Restoration of cataract fundus images via unsupervised domain adaptation

Heng Li, Haofeng Liu, Yan Hu, Risa Higashita, Yitian Zhao, Hong Qi, Jiang Liu

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

3 Citations (Scopus)

Abstract

Cataract presents the leading cause of preventable blindness in the world. The degraded image quality of cataract fundus increases the risk of misdiagnosis and the uncertainty in preoperative planning. Unfortunately, the absence of annotated data, which should consist of cataract images and the corresponding clear ones from the same patients after surgery, limits the development of restoration algorithms for cataract images. In this paper, we propose an end-to-end unsupervised restoration method of cataract images to enhance the clinical observation of cataract fundus. The proposed method begins with constructing an annotated source domain through simulating cataract-like images. Then a restoration model for cataract images is designed based on pix2pix framework and trained via unsupervised domain adaptation to generalize the restoration mapping from simulated data to real one. In the experiment, the proposed method is validated in an ablation study and a comparison with previous methods. A favorable performance is presented by the proposed method against the previous methods. The code of of this paper will be released at https://github.com/liamheng/Restoration-of-Cataract-Images-via-Domain-Adaptation.

Original languageEnglish
Title of host publication2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021
PublisherIEEE Computer Society
Pages516-520
Number of pages5
ISBN (Electronic)9781665412469
DOIs
Publication statusPublished - 13 Apr 2021
Externally publishedYes
Event18th IEEE International Symposium on Biomedical Imaging, ISBI 2021 - Nice, France
Duration: 13 Apr 202116 Apr 2021

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2021-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference18th IEEE International Symposium on Biomedical Imaging, ISBI 2021
Country/TerritoryFrance
CityNice
Period13/04/2116/04/21

Keywords

  • Cataract
  • Image restoration
  • Unsupervised domain adaptation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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