摘要
医学图像处理及应用,是计算机组合诊疗系统中的关键技术,也是一个多学科交叉融合的研究领域,涉及数字图像处理、计算机图形学以及医学领域的相关知识。在目前临床应用中,大多数医生还是借助CT、MRI拍摄的二维断层图像,根据临床经验进行局部分析和诊断,这对于病变区域的精确定位和定量分析是远远不够的。因此,在普通计算机上实现医学图像处理,将使临床医生可以对可视化三维图像任意剖分。这对于诊断医学、手术规划、放射治疗规划、模拟仿真及解剖教学等方面,都具有重要的学术意义和应用价值。
本研究课题是南京航空航天大学“十五”重点学科建设项目“计算机集成诊断与治疗系统”中的子课题。论文将详细阐述作者攻读博士学位期间在医学图像处理方面从事的研究工作,主要涉及图像分割、图像三维重建及可视化、图像测量这三个关键技术的研究,包括各种基础算法的理论研究和应用系统的设计研发。论文主要研究工作及创新成果归纳如下:
1)针对图像分割算法的具体应用,在分析综合融合变形模型、小波变换、数学形态学等先进理论的基础上,将新型图像分割算法——梯度向量流场的变形模型和改进的分水岭算法应用于颅脑内胼胝体和脑部星形细胞瘤的分割提取,取得了良好效果。针对彩色视网膜血管图像,提出一种基于网格划分的全自动分割提取算法,保证眼底测量结果的准确性、客观性和实用性。
2)针对数字化医疗系统的需要,利用普通配置计算机群和医院内部局域网进行超大规模医学数据并行重建的研究,是符合我国大多数医院实情的有效手段,也是医院PACS系统建设的必然要求。该方法较好地解决了运算速度、内存空间以及资金投入这三大难题,既节省大量资金,又能够满足临床诊断需求。
3)将分形和分形维数的基本方法引入医学图像定量测量中来,首次将分形维数用于定量考察和分析不同浓度神经生长素对体外培养新生大鼠背根神经突起生长的影响。与采用显微镜进行定性观察相比,该方法不仅可以测量复杂结构的变化,而且可以描述它的生长和演变过程。分形维数的测量方法能够从量化角度更准确深刻地说明神经生长素能够促进大鼠背根神经节神经突起的生长,而且生长状况表现出与剂量的依赖关系。
4)针对生物医学微细结构研究的需要,进行激光扫描共聚焦显微镜图像计算机处理的相关研究。首先对显微镜图像进行激光吸收和散射的补偿以及基于最大后验的图像盲解卷积,改善图像模糊,提高图像质量。然后利用光线跟踪算法重建三维物体,实现三维图像的平移、旋转、缩放、光线设置等操作,从而清晰全面地显示三维微细结构。此外,还可以通过电影放映方式显示三维结构随时间变化的过程,实现四维成像,为生物医学显微图像的分析提供技术支持。
5)将生物医学可视化技术推进到微观切片水平,实现生物组织连续切片图像的两步配准和快速重建。考虑到生物体在序列切片图像上的重心位置具有连续性的事实,提出一种新的逐步求精的自动配准方法。在使用力矩主轴法对两幅图像进行粗略配准的基础上,对已有配准结果作微小干扰,当图像互信息最大时获得最终精确配准结果。采用基于有序体数据结构的Shear-Warp算法重建生物体内部结构,提高对体数据的遍历效率,减少对无效数据的访问,加速绘制过程。
6)在充分吸收国外知名图像处理软件各项优点的基础上,利用IDL这一开发平台,进行医学图像处理分析系统MIPAS和CTA/MRA图像后处理软件VICAAT的研发,形成具有自主知识产权的软件系统。通过对实际医学图像的处理,证明该系统的理论意义和应用价值,取得大量实验结果,为医学图像处理和分析创造良好条件,并将逐步推广应用于临床诊断。
归纳而言,本论文针对计算机组合诊疗系统中的关键技术,在理论上提出了一些新算法,在应用中创建了一些实用的新方法,并获得了很好的验证。同时,还研发了相应的基础应用软件,为生物医学图像处理提供了重要工具。
Medical image processing is a multi-disciplinary subject, which relates to the subjects of digital image processing, computer graphics and some related knowledge of medicine. However, until now most of the clinical physicians can only utilize their experience to analyze the two-dimensional image series obtained by CT and MRI, which might be very limited to determine the perfect spatial location and exact area of the disease. Therefore, there is a crying need to build suitable software system based on common-configuration personal computer, which can be applied to visualize the corresponding three-dimensional images by image reconstruction techniques. Furthermore, through the necessary splitting and some other useful analyses or simulations before the actual operation, the clinical physicians could be more confident about the disease. In brief, study on processing and analysis of medical images is widely used in diagnostic, surgery and radiotherapy planning, and teaching in anatomy, which is of great important significance on science and worthiness in practical applications.
The research project is one part of“The Diagnostic and Therapeutic System of Computer Integration”, supported by“The Tenth Five Years Constructive Finance”in College of Automation Engineering, NUAA. This dissertation describes the author's work on medical image processing and analysis, including algorithm research and software development. The research focuses on three important research fields: image segmentation, reconstruction and measurement. The main research fields and innovative results in this dissertation focus on the following aspects:
1) Two novel segmentation algorithms: gradient vector flow deformable model and improved watershed algorithm, are implemented and applied to segment corpus callosum and astrocytoma, both achieved favorable results. Another automatic segmentation algorithm for color retinal vascular images, whose performance exceeds traditional methods, is proposed to guarantee accuracy, objectivity and practicability.
