鼻咽癌近距离放射治疗手术计划和仿真系统的关键技术研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
现代科学技术的发展越来越体现多门学科的交叉和渗透。医学虚拟现实和仿真技术作为正在发展起来的研究方向,是集医学、计算机图形学、计算机视觉、数学分析等学科为一体的新型交叉研究领域。近20年来,随着计算机技术和医学影像学的发展,肿瘤放射治疗技术也经历了很大的变革。正像著名的美国医学物理学家J.Purdy所描述的那样,放射治疗已进入一个崭新的令人振奋的时代,即三维放射治疗时代(Three—Dimensional RadiationTherapy,3DRT)。
     鼻咽癌是我国的高发恶性肿瘤,由于其解剖部位、病理类型、生物学行为等的特殊性,放射治疗是其治疗的主要手段。近年来国内外开展经颌下咽旁间隙插植组织间近距离放疗技术,是近距离治疗技术一项重要进展。但是由于鼻咽癌靶区附近存在着众多正常的神经、血管等重要解剖结构,因此如果能结合医学虚拟现实和仿真技术精确地明确靶区、合理设计剂量计划,将可以进一步做到手术的精确化,保护正常组织、提高疗效和生活质量。同时通过构建手术仿真系统,使医生可以借助虚拟环境进行手术预演,从而使研究结果可以应用于手术计划、手术训练、医学教学等医学科研、临床和教学培训各个环节,具有非常重要的意义。
     本文首先简要介绍了近距离放射治疗计划与手术仿真方面的背景。然后对人体鼻咽部组织CT图像的分割、三维重建、网格化简、近距离放射源的剂量计算、剂量优化模型和方法、基于质点弹簧模型的针管插植仿真、基于OBB包围盒的碰撞检测等关键技术进行了研究。本文工作的主要创新之处在于:
     1.提出了一种基于PCA形变模型的医学序列图像分割算法。
     一个组织在CT序列图像中其形状变化往往是连续的,因此,我们先对病人某个组织的CT扫描序列图像中的相隔的几幅图像用其他方法做一个分割(由于边界不清晰,一般需要医生的参与)。然后将分割后的组织提取出来,生成其距离图。再对这几幅距离图使用主成分分析算法(Principle Component Analysis)进行分析,求其平均距离图及其协方差矩阵的特征值和特征矢量。然后利用平均距离图和这些特征值和特征矢量生成一个在参数作用下可以连续变形的模板,仿真组织在序列图像中的形状变化。再将这个模板采用互信息法和主动轮廓模型法(snake)去匹配分割序列中其他未分割的图像,从而达到一个比较理想的分割效果。
     2.提出了一种基于超椭圆形变模型的医学图像分割算法
     椭圆变形模板分割算法对目标组织的轮廓形状有要求,在医学图像中,只要组织的轮廓比较光滑、结构对称,采用超椭圆模板来进行匹配分割往往能够取得比较好的结果,而且其没有序列图像分割这~限制。算法先对待分割组织的典型形状用超椭圆进行拟合,获得先验信息。然后使用优化算法获得超椭圆与目标组织的最佳匹配。然后再使用主动轮廓模型法进行进一步调整,得到最终分割结果。由于超椭圆的控制参数比较少,因此相对于标准的主动形状模型(ASM),它的优点在于其无论是变形还是形状参数的统计都比较方便,特别是省去了进行形状参数统计分析时各形状图的大小、角度、位置对准。
     3.本文提出了一种基于GENOCOP和POWELL算法并支持线性约束的混合遗传算法
     本文对标准的POWELL算法进行了修改,使其支持线性约束,并将其和遗传算法GENOCOP进行结合,构成一种新的支持线性约束的混合遗传算法。POWELL算法经过修改后,并不能找到线性约束下的函数极值点,只能达到最优解附近区域。本文根据对其原因的分析已及对实验结果的统计分析,对GENOCOP算法的变异、交叉算子进行了进一步的改进,降低遗传算子的收敛能力,增强其全局搜索能力。新的算法融合了遗传算法的全局搜索能力和POWELL的局部优化能力,并利用遗传算法中交叉算子的特性有效的解决了POWELL算法修改后所带来的问题,从而将两者有机的结合了起来。
     4.本文提出了一种连续驻留位置和驻留时间的近距离放疗剂量优化方法
     本文提出了一种连续驻留位置和驻留时间的近距离放疗剂量优化方法。首先将驻留t看成是位置x的一个连续函数,建立各参考剂量点剂量计算的积分模型,计算每个参考剂量点的剂量。然后用计算剂量和目标剂量值之差的加权平方和为目标函数,用优化算法求解最优的曲线参数。在优化的过程中由于实际的情况的复杂性,可以根据不同的情况不同的特点对曲线进行分段。
     得到优化的曲线后再用积分的数值逼近方法将其离散化,得到最终的插值点源治疗计划。算法不仅解决了负的驻留时间问题,还让相邻驻留位置的驻留时间更加平滑。同时,在最后的离散化过程中,可以得到不同的驻留位置和驻留时间结果,使计划具有更好的灵活性。
     5.应用质点弹簧模型实现了二维软组织的针管插植仿真
     鼻咽部近距离放射治疗时放射源需经针管插植的路径送到肿瘤组织附近。对针管插植过程进行仿真,其结果可以用于医生的训练,同时可以估计插植引起的软组织变形,使剂量计划更准确。本文使用OBBTREE进行碰撞检测,使用质点弹簧模型对软组织进行了建模,对插植手术进行了仿真,模拟了针管插入二维软组织时的组织变形和受力。由于质点弹簧模型模型简单,实现容易,计算速度比较快,因此能够满足仿真的实时性要求。
The development of present-day science and technology was more and more characterized by the crossover of multi-disciplinarity.Virtual reality and simulation as a new area of rearch encompasses a wide spectrum of techniques including medicine、computer graphic technology、computer vision technology、mathematic analyzing and so on.Going with the development of computer technology and studying of medical image,cancer treatment technology go through a great change.Just as americal physical scientist J.Purdy described:radiation therapy has entrance a new era,the era of 3DRT(Three-Dimensional Radiation Therapy).
