基于平板成像器件的数字血管减影技术
摘要
在当前的临床实践中,数字血管减影技术是一种有效的血管可视化工具。特别是近年来,基于平板成像器件的数字血管减影技术逐渐取代了传统的胶片和影像增强器型减影技术,成为医疗诊断中必不可少的工具。如何使减影更加清晰也成了近年来研究的热点。
本文以平板探测器型DSA为主要研究对象,比较了基于平板成像器件的DSA和基于影像增强器件的DSA的主要差别,通过结果可以看到平板成像DSA具有很大的显影优势。在数字血管减影的研究上,对于成像条件比较好的DSA图像,可以使用直接减影的方法。但大部分DSA图像在进行减影时会受到背景器官的影响,因此本文采用了基于对数变换的减影方法,该方法使减影后的血管更加清晰可见。在减影的过程中,由于病人本身和人体器官不可避免的移动,使减影图像出现伪影。针对这种现象,本文介绍DSA图像中的配准技术,通过图像的配准尽量减少伪影对正常诊断的影响。根据血管图像的特点,采取特征点方法对图像进行配准。首先在造影图像上选取特征点,然后在原始图像上进行特征点偏移量的计算。在此基础上应用带有平滑参数的薄板样条插值方法,通过改变平滑参数来控制形变和平滑程度,从而对两幅图像进行配准。实验结果显示可以有效消除伪影。目前,绝大部分DSA图像都是满足DICOM3.0标准的,本文通过深入研究DICOM标准,来对DSA图像做正确的解析,并可以用VC++6.0实现DSA图像的显示。
数字血管减影技术由于能够动态显示血管的流动情况,从而清晰显示病灶,提高疾病发现率与诊断的准确率,降低造影剂的使用,提高了手术的安全性,降低了手术成本,因此,其应用前景将十分广阔。
In current clinic practice, Digital Subtraction Angiography (DSA) technique is an efficacious visualization tool for the blood vascular structures. Especially in recent years, Digital Subtraction Angiography technique gradually takes place of traditional film and image intensifier model DSA. And it becomes absolutely necessary tool in medical diagnosis. How to make subtraction more clear become of a research hotspot in the field of medical imaging in recently.
The flat panel detector DSA is researched in this dissertation. The difference is compared with flat panel DSA and image intensifier DSA. By the experimental results, we can see that flat panel detector DSA has obvious advantage.
In the study of DSA technique, the better image effect can use directly subtract method. But most of DSA image are affected by background organs in subtraction, so this paper use the logarithmic transformation subtraction method. This method makes the vascular image was subtracted more clearly. In the course of subtraction, the image appears artifacts because patient’s human organs inevitable moving. In this thesis, image registration problem in DSA technique is discussed and a new image registration approach is used. Firstly, the evenly chosen small number of points on the vascular centerlines forms the control points set. Secondly, control points offset is calculated in the mask image. Finally, a smoothed thin-plate splines (TPS) interpolation function is used to conduct image warping towards the mask image based on the corresponding control point sets. The smoothed thin-plate splines interpolation function can control the warping and smooth degree by adjusting the smooth parameter. The experimental results show this method can make the mask image registration. At present, most DSA image follows DICOM 3.0 Standard. In this dissertation the DSA image is displayed by research DICOM Standard, and a DSA image display software is developed by VC++6.0 programming.
The DSA technique can dynamically display the vascular flowing condition, clearly display lesions, improve diseases discover-rate and diagnostic accuracy, which can decrease the contrast agent using, improve operation safety and reduce operation cost. In a word, the DSA technique will have extensive appliance and wide prospect.
