基于眼底影像的计算机辅助诊断研究及系统实现
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摘要
本课题针对视网膜图像处理中的关键技术问题作了研究，包括视网膜血管网络的提取、视网膜血管宽度的测量、视网膜图像的配准。通过对比研究常见的几种视网膜血管分割算法，采用KNN算法较好的完成了视网膜血管网络的提取。对于视网膜血管宽度的测量，文中在血管网络提取的基础上，应用血管的中心线来确定血管方向，构造匹配模板，建立近似血管灰度分布的高斯模型，并结合最小二乘法，求解出血管的宽度。针对视网膜图像的配准，考虑到视网膜图像的特点及图像配准算法的精度、速度及实际应用性等因素，提出了基于血管网络相似性的图像配准方法，利用视网膜图像血管重叠像素对的灰度互信息最大作为目标函数，并采用全局优化算法——遗传算法对配准参数进行优化求取。最后，基于VC++平台，实现了一个初步的基于眼底影像的计算机辅助诊断系统。
The key technical problems of retinal image processing have been studied in this paper, which involves the extraction of the retinal image, the measurement of the width of retinal blood vessel, the registration of retinal images. Firstly, comparing the performance of retinal vessel segmentation methods, we chose the KNN method .In this way, the precision of the retinal image segmentation can be greatly improved. Secondly, based on the extraction of the retinal image, the measurement of the width of retinal blood vessel is carried out through four steps. The first step is to decide the direction of the blood vessel by taking into account the centerline of the blood vessel. The second step is to construct the matching template. The third step is to present the Gaussian model that can approximately simulate the gay distribution of the blood vessel. The last step is to solve the width of the blood vessel by applying Least Squares method optimize the model parameters. Thirdly, a method based on the blood vessel resemblance is proposed for the retinal image registration after considering the feature of retinal images, the precision, speed and practical application of the registration algorithm. In this method, the registration objective function is developed by using the maximal overlap degree of the retinal blood vessel information and its parameters is resolved by introducing a global optimization algorithm --Genetic Algorithm (GA). Finally, Based on VC++ platform, a preliminary computer-aided diagnosis system based on the fundus images is carried.
The key technical problems of retinal image processing have been studied in this paper, which involves the extraction of the retinal image, the measurement of the width of retinal blood vessel, the registration of retinal images. Firstly, comparing the performance of retinal vessel segmentation methods, we chose the KNN method .In this way, the precision of the retinal image segmentation can be greatly improved. Secondly, based on the extraction of the retinal image, the measurement of the width of retinal blood vessel is carried out through four steps. The first step is to decide the direction of the blood vessel by taking into account the centerline of the blood vessel. The second step is to construct the matching template. The third step is to present the Gaussian model that can approximately simulate the gay distribution of the blood vessel. The last step is to solve the width of the blood vessel by applying Least Squares method optimize the model parameters. Thirdly, a method based on the blood vessel resemblance is proposed for the retinal image registration after considering the feature of retinal images, the precision, speed and practical application of the registration algorithm. In this method, the registration objective function is developed by using the maximal overlap degree of the retinal blood vessel information and its parameters is resolved by introducing a global optimization algorithm --Genetic Algorithm (GA). Finally, Based on VC++ platform, a preliminary computer-aided diagnosis system based on the fundus images is carried.
