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pith:EATLRC4T

pith:2025:EATLRC4TQHO4QBCKXUSSODUAFU

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FunduSegmenter: Leveraging the RETFound Foundation Model for Joint Optic Disc and Optic Cup Segmentation in Retinal Fundus Images

Emanuele Trucco, Muthu Rama Krishnan Mookiah, Zhenyi Zhao

Adapting RETFound with new adapters and a decoder enables accurate joint optic disc and optic cup segmentation in fundus images.

arxiv:2508.11354 v3 · 2025-08-15 · cs.CV · cs.AI · cs.LG

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Claims

C1strongest claim

This study introduces the first adaptation of RETFound for joint optic disc (OD) and optic cup (OC) segmentation. ... An average Dice similarity coefficient of 90.51% was achieved in internal verification, which outperformed all baselines, some substantially (nnU-Net: 82.91%; DUNet: 89.17%; TransUNet: 87.91%). In all external verification experiments, the average results were about 3% higher than those of the best baseline.

C2weakest assumption

The assumption that the proposed modules (Pre-adapter, Decoder, Post-adapter, CBAM skip connections, and ViT block adapter) transfer usefully to other foundation models and that performance on the tested mix of proprietary and public datasets indicates reliable behavior on unseen clinical data sources.

C3one line summary

FunduSegmenter adapts RETFound with custom adapters and attention modules to reach 90.51% average Dice score for optic disc and cup segmentation, outperforming baselines on internal and external tests across five datasets.

References

49 extracted · 49 resolved · 5 Pith anchors

[1] Zhou, Y ., Chia, M. A., Wagner, S. K., Ayhan, M. S., Williamson, D. J., Struyven, R. R., ... & Keane, P . A. (2023). A foundation model for generalizable disease detection from retinal images. Nature, 2023

[2] Mookiah, M. R. K., Hogg, S., MacGillivray, T., & Trucco, E. (2021). On the quantitative effects of compression of retinal fundus images on morphometric vascular measurements in VAMPIRE. Computer Metho 2021

[3] W., & Heng, P 2020

[4] Porwal, P ., Pachade, S., Kamble, R., Kokare, M., Deshmukh, G., Sahasrabuddhe, V ., & Meriaudeau, F . (2018). Indian diabetic retinopathy image dataset (IDRiD): a database for diabetic retinopathy scr 2018

[5] Sivaswamy, J., Krishnadas, S., Chakravarty, A., Joshi, G., & Tabish, A. S. (2015). A comprehensive retinal image dataset for the assessment of glaucoma from the optic nerve head analysis. JSM Biomedic 2015

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Cited by

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TAPE: A two-stage parameter-efficient adaptation framework for foundation models in OCT-OCTA analysis

Receipt and verification

First computed	2026-05-21T01:05:07.869446Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

2026b88b9381ddc8044abd25270e802d2d8f0b67ca1091674848f68d0c1575f5

Aliases

arxiv: 2508.11354 · arxiv_version: 2508.11354v3 · doi: 10.48550/arxiv.2508.11354 · pith_short_12: EATLRC4TQHO4 · pith_short_16: EATLRC4TQHO4QBCK · pith_short_8: EATLRC4T

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curl -sH 'Accept: application/ld+json' https://pith.science/pith/EATLRC4TQHO4QBCKXUSSODUAFU \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 2026b88b9381ddc8044abd25270e802d2d8f0b67ca1091674848f68d0c1575f5

Canonical record JSON

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    "license": "http://creativecommons.org/licenses/by/4.0/",
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    "submitted_at": "2025-08-15T09:43:49Z",
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