Interpretable Fundus Image Classification via Ring-Based Retinal Vasculature Features

arXiv:2608.24723 · cs.CV, stat.ML · Submitted 2026-08-25 · Read on arXiv

cs.CV, stat.ML

Submitted: 2026-08-25

Updated: 2026-08-25

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Accuracy — 32× in this paper · explained in 1 episode
Transformer — 9× in this paper · explained in 2 episodes
AUC — 6× in this paper · explained in 2 episodes
Ablation — 5× in this paper · explained in 1 episode
Feature Extraction — 5× in this paper · explained in 2 episodes
Robustness — 4× in this paper · explained in 5 episodes
Embeddings — 3× in this paper · explained in 2 episodes
External Validation — 3× in this paper · explained in 2 episodes
Foundation Model — 3× in this paper · explained in 3 episodes
High-Resolution Fundus — 3× in this paper
Integrated Gradients — 3× in this paper
Interpretability — 3× in this paper · explained in 15 episodes
Latent Representation — 3× in this paper · explained in 2 episodes
Latent Representations — 3× in this paper · explained in 3 episodes
Domain Shift — 2× in this paper · explained in 4 episodes
Fine-Tuning — 2× in this paper · explained in 5 episodes
Regularization — 2× in this paper · explained in 3 episodes
Ablation study — 1× in this paper · explained in 1 episode
Adaptation — 1× in this paper · explained in 1 episode
Benchmarking — 1× in this paper · explained in 3 episodes
Calibration — 1× in this paper · explained in 7 episodes
Domain Adaptation — 1× in this paper · explained in 5 episodes
Generalization — 1× in this paper · explained in 13 episodes
Transferability — 1× in this paper · explained in 4 episodes

Sources

SmoothGrad: removing noise by adding noise

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