2) On the basis of grid computing, the essence and key techniques of parallel visualization of large medical datasets are discussed based on Intranet and common-configuration computers of hospitals. It is suitable and effective for our countries’most hospitals and is also the outcome of PACS construction. It is demonstrated that this method provide promising and real-time results, which resolve the computational speed, memory requirements and undercapitalization puzzles.
3) The neurite growth of cultured dorsal root ganglion is detected by fluorescent immunocytochemistry treated with nerve regeneration factor in different concentration. A novel method based on triangular prism surface area is introduced to calculate the fractal dimension of the two-dimensional immunofluorescent images. Experimental results demonstrate that this method is easy to understand and convenient to operate, with quantitative results according to observations of microscope.
4) The methodology is proposed for image processing and interactive visualization of laser scanning confocal microscopy datasets, including automatic pre-processing and ray-casting reconstruction. The program allows for convenient, fast, interactive examination of unknown cell structures even on common PC, which significantly improve the task of understanding the internal structure of laser scanning confocal microscopy image stacks. Meanwhile, it can be used to visualize dynamically changing temporary structures conveniently in addition to static images.
5) A novel method, two-step slices registration and fast Shear-Warp reconstruction, is proposed for serial tissue section images. Based on the elementary result of the principal axes transformation method, the optimal registration result is achieved when the mutual information reaches maximum. An improved Shear-Warp algorithm based on sorted volumetric data structure is applied to reduce the access time of non-contribution data cells and consequently speed up the reconstruction process.
6) Several famous foreign image processing software are analyzed and evaluated respectively, and advantages are derived and absorbed from them. Two software systems: medical image processing and analysis system (MIPAS) and vascular image computer assisted analysis tool (VICAAT) are developed based on IDL language, with some examples demonstrated. Modular programming is used to design these systems, which are easier to be modeled, organized, maintained and extended by using encapsulation, inheritance and polymorphism features of objects.
The new algorithms and methods built in this dissertation are of important value to theoretical research and clinical application, along with the corresponding software, which provide important tools for medical image processing and analysis.
引文
[1] Philippe Lacroute, Marc Levoy, Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation, SIGGRAPH, Proceedings of ACM SIGGRAPH, Florida, ACM Press, 1994: 451~458.
[2] Philippe Lacroute, Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation, [Ph.D. Dissertation], USA, Stanford University, 1995.
[3] VolPack, http://graphics.stanford.edu/software/volpack
[4] Helwig Hauser, Lukas Mroz, Gian-Italo Bischi, M Ecluard Groller, Two-Level Volume Rendering-Fusing MIP and DVR, IEEE-CS\TCVCG, Proceedings of the Conference on Visualization’00, USA, IEEE Computer Society Press, 2000: 211~218.
[5] RTVR, http://www.vrvis.at/vis/research/rtvr
[6] H Pfister, J Hardenbergh, J Knittel, H Laner, L Seiler, The VolumePro Real-Time Ray-Casting System, ACM SIGGRAPH, Proceedings of the ACM SIGGRAPH’99, USA, ACM Press, 1999: 251~260.
[7] VHP, http://www.nlm.nih.gov/research/visible/visible-human.html
[8] http://www.med.harvard.edu/ANNLIB/home.html
[9] http://sig.biostr.washington.edu/projects/da
[10] http://www.voxel-man.de
[11] http://www.toltech.net/index.htm
[12] http://www.cbeis.zju.edu.cn/key_lab
[13] http://www.cad.zju.edu.cn
[14] http://www.imagetech.com.cn
[15] http://www.3dmed.net
[16] http://unit.xjtu.edu.cn/bme
[17] http://life.sjtu.edu.cn/biomed
[18] http://www.ios.ac.cn
[19] http://vis.cs.tsinghua.edu.cn
[20]陈凌钧,医学图象三维重建的研究,[博士学位论文],浙江,浙江大学,1996
[21]田捷、包尚联、周明全,医学影像处理与分析,北京,电子工业出版社,2003:9~33、35~95、117~122、315~327
[22] Stytz M R, Frieder O, Three-Dimensional Medical Imaging Modalities: an Overview, Critical Reviews of Biomedical Engineering, 1990, 18(1): 1~25.
[23]高上凯,医学成像系统,北京,清华大学出版社,2000:10~143
[24]吕维雪、段会龙,三维医学图像可视化及其应用,浙江,浙江大学出版社,2001:8~68、119~142、147~150、191~200
[25] DICOM, http://medical.nema.org/dicom/2004.html
[26] DICOM Introduction, http://www.sph.sc.edu/comd/rorden/dicom.html
[27]王延华,通用医学图像处理系统的设计和实现,[硕士学位论文],北京,中国科学院软件研究所,2002
[28]章毓晋,图像分割,北京,科学出版社,2001:1~77
[29]罗述谦、周果宏,医学图象处理与分析,北京,科学出版社,2003:65~92
[30]李淑宇,医学图像信息处理与自动分析的研究,[博士学位论文],北京,中国科学院生物物理所,2003
[31]吴建明,断层医学图像重建的几个关键技术研究,[博士学位论文],上海,上海交通大学,2003
[32]林瑶、田捷,医学图像分割方法综述,模式识别与人工智能,2002,15(2):192~204
[33]罗希平、田捷、诸葛婴,等,图像分割方法综述,模式识别与人工智能,1999,12(3):300~312
[34]罗渝兰、王景熙、郑昌琼,图像分割在生物医学工程中的应用,计算机应用,2002,22(8):20~22
[35]赵荣椿、迟耀斌、朱重光,图像分割技术进展,中国体视学与图像分析,1998,3(2):121~128
[36] Nikhil R Pal, Sankar K Pal, A Review on Image Segmentation Techniques, Pattern Recognition, 1993, 26(9): 1277~1294.