本文以平板探测器型DSA为主要研究对象,比较了基于平板成像器件的DSA和基于影像增强器件的DSA的主要差别,通过结果可以看到平板成像DSA具有很大的显影优势。在数字血管减影的研究上,对于成像条件比较好的DSA图像,可以使用直接减影的方法。但大部分DSA图像在进行减影时会受到背景器官的影响,因此本文采用了基于对数变换的减影方法,该方法使减影后的血管更加清晰可见。在减影的过程中,由于病人本身和人体器官不可避免的移动,使减影图像出现伪影。针对这种现象,本文介绍DSA图像中的配准技术,通过图像的配准尽量减少伪影对正常诊断的影响。根据血管图像的特点,采取特征点方法对图像进行配准。首先在造影图像上选取特征点,然后在原始图像上进行特征点偏移量的计算。在此基础上应用带有平滑参数的薄板样条插值方法,通过改变平滑参数来控制形变和平滑程度,从而对两幅图像进行配准。实验结果显示可以有效消除伪影。目前,绝大部分DSA图像都是满足DICOM3.0标准的,本文通过深入研究DICOM标准,来对DSA图像做正确的解析,并可以用VC++6.0实现DSA图像的显示。
数字血管减影技术由于能够动态显示血管的流动情况,从而清晰显示病灶,提高疾病发现率与诊断的准确率,降低造影剂的使用,提高了手术的安全性,降低了手术成本,因此,其应用前景将十分广阔。
In current clinic practice, Digital Subtraction Angiography (DSA) technique is an efficacious visualization tool for the blood vascular structures. Especially in recent years, Digital Subtraction Angiography technique gradually takes place of traditional film and image intensifier model DSA. And it becomes absolutely necessary tool in medical diagnosis. How to make subtraction more clear become of a research hotspot in the field of medical imaging in recently.
The flat panel detector DSA is researched in this dissertation. The difference is compared with flat panel DSA and image intensifier DSA. By the experimental results, we can see that flat panel detector DSA has obvious advantage.
In the study of DSA technique, the better image effect can use directly subtract method. But most of DSA image are affected by background organs in subtraction, so this paper use the logarithmic transformation subtraction method. This method makes the vascular image was subtracted more clearly. In the course of subtraction, the image appears artifacts because patient’s human organs inevitable moving. In this thesis, image registration problem in DSA technique is discussed and a new image registration approach is used. Firstly, the evenly chosen small number of points on the vascular centerlines forms the control points set. Secondly, control points offset is calculated in the mask image. Finally, a smoothed thin-plate splines (TPS) interpolation function is used to conduct image warping towards the mask image based on the corresponding control point sets. The smoothed thin-plate splines interpolation function can control the warping and smooth degree by adjusting the smooth parameter. The experimental results show this method can make the mask image registration. At present, most DSA image follows DICOM 3.0 Standard. In this dissertation the DSA image is displayed by research DICOM Standard, and a DSA image display software is developed by VC++6.0 programming.
The DSA technique can dynamically display the vascular flowing condition, clearly display lesions, improve diseases discover-rate and diagnostic accuracy, which can decrease the contrast agent using, improve operation safety and reduce operation cost. In a word, the DSA technique will have extensive appliance and wide prospect.
引文
[1] 余建明.数字减影血管造影技术[M].北京:人民军医出版社.1999.
[2] Shechter G., Devemay F. Three.Dimensional Motion Tracking of Coronary Arteries in Biplane Cineangiograms. IEEE Transactions on Medical Imaging[J]. 2000, 22:321-337.
[3] Keith M. Andress. Evidential Reconstruction of Vessel Trees from Rotational Angiograms[M]. Proc. IEEE Conf. Image Processing. 1998,3:385-389.
[4] 吴恩惠.医学影像学[M].北京:人民卫生出版社.2003.
[5] 李敏.数字减影造影设备的新技术发展及其应用[J].医疗卫生装备.2005,26(12):54.
[6] 李信度,曾勇明,陆云峰,谭欢等.平板探测器 DSA 冠状动脉造影的临床应用及评价[J].实用医学影像杂志.2005,6(6):304-306.
[7] 王庆根.基于 PaxScan2520 平板探测器的 X 射线成像处理系统研究[D].北京:北京机械工业自动化研究所.2005
[8] 陈小松.DSA 医学图像的增强技术及应用研究[D].苏州:苏州大学.2005
[9] 王明时,诸强,韩建新等.数字血管减影系统的研究[J].天津大学学报.2002,35(1):120-125.
