在体肝脏图像配准方法及应用研究
摘要
肝脏是人体重要的消化器官,肝脏疾病直接影响人的健康和生存。随着医学、计算机技术及生物医学工程技术的发展,医学影像学为临床诊断提供了多种模式的医学图像,这些图像在医学诊断和治疗中的作用显得非常重要。但是单一模式的图像往往不能提供医生所需要的足够的诊断信息。在实际临床应用中,往往需要将不同模式的医学图像有机地结合起来,得到更丰富的信息以便了解病变组织或器官的综合信息,从而做出准确的诊断或制订出合适的治疗方案,这就首先寻找一种(或一系列)空间变换,使两幅图像的对应点达到空间位置和解剖结构上的完全一致即进行图像配准。配准结果应使两幅图像上所有的解剖点,或至少是所有具有诊断意义的点都达到匹配。由于在体肝脏图像是患者在临床检查中获取的,其中包含了患者的个体特征信息,对其进行处理分析对临床诊断具有更加直接的意义。本文以福建省卫生教育联合攻关计划项目“数字化虚拟肝脏及手术计划系统”课题为依托,以肝脏图像配准为背景,系统研究了在体肝脏图像的配准方法,研究实现了肝脏CT多相期扫描图像配准方法,肝脏CT与MR图像配准方法,肝脏CT与DSA图像配准方法,以及肝脏管道系统分支变异与走行分析,为进一步的研究和应用奠定基础。
本文研究的创新点体现在以下五个方面:
1.提出了一种基于联合直方图的刚性配准算法,该算法分别对刚性配准过程中的四个关键步骤进行了改进,实现了肝脏CT多相期扫描图像刚性配准。分别对图像变换方法、图像插值方法、配准的相似函数以及配准的优化搜索方法是刚性配准过程中四个关键步骤,提出了不同的改进优化算法:1)提出一种图像刚性变换的快速坐标变换方法,大大提高了图像刚性变换的速度;2)提出一种改进的B样条插值方法,改进了B样条插值函数的缺陷,提高了图像插值的效果;3)提出了一种改进的基于联合直方图的计数函数作为配准的相似函数,大大提高了图像配准的速度;4)提出了一种混合优化算法,将PSO优化算法与Powell优化算法相结合,克服了Powell算法的局部最优的缺陷。实现肝脏CT多相期扫描图像刚性配准。
2.提出了一种具有自动设定标记点的薄板样条配准方法,该方法能够自动设定图像中的标记点,同时改进了薄板样条配准中存在的空值间隙的问题,实现了肝脏CT多相期扫描图像非刚性配准。
标记点的选取及插值函数的确定是非刚性配准方法中最关键的两步。本文采用薄板样条函数实现图像的非刚性配准过程,采用加权插值方法克服了存在的空值间隙的问题。此外,本文提出一种改进的SIFT算法,自动提取图像中的感兴趣点,有效的提高了配准的方便性以及配准的精度。最后利用图像的小波变换算法将配准后的肝脏CT多相期扫描图像进行图像融合。
3.针对肝脏DSA图像的特点,提出了一种肝脏血管配准方法,实现了肝脏CT图像与DSA图像的配准。
首先将CT图像进行投影处理,把DSA与CT图像变换到一个统一的坐标系中,将3D/2D的配准过程转化为2D/2D的配准过程。在对CT图像中肝脏管道进行血管分割、血管细化、提取血管骨骼线后,以肝脏内血管的结点为基准点,将CT内的血管切分为若干部分,在最大互信息配准算法的基础上,实现了肝脏CT图像与DSA图像的多模配准。。
4.提出一种由粗到精的混合配准算法,实现了肝脏CT图像与MR图像的多模配准。算法具有较好的收敛速度,且可以避免由于配准过程陷入局部极值而引起的错误。
图像配准通常在开始时使用粗略的快速算法,然后使用精确的慢速算法。力矩主轴配准法是根据图像的形状信息获得图像的质心、主轴,该方法可以获得图像的平移、旋转参数;基于Fourier-Mellin变换的图像配准算法是将图像变换到频域上后进行基于非特征的图像配准。采用以上两种配准方法后,图像自动快速大致配准,进一步采用最大互信息法对图像进行精确配准。
5.针对肝脏内部管道的特点,提出一种管道分析算法,实现了对肝脏管道系统分支变异以及管道走行情况分析判断。
肝脏内部的血管包括肝动脉,肝静脉以及门静脉系统,根据解剖学上的统计分析以及管道拓扑结构的特点,对肝脏内部的管道进行分析,判断它们类型,在计算管道直径、长度的基础上,对肝内的肝静脉、肝动脉以及门静脉的分支类型进行分析,判定其走行以及拓扑结构,有利于保护重要的血管结构,对于肝脏的手术计划有重要的意义。
总之,本文系统地研究了在体肝脏图像配准方法,主要包括肝脏CT多相期扫描图像的刚性配准方法,肝脏CT多相期扫描图像的非刚性配准方法,肝脏CT与MR图像配准方法,肝脏CT与DSA图像配准方法,以及肝脏管道系统分支变异与走行的分析,为数字化虚拟肝脏及手术计划系统的建立奠定了算法和程序基础。
Liver is one of the most important organs in human.With the development of the medicine and computer technique,more and more modals medical images have emerged.Modern medical research usually requires integrated analysis of multiple images to get more information.A fundamental problem in medical image integrated analysis is that the images should be perfectly aligned,one essential aspect thereof is image registration,i.e.,recovering the geometric relationship between corresponding points in multiple images of the same scene.Medical image registration is an important technique in the field of medical image processing,and becoming more and more important for clinical diagnosis and treatment.The living liver images are obtained from the clinical medical examination,which contain the individual characteristic information.Registration of the living liver images will help for clinical diagnosis directly.Based on the registration methods,this work was supported by the National Nature Science Foundation of China(30770561 and 60701022)and the Science Research Foundation of ministry of Health & United Fujian Provincial Health and Education Project for Tacking the Key Research,P.R.China(WKJ2005-2-001). This thesis covered several registration methods of living liver images such as rigid registration of different phases of contrast enhanced liver CT data,nonrigid registration of different phases of contrast enhanced liver CT data,registration of MR and CT images,registration of DSA and CT images and the analysis of the types of branch variation of liver vessels.
The main contents and contributions of this thesis are as follows:
1)A rigid registration algorithm based on joint distribution histogram was proposed for different phases of contrast enhanced liver CT data.
The four key steps of the rigid algorithm have been improved in this algorithm.1) A fast image transformation method was proposed,which speed up the transformation procedure 2)An improved measure function based on joint distribution histogram was proposed,which speed up the registration procedure without losing the accuracy;3)A hybrid interpolation algorithm based on B-spline transform was proposed,which improved the interpolation results;4)A hybrid optimization algorithm based on PSO and Powell was proposed,which had higher convergence speed and settling local extremum preferably.After rigid registration the images of different phases of contrast enhanced liver CT were aligned approximately.
2)A nonrigid registration algorithm based on thin-plate splines was proposed which locate the control points automatically.
The control points and the interpolation function are the key factors of the nonrigid algorithm.This algorithm adopted weighted interpolation based on thin-plane splines interpolation so that there were no“blank value points”in the images.Because the images were aligned approximately after rigid registration,the control points could be located by an improved SIFT algorithm.After nonrigid registration the images of different phases of contrast enhanced liver CT were aligned precisely.Finally,the post-registration images were fused by a wavelets-based scheme and the different information was merged into a new image.
3)An algorithm based on maximum mutual information was proposed for the registration of CT and DSA images.
Firstly,projection transformation was applied to CT images so that 2D DSA information and 3D CT information was in the same coordinate system.Then after segment blood vessels and extracting skeleton line of blood vessels,the blood vessels were separated into several parts by some blood vessel nodes in the liver.Finally based on the maximum mutual information registration algorithm,the multimode registration of CT and DSA liver images was achieved.
4)A two-step registration algorithm was proposed for the registration of CT and MRI images.
Firstly a method based on principle axes and Fourier-Mellin transform was adopted for the coarse registration.Because there are clear contours in CT and MR image,we presented a registration method based on principal axes.Through matching the centroid and principal axes of image,the desired parameters for translation and rotation transform were obtained.After that the scaling parameter was obtained by Fourier-Mellin transform.Secondly,maximum mutual information algorithm was applied to achieve precise registration.Experiments show that the two-step algorithm could avoid erroneous results because of the local extremum.