引文
[1] 包尚联，谢耀钦，基于医学影像计算机辅助诊断的分割方法．中国医学物理杂志，2003 20(2)：153～159
[2] 姜兴岳，耿道颖，计算机辅助诊断在医学影像学中的应用．中华现代影像学杂志，2005 2(9)：162～165
[3] 闰云娟，计算机图像处理技术在眼底图像中的应用．太原师范学院学报，2003，2(3)，
[4] 黄淑英，视网膜图像处理与分析中关键技术研究：[硕士学位论文]，西安理工大学，2005
[5] 王蜀，基于数学形态学的医学图像分割．计算机应用，2005，25(10)
[6] 陈煜，医学影像中的图像配准和融合技术．中国医疗器械杂志，1999，33(3)
[7] 王鑫，图像配准理论及其算法研究：[硕士学位论文]．哈尔滨工程大学，2005
[8] http://www.isi.uu.nl/
[9] 朱宏擎，基于灰度-梯度共生矩阵的视网膜血管分割方法．上海交通大学学报，2004，38(9)
[10] 陆剑峰，自适应区域生长算法在医学图像分割中的应用．计算机辅助设计与图形学报，2005，17(10)
[11] 李磊等，基于高斯拟合的自适应多阈值分割算法．计算机应用研究，2006，12(4)
[12] M. Niemeijer, J. Staal, B. van Ginneken, M. Loog andM. D. Abramoff, Comparative study retinalvessel segmentation methods on a new publicly available database. IEEE Transaction on Medical Imaging19(4), 2003
[13] 邓子建，基于区域的多特征图象目标识别与检索研究：[工学硕士论文]．解放军信息工程大学，2005
[14] 刘潇潇，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，2005，10(12)
[15 杨建良，王永成，基于KNN与自动榆索的迭代近邻法在自动分类中的应用．情报学报，2004，23(2)
[16] Thitiporn Chanwimaluang, Guoliang Fan, An efficient blood vesses detection algorithm for retinal images using local entropythresholding, IEEE Trans. Medical imaging, vol. 17, 2003
[17] 张小洪，基于Canny算子的改进型边缘榆测算法．计算机工程与应用，(7)29，2003
[18] 许雷，张恒义，虞亚军，郑筱祥．一种糖尿病性眼底静脉串珠状变形程度定量分析方法，生物医学工程学杂志．1，1999
[19] P. Echevarria,, T. Miller, Blood Vessel Segmentation in Retinal Images. IEEE Tran. on Imaging, 8(3), 2005
[20] 孙富国，广义最小二乘法的研究与计算机实现．长沙铁道学院学报，3(17)，1999
[21] 赵天均，像素级图像融合技术研究：[硕士学位论文]．成都理工大学，2004
[22] 张二虎，卞正中，基于互信息的视网膜眼底图像配准方法．西安理工大学学报，18(1)：14-17，2002．
[23] 杨日容，基于遗传算法及最大互信息的医学图像配准研究：[硕士学文论文]．昆明理工大学，2005
[24] 王飞朝，遗传算法编程分析．火控雷达技术．第34卷，2005
[25] 余新宁，遗传算法程序的模块化设计．微机发展，13(3)，2003
[26] 王建军，医学图像处理软件的设计与实现：[硕士学位论文]．电子科技大学，2004
[27] 王延华，通用医学图像处理系统的设计和实现：[硕士学位论文]．中国科学院软件研究所，2002
[28] 张恒义，计算机眼底血管图像分析诊断系统，生物医学工程学杂志．16(2)：198-202，1999
[29] A. Hoover, M. Goldbaum, Locating the opitic nerve in a retinal image using the fuzzy convergence of the blood vessels. IEEE Transactions on Medical Imaging 22(8), 2003
[30] A. Hoover, V. Kouznetsova, Locating blood vessels in retinal images by piecewise probing of a matched filter response. IEEE Transactions on Medical Imaging19(3), 2000
[31] Jun-ichiro, Takamitsu, A Development of Computer-Aided Diagnosis System Using Fundus Images, Trans. of IEICE. Vol. J83-D-Ⅱ, No.1, pp. 342-350, 2001
[32] K.A. Vermeer, F.M. Vos, A model based method for retinal blood vessel detection, Computer in Biology and Medicine.209-219, 2004
[33] F. Zana, J.C. Klein, A Multimodal Registration Algorithm of Eye Fundus Images Using Vessels Detection and Hough Transform, IEEE Trans. pattern Anal. Machine Intell, vol. 8, pp. 679-698, 2005
[34] L. perdersen, M. Grunkin, Quantitative measurement of changes in retinal vessel diameter in ocular fundus images, Pattern Recogition Lett. 21(13-14), 2000
