Topology-Aware Parameter-Efficient Adaptation for Cross-Dataset Retinal Vessel Segmentation

arXiv:2609.26189 · cs.CV · Submitted 2026-08-10 · Read on arXiv

cs.CV

Submitted: 2026-08-10

Updated: 2026-08-10

Terminology

• Adaptation — 41× in this paper · explained in 1 episode
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Domain Shift — 2× in this paper · explained in 4 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Parameter-Efficient Fine-Tuning — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• U-net architecture — 1× in this paper · explained in 3 episodes

Sources

• VesSAM: Efficient Multi-Prompting for Segmenting Complex Vessel
• TopoLoRA-SAM: Topology-Aware Parameter-Efficient Adaptation of Foundation Segmenters for Thin-Structure and Cross-Domain Binary Semantic Segmentation
• SAM2LoRA: Composite Loss-Guided, Parameter-Efficient Finetuning of SAM2 for Retinal Fundus Segmentation
• Medical SAM 2: Segment medical images as video via Segment Anything Model 2

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