ArticleScientific data2023
Chákṣu: A glaucoma specific fundus image database.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Retinal lesion annotation on fundus imaging: an interobserver variability study.Scientific reports · 2026Article
- AUBADE-syn: a novel deep learning ensemble method for glaucoma detection using synthetic fundus images on imbalanced datasets.NPJ digital medicine · 2026Article
- Mask of Truth: Model Sensitivity to Unexpected Regions of Medical Images.Journal of imaging informatics in medicine · 2026Article
- MIDAS: a technology-enabled hub-and-spoke system for the collection and dissemination of high-quality medical datasets in India.BMC medical informatics and decision making · 2025Article
- Optic Cup and Disc Segmentation of Fundus Images Using Artificial Intelligence Externally Validated With Optical Coherence Tomography Measurements.Translational vision science & technology · 2025Article
- A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset.Scientific data · 2025Article
- A hybrid multi model artificial intelligence approach for glaucoma screening using fundus images.NPJ digital medicine · 2025Article
- MIDAS: a new platform for quality-graded health data for AI-enabled healthcare in India.Nature medicine · 2024Article
- MAPLES-DR: MESSIDOR Anatomical and Pathological Labels for Explainable Screening of Diabetic Retinopathy.Scientific data · 2024Article
- A fundus image dataset for intelligent retinopathy of prematurity system.Scientific data · 2024Article
- EyeLiner: A Deep Learning Pipeline for Longitudinal Image Registration Using Fundus Landmarks.Ophthalmology scienceArticle
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
Abstract
We introduce Chákṣu-a retinal fundus image database for the evaluation of computer-assisted glaucoma prescreening techniques. The database contains 1345 color fundus images acquired using three brands of commercially available fundus cameras. Each image is provided with the outlines for the optic disc (OD) and optic cup (OC) using smooth closed contours and a decision of normal versus glaucomatous by five expert ophthalmologists. In addition, segmentation ground-truths of the OD and OC are provided by fusing the expert annotations using the mean, median, majority, and Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm. The performance indices show that the ground-truth agreement with the experts is the best with STAPLE algorithm, followed by majority, median, and mean. The vertical, horizontal, and area cup-to-disc ratios are provided based on the expert annotations. Image-wise glaucoma decisions are also provided based on majority voting among the experts. Chákṣu is the largest Indian-ethnicity-specific fundus image database with expert annotations and would aid in the development of artificial intelligence based glaucoma diagnostics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.