     Nasopharyngeal Cancer is one of the most common form of human cancer and the leading cause of human cancer deaths.Because of its characteristic,radiation therapy has become its major treatment option and Brachytherapy:which is a type of internal radiation thrapy given by placing radioactive sources directly into the cancerous tissue,is often used.Because there are many important tissues such as vas、nerve,lie around the nasopharynx,the dosimetric treatment planning must be designed carefully to achieves a desired dose distribution to the target,while sparing the critical structures.The image based treatment planning and treatment simulation for brachytherapy which can improve treatment quality,was studied by many researchers in recent years.The results of these research are of great value to treatment teaching,doctor training,clinical diagnosis and therapy.
     Firstly,we introduced the background of this area,then the key technology of image segmentation of soft tissues,three-dimensional modeling,calculation and optimization of HDR radiation dose,needle insertion simulation based on mass-springs model was researched.
     The main contents and contributions of this dissertation are as follows:
     (1) An algorithm based on the active shape model is proposed for the segmentation of medical image series.The edge of soft tissue in medical images usually are not very clearly,so it's difficult to segment them only by the computer.But a tissue's shape transform sequentially in medical image series,we asked doctor to select some images from image series and segment the tissue in these images,then we used the results of the segmentation as training maps,created a active shape model by PCA Algorithm.Next we used this model to segemnt other images.The experimental results show the accuracy of this method.
     (2) A parametric shape modeling using deformable superellipses for segmentation of medical image was proposed.Superellipses can represent the smooth and symmetrical contour perfectly, Most of anatomical structures having such characters can be approached by a superellipse.Prior shape information been got from a statistical modal analysis of a training set.This information was used to restrict the transformation of the surperellipse parameters.We used Hybrid Genetic Optimization Algorithm to find the optimal superellipse parameters,and snake algorithm embed with these shape information to segment the image.With shape guidance,this algorithm is less sensitive to initial contour placement and more robust even in the presence of large boundary gaps.
     The experiments show the efficiency of this method.
     (3) A new hybrid genetic algorithm based on a continuous-parameter GA with linear constraints (GENOCOP) and POWELL algorithm was proposed.The genetic algorithm has been widely used in many fields as an easy robust global search and optimization method.To optimizing the dose distribution,a new hybrid genetic algorithm based on a continuous-parameter GA with linear constraints(GENOCOP) and POWELL algorithm was proposed.The POWELL algorithm was modified to support the linear constraints and was embed in hybrid genetic algorithm as a local search operation,and the operators of GENOCOP were amended to improve its ability of global search.The simulation results show that compared to traditional GENOCOP methods,this hybrid genetic algorithm has obvious potential on many respects,such as convergence speed,solution accuracy,ability of global optimization.
