Cargando…
GRAPE: A multi-modal dataset of longitudinal follow-up visual field and fundus images for glaucoma management
As one of the leading causes of irreversible blindness worldwide, glaucoma is characterized by structural damage and functional loss. Glaucoma patients often have a long follow-up and prognosis prediction is an important part in treatment. However, existing public glaucoma datasets are almost cross-...
Autores principales: | Huang, Xiaoling, Kong, Xiangyin, Shen, Ziyan, Ouyang, Jing, Li, Yunxiang, Jin, Kai, Ye, Juan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10404253/ https://www.ncbi.nlm.nih.gov/pubmed/37543686 http://dx.doi.org/10.1038/s41597-023-02424-4 |
Ejemplares similares
-
PAPILA: Dataset with fundus images and clinical data of both eyes of the same patient for glaucoma assessment
por: Kovalyk, Oleksandr, et al.
Publicado: (2022) -
FIVES: A Fundus Image Dataset for Artificial Intelligence based Vessel Segmentation
por: Jin, Kai, et al.
Publicado: (2022) -
MSHF: A Multi-Source Heterogeneous Fundus (MSHF) Dataset for Image Quality Assessment
por: Jin, Kai, et al.
Publicado: (2023) -
Chákṣu: A glaucoma specific fundus image database
por: Kumar, J. R. Harish, et al.
Publicado: (2023) -
Multi-modal Dataset of a Polycrystalline Metallic Material: 3D Microstructure and Deformation Fields
por: Stinville, J. C., et al.
Publicado: (2022)