Fluid Segmentation in Retinal Optical Coherence Tomography (OCT)
About
Summary
This algorithm segments intraretinal fluid, subretinal fluid, and pigment epithelial detachments in OCT scans. Optimized for Spectralis, Cirrus and Topcon scanners. The data was developed with training data from the RETOUCH challenge.
This algorithm was developed by the Diagnostic Image Analysis Group and Amsterdam University Medical Center. It is currently maintained by Coen de Vente.
Mechanism
💾 Input and output
Users can upload their 3D OCT images and inspect the results using a web-based image viewer or directly download the segmentation masks. In the output masks, each fluid will be assigned a different scalar value:
- Intraretinal Fluid (IRF)
- Subretinal Fluid (SRF)
- Pigment Epithelium Detachments (PED)
Note, the algorithm works on full OCT scans, not on individual B-scans. For further input requirements, see the image upload page.
🕹 Algorithm description
The algorithm is the 3D variant of nnU-Net.
Interfaces
This algorithm implements all of the following input-output combinations:
Validation and Performance
Dice scores (std. dev.)¶
| IRF | SRF | PED | |
|---|---|---|---|
| Cirrus | 0.79 (0.07) | 0.71 (0.27) | 0.61 (0.31) |
| Spectralis | 0.76 (0.07) | 0.64 (0.28) | 0.73 (0.25) |
| Topcon | 0.54 (0.29) | 0.84 (0.08) | 0.76 (0.13) |
Uses and Directions
This algorithm was developed for research purposes only.