OCT Retinal Dataset
Dataset of volumetric OCT scans of retinal layers with annotations for structural segmentation and disease diagnosis.
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-
- Scans
- 1,000
-
- B-scans per volume
- 100
- Medicine
- Computer vision
- Machine Learning
- Segmentation
- Classification
-
- Scans
- 1,000
-
- B-scans per volume
- 100
Dataset Info
| Characteristic | Data |
| Description | Volumetric OCT scans (B-scans) of the retina with annotated layers, fluid regions, and clinical diagnoses |
| Data types | DiCOM |
| Annotation | Retinal layer boundaries, fluid regions, diagnosis labels (normal/AMD/diabetic/glaucoma). |
| Tasks | Recognition, classification and segmentation of pathologies, computer vision |
| Number of files | 1,000 |
| Labeling | Metadata(age, gender, device model, scan position) |
Technical
Characteristics
| Characteristic | Data |
| File Extension | DiCOM |
| File Resolution | Min = 512×512 px |
| Labeling Format | Json |
Industries
Medicine and Healthcare
-
Disease Diagnosis:
Utilizing OCT scans to detect and classify various retinal diseases such as AMD, diabetic retinopathy, glaucoma.
-
Telemedicine:
Enabling remote diagnosis by ophthalmologists via AI-assisted analysis.
-
Personalized Treatment Planning:
Tracking disease progression and treatment efficacy through structural segmentation.
Education
-
Medical training:
Using annotated OCT scans to teach students about retinal anatomy, pathology, and segmentation techniques.
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