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---
language: en
license: mit
datasets:
- DDR
- FGADR
- IDRID
- MESSIDOR
- RETLES
library: torchSeg
model-index:
- name: unet_seresnext50_32x4d
results:
- task:
type: image-segmentation
dataset:
name: IDRID
type: IDRID
metrics:
- type: roc_auc
value: 0.6701094508171082
name: AUC Precision Recall - IDRID COTTON_WOOL_SPOT - COTTON_WOOL_SPOT
- type: roc_auc
value: 0.7860875129699707
name: AUC Precision Recall - IDRID EXUDATES - EXUDATES
- type: roc_auc
value: 0.6743975877761841
name: AUC Precision Recall - IDRID HEMORRHAGES - HEMORRHAGES
- type: roc_auc
value: 0.39846163988113403
name: AUC Precision Recall - IDRID MICROANEURYSMS - MICROANEURYSMS
- task:
type: image-segmentation
dataset:
name: FGADR
type: FGADR
metrics:
- type: roc_auc
value: 0.4449217915534973
name: AUC Precision Recall - FGADR COTTON_WOOL_SPOT - COTTON_WOOL_SPOT
- type: roc_auc
value: 0.6951484084129333
name: AUC Precision Recall - FGADR EXUDATES - EXUDATES
- type: roc_auc
value: 0.6508341431617737
name: AUC Precision Recall - FGADR HEMORRHAGES - HEMORRHAGES
- type: roc_auc
value: 0.2895563244819641
name: AUC Precision Recall - FGADR MICROANEURYSMS - MICROANEURYSMS
- task:
type: image-segmentation
dataset:
name: MESSIDOR
type: MESSIDOR
metrics:
- type: roc_auc
value: 0.3307325839996338
name: AUC Precision Recall - MESSIDOR COTTON_WOOL_SPOT - COTTON_WOOL_SPOT
- type: roc_auc
value: 0.7123324871063232
name: AUC Precision Recall - MESSIDOR EXUDATES - EXUDATES
- type: roc_auc
value: 0.3926454186439514
name: AUC Precision Recall - MESSIDOR HEMORRHAGES - HEMORRHAGES
- type: roc_auc
value: 0.4098129868507385
name: AUC Precision Recall - MESSIDOR MICROANEURYSMS - MICROANEURYSMS
- task:
type: image-segmentation
dataset:
name: DDR
type: DDR
metrics:
- type: roc_auc
value: 0.5084977746009827
name: AUC Precision Recall - DDR COTTON_WOOL_SPOT - COTTON_WOOL_SPOT
- type: roc_auc
value: 0.6117375493049622
name: AUC Precision Recall - DDR EXUDATES - EXUDATES
- type: roc_auc
value: 0.5447860956192017
name: AUC Precision Recall - DDR HEMORRHAGES - HEMORRHAGES
- type: roc_auc
value: 0.23405438661575317
name: AUC Precision Recall - DDR MICROANEURYSMS - MICROANEURYSMS
- task:
type: image-segmentation
dataset:
name: RETLES
type: RETLES
metrics:
- type: roc_auc
value: 0.5254419445991516
name: AUC Precision Recall - RETLES COTTON_WOOL_SPOT - COTTON_WOOL_SPOT
- type: roc_auc
value: 0.7039055824279785
name: AUC Precision Recall - RETLES EXUDATES - EXUDATES
- type: roc_auc
value: 0.5196094512939453
name: AUC Precision Recall - RETLES HEMORRHAGES - HEMORRHAGES
- type: roc_auc
value: 0.4127877354621887
name: AUC Precision Recall - RETLES MICROANEURYSMS - MICROANEURYSMS
---
# Lesions Segmentation in Fundus
## Introduction
We focus on the semantic segmentations of:
1. Cotton Wool Spot
2. Exudates
3. Hemmorrhages
4. Microaneurysms
For an easier use of the models, we refer to cleaned-up version of the code provided in the [fundus lesions toolkit](https://github.com/ClementPla/fundus-lesions-toolkit/tree/main/).
## Architecture
The model uses unet_seresnext50_32x4d as architecture. The implementation is taken from [torchSeg](https://github.com/isaaccorley/torchseg)
## Training datasets
The model was trained on the following datasets:
DDR, FGADR, IDRID, MESSIDOR, RETLES
## Resolution
The image resolution for training was set to 1024 x 1024.
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