NV-Reason-CT: 3D Visual Language Model for CT Analysis

arXiv:2609.27511 · cs.CV, cs.AI · Submitted 2026-09-23 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-23

Updated: 2026-09-25

Code: https://github.com/NVIDIA-Medtech/NV-Reason-CT

Terminology

• AUROC — 49× in this paper · explained in 2 episodes
• GRPO — 20× in this paper · explained in 6 episodes
• Transformer — 18× in this paper · explained in 2 episodes
• Ontology — 13× in this paper · explained in 2 episodes
• Alignment — 12× in this paper · explained in 1 episode
• F1 Score — 11× in this paper · explained in 3 episodes
• Adaptation — 10× in this paper · explained in 1 episode
• Foundation Model — 10× in this paper · explained in 3 episodes
• Fine-Tuning — 9× in this paper · explained in 5 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Calibration — 8× in this paper · explained in 7 episodes
• Instruction Tuning — 7× in this paper · explained in 2 episodes
• Reinforcement Learning — 7× in this paper · explained in 4 episodes
• Trace — 6× in this paper · explained in 2 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Aggregation — 5× in this paper · explained in 1 episode
• Consistency — 5× in this paper · explained in 3 episodes
• Foundation Models — 5× in this paper · explained in 7 episodes
• Representation Learning — 5× in this paper · explained in 2 episodes
• Verifiable Rewards — 5× in this paper · explained in 2 episodes
• Contrastive Learning — 4× in this paper · explained in 5 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Resolution Meets Reduction — 4× in this paper
• Chain-of-Thought Prompting — 3× in this paper · explained in 2 episodes
• Grounding — 3× in this paper · explained in 3 episodes
• Group Relative Policy Optimization — 3× in this paper
• Supervised Fine-Tuning (SFT) — 3× in this paper · explained in 8 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Quantization — 2× in this paper · explained in 12 episodes
• Semantic Similarity — 2× in this paper · explained in 2 episodes
• Tokenization — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• GRPO Objective — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Group Relative Policy Optimization (GRPO) — 1× in this paper · explained in 5 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• International Symposium on Biomedical Imaging — 1× in this paper
• Linear probe — 1× in this paper · explained in 2 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Reasoning Traces — 1× in this paper · explained in 3 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes

Sources

• Comprehensive language-image pre-training for 3D medical image understanding
• Reasoning Visual Language Model for Chest X-Ray Analysis
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Flamingo: a Visual Language Model for Few-Shot Learning
• Pillar-0: A New Frontier for Radiology Foundation Models
• Learning Robust Visual Features in Computed Tomography Enables Efficient Transfer Learning for Clinical Tasks
• Jolia: Concept-Level Vision-Language Alignment for 3D CT Contrastive Learning
• Better Tokens for Better 3D: Advancing Vision-Language Modeling in 3D Medical Imaging
• Read Like a Radiologist: Efficient Vision-Language Model for 3D Medical Imaging Interpretation
• Enhancing Fine-Grained Spatial Grounding in 3D CT Report Generation via Discriminative Guidance
• EXACT: an explainable anomaly-aware vision foundation model for analysis of 3D chest CT
• MonteRET: AI Agent Enhancing Multimodal LLMs with Multi-granularity Knowledge Retrieval for Chest CT Report Generation
• Astra: a generalizable report generation foundation model for 3D computed tomography
• Resolution Meets Reduction: Efficient Visual Context for 3D Radiology Report Generation
• Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data
• M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models
• MedGemma 1.5 Technical Report
• ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• Qwen2.5-VL Technical Report

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