Update README.md

README.md

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 license: cc-by-nc-3.0
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 This repo contains the checkpoints for OminiAbnorm-CT, a multi-modal generative model for grounded abnormality analysis on CT images from multiple planes and all human body regions.
-It support three representative task:
-- Visual prompted report generation: Interpretate an abnormality marked by red bounding box, ellipse, contour, or cropped region.
-- Grounded report generation: Ground and interpretate all abnormalities on the CT image.
-- Text-guided grounded report generation: Detect, ground and interpretate specific abnormality on the CT image.
-![Example Figure](docs/resources/model.png)
+It supports three representative tasks:
+- Visual prompted report generation: Interpret an abnormality marked by a red bounding box, ellipse, contour, or cropped region.
+- Grounded report generation: Ground and interpret all abnormalities on the CT image.
+- Text-guided grounded report generation: Detect, ground and interpret a specific abnormality on the CT image.
+- 
+![Example Figure](Model.png)
 
 It is built on **[OminiAbnorm-CT-14K](https://huggingface.co/datasets/zzh99/OminiAbnorm-CT-14K)**, the first large-scale dataset designed for abnormality grounding and description on multi-plane whole-body CT imaging. 
 It contains 14.5K CT images with grounding annotation for 19K abnormal findings.
-Each abnormal findings is further linked to the detailed description in the report, and categorized according to a comprehensive hierarchical taxonomy.
+Each abnormal finding is further linked to the detailed description in the report, and categorized according to a comprehensive hierarchical taxonomy.
 
-![Example Figure](docs/resources/data.png)
+![Example Figure](Demo.png)
 
 Check our [paper](https://www.arxiv.org/abs/2506.03238) and [github repo](https://github.com/zhaoziheng/OminiAbnorm-CT) for more details.