121 docs tagged with "fundus"

705 optic disc-centred fundus photographs (396 normal + 309 glaucoma) from Hospital Clinico San Carlos. Expert-annotated binary glaucoma classification.

1200 fundus images for AMD classification, five-class lesion segmentation, fovea/optic disc localisation.

One hundred retinal fundus images from Armed Forces Institute of Ophthalmology, Rawalpindi, with expert annotations for vessels and hypertensive retinopathy, diabetic retinopathy, and papilledema task

The first public AGAR300 release contains 28 color fundus images with microaneurysms, captured at a 45 degree field of view and 2448 by 3264 pixel resolution.

~113,893 color fundus images labelled as referable glaucoma (RG), no referable glaucoma (NRG), or ungradable. Large-scale, multi-ethnic, multi-site screening dataset.

Two thousand preprocessed fundus images compiled from six public sources for normal, diabetes, cataract, and age-related macular degeneration classification.

De-identified fluorescein and indocyanine-green angiography images paired with structured lesion descriptions and reports.

Augmented ODIR-5K fundus photographs for 8-class ocular disease classification: Normal, Diabetes, Glaucoma, Cataract, AMD, Hypertension, Myopia, Other. Preprocessing includes CLAHE and standard augmen

3662 fundus images from Aravind Eye Hospital, graded 0-4 for diabetic retinopathy severity.

Segmentation masks for the vascular arcade and optic nerve head derived from APTOS 2019 fundus images.

Small four-class eye-disease image dataset with normal, cataract, glaucoma, and retinal disease categories.

One thousand seven hundred eighty-six original color fundus images for diabetic retinopathy, age-related macular degeneration, and glaucoma grading/classification.

Fundus photographs from Bangladesh Eye Hospital for glaucoma detection. Includes optic cup/disc crops and vessel segmentation masks alongside binary glaucoma/normal labels.

35,126 fundus images for 5-class diabetic retinopathy grading (No DR: 25,810 / Mild: 2,443 / Moderate: 5,292 / Severe: 873 / Proliferative: 708). Available via Kaggle.

16,266 color fundus images from 8,524 Brazilian patients with 14 disease labels (DR, AMD, glaucoma, drusen, others), image quality flags, and demographic attributes.

601 fundus images in 4 classes: Normal, Cataract, Glaucoma, and Retina Disease. Intended for ocular disease classification.

Fundus photographs and segmentation masks for subretinal fluid in central serous chorioretinopathy, with healthy-eye classification controls.

1,345 fundus images captured across multiple camera manufacturers with OD/OC segmentation + glaucoma classification labels.

28 fundus images with manual vessel segmentations (two annotators).

Composite fundus and OCT dataset with retinal layer, retinal lesion, and macular/glaucomatous disorder markings.

100 infant eyes with 491 image pairs annotated with ground-truth control points and vessel masks. Enables pediatric / ROP-relevant fundus registration research.

Fundus photographs grouped for corneal curvature prediction, with 50 images per group.

187 cataract cases with color fundus images and paired professional cataract-grading diagnostic reports. Designed for medical multimodal-LLM evaluation.

Fifty OCT and fundus images with healthy/glaucomatous labels and cup-to-disc ratio annotations by ophthalmologists.

12522 fundus images with DR grading (0-5) and lesion-level segmentation annotations.

2,000 regular fundus images (500 patients × 2 fields × 2 eyes) plus 256 ultra-widefield fundus images labeled for DR severity (ICDR grades 0-4) and image quality assessment (gradable/ungradable). From

15,709 fundus images with paired medical reports and extracted keywords. Only public fundus report-generation dataset — useful for VLM / captioning evaluation.

Fundus-image VQA dataset for diabetic macular edema derived from IDRiD and e-ophtha.

35,126 fundus images organised for 5-class DR severity grading (ICDR grades 0-4): No DR 25,810 / Mild 2,443 / Moderate 5,292 / Severe 873 / Proliferative 708. Hosted on Alibaba Tianchi.

Extension of the DME VQA dataset with logical-relation consistency annotations.

Fifty color fundus images with expert markings of diabetic retinopathy lesions, blood vessels, optic disc, and macula.

110 color fundus images with optic-disc contour annotations by two experts. Foundational OD-segmentation dataset.

101 fundus images annotated for optic disc and cup segmentation by 4 clinicians. Train/test: 50/51.

Forty color fundus photographs from a diabetic retinopathy screening program, divided into 20 training and 20 test images, with vessel reference annotations and field of view masks.

3,100 paired two-field fundus images with DR grading labels. Only public two-field paired DR benchmark.

463 color fundus images with pixel-level segmentation: 82 with exudate (EX) + 381 with microaneurysm (MA) annotations. Standard DR lesion-segmentation benchmark.

Original and augmented eye-disease image dataset covering retinitis pigmentosa, retinal detachment, pterygium, myopia, macular scar, glaucoma, disc edema, diabetic retinopathy, central serous choriore

~102K VQA pairs derived from 58,485 images across 8 ophthalmic modalities (fluorescein angiography, ICGA, OCT, CFP, ultrasound biomicroscopy, slit-lamp, fundus auto-fluorescence, CT) covering 100+ dis

~88,000 fundus images graded 0–4 for DR severity. Largest public DR dataset; competition images from EyePACS clinics.