[37] Dzung L Pham, Chenyang Xu, Jerry L Prince, Current Methods in Medical Image Segmentation, Annual Review of Biomedical Engineering, 2000, 2: 315~337.
[38] James S Duncan, Nicholas Ayache, Medical Image Analysis: Progress over Two Decades and the Challenges Ahead, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(1): 85~105.
[39] P K Sahoo, S Soltani, A K C Wong, et al, A Survey of Thresholding Techniques, Computer Vision, Graphics, and Image Processing, 1988, 41(2): 233~260.
[40] G B Coleman, H C Andrews, Image Segmentation by Clustering, Proceedings of IEEE, 1979, 67(5): 773~785.
[41] J C Bezdek, L O Hall, L P Clarke, Review of MR Image Segmentation Techniques Using Pattern Recognition, Medical Physics, 1993, 20(4): 1033~1048.
[42] Tim McInerney, Demetri Terzopoulos, Deformable Models in Medical Image Analysis: a Survey, Medical Image Analysis, 1996, 1(2): 91~108.
[43] Chenyang Xu, Dzung L Pham, Jerry L Prince, Image Segmentation Using Deformable Models, SPIE, Handbook of Medical Imaging: Volume 2. Medical Image Processing and Analysis, London, SPIE Press, 2000: 129~174.
[44]陈昱、庄天戈,医学图像分析的形变模型研究,生物医学工程学杂志,1999,16(4):497~501
[45]肖敏、严勇、夏顺仁,医学图像处理中可变模型技术的研究进展,航天医学与医学工程,2005,18(1):75~78
[46] Tony F Chan, Luminita A Vese, Active Contours without Edges, IEEE Transactions on Image Processing, 2001, 10(2): 266~277.
[47] Jinshan Tang, Scott T Acton, Vessel Boundary Tracking for Intravital Microscopy via Multiscale Gradient Vector Flow Snakes, IEEE Transactions on Biomedical Engineering, 2004, 51(2): 316~324.
[48]尤建洁、周则明、王平安,等,基于模拟退火的简化Snake弱边界医学图像分割,中国图象图形学报,2004,9(1):11~17
[49] Cheng Huang Chuang, Wen-Nung Lie, A Downstream Algorithm Based on Extended Gradient Vector Flow Field for Object Segmentation, IEEE Transactions on Image Processing, 2004, 13(10): 1379~1392.
[50] Mathens Jacob, Thierry Blu, Michael Unser, Efficient Energies and Algorithms for Parametric Snakes, IEEE Transactions on Image Processing, 2004, 13(9): 1231~1244.
[51] Kass M, Witkin A, Terzopoulos D, Snakes: Active Contour Models, International Journal of Computer Vision, 1988, 1(4): 321~331.
[52] Chenyang Xu, Jerry L Prince, Snakes, Shapes, and Gradient Vector Flow, IEEE Transactionson Image Processing, 1998, 7(3): 359~369.
[53] Chenyang Xu, Jerry L Prince, Gradient Vector Flow Deformable Models, Handbook of Medical Imaging, 2000, 9: 159~170.
[54]王纪佐,神经系统临床诊断学,北京,人民军医出版社,2002:149~150
[55]陈少琼,姚志彬,全显跃,胼胝体正常发育及老化的MRI研究,解剖学杂志,2001,24(5):455~458
[56] Luc Vincent, Pierre Soille, Watersheds in Digital Spaces: an Efficient Algorithm Based on Immersion Simulations, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991, 13(6): 583~597.
[57] Horst Karl Hahn, Morphological Volumetry: Theory, Concepts, and Application to Quantitative Medical Imaging, [Ph.D Dissertation], Germany, Bremen University, 2005.
[58]杜啸晓、杨新、施鹏飞,一种新的基于区域和边界的图像分割方法,中国图象图形学报,2001,6(8) :755~759
[59] Norberto Malpica, Carlos Ortiz de Solorzano, Juan Jose Vaquero, et al, Applying Watershed Algorithms to the Segmentation of Clustered Nuclei, Cytometry, 1997, 28(4): 289~297.
[60] Olivier Lezoray, Hubert Cardot, Cooperation of Color Pixel Classification Schemes and Color Watershed: a Study for Microscopic Images, IEEE Transactions on Image Processing, 2002, 11(7): 783~789.
[61] Paul R Hill, C Nishan Canagarajan, David R Bull, Image Segmentation Using a Texture Gradient Based Watershed Transform, IEEE Transactions on Image Processing, 2003, 12(2): 1618~1633.
[62] Shengcai Peng, Lixu Gu, A Novel Implementation of Watershed Transform Using Multi-Degree Simulation, IEEE, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, IEEE Press, 2005: 1754~1757.
