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transunet/config/experiment_config.json

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+{
+  "timestamp": "20251124_171430",
+  "input_shape": [
+    256,
+    256,
+    1
+  ],
+  "target_size": [
+    256,
+    256
+  ],
+  "epochs": 50,
+  "batch_size": 8,
+  "learning_rate": 0.0001,
+  "validation_split": 0.1,
+  "random_state": 42,
+  "loss_options": {
+    "scenario1": "weighted_bce",
+    "scenario2": "weighted_categorical"
+  }
+}

transunet/leverage_summary.txt

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+
+    LEVERAGE PAPER RESULTS SUMMARY
+    ================================
+    Experiment Timestamp: 20251124_171430
+    WMH Segmentation: Binary vs Three-class Classification Comparison
+
+    DATASET INFORMATION:
+    --------------------
+    Training Images: 1044 
+    Test Images: 161
+    Image Size: (256, 256)
+    Classes: Background (0), Normal WMH (1), Abnormal WMH (2)
+
+    METHODOLOGY:
+    ------------
+    Architecture: Enhanced U-Net with Batch Normalization and Dropout
+    Loss Functions: 
+    - Scenario 1: weighted_bce
+    - Scenario 2: weighted_categorical
+    Training Epochs: 50
+    Batch Size: 8
+    Learning Rate: 0.0001
+
+    PERFORMANCE RESULTS:
+    --------------------
+                        | Scenario 1 (Binary) | Scenario 2 (3-class) | Improvement
+    --------------------|---------------------|----------------------|------------
+    Accuracy            | 0.9860            | 0.9946             | +0.0086
+    Precision           | 0.3462           | 0.6029            | +0.2567
+    Recall              | 0.9650              | 0.8342               | -0.1307
+    Dice Coefficient    | 0.5096                | 0.7000                 | +0.1904
+    IoU Coefficient     | 0.3419                 | 0.5384                  | +0.1965
+
+    STATISTICAL SIGNIFICANCE:
+    -------------------------
+    DICE COEFFICIENT:
+    Test: Paired t-test
+    t-statistic: 7.9888
+    p-value: 0.0000
+    Effect Size (Cohen's d): 0.4778
+    95% Confidence Interval: [0.1090, 0.1807]
+    Result: SIGNIFICANT improvement
+
+    IoU COEFFICIENT:
+    Test: Paired t-test
+    t-statistic: 8.5581
+    p-value: 0.0000
+    Effect Size (Cohen's d): 0.5589
+    95% Confidence Interval: [0.1121, 0.1793]
+    Result: SIGNIFICANT improvement
+
+    KEY FINDINGS:
+    -------------
+    1. Three-class segmentation shows 46.70% improvement in Dice coefficient
+    2. Three-class segmentation shows 67.84% improvement in IoU coefficient
+    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
+    

transunet/tables/comprehensive_results.csv

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+Scenario,Accuracy,Precision,Recall,Specificity,Dice,IoU,HD95,ASSD
+Binary Classification (Processed),0.986004278526543,0.3461836987030803,0.9649564156425705,0.9997302921073945,0.5095598516138679,0.3418854773044586,,
+Three-class Classification (Processed),0.9946109937584918,0.6029034779921095,0.8342410787285695,0.9987378954133063,0.6999530360371915,0.5384059548377991,,
+Statistical Analysis,Dice p=0.0000,Dice t=7.9888,Dice Δ=0.1449,Dice ES=0.4778,IoU p=0.0000,IoU Δ=0.1457,HD95 Δ=3.0926px,ASSD Δ=-1.2769px

transunet/tables/latex_table.tex

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+\begin{table}
+\caption{Performance comparison between binary and three-class segmentation approaches}
+\label{tab:performance_comparison}
+\begin{tabular}{lllllllll}
+\toprule
+Scenario & Accuracy & Precision & Recall & Specificity & Dice & IoU & HD95 & ASSD \\
+\midrule
+Binary Classification (Processed) & 0.9860 & 0.3462 & 0.9650 & 0.9997 & 0.5096 & 0.3419 & NaN & NaN \\
+Three-class Classification (Processed) & 0.9946 & 0.6029 & 0.8342 & 0.9987 & 0.7000 & 0.5384 & NaN & NaN \\
+\bottomrule
+\end{tabular}
+\end{table}