Update README.md

README.md

@@ -9,8 +9,6 @@ framework: keras
 task: image-translation
 ---
 
-
-
 # pyMEAL: Multi-Encoder-Augmentation-Aware-Learning
 
 pyMEAL is a multi-encoder framework for augmentation-aware learning that accurately performs CT-to-T1-weighted MRI translation under diverse augmentations. It utilizes four dedicated encoders and three fusion strategies, concatenation (CC), fusion layer (FL), and controller block (BD), to capture augmentation-specific features. MEAL-BD outperforms conventional augmentation methods, achieving SSIM > 0.83 and PSNR > 25 dB in CT-to-T1w translation.
@@ -27,8 +25,49 @@ scipy
 
 antspyx
 
-## Tutorials
-To use the different modules of pyMEAL, please refer to the tutorial section in our GitHub repository (https://github.com/ai-vbrain/pyMEAL)
+
+---
+
+## Available Models
+
+| Model ID | File Name                                      | Description                                 |
+|----------|------------------------------------------------|---------------------------------------------|
+| BD       | `builder1_mode1l1abW512_1_11211z1p1rt_.h5`     | Builder-based architecture model            |
+| CC       | `best_moderRl_RHID2_1mo.h5`                    | Encoder-concatenation-based configuration   |
+| FL       | `bestac22_mode3l_512m2_m21.h5`                 | Feature-level fusion-based model            |
+| NA       | `direct7_11ag23f11.h5`                         | Direct training baseline model              |
+| TA       | `best_modelaf2ndab7_221ag12g11.h5`             | traditional augmentation configuration model|
+
+---
+
+## Download Model Files
+
+You can download any `.h5` file directly:
+
+- [Download builder1_mode1l1abW512_1_11211z1p1rt_.h5](https://huggingface.co/AI-vBRAIN/pyMEAL/resolve/main/builder1_mode1l1abW512_1_11211z1p1rt_.h5)
+- [Download best_moderRl_RHID2_1mo.h5](https://huggingface.co/AI-vBRAIN/pyMEAL/resolve/main/best_moderRl_RHID2_1mo.h5)
+- [Download bestac22_mode3l_512m2_m21.h5](https://huggingface.co/AI-vBRAIN/pyMEAL/resolve/main/bestac22_mode3l_512m2_m21.h5)
+- [Download direct7_11ag23f11.h5](https://huggingface.co/AI-vBRAIN/pyMEAL/resolve/main/direct7_11ag23f11.h5)
+- [Download best_modelaf2ndab7_221ag12g11.h5](https://huggingface.co/AI-vBRAIN/pyMEAL/resolve/main/best_modelaf2ndab7_221ag12g11.h5)
+
+---
+
+## How to Use
+
+### Load a Model (Basic)
+
+```python
+import tensorflow as tf
+
+# Load the model
+model = tf.keras.models.load_model("model.h5", compile=False)
+
+# Run inference
+output = model.predict(input_data)
+
+Here, input_data refers to a CT image, and the corresponding T1-weighted (T1w) image is produced as the output.
+
+For detailed instructions on how to use each module of the pyMEAL software, please refer to the tutorial section of our GitHub repository.
 
 ## How to get support?
-Just write to amoilyas@hkcoche.org or amaradesa@hkcoche.org
+Just write to Dr. Ilyas (amoilyas@hkcoche.org) or Dr. Maradesa (amaradesa@hkcoche.org)