[63] Joakim Lindblad, Technology in Computerized Image Analysis, [Ph.D Dissertation], Germany, Uppsala University, 2003.
[64]崔屹,图像处理与分析——数学形态学方法及应用,北京,科学出版社,2000:125~132
[65]飞思科技产品研发中心,MATLAB6.5辅助小波分析与应用,北京,电子工业出版社,2003:219~220
[66] Rafael C Gonzalez, Richard E Woods, Digital Image Processing, USA, Prentice Hall, 2003:379~386, 556~558
[67] IDL Online Manuals, Research Systems Inc, 2003.
[68]张惠蓉,眼微循环及其相关疾病,北京,北京医科大学中国协和医科大学联合出版社, 1993:164~173
[69]吴振中,现代临床眼科学,长沙,湖南科学技术出版社,1996:217~227
[70] http://www.cse.sc.edu/~songwang/CouseProj/proj2003/lockhard/Lockhart.pdf
[71] Can A, H Shen, J N Turner, et al, Rapid Automated Tracing and Feature Extraction from Live High-Resolution Retinal Fundus Images Using Direct Exploratory Algorithms, IEEE Transactions on Information Technology in Biomedicine, 1999, 3(2): 125~138.
[72] M Sonka, M D Winniford, X Zhang, et al, Robust Simultaneous Detection of Coronary Borders in Complex Images, IEEE Transaction on Medical Images, 1995, 14(1): 151~161.
[73]林土胜、秦华标、赖声礼,基于拆支跟踪法提取特征的视网膜血管形态识别,华南理工大学学报,2000,28(5):54~58
[74]朱宏擎,基于灰度—梯度共生矩阵的视网膜血管分割方法,上海交通大学学报,2004, 38(9):1485~1488
[75]张恒义、蒋黔麟、虞亚军,等,基于视网膜血管模型的图像分割与血管提取,电子学报,1999,27(6):65~67
[76]许雷、郑筱祥、俞锋,等,基于眼底视网膜血管网络模型的血管提取方法,浙江大学学报,1999,33(4):386~392
[77]许雷、张恒义、郑筱祥,等,荧光视网膜血管骨架图快速提取法,科技通报, 1999,15(2):141~144
[78] Otsu N, A Threshold Selection Method from Gray-Level Histogram, IEEE Transactions on System Man and Cybernetic, 1979, 9(1): 62~66.
[79]崔波、徐元鼎、张农,肝脏血管的医学图象三维重建,中国图象图形学报,1998,3(1):29~33
[80] McCormick B H, DeFanti T A, Brown M D, Visualization in Scientific Computing, Computer Graphics, 1987, 21(6): 249~266.
[81]秦绪佳,医学图象三维重建及可视化技术研究,[博士学位论文],大连,大连理工大学,2001
[82]彭延军,虚拟内窥镜关键技术研究,[博士学位论文],浙江,浙江大学,2003
[83]沈海戈、柯有安,医学体数据三维可视化方法的分类与评价,中国图象图形学报,2000,5(7):545~550
[84] William E Lorensen, Harvey E Cline, Marching Cubes: a High Resolution 3D Surface Construction Algorithm, Computer Graphics, 1987, 21(4): 163~169.
[85] Durst M J, Additional Reference to“Marching Cubes”, Computer Graphics, 1988, 22(2): 72~73.
[86] Adriano Lopes, Ken Brodlie, Improving the Robustness and Accuracy of the Marching Cubes Algorithm for Isosurfacing, IEEE Transactions on Visualization and Computer Graphics, 2003, 9(1): 16~29.
[87] Evgeni V Chernyaev, Marching Cubes 33: Construction of Topologically Correct Isosurfaces, Technical Report CN/95-17, CERN, 1995, http://wwwinfo.cern.ch/asdoc/psdir/mc.ps.gz.
[88]管伟光,体视化技术及其应用,北京,电子工业出版社,1998:55~67
[89] Nielson G, Hamann B, The Asymptotic Decider: Resolving the Ambiguity in Marching Cube, IEEE, Proceedings of Visualization '90, Los Alamitos, IEEE Computer Society Press, 1991: 83~91.
[90] Doi A, Koide A, An Efficient Method of Triangulating Equi-Valued Surfaces by Using Tetrahedral Cells, IEICE Transactions on Communications, Electronics, Information and Systems, 1991, E74(1): 214~224.
[91] Cline H, Lerensen W, Two Algorithms for the 3D Reconstruction of Tomograms, Medical Physics, 1988, 15(3): 225~233.
[92]时丕丽,医学图像三维重建及可视化技术研究,[硕士学位论文],北京,北京交通大学,2004
[93]张敬敏、蒋力培、邓双成,医学图像三维可视化技术研究,中国医学影像技术,2004,20(7):1129~1132
[94]诸葛斌,基于微机的医学图像三维重建,[博士学位论文],安徽,中国科学技术大学,2003
[95]张尤赛、陈福民,三维医学图像的体绘制技术综述,计算机工程与应用,2002,38(8):18~20
[96] P Sabella, A Rendering Algorithm for Visualization 3D Scalar Fields, Computer Graphics, 1988, 22(4): 51~58.
[97] M Levoy, Efficient Ray Tracing of Volume Data, ACM Transaction on Graphics, 1990, 9(3): 245~261.
[98] L Westover, Footprint Evaluation for Volume Rendering, SIGGRAPH, Proceedings of the 17th Annual Conference on Computer Graphics and Interactive Techniques, USA, ACM Press, 1990: 367~376.
