Optic disc detection via deep learning in fundus images

Peiyuan Xu, Cheng Wan, Jun Cheng, Di Niu, Jiang Liu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

15 Citations (Scopus)

Abstract

In order to realize the localization of optic disc (OD) effectively, a new end-to-end approach based on CNN was proposed in this paper. CNN is a revolutionary network structure which has shown its power in fields of computer vision like classification, object detection and segmentation. We intend to make use of CNN in the study of fundus images. Firstly, we use a basic CNN on which specialized layers are trained to find the pixels probably in OD region. Then we sort out candidate pixels furtherly via threshold. By calculating the center of gravity of these pixels, the location of OD is finally determined. The method has been tested on three databases including ORIGA, MESSIDOR and STARE. In totally 1240 images to be tested, the OD of 1193 are successfully located with the rate of 96.2%. Besides the accuracy, the time cost is another advantage. It takes only 0.93 s to test one image on average in STARE and 0.51 s in MESSIDOR.

Original languageEnglish
Title of host publicationFetal, Infant and Ophthalmic Medical Image Analysis - International Workshop, FIFI 2017 and 4th International Workshop, OMIA 2017 Held in Conjunction with MICCAI 2017, Proceedings
EditorsM. Jorge Cardoso, Tal Arbel
PublisherSpringer Verlag
Pages134-141
Number of pages8
ISBN (Print)9783319675602
DOIs
Publication statusPublished - 2017
Externally publishedYes
EventInternational Workshop on Fetal and Infant Image Analysis, FIFI 2017 and 4th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: 14 Sept 201714 Sept 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10554 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Workshop on Fetal and Infant Image Analysis, FIFI 2017 and 4th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
Country/TerritoryCanada
CityQuebec City
Period14/09/1714/09/17

Keywords

  • Convolution neural networks
  • Optic disc localization
  • Retinal fundus image

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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