COph100: A comprehensive fundus image registration dataset from infants constituting the “RIDIRP” database

  • Yan Hu*
  • , Mingdao Gong
  • , Zhongxi Qiu
  • , Jiabao Liu
  • , Hongli Shen
  • , Mingzhen Yuan
  • , Xiaoqing Zhang
  • , Heng Li
  • , Hai Lu
  • , Jiang Liu*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on adult retinal pathologies with high-quality images, have limited number of image pairs and neglect clinical challenges. To address this gap, we introduce COph100, a novel and challenging dataset known as the Comprehensive Ophthalmology Retinal Image Registration dataset for infants with a wide range of image quality issues constituting the public “RIDIRP” database. COph100 consists of 100 eyes, each with 2 to 9 examination sessions, amounting to a total of 491 image pairs carefully selected from the publicly available dataset. We manually labeled the corresponding ground truth image points and provided automatic vessel segmentation masks for each image. We have assessed COph100 in terms of image quality and registration outcomes using state-of-the-art algorithms. This resource enables a robust comparison of retinal registration methodologies and aids in the analysis of disease progression in infants, thereby deepening our understanding of pediatric ophthalmic conditions.

Original languageEnglish
Article number99
JournalScientific data
Volume12
Issue number1
DOIs
Publication statusPublished - Dec 2025
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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