Dataset

This dataset was created by Toaha Rahman Ratul

Contents

A new clinical database, ACRIMA, has been made publicly available, containing 705 labelled images. It is composed of 396 glaucomatous images and 309 normal images. Additionally, python scripts used to obtain the presented results are also available.

Z. Zhang et al., "ORIGA-light: An online retinal fundus image database for glaucoma analysis and research," 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, Buenos Aires, Argentina, 2010, pp. 3065-3068, doi: 10.1109/IEMBS.2010.5626137.Huazhu Fu, Fei Li, José Ignacio Orlando, Hrvoje Bogunović, Xu Sun, Jingan Liao, Yanwu Xu, Shaochong Zhang, Xiulan Zhang, July 9, 2019, "REFUGE: Retinal Fundus Glaucoma Challenge", IEEE Dataport, doi: https://dx.doi.org/10.21227/tz6e-r977.https://www.kaggle.com/datasets/arnavjain1/glaucoma-datasets

Dataset

This dataset was created by Nihal Morshed

Contents

1) Data Introduction • The Glaucoma Classification Datasets is a collection of fundus image datasets designed for the early detection and classification of glaucoma. Each image is labeled with a binary class indicating the presence or absence of glaucoma (Glaucoma / Normal).

2) Data Utilization (1) Characteristics of the Glaucoma Classification Datasets: • The dataset integrates five major publicly available fundus image datasets: DRISHTI-GS, RIM-ONE, ACRIMA, ORIGA, and G1020. • It consists of high-resolution images that capture abnormalities in the optic disc and surrounding structures, making it suitable for glaucoma diagnosis.

(2) Applications of the Glaucoma Classification Datasets: • Development of automated glaucoma classification models: The dataset can be used to train deep learning models that automatically classify normal and glaucomatous eyes based on morphological features such as optic disc size and vascular patterns. • Early diagnosis support systems: The dataset can help build AI-powered early warning systems that visually detect early signs of glaucoma.