5)An algorithm was proposed to analyze the route and topology configuration of the liver vessels.
After registration the types of branch variation of liver vessels were determined, while the diameter and length of vessels were calculated.This algorithm helped the liver surgery planning greatly.
In summary,this thesis covered on several registration methods of living liver images including rigid registration of different phases of contrast enhanced liver CT data,nonrigid registration of different phases of contrast enhanced liver CT data, registration of MR and CT images,registration of DSA and CT images and the analysis of the types of branch variation of liver vessels.Several algorithms were proposed in this thesis for solving some problems for liver image registration. Although there is still much work to do,this thesis may help a lot for establishing a real applied digital virtual liver and liver surgery planning system.
本文研究的创新点体现在以下五个方面:
1.提出了一种基于联合直方图的刚性配准算法,该算法分别对刚性配准过程中的四个关键步骤进行了改进,实现了肝脏CT多相期扫描图像刚性配准。分别对图像变换方法、图像插值方法、配准的相似函数以及配准的优化搜索方法是刚性配准过程中四个关键步骤,提出了不同的改进优化算法:1)提出一种图像刚性变换的快速坐标变换方法,大大提高了图像刚性变换的速度;2)提出一种改进的B样条插值方法,改进了B样条插值函数的缺陷,提高了图像插值的效果;3)提出了一种改进的基于联合直方图的计数函数作为配准的相似函数,大大提高了图像配准的速度;4)提出了一种混合优化算法,将PSO优化算法与Powell优化算法相结合,克服了Powell算法的局部最优的缺陷。实现肝脏CT多相期扫描图像刚性配准。
2.提出了一种具有自动设定标记点的薄板样条配准方法,该方法能够自动设定图像中的标记点,同时改进了薄板样条配准中存在的空值间隙的问题,实现了肝脏CT多相期扫描图像非刚性配准。
标记点的选取及插值函数的确定是非刚性配准方法中最关键的两步。本文采用薄板样条函数实现图像的非刚性配准过程,采用加权插值方法克服了存在的空值间隙的问题。此外,本文提出一种改进的SIFT算法,自动提取图像中的感兴趣点,有效的提高了配准的方便性以及配准的精度。最后利用图像的小波变换算法将配准后的肝脏CT多相期扫描图像进行图像融合。
3.针对肝脏DSA图像的特点,提出了一种肝脏血管配准方法,实现了肝脏CT图像与DSA图像的配准。
首先将CT图像进行投影处理,把DSA与CT图像变换到一个统一的坐标系中,将3D/2D的配准过程转化为2D/2D的配准过程。在对CT图像中肝脏管道进行血管分割、血管细化、提取血管骨骼线后,以肝脏内血管的结点为基准点,将CT内的血管切分为若干部分,在最大互信息配准算法的基础上,实现了肝脏CT图像与DSA图像的多模配准。。
4.提出一种由粗到精的混合配准算法,实现了肝脏CT图像与MR图像的多模配准。算法具有较好的收敛速度,且可以避免由于配准过程陷入局部极值而引起的错误。
图像配准通常在开始时使用粗略的快速算法,然后使用精确的慢速算法。力矩主轴配准法是根据图像的形状信息获得图像的质心、主轴,该方法可以获得图像的平移、旋转参数;基于Fourier-Mellin变换的图像配准算法是将图像变换到频域上后进行基于非特征的图像配准。采用以上两种配准方法后,图像自动快速大致配准,进一步采用最大互信息法对图像进行精确配准。
5.针对肝脏内部管道的特点,提出一种管道分析算法,实现了对肝脏管道系统分支变异以及管道走行情况分析判断。
肝脏内部的血管包括肝动脉,肝静脉以及门静脉系统,根据解剖学上的统计分析以及管道拓扑结构的特点,对肝脏内部的管道进行分析,判断它们类型,在计算管道直径、长度的基础上,对肝内的肝静脉、肝动脉以及门静脉的分支类型进行分析,判定其走行以及拓扑结构,有利于保护重要的血管结构,对于肝脏的手术计划有重要的意义。
总之,本文系统地研究了在体肝脏图像配准方法,主要包括肝脏CT多相期扫描图像的刚性配准方法,肝脏CT多相期扫描图像的非刚性配准方法,肝脏CT与MR图像配准方法,肝脏CT与DSA图像配准方法,以及肝脏管道系统分支变异与走行的分析,为数字化虚拟肝脏及手术计划系统的建立奠定了算法和程序基础。
Liver is one of the most important organs in human.With the development of the medicine and computer technique,more and more modals medical images have emerged.Modern medical research usually requires integrated analysis of multiple images to get more information.A fundamental problem in medical image integrated analysis is that the images should be perfectly aligned,one essential aspect thereof is image registration,i.e.,recovering the geometric relationship between corresponding points in multiple images of the same scene.Medical image registration is an important technique in the field of medical image processing,and becoming more and more important for clinical diagnosis and treatment.The living liver images are obtained from the clinical medical examination,which contain the individual characteristic information.Registration of the living liver images will help for clinical diagnosis directly.Based on the registration methods,this work was supported by the National Nature Science Foundation of China(30770561 and 60701022)and the Science Research Foundation of ministry of Health & United Fujian Provincial Health and Education Project for Tacking the Key Research,P.R.China(WKJ2005-2-001). This thesis covered several registration methods of living liver images such as rigid registration of different phases of contrast enhanced liver CT data,nonrigid registration of different phases of contrast enhanced liver CT data,registration of MR and CT images,registration of DSA and CT images and the analysis of the types of branch variation of liver vessels.
The main contents and contributions of this thesis are as follows:
1)A rigid registration algorithm based on joint distribution histogram was proposed for different phases of contrast enhanced liver CT data.
The four key steps of the rigid algorithm have been improved in this algorithm.1) A fast image transformation method was proposed,which speed up the transformation procedure 2)An improved measure function based on joint distribution histogram was proposed,which speed up the registration procedure without losing the accuracy;3)A hybrid interpolation algorithm based on B-spline transform was proposed,which improved the interpolation results;4)A hybrid optimization algorithm based on PSO and Powell was proposed,which had higher convergence speed and settling local extremum preferably.After rigid registration the images of different phases of contrast enhanced liver CT were aligned approximately.
2)A nonrigid registration algorithm based on thin-plate splines was proposed which locate the control points automatically.
The control points and the interpolation function are the key factors of the nonrigid algorithm.This algorithm adopted weighted interpolation based on thin-plane splines interpolation so that there were no“blank value points”in the images.Because the images were aligned approximately after rigid registration,the control points could be located by an improved SIFT algorithm.After nonrigid registration the images of different phases of contrast enhanced liver CT were aligned precisely.Finally,the post-registration images were fused by a wavelets-based scheme and the different information was merged into a new image.
3)An algorithm based on maximum mutual information was proposed for the registration of CT and DSA images.
Firstly,projection transformation was applied to CT images so that 2D DSA information and 3D CT information was in the same coordinate system.Then after segment blood vessels and extracting skeleton line of blood vessels,the blood vessels were separated into several parts by some blood vessel nodes in the liver.Finally based on the maximum mutual information registration algorithm,the multimode registration of CT and DSA liver images was achieved.
4)A two-step registration algorithm was proposed for the registration of CT and MRI images.
Firstly a method based on principle axes and Fourier-Mellin transform was adopted for the coarse registration.Because there are clear contours in CT and MR image,we presented a registration method based on principal axes.Through matching the centroid and principal axes of image,the desired parameters for translation and rotation transform were obtained.After that the scaling parameter was obtained by Fourier-Mellin transform.Secondly,maximum mutual information algorithm was applied to achieve precise registration.Experiments show that the two-step algorithm could avoid erroneous results because of the local extremum.
5)An algorithm was proposed to analyze the route and topology configuration of the liver vessels.
After registration the types of branch variation of liver vessels were determined, while the diameter and length of vessels were calculated.This algorithm helped the liver surgery planning greatly.
In summary,this thesis covered on several registration methods of living liver images including rigid registration of different phases of contrast enhanced liver CT data,nonrigid registration of different phases of contrast enhanced liver CT data, registration of MR and CT images,registration of DSA and CT images and the analysis of the types of branch variation of liver vessels.Several algorithms were proposed in this thesis for solving some problems for liver image registration. Although there is still much work to do,this thesis may help a lot for establishing a real applied digital virtual liver and liver surgery planning system.
