Learning Where to Look: Anatomical Grounding and Guided Attention for Cardiac MRI Vision-Language Models

arXiv:2609.39899 · cs.CV · Submitted 2026-09-30 · Read on arXiv

cs.CV

Submitted: 2026-09-30

Updated: 2026-09-30

Terminology

• Grounding — 41× in this paper · explained in 3 episodes
• Segmentation Masks — 10× in this paper · explained in 2 episodes
• Generalization — 7× in this paper · explained in 13 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Cardiac Anatomy-Routed Attention — 5× in this paper
• Guided attention — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Adaptation — 4× in this paper · explained in 1 episode
• APEX — 3× in this paper · explained in 1 episode
• American Heart Association — 3× in this paper
• Consistency — 3× in this paper · explained in 3 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Two-stage training — 2× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Zero-Shot Generalization — 1× in this paper · explained in 5 episodes

Sources

• Qwen2.5-VL Technical Report
• MARCUS: An agentic, multimodal vision-language model for cardiac diagnosis and management
• BAAI Cardiac Agent: An intelligent multimodal agent for automated reasoning and diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging
• MedGemma 1.5 Technical Report
• Learning Volumetric Neural Deformable Models to Recover 3D Regional Heart Wall Motion from Multi-Planar Tagged MRI
• MedGround: Bridging the Evidence Gap in Medical Vision-Language Models with Verified Grounding Data

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