43 docs tagged with "unknown"

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.

Expert-curated ophthalmology multiple-choice benchmark with rationales, assembled for held-out language-model evaluation.

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.

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

1,500 in-vivo confocal microscopy images of corneal subbasal nerve plexus, graded for tortuosity (4 levels). Train: 1,200 / Test: 300. 384×384 px, 400×400 µm FOV.

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.

Twenty OCT volumes with 220 selected B-scans from eyes with non-neovascular AMD, drusen, and geographic atrophy, including manual and automated pathology markings.

Precomputed image embeddings for BRSET and mBRSET to support efficient ophthalmic AI research without raw-image redistribution.

5,381 B-scan ocular ultrasound video clips with retinal-detachment presence and macula-on/off status labels. Total runtime approximately 5 hours 10 minutes. Only public ocular ultrasound video benchma

~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

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

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

Fundus-focused text dataset for LLM/RAG workflows.

Large fundus-related multilingual text corpus for LLM pretraining or retrieval.

Indoor and outdoor panoramic-camera recordings with continuous three-dimensional gaze labels across wide head poses and distances.

Crowdsourced iPhone and iPad face videos with screen-fixation coordinates for appearance-based mobile gaze estimation.

HD-OCT scans and clinical outcome variables for macular-hole visual-improvement prediction after surgery.

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

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.

Corneal map images for three-class keratoconus detection.

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

One thousand infrared meibography images with meibomian-gland masks, eyelid masks, and six rounds of expert meiboscore grading.

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

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

160,185 video clip-instruction pair samples from 9,819 ophthalmic surgical videos, covering multiple procedure types. Designed for text-guided surgical video generation and understanding. Published at

Ophthalmology-focused PubMed text corpus for retrieval, pretraining, or RAG experiments.

Text-only ophthalmology explanatory/free-form question-answering dataset for LLM training/evaluation.

Text-only ophthalmology multiple-choice question-answering dataset for LLM training/evaluation.

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

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.

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

~24,000 retinal OCT images across 8 disease classes: AMD, BRAO, BRVO, CSC, CRAO, CRVO, DME, MH.

~2,617 annotated slit-lamp frames covering anterior-segment anatomy + multi-lesion detection (cataract, corneal disease, conjunctivitis).

Restricted corneal confocal microscopy image set with pixel-level corneal-nerve masks annotated for high-precision segmentation.

Head-mounted eye images with pupil, iris, eyelid, eyeball, gaze, landmark, segmentation, and eye-movement annotations.

Visible-light iris images captured at a distance and on the move with realistic blur, reflection, occlusion, pose, and illumination noise.

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.