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matthewchung74/
alzheimer-cbam-cnn

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Alzheimer Disease MRI Classification (CBAM CNN)

This model uses a custom Convolutional Neural Network (CNN) integrated with CBAM (Convolutional Block Attention Module) attention mechanisms. It distinguishes between four classes: Mild Demented, Moderate Demented, Non Demented, and Very Mild Demented.

Model Architecture

Backbone: 4-block Custom CNN
Attention: Channel & Spatial Attention (CBAM) in each block
Input: 224x224 RGB images

Performance (Test Set)

Accuracy: 0.6375
Weighted Average F1-Score: 0.6255

Classification Report:

                    precision    recall  f1-score   support

     Mild Demented       0.67      0.32      0.43       172
 Moderate Demented       0.00      0.00      0.00        15
      Non Demented       0.72      0.79      0.75       634
Very Mild Demented       0.52      0.57      0.54       459

          accuracy                           0.64      1280
         macro avg       0.48      0.42      0.43      1280
      weighted avg       0.63      0.64      0.63      1280

matthewchung74/alzheimer-cbam-cnn

Alzheimer Disease MRI Classification (CBAM CNN)

Model Architecture

Performance (Test Set)

Classification Report:

matthewchung74/
alzheimer-cbam-cnn