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基于L^＊a^＊b^＊色彩空间的视神经边缘自动提取 被引量：3

Automated Detection of Optic Nerve Boundary Based on L^＊a^＊b^＊ Color Space
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摘要 视神经(Optic nerve)形状、面积和深度等参数是衡量眼底健康状况的重要指标,其边缘提取是量化这些参数的前提.为精确识别视神经边缘,本文提出了一种基于L*a*b*色彩空间眼底图像视神经边缘自动提取算法.该方法通过L*a*b*色彩空间自适应形态学方法与区域辅助几何活动轮廓模型边缘提取方法,结合基于交义网络的视神经自动定位,实现视神经边缘的自动提取.采用国际上通用的DRIVE眼底图像库和临床图像进行实验,验证了该算法的有效性. The parameters of optic nerve, such as shape, area, depth and so on, are the important indices to estimate the retinal health. Extraction of the optic nerve boundary is the precondition for quantifying these parameters. To accurately identify the boundary, a new method to detect the exact optic nerve boundary is proposed based on the L^＊a^＊b^＊ color space in this paper. Using morphology and region-aided geometric snake in the L^＊a^＊b^＊ color space, the method applies the automatic optic nerve localization base on cross-network to realize the automatic extraction of optic nerve boundary. The feasibility of the new method has been successfully tested for the DRIVE fundus image databases and our clinic images.
作者 李居朋 陈后金 于江波 张新媛
机构地区 北京交通大学电子信息工程学院 北京市眼科研究所北京
出处 《自动化学报》 EI CSCD 北大核心 2009年第1期103-106,共4页 Acta Automatica Sinica
基金 教育部新世纪优秀人才支持计划(50051) 教育部科学技术研究重点项目(106030)~~
关键词 视神经边缘提取 L*a*b色彩空间 自适应形态学 区域辅助几何轮廓模型 Optic nerve boundary detection, L^＊a^＊b^＊ color space, adaptable morphology, region-aided geometric snake （RAGS）
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献15

  • 1Mendels F, Heneghan C, Harper P D, Reilly R B, Thiran J P. Extraction of the optic disk boundary in digital fundus images. In: Proceedings of the 1st Joint BMES/EMBS Conference. Atlanta, USA: IEEE, 1999. 1139
  • 2Osareh A, Mirmehdi M, Thomas B, Markham R. Comparison of color spaces for optic disc localization in retinal images. In: Proceedings of the 16th International Conference on Pattern Recognition. Quebec, Canada: IEEE, 2002. 743 - 746
  • 3El-Allali S, Brown S. Active contours technique in retinal image identification of the optic disk boundary [Online], available: http://www.cse.sc.edu, 2003
  • 4Chanwimaluang T, Fan G. An efficient algorithm for extraction of anatomical structures in retinal images. In: Proceedings of International Conference on Image Processing. Barcelona, Spain: IEEE, 2003. 1093-1096
  • 5Abdel-Ghafar R A, Morris T, Ritchings T, Wood I. Detection and characterisation of the optic disk in glaucoma and diabetic retinopathy. In: Proceedings of International Conference on Medical Image Understanding and Analysis. London, UK: BMVA Press, 2004. 1-4
  • 6Mendels F, Heneghan C, Thiran J. Identification of the optic disk boundary in retinal images using active contous. In: Proceedings of the Irish Machine Vision and Image Processing Conference. Dublin, Ireland: Dublin City University Press, 1999. 103-115
  • 7Lowell J, Hunter A, Steel D, Basu A, Ryder R, Fletcher E. Optic nerve head segmentation. IEEE Transactions on Medical Imaging, 2004, 23(2): 256-264
  • 8Jiang X Q, Kwon H K, Alward L M, Abramoff M D. Robust automatic optic disk segmentation. In: Proceedings of International Conference on Computer Graphics and Interactive Techniques. Los Angeles, California: ACM, 2005. 134
  • 9Jelinek H F, Depardieu C, Lucas C, Cornforth D J, Huang W, Cree M J. Towards vessel characterization in the vicinity of the optic disc in digital retinal images. In: Proceedings of International Conference on Image and Vision Computing. Dunedin, New Zealand: University of Otago Press, 2005. 1-6
  • 10Bovik A C. Handbook of Image and Video Processing (Second Edition). San Diego: Academic Press, 2006. 411-429

二级参考文献7

共引文献9

同被引文献28

  • 1Lowell J, Hunter A, Steel D, et al. Optic nerve head segmentation [ J ]. IEEE Trans on Medical Imaging, 2004,23 (2) :256-264.
  • 2Jelinek H F, Depardieu C, Lucas C, et al. Towards vessel characterization in the vicinity of the optic disc in digital retinal images[ A]. In : Proceedings of International Conference on Image and Vision Computing [ C], Dunedin, New Zealand: University of Otago Press ,2005.1-6.
  • 3Abdel-Ghafar R A, Morris T, Ritchings T, et al. Detection and characterization of the optic disk in glaucoma and diabetic retinopathy~ A ]. In : Proceedings of International Conference on Medical Image Understanding and Analysis [ C ] , London, UK : BMVA Press,2004.1-4.
  • 4Chanwimaluang T, Fan G. An efficient algorithm for extraction of anatomical structures in retinal images[ A]. In:Proceedings International Conference on Image Processing [ C ] , Barcelona, Catalonia, Spain : IEEE Press, 2003. 1093- 1096.
  • 5El-Allali S, Brown S. Active contours technique in retinal image identification of the optic disk boundary. [ DB/OL], available: http ://www. cse. sc. edu ,2003.
  • 6Osareh A, Mirmehdi M, Thomas B, et al. Comparison of color spaces for optic disc localization in retinal images [ A ]. In:Proceeding of the IEEE 16th International Conference on Pattern Recognition [ C ] , Quebec, Canada: IEEE Press, 2002.743 -746.
  • 7Mendels F,Heneghan C,Thiran J. Identification of the optic disk boundary in retinal images using active contours [ A]. In:Proceedings of the Irish Machine Vision and Image Processing Conference [ C ] , Dublin, Ireland : Dublin City University Press, 1999. 103-115.
  • 8Grady L. Random Walks for Image Segmentation[ J]. IEEE Trans on Pattern Analysis and Machine Intelligence, Vol. 28, No. 11, pp. 1768-1783,2006.
  • 9孙惠泉.图论及其应用[M].科学出版社,北京,2005.
  • 10刘国才,王耀南,全惠敏.基于多层Mumford-Shah向量模型的彩色视乳头图像杯盘重建、分割与度量[J].中国生物医学工程学报,2007,26(5):700-707. 被引量：11

引证文献3

二级引证文献8

自动化学报
2009年 第1期

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