     (4) An algorithm to optimize the dwell time of the radioactive source was proposed. Brachytherapy is the treatment of cancer by means of radioactive sources that are placed at short distances from the target cells.The computer-based HDR planning system of brachytherapy is becoming more and more widely used.To get the solution that best satisfies the clinical dose constraints,we proposed an algorithm to optimize the dwell time of the radioactive source.Firstly we considered the dwell time as a continuous function of the dwell position,computed the dose values of referenced dose points.The minimal difference between these dose values and demanded dose values was used as the objective of an optimization algorithm to get the optimized function parameters.The function curve can be separated to several sects.At last the optimized curve was dispersed using compound trapezoid formula to get the dwell positions and dwell times.This method not only avoids the emergence of negative dwell time,but also reduces the dwell time gradient.And during the process of dispersing the curve,we can get different dwell times and dwell positions.This makes the brachytherapy treatment plan more flexible.
     (5) Simulation of needle insertion based on mass-spring model was developed to facilitate surgeon training and planning for brachytherapy.Inserting a needle into soft tissues causes the tissues to displace and deform:ignoring these effects during seed implantation leads to imprecise dose distribution.We construct a 2-D dynamic mass-spring model using 400 springs and simulated the needle insertion.The deformation of the tissue and the force can be calculated.Simulation achieved 100 flames per second on a 2Ghz Pentium PC.
引文
[1]MD US Department of Health.NLM Long Range Plan:Electronic Imaging.Report of the Board of Regents Bethesda,1990.NIH Pub 90-2197
    [2]Ackerman MJ.The Visible Human Project.Journal of Biocommunicate,1991,18(2):14-18
    [3]Glombitza G,Lamade W.and Demiris A.M.Virtual Planning of Liver Resections:Image Processing,Visualization and Volumetric Evaluation.International Journal of Medical Information,1999,53:225-237
    [4]Miller K.Constitutive Modelling of Abdominal Organs.Journal of Biomechanics,2000,33:367-373
    [5]Wyatt C.L,Y.Ge,Vining D.J.Automatic segmentation of the colon for virtual colonscopy.Computerized Medical Imaging and Graphics,2000,24(1):1-9
    [6]Mori K,Hoshino Y,Suenaga Y,et al.An improved method for generating virtual stretched view of stomach based on shape deformation.International Congress Series,2001,1230:447-453
    [7]Kitaoko H.Computational Morphology of the Lung and Its Virtual Imaging.European Journal of Radiology,2002,44:164-171
    [8]夏顺仁,汪元美,吕维雪.血管双投影下多目标优化截面重建方法[J].中国生物医学工程学报,1996,15(4):289-294
    [9]吕维雪,夏灵,刘峰,等.人体左心室复合材料有限元机械模型的建立[J].中国生物医学工程学报,2002,21(5):404-410
    [10]夏玲,吕维雪.基于虚拟心脏的心电拟问题求解[J].中国生物医学工程学报,1998,17(4):301-309
    [11]张立峰,刘锋,吕维雪.虚拟心脏的研究与应用[J].中国生物医学工程学报,2000.24(2):93-96
    [12]白净.血液循环系统仿真.长春:吉林省科技出版社,1996
    [13]仇安琪,白净.人体呼吸系统数学模型[J].北京生物医学工程,19(1):6-13
    [14]卢虹冰,白净,张立藩.多元非线性人体循环呼吸系统模型及其应用[J].第四军医大学学报,1999,20(3),190-194
    [15]郑筱祥,戴品忠,白净.生理系统仿真建模[M].北京:北京理工大学出版社,2003:36-95
    [16]Kuhn,C.,U.Kuhnapfel,H.-G.Krumm,and B.Neisius,A 'virtual reality' based training system for inimally invasive surgery,Computer Assisted Radiology(CAR'96),Paris,Jun.26-29,1996,pp.764-769.
    [17]K(u|¨)hnapfel U G,Neisius B.Realtime graphical computer simulation for endoscopic surgery[A].Proceedings of Medical Meets Virtual Reality Ⅱ[C].San Diego,CA,January 27-30,1994.
    [18]Bro-Nielsen M,Cotin S.Soft Tissue Modeling in Surgery Simulation for Prediction of Results of Craniofacial Operations & Steps Toward Virtual Reality Training Systems[A].Proceedings of 3rd International Workshop Rapid Prototyping in Medicine & Computer-Assisted Surgery[C].Edangen,Germany,October 19-21,1995.35-46.
