,M.,The numerical evaluation of B-splines.J.inst.maths,applications,1972.10.
    116.王瑜,郑津津,周洪军,沈连嬉,断层轮廓的双三次非均匀B样条曲面重构.中国科学技术大学学报,2008.
    117.倪明田,吴良芝,计算机图形学[M].北京-北京大学出版社,1999.
    118.Boehm,W.,Inserting new knots into B-spline curves[J].Computer-Aided Design,1980.12(4):p.199-201.
    119.Herman,G.T.and H.K.Liu,Three-dimensional display of human organs from computed tomograms[J].Computer Graphics Image Processing,1979.9(4):p.1-21.
    120.Cline,H.and W.Lerensen,Tow algorithms for the 3D reconstruction of tomograms[J].Medical Physics,1988.15(3):p.320-327.
    121.Meyers,D.and S.Skinner,Surfaces from contours[J].ACM Trans.s on Graphics,1992.11(3):p.228-258.
    122.Bezier,P.,Mathematical and practical possibility of UNISURE In:Computer aided geometric desigh,Edited by Bamhill R and Riesenfield R,Academic press.,1974:p.127-152.
    123.Barnhill,R.E.,G.Birkhoff,and W.J.Gordon,Smooth interpolation in triangles[J].J.Approx.Theory.,1974.8:p.114-128.
    124.Rogers,D.and N.Fog,Constrained B-Spline curve and surface fitting[J].Computer-Aided Design,1989.21:p.641-648.
    125.Farin,G.,Smooth interpolation to scattered 3D data.In:Surface in CAGD,Edited by Barnhill R and Boehm W,North-Holland Publishing Company,1983.
    126.Choi,.B.K.,H.Y.Shin,and Y.L.Yoon,Trianglation of scattered data in 3D space[J].Computer-Aided Design,1988.20(5):p.239-248.
    127.Farin,G.,A modified Clough-Tocher interpolant[J].Computer Aided Geometric Design,1985.2:p.19-27.
    128.Hoppe,H.,Surface reconstruction from unorganized points.Dorctoral Dissertation,1998(http://research.microsoft,com/-hoppe/).
    129.Bajaj,C.,F.Bernardini,and G.Xu,Automatic reconstruction of surfaces and scalar fields from 3D scans[C].SIGGRAPH'95 Prec.New York:ACM,,1995.
    130.Amenta,N.,M.Ben,and M.Kamvysselis,A new voronoi-based surface reconstruction algorithm[C].SIGGRAPH'95 Prec.New York:ACM,1995.
    131.Weishi,L.,X.Shuhong,and Z.Gang,Adaptive knot placement in B-spline curve approximation[J].Computer Aided Design,2005.37:p.791-797.
    132.Park,H.,K.Kim,and S.C.Lee,A method for approximate NURBS curve compatibility based on multiple curve refitting[J].Computer Aided Design,2000.32:p.237-252.
    133.黄健民,施法中,基于广义逆节点消去的B样条曲线的可控逼近 计算机工程与应用,2006.42(13):p.80-83.
    134.来新民,黄田,曾子平等,基于NURBS的散乱数据点自由曲面重构.计算机辅助设计与图形学学报,1999.11(5):p.433-436.
    135.Ma Weiyin,K.J.P.,Parametrisation of randomly measured points for the least squares fitting of B spline curves and surfaces.Computer Aided Design,1995.27(9):p.663-675.
    136.Sarkar B,M.C.,Parameter optimization in approximation curves and surfaces to measurement data.Computer Aided Geometric Design,1991.8(4):p.267-290.
    137.Piegl L,T.W.,Parameterizationfor surface fitting in reverse engineering.Computer Aided Design,2001.33(8):p.593-603.
    138.V Weiss,L.A.,G Rennet,T Varady Advanced surface fitting techniques.Computer Aided Geometric Design,2002.1.19(1):p.19-42.
    139.MJ Milroy,C.B.,GW Vickers,DJ Weir G~1 continuity of B-spline surface patches in reverse engineering Computer-Aided Design,1995.27(6):p.471-478.