引文
[1]范毓东,周代全,王成波等.肝脏外科中的虚拟手术方案设计[J].消化外科2005,(5):336-340.
[2]方驰华,周五一,黄立伟等.虚拟中国人女性一号肝脏图像三维重建和虚拟手术的切割[J].中华外科杂志 2005,(11):748-752.
[3]方驰华.肝脏管道系统数字化及虚拟肝脏的研究[D].第一军医大学临床解剖学博士学位论文:2005.
[4]李恺,谭立文,刘正津,等.数字化人体肝脏可视化与虚拟肝段切除[J].医用生物力学2006(3):187-191.
[5]李恺.肝脏管道系统可视化研究[D].第三军医大学人体解剖与组织胚胎学硕士学位论文.
[6]陈官发生.基于PHANTOM设备的肝脏虚拟手术的研究[D].华南师范大学计算机软件与理论硕士学位论文2006.
[7]Yamanaka J,Saito S,Fujimoto J.Impact of preoperative planning using virtual segmental volumetry on liver resection for hepatocellular carcinoma[J].World J Surg.2007Jun.31(6):1249-55.
[8]Radtke A,Bockhorn M,Sehroeder T,Lang H,Paul A,Nadalin S,Saner F,Schenk A,Broelsch CE,Malago M,Computer-assisted planning in living donor liver operation[J].ZENTRALBLATT FUR CHIRURGIE.FEB 2006,131(1):69-74.
[9]Lang H,Radtke A,Hindennach M,Schroeder T,Bourquain H,Schenk A,Oldhafer K J,Prause G,Peitgen HO,Broelsch CE.Virtual hepatic surgery-computer-assisted operation planning on the 3-dimensional reconstructed liver[J].Z Gastroenterol.2007Sep;45(9):965-70.Epub 2007 Sep 4.
[10]Radtke A,Schroeder T,Molmenti EP,Sotiropoulos GC,Schenk A,Paul A,Frilling A,Lang H,Nadalin S,Malago M.Anatomical and physiological comparison of liver volumes among three frequent types of parenchyma transection in live donor liver transplantation[J]..HEPATO-GASTROENTEROLOGY 52(62):333-338 MAR-APR 2005.
[11]Reitinger,B.;Bornik,A.;Beichel,R.;Werkgartner,G.;Sorantin,E.Tools for augmented-reality-based liver resection planning.[J].Proceedings of the SPIE-The International Society for Optical Engineering Volume:5367 Issue:1 Pages:88-99.
[12]Glombitza G,Lamade W,Demiris AM,Gopfert MR,Mayer A,Bahner ML,Meinzer HP,Richter G,Lehnert T,Herfarth C.Virtual planning of liver resections:image processing,visualization and volumetric evaluation[J].International Journal of Medical Information.1999,53:225-237.
[13]Bourquain H,Schenk A,Link F,Preim B,Prause G,Peitgen H.HepaVision2—A software assistant for preoperative planning in living-related liver transplantation and oncologic liver surgery[J].Computer Assisted Radiology and Surgery,2002:341-346.
[14]http://www-iri.upc.es/.
[15]J.O.Neumann et al.Branching Patterns and Drainage Territories of the Middle Hepatic Vein in Computer-Simulated Right Living-Donor Hepatectomies[J].American Journal of Transplantation,2006,(6):1407-1415.
[16]Hogemann D,Stamm G,et al.Individual planning of liver surgery using a virtual model of the liver and associated structures[J].Radiologe,2000,40(3):267-273.
[17]Kamel IR,Kruskal JB,Raptopoulos V.Imaging for right lobe living donor liver transplantation[J].Seminars in Liver Disease,2001,21(2):271-282.
[18]Saito S,Yamanaka J,et al.A novel 3D hepatectomy simulation based on liver circulation:Application to liver resection and transplantation[J].Hepatology,2005,41(6):1297-1304.
[19]Radtke A,Bockhorn M,et al.Computer-assisted planning in living donor liver operation[J].Zentralblatt Fur Chirurgie,2006,131(1):69-74.
[20]Radtke A,Schroeder T,Molmenti EP,et al.Anatomical and physiological comparison of liver volumes among three frequent types of parenchyma transection in live donor liver transplantation[J].Hepato-Gastroenterology,2005,52(62):333-338.
[21]罗述谦.医学图像配准技术[J].国外医学生物医学工程分册,1999,22(1):1-7.
[22]ANTOINE MAINTZ J B,MAX A.Viergever.A survey of medical image registration[J].Medical Image Analysis,1998,2(1):1-36.
[23]俞亚青,田学隆,闫春红.医学图像配准方法分类及现状[J].重庆大学学报 2003,26(8),114-118
[24]REN HAI-PING,HU YANG,WU WEN-KAI,et al.Multi-resolution three-dimensional multi-modality image registration by maximization of mutual information.Proceedings of the 23rd Annual International Conference of the IEEE[C].Istanbul,Turkey:The Institute of Electrical and Electronics Engineers,Inc.,2001,3:2411-2413.
[25]HE RENJIE,PONNADA A.NARAYANA.Global optimization of mutual information:application to three dimensional retrospective registration of magnetic resonance images[J].Computerized Medical Imaging and Graphics,2002,26(4):277-292.
[26]PORTER B C,RUBENS D J,STRANG J G,et al.Three dimensional registration and fusion of ultrasound and MRI using major vessels as fiducial markers[J].IEEE Transactions on Medical Imaging,2001,20(4):354-359.
[27]A RANGARAJAN,CHUI HAILI,DUNCAN JAMES S.Rigid point feature registration using mutual information[J].Medical Image Analysis,1999,3(4):425-440.
[28]周永新,罗述谦.基于形状特征点最大互信息的医学图象配准[J].计算机辅助设计与图形学学报,2002,14(7):654-658.
[29]周鹏,谭勇,徐守时.基于角点检测图像配准的一种新算法[J].中国科学技术大学学报,2002,32(4):455-461.
[30]DING L,GOSHTASBY A,SATTER M.Volume image registration by template matching[J].Image and Vision Computing,2001,19(12):821-832.
[31]B LOW H,DOOLEY L,WERMSER D.Application of principal axes for registration of NMR image sequences[J].Pattern Recognition Letters,2000,21(4):329-336.
[32]吴锋,钱宗才,杭洽时,等.基于轮廓的力矩主轴法在医学图像配准中的应用[J].第四军医大学学报,2001,22(6):567-569.
[33]葛云,舒华忠,罗立民.基于Legendre正交矩的配准方法及其在二值图像配准中的应用[J].电子学报,2001,29(1):54-57.
[34]WACHOWIAK M P,SMOLIKOVA R,TOURASSI GD,et al.Generalized mutual information similarity metrics for multimodal biomedical image registration[A].Engineering in Medicine and Biology.24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society[C].Houston,Texas,USA:The Institute of Electrical and Electronics Engineers,Inc.,2002,2:1005-1006.
[35]LUO SHUQIAN,LI XIANG.Implementation of mutual information based multi-modality medical image registration[A].Engineering in Medicine and Biology Society.Proceedings of the 22nd Annual International Conference of the IEEE[C].Navy Pier Convention Center Chicago,Illinois,USA:The Institute of Electrical and Electronics Engineers,inc,2000,2:1447-1450.
[36]JOSIEN P W,PLUIM J B.Anitoine Maintz,Max A.Viergever.Interpolation artifacts in mutual information based image registration[J].Computer Vision and Image Understanding,2000,77(22):211-232.
[37]ROHR K,STIEHL H S.,Sprengel R.,et al.Landmark based Elastic registration using approximating thin-plate splines[J].IEEE Transactions On Medical Imaging,2001,20(6):526-533.
[38]THOMAS M.LEHMANN,CLAUDIA GONNER,KLAUS SPITZER.Survey:Interpolation methods in medical images processing[J].IEEE Transactions On Medical Imaging,1999,18(11):1049-1072.
[39]PLUIM J P W.Information and gradient information[J].IEEE Transactions on Medical Imaging,2000,19(8):809-814.
[40]杨虎,马斌荣,任海萍,等.基于互信息的人脑图像配准研究[J].中国医学物理学杂志,2001,18(2):69-72.
[41]赵富强,于红玉,马斌荣,等.基于图像特征的CT-MR图像配准[J].北京生物医学工程,2000,19(4):206-211.
[42]罗纲,罗斌.图象特征点集配准的加权相关迭代算法[J].中国图象图形学报,2000,2(9):755-758.
