| --- |
| base_model: |
| - xinlai/LISA-7B-v1 |
| pipeline_tag: image-text-to-text |
| --- |
| |
| # ROSALIA-7B-v1 |
|
|
| **ROSALIA** is a vision-language model (VLM) designed for precise lesion segmentation in chest X-rays (CXRs). It is a LISA model fine-tuned on the **MIMIC-ILS** dataset, a large-scale instruction-answer dataset for CXR lesion segmentation. |
|
|
| ROSALIA is capable of **Instruction-Guided Lesion Segmentation (ILS)**, a medical-domain adaptation of referring image segmentation (RIS), allowing it to segment diverse lesions and provide textual explanations in response to simple, user-friendly instructions. |
|
|
| This model is the core checkpoint of the paper: |
| **[Instruction-Guided Lesion Segmentation for Chest X-rays with Automatically Generated Large-Scale Dataset](https://arxiv.org/abs/2511.15186)**, accepted to **CVPR 2026**. |
|
|
| - **Code:** [https://github.com/checkoneee/ROSALIA](https://github.com/checkoneee/ROSALIA) |
| - **Dataset:** [https://physionet.org/content/mimic-cxr-ext-ils/1.0.0/](https://physionet.org/content/mimic-cxr-ext-ils/1.0.0/) |
| - **Paper:** [arXiv:2511.15186](https://arxiv.org/abs/2511.15186) |
|
|
| ## 📖 Citation |
|
|
| If you find this model or the related research useful, please cite our work: |
|
|
| ```bibtex |
| @article{choi2025instruction, |
| title={Instruction-Guided Lesion Segmentation for Chest X-rays with Automatically Generated Large-Scale Dataset}, |
| author={Choi, Geon and Yoon, Hangyul and Shin, Hyunju and Park, Hyunki and Seo, Sang Hoon and Yang, Eunho and Choi, Edward}, |
| journal={arXiv preprint arXiv:2511.15186}, |
| year={2025} |
| } |
| ``` |
