CheXpert Radiography

CheXpert is a large dataset of chest X-rays and competition for automated chest x-ray interpretation

Requirements

pip install -r requirements.txt

Pre-process

python preprocess_metadata.py

train_processed_0_4.csv CheXpert-v1.0-processed_0_4.zip

• Remove rows without specified value in column Age
• Keep only x-rays with frontal view (AP)
• Treat uncertainty(-1), 50%-50% rule
• Sub-sample full dataset for computational reasons(use only 0.4 of entire set, >60K)

Launch jupyter

jupyter notebook CheXpert-nb-small.ipynb

Deal with uncertainty

We only take 2 approaches here

• U-zeros -> all uncertainty labels treated as no label activation
• U-ones -> all uncertainty labels treated as label activation

Pipeline Overview

Pre-trained Models

• DensetNet121
• EfficientNetB0

Performance Metrics

• Confusion Matrix
• Receiver Operating Characteristics (ROC) curve

Explanatory Analysis

• Gradient-weighted Class Activation Mapping (Grad-CAM)