    [19]熊岳山,徐凯,王彦臻,等,虚拟膝关节镜手术仿真系统的关键技术研究[J],国防科技大学学报,2007,29(1),76-80
    [20]张红志.三维放射治疗的发展(上)[J].中华医学信息导报,2005,20(18):19.
    [21]张红志.三维放射治疗的发展(下)[J].中华医学信息导报,2005,20(21):22.
    [22]Mamoudieh A.,Tremblay C.et al.Anatomy based inverse planning dose optimization in HDR prostate implant:A toxicity study[J],Radiotherapy and Ontology.2005,75(3):318-324
    [23]潘建基,吴君心.近距离放射治疗的临床应用进展[J],中国癌症杂志,2006,16(6):459-463
    [24]张书旭,李文华,徐海荣.宫颈癌三维放射治疗的新进展[J].中国医学物理学杂志[J], 2004,21(4):196-199
    [25]惠周光 徐国镇.鼻咽癌调强适形放射治疗[J].放射肿瘤治疗学.2005,20(16):22-23
    [26]潘建基,吴君心.近距离放射治疗的临床应用进展[J],中国癌症杂志,2006,16(6):459-463
    [27]吕长兴,张红志,殷蔚伯,等.国产与核通后装治疗计划系统治疗方案的比较[J]中华放射肿瘤学杂志,1999,8(6):109-112
    [28]李文华,张书旭,周猛,徐海荣.临床后装放射治疗计划系统的研究进展[J].中国医学物理学杂志,2004,21(5):255-257
    [29]项晖,庄天戈.基于CT/MRI图像的三维近距离放射治疗计划系统[J],中国医疗器械杂志,2002,26(6):398-401
    [30]肖杰,李树祥,王志远.三维近距离放射治疗计划系统的研究[J],医疗卫生装备,2000,1:7-9
    [31]陈为,彭群生等.手动式电磁定位及图像导航的短径癌症放射治疗系统[J].计算机辅助设计与图形学学报.2002,14(9):870-876
    [32]Michael Lahanas and Dimes Baltas,Are dose calculations during dose optimization in brachytherapy necessary?[J].Med.Phys.2003,30(23):2368-2375,
    [33]Michael Lahanas,Kostas Karouzakis,Stavroula Giannouli,Richard Mould and Dimes Baltas,Inverse Planning in Brachytherapy:Radium to High Dose Rate 192 Iridium Afterloading[J],Nowotwory Journal of Oncology.2004,54(1):195-218
    [34]Ron Alterovitz,Etienne Lessard,et al.,Optimization of HDR brachytherapy dose distributions using linear programming with penalty costs[J],Medical Physics,2006,33(11):4012-4019
    [35]Michael Lahanas,Eduard Schreibmann and Dimos Baltas,Constrained free gradient-based optimization algorithms for multiobjective inverse planning in intensity modulated radiotherapy[J],Phys.Med.Biol.2003,48(28):2843-2871
    [36]M.Lahanas,D.Baltas and S.Giannouli,Global Convergence Analysis of Fast Multiobjective Gradient based Dose Optimization Algorithms for High Dose Rate Brachytherapy[J],Phys.Med.Biol.2003,48(5):599-617
    [37]Chajon,Ertrique,Dumas,Isabelle ere al,Inverse Planning Approach for 3-D MRI-Based Pulse-Dose Rate Intracavitary Brachytherapy in Cervix Cancer[J],International Journal of Radiation Ontology Biology Physics,2007,69(9):955-961
    [38]Martin,Andre-Guy,Roy,Jean etc al,Permanent prostate implant using high activity seeds and inverse planning with fast simulated annealing algorithm:A 12-year Canadian experience[J].International Journal of Radiation Ontology Biology Physics,2007,67(2):334-341
    [39]Christina Simone,Modeling of Needle Insertion Forces for Percutaneous Therapies[D],American Baltimore,Department of Mechanical Engineering,Johns Hopkins University.2002
    [40]S.P.DiMaio,S.E.Salcudean.Needle Steering and Motion Planning in Soft Tissues[J],IEEE Trans.Biomedical Engineering,52(6),pp.965-974,June 2005
    [41]Han-Wen Nienhuys,Interactive needle insertions in 3D nonlinear material[R],UU-CS-2003-019,2003
    [42]Ron Alterovitz,Jean Pouliot,Richard Taschereau etc al,Simulating Needle Insertion and Radioactive Seed Implantation for Prostate Brachytherapy[C],in Medicine Meets Virtual Reality 11(MMVR11),J.D.Westwood et al.(Eds.),IOS Press,Jan.2003,pp.19-25
    [43]付忠良,一些新的图像闽值选取方法[J].计算机应用,2000,10(9):15-17
    [44]Olivo.J.C.Automatic threshold selection using the Wavelet transform[J].CVGIP-GMIP,1994,5(1):3-14.