    140.肖轶军等,基于迭代最近点的B样条曲线拟合方法研究.中国图象图形学报,2000(7):p.585-588.
    141.D,W.C.,Skinning techniques for interactive B spline surface interpolation.Computer Aided Design,1988.20(8):p.441-451.
    142.Rogers D F,F.N.G.,Constrained B spline curve and surface fitting.Computer Aided Design,1989.21(10):p.641-648.
    143.Park H,K.K.,Smooth surface approximation to serial cross sections.Computer Aided Design,1996.28(12):p.995-1005.
    144.何芳,束长林,秦伟一,截面数据的B样条曲面重建研究.现代制造工程,2003(10):p.73-76.
    145.闫贺庆,叶铭,王成焘,股骨解剖结构B样条曲面重构.计算机辅助设计与图形学学报,2004.7.16(7):p.1020-1024.
    146.Piegl L,T.W.,The NURBS book.Berlin Heidelberg:Springer-Verlag,1997:p.47-140.
    147.朱心雄等,自由曲线曲面造型技术.北京:科学出版社,2000.
    148.张文景,许晓鸣,丁国骏,杨煜普,一种基于曲率提取轮廓特征的方法.上海交通大学学报,1999.5.32(5):p.592-595.
    149.Yu Wang,J.Z.,Hongjun Zhou,Lianguan Shen,Medical Image Processing by Denoising and Contour Extraction.IEEE International Conference on Information and Automation.ZhangJiaJie,2008.
    150.赵秀阳,尹衍升,杨波,基于优势点检测的晶粒轮廓非均匀B样条逼近.中国科学,2007.37(7):p.851-856.
    151.Weiss,V.,et al.,Advanced Surface Fitting Technique[J].Computer Aided Geometry Design,2002.19:p.19-42.
    152.Ma,W.Y.and J.P.Kruth,Parameterization of randomly measured points for least squares firing of B-spline curves and surfaces[J].Computer-Aided Design,1995.27(9):p.663-675.
    153.Lin,F.Q.and W.T.Hewit,Expressing Coons-Gordon Surface As NURBS[J].Computer-Aided Design,1994.26(2):p.145-155.
    154.Piegl,L.A.and W.Tiller,Parametrization for surface fitting in reverse engineering[J].Computer Aided Design,2001.33:p.593-903.
    155.Sarkar,B.and C.H.Menq,Parameter optimization in approximating curves and surfaces to measurement data[J].Computer Aided Geometric Design,1991.8:p.267-290.
    156.Piegl,L.A.and W.Tiller,Surface approximation to scanned data[J].The Visual Computer,2000.16:p.386-395.
    157.彭芳瑜,曲面数控加工中的拟合、光顺及干涉问题研究.华中理工大学博士学位论文,2000.5:p.13-33.
    158.Ma,Y.L.and W.T.Hewitt,Point inversion and projection for NURBS curve and surface:control polygon approach[J].Computer Aided Geometric Design,2003.20:p.79-99.
    159.王国夫,孙尧,张海勋,杨传安,基于节点插入原理的大规模散乱数据插值.哈尔滨工程大学学报,2001.2.22(1):p.45-48.
    160.秦开怀,关右江等,B样条曲线的节点插入问题两个新算法[J].计算机学报,1997.6.20(6):p.556-561.
    161.Kruth J P,K.A.,Reverse engineering modeling of free form surfaces from point clouds subject to boundary conditions.Journal of Materials Processing Technology,1998.76(4):p.120-127.
    162.王刘记,张李超,曾少勇,基于B-Rep.实体模型的IGES转换为STL[J].计算机辅助设计与图形学学报,2007.19(1):p.37-41.
    163.Piegl,L.A.and M.R.Arnaud,Tessellating timmed NURBS surfaces[J].Computer Aided Design,1995.27(1):p.16-26.
    164.王静,张树生,孙宏伟和刘晓翔,产品层析图像的轮廓序列匹配技术研究.计算机研究与发展,2002.39(9):p.1127-1131.