[99] Malzbender T, Fourier Volume Rendering, ACM Transactions on Graphics, 1993, 12(3): 232~250.
[100] Totsuka T, Levoy M, Frequency Domain Volume Rendering, ACM SIGGRAPH, Computer Graphics Proceedings, Annual Conference Series, CA, ACM SIGGRAPH, 1993: 271~278.
[101] Lippert L, Gross M H, Fast Wavelet Based Volume Rendering by Accumulation of Transparent Texture Maps, Computer Graphics Forum, 1995, 14(3): 431~433.
[102] Gross M H, Lippert L, Dreger A, et al, A New Method to Approximate the Volume-Rendering Equation Using Wavelet Based and Piecewise Polynomials, Computer & Graphics, 1995, 19(1): 47~62.
[103] Gross M H, Lippert L, Haring S, Two Methods for Wavelet-based Volume Rendering, Computer & Graphics, 1997, 21(2): 237~252.
[104]彭延军、石教英,体绘制技术在医学可视化中的新发展,中国图象图形学报,2002,7(12):1239~1246
[105] Westermann R, Ertl T, A Multiscale Approach to Integrated Volume Segmentation and Rendering, Computer Graphics Forum, 1997, 16(3): C117~C127.
[106] Wilhelms J, Gelder A V, A Coherent Projection Approach for Direct Volume Rendering, Computer Graphics, 1991, 25(4): 275~284.
[107] Jayaram K Udupa, Three-Dimensional Visualization and Analysis Methodologies: a Current Perspective, RadioGraphics, 1999, 19(3): 783~806.
[108] Arie E Kaufman, Volume Visualization: Principles and Advances, In Course Notes of the 24th Conference on Computer Graphics and Interactive Techniques (SIGGRAPH 1997), 1997.
[109]都志强、陈渝、刘鹏,网格计算,北京,清华大学出版社,2002:3~15
[110] Jeremy Kepner, Maya Gokhale, Ron Minnich, et al, Interfacing Interpreted and Compiled Languages to Support Applications on a Massively Parallel Network of Workstation (MP-NOW), Cluster Computing, 2000, 3(1): 35~44.
[111] James Ahrens, Charles Law, Will Schroeder, et al, A Parallel Approach for Efficiently Visualizing Extremely Large, Time-Varying Datasets, LAUR-00-1620, Los Alamos National Laboratory Technical Report, 2000, http://citeseer.ist.psu.edu/ahrens00parallel.html.
[112] Liu Qian, Gong Hui, Luo Qingming, Parallel Visualization of Visible Chinese Human with Extremely Large Datasets, IEEE, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, IEEE Press, 2005: 1472~1475.
[113]苏德富、梁正友、华云,并行计算技术及其应用,重庆,重庆大学出版社,2001:4
[114]李晓梅、蔡勋、汤红波,并行与分布式科学可视化研究与实现,自然杂志,1996,18(4): 232~236.
[115]李晓梅、黄朝晖、蔡勋,等,并行与分布式可视化技术及应用,北京,国防工业出版社,2001:1~10
[116]潘志庚、钱喜武、石教英,并行分布式体绘制算法的设计,小型微型计算机系统,1994, 15(10):35~39
[117]潘志庚,分布式图形处理的理论与应用研究,[博士学位论文],浙江,浙江大学,1993
[118] Bernd F T, Peter H, Christof R S, et al, Local and Remote Visualization Techniques for Interactive Direct Volume Rendering in Neuroradiology, RadioGraphics, 2001, 21(6): 1561~1572.
[119]汪成为,人类认识世界的帮手——虚拟现实,北京,清华大学出版社,2000:1~12
[120]张家祥、方凌江、毛全胜,基于MATLAB6.X的系统分析与设计——虚拟现实,西安,西安电子科技大学出版社,2002:24~32
[121] VRML, http://www.web3d.org
[122]韦有双、杨湘龙、王飞,虚拟现实与系统仿真,北京,国防工业出版社,2004:25
[123] Colin R F Monks, Patricia J Crossno, George Davidson, et al, Three Dimensional Visualization of Proteins in Cellular Interactions, IEEE, Proceedings of the 7th IEEE Visualization Conference, CA, IEEE Press, 1996: 363~366.
[124] Andrew S Forsberg, David H Laidlaw, Andries van Dam, et al, Immersive Virtual Reality for Visualizing Flow Through an Artery, IEEE, Proceedings of the conference on Visualization'00, USA, IEEE Computer Society Press, 2000: 457~460.
[125] Keith Y C Goh, Virtual Reality Applications in Neurosurgery, IEEE, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, IEEE Press, 2005: 4171~4174.
[126] Pheng Ann Heng, Research and Applications of Virtual Medicine, IEEE, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, IEEE Press, 2005: 3433~3436.
[127] Bin Qin, Yong Qian Xiong, Xiong Jian, et al, A Framework Design for a Cyclotron Virtual Control Platform Based on Object-Oriented Methodology, IEEE, Proceedings of the 2000 Particle Accelerator Conference, Portland, IEEE Press, 2000: 3506~3508.
[128] Liu Hong, Zheng Feng, The Application of Visual Reality in Medicine, IEEE, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, IEEE Press, 2005: 2874~2877.