[43]SHUN'ICHI KANEKO,YUTAKA SATOH,SATORU I-GARASHI.Using selective correlation coefficient for robust image registration[J].Pattern Recognition,2003,36(5):1165-1173.
[44]ROCHEA,MALANDAING,PENNECX,etal.Multi-modal image registration by maximization of the correlatiratio(TechnicalReport3378)[R].France:INRIA,1999.
[45]QIN BIN-JIE,ZHUANG TIAN-GE.Choice of similarity measure in voxel intensity based 3D multi-modal medical image registration[J].Space Medicine & Medical Engineering,2002,15(4):241-245.
[46]刘文亚,蒋黛蒂,洪润环,等.螺旋CT多期增强扫描诊断小肝癌的价值[J].中国医学影像 学杂志,2002,10(1):8-10.
[47]王爽,周纯武,赵心明.多层螺旋CT在肝脏肿瘤诊断中的应用[J].临床放射学杂志,2003,3:248-250.
[48]Xiaoyang Huang,Boliang Wang and Shaohui Huang et al.Registration of different phases of contrast-enhanced liver CT data[J].Peoceedings of the 1st International Conference on Bioinformatics and BiomedicalEngineering.(2)2007,pp786-789.
[49]孙家广.计算机图形学(第三版)[M].北京:清华大学出版社,2000.
[50]高智勇,徐凯,刘丽荣,等.医学图像配准中快速坐标变换方法[J].上海:中国医疗器械杂志,2003,27(2):92-94.
[51]黄晓阳,王博亮,吴志坚,.快速坐标变换方法及其在图像配准中的应用[J].中国数字医学,2009,4(1)19-21.
[52]吕维雪段会龙.三维医学图像可视化及其应用[M].杭州:浙江大学出版社,2001.
[53]黄晓阳.人眼组织切片图像的配准、三维重建的研究与实现[D].厦门大学硕士论文,2003.
[54]Antoine Maintz J.B.,and Viergever M.A..Mutual-information-based registration of medical images:a survey[J].IEEE Transactions On Medical Imaging,22(2003),pp.986-1004.
[55]Frederik Maes,Andr e Collignon,Dirk Vandermeulen,Guy Marchal,and Paul Suetens,.Multimodality Image Registration by Maximization of Mutual Information[J].IEEE Transactions On Medical Imaging,16(1997),pp.187-198.
[56]C.Studholme,D.L.G.Hill and D.J.Hawkes,.An overlap invariant entropy measure of 3D medical image alignment[J].Pattern Recognition,32(1999),pp.71-86.
[57]Thomas M.Lehmann,Claudia G(?)onner,and Klaus Spitzer,Survey:Interpolation Methods in Medical Image Processing[J].IEEE TRANSACTIONS ON MEDICAL IMAGING,1999,18(11):1049-1075.
[58]J.A.Parker,R.V.Kenyon,and D.E.Troxel.Comparison of interpolating methods for image resampling[J].IEEE Trans.Med.Imag.,1983,2,:31-39.
[59]M.Unser,A.Aldroubi and M.Eden.Fast B-spline transform for continuous image representation and interpolation[J].IEEE Trans.Pattern Analysis And Machine Intelligence,1991,13:277-285.
[60]刘洪臣,杨旭强,冯勇.亚像元成像系统B样条插值方法[J].光电工程, 2006.2,33(2):90-93,126.
[61]任海萍,吴文凯,杨虎,陈盛祖.医学图像插值方法对比[J].北京生物医学工程,2002.3,21(1):19-23.
[62]席少霖,赵凤治.最优化计算方法[M].上海:上海科学计算出版社,1983
[63]陈开周.最优化计算方法[M].陕西:西北电讯工程学院出版社,1985.
[64]刘哲星,江贵平,张煜,等.基于互信息量图像配准中目标函数局部极值的成因分析与克服.中国生物医学工程学报,2003,12(6),503-507.
[65]Kennedy.J.Eberhart R.Particle Swarm Optimization[C].Australia Perth:IEEE Int Conf on Neural Networks,1995.1942-1945.
[66]Eberhart R,Kennedy J.A new optimizer using particle swarm theory[C].Japan Nagoya:Proc of the Sixth International Symposium on Micro Machine and Human Science,1995.39-42.
[67]Shi Y,Eberhart R.A Modified Particle Swarm Optimizer[C].IEEE World Congress on Computational Intelligence,1998.69.
[68]曾建潮,介婧,崔志华著.微粒群算法[M].北京:科学出版社.2004.
[69]冯林,严亮,黄德根等.PSO和Powell混合算法在医学图像配准中的应用研究[J].北京生物医学工程.2005,24(1).8-12.
[70]http://www.itk.org/.
[71]F.L.Bookstein.Prineipal Warps:Thin-plate splines and the decomposition of deformations[J].IEEE Trans.Pattern Analysis and Machine Intelligence,1989,11:567-585.
[72]M.Moshfeghi,S.Ranganath,and K.Nawyn.Three-dirnensional elastic matehing of volumes[J].IEEE Trans.Image Proeessing,1994,3(2):128-138.
[73]C.Davatzikos.Spatial normalization of 3d brain images using deformable models[J].Journal of Computer Assisted Tomography,1996.
[74]G.E.Christensen,R.D.Rabbitt and M.I.Miller.3D brain mapping using a deformable neuroanatomy[J].Physics in Medicine and Biology,1994,39:609-618.
[75]张煜.MRI-Man可视化模型建立中弹性配准新方法及显示方法研究[D].第一军医大学博士学位论文,2003.
[76]刘哲星.医学图像回溯性配准研究[D].第一军医大学博士学位论文,2002.
[77]戚正君.非刚性图像配准算法研究与应用[D].大连理工大学硕士论文,2004.
[78]罗述谦、周果宏.医学图像处理与分析[M].北京:科学出版社,2003.
[79]Nur Arad,Nira Dyn,Daniel Reisfeld et al.Image warping by radial basis functions:application to facial expressions[J].CVGIP.Graphical models and image processing,1994,56(2),161-172.
[80]K.Rohr.Loealization properties of direet corner detectors[J].Jurnal of Mathematical Imaging and Vision,1994,4:139-150.
[81]L.Kitehen and A.Rosenfeld.Gray level corner detection[J].Pattern Recognition Letters,1982,vol.1,95-102.
[82]K.Brunnstrom,T.Lindeberg,J.O.Eklundh.Active detection and classification of junctions[J].Proe.2nd European Conf.Computer Vision,St.Margherita,Italy,1992,LNCS 588,701-709.
[83]O.A.Zuniga,R.Haraliek.Corner detection using the facet model[J].Proe.IEEE Conf.Computer Vision Pattern Recognition,1983,30-37.
[84]J.A.Noble.Finding corners[J].Image Comput.,1988,6(2),121-128.
[85]D.G.Lowe,Distinctive image features from scale-invariant Keypoints,[J].International Journal of Computer Vision 60(2004),no.2,pp.91-110.
[86]Lindeberg T.Scale space theory,A basic tool for analyzing structures at different scales,[J].Journal of Applied Statistics,1994,21(2):pp.224-270.
[87]那彦、焦李成.基于多分辨分析理论的图像融合方法[M].西安:西安电子科技大学出版社,2007.
[88]H.Li,B.S.Manjunath and S.K.Mitra.Multisensor image fusionusing the wavelet transform,[J].Graphical Models Image Process.57(3)(1995),pp.235-245.
[89]Huang Xiaoyang,Wang Boliang,Cheng Ming et al.Image registration and data fusion for different phases of contrast enhanced liver CT data,[Z].Proceedings of the 2nd International Conference on Bioinformatics and Biomedical Engineering,2008,pp.2682-2685.
[90]余建明.医学影像技术学[M].科学出版社,2004,(247-249).
[91]刘潇潇.数字减影技术中的图像配准[D].华中科技大学硕士论文,2005.
[92]孙晓鹏.数字剪影血管造影(DSA)图象处理系统研究[D].北京工业大学硕士论文,2003.
[93]李雯.DSA/CT图像的无框架配准与融合技术的应用研究[J].上海交通大学,2004.
[94]Helen Hong,Ho Lee,Yeong Gil Shin,Yeol Hun Seong.Three-Dimensional Brain CT-DSA Using Rigid Registration and Bone Masking for Early Diagnosis and Treatment Planning[J].D.-K.Baik(Ed.):AsiaSim 2004,LNAI 3398,pp.167.176,2005.