Quality labels for 28,792 EyePACS fundus images, graded as good, usable, or reject and divided into the original EyePACS train and test partitions.

Ophthalmic clinical text + NPZ records covering glaucoma, cataract, and neuro-ophthalmology with paired age, sex, race/ethnicity, and language attributes. Derived from the same Harvard clinical popula

Wide-field fundus images from premature infants for ROP staging (Stages 1–5 + Plus Disease). Expert-annotated for AI-assisted ROP diagnosis and screening.

Fundus fluorescein angiography images paired with Chinese and translated English reports for report-generation research.

A set of 2,246 fundus images with continuous mean opinion scores from 0 to 100, three quality grades, and the individual scores of six ophthalmologists.

129 fundus images from 39 patients forming 134 registration pairs with anatomical ground-truth control points. Only public registration benchmark for ophthalmology.

800 high-resolution (2048x2048) fundus images with pixel-wise vessel segmentation. Covers normal, DR, AMD, glaucoma.

40 patients with paired pre-operative fundus images and intra-operative biomicroscopy video clips. Annotated for optic disc and vessel segmentation across domains.

Fundus photography, multispectral and functional retinal imaging, retinal blood-flow and pupillary-light videos, retina-characteristic labels, quality labels, demographics, and psychological assessmen

Five-domain optic disc/cup segmentation benchmark composed from REFUGE, Drishti-GS, ORIGA, RIGA, and related sources.

1,099 pediatric fundus images from 483 premature infants annotated for retinopathy of prematurity (ROP) staging. Standard fundus (RetCam) — not ultra-widefield; `rop_uwf_intelligent` is retained as th

Seventy retinal image pairs with visible myopia development and manually annotated corresponding control points.

Fundus/UWF image-report dataset derived from DeepDRiD and OUWFD-style resources for report-generation research.

100 high-resolution color fundus images with pixel-wise artery / vein / crossing labels from a mixed disease cohort.

1020 fundus images with binary glaucoma labels (697 normal, 323 glaucoma), plus optic disc/cup annotations.

300 paired fundus + 3D OCT volumes. Glaucoma grading into Normal / Early / Advanced plus OD/OC segmentation and fovea location.

263 eyes × 1,115 visits. Multi-modal: VF (HFA 24-2), fundus photographs, OCT RNFL, IOP, CCT. Labels: VF progression, OD segmentation, glaucoma stage.

Fundus images for glaucoma detection from Harvard Medical School / Mass Eye and Ear. Binary glaucoma classification.

30,000 subjects (10K each AMD, DR, glaucoma) with paired SLO fundus and OCT B-scans, demographic attributes (race, ethnicity, gender, language), for fairness analysis.

A collection of 169 fundus photographs with expert exudate and bright lesion annotations, clinical metadata, optic nerve locations, vessel estimates, and image quality scores.

4,011 color fundus images labeled for high-myopia vs pathological-myopia classification — largest public dataset for HM/PM separation.

Extended HRF annotations for optic disc, cup, retinal vessels, and alpha/beta peripapillary zones.

45 high-resolution fundus images (healthy/DR/glaucoma) with manual vessel segmentation.

High-resolution fundus images from Hillel Yaffe Medical Center for age-related macular degeneration diagnosis.

747 fundus images from 288 patients with glaucoma labels confirmed by paired OCT + visual field. First public dataset with gold-standard multimodal glaucoma confirmation.

400 training fundus images with AMD classification (non-AMD vs AMD) and lesion annotations. Challenge dataset from ISBI 2020.

516 fundus images with DR grade (0-4), macular edema grade (0-2), and pixel-level lesion segmentation for 81 images.

Retinal fundus dataset for five-class diabetic-retinopathy grading.

9,939 color fundus images from Japanese patients with DR grading labels (Davis grading scale).

Multi-modal retinal vessel segmentation dataset spanning fluorescence angiography, fundus autofluorescence, and infrared imaging.

1,000 fundus images spanning 39 ophthalmic disease categories from the Joint Shantou International Eye Center. Used for multi-class fundus disease classification.

101,442 gradable fundus images labeled as referable (RG) or non-referable (NRG) for glaucoma. Image data from EyePACS LLC; labels from Rotterdam Eye Hospital expert graders.

11,760 fundus images with glaucoma classification labels and ophthalmologist-derived attention maps. Largest public glaucoma dataset with attention ground truth.

Composite multimodal ophthalmology benchmark with multi-granular anatomical, diagnostic, staging, demographic, and text annotations.

Anonymized retinal fundus images from an ophthalmology clinic in M'Sila, Algeria for diabetic-retinopathy classification.

198 fundus images (from MESSIDOR) with pixel-wise segmentation for 10 biomarkers (lesions + structures) + DR and ME severity grades.

5,164 fundus images from 1,291 patients captured with the Phelcom Eyer handheld smartphone-based fundus camera. Labels for DR grading + clinical/demographic prediction.

