62 docs tagged with "oct"

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

3,049 OCT B-scan images (1,140×380 px) from 138 wet AMD patients (156 eyes) with pixel-level annotations for 5 lesion classes: Subretinal Fluid (SRF), Intraretinal Fluid (IRF), Ellipsoid Zone Continui

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.

1,168 anterior-segment OCT images of keratitis with per-pixel lesion, cornea, and iris segmentation labels. Enables 3D reconstruction from B-scan stacks.

Surgical-microscope and intraoperative-OCT data for autonomous robotic retinal-vein cannulation in ex vivo porcine eyes.

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

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

Swept-source OCT volumes for AMD and DME with three-dimensional pigment epithelial detachment and intraretinal-fluid masks.

Right-eye corneal OCT and rotating Scheimpflug tomography data with MATLAB code for automatic corneal-layer segmentation.

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

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

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.

~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

SD-OCT B-scans with bounding-box and polygon annotations for paracentral acute middle maculopathy lesions.

Repeated light/dark SD-OCT acquisitions and retinal reflectivity profiles from healthy, neuromyelitis-optica, and Alzheimer groups.

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

300 circumpapillary OCT images. RNFL/GCIPL/choroid layer segmentation plus binary glaucoma classification.

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

1,000 patients with OCT RNFLT maps (225×225), visual field measurements, and demographics for glaucoma detection (binary) and longitudinal progression forecasting (6 definitions). First public glaucom

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.

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

OCT screen recordings, annotated frames, and pressure data from robot-assisted subretinal injections in ex vivo porcine eyes.

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

OCT images for intraretinal cystoid-fluid segmentation, partly derived from public OCT DME sources with expert-selected masks.

~84,000 retinal OCT B-scan images across 4 classes: CNV, DME, DRUSEN, NORMAL. Train: ~83,484 / Test: 1000.

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

~30,000 longitudinal OCT B-scans across multiple patient visits, annotated for AMD change detection and progression monitoring.

6,272 AS-OCT images + 392 anterior-segment photographs for corneal opacity assessment with expert grading. First large public multimodal AS-OCT + photo dataset for cornea.

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

Anonymized clinical metadata and automated 3D OCT segmentation volumes for neovascular age-related macular degeneration.

Longitudinal quantitative OCT biomarkers and treatment-response variables for predicting visual acuity in neovascular AMD.

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

Retinal OCT B-scans from Noor Eye Hospital for classification of Normal, Drusen, and CNV (choroidal neovascularisation) cases. 16,822 B-scans from 441 eyes (Normal 120 / Drusen 160 / CNV 161 eyes).

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

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

35 Spectralis OCT volumes (1,715 B-scans) with 9 manually delineated retinal layer boundaries. 14 healthy controls, 21 MS subjects.

A set of 1,110 optic nerve head OCT volumes from 624 patients, including 847 scans with primary open angle glaucoma and 263 healthy scans.

1,672 OCT B-scans from AMD, DME, and healthy controls with 5,016 multi-grader layer annotations + lesion detection labels.

198 annotated 3D SD-OCT volumes (3,762 B-scans) with pixel-level labels for 13 anatomic and pathological retinal features: retina, choroid, vitreous, RPE, hyaloid, ERM, fluid, subretinal material, hyp

2,000+ OCT images labeled for 7 conditions: AMD, DME, ERM, NO (normal), RAO, RVO, VID.

500 OCT images: NORMAL (206), AMD (50), CSC (128), DR (59), MH (57). High-resolution B-scans for 5-class classification.

3,859 OCT B-scan images (125 eyes, 119 patients) for macular hole segmentation. Each PNG is side-by-side: left half raw B-scan, right half colour-coded mask for 4 classes: Retina, Macular Hole, Intrar

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.

High-resolution swept-source OCT images and mechanical-model data for outer retinal corrugations in rhegmatogenous retinal detachment.

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

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

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).

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

3,012 OCT B-scans from 146 eyes / 130 patients with retinal vein occlusion. Dual-task labels: fluid segmentation + retinal-layer segmentation. Detection of macular lesions.

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.

Synthetic circumpapillary OCT images for healthy and glaucomatous eyes with retinal-layer masks and RNFL thickness values.

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

10 Heidelberg Spectralis SD-OCT volumes (510 B-scans, 496×644×51 voxels) from healthy subjects with 8 retinal layer boundary annotations by 2 independent observers. MATLAB .mat format; used as the OCT

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

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