[95]Julien Jomier,Elizabeth Bullitt,Mark Van Horn,Chetna Pathak,and Stephen R.Aylward.3D/2D Model-to-Image Registration Applied to TIPS Surgery.R.Larsen,M.Nielsen,and J.Sporring(Eds.):MICCAI2006,LNCS 4191,pp.662-669,2006.
[96]T.Rohlfing,C.R.Maurer Jr,J.Beierb.Reduction of motion artifacts in three-dimensional CT-DSA using constrained adaptive multilevel free-form registration[J].International Congress Series 1230(2001)365-371.
[97]梁玮.2D-3D医学图像配准研究[D].东南大学硕士论文.2004.
[98]陆忞,鲍旭东,罗立民,李鉴轶.基于改进SLNC的2D-3D医学图像配准[J].生物医学工程研究(2007)02-0170-04:170-173.
[99]梁玮,鲍旭东,罗立民.基于互信息的2D-3D医学图像配准[J].生物医学工程研究.2004,01:14-16.
[100]Dirk Selle,Bernhard Preim,Andrea Schenk,et al.Analysis of vasculature for liver surgical planning[J].IEEE transactions on medical imaging(S0278-0062),2002,21(11):1344-1357.
[101]Sethian,J.A.Fast marching methods[J].SIAM Review,1999,41(2):199-235.
[102]苏金明,王永利.Matlab图形图像[M].电子工业出版社,2005:117-119.
[103]王家文,李仰军.matlab7.0图形图像处理[M].国防工业出版社,2006:163-164.
[104]和青芳.计算机图形学原理及算法教程(Visual C++版)[M].清华大学出版社,2006.
[105]Louisa Lam,Seong-Whan Lee,and Ching Y.Suen.Thinning methodologies—a comprehensive survey[J].IEEE transactions on pattern analysis and machine intelligence (SO 162-8828),1992,14(9):869-883.
[106]Ta-Chin Lee and Rangasami L.Kashyap.Building skeleton models via 3-D medial surface/axis thinning algorithm[J].Graph.Models Image Processing(S1049-9552),1994,56(6):462-478.
[107]A RAN GARAJAN,CHU I HAIL I,DUNCAN JAMES S.Rigid Point Feature Registration Using Mutual Information[J].Medical Image Analysis,1999,3(4):425-440.
[108]张煜.一种用于医学图象配准的图象外边界的提取方法[J].北京生物医学工程,2000,VOL,19,No.4,217-220.
[109]Rohr K.Stiehl H S.Sprengel R.Point-based elastic registration of medical image data using approximating thin-plate splines[A].In:Proceedings Fourth International Conference on Visualization in Biomedical Computer(VBC'96)[C],Berlin,Germany:Springer Verlag,1996,1131:297-306.
[110]俎栋林,余立锋,王卫东,包尚联,等.基于轮廓特征的多模态医学图像的配准[J].系统工程与电子技术,2000,22(7):61-64.
[111]Van den Elson PA,Pol EJD,Viergever MA.Medical image matching-a review with classification.IEEE Engineering in Medicine and Biology,1993,12(4):26-39.
[112]沈晋慧,马斌荣,杨虎,于红玉.利用边缘和表面特征实现脑图像的自动配准[J].中国医学物理学杂志;2002年01期;14-18.
[113]Besl PJ,McKay NM.A method for registration of 3D shapes[J].IEEE Trans.Pattern Anal.and Machine Intell.,1989,14:567-585.
[114]Woods RP,Cherry SR,Mazziotta JC.Rapid aytomaited_algorilhm for aligning and reslicing PET images[J].Journal of Computer Assisted Tomography,992,16(4):620-633.
[115]Woods RP,Mazziotta JC,Cherry SR.MRI-PET registration with automated algorithm[J].Journal of Computer Assisted Tomography,1993,17(4):536-546.
[116]Van den Elson PA,Maintz JBA,Pole JD,et al.Automatic registration of CT and MR brain image using correlation of geometric features[J].IEEE Transactions on Medical Imaging,1995,14(2):384-396.
[117]Van den Elson PA,Pol EJD,Sumanaweera TS,et al.Grey value correlation techniques for automatic matching of CT and MR brain and spine images[J].In:Proceeding of Visualization in Biomedical Computing 1994,SPIE,1994,2359:227-237.
[118]冯林,张名举,贺明峰等.用分层互信息和薄板样条实现医学图像弹性自动配准[J].计算机辅助设计与图形学学报,2005,17(7):1492-1496.
[119]Xiaoyang Huang,Boliang Wang,Ruhuan Liu.CT-MR Image Registration in Liver Treatment by Maximization of Mutual Information,[J].Proceedings of 2008 IEEE International Symposium on IT in Medicine & Education,2008,Xiamen,China,pp.715-718.
[120]秦斌杰,庄天戈.利用相关比相似性测度多分辨率配准MR和CT医学图像的方法[J].中国生物医学工程学报,2003,22(1):1-5.
[121]Viola P A.Alignment by maximization of mutual information[D].Massachusetts Institute of Technology-Artificial Intelligence Laboratory,1995.
[122]J.B.A.Maintz and M.A.Viergever.A survey of medical image registration[J].Medieal Image Analysis,1998,2(1):1-36.
[123]王凯.多模态医学图像配准研究[D].中南大学;2008.
[124]冯林,严亮,黄德根,等.PSO和Powell混合算法在医学图像配准中的应用研究[J].北京生物医学工程 2005,24(01):8-12.
[125]Alpert NM,Bradshaw D,Kennedy D et al.The principal axes transtormation:A method for image registration[J].J nuclmed,1990,31:1717-1722.
[126]周建方.材料力学[M].北京:机械工业出版社.2002.
[127]陈瑛,蒋志新,顾顺德.利用矩运算完成图象的配准[J].上海第二医科大学学报,1999,3:277-279.
[128]Q.Chen,M.Defrise,F.Deconinck.Symmetric phase-only matched filtering of Fourier Mellin transform for image registration and recognition[J].IEEE Transactions on Pattern Analysis and Machine Intellgience.1994,16:1156-1168.
[129]B.S.Reddy,B.N.Chatterji,.An FFT-based technique for translation,rotation,and scale-invariant image registration[J].IEEE Trans.on Image Processing,1996,5(8),1266-1271.
[130]Brown L.G..A survey of image registration techniques[J].ACM Computing Surveys,1992,24(4):325-376.
[131]Zitov B..Flusser J..Image registration methods:A survey[J].Imaging and Vision Computing,2003,21(11):977-1000.
[132]Xiaoyang Huang,Boliang Wang,Ruhuan Liu.CT-MR Image Registration in Liver Treatment by Maximization of Mutual Information[J].Proceedings of 2008 IEEE International Symposium on IT in Medicine & Education,715-718.
[133]朱明德,方驰华.肝脏管道系统变异在活体肝移植中的意义[J].肝胆外科杂志.2005,13(6):473-475.
[134]Fasel JH,Gingins P,Kalra P,et al.Liver of the “visible man”[J].Clin Anat,1997, 10(6):389-393.
[135]丁家明,李惠君,刘群辉.肝静脉的应用解剖学研究[J].肝胆外科杂志.2003,11(4):308-310.
[136]冯新富,陈晓理.变异肝静脉的临床意义[J].华西医学.2003,18(2):270-271.
[137]Soyer P,Bluemke D A,Choti M A,et al.Variation in the intrahepatic portions of the hepatic and portal veins:Findings on helical CT scans during arterial portography[J].AMJ Roentgenol.1995,164(1):103-108.
[138]丁家明,李惠君.肝动脉的应用解剖[J].解剖科学进展.2000,6(4):350-351.
[139]Lee S S,Kim J K,Byun J H,et al.Hepatic arteries in potential donors for living related liver transplantation:Evaluation with multi2detector row CT angiography[J].Radiology,2003,227(2):391-399.
[140]陈孝平,陈汉.肝胆外科学[M].北京:人民卫生出版社2005.
[141]许敏,吴在德.肝脏外科解剖及肝段体积的测定[J].中国普通外科杂志,1996,5(1):1-2.
[142]Deshpande RR,Heaton ND,Rela M.Surgical anatomy of segmental liver transplantation [J].B r J Surg,2002,89(9):1078-1088.
