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HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale

📃 Paper • 🖥️ Demo

✨ Updates

🩻 PubMedVision

  • PubMedVision is a large-scale, high-quality medical VQA dataset, constructed from the image-text pairs from PubMed and reformatted using GPT-4V.
# Data Download
PubMedVision Dataset 1,294,062 HF Link
  • PubMedVision could significantly improve the medical multimodal capabilities of MLLMs such as LLaVA-v1.5.
VQA-RAD SLAKE PathVQA PMC-VQA
LLaVA-v1.6-34B 58.6 67.3 59.1 44.4
LLaVA-v1.5-LLaMA3-8B 54.2 59.4 54.1 36.4
LLaVA-v1.5-LLaMA3-8B + PubMedVision 63.8 74.5 59.9 52.7
OmniMedVQA MMMU Health & Medicine (Test Set)
LLaVA-v1.6-34B 61.4 48.8
LLaVA-v1.5-LLaMA3-8B 48.8 38.2
LLaVA-v1.5-LLaMA3-8B + PubMedVision 75.1 49.1

👨‍⚕️ HuatuoGPT-Vision

HuatuoGPT-Vision is our medical multimodal LLMs, built on PubMedVision.

Model Access

Our model is available on Huggingface in two versions:

Backbone Checkpoint
HuatuoGPT-Vision-7B Qwen2-7B HF Link
HuatuoGPT-Vision-34B Yi-1.5-34B HF Link

Model Usage

  • Command Line Interface

Chat via the command line:

python cli.py --model_dir path-to-huatuogpt-vision-model
  • Model Inference

Inference using our ChatBot:

query = 'What does the picture show?'
image_paths = ['image_path1']

from cli import HuatuoChatbot
bot = HuatuoChatbot(path-to-huatuogpt-vision-model)
output = bot.inference(query, image_paths)
print(output) # Prints the output of the model

Performance of Medical Multimodal

VQA-RAD SLAKE PathVQA PMC-VQA
LLaVA-Med-7B 51.4 48.6 56.8 24.7
LLaVA-v1.6-34B 58.6 67.3 59.1 44.4
HuatuoGPT-Vision-7B 63.7 76.2 57.9 54.3
HuatuoGPT-Vision-34B 68.1 76.9 63.5 58.2
OmniMedVQA MMMU Health & Medicine (Test Set)
LLaVA-Med-7B 44.5 36.9
LLaVA-v1.6-34B 61.4 48.8
HuatuoGPT-Vision-7B 74.0 50.6
HuatuoGPT-Vision-34B 76.9 54.4

🩺 HuatuoGPT Series

Explore our HuatuoGPT series:

  • HuatuoGPT: Taming Language Models to Be a Doctor
  • HuatuoGPT-II: One-stage Training for Medical Adaptation of LLMs
  • HuatuoGPT-Vision: Injecting Medical Visual Knowledge into Multimodal LLMs at Scale

Citation

@misc{chen2024huatuogptvisioninjectingmedicalvisual,
      title={HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale}, 
      author={Junying Chen and Ruyi Ouyang and Anningzhe Gao and Shunian Chen and Guiming Hardy Chen and Xidong Wang and Ruifei Zhang and Zhenyang Cai and Ke Ji and Guangjun Yu and Xiang Wan and Benyou Wang},
      year={2024},
      eprint={2406.19280},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2406.19280}, 
}