1748 fundus images with DR grading (0-3 Retinopathy Grade) and macular edema risk (0-2).

34,452 fundus images from 4,344 patients across multiple fields per eye, with DR screening labels. Largest public four-field DR dataset.

Ophthalmology-specific multimodal reasoning dataset built from 45 public datasets. Chain-of-thought reasoning traces for retinal VQA.

Multi-modal DR dataset combining color fundus photographs (CFP), OCT B-scans, and ultra-widefield (UWF) fundus images, annotated for DR detection and severity grading. Published in Nature Scientific D

Multi-source heterogeneous retinal fundus image-quality assessment dataset for training and evaluating quality-control models.

58,036 fundus + 45,923 OCT images assembled for multi-disease classification (8 classes) with cross-modal distillation. Sourced from multiple public ophthalmic datasets.

2,208 color fundus images with 20-class multi-label disease annotations.

Public sample fundus photographs and measurements for modeling myopic regression after corneal refractive surgery.

Augmented DRIVE, STARE, and CHASE_DB1 vessel-segmentation images for out-of-distribution robustness evaluation.

Linked color fundus and macular OCT images for diabetic macular edema and diabetic retinopathy classification, with CSV labels and shared patient/eye/image nomenclature.

8000 patients (16000 fundus images, left + right eye) with 8 disease labels for multi-label ocular disease classification.

Longitudinal OCT + fundus dataset from AMD/DME patients across multiple clinical visits. 9,408 OCT B-scans have biomarker labels for 8 categories (fluid, drusen, scarring, PED variants, etc.); 78,000+

Ophthalmic visual question-answering benchmark dataset released as supplementary data for evaluating multimodal language models in ophthalmology.

Paired tabletop and portable retinal images from the same patients, enabling cross-device domain-adaptation research.

1200 fundus images for pathologic myopia classification and optic disc / lesion segmentation. 50 % PM / 50 % non-PM.

488 fundus images from 244 patients (both eyes). Expert OD/OC segmentation, glaucoma stage, IOP, and clinical metadata.

757 color fundus images from a Paraguayan cohort with 7-class DR grading labels. Adds Latin-American representation.

Fundus-photography dataset for retinal artery occlusion diagnosis, based on web-derived public data and public fundus datasets.

42 infrared reflectance fundus images with separate artery and vein segmentation masks. 23 train / 19 test.

Fundus-image benchmark with retinal vessel branching-angle annotations for evaluating branching-angle detection and measurement algorithms.

One hundred twenty paired low quality and high quality clinical fundus photographs of the same eyes at 2560 by 2560 pixels for image restoration and enhancement research.

1200 fundus images: 400 train, 400 val, 400 test. Labels: glaucoma/non-glaucoma + optic disc/cup segmentation.

1200 fundus images from REFUGE1 with optic disc/cup segmentation masks annotated by multiple expert raters.

2000 fundus images for glaucoma classification, optic disc/cup segmentation, and fovea localisation. Extends REFUGE1.

Retinal vessel analysis benchmark with vessel masks, artery/vein masks and skeletons, bifurcation points, vascular trees, and abnormality annotations.

Fundus images and age labels for retinal age prediction and regression.

Baseline and two-year follow-up color fundus image pairs from Tianjin Medical University for diabetic-retinopathy progression research.

6,004 pediatric RetCam fundus images from 188 newborns in Ostrava (Czech Republic), annotated for retinopathy of prematurity (ROP) screening + classification.

Auxiliary RFMiD 2.0 retinal fundus dataset spanning 51 disease categories.

3200 fundus images annotated for 45 retinal conditions. Used for multi-label disease classification.

750 fundus images with optic disc and optic cup segmentations from 6 ophthalmologists per image. Multi-rater benchmark.

RIGA/MESSIDOR-derived benchmark for optic disc and cup segmentation domain adaptation.

485 fundus images (313 normal, 172 glaucoma) with optic disc region of interest crops for deep learning.

40 fundus images (derived from DRIVE) with artery/vein annotations and vessel-tree structural labels.

100 fundus images with microaneurysm annotations from the Retinopathy Online Challenge.

~12,000 fundus images aggregated from 19 public glaucoma datasets with standardized disc/cup/vessel channels and unified labels. CC0 — fully public domain.

20 fundus images with manual vessel segmentation (two annotators).

1,219 color fundus images with DR severity grading + pixel-level exudate segmentation masks. Multi-center (SUSTech + Sun Yat-sen University).

Retinopathy-of-prematurity fundus-image dataset and synthetic-image resources for privacy-preserving AI training.

Fundus photographs for ocular toxoplasmosis detection: active toxoplasmosis, inactive (scarred) lesions, and normal. ~412 images total (adult + pediatric cases).

Portable fundus images and segmentations for retinal microvascular network analysis.

Extension of TREND portable fundus imaging for chronic-disease and microvascular analysis.

Fundus and synthetic OCTA vessel-segmentation resource for domain-transfer research.

A multilabel fundus classification challenge with 3,435 labeled training images and 350 test images covering six disease groups and normal findings.

Ophthalmic image-text VQA/reasoning benchmark with retinal modalities and expert-verified question-answer pairs.