Update README.md

README.md

@@ -44,6 +44,17 @@ The model was trained on medical CT scan data with corresponding segmentation ma
 
 ## Usage
 
+This model can be used to **add more diversity to your CT-scan dataset**, which is particularly valuable when:
+- You have a **limited dataset size** (e.g., only a few hundred scans).
+- You want to **balance underrepresented anatomical variations** or rare conditions.
+- You need **synthetic augmentation** for training deep learning models in tasks such as segmentation, detection, or classification.
+
+### Example Applications
+- Generate additional training samples from segmentation masks to **reduce overfitting**.
+- Create synthetic CT images with controlled variations to **test model robustness**.
+- Improve representation of minority cases in the dataset to **reduce bias in medical AI**.
+
+
 ### Using the Hugging Face API
 
 ```python