[143]金武男,杨香,车成日.门静脉的解剖与变异[J].中国临床解剖学杂志.2006,24(2):157-159.
[2]方驰华,周五一,黄立伟等.虚拟中国人女性一号肝脏图像三维重建和虚拟手术的切割[J].中华外科杂志 2005,(11):748-752.
[3]方驰华.肝脏管道系统数字化及虚拟肝脏的研究[D].第一军医大学临床解剖学博士学位论文:2005.
[4]李恺,谭立文,刘正津,等.数字化人体肝脏可视化与虚拟肝段切除[J].医用生物力学2006(3):187-191.
[5]李恺.肝脏管道系统可视化研究[D].第三军医大学人体解剖与组织胚胎学硕士学位论文.
[6]陈官发生.基于PHANTOM设备的肝脏虚拟手术的研究[D].华南师范大学计算机软件与理论硕士学位论文2006.
[7]Yamanaka J,Saito S,Fujimoto J.Impact of preoperative planning using virtual segmental volumetry on liver resection for hepatocellular carcinoma[J].World J Surg.2007Jun.31(6):1249-55.
[8]Radtke A,Bockhorn M,Sehroeder T,Lang H,Paul A,Nadalin S,Saner F,Schenk A,Broelsch CE,Malago M,Computer-assisted planning in living donor liver operation[J].ZENTRALBLATT FUR CHIRURGIE.FEB 2006,131(1):69-74.
[9]Lang H,Radtke A,Hindennach M,Schroeder T,Bourquain H,Schenk A,Oldhafer K J,Prause G,Peitgen HO,Broelsch CE.Virtual hepatic surgery-computer-assisted operation planning on the 3-dimensional reconstructed liver[J].Z Gastroenterol.2007Sep;45(9):965-70.Epub 2007 Sep 4.
[10]Radtke A,Schroeder T,Molmenti EP,Sotiropoulos GC,Schenk A,Paul A,Frilling A,Lang H,Nadalin S,Malago M.Anatomical and physiological comparison of liver volumes among three frequent types of parenchyma transection in live donor liver transplantation[J]..HEPATO-GASTROENTEROLOGY 52(62):333-338 MAR-APR 2005.
[11]Reitinger,B.;Bornik,A.;Beichel,R.;Werkgartner,G.;Sorantin,E.Tools for augmented-reality-based liver resection planning.[J].Proceedings of the SPIE-The International Society for Optical Engineering Volume:5367 Issue:1 Pages:88-99.
[12]Glombitza G,Lamade W,Demiris AM,Gopfert MR,Mayer A,Bahner ML,Meinzer HP,Richter G,Lehnert T,Herfarth C.Virtual planning of liver resections:image processing,visualization and volumetric evaluation[J].International Journal of Medical Information.1999,53:225-237.
[13]Bourquain H,Schenk A,Link F,Preim B,Prause G,Peitgen H.HepaVision2—A software assistant for preoperative planning in living-related liver transplantation and oncologic liver surgery[J].Computer Assisted Radiology and Surgery,2002:341-346.
[14]http://www-iri.upc.es/.
[15]J.O.Neumann et al.Branching Patterns and Drainage Territories of the Middle Hepatic Vein in Computer-Simulated Right Living-Donor Hepatectomies[J].American Journal of Transplantation,2006,(6):1407-1415.
[16]Hogemann D,Stamm G,et al.Individual planning of liver surgery using a virtual model of the liver and associated structures[J].Radiologe,2000,40(3):267-273.
[17]Kamel IR,Kruskal JB,Raptopoulos V.Imaging for right lobe living donor liver transplantation[J].Seminars in Liver Disease,2001,21(2):271-282.
[18]Saito S,Yamanaka J,et al.A novel 3D hepatectomy simulation based on liver circulation:Application to liver resection and transplantation[J].Hepatology,2005,41(6):1297-1304.
[19]Radtke A,Bockhorn M,et al.Computer-assisted planning in living donor liver operation[J].Zentralblatt Fur Chirurgie,2006,131(1):69-74.
[20]Radtke A,Schroeder T,Molmenti EP,et al.Anatomical and physiological comparison of liver volumes among three frequent types of parenchyma transection in live donor liver transplantation[J].Hepato-Gastroenterology,2005,52(62):333-338.
[21]罗述谦.医学图像配准技术[J].国外医学生物医学工程分册,1999,22(1):1-7.
[22]ANTOINE MAINTZ J B,MAX A.Viergever.A survey of medical image registration[J].Medical Image Analysis,1998,2(1):1-36.
[23]俞亚青,田学隆,闫春红.医学图像配准方法分类及现状[J].重庆大学学报 2003,26(8),114-118
[24]REN HAI-PING,HU YANG,WU WEN-KAI,et al.Multi-resolution three-dimensional multi-modality image registration by maximization of mutual information.Proceedings of the 23rd Annual International Conference of the IEEE[C].Istanbul,Turkey:The Institute of Electrical and Electronics Engineers,Inc.,2001,3:2411-2413.
[25]HE RENJIE,PONNADA A.NARAYANA.Global optimization of mutual information:application to three dimensional retrospective registration of magnetic resonance images[J].Computerized Medical Imaging and Graphics,2002,26(4):277-292.
[26]PORTER B C,RUBENS D J,STRANG J G,et al.Three dimensional registration and fusion of ultrasound and MRI using major vessels as fiducial markers[J].IEEE Transactions on Medical Imaging,2001,20(4):354-359.
[27]A RANGARAJAN,CHUI HAILI,DUNCAN JAMES S.Rigid point feature registration using mutual information[J].Medical Image Analysis,1999,3(4):425-440.
[28]周永新,罗述谦.基于形状特征点最大互信息的医学图象配准[J].计算机辅助设计与图形学学报,2002,14(7):654-658.
[29]周鹏,谭勇,徐守时.基于角点检测图像配准的一种新算法[J].中国科学技术大学学报,2002,32(4):455-461.
[30]DING L,GOSHTASBY A,SATTER M.Volume image registration by template matching[J].Image and Vision Computing,2001,19(12):821-832.
[31]B LOW H,DOOLEY L,WERMSER D.Application of principal axes for registration of NMR image sequences[J].Pattern Recognition Letters,2000,21(4):329-336.
[32]吴锋,钱宗才,杭洽时,等.基于轮廓的力矩主轴法在医学图像配准中的应用[J].第四军医大学学报,2001,22(6):567-569.
[33]葛云,舒华忠,罗立民.基于Legendre正交矩的配准方法及其在二值图像配准中的应用[J].电子学报,2001,29(1):54-57.
[34]WACHOWIAK M P,SMOLIKOVA R,TOURASSI GD,et al.Generalized mutual information similarity metrics for multimodal biomedical image registration[A].Engineering in Medicine and Biology.24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society[C].Houston,Texas,USA:The Institute of Electrical and Electronics Engineers,Inc.,2002,2:1005-1006.
[35]LUO SHUQIAN,LI XIANG.Implementation of mutual information based multi-modality medical image registration[A].Engineering in Medicine and Biology Society.Proceedings of the 22nd Annual International Conference of the IEEE[C].Navy Pier Convention Center Chicago,Illinois,USA:The Institute of Electrical and Electronics Engineers,inc,2000,2:1447-1450.
[36]JOSIEN P W,PLUIM J B.Anitoine Maintz,Max A.Viergever.Interpolation artifacts in mutual information based image registration[J].Computer Vision and Image Understanding,2000,77(22):211-232.
[37]ROHR K,STIEHL H S.,Sprengel R.,et al.Landmark based Elastic registration using approximating thin-plate splines[J].IEEE Transactions On Medical Imaging,2001,20(6):526-533.
[38]THOMAS M.LEHMANN,CLAUDIA GONNER,KLAUS SPITZER.Survey:Interpolation methods in medical images processing[J].IEEE Transactions On Medical Imaging,1999,18(11):1049-1072.
[39]PLUIM J P W.Information and gradient information[J].IEEE Transactions on Medical Imaging,2000,19(8):809-814.
[40]杨虎,马斌荣,任海萍,等.基于互信息的人脑图像配准研究[J].中国医学物理学杂志,2001,18(2):69-72.
[41]赵富强,于红玉,马斌荣,等.基于图像特征的CT-MR图像配准[J].北京生物医学工程,2000,19(4):206-211.
[42]罗纲,罗斌.图象特征点集配准的加权相关迭代算法[J].中国图象图形学报,2000,2(9):755-758.
