52 docs tagged with "research-only"

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

4800 AS-OCT images from 199 patients. Two tasks: angle closure classification and scleral spur localization.

1,136 OCT B-scans from 24 AMD patients. Expert annotations for 3 retinal fluid types (IRF, SRF, PED) and 3 retinal layer boundaries for joint layer and fluid segmentation.

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

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.

Semantic segmentation labels for 4,670 frames from 25 cataract surgery videos (CATARACTS challenge). 25 anatomy and instrument classes.

101 cataract surgery videos with 10-phase workflow annotations. Canonical older cataract benchmark.

1000 cataract surgery videos from multiple surgeons annotated for 10 surgical phases, instrument segmentation, and tool presence detection. First large-scale cataract surgical video dataset.

50 annotated 3D SD-OCT volumes (7,050 B-scans, 640×385 px) from subjects with vitreomacular adhesion (VMA, 25 eyes) and vitreomacular traction (VMT, 25 eyes). Each volume: 141 B-scans over 2×7×7 mm. A

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

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.

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

Paired low signal and high signal retinal OCT data used to study sparse acquisition, denoising, interpolation, and reconstruction in normal and non-neovascular AMD eyes.

110 OCT B-scans from 10 DME subjects with 8 layer boundaries and fluid region annotations by 2 clinicians.

OCT data from 384 subjects, including 269 with AMD and 115 normal subjects, with 38,400 B-scans and derived total retina and RPE-drusen complex thickness measurements.

Forty-five retinal OCT volumes acquired with a Spectralis system: 15 dry AMD, 15 diabetic macular edema, and 15 normal volumes. The official Duke release provides the study data.

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

Pediatric external-eye photographs with gaze-view annotations, corneal masks, eyelid/eyelash-line keypoints, and clinical tabular parameters for astigmatism-related research.

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

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

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

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

OCT challenge datasets from HDMILab covering retinal layer segmentation and fluid detection tasks from MICCAI/OMIA workshops. Includes sub-challenges such as AMD/CSC/DR classification and retinal laye

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

Two COCO-format instance-segmentation datasets derived from cataract surgery videos, covering instruments and anatomical structures.

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

High-speed head-mounted eye-region videos with pupil-center annotations under varied indoor, outdoor, eyewear, and lighting conditions.

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).

Longitudinal near-infrared iris images with subject, eye, age, sex, and ethnicity metadata used in ICE iris-recognition evaluations.

A collection of 640 retinal OCT images with expert choroidal region annotations for choroid segmentation.

500 subjects with OCTA volumes, vessel segmentation, FAZ (foveal avascular zone) annotations, and layer segmentation. Largest public OCTA dataset.

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

148 Heidelberg Spectralis SD-OCT volumes (~4,254 B-scans) for 3-class volume-level classification: Normal (50 volumes), AMD (48 volumes), DME (50 volumes). Variable B-scans per volume: 19, 25, 31, or

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.

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

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

112 OCT volumes from three vendors (Cirrus / Spectralis / Topcon) with pixel-level segmentation of intraretinal fluid (IRF), subretinal fluid (SRF), and pigment epithelium detachment (PED).

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.

Grand Challenge OCT classification dataset for diabetic-retinopathy related OCT classification.

400 macular OCT volumes; predict glaucoma Mean Deviation (MD, dB) from 24-2 Humphrey visual field test. Scalar regression task.

400 macular OCT volumes; predict 52-point Humphrey 24-2 visual field sensitivity map (0–100 dB per point). Multi-output regression.

400 macular OCT volumes; predict 52-point pattern deviation probability map from 24-2 Humphrey visual field test. Multi-output regression.

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

A collection of 1,800 preprocessed retinal OCT B-scans, with 600 images each for AMD, diabetic macular edema, and normal retina.

13,047 ultra-widefield fundus photographs (Optos, 200° FOV) from Tsukazaki Hospital, annotated with 8 binary disease labels: AO, AMD, DR, Glaucoma, MH, RD, RP, RVO. Associated with Scientific Data 202

600 Spectralis OCT B-scans from 24 exudative AMD subjects. Three fluid region classes: IRF, SRF, PED. Dual expert annotation.

Ultra-widefield fundus photographs for diabetic retinopathy grading (5-level ICDR scale). Released alongside the Reasoning-Enhanced VLM paper for interpretable UWF DR detection. Related to the UWF4DR