[35] T. Chanwimaluang, G. Fan, An efficient blood vessel detection algorithm for retinal images using local entropy thresholding, In Proc. Of the IEEE Intl. Symp. on Circuits and System, 003
[36] Yuji Hatanka, Tajeshi Hara, Automated Analysis of the Distributions and Geometries of Blood Vessels on Retinal Fundus Images, Medical Imaging, 2004
[37] P. Echevarria, T. Miller, Blood Vessel Segmentation in Retinal Images, IEEE Tran. on Medical Imaging, 8(3), 2005
[38] A. Pinz, S. Bernogger, Mapping the human retinal, IEEE Trans. Med. Imaging, 17(4), 1998
[39] E. Sugio, T. Kunieda, A Development of Computer-aided Diagnosis System Using Fondus Images, Proc. of 7th International Conference on Virtual System and Mutimedia, IEEE Computer Society, 2001
[40] 罗述谦，医学图像配准技术国外医学：生物医学工程分册．22(1)，1999
[41] Z. Woshfeghi, S.R. aganath, K. Nawyn. 3D elastic matching of volumes. IEEE Trans. Image Processing, 3(2):128, 1999
[42] P.A. vanden Elaeu, E.J.D. Pol. Medical image matching-A review with classification, IEEE Eng. In Medicine and Biology, 3: 26-38. 2003
[43] Kenneth R．Castleman主编，数字图像处理(影印版)，清华大学出版社，1998年4月第1版
[44] Maria Petrou，Panagiota Bosdogianni著，数字图像处理疑难解析，机械工业出版社，2005年4月第1版
[45] 杨淑莹著，VC++图像处理程序设计，清华大学出版社，2005年1月第2版
[46] 高守传，姚领田 编著，Visual C++数字图像处理与工程应用，中国铁道出版社，2006
[2] 姜兴岳，耿道颖，计算机辅助诊断在医学影像学中的应用．中华现代影像学杂志，2005 2(9)：162～165
[3] 闰云娟，计算机图像处理技术在眼底图像中的应用．太原师范学院学报，2003，2(3)，
[4] 黄淑英，视网膜图像处理与分析中关键技术研究：[硕士学位论文]，西安理工大学，2005
[5] 王蜀，基于数学形态学的医学图像分割．计算机应用，2005，25(10)
[6] 陈煜，医学影像中的图像配准和融合技术．中国医疗器械杂志，1999，33(3)
[7] 王鑫，图像配准理论及其算法研究：[硕士学位论文]．哈尔滨工程大学，2005
[8] http://www.isi.uu.nl/
[9] 朱宏擎，基于灰度-梯度共生矩阵的视网膜血管分割方法．上海交通大学学报，2004，38(9)
[10] 陆剑峰，自适应区域生长算法在医学图像分割中的应用．计算机辅助设计与图形学报，2005，17(10)
[11] 李磊等，基于高斯拟合的自适应多阈值分割算法．计算机应用研究，2006，12(4)
[12] M. Niemeijer, J. Staal, B. van Ginneken, M. Loog andM. D. Abramoff, Comparative study retinalvessel segmentation methods on a new publicly available database. IEEE Transaction on Medical Imaging19(4), 2003
[13] 邓子建，基于区域的多特征图象目标识别与检索研究：[工学硕士论文]．解放军信息工程大学，2005
[14] 刘潇潇，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，2005，10(12)
[15 杨建良，王永成，基于KNN与自动榆索的迭代近邻法在自动分类中的应用．情报学报，2004，23(2)
[16] Thitiporn Chanwimaluang, Guoliang Fan, An efficient blood vesses detection algorithm for retinal images using local entropythresholding, IEEE Trans. Medical imaging, vol. 17, 2003
[17] 张小洪，基于Canny算子的改进型边缘榆测算法．计算机工程与应用，(7)29，2003
[18] 许雷，张恒义，虞亚军，郑筱祥．一种糖尿病性眼底静脉串珠状变形程度定量分析方法，生物医学工程学杂志．1，1999
[19] P. Echevarria,, T. Miller, Blood Vessel Segmentation in Retinal Images. IEEE Tran. on Imaging, 8(3), 2005
[20] 孙富国，广义最小二乘法的研究与计算机实现．长沙铁道学院学报，3(17)，1999
