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

Summary: Can AI spot severe ROP? Study introduces FARFUM-RoP dataset to enhance AI-driven ROP diagnosis. #RetinopathyOfPrematurity #AIDiagnosis

Akbari M¹ ; Pourreza HR^{1, 2} ; Khalili Pour E³ ; Dastjani Farahani A³ ; Bazvand F³ ; Ebrahimiadib N³ ; Imani Fooladi M³ ; Ramazani K F¹
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.