Update transunet/leverage_summary.txt

transunet/leverage_summary.txt

@@ -2,18 +2,19 @@
     LEVERAGE PAPER RESULTS SUMMARY
     ================================
     Experiment Timestamp: 20251124_171430
+    Model Architecture: TRANS_UNET
     WMH Segmentation: Binary vs Three-class Classification Comparison
 
     DATASET INFORMATION:
     --------------------
-    Training Images: 1044 
-    Test Images: 161
+    Training Images: 2050 
+    Test Images: 350
     Image Size: (256, 256)
     Classes: Background (0), Normal WMH (1), Abnormal WMH (2)
 
     METHODOLOGY:
     ------------
-    Architecture: Enhanced U-Net with Batch Normalization and Dropout
+    Architecture: TRANS_UNET
     Loss Functions: 
     - Scenario 1: weighted_bce
     - Scenario 2: weighted_categorical
@@ -56,21 +57,3 @@
     3. Dice analysis confirms significant improvement
     4. IoU analysis confirms significant improvement
     5. Post-processing provided substantial improvements in both scenarios
-
-    FILES GENERATED:
-    ----------------
-    - Models: scenario1_binary_model.h5, scenario2_multiclass_model.h5
-    - Figures: training_curves.png/.pdf, comparison_visualization.png/.pdf, metrics_comparison.png/.pdf
-    - Tables: comprehensive_results.csv/.xlsx, latex_table.tex
-    - Statistics: statistical_analysis.json, statistical_report.txt
-    - Predictions: All test predictions and ground truth data saved
-
-    PUBLICATION READINESS:
-    ----------------------
-    ✓ High-resolution figures (300 DPI, PNG/PDF)
-    ✓ LaTeX-formatted tables
-    ✓ Comprehensive statistical analysis (Dice + IoU)
-    ✓ Post-processing impact analysis
-    ✓ Reproducible results with saved models
-    ✓ Professional documentation
-