Annotated dataset for retinal fundus image segmentation: vascular arcade and optic nerve head
- 1Escuela de Ciencias de la Salud, Universidad Autónoma de Baja California, Carretera Transpeninsular S/N, Valle Dorado, 22890 Ensenada, BC México
- 2Facultad de Ingeniería, Arquitectura y Diseño, Universidad Autónoma de Baja California, Carretera Transpeninsular 3917, Playitas, 22860 Ensenada, BC México
Abstract
Objectives: Digital fundoscopy is an ophthalmological technique used to evaluate the posterior segment of the eye, including the retina and its anatomical structures [1]. This technique acquires fundus images, visually documenting the aforementioned structures. This dataset was generated from a subset of images from the public Asia Pacific Tele-Ophthalmology Society 2019 Blindness Detection (APTOS 2019 BD) dataset [2], these were manually annotated to generate segmentation masks of anatomical fundus structures, specifically the vascular arcade and the optic nerve head. We contribute to the development and evaluation of artificial intelligence models under comparable conditions by generating data to serve as input for segmentation models, thereby supporting the design of more efficient algorithms for the automated identification of ophthalmological structures [3, 4].
Data description: This dataset consists of 500 masks generated from 500 images randomly selected from the APTOS 2019 BD dataset [2]. These are non-homogeneous color fundus images containing global labels for pathological alterations, illumination, as well as varying image resolutions. Image dimensions vary from 474 × 358 pixels to 4288 × 2848 pixels. This dataset provides manual masks for specific ophthalmic structures.
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BibTeX
@article{figueroagarza2026annotated,
title = {{Annotated dataset for retinal fundus image segmentation: vascular arcade and optic nerve head}},
author = {Bryan Alejandro Figueroa-Garza and Betsaida Lariza López-Covarrubias and Laura Johana González-Zazueta and Christian Xavier Navarro-Cota and Mabel Vázquez-Briseño and Juan Iván Nieto-Hipólito and Gener José Avilés-Rodríguez},
journal = {BMC Research Notes},
year = {2026},
month = aug,
doi = {10.1186/s13104-026-07957-6},
url = {https://doi.org/10.1186/s13104-026-07957-6},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Annotated dataset for retinal fundus image segmentation: vascular arcade and optic nerve head
AU - Bryan Alejandro Figueroa-Garza
AU - Betsaida Lariza López-Covarrubias
AU - Laura Johana González-Zazueta
AU - Christian Xavier Navarro-Cota
AU - Mabel Vázquez-Briseño
AU - Juan Iván Nieto-Hipólito
AU - Gener José Avilés-Rodríguez
PY - 2026
DA - 2026/08/07
JO - BMC Research Notes
DO - 10.1186/s13104-026-07957-6
UR - https://doi.org/10.1186/s13104-026-07957-6
AB - Objectives: Digital fundoscopy is an ophthalmological technique used to evaluate the posterior segment of the eye, including the retina and its anatomical structures [1]. This technique acquires fundus images, visually documenting the aforementioned structures. This dataset was generated from a subset of images from the public Asia Pacific Tele-Ophthalmology Society 2019 Blindness Detection (APTOS 2019 BD) dataset [2], these were manually annotated to generate segmentation masks of anatomical fundus structures, specifically the vascular arcade and the optic nerve head. We contribute to the development and evaluation of artificial intelligence models under comparable conditions by generating data to serve as input for segmentation models, thereby supporting the design of more efficient algorithms for the automated identification of ophthalmological structures [3, 4]. Data description: This dataset consists of 500 masks generated from 500 images randomly selected from the APTOS 2019 BD dataset [2]. These are non-homogeneous color fundus images containing global labels for pathological alterations, illumination, as well as varying image resolutions. Image dimensions vary from 474 × 358 pixels to 4288 × 2848 pixels. This dataset provides manual masks for specific ophthalmic structures.
SN - 1756-0500
ER -