Brain Tumor Detection Model
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.
Model Description
- Architecture: Convolutional Neural Network (CNN) built using TensorFlow/Keras.
- Input Shape: The model expects input images of shape
(224, 224, 3), which corresponds to resized RGB images. - Output: The model outputs a probability distribution over two classes:
malignantandnon-malignant.
Training Data
- The model was trained on a dataset of brain MRI images. The dataset includes both images with and without tumors.
- Data Augmentation techniques were applied during training to improve model generalization.
Usage
Installation
To use this model, ensure you have the required libraries installed:
pip install tensorflow fastapi numpy pillow
- Downloads last month
- 0
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.