Fundus image classification for diabetic retinopathy using disease severity grading

Aiki Sakaguchi, Renjie Wu, Seiichiro Kamata

研究成果: Conference contribution

8 被引用数 (Scopus)

抄録

Diabetic Retinopathy (DR) is ranked at the top of blindness causes. It progresses without subjective symptoms and leads to blindness in the worst case. However early detections and proper treatments can prevent visual disturbance. Because it takes time and cost for diagnoses by clinicians, research and development of diagnostic support systems has actively been conducted. This research aims to establish a fundus image classification method based on disease severity assessment for a diagnostic support by a fundus image analysis. In this paper, we propose a Graph Neural Network (GNN)-based method to improve accuracy for severity classification. Our method has two features. The first is to extract Region-Of-Interest (ROI) sub-images focusing on regions locally capturing lesions in order to minimize background noise in image preprocessing for the classification. The second is to utilize the GNN which is not yet applied for fundus image classification. In order to evaluate our proposed method, we use Indian Diabetic Retinopathy Image Dataset (IDRiD) utilized in "Diabetic Retinopathy: Segmentation and Grading Challenge" on Biomedical Imaging held at the IEEE International Symposium in 2018. We verified that the accuracy of our method improved 2.9% over the conventional method in this contest.

本文言語English
ホスト出版物のタイトルProceedings of the 2019 9th International Conference on Biomedical Engineering and Technology, ICBET 2019
出版社Association for Computing Machinery
ページ190-196
ページ数7
ISBN(電子版)9781450361309
DOI
出版ステータスPublished - 2019 3 28
イベント9th International Conference on Biomedical Engineering and Technology, ICBET 2019 - Tokyo, Japan
継続期間: 2019 3 282019 3 30

出版物シリーズ

名前ACM International Conference Proceeding Series

Conference

Conference9th International Conference on Biomedical Engineering and Technology, ICBET 2019
国/地域Japan
CityTokyo
Period19/3/2819/3/30

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • コンピュータ ビジョンおよびパターン認識
  • 人間とコンピュータの相互作用
  • ソフトウェア

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