    [45]景晓军,蔡安妮,孙景鳌.一种基于二维最大类间方差的图像分割算法.通信学报,2001:22(4):71-76
    [46]付忠良,基于图像差距度量的阈值选取方法[J].计算机研究与发展,2001,38(5):563-567
    [47]薛景浩,章毓晋,林行刚.二维遗传算法用于图象动态分割.自动化学报,2000,26(5):749-753.
    [48]张毅军,吴雪菁,夏良正,二维熵图象分割的快速递推算法,模式识别与人工智能,1997,10:259-264.
    [49]章毓晋.图象分割.北京:科学出版社,2001.
    [50]郑南宁.计算机视觉与模式识别.北京:国防工业出版社,1998.
    [51]王树文,闫成新,张天序.数学形态学在图像处理中的应用.计算机工程与应用,2004,3:89-92.
    [52]冯俊萍,赵转萍.基于数学形态学的图像边缘检测技术.航空计算技术,2004,34(3):53-56
    [53]王建中,赵军.图像边缘提取的小波多孔算法及改进.武汉理工大学学报,2004,26(1):76-79.
    [54]Udupa J.K.,and S.Samarasekera,Fuzzy Connectedness and Object Definition:Theory,Algorithms,And Applications in Image Segmentation,Graphical Model and Image Processing,1995,58(3):246-261
    [55]Shu-Yen Wan 1 and William E.Higgin,Symmetric Region Growing,Departments of Electrical Engineering and Computer Science and Engineering,Pennsylvania State University
    [56]Mangin J.F.,Frouin V.,Bloch I.,J.Regis,Lopez-Krahe J..From 3D magnetic resonance images to structural representations of the cortex topography using topology preserving deformations.J.Math.Imag.Vis.,5:297-318,1995.
    [57]Kass M,Witkin A,Terzopoulos D.Snakes:Active Contour Models[J].International Journal of Computer Vision(S0920-5691),1987:321-331
    [58]Cohen L.D.,On Active Models and Balloons,CVGIP:IU,1999,53(2),211-218
    [59]X u C.,Prince J.L.,Snakes,Shapes and gradient vector flow,IEEE Tran.Image Processing,1998,17(3):359-369
    [60]黄万军,尹宝才,陈通波,等。基于三维可变形模板的眼睛特征提取[J]。计算机研究与发展,2002,39(4):495-501
    [61]Li Mengdong,Ruan Qiuqi.An alogrithm of extracting mouth features from image using deformable templates[J].Journal of Northern Jiaotong University,2002,26(2):11-14(in Chianese)
    [62]Cootes T.F.,Hill A.,Taylor C.J.,and Haslam J.,Use of active shape models for locating structures in medical images[J].Image and Vision Computing(S0262-8856),1994.12(6):355-366
    [63]Cootes T.F.,Taylor C.J.,Cooper D.H.,and Graham J.,Active shape models - their training and application[J],Computer Vision and Image Understanding(S1077-3142).,1995.61(1):38-59
    [64]Cootes T.E,Edwards G.J.and Taylor C.J.Active Appearance Models[J],IEEE PAMI(S 0162-8828),2001,23(6):681-685
    [65]Leventn M.E,Grimson W.E.L,Faugeras O.Statistical shape influence in geodesic active contours[C].In Proc.Conf.Computer Vision and Pattern Recognition.Hilton Head Island,2000,1:316-323.
    [66]Gong L.,Pathak S.,Haynor D.,Cho P.,and Kim Y.,"Parametric shape modeling using deformable superellipse for prostate segmentation," IEEE Transactions on Medical Imaging,vol.23,no.3,pp.340-349,2004
    [67]Solina F.andBajcsy R.,"Recovery of parametric models from range images:The Case for superquaddcs with global deformations," IEEE Trans.Pattern Anal.Machine Intell.,vol.12,pp.131-147,Feb.1990
    [68]Keppel E.Approximating complex surfaces by triangulation of contour lines[J].IBM Journal of Research and Development(S 0018-8646),1975,19(1):2-11
    [69]Lorensen W.E,Cline H.E.Marching cubes:a high-resolution 3D surface construction algorithm[J].ACM SIGGRAPH Computer Graphics(S 0097-8930),1987,21(4):163-169
    [70]Rajon DA,Bolch WE.Marching cube algorithm:review and trilinear interpolation adaptation for image-based dosimetric models.Computerized medical imaging and graphics(S0895-6111),2003,27:411-435.
