FARFUM-RoP, A dataset for computer-aided detection of Retinopathy of Prematurity.

Autor: Akbari M; Machine Vision Lab., Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, 9177948974, Iran., Pourreza HR; Machine Vision Lab., Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, 9177948974, Iran. hpourreza@um.ac.ir.; Faculty of Engineering, McMaster University, Hamilton, Ontario, L8S 4L7, Canada. hpourreza@um.ac.ir., Khalili Pour E; Department of Pediatric Ophthalmology, Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran, 1336616351, Iran. ekhalilipour@gmail.com., Dastjani Farahani A; Department of Pediatric Ophthalmology, Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran, 1336616351, Iran., Bazvand F; Department of Pediatric Ophthalmology, Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran, 1336616351, Iran., Ebrahimiadib N; Department of Pediatric Ophthalmology, Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran, 1336616351, Iran., Imani Fooladi M; Department of Pediatric Ophthalmology, Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran, 1336616351, Iran., Ramazani K F; Machine Vision Lab., Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, 9177948974, Iran.
Jazyk: angličtina
Zdroj: Scientific data [Sci Data] 2024 Oct 30; Vol. 11 (1), pp. 1176. Date of Electronic Publication: 2024 Oct 30.
DOI: 10.1038/s41597-024-03897-7
Abstrakt: 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.
(© 2024. The Author(s).)
Databáze: MEDLINE
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