[129]阳化冰、刘忠丽、刘忠轩,等,虚拟现实构造语言VRML,北京,北京航空航天大学出版社,2000:172~173、266~295
[130] MATLAB, http://www.mathworks.com
[131] Dirk-Alexander Sennst, Marc Kachelriess, Christianne Leidecker, et al, An Extensible Software-Based Platform for Reconstruction and Evaluation of CT Images, RadioGraphics, 2004, 24(2): 601~613.
[132] Th Flohr, K Stierstorfer, H Bruder, et al, Image Reconstruction and Image Quality Evaluation for a 16-Slice CT Scanner, Medical Physics, 2003, 30(5): 832~845.
[133]王召巴,CT扫描系统中成像系统响应的不一致性对重建图像质量的影响,光学技术, 2001,27(2):100~102
[134]刘晓,杨朝文,抽样间距和投影数对卷积滤波法图像重建质量的影响,四川大学学报,2004,41(3):588~593
[135] Michael Meibner, Jian Huang, Dirk Bartz, et al, A Practical Evaluation of Popular Volume Rendering Algorithms, SIGGRAPH, Proceedings of the 2000 IEEE Symposium on Volume Visualization, USA, ACM Press, 2000: 81~90.
[136] Schreiner Steven, Paschal Cynthia B, Galloway Robert L, Comparison of Projection Algorithms Used for the Construction of Maximum Intensity Projection Images, Journal of Computer Assisted Tomography, 1996, 20(1): 56~67.
[137] Kim Kwansik, Craig M Wittenbrink, Alex Pang, Extended Specifications and Test Data Sets for Data Level Comparisons of Direct Volume Rendering Algorithms, IEEE Transactions on Visualization and Computer Graphics, 2001, 7(4): 299~317.
[138] A C Kak, Malcolm Slaney, Principles of Computerized Tomographic Imaging, Society of Industrial and Applied Mathematics, 2001: 75~92.
[139] Jiang Hsieh, Computed Tomography: Principle, Design, Artifacts and Recent Advances, USA, SPIE, 2003: 118~122
[140] G T Herman, Image Reconstruction from Projections: the Fundamentals of Computerized Tomography, New York, Academic Press, 1980.
[141] L Shepp, B Logan, The Fourier Reconstruction of a Head Section, IEEE Transactions in Nuclear Science, 1974, 21(6): 21~43.
[142]吕翔,病理图像定量分析及其测量误差的控制,中国体视学与图像分析,2002,7(1):58~62
[143]王树党,计算机图像分析技术在形态计量学、立体计量学研究中的应用及发展趋势,基础医学教育,2001,3(3):198
[144]薛淑莲、王亚方、葛晓静,图像分析技术及其在生物医学界的应用,山西医药杂志,2003,32(6):553~554
[145]杨建茹,平均光密度在医学图像分析中的定量,中国医学影像技术,1999,15(4):322~323
[146]王树党,图像分析系统中光度学参数——灰度与光密度的应用,山西医科大学学报,2003,34(5):462
[147]杨建茹、管增伟、陈跃,等,定量分析的显微医学图像的获取条件,中国医学影像技术,2001,17(8):801~802
[148]司京玉、聂生东、陈瑛,等,免疫组织化学显微图像分析技术进展,国外医学生物医学工程分册,2002,25(3):117~121
[149]曹云新、陈镔复,影响生物组织图像灰度测量的因素探讨,分析测试技术和仪器,1995,1(2):45~48
[150]王浩军、林英华,图像处理和分析技术在免疫细胞化学和免疫组织化学中的应用,第四军医大学学报,1996,17(3):209~211
[151] Kenneth Falconer, The Geometry of Fractal Sets, Cambridge, Cambridge University Press, 2002: 9.
[152]张济忠,分形,北京,清华大学出版社,1995:56、111
[153] Herbert F J, Eduardo F, Neurons and Fractals: How Reliable and Useful Are Calculations of Fractal Dimensions? Journal of Neuroscience Methods, 1998, 81(1): 9~18.
[154] Khan M Iftekharuddin, Wei Jia, Ronald Marsh, Fractal Analysis of Tumor in Brain MR Images, Machine Vision and Applications, 2003, 13(5): 352~362.
[155] Thanh M Nguyen, Rangaraj M Rangayyan, Shape Analysis of Breast Masses in Mammograms via the Fractal Dimension, IEEE, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, IEEE Press, 2005: 3210~3213.
[156] H Ahammer, T T J Devaney, H A Tritthart, Fractal Dimension for a Cancer Invasion Model, Fractals, 2001, 9(1): 61~76.
[157] F Caserta, W D Eldred, E Fernandez, et al, Determination of Fractal Dimension of Physiologically Characterized Neurons in Two and Three Dimensions, Journal of Neuroscience Methods, 1995, 56(2): 133~144.
[158]陈真诚、周兆英、赵于前,等,人体肝脏组织CT图像的分维特征研究,航天医学与医学工程,2005,18(3):206~210.
[159] Sun Wan-rong, Yu Bian-zhang, Zhang Xiao-jing, et al, Fractal Feature Extraction of Marrow Cell Images, IEEE, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, IEEE Press, 2005: 6375~6378.
[160]姚宇华、严洪、熊江辉,基于分形特征的模拟失重条件下细胞骨架的图像分析,中国图象图形学报,2004,9(2):230~233.