[10] 江林华,陈仕东,柴振明.基于对数非线性映射的 X 光数字减影图像的获取与处理[J].中国图象图形学报.1999,4(9):773-776
[11] W.R.Brody, D.R.Enzmann, L..S.Deutsch.A.Hall, N.Pelc. Intravenous Carotid Arteriography using Line: Scanned Digital Radiography[J]. Radiology, 1981, 139(2): 297-300.
[12] W.A.Chilcote, M.T. Modic, W.A.Pavlicek, J.R.Little, A.J.Furian, P. M.Duchesneau, M.A.Weinstein. Digital Subtraction Angiography of the Carotid Arteries: A Comparitive Study in 100Patients[J]. Radiology, 1981, 139(2): 287-295.
[13] B.J.Hillman, T.W.Ovitt, S.Nudelman, H.D.Fischer, M.M.Frost, P.Capp, H.Roehrig, G.Seeley. Digital Video Subtraction Angiography of Renal Vascular Abnormalities[J]. Radiology, 1981,139(2):277-280.
[14] R.A.Kruger, J.A.Nelson, D.G.Roy, F.J.Miller, R.E.Anderson, P.Liu. Dynamic Tomographic Digital Subtraction Angiography using Temporal Filtration[J]. Radiology, 1983,147(3):863-867.
[15] R.A.Kruger, M.Sedaghati, D.G.Roy, P.Liu, J.A.Nelson, W.Kubal, P.Del Rio. Tomosynthesis Applied to Digital Subtraction Angiography[J]. Radiology, 1984, 152(3):805-808.
[16] A.Kruger, C.A.Mistretta, A.B.Crummy, J.F.Sackett, M.M.Goodsitt, S. J.Riederer, T.L.Houk, C.G. Shaw, D. Flemming. Digital K.Edge Subtraction Radiography[J]. Radiology, 1977,125(1):243-245.
[17] W. R. Brody. Hybrid Subtraction for Improved Arteriography[J]. Radiology, 1981,141(3):828-831.
[18] H. Oung, A. M. Smith. Real Time Motion Detection in Digital Subtraction Angiography in Proceedings of the International Symposium on Medical Images and Icons, A. Deurinckx, M. H. Loew, J. M. S Prewitt (eds.), IEEE Computer Society Press, Silver Spring, RI, 1984,4:336-339.
[19] J. K. Aggerwal, N. Nandhakumar. On the Computation of Motion from Sequences of Images A Review[J]. Proceedings of the IEEE, 1988,76(8):917-935.
[20] L. G. Brown. A Survey of Image Registration Techniques[J]. ACM Computing Surveys, 1992,24(4):325-376.
[21] P.A.van den Elsen, E..J. D. Pol, M. A. Viergever. Medical Image Matching: A Review with Classification[J]. IEEE Engineering in Medicine and Biology, 1993, 12(1):26-39.
[22] J. B. A. Maintz, M. A. Viergever. A Survey of Medical Image Registration[J], Medical Image Analysis. 1998,2(1):1-361.
[23] Rusinck H, Levy A, Noz ME. Performance of two methods for registeringPET and MR brain scans[J]. Conf Record 1991 IEEE Nuclear Science Symp Med Image Conf 1991,3:2195.
[24] Besl P J, Macky ND.A method for registration of 3-D shapes[J]. IEEE Trans patt Anal Mach Intell. 1992,14(4):239.
[25] 王卫东,俎栋林,包尚联,王泽华.基于边缘提取的医学图像配准方法[J].中国体视学与图像分析.1998,3(12):204-207.
[26] D.M.Pelz, A.J.Fox, F.Vinuela. Digital Subtraction Angiography: Current Clinical Applications. 1985,16(3):528–536.
[27] P.Dawson. Digital Subtraction Angiography: a Critical Analysis Clinic[J]. Radiology, 1988,39(5):474-477.
[28] W.D. Jeans. The Development and Use of Digital Subtraction Angiography[J]. Br. J.Radiol, 1990,63(747):161-168.