    165.Zyda,M.J.M.and R.J.Allan,Surface construction from planar contours[J].Computer Graphics,1987.V21(4):p.393-408.
    166.Marsan,A.L.and D.Dutta,Computational techniques for qutomatically tilling and skinning branched objects[J].Computers and Graphics,1999.23:p.111-126.
    167.Soroka,B.I.,Generalized Cones form serial sections[J].Computer Graphics Image Processing,1981.V15:p.154-166.
    168.Bresler,Y.,J.A.Fessler,and A.Macovski,,4 Bayesian approach to reconstruction from incomplete projections of a multiple objects 3D domain[J].IEEE Transaction on Patern Analysis and Machine intelligent,1989.V11(8):p.840-858.
    169.Christiansen,H.N.and T.W.Soderberg,Conversion of complex contour line definitions into polygonal element mosaics[J].Computer Graphics,1978.V12(3):p.187-192.
    170.Shantz,M.,Surface definition for branching contour from planar contours[J].Computer graphics,1981.V15(2):p.242-270.
    171.管伟光,体视华技术及其应用.用电子工业出版社,1998.
    172.Xu,M.H.and Z.S.Tang.General surface reconstruction from a set of planar contours[J].清华人学学报,1997.V37(4):p.59-64.
    173.石教英,蔡文立,科学计算可视华算法与系统[M].科学出版社,1996.
    174.YORAM BRESLER,J.A.F.A.A.M.,A Bayesian Approach to Reconstruction from Incomplete Projections of a Multiple Object 3D Domain.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,1989.11(8):p.840-858.
    175.Aggarwal,Y.F.W.a.J.K.,Surface reconstruction and representation of 3-D scenes.Pattern Recognition,1986.19(3):p.197-207.
    176.廖胜辉,许.,董金祥,颌骨重建中的图像分割和轮廓对应及分支问题.计算机辅助设计与图形学学报,2004.16(9):p.1225-1230.
    177.A.B.EKOULE,F.C.P.a.C.L.O.,A triangulation algorithm from arbitrary shaped multiple planar contours.ACM Transactions on Graphics,1991.10(2):p.182-199.
    178.BAJAJ,C.L.,Arbitrary Topology Shape Reconstruction from Planar Cross Sections.GRAPHICAL MODELS AND IMAGE PROCESSING,1996.58(6):p.524-543.
    179.N.C.Gabrielides,A.I.G.a.P.D.K.,Constructing smooth branching surfaces from cross sections.Proceedings of the 2006 ACM symposium on Solid and physical modeling,2006:p.161-170.
    180.G Barequet,D.S.a.A.T.,Multilevel sensitive reconstruction of polyhedral surfaces from parallel slices.The Visual Computer,2000.16(2):p.116-133.
    151.S Yuwen,W.Y.,L Weijun,FREE-FORM SURFACE RECONSTRUCTION BASED ON NURBS TO SERIAL CROSS-SECTIONS.Chinese Journal of Mechanical Engineering,2003.16(4):p.420-423.
    182.J-M.Oliva,M.P.a.S.C.,3D Reconstruction of Complex Polyhedral Shapes from Contours using a Simplified Generalized Voronoi Diagram.EUROGRAPHICS'96,1996.15(3):p.397-408.
    183.J.Jeong,K.K.,H.Park and M.Jung,A New Method for Solving Branching Problems in Surface Reconstruction.Advanced Manufacturing Technology,2000.16(4):p.259-264.
    184.Gabrielides,N.C.,A.I.Ginnis,and P.D.Kaklis,Constructing Smooth Branching Surfaces from Cross Sections[C].SPA 2006,Cardiff,Wales,United Kingdom,06-08,2006.
NGLC 2004-2010.National Geological Library of China All Rights Reserved.
Add:29 Xueyuan Rd,Haidian District,Beijing,PRC. Mail Add: 8324 mailbox 100083
For exchange or info please contact us via email.