Accurate and reliable segmentation of the optic disc in digital fundus images

Andrea Giachetti, Lucia Ballerini, Emanuele Trucco

Research output: Contribution to journalArticlepeer-review

56 Citations (Scopus)
276 Downloads (Pure)


We describe a complete pipeline for the detection and accurate automatic segmentation of the optic disc in digital fundus images. This procedure provides separation of vascular information and accurate inpainting of vessel-removed images, symmetry-based optic disc localization, and fitting of incrementally complex contour models at increasing resolutions using information related to inpainted images and vessel masks. Validation experiments, performed on a large dataset of images of healthy and pathological eyes, annotated by experts and partially graded with a quality label, demonstrate the good performances of the proposed approach. The method is able to detect the optic disc and trace its contours better than the other systems presented in the literature and tested on the same data. The average error in the obtained contour masks is reasonably close to the interoperator errors and suitable for practical applications. The optic disc segmentation pipeline is currently integrated in a complete software suite for the semiautomatic quantification of retinal vessel properties from fundus camera images (VAMPIRE).

Copyright 2014 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Original languageEnglish
Article number024001
Number of pages11
JournalJournal of Medical Imaging
Issue number2
Publication statusPublished - 14 Jul 2014


  • optic disc
  • inpainting
  • multiresolution
  • radial symmetry
  • active contours
  • validation


Dive into the research topics of 'Accurate and reliable segmentation of the optic disc in digital fundus images'. Together they form a unique fingerprint.

Cite this