| license: apache-2.0 | |
| pipeline_tag: image-text-to-text | |
| library_name: transformers | |
| # M3D-RAD Model | |
| The official Model for the paper "[3D-RAD: A Comprehensive 3D Radiology Med-VQA Dataset with Multi-Temporal Analysis and Diverse Diagnostic Tasks](https://huggingface.co/papers/2506.11147)". | |
| In our project, we collect a large-scale dataset designed to advance 3D Med-VQA using radiology CT scans, 3D-RAD, encompasses six diverse VQA tasks: anomaly detection (task 1), image observation (task 2), medical computation (task 3), existence detection (task 4), static temporal diagnosis (task 5), and longitudinal temporal diagnosis (task 6). | |
|  | |
| ## Code | |
| You can find our code in [M3D-RAD_Code](https://github.com/Tang-xiaoxiao/M3D-RAD). | |
| ## 3D-RAD Dataset | |
| You can find our dataset in [3D-RAD_Dataset](https://huggingface.co/datasets/Tang-xiaoxiao/3D-RAD). | |
| ## Model Links | |
| | Model | Paper | | |
| | ----- | ------------------------------------------------------------ | | |
| | [RadFM](https://github.com/chaoyi-wu/RadFM) | Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data | https://github.com/chaoyi-wu/RadFM | | |
| | [M3D](https://github.com/BAAI-DCAI/M3D) | M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models | | |
| | OmniV(not open) | OmniV-Med: Scaling Medical Vision-Language Model for Universal Visual Understanding | |