[43]SHUN'ICHI KANEKO,YUTAKA SATOH,SATORU I-GARASHI.Using selective correlation coefficient for robust image registration[J].Pattern Recognition,2003,36(5):1165-1173.
[44]ROCHEA,MALANDAING,PENNECX,etal.Multi-modal image registration by maximization of the correlatiratio(TechnicalReport3378)[R].France:INRIA,1999.
[45]QIN BIN-JIE,ZHUANG TIAN-GE.Choice of similarity measure in voxel intensity based 3D multi-modal medical image registration[J].Space Medicine & Medical Engineering,2002,15(4):241-245.
[46]刘文亚,蒋黛蒂,洪润环,等.螺旋CT多期增强扫描诊断小肝癌的价值[J].中国医学影像 学杂志,2002,10(1):8-10.
[47]王爽,周纯武,赵心明.多层螺旋CT在肝脏肿瘤诊断中的应用[J].临床放射学杂志,2003,3:248-250.
[48]Xiaoyang Huang,Boliang Wang and Shaohui Huang et al.Registration of different phases of contrast-enhanced liver CT data[J].Peoceedings of the 1st International Conference on Bioinformatics and BiomedicalEngineering.(2)2007,pp786-789.
[49]孙家广.计算机图形学(第三版)[M].北京:清华大学出版社,2000.
[50]高智勇,徐凯,刘丽荣,等.医学图像配准中快速坐标变换方法[J].上海:中国医疗器械杂志,2003,27(2):92-94.
[51]黄晓阳,王博亮,吴志坚,.快速坐标变换方法及其在图像配准中的应用[J].中国数字医学,2009,4(1)19-21.
[52]吕维雪段会龙.三维医学图像可视化及其应用[M].杭州:浙江大学出版社,2001.
[53]黄晓阳.人眼组织切片图像的配准、三维重建的研究与实现[D].厦门大学硕士论文,2003.
[54]Antoine Maintz J.B.,and Viergever M.A..Mutual-information-based registration of medical images:a survey[J].IEEE Transactions On Medical Imaging,22(2003),pp.986-1004.
[55]Frederik Maes,Andr e Collignon,Dirk Vandermeulen,Guy Marchal,and Paul Suetens,.Multimodality Image Registration by Maximization of Mutual Information[J].IEEE Transactions On Medical Imaging,16(1997),pp.187-198.
[56]C.Studholme,D.L.G.Hill and D.J.Hawkes,.An overlap invariant entropy measure of 3D medical image alignment[J].Pattern Recognition,32(1999),pp.71-86.
[57]Thomas M.Lehmann,Claudia G(?)onner,and Klaus Spitzer,Survey:Interpolation Methods in Medical Image Processing[J].IEEE TRANSACTIONS ON MEDICAL IMAGING,1999,18(11):1049-1075.
[58]J.A.Parker,R.V.Kenyon,and D.E.Troxel.Comparison of interpolating methods for image resampling[J].IEEE Trans.Med.Imag.,1983,2,:31-39.
[59]M.Unser,A.Aldroubi and M.Eden.Fast B-spline transform for continuous image representation and interpolation[J].IEEE Trans.Pattern Analysis And Machine Intelligence,1991,13:277-285.
[60]刘洪臣,杨旭强,冯勇.亚像元成像系统B样条插值方法[J].光电工程, 2006.2,33(2):90-93,126.
[61]任海萍,吴文凯,杨虎,陈盛祖.医学图像插值方法对比[J].北京生物医学工程,2002.3,21(1):19-23.
[62]席少霖,赵凤治.最优化计算方法[M].上海:上海科学计算出版社,1983
[63]陈开周.最优化计算方法[M].陕西:西北电讯工程学院出版社,1985.
[64]刘哲星,江贵平,张煜,等.基于互信息量图像配准中目标函数局部极值的成因分析与克服.中国生物医学工程学报,2003,12(6),503-507.
[65]Kennedy.J.Eberhart R.Particle Swarm Optimization[C].Australia Perth:IEEE Int Conf on Neural Networks,1995.1942-1945.
[66]Eberhart R,Kennedy J.A new optimizer using particle swarm theory[C].Japan Nagoya:Proc of the Sixth International Symposium on Micro Machine and Human Science,1995.39-42.
[67]Shi Y,Eberhart R.A Modified Particle Swarm Optimizer[C].IEEE World Congress on Computational Intelligence,1998.69.
[68]曾建潮,介婧,崔志华著.微粒群算法[M].北京:科学出版社.2004.
[69]冯林,严亮,黄德根等.PSO和Powell混合算法在医学图像配准中的应用研究[J].北京生物医学工程.2005,24(1).8-12.
[70]http://www.itk.org/.
[71]F.L.Bookstein.Prineipal Warps:Thin-plate splines and the decomposition of deformations[J].IEEE Trans.Pattern Analysis and Machine Intelligence,1989,11:567-585.
[72]M.Moshfeghi,S.Ranganath,and K.Nawyn.Three-dirnensional elastic matehing of volumes[J].IEEE Trans.Image Proeessing,1994,3(2):128-138.
[73]C.Davatzikos.Spatial normalization of 3d brain images using deformable models[J].Journal of Computer Assisted Tomography,1996.
[74]G.E.Christensen,R.D.Rabbitt and M.I.Miller.3D brain mapping using a deformable neuroanatomy[J].Physics in Medicine and Biology,1994,39:609-618.
[75]张煜.MRI-Man可视化模型建立中弹性配准新方法及显示方法研究[D].第一军医大学博士学位论文,2003.
[76]刘哲星.医学图像回溯性配准研究[D].第一军医大学博士学位论文,2002.
[77]戚正君.非刚性图像配准算法研究与应用[D].大连理工大学硕士论文,2004.
[78]罗述谦、周果宏.医学图像处理与分析[M].北京:科学出版社,2003.
[79]Nur Arad,Nira Dyn,Daniel Reisfeld et al.Image warping by radial basis functions:application to facial expressions[J].CVGIP.Graphical models and image processing,1994,56(2),161-172.
[80]K.Rohr.Loealization properties of direet corner detectors[J].Jurnal of Mathematical Imaging and Vision,1994,4:139-150.
[81]L.Kitehen and A.Rosenfeld.Gray level corner detection[J].Pattern Recognition Letters,1982,vol.1,95-102.
[82]K.Brunnstrom,T.Lindeberg,J.O.Eklundh.Active detection and classification of junctions[J].Proe.2nd European Conf.Computer Vision,St.Margherita,Italy,1992,LNCS 588,701-709.
[83]O.A.Zuniga,R.Haraliek.Corner detection using the facet model[J].Proe.IEEE Conf.Computer Vision Pattern Recognition,1983,30-37.
[84]J.A.Noble.Finding corners[J].Image Comput.,1988,6(2),121-128.
[85]D.G.Lowe,Distinctive image features from scale-invariant Keypoints,[J].International Journal of Computer Vision 60(2004),no.2,pp.91-110.
[86]Lindeberg T.Scale space theory,A basic tool for analyzing structures at different scales,[J].Journal of Applied Statistics,1994,21(2):pp.224-270.
[87]那彦、焦李成.基于多分辨分析理论的图像融合方法[M].西安:西安电子科技大学出版社,2007.
[88]H.Li,B.S.Manjunath and S.K.Mitra.Multisensor image fusionusing the wavelet transform,[J].Graphical Models Image Process.57(3)(1995),pp.235-245.
[89]Huang Xiaoyang,Wang Boliang,Cheng Ming et al.Image registration and data fusion for different phases of contrast enhanced liver CT data,[Z].Proceedings of the 2nd International Conference on Bioinformatics and Biomedical Engineering,2008,pp.2682-2685.
[90]余建明.医学影像技术学[M].科学出版社,2004,(247-249).
[91]刘潇潇.数字减影技术中的图像配准[D].华中科技大学硕士论文,2005.
[92]孙晓鹏.数字剪影血管造影(DSA)图象处理系统研究[D].北京工业大学硕士论文,2003.
[93]李雯.DSA/CT图像的无框架配准与融合技术的应用研究[J].上海交通大学,2004.
[94]Helen Hong,Ho Lee,Yeong Gil Shin,Yeol Hun Seong.Three-Dimensional Brain CT-DSA Using Rigid Registration and Bone Masking for Early Diagnosis and Treatment Planning[J].D.-K.Baik(Ed.):AsiaSim 2004,LNAI 3398,pp.167.176,2005.
