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Nested Radially Monotone Polar Occupancy Estimation: Clinically-Grounded Optic Disc and Cup Segmentation for Glaucoma Screening

arXiv 2604.09062 ↗First posted 10 Apr 2026cs.CVcited by 0

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Abstract (arXiv)

Valid segmentation of the optic disc (OD) and optic cup (OC) from fundus photographs is essential for glaucoma screening. Unfortunately, existing deep learning methods do not guarantee clinical validness including star-convexity and nested structure of OD and OC, resulting corruption in diagnostic metric, especially under cross-dataset domain shift. To adress this issue, this paper proposed NPS-Net (Nested Polar Shape Network), the first framework that formulates the OD/OC segmentation as nested radially monotone polar occupancy estimation.This output representation can guarantee the aforementioned clinical validness and achieve high accuracy. Evaluated across seven public datasets, NPS-Net shows strong zero-shot generalization. On RIM-ONE, it maintains 100% anatomical validity and improves Cup Dice by 12.8% absolute over the best baseline, reducing vCDR MAE by over 56%. On PAPILA, it achieves Disc Dice of 0.9438 and Disc HD95 of 2.78 px, an 83% reduction over the best competing method.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 16 of its 37 references that are in the map. First posted on arXiv 10 Apr 2026.

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References · 16

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,558
  3. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,435
  4. 2015Spatial Transformer Networkscited by 1,429
  5. 2018Deep Visual Domain Adaptation: A Surveycited by 635
  6. 2019REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographscited by 228
  7. 2019CE-Net: Context Encoder Network for 2D Medical Image Segmentationcited by 220
  8. 2020DoFE: Domain-oriented Feature Embedding for Generalizable Fundus Image Segmentation on Unseen Datasetscited by 70
  9. 2020Tent: Fully Test-time Adaptation by Entropy Minimizationcited by 69
  10. 2019Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentationcited by 46
  11. 2018Disc-aware Ensemble Network for Glaucoma Screening from Fundus Imagecited by 39
  12. 2022Test-Time Adaptation with Shape Moments for Image Segmentationcited by 19
4 more
  1. 2022CDDSA: Contrastive Domain Disentanglement and Style Augmentation for Generalizable Medical Image Segmentationcited by 18
  2. 2022Unsupervised Domain Adaptive Fundus Image Segmentation with Category-level Regularizationcited by 6
  3. 2023Test-time augmentation-based active learning and self-training for label-efficient segmentationcited by 3
  4. 2023Pay Attention to the Atlas: Atlas-Guided Test-Time Adaptation Method for Robust 3D Medical Image Segmentationcited by 2

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