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Farfum-Rop, a Dataset for Computer-Aided Detection of Retinopathy of Prematurity Publisher Pubmed



Akbari M1 ; Pourreza HR1, 2 ; Khalili Pour E3 ; Dastjani Farahani A3 ; Bazvand F3 ; Ebrahimiadib N3 ; Imani Fooladi M3 ; Ramazani K F1
Authors
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Authors Affiliations
  1. 1. Machine Vision Lab., Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, 9177948974, Iran
  2. 2. Faculty of Engineering, McMaster University, Hamilton, L8S 4L7, ON, Canada
  3. 3. Department of Pediatric Ophthalmology, Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran, 1336616351, Iran

Source: Scientific Data Published:2024


Abstract

Retinopathy of Prematurity (ROP) is a critical eye disorder affecting premature infants, characterized by abnormal blood vessel development in the retina. Plus Disease, indicating severe ROP progression, plays a pivotal role in diagnosis. Recent advancements in Artificial Intelligence (AI) have shown parity with or surpass human experts in ROP detection, especially Plus Disease. However, the success of AI systems depends on high-quality datasets, emphasizing the need for collaboration and data sharing among researchers. To address this challenge, the paper introduces a new public dataset, FARFUM-RoP (Farabi and Ferdowsi University of Mashhad’s ROP dataset), comprising 1533 ROP fundus images from 68 patients, annotated independently by five experienced childhood ophthalmologists as “Normal,” “Pre-Plus,” or “Plus.” Ethical principles and consent were meticulously followed during data collection. The paper presents the dataset structure, patient details, and expert labels. © The Author(s) 2024.