Retinal Image Dataset of Infants and Retinopathy of Prematurity
Jazyk angličtina Země Anglie, Velká Británie Médium electronic
Typ dokumentu dataset, časopisecké články
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)
PubMed
39043697
PubMed Central
PMC11266588
DOI
10.1038/s41597-024-03409-7
PII: 10.1038/s41597-024-03409-7
Knihovny.cz E-zdroje
- MeSH
- lidé MeSH
- novorozenec nedonošený * MeSH
- novorozenec MeSH
- počítačové zpracování obrazu MeSH
- retina * diagnostické zobrazování MeSH
- retinopatie nedonošených * diagnostické zobrazování MeSH
- Check Tag
- lidé MeSH
- novorozenec MeSH
- Publikační typ
- časopisecké články MeSH
- dataset MeSH
- Geografické názvy
- Česká republika MeSH
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.
Zobrazit více v PubMed
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