[29] B.T. Katzen. Current Status of Digital Angiography in Vascular Imaging[J], Radiologic Clinics N. Amer, 1995,33(1):1-14.
[30] 杨健.基于互信息量和薄板样条的 X 射线造影图像弹性配准[J].电子学报.2007,35(1):127-130.
[31] 冯林,颜世鹏等.启发策略的确定性退火技术非刚性点匹配算法[J].计算机工程与应用.2006,2:33-36.
[32] 冯林.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.
[33] 王小波.实用数字血管减影配准算法研究[J].计算机仿真.2004,21(2): 112-114.
[34] M. Yanagisawa, S. Shigemitsu, T. Akatsuka. Registration of Locally Distorted Images by Multiwindow Pattern Matching and Displacement Interpolation: The Proposal of an Algorithm and Its Application to Digital Subtraction Angiography. in Proceedings of the Seventh International Conference on Pattern Recognition, M. D. Levine (ed.), IEEE Publishing Services, New York, NY, 1984, 2:1288-1291.
[35] A. Venot, V. Leclerc. Automated Correction of Patient Motion and Gray ValuesPrior to Subtraction in Digitized Angiography[J]. IEEE Transactions on Medical Imaging, 1984,3(4):179-186.
[36] R. Szeliski , J. Coughlan. Spline.Based Image Registration[J]. International Journal of Computer Vision, 1997,22(3):199-218.
[37] L. van Tran, J. Sklansky. Flexible Mask Subtraction for Digital Angiography[J]. IEEE Transactions on Medical Imaging, 1992, 11(3):407-415.
[38] G. C. Stockman, S. Kopstein, S. Benett. Matching Images to Models for Registration and Object Detection via Clustering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1982, 4(3):229-241.
[39] L. S. Davis, Z. Wu, H. Sun. Contour.Based Motion Estimation[J]. Computer Vision, Graphics and Image Processing, 1983,23(3):313-326.
[40] E. C. Hildreth. The Computation of the Velocity Field[J]. Proceedings of the Royal Society of London, Series B, 1984,221:189-220.
[41] Erik H.W. Meijering, Karel J Zuiderveld, Max A.Viergever. Image registration for Digital Subtraction Angiography[J]. International Journal of Computer Vision, 1999,31(2/3):227-246.
[42] 刘潇潇,曹治国,李抱朴,唐奇伶,翁文杰,桑农. 基于多尺度 Gabor 滤波的造影血管中轴线的自动提取.中国图象图形学报[J].2005,10(12):1542-1547.
[43] Mehrotra R, Namuduri K R, Ranganathan N. Odd Gabor filter.based edge detection [J]. Pattern Recognition (S0031.3203), 1992,25(12):1479-1494.
[44] Erik H.W. Meijering, Karel J Zuiderveld, Max A.Viergever. Image registration for Digital Subtraction Angiography[J]. International Journal of Computer Vision, 1999,31(2/3):227-246.
[45] Woods R.P, Cherry S.R, Mazziotta J.C. Rapid automated algorithm for aligning and reslicing PET images[J]. Comput Assist Tomogr 1992,16,(4):620-633.
[46] G. Wahba. Spline Models for Observational Data[M]. In Regional Conference Series in Applied Mathematics,Society for Industrial & Applied Mathematics, 1998.
[47] Fred L. Bookstein. Principal Warps: Thin Plate Splines and the Decomposition of Deformations[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989,11:567-585.
[48] A Rangarajan, HChui,et al. A new Distance Measure for Non Rigid Image Matching[J]. Energy Mininization Methods in Computer Vision and Pattern Recognition (EMMCVPR) Youk, UK1999:237-252.
[49] Rainer Sprengel, Karl Rohr, H.Siegfried Stiehl. Thin-Plate Spline Approximation for Image Registration[J].18th Annual International Conference of the IEEEE Engineering in Medicine and Biology Society , Amsterdam 1996:1190-1191.
[50] 罗述谦,周果宏.医学图像处理与分析[M].北京:科学出版社.2003.