[161]张红新,张云汉,黄长征,分形和分形维数及其在医学形态学领域的应用,中国体视学与图像分析,1998,3(3):189~192
[162]陈钢、欧阳明、俞帆,等,细胞核形态的分形研究,中国体视学与图像分析,1998,3(3):154~157
[163]赵健,小波与分形理论在图像处理中的应用研究,[博士学位论文],陕西,西北工业大学,2003
[164] Keith C C, Computation of the Fractal Dimension of Topographic Surfaces Using the Triangular Prism Surface Area Method, Computers & Geosciences, 1986, 12(5): 713~722.
[165] H W Zhou, H Xie, Direct Estimation of the Fractal Dimensions of a Fracture Surface of Rock, Surface Review and Letters, 2003, 10(5): 751~762.
[166] Pierre S, Jean-F R, On the Validity of Fractal Dimension Measurements in Image Analysis, Journal of Visual Communication and Image Representation, 1996, 7(3): 217~229.
[167]张琦,神经再生素促大鼠背根神经节生长作用的研究,[硕士学位论文],江苏,南通大学,2003
[168] Georgios Sakas, Michael G Vicker, Peter J Plath, Case Study: Visualization of Laser Confocal Microscopy Datasets, IEEE, Proceedings of the 7th IEEE Visualization Conference, San Francisco, IEEE Press, 1996: 375~379.
[169] Nathan S Claxton, Thomas J Fellers, Michael W Davidson, Laser Scanning Confocal Microscopy, http://www.olympusfluoview.com/theory/LSCMIntro.pdf.
[170] YinLong Sun, Bartek Rajwa, J Paul Robinson, Adaptive Image-Processing Technique and Effective Visualization of Confocal Microscopy Images, Microscopy Research and Technique, 2004, 64(2): 156~163.
[171] Wim C de Leeuw, Robert van Liere, Pernette J Verschure, et al, Visualization of Time Dependent Confocal Microscopy Data, http://homepages.cwi.nl/~wimc/psgz/vis000.pdf.
[172] YQ Guan, M Opas, YY Cai, et al, Application of Virtual Reality in Volumetric Cellular Visualization, http://www.terarecon.com/downloads/products/vp_confocalimaging.pdf.
[173] Anshuman Razdan, Kamal Patel, Gerald E Farin, et al, Volume Visualization of Multicolor Laser Confocal Microscope Data, Computers & Graphics, 2001, 25(3): 371~382.
[174] ShiaoFen Fang, Yi Dai, Frederick Myers, et al, Three-Dimensional Microscopy Data Exploration by Interactive Volume Visualization, Scanning, 2000, 22(4): 218~226.
[175]于大勇,生物医学显微图像处理及研究,[硕士学位论文],南京,南京理工大学,2002.
[176]陈箐、彭承琳、楚燕飞,等,周围神经损伤与再生的可视化研究,生物医学工程学杂志,2005,22(2):324~326
[177] B S Duerstock, C L Bajaj, R B Borgens, A Comparative Study of the Quantitative Accuracy of Three-Dimensional Reconstructions of Spinal Cord from Serial Histological Sections, Journal of Microscopy, 2003, 210(2): 138~148.
[178] B S Duerstock, Double Labeling Serial Sections to Enhance Three-Dimensional Imaging of Injured Spinal Cord, Journal of Neuroscience Methods, 2004, 134(1): 101~107.
[179] Eric M B, Timothy W K, Carol J, et al, A Technique for Quantitative Three-Dimensional Analysis of Microvascular Structure, Microvascular Research, 2002, 63(3): 279~294.
[180] Tao Ju, Building a 3D Atlas of the Mouse Brain, [Ph.D. Dissertation], USA, Rice University, 2005.
[181]罗述谦,医学图像配准技术,国外医学生物医学工程分册,1999,22(1):1~8
[182] N M Alpert, D Bradshaw, D Kennedy, et al, The Principal Axes Transformation: a Method for Image Registration, Journal of Nuclear Medicine, 1990, 31(10): 1717~1722.
[183] P Josien, W Pluim, J B Antonie Maintz, et al, Image Registration by Maximization of Combined Mutual Information and Gradient Information, IEEE Transactions on Medical Imaging, 2000, 19(8): 809~814.
[184] Lukas Mroz, Real-Time Volume Visualization of Low-End Hardware, [Ph.D. Dissertation], Germany, Vienna University of Technology, 2001.
[185] Analyze, http://www.mayo.edu/bir/
[186]杜光伟,医学图像的三维可视化方法学研究及Medvis的开发与应用,[硕士学位论文],北京,首都医科大学,2002
[187] Amira, http://www.amiravis.com/
[188] VTK, http://public.kitware.com/VTK/index.php
[189] Yan Zhang, Peter J Passmore, Richard H Bayford, Visualization and Post-Processing of 5D Brain Images, IEEE, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, IEEE Press, 2005: 1083~1086.
[190] C Charles Law, Amy Henderson, James Ahrens, An Application Architecture for Large Data Visualization: a Case Study, IEEE, Proceedings of the IEEE 2001 Symposium on Parallel and Large-Data Visualization and Graphics, USA, IEEE Press, 2001: 125~128.