[21] 赵天均，像素级图像融合技术研究：[硕士学位论文]．成都理工大学，2004
[22] 张二虎，卞正中，基于互信息的视网膜眼底图像配准方法．西安理工大学学报，18(1)：14-17，2002．
[23] 杨日容，基于遗传算法及最大互信息的医学图像配准研究：[硕士学文论文]．昆明理工大学，2005
[24] 王飞朝，遗传算法编程分析．火控雷达技术．第34卷，2005
[25] 余新宁，遗传算法程序的模块化设计．微机发展，13(3)，2003
[26] 王建军，医学图像处理软件的设计与实现：[硕士学位论文]．电子科技大学，2004
[27] 王延华，通用医学图像处理系统的设计和实现：[硕士学位论文]．中国科学院软件研究所，2002
[28] 张恒义，计算机眼底血管图像分析诊断系统，生物医学工程学杂志．16(2)：198-202，1999
[29] A. Hoover, M. Goldbaum, Locating the opitic nerve in a retinal image using the fuzzy convergence of the blood vessels. IEEE Transactions on Medical Imaging 22(8), 2003
[30] A. Hoover, V. Kouznetsova, Locating blood vessels in retinal images by piecewise probing of a matched filter response. IEEE Transactions on Medical Imaging19(3), 2000
[31] Jun-ichiro, Takamitsu, A Development of Computer-Aided Diagnosis System Using Fundus Images, Trans. of IEICE. Vol. J83-D-Ⅱ, No.1, pp. 342-350, 2001
[32] K.A. Vermeer, F.M. Vos, A model based method for retinal blood vessel detection, Computer in Biology and Medicine.209-219, 2004
[33] F. Zana, J.C. Klein, A Multimodal Registration Algorithm of Eye Fundus Images Using Vessels Detection and Hough Transform, IEEE Trans. pattern Anal. Machine Intell, vol. 8, pp. 679-698, 2005
[34] L. perdersen, M. Grunkin, Quantitative measurement of changes in retinal vessel diameter in ocular fundus images, Pattern Recogition Lett. 21(13-14), 2000
[35] T. Chanwimaluang, G. Fan, An efficient blood vessel detection algorithm for retinal images using local entropy thresholding, In Proc. Of the IEEE Intl. Symp. on Circuits and System, 003
[36] Yuji Hatanka, Tajeshi Hara, Automated Analysis of the Distributions and Geometries of Blood Vessels on Retinal Fundus Images, Medical Imaging, 2004
[37] P. Echevarria, T. Miller, Blood Vessel Segmentation in Retinal Images, IEEE Tran. on Medical Imaging, 8(3), 2005
[38] A. Pinz, S. Bernogger, Mapping the human retinal, IEEE Trans. Med. Imaging, 17(4), 1998
[39] E. Sugio, T. Kunieda, A Development of Computer-aided Diagnosis System Using Fondus Images, Proc. of 7th International Conference on Virtual System and Mutimedia, IEEE Computer Society, 2001
[40] 罗述谦，医学图像配准技术国外医学：生物医学工程分册．22(1)，1999
[41] Z. Woshfeghi, S.R. aganath, K. Nawyn. 3D elastic matching of volumes. IEEE Trans. Image Processing, 3(2):128, 1999
[42] P.A. vanden Elaeu, E.J.D. Pol. Medical image matching-A review with classification, IEEE Eng. In Medicine and Biology, 3: 26-38. 2003
[43] Kenneth R．Castleman主编，数字图像处理(影印版)，清华大学出版社，1998年4月第1版
[44] Maria Petrou，Panagiota Bosdogianni著，数字图像处理疑难解析，机械工业出版社，2005年4月第1版
[45] 杨淑莹著，VC++图像处理程序设计，清华大学出版社，2005年1月第2版
[46] 高守传，姚领田 编著，Visual C++数字图像处理与工程应用，中国铁道出版社，2006