MilitaryHospital175/VNMedical_bv175
ViX-Ray: A Vietnamese Chest X-Ray Dataset for Vision-Language Models ViX-Ray is the first publicly available Vietnamese chest X-ray dataset designed for vision-language model (VLM) research in medical AI. It pairs radiographic images from Vietnamese patients with expert-written clinical annotations in Vietnamese, directly addressing the lack of Vietnamese medical data in existing VLMs. License: CC BY-NC-SA 4.0 Paper: arXiv:2603.15513 Dataset Overview Each… See the full description on the dataset page: https://huggingface.co/datasets/MilitaryHospital175/VNMedical_bv175.
ViX-Ray: A Vietnamese Chest X-Ray Dataset for Vision-Language Models
ViX-Ray is the first publicly available Vietnamese chest X-ray dataset designed for vision-language model (VLM) research in medical AI. It pairs radiographic images from Vietnamese patients with expert-written clinical annotations in Vietnamese, directly addressing the lack of Vietnamese medical data in existing VLMs.
- License: CC BY-NC-SA 4.0
- Paper: arXiv:2603.15513
Dataset Overview
Each sample contains a PA-view chest X-ray image paired with Vietnamese-language radiology reports written by certified radiologists. All Protected Health Information (PHI) has been removed; clinically relevant metadata (age, gender) is retained. The dataset was collected under Institutional Review Board (IRB) approval.
Splits
Fields
Report Text Length (tokens)
Average patient age: ~69–70 years across all splits.
Common Findings
Most frequently mentioned anatomical structures: Heart (tim), Lungs (phổi), Ribs (xương sườn), Diaphragm (vòm hoành), Pulmonary hilum (rốn phổi)
Most common diagnoses: Interstitial lung disease, Cardiomegaly, Pulmonary infiltrates/consolidations, Rib fractures, Aortic calcifications
Intended Use
- Training and fine-tuning vision-language models for Vietnamese medical image analysis
- Benchmarking multilingual and Vietnamese-specific VLMs
- Research on hallucination reduction in clinical AI
- Multi-turn clinical diagnostic conversation modeling
Benchmark Results
Five open-source VLMs were fine-tuned and evaluated on three stages: findings generation → impression generation → multi-turn clinical dialogue. Best performing model: Qwen2.5-VL-7B (ROUGE-1: 84.30% on findings, 95.20% on multi-turn impressions).
Citation
If you use this dataset, please cite:
@article{nguyen2026vix,
title={ViX-Ray: A Vietnamese Chest X-Ray Dataset for Vision-Language Models},
author={Nguyen, Duy Vu Minh and Truong, Chinh Thanh and Tran, Phuc Hoang and Le, Hung Tuan and Dat, Nguyen Van-Thanh and Pham, Trung Hieu and Van Nguyen, Kiet},
journal={arXiv preprint arXiv:2603.15513},
year={2026}
}