[51] National Electrical Manufacturers Association (NEMA), Digital Imaging and Communications in Medicine(DICOM), http://medical.nema.org /dicom/ 2004.html,2004
[52] National Electrical Manufacturers Association. Digital Imaging and Communications in Medicine (DICOM). PS3, 2004.
[53] Grevera G J, Feingold E, Horii S C, WWW to DICOM Interface. SPIE Proceedings: Medical imaging 1996: PACS Design and Evaluation: Engineering and Clinical issues, 109-117.
[54] Levine B A, Cleary K R, Norton G S et al. Challenges encountered xhile Plementing a multi.endorteleradiology network using DICOM3.0. SPIE processings: Medical Imaging 1997: PACS Design and Evaluation: Engineering and Clinical Issue, 237-245
[55] 徐潘辉,林峰. DICOM 医学数字图像格式与 BMP 通用图像格式转换软件的设计与实现[J]. 医疗设备信息,2006,21(3):1-5.
[56] 陈远新. 基于 DICOM3.0 标准的医学图像显示和处理研究[D],重庆:重庆大学. 2005.
[57] 张尤赛,陈福民. DICOM 医学图像窗口变换的加速算法[J]. 计算机工程与应用,2003,13:218-220.
[58] 张宇明.基于 DICOM 标准的 mini-PACS 的设计与实现技术研究[D].西安:中国科学院西安光学精密机械研究所.2004.
[2] Shechter G., Devemay F. Three.Dimensional Motion Tracking of Coronary Arteries in Biplane Cineangiograms. IEEE Transactions on Medical Imaging[J]. 2000, 22:321-337.
[3] Keith M. Andress. Evidential Reconstruction of Vessel Trees from Rotational Angiograms[M]. Proc. IEEE Conf. Image Processing. 1998,3:385-389.
[4] 吴恩惠.医学影像学[M].北京:人民卫生出版社.2003.
[5] 李敏.数字减影造影设备的新技术发展及其应用[J].医疗卫生装备.2005,26(12):54.
[6] 李信度,曾勇明,陆云峰,谭欢等.平板探测器 DSA 冠状动脉造影的临床应用及评价[J].实用医学影像杂志.2005,6(6):304-306.
[7] 王庆根.基于 PaxScan2520 平板探测器的 X 射线成像处理系统研究[D].北京:北京机械工业自动化研究所.2005
[8] 陈小松.DSA 医学图像的增强技术及应用研究[D].苏州:苏州大学.2005
[9] 王明时,诸强,韩建新等.数字血管减影系统的研究[J].天津大学学报.2002,35(1):120-125.
[10] 江林华,陈仕东,柴振明.基于对数非线性映射的 X 光数字减影图像的获取与处理[J].中国图象图形学报.1999,4(9):773-776
[11] W.R.Brody, D.R.Enzmann, L..S.Deutsch.A.Hall, N.Pelc. Intravenous Carotid Arteriography using Line: Scanned Digital Radiography[J]. Radiology, 1981, 139(2): 297-300.
[12] W.A.Chilcote, M.T. Modic, W.A.Pavlicek, J.R.Little, A.J.Furian, P. M.Duchesneau, M.A.Weinstein. Digital Subtraction Angiography of the Carotid Arteries: A Comparitive Study in 100Patients[J]. Radiology, 1981, 139(2): 287-295.
[13] B.J.Hillman, T.W.Ovitt, S.Nudelman, H.D.Fischer, M.M.Frost, P.Capp, H.Roehrig, G.Seeley. Digital Video Subtraction Angiography of Renal Vascular Abnormalities[J]. Radiology, 1981,139(2):277-280.
[14] R.A.Kruger, J.A.Nelson, D.G.Roy, F.J.Miller, R.E.Anderson, P.Liu. Dynamic Tomographic Digital Subtraction Angiography using Temporal Filtration[J]. Radiology, 1983,147(3):863-867.
