Synergistic Vision-Language Reinforcement Enables Scalable On-Demand Analysis across Diverse Clinical Tasks

arXiv:2505.03380 · cs.CV, cs.AI, eess.IV · Submitted 2025-05-06 · Read on arXiv

cs.CV, cs.AI, eess.IV

Submitted: 2025-05-06

Updated: 2026-09-09

Code: https://github.com/xmed-lab/RCMed

Project page: https://xmed-lab.github.io/RCMed

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

Terminology

Foundation Model — 28× in this paper · explained in 3 episodes
Alignment — 13× in this paper · explained in 1 episode
Accuracy — 11× in this paper · explained in 1 episode
Generalizability — 11× in this paper · explained in 6 episodes
Foundation Models — 9× in this paper · explained in 7 episodes
Adaptation — 8× in this paper · explained in 1 episode
External Validation — 5× in this paper · explained in 2 episodes
Generalization — 5× in this paper · explained in 13 episodes
Dice Similarity Coefficient — 4× in this paper
Grounding — 4× in this paper · explained in 3 episodes
Consistency — 3× in this paper · explained in 3 episodes
Embeddings — 3× in this paper · explained in 2 episodes
Segmentation Masks — 3× in this paper · explained in 2 episodes
Benchmark — 2× in this paper · explained in 2 episodes
Catastrophic Forgetting — 2× in this paper · explained in 5 episodes
Closed-Loop System — 2× in this paper · explained in 4 episodes
Color Region Describing — 2× in this paper
Feature Extraction — 2× in this paper · explained in 2 episodes
Fine-Tuning — 2× in this paper · explained in 5 episodes
Interpretability — 2× in this paper · explained in 15 episodes
Multi-modal Inputs — 2× in this paper · explained in 2 episodes
Transformer — 2× in this paper · explained in 2 episodes
Adam — 1× in this paper · explained in 2 episodes
Adaptability — 1× in this paper · explained in 1 episode
Attention Mechanism — 1× in this paper · explained in 2 episodes
Class Activation Mapping — 1× in this paper
Continual Learning — 1× in this paper · explained in 2 episodes
Cross-Attention Mechanism — 1× in this paper · explained in 2 episodes
Distribution Shift — 1× in this paper · explained in 5 episodes
Domain Adaptation — 1× in this paper · explained in 5 episodes
Generative AI — 1× in this paper · explained in 2 episodes
Guided attention — 1× in this paper · explained in 2 episodes
Instruction Tuning — 1× in this paper · explained in 2 episodes
Mask Generation — 1× in this paper · explained in 2 episodes
Meta-learning — 1× in this paper · explained in 2 episodes
Multimodal Inputs — 1× in this paper · explained in 2 episodes
Semantic Gap — 1× in this paper · explained in 2 episodes
Trace — 1× in this paper · explained in 2 episodes
Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes
nnU-Net — 1× in this paper · explained in 2 episodes

Sources

SAM-Med2D

Terminology

Sources

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