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--- |
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language: en |
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tags: |
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- image-classification |
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- brain-tumor-detection |
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- medical-imaging |
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- deep-learning |
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- keras |
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--- |
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# Brain Tumor Detection Model |
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This model predicts the presence of brain tumors based on medical imaging data (e.g., MRI scans). It is designed to assist healthcare professionals in identifying tumors in brain scans, enhancing diagnostic capabilities. |
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## Model Description |
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- **Architecture**: Convolutional Neural Network (CNN) built using TensorFlow/Keras. |
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- **Input Shape**: The model expects input images of shape `(224, 224, 3)`, which corresponds to resized RGB images. |
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- **Output**: The model outputs a probability distribution over two classes: `malignant` and `non-malignant`. |
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## Training Data |
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- The model was trained on a dataset of brain MRI images. The dataset includes both images with and without tumors. |
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- Data Augmentation techniques were applied during training to improve model generalization. |
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## Usage |
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### Installation |
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To use this model, ensure you have the required libraries installed: |
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```bash |
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pip install tensorflow fastapi numpy pillow |
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