[15] R.A.Kruger, M.Sedaghati, D.G.Roy, P.Liu, J.A.Nelson, W.Kubal, P.Del Rio. Tomosynthesis Applied to Digital Subtraction Angiography[J]. Radiology, 1984, 152(3):805-808.
[16] A.Kruger, C.A.Mistretta, A.B.Crummy, J.F.Sackett, M.M.Goodsitt, S. J.Riederer, T.L.Houk, C.G. Shaw, D. Flemming. Digital K.Edge Subtraction Radiography[J]. Radiology, 1977,125(1):243-245.
[17] W. R. Brody. Hybrid Subtraction for Improved Arteriography[J]. Radiology, 1981,141(3):828-831.
[18] H. Oung, A. M. Smith. Real Time Motion Detection in Digital Subtraction Angiography in Proceedings of the International Symposium on Medical Images and Icons, A. Deurinckx, M. H. Loew, J. M. S Prewitt (eds.), IEEE Computer Society Press, Silver Spring, RI, 1984,4:336-339.
[19] J. K. Aggerwal, N. Nandhakumar. On the Computation of Motion from Sequences of Images A Review[J]. Proceedings of the IEEE, 1988,76(8):917-935.
[20] L. G. Brown. A Survey of Image Registration Techniques[J]. ACM Computing Surveys, 1992,24(4):325-376.
[21] P.A.van den Elsen, E..J. D. Pol, M. A. Viergever. Medical Image Matching: A Review with Classification[J]. IEEE Engineering in Medicine and Biology, 1993, 12(1):26-39.
[22] J. B. A. Maintz, M. A. Viergever. A Survey of Medical Image Registration[J], Medical Image Analysis. 1998,2(1):1-361.
[23] Rusinck H, Levy A, Noz ME. Performance of two methods for registeringPET and MR brain scans[J]. Conf Record 1991 IEEE Nuclear Science Symp Med Image Conf 1991,3:2195.
[24] Besl P J, Macky ND.A method for registration of 3-D shapes[J]. IEEE Trans patt Anal Mach Intell. 1992,14(4):239.
[25] 王卫东,俎栋林,包尚联,王泽华.基于边缘提取的医学图像配准方法[J].中国体视学与图像分析.1998,3(12):204-207.
[26] D.M.Pelz, A.J.Fox, F.Vinuela. Digital Subtraction Angiography: Current Clinical Applications. 1985,16(3):528–536.
[27] P.Dawson. Digital Subtraction Angiography: a Critical Analysis Clinic[J]. Radiology, 1988,39(5):474-477.
[28] W.D. Jeans. The Development and Use of Digital Subtraction Angiography[J]. Br. J.Radiol, 1990,63(747):161-168.
[29] B.T. Katzen. Current Status of Digital Angiography in Vascular Imaging[J], Radiologic Clinics N. Amer, 1995,33(1):1-14.
[30] 杨健.基于互信息量和薄板样条的 X 射线造影图像弹性配准[J].电子学报.2007,35(1):127-130.
[31] 冯林,颜世鹏等.启发策略的确定性退火技术非刚性点匹配算法[J].计算机工程与应用.2006,2:33-36.
[32] 冯林.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.
[33] 王小波.实用数字血管减影配准算法研究[J].计算机仿真.2004,21(2): 112-114.
[34] M. Yanagisawa, S. Shigemitsu, T. Akatsuka. Registration of Locally Distorted Images by Multiwindow Pattern Matching and Displacement Interpolation: The Proposal of an Algorithm and Its Application to Digital Subtraction Angiography. in Proceedings of the Seventh International Conference on Pattern Recognition, M. D. Levine (ed.), IEEE Publishing Services, New York, NY, 1984, 2:1288-1291.
[35] A. Venot, V. Leclerc. Automated Correction of Patient Motion and Gray ValuesPrior to Subtraction in Digitized Angiography[J]. IEEE Transactions on Medical Imaging, 1984,3(4):179-186.
[36] R. Szeliski , J. Coughlan. Spline.Based Image Registration[J]. International Journal of Computer Vision, 1997,22(3):199-218.
