Whole-Slide Image Analysis under Realistic Few-Shot Annotation Protocols

arXiv:2608.30420 · cs.CV, cs.AI · Submitted 2026-08-31 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-08-31

Updated: 2026-08-31

Code: https://github.com/tgodelaine/SlideCRF

Terminology

• Accuracy — 17× in this paper · explained in 1 episode
• Linear probe — 8× in this paper · explained in 2 episodes
• Foundation Model — 6× in this paper · explained in 3 episodes
• Adaptation — 5× in this paper · explained in 1 episode
• Benchmark — 5× in this paper · explained in 2 episodes
• Objective Function — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Human-in-the-Loop — 3× in this paper · explained in 3 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• F1 Score — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Pseudo-labels — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Segmentation Masks — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes

Sources

• Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
• Interactive segmentation of medical images through fully convolutional neural networks
• VISTA-PATH: An interactive foundation model for pathology image segmentation and quantitative analysis in computational pathology

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