Semantic Reconstruction-Based Nuclear Cataract Grading from Slit-Lamp Lens Images

  • Yanwu XuEmail author
  • Lixin Duan
  • Damon Wing Kee Wong
  • Tien Yin Wong
  • Jiang Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9902)


Cataracts are the leading cause of visual impairment and blindness worldwide. Cataract grading, i.e. assessing the presence and severity of cataracts, is essential for diagnosis and progression monitoring. We present in this work an automatic method for predicting cataract grades from slit-lamp lens images. Different from existing techniques which normally formulate cataract grading as a regression problem, we solve it through reconstruction-based classification, which has been shown to yield higher performance when the available training data is densely distributed within the feature space. To heighten the effectiveness of this reconstruction-based approach, we introduce a new semantic feature representation that facilitates alignment of test and reference images, and include locality constraints on the linear reconstruction to reduce the influence of less relevant reference samples. In experiments on the large ACHIKO-NC database comprised of 5378 images, our system outperforms the state-of-the-art regression methods over a range of evaluation metrics.


  1. 1.
    Kanski, J.J.: Clinical Ophthalmology – A systematic Approach. Elsevier Butterworth-Heinemann, Edinburgh (2007)Google Scholar
  2. 2.
    Thylefors, B., Chylack Jr., L.T., Konyama, K., Sasaki, K., Sperduto, R., Taylor, H.R., West, S.: A simplified cataract grading system. Ophthalmic Epidemiol. 9(2), 83–95 (2002)CrossRefGoogle Scholar
  3. 3.
    Chylack, L., Wolfe, J., Singer, D., Leske, M.C., Bullimore, M.A., Bailey, I.L., Friend, J., McCarthy, D., Wu, S.Y.: The lens opacities classificatin system III. Arch Ophthalmol. 111(6), 831–836 (1993)CrossRefGoogle Scholar
  4. 4.
    Klein, B., Klein, R., Linton, K., Magli, Y., Neider, M.: Assessment of cataracts from photographs in the beaver dam eye study. Ophthalmology 97, 1428–1433 (1990)CrossRefGoogle Scholar
  5. 5.
    Xu, Y., Gao, X., Lin, S., Wong, D.W.K., Liu, J., Xu, D., Cheng, C.Y., Cheung, C.Y., Wong, T.Y.: Automatic grading of nuclear cataracts from slit-lamp lens images using group sparsity regression. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds.) MICCAI 2013, Part II. LNCS, vol. 8150, pp. 468–475. Springer, Heidelberg (2013)Google Scholar
  6. 6.
    Li, H., Lim, J.H., Liu, J., Mitchell, P., Tan, A., Wang, J., Wong, T.: A computer-aided diagnosis system of nuclear cataract. IEEE Trans. Biomed. Eng. 57, 1690–1698 (2010)CrossRefGoogle Scholar
  7. 7.
    Fan, S., Dyer, C.R., Hubbard, L., Klein, B.: An automatic system for classification of nuclear sclerosis from slit-lamp photographs. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2878, pp. 592–601. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  8. 8.
    Huang, W., Li, H., Chan, K.L., Lim, J.H., Liu, J., Wong, T.Y.: A computer-aided diagnosis system of nuclear cataract via ranking. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009, Part II. LNCS, vol. 5762, pp. 803–810. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  9. 9.
    Duncan, D.D., Shukla, O.B., West, S.K., Schein, O.D.: New objective classification system for nuclear opacification. J. Opt. Soc. Am. 14, 1197–1204 (1997)CrossRefGoogle Scholar
  10. 10.
    Khu, P.M., Kashiwagi, T.: Quantitating nuclear opacification in color scheimpflug photographs. Invest. Ophthalmol. Vis. Sci. 34, 130–136 (1993)Google Scholar
  11. 11.
    Xu, D., Huang, Y., Zeng, Z., Xu, X.: Human gait recognition using patch distribution feature and locality-constrained group sparse representation. IEEE Trans. Image Process. 21(1), 316–326 (2012)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 2.5 International License (, which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Authors and Affiliations

  • Yanwu Xu
    • 1
    Email author
  • Lixin Duan
    • 2
  • Damon Wing Kee Wong
    • 1
  • Tien Yin Wong
    • 3
  • Jiang Liu
    • 1
    • 4
  1. 1.Institute for Infocomm Research, Agency for Science, Technology and ResearchSingaporeSingapore
  2. 2.AmazonSeattleUSA
  3. 3.Singapore Eye Research InstituteSingaporeSingapore
  4. 4.Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and EngineeringChinese Academy of SciencesBeijingChina

Personalised recommendations