Inception V3 Covid-19 Classifier
Model description
This model is a fine-tuned Inception V3 convolutional neural network designed for chest X-ray image classification, with a focus on Covid-19 detection.
The model was trained using transfer learning from ImageNet weights and further fine-tuned on medical imaging data.
An optionnal lung auto-masking preprocessing step can be applied upstream to reduce background bias and improve interpretability.
This model is entended for research and educational purposes only.
Intended use
- Binary or multi-class classification of chest X-ray images
- Research on medical image classification
- Demonstration of deep learning pipelines (preprocessing, fine-tuning, Grad-CAM)
Not intended for
- Clinical diagnosis
- Medical decision-making
- Production healthcare systems
Training data
The model was trained on the COVID-19 Radiography Dataset (Kaggle):
https://www.kaggle.com/datasets/tawsifurrahman/covid19-radiography-database/data
The dataset contains chest X-ray images labeled as:
- COVID
- Normal
- Lung-Opacity
- Viral Pneumonia
Only frontal chest X-ray images were considered.
Input format
- Image size : 299x299 px
- Channels : 3 (RBG)
- Pixel values : normalized to [-1,1]
Output format
- Class probabilites (softmax)
- Final prediction via argmax
Training details
- Base model : Inception V3 (ImageNet pretrained)
- Fine-tuning : last 20 layers unfrozen
- Optimizer : SGD
- Loss function : Categorical crossentropy
Evaluation results
The model achieves an accuracy of approximately 84% on the validation set.
Performance metrics were evaluated using :
- Accuracy
- Confusion matrix
- ROC/AUC curves
Results are dataset-dependent and may vary under different data distributions.
Explainability
Model predictions can be interpreted using Grad-CAM visualizations, highlighting salient lung regions contributing to the decision.
Limitations
- Trained on a single public dataset
- Sensitive to image quality and acquisition protocol
- Performance may degrade on non-frontal or low-quality X-ray
- Not validated on clinical-grade datasets
Ethical considerations
This model is provided for research purposes only. It must not be used as a diagnostic tool or to guide clinical decisions.
Example usage
from tensorflow.keras.models import load_model
import numpy as np
model = load_model("inception_V3_covid.keras")
preds = model.predict(input_tensor)
Author
Asma Sima
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