[37] L. van Tran, J. Sklansky. Flexible Mask Subtraction for Digital Angiography[J]. IEEE Transactions on Medical Imaging, 1992, 11(3):407-415.
[38] G. C. Stockman, S. Kopstein, S. Benett. Matching Images to Models for Registration and Object Detection via Clustering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1982, 4(3):229-241.
[39] L. S. Davis, Z. Wu, H. Sun. Contour.Based Motion Estimation[J]. Computer Vision, Graphics and Image Processing, 1983,23(3):313-326.
[40] E. C. Hildreth. The Computation of the Velocity Field[J]. Proceedings of the Royal Society of London, Series B, 1984,221:189-220.
[41] Erik H.W. Meijering, Karel J Zuiderveld, Max A.Viergever. Image registration for Digital Subtraction Angiography[J]. International Journal of Computer Vision, 1999,31(2/3):227-246.
[42] 刘潇潇,曹治国,李抱朴,唐奇伶,翁文杰,桑农. 基于多尺度 Gabor 滤波的造影血管中轴线的自动提取.中国图象图形学报[J].2005,10(12):1542-1547.
[43] Mehrotra R, Namuduri K R, Ranganathan N. Odd Gabor filter.based edge detection [J]. Pattern Recognition (S0031.3203), 1992,25(12):1479-1494.
[44] Erik H.W. Meijering, Karel J Zuiderveld, Max A.Viergever. Image registration for Digital Subtraction Angiography[J]. International Journal of Computer Vision, 1999,31(2/3):227-246.
[45] Woods R.P, Cherry S.R, Mazziotta J.C. Rapid automated algorithm for aligning and reslicing PET images[J]. Comput Assist Tomogr 1992,16,(4):620-633.
[46] G. Wahba. Spline Models for Observational Data[M]. In Regional Conference Series in Applied Mathematics,Society for Industrial & Applied Mathematics, 1998.
[47] Fred L. Bookstein. Principal Warps: Thin Plate Splines and the Decomposition of Deformations[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989,11:567-585.
[48] A Rangarajan, HChui,et al. A new Distance Measure for Non Rigid Image Matching[J]. Energy Mininization Methods in Computer Vision and Pattern Recognition (EMMCVPR) Youk, UK1999:237-252.
[49] Rainer Sprengel, Karl Rohr, H.Siegfried Stiehl. Thin-Plate Spline Approximation for Image Registration[J].18th Annual International Conference of the IEEEE Engineering in Medicine and Biology Society , Amsterdam 1996:1190-1191.
[50] 罗述谦,周果宏.医学图像处理与分析[M].北京:科学出版社.2003.
[51] National Electrical Manufacturers Association (NEMA), Digital Imaging and Communications in Medicine(DICOM), http://medical.nema.org /dicom/ 2004.html,2004
[52] National Electrical Manufacturers Association. Digital Imaging and Communications in Medicine (DICOM). PS3, 2004.
[53] Grevera G J, Feingold E, Horii S C, WWW to DICOM Interface. SPIE Proceedings: Medical imaging 1996: PACS Design and Evaluation: Engineering and Clinical issues, 109-117.
[54] Levine B A, Cleary K R, Norton G S et al. Challenges encountered xhile Plementing a multi.endorteleradiology network using DICOM3.0. SPIE processings: Medical Imaging 1997: PACS Design and Evaluation: Engineering and Clinical Issue, 237-245
[55] 徐潘辉,林峰. DICOM 医学数字图像格式与 BMP 通用图像格式转换软件的设计与实现[J]. 医疗设备信息,2006,21(3):1-5.
[56] 陈远新. 基于 DICOM3.0 标准的医学图像显示和处理研究[D],重庆:重庆大学. 2005.
[57] 张尤赛,陈福民. DICOM 医学图像窗口变换的加速算法[J]. 计算机工程与应用,2003,13:218-220.
[58] 张宇明.基于 DICOM 标准的 mini-PACS 的设计与实现技术研究[D].西安:中国科学院西安光学精密机械研究所.2004.