COVID-19 Detection from Chest X