    [71]Wu J.,Sullivan J.M.Multiple material marching cubes algorithm[J].International Journal for Numerical Methods in Engineering(S0029-5981),2003,58:189-207
    [72]Tomoyuki Fujimori,Hiromasa Suzuki.Surface Extraction from Multi-material CT data[C].Ninth International Conference on Computer Aided Design and Computer Graphics(CAD/CG 2005).
    [73]王延华,洪飞,吴恩华等.基于VTK库的医学图像处理子系统设计和实现[J].计算机工程与应用,2003,(8):205-207.
    [74]Hoppe H,Progressive meshes,Computer Graphics(SIGGRAPH '96),1996,30(30):99-108
    [75]Alliez P,Debrun M,Debrun M,Interactive geometry remeshing,ACM Transactions on Graphics,2002,21(3):347-354
    [76]Schroeder W J,Decimation of triangle meshes,Computer Graphics,1992,26(2):65-70
    [77]胡逸民.肿瘤放射物理学[M].北京:原子能出版社,1999 317-327.
    [78]石成玉.EGS4程序介绍与使用[D].http://www.virtualphantoms.org/egs4/training/egs4books_-/index.html.2000
    [79]Andreo P.Monte Carlo Techniques in Medical Physics[J].Phys Med Biol,1991,36..861-920.
    [80]Nath R.et al.,Dosimetry of interstitial brachytherapy sources:Recommendations of the AAPM Radiation Therapy Committee Task Group No.43[J],Med.Phys.1995,22(2):209-234
    [81]Rivard M.J.et al.,Update of AAPM Task Group No.43 Report:A revised AAPM protocol for brachytherapy dose calculations[J],Med.Phys,2004,31(3):633-674.
    [82]Rivard M.J.et al.,Code of practice for brachytherapy physics:Report of the AAPM Radiation Therapy Commitee Task Group No.56,Med.Phys.1997,24(10),October
    [83]Nath R.et al.,Dosirnetry of interstitial brachytherapy sources:Recommendations of the AAPM Radiation Therapy Committee Task Group No.43[J],Med.Phys.1995,22(2):209-234
    [84]Rivard M.J.et al.,Update of AAPM Task Group No.43 Report:A revised AAPM protocol for brachytherapy dose calculations[J],Med.Phys,2004,31(3):633-674.
    [85]Nath R.et al.,Dosimetry of interstitial brachytherapy sources:Recommendations of the AAPM Radiation Therapy Committee Task Group No.43[J],Med.Phys.1995,22(2):209-234
    [86]Anderson L.L.,Nath R.,and.Weaver Raven K.A,Interstitial Brachytherapy:Physical,Biological and Clinical Conside rations,Interstitial Collaborative Working Group(ICWG),NewYork,1990
    [87]胡逸民.肿瘤放射物理学[M].北京:原子能出版社,1999 317-327.
    [88]Lessard E,Development and clinical introduction of an inverse planning dose optimization by simulated annealing(IPSA) for high dose rate brachytherapy[J],Med.Phys.2004,31(10),29-35
    [89]Ron Alterovitz,Etienne Lessard,et al.,Optimization of HDR brachytherapy dose distributions using linear programming with penalty costs[J],Medical Physics,2006,33(11):4012-4019.
    [90]Milickovic N,Lahanas M,Papagiarmopoulou M,and Baltas D.Multiobjective anatomy-based dose optimization for HDR brachytherapy with constrained free deterministic algorithms[J],Phys.Med.Biol.,2002,47:2263-228
    [91]Lahanas M,Baltas D,and Zamboglo N.A Hybrid Evolutionary Multiobjective Algorithm for Anatomy-Based Dose Optimization Algorithm in HDR Brachytherapy[J],Phys.Med.Biol.2003,48399-415
    [92]何光渝.VISUL C++常用数值算法集.北京:科学出版社,2002,622-630
    [93]张丽萍,柴跃廷.遗传算法的现状及发展动向.信息与控制,2001,30(6):531-536
    [94]Il-Seok Oh;Jin-Seon Lee;Byung-Ro Moon.Hybrid genetic algorithms for feature selection,IEEE Transactions on Pattern Analysis and Machine Intelligence,2004,26(11):1424-1437
    [95]Hong,Wang;Zhao,Pei-xin.ANew Hybrid Genetic Algorithm for the Stochastic Loader Problem.Eighth ACIS International Conference on Software Engineering,Artitlcial Intelligence,Networking,and Parallel/Distributed Computing,Qingdao,2007.
