Proceedings of the Korea Information Processing Society Conference (한국정보처리학회:학술대회논문집)

  • 2022.11a
  • /
  • Pages.556-558
  • /
  • 2022
  • /
  • 2005-0011(pISSN)
  • /
  • 2671-7298(eISSN)
Korea Information Processing Society (한국정보처리학회)
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Data Augmentation for Diabetic Retinopathy Grading in Fundus Images

안저 영상에서 당뇨병 망막병증 등급을 위한 data augmentation

  • Pham, Van-Nguyen (Department of Electrical and Computer Engineering, Sungkyunkwan University) ;
  • Choo, Hyunseung (Department of Electrical and Computer Engineering, Sungkyunkwan University)
  • ;
  • 추현승 (성균관대학교 전자전기컴퓨터공학과)
  • Published : 2022.11.21
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Abstract

Diabetic retinopathy (DR) is one of the leading diseases causing vision loss. Early detection of this disease has a crucial role in protecting patients' eyes. Recent works have achieved impressive result when performing DR detection on fundus images using deep learning. In the deep learning-based approach, data augmentation has significant impact on the result. Recently, many data augmentation policies have been proposed and achieved state-of-the-art performance on different tasks. In this work, we compare effects of three data augmentation policies on DR grading in fundus images.

Keywords

Acknowledgement

This work was supported by the BK21 FOUR Project, the MSIT(Ministry of Science and ICT), Korea, under the ICT Creative Consilience program(IITP-2022-2020-0-01821) supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation), the MSIT, under the Grand Information Technology Research Center support program (IITP-2022-2015-0-00742) supervised by the IITP, the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2020R1A2C2008447), and IITP grant funded by the Korea government (MSIT) (No.2021-0-02068, Artificial Intelligence Innovation Hub).