[95]Julien Jomier,Elizabeth Bullitt,Mark Van Horn,Chetna Pathak,and Stephen R.Aylward.3D/2D Model-to-Image Registration Applied to TIPS Surgery.R.Larsen,M.Nielsen,and J.Sporring(Eds.):MICCAI2006,LNCS 4191,pp.662-669,2006.
[96]T.Rohlfing,C.R.Maurer Jr,J.Beierb.Reduction of motion artifacts in three-dimensional CT-DSA using constrained adaptive multilevel free-form registration[J].International Congress Series 1230(2001)365-371.
[97]梁玮.2D-3D医学图像配准研究[D].东南大学硕士论文.2004.
[98]陆忞,鲍旭东,罗立民,李鉴轶.基于改进SLNC的2D-3D医学图像配准[J].生物医学工程研究(2007)02-0170-04:170-173.
[99]梁玮,鲍旭东,罗立民.基于互信息的2D-3D医学图像配准[J].生物医学工程研究.2004,01:14-16.
[100]Dirk Selle,Bernhard Preim,Andrea Schenk,et al.Analysis of vasculature for liver surgical planning[J].IEEE transactions on medical imaging(S0278-0062),2002,21(11):1344-1357.
[101]Sethian,J.A.Fast marching methods[J].SIAM Review,1999,41(2):199-235.
[102]苏金明,王永利.Matlab图形图像[M].电子工业出版社,2005:117-119.
[103]王家文,李仰军.matlab7.0图形图像处理[M].国防工业出版社,2006:163-164.
[104]和青芳.计算机图形学原理及算法教程(Visual C++版)[M].清华大学出版社,2006.
[105]Louisa Lam,Seong-Whan Lee,and Ching Y.Suen.Thinning methodologies—a comprehensive survey[J].IEEE transactions on pattern analysis and machine intelligence (SO 162-8828),1992,14(9):869-883.
[106]Ta-Chin Lee and Rangasami L.Kashyap.Building skeleton models via 3-D medial surface/axis thinning algorithm[J].Graph.Models Image Processing(S1049-9552),1994,56(6):462-478.
[107]A RAN GARAJAN,CHU I HAIL I,DUNCAN JAMES S.Rigid Point Feature Registration Using Mutual Information[J].Medical Image Analysis,1999,3(4):425-440.
[108]张煜.一种用于医学图象配准的图象外边界的提取方法[J].北京生物医学工程,2000,VOL,19,No.4,217-220.
[109]Rohr K.Stiehl H S.Sprengel R.Point-based elastic registration of medical image data using approximating thin-plate splines[A].In:Proceedings Fourth International Conference on Visualization in Biomedical Computer(VBC'96)[C],Berlin,Germany:Springer Verlag,1996,1131:297-306.
[110]俎栋林,余立锋,王卫东,包尚联,等.基于轮廓特征的多模态医学图像的配准[J].系统工程与电子技术,2000,22(7):61-64.
[111]Van den Elson PA,Pol EJD,Viergever MA.Medical image matching-a review with classification.IEEE Engineering in Medicine and Biology,1993,12(4):26-39.
[112]沈晋慧,马斌荣,杨虎,于红玉.利用边缘和表面特征实现脑图像的自动配准[J].中国医学物理学杂志;2002年01期;14-18.
[113]Besl PJ,McKay NM.A method for registration of 3D shapes[J].IEEE Trans.Pattern Anal.and Machine Intell.,1989,14:567-585.
[114]Woods RP,Cherry SR,Mazziotta JC.Rapid aytomaited_algorilhm for aligning and reslicing PET images[J].Journal of Computer Assisted Tomography,992,16(4):620-633.
[115]Woods RP,Mazziotta JC,Cherry SR.MRI-PET registration with automated algorithm[J].Journal of Computer Assisted Tomography,1993,17(4):536-546.
[116]Van den Elson PA,Maintz JBA,Pole JD,et al.Automatic registration of CT and MR brain image using correlation of geometric features[J].IEEE Transactions on Medical Imaging,1995,14(2):384-396.
[117]Van den Elson PA,Pol EJD,Sumanaweera TS,et al.Grey value correlation techniques for automatic matching of CT and MR brain and spine images[J].In:Proceeding of Visualization in Biomedical Computing 1994,SPIE,1994,2359:227-237.
[118]冯林,张名举,贺明峰等.用分层互信息和薄板样条实现医学图像弹性自动配准[J].计算机辅助设计与图形学学报,2005,17(7):1492-1496.
[119]Xiaoyang Huang,Boliang Wang,Ruhuan Liu.CT-MR Image Registration in Liver Treatment by Maximization of Mutual Information,[J].Proceedings of 2008 IEEE International Symposium on IT in Medicine & Education,2008,Xiamen,China,pp.715-718.
[120]秦斌杰,庄天戈.利用相关比相似性测度多分辨率配准MR和CT医学图像的方法[J].中国生物医学工程学报,2003,22(1):1-5.
[121]Viola P A.Alignment by maximization of mutual information[D].Massachusetts Institute of Technology-Artificial Intelligence Laboratory,1995.
[122]J.B.A.Maintz and M.A.Viergever.A survey of medical image registration[J].Medieal Image Analysis,1998,2(1):1-36.
[123]王凯.多模态医学图像配准研究[D].中南大学;2008.
[124]冯林,严亮,黄德根,等.PSO和Powell混合算法在医学图像配准中的应用研究[J].北京生物医学工程 2005,24(01):8-12.
[125]Alpert NM,Bradshaw D,Kennedy D et al.The principal axes transtormation:A method for image registration[J].J nuclmed,1990,31:1717-1722.
[126]周建方.材料力学[M].北京:机械工业出版社.2002.
[127]陈瑛,蒋志新,顾顺德.利用矩运算完成图象的配准[J].上海第二医科大学学报,1999,3:277-279.
[128]Q.Chen,M.Defrise,F.Deconinck.Symmetric phase-only matched filtering of Fourier Mellin transform for image registration and recognition[J].IEEE Transactions on Pattern Analysis and Machine Intellgience.1994,16:1156-1168.
[129]B.S.Reddy,B.N.Chatterji,.An FFT-based technique for translation,rotation,and scale-invariant image registration[J].IEEE Trans.on Image Processing,1996,5(8),1266-1271.
[130]Brown L.G..A survey of image registration techniques[J].ACM Computing Surveys,1992,24(4):325-376.
[131]Zitov B..Flusser J..Image registration methods:A survey[J].Imaging and Vision Computing,2003,21(11):977-1000.
[132]Xiaoyang Huang,Boliang Wang,Ruhuan Liu.CT-MR Image Registration in Liver Treatment by Maximization of Mutual Information[J].Proceedings of 2008 IEEE International Symposium on IT in Medicine & Education,715-718.
[133]朱明德,方驰华.肝脏管道系统变异在活体肝移植中的意义[J].肝胆外科杂志.2005,13(6):473-475.
[134]Fasel JH,Gingins P,Kalra P,et al.Liver of the “visible man”[J].Clin Anat,1997, 10(6):389-393.
[135]丁家明,李惠君,刘群辉.肝静脉的应用解剖学研究[J].肝胆外科杂志.2003,11(4):308-310.
[136]冯新富,陈晓理.变异肝静脉的临床意义[J].华西医学.2003,18(2):270-271.
[137]Soyer P,Bluemke D A,Choti M A,et al.Variation in the intrahepatic portions of the hepatic and portal veins:Findings on helical CT scans during arterial portography[J].AMJ Roentgenol.1995,164(1):103-108.
[138]丁家明,李惠君.肝动脉的应用解剖[J].解剖科学进展.2000,6(4):350-351.
[139]Lee S S,Kim J K,Byun J H,et al.Hepatic arteries in potential donors for living related liver transplantation:Evaluation with multi2detector row CT angiography[J].Radiology,2003,227(2):391-399.
[140]陈孝平,陈汉.肝胆外科学[M].北京:人民卫生出版社2005.
[141]许敏,吴在德.肝脏外科解剖及肝段体积的测定[J].中国普通外科杂志,1996,5(1):1-2.
[142]Deshpande RR,Heaton ND,Rela M.Surgical anatomy of segmental liver transplantation [J].B r J Surg,2002,89(9):1078-1088.
[143]金武男,杨香,车成日.门静脉的解剖与变异[J].中国临床解剖学杂志.2006,24(2):157-159.