Creation of Retinal Mosaics for Diabetic Retinopathy Screening: A Comparative Study

  • Tânia MeloEmail author
  • Ana Maria Mendonça
  • Aurélio Campilho
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10882)


The creation of retinal mosaics from sets of fundus photographs can significantly reduce the time spent on the diabetic retinopathy (DR) screening, because through mosaic analysis the ophthalmologists can examine several portions of the eye at a single glance and, consequently, detect and grade DR more easily. Like most of the methods described in the literature, this methodology includes two main steps: image registration and image blending. In the registration step, relevant keypoints are detected on all images, the transformation matrices are estimated based on the correspondences between those keypoints and the images are reprojected into the same coordinate system. However, the main contributions of this work are in the blending step. In order to combine the overlapping images, a color compensation is applied to those images and a distance-based map of weights is computed for each one. The methodology is applied to two different datasets and the mosaics obtained for one of them are visually compared with the results of two state-of-the-art methods. The mosaics obtained with our method present good quality and they can be used for DR grading.


Diabetic retinopathy screening Retinal mosaicking Image registration Image blending Qualitative evaluation 



This work is financed by the ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme, and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia within project CMUP-ERI/TIC/0028/2014.


  1. 1.
    Adal, K.M., Ensing, R.M., Couvert, R., van Etten, P., Martinez, J.P., Vermeer, K.A., van Vliet, L.J.: A hierarchical coarse-to-fine approach for fundus image registration. In: Ourselin, S., Modat, M. (eds.) WBIR 2014. LNCS, vol. 8545, pp. 93–102. Springer, Cham (2014). Scholar
  2. 2.
    Adal, K.M., van Etten, P.G., Martinez, J.P., van Vliet, L.J., Vermeer, K.A.: Accuracy assessment of intra- and intervisit fundus image registration for diabetic retinopathy screening. Invest. Ophthalmol. Vis. Sci. 56(3), 1805–1812 (2015). Scholar
  3. 3.
    Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981). Scholar
  4. 4.
    Ghosh, D., Kaabouch, N.: A survey on image mosaicing techniques. J. Vis. Commun. Image Represent. 34, 1–11 (2016). Scholar
  5. 5.
    Hernandez-Matas, C., Zabulis, X., Triantafyllou, A., Anyfanti, P., Argyros, A.A.: Retinal image registration under the assumption of a spherical eye. Comput. Med. Imaging Graph. 55, 95–105 (2017). Scholar
  6. 6.
    Jelinek, H., Cree, M.: Automated Image Detection of Retinal Pathology. CRC Press, Boca Raton (2009)CrossRefGoogle Scholar
  7. 7.
    Lee, R., Wong, T.Y., Sabanayagam, C.: Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss. Eye Vis. 2(1), 17 (2015). Scholar
  8. 8.
    Legg, P.A., Rosin, P.L., Marshall, D., Morgan, J.E.: Improving accuracy and efficiency of mutual information for multi-modal retinal image registration using adaptive probability density estimation. Comput. Med. Imaging Graph. 37(7), 597–606 (2013). Scholar
  9. 9.
    Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004). Scholar
  10. 10.
    Matsopoulos, G.K., Asvestas, P.A., Mouravliansky, N.A., Delibasis, K.K.: Multimodal registration of retinal images using self organizing maps. IEEE Trans. Med. Imaging 23(12), 1557–1563 (2004). Scholar
  11. 11.
    Stewart, C.V., Tsai, C.L., Roysam, B.: The dual-bootstrap iterative closest point algorithm with application to retinal image registration. IEEE Trans. Med. Imaging 22(11), 1379–1394 (2003). Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.INESC TEC - Institute for Systems and Computer Engineering, Technology and SciencePortoPortugal
  2. 2.Faculty of Engineering of the University of PortoPortoPortugal

Personalised recommendations