metadata
license: gpl-3.0
datasets:
- Kaynaaf/Brain-Tumour-MRI
metrics:
- accuracy 0.90
- precision 0.90
library_name: keras
tags:
- medical
- healthcare
Model Card
An Image Classifier that predicts the presence of certain Brain tumours from their MRI scans
Model Details
A 134M Parameter ConvNet designed for classification of Brain tumours in MRI scans.
Uses
Direct Use
Load the model, finetune the model if needed or just go straight towards generating inferences using the model.
Downstream Use
Finetune the model on other diagnostic scans, though the model only accepts grayscale images of size 256x256.
How to Get Started with the Model
Evaluation
Metrics
| Class | Precision | Recall | F1-Score | Support |
|---|---|---|---|---|
| Glioma | 0.96 | 0.87 | 0.91 | 300 |
| Meningioma | 0.84 | 0.71 | 0.77 | 306 |
| No Tumor | 0.88 | 1.00 | 0.93 | 405 |
| Pituitary | 0.93 | 0.99 | 0.96 | 300 |
| Accuracy | 0.90 | 1311 | ||
| Macro Avg | 0.90 | 0.89 | 0.89 | 1311 |
| Weighted Avg | 0.90 | 0.90 | 0.90 | 1311 |
Results
This model was developed for my project that can be found on github
