Update README.md

README.md

@@ -3,11 +3,8 @@ license: apache-2.0
 tags:
 - object-detection
 - medical-imaging
-- rf-detr
 - heart-anatomy
 - computer-vision
-datasets:
-- roboflow/heart-anatomy-types
 metrics:
 - mean-average-precision
 model-index:
@@ -24,9 +21,9 @@ model-index:
       name: mAP@50
 ---
 
-# Heartformer: Heart Anatomy Type Detection with RF-DETR
+# Heartformer: Heart Anatomy Type Detection
 
-**Heartformer** is a specialized object detection model for identifying and localizing different types of heart anatomy visualizations in medical images. Built on the RF-DETR (Roboflow Detection Transformer) architecture, this model can detect and classify seven distinct categories of cardiac imaging and illustration modalities.
+**Heartformer** is a specialized object detection model for identifying and localizing different types of heart anatomy visualizations in medical images. Built on the RF-DETR architecture, this model can detect and classify seven distinct categories of cardiac imaging and illustration modalities.
 
 ## 📋 Model Description
 
@@ -44,9 +41,6 @@ Heartformer addresses the challenge of automatically categorizing diverse repres
 - **Real-time Inference**: Optimized RF-DETR Nano architecture for fast detection
 - **Robust Generalization**: Tested on diverse image sources and artistic styles
 
-## 🏗️ Model Architecture
-
-Heartformer is based on **RF-DETR Nano**, a lightweight variant of the Detection Transformer (DETR) architecture optimized for real-time object detection:
 
 ### Architecture Overview
 
@@ -373,7 +367,7 @@ If you use Heartformer in your research or application, please cite:
 
 ### Acknowledgments
 
-- **RF-DETR**: Based on Roboflow's RF-DETR architecture
+- **RF-DETR**: Based on RF-DETR architecture
   ```bibtex
   @misc{rfdetr2024,
     title={RF-DETR: Real-time Detection Transformer},
@@ -427,4 +421,4 @@ For questions, issues, or collaboration opportunities:
 
 ---
 
-**Note**: This model is continuously being improved. Check back for updates and new versions!
+**Note**: This model is continuously being improved. Check back for updates and new versions!