[191]赵明昌、田捷、薛健,等,医学影像处理与分析开发包MITK的设计与实现,软件学报,2005,16(4):485~495
[192] ITK, http://www.itk.org/
[193] OpenGL, http://www.sgi.com/products/software/opengl/
[194] OSIRIS, http://www.sim.hcuge.ch/osiris/01_Osiris_Presentation_EN.htm
[195] OSIRIS User Manual Version 3.1, http://www.sim.hcuge.ch/osiris/OsirisUsersManual.pdf
[196] Image-Pro Plus, http://www.mediacy.com
[197] A Rawlinson, C Elcock, A Cheung, et al, An In-Vitro and In-Vivo Methodology Study of Alveolar Bone Measurement Using Extra-Oral Radiographic Alignment Apparatus, Image-Pro Plus Software and a Subtraction Programme, Journal of Dentistry, 2005, 33(9): 781~788.
[198] 3DViewnix, http://mipgsun.mipg.upenn.edu/~Vnews/
[199] Alice, http://www.alicesoftware.com/index.htm
[200] Mvox, http://www.anamedic.dk/
[201] IDL, http://www.ittvis.com/index.asp
[202] Paul A DeYoung, Benjamin B Hilldore, Lee M Kiessel, et al, Analysis of Event-Mode Data with Interactive Data Language, Nuclear Instruments and Methods in Physics Research A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2003, 505(1): 294~296.
[203] Ron Knensel, Visualization and Analyzing Medical Images from Multiple Modalities Using IDL, http://www.ittvis.com/index.asp
[204] Hongjie Xie, Nigel Hicks, G Randy Keller, et al, An IDL/ENVI Implementation of the FFT-Based Algorithm for Automatic Image Registration, Computers & Geosciences, 2003, 29(8): 1045~1055.
[205] Charles Seiter, IDL 6.0, MacWorld, 2004, 21(7): 43.
[206]徐智勇,IDL——第四代科学计算可视化语言,中国图象图形学报,1996,1(1):86
[207]杜捷,IDL5.0——第四代可视化语言的飞跃,中国图象图形学报,1996,1(4):349~351
[208]聂斌、胡冬梅、张琳,等,IDL及其在医学图像处理中的应用,中国中西医结合影像学杂志,2005,3(2):132~134
[209]闫殿武,IDL可视化工具入门与提高,北京,机械工业出版社,2003:153~155
[210] Charles A Taylor, Mary T Draney, Joy P Ku, et al, Predictive Medicine: Computational Techniques in Therapeutic Decision-Making, Computer Aided Surgery, 1999, 4(5): 231~247.
[211] Luis Serra, Ng Hern, Chua Gim Guan, et al, An Interface for Precise and Comfortable 3D Work with Volumetric Medical Datasets, Studies in Health Technology and Informatics, 1999, 62: 328~334.
[212] Alexandra Chabrerie, Fatma Ozlen, Shin Nakajima, et al, Three-Dimensional Reconstruction and Surgical Navigation in Pediatric Epilepsy Surgery, Pediatric Neurosurgery, 1997, 27(6): 304~310.
[213] David T Gering, Arya Nabavi, Ron Kikinis, et al, An Integrated Visualization System for Surgical Planning and Guidance Using Image Fusion and Interventional Imaging, Springer, Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention, Cambridge England, Springer, 1999: 809~819.
[214] S A Blackett, D Bullivant, C Stevens, et al, Open Source Software Infrastructure for Computational Biology and Visualization, IEEE, Proceedings of the 2005 IEEE Engineering inMedicine and Biology 27th Annual Conference, Shanghai, IEEE Press, 2005: 6079~6082.
[215] Ligong Wang, Weiqiang Liu, Yonghua Yu, et al, A Research on the Hospital Intranet-Based Three-Dimensional Image Assisted Diagnosis System, IEEE, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, IEEE Press, 2005: 5165~5168.
[216] Matthew J McAuliffe, Francois M Lalonde, Delia McGarry, et al, Medical Image Processing, Analysis & Visualization in Clinical Research, IEEE, Proceedings of the 14th IEEE Symposium on Computer-Based Medical Systems, Washington USA, IEEE Press, 2001: 381~386.
[217]刘济全、冯靖、蔡超,等,一个三维医学图像实时可视化系统4DView,生物医学工程学杂志,2002,19(3):532~536
[218] Asklof J, Carlander M L, Christopoulos C, Region of Interest Coding in JPEG2000, Signal Processing: Image Communication, 2002, 17(1): 105~111.
[219]张廉良,MRA与CTA头部血管成像技术探讨,实用医技杂志,2004,11(7):1276~1277
[220]葛雅丽、郑敏文、张劲松,等,动态增强磁共振血管成像技术及应用优势,临床放射学杂志,2003,22(9):789~792
[221]李惠民、于红、肖湘生,等,颅内血管病变CTA综合评价,临床放射学杂志,2003,22(2):97~100
[222] Tobias Boskamp, Daniel Rinck, Florian Link, et al, New Vessel Analysis Tool for Morphometric Quantification and Visualization of Vessels in CT and MR Imaging Data Sets, RadioGraphics, 2004, 24(1): 287~297.
[223] Marcela Hernandez-Hoyos, Maciej Orkisz, Philippe Puech, et al, Computer-Assisted Analysis of Three-Dimensional MR Angiograms, RadioGraphics, 2002, 22(2): 421~436.
[224]陆建平、刘崎,三维增强磁共振血管成像,上海,上海科学技术出版社,2005:15~20
[225] Milan Sonka, Vaclav Hlavac, Roger Boyle, Image Processing, Analysis, and Machine Vision, Second Edition, USA, Thomson Learning, 2002: 576~578.