    [96]Qi X.and Palmieri F.,Theoretical analysis of evolutionary algorithms with an infinite population size in continuous space,Part Ⅰ:Basic properties of selection and mutation,IEEE Trans.Neural Netw.,1994,5(1):102-119.
    [97]Zbigniew Michalewicz et al,GENOCOP:A Genetic Algorithm for Numerical Optimization Problems with Linear Constraints.Communications of the ACM.1996.39(12):1-27.
    [98]王小平,曹立明.遗传算法—理论、应用与软件实现.西安:西安交通大学出版社,2002
    [99]Powell M J D.An efficient method for finding the minimum of a function of several variables without calculating derivatives.Computer Journal,1964,7:155-162
    [100]Bro-Nielsen M.Modeling elasticity in solids using active cubes- application to simulated operations [C].in:Computer Vision,Virtual Reality and Robotics in Medicine,volume 905 of Lecture Notes in Computer Science[M].Springer,April 1995:535-541
    [101]Sagar M.et al.A Virtual Environment and Model of the Eye for Surgery Simulation[C].in:Computer Graphics(SIGGRAPH'94),1994:205-212
    [102]Wu X,et al.Adaptive Nonlinear Finite Elements for deformable body simulation using dynamic progressive Meshes[J].Computer graphics forum,2001,20(3)
    [103]Yang T Q.The visco-elastic theory and applications.Beijng:Scien-tific press.2004.9
    [104]Yan L X et al.Study of the Simulation of Soft Tissue Deformation in Virtual Surgery[J].Journal of System Simulation,2001(13),3:294-296(in Chinese)
    [105]Sederberg T,S Parry.Free-form deformation of solid geometric models[C].In:Proc.of SIGGRAPH 86,Annual Conference Series(Computer Graphics),ACM,1986:151-160
    [106]Gibson S FF.3D ChainMall:A Fast Algorithm for Deforming Volumetric Objects[C].In:1997Symposium on Interactive 3D Graphics,2000:149-154
    [107]Berkley J,Turkiyyah G,Berg D,Ganter M,Weghorst S,Real-Time Finite Element Modeling for Surgery Simulation:An Application to Virtual Suturing[C].IEEE Transactions On Visualization And Computer Graphics,Vol.10,No.3,May/June 2004
    [108]Bro-Nielsen M.Finite element modeling in surgery simulation[C].In:Proceedings of the IEEE,1998,86(3):490-503.
    [109]Sederberg T,Parry S.Free-form deformation of solid geometric models[C].In:Proc.of SIGGRAPH 86,Annual Conference Series(Computer Graphics),ACM,1986:151-160
    [110]Kalra P,Mangili A,Magnenat Thalmann N,Thalmann D.Simulation of Facial Muscle Actions Based on Rational Free Form Deforma- tions[J].Eurographics,1992
    [111]Su W H,Hughes J,Kaufman H.Direct manipulation of free-form deformations[J].Computer Graphics,July,1992,26(2):177-182.
    [112]Coquillart S.Extended Free-Form Deformation:A sculpturing Tool for 3D Geometric Modeling[C].In:Computer Graphics,SIGGRAPH Proceedings,1990,24(4):187-196.
    [113]Moccozet L,Mhalmarm T N.Dirichlet free-form deformations and their application to hand simulation[C].In:Proc.Of Computer Animation '97,IEEE,1997:93-102
    [114]Cover S,Ezquerra N,Brien J,Rowe R,Gadacz T,Palm E.Interactively deformable models for surgery simulation[J].IEEE Computer Graphics & Applications,November 1993:68-75
    [115]Yamashita J.,Yokoi H.,Fukui Y.,and Shimojo M..A virtual surface modeler for direct and regional flee form manipulation[C].In:Proc.of ICAT 94,The Fourth International Conference on Artificial Reality and Tele-Existence,1994:35-42.
    [116]M Kass,A Witkin,Terzopoulos D.Snakes:Active contour models[J].Int.J.Comput.Vision,1988,1(4):321-331
    [117]S FF Gibson.3D ChainMail:A Fast Algorithm for Deforming Volumetric Objects[C].In:1997Symposium on Interactive 3D Graphics,2000:149-154
    [118]Schill M A,Gibson S F,Bender H J,Manner R.Biomechanical simulation of the vitreous humor in the eye using an enhanced Chain Mail algorithm[M],Lecture Notes in Computer Science,Springer,1998,1496:679-687.
    [119]Haumann D.and Parent R.,The Behavioral Test-Bed:Obtaining Complex Behavior from Simple Rules,The Visual Computer,1988,4(6):332-347
    [120]Brown J.Real-Time simulation of Deformable Objects:Tools and Application[A].In:Proceedings of Computer Animation[C].2001.228-236
    [121]Deussen O,Kobbelt L,Tucke P.Using simulated annealing to obtain a good approximations of deformable bodies[C].In:Proc.Eurographics Workshop on Animation and Simulation,1995.
    [122]Provot X.Deformation Constraints in A Mass-spring Model to Describe Rigid Cloth Behavior[C].In:Proceeding of Graphics Interface' 95,Québec,Québec,1995:147-155.
    [123]Terzopoulos D,Waters K.Physically-based facial modeling,analysis,and animation[J].Journal of Visualization and Computer Animation,1990,1:73-80,
    [124]Lee Y,Terzopoulos D,Waters K.Realistic modeling for facial animation[C].In:Computer Graphics Proceedings,Annual Conference Series,Proceedings of SIGGRAPH 95,ACM SIGGRAPH,1995,45:55-62.
    [125]Mollemans W,,et al.Tetrahedral Mass Spring Model for Fast Soft Tissue Deformation[C].In:Proceedings of the International Symposium on Surgery Simulation and Soft-Tissue Modeling,2003
    [126]Kühnapfel,U.,(?)akmak,H.K.,Maa,H.Endoscopic surgery training using virtual reality and deformable tissue simulation.Computers and Graphics,2000,24(5):671-682.
    [127]Berkley J,Turkiyyah G,Berg D,Ganter M,Weghorst S,Real-Time Finite Element Modeling for Surgery Simulation:An Application to Virtual Suturing[C].IEEE Transactions On Visualization And Computer Graphics,Vol.10,No.3,May/June 2004
    [128]Bro-Nielsen M.Finite element modeling in surgery simulation[C].In:Proceedings of the IEEE,1998,86(3):490-503.
    [129]Cotin S,Delingette H,Ayache N.Real Time Volumetric Deformable Models for Surgery Simulation [M].Holme K,Kikinis R,editors,Vizualisation in Biomedical Computing,volume 1131 of Lecture Notes in Computer Science,Springer,1996:535-540.
    [130]Wu X,et al.Adaptive Nonlinear Finite Elements for deformable body simulation using dynamic progressive Meshes[J].Computer graphics forum,2001,20(3)
    [131]Bathe K J.In Finite Element Procedures in Engineering Analysis.Prentice Hall,1982
    [132]Lin M C,Manocha D,Cohen J,et al.Collision Detection:Algorithms and Applications.University of North Carolina,1996
    [133]石教英.虚拟现实基础及实用算法.北京:科学出版社,2002
    [134]Ganovelli F,Dingliana J,O' Sullivan C.Buckettree:improving collision detection between deformable objects[C]//Proc of Spring Conference on Computer Graphics SCCG'00,2000.
    [135]Terdiman P.Memory- optimized bounding- volume hierarchies[M].[S.1.]:[S.n],2001.
    [136]van den Bergen G.Efficient collision detection of complex de formable models using AABB trees[J].Journal of Graphics Tools:JGT,1997,2(4):1-14,
    [137]Louchet J.Provot X,et al.Evolutionary identification Of colth animationg models[A].Proceedings Of the Computer Animation and Simulation 95[C].1995,NewYork.Springer.Verlag,.44-54
    [138]GottschalkS,LinMC,ManochaD.OBBTree:A Hierarchical Structure for Rapid Interference Detection[A].Computer Graphics(SIGGRAPH '96)[C],New Orleans,LA,USA,1996,30:171-180
    [139]Kay,T.L,Kajiya,J.T.Raytraing complesscenes.Conpter Graphics,1986,20(4):269-278
    [140]魏迎梅.虚拟环境中碰撞检测问题的研究[D].国防科学技术学院,2000,10
    [141]周云波,闫清东,李宏才.虚拟环境中碰撞检测算法分析,2006,18(SUPPL1):103-107

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700