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Retinal Image Dataset of Infants and Retinopathy of Prematurity

J. Timkovič, J. Nowaková, J. Kubíček, M. Hasal, A. Varyšová, L. Kolarčík, K. Maršolková, M. Augustynek, V. Snášel

. 2024 ; 11 (1) : 814. [pub] 20240723

Jazyk angličtina Země Anglie, Velká Británie

Typ dokumentu dataset, časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc24019693

Grantová podpora
GF22-34873K Grantová Agentura České Republiky (Grant Agency of the Czech Republic)
CZ.02.01.01/00/22_008/0004590 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
SP2024/071 Vysoká Škola Bánská - Technická Univerzita Ostrava (VŠB - Technical University of Ostrava)
CZ.02.1.01/0.0/ 0.0/15_003/0000466 EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj)
SP2024/071 Vysoká Škola Bánská - Technická Univerzita Ostrava (VŠB - Technical University of Ostrava)
CZ.02.01.01/00/22_008/0004590 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)

Retinopathy of prematurity (ROP) represents a vasoproliferative disease, especially in newborns and infants, which can potentially affect and damage the vision. Despite recent advances in neonatal care and medical guidelines, ROP still remains one of the leading causes of worldwide childhood blindness. The paper presents a unique dataset of 6,004 retinal images of 188 newborns, most of whom are premature infants. The dataset is accompanied by the anonymized patients' information from the ROP screening acquired at the University Hospital Ostrava, Czech Republic. Three digital retinal imaging camera systems are used in the study: Clarity RetCam 3, Natus RetCam Envision, and Phoenix ICON. The study is enriched by the software tool ReLeSeT which is aimed at automatic retinal lesion segmentation and extraction from retinal images. Consequently, this tool enables computing geometric and intensity features of retinal lesions. Also, we publish a set of pre-processing tools for feature boosting of retinal lesions and retinal blood vessels for building classification and segmentation models in ROP analysis.

Citace poskytuje Crossref.org

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