Fundus Image Registration Dataset
Fundus Image Registration Dataset (FIRE) is a dataset consisting of 129 retinal images forming 134 image pairs. These image pairs are split into 3 different categories depending on their characteristics. The images were acquired with a Nidek AFC-210 fundus camera, which acquires images with a resolution of 2912x2912 pixels and a FOV of 45° both in the x and y dimensions. Images were acquired at the Papageorgiou Hospital, Aristotle University of Thessaloniki, Thessaloniki from 39 patients.
Variants: FIRE
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Image Registration | LKRetina | Reverse Knowledge Distillation: Training a … | 2023-07-20 |
| Image Registration | SuperRetina | Semi-Supervised Keypoint Detector and Descriptor … | 2022-07-16 |
| Image Registration | REMPE, JBHI 2020 | Semi-Supervised Keypoint Detector and Descriptor … | 2022-07-16 |
| Image Registration | PBO, ICIP 2010 | Semi-Supervised Keypoint Detector and Descriptor … | 2022-07-16 |
| Image Registration | GLAMpoints, ICCV 2019 | GLAMpoints: Greedily Learned Accurate Match … | 2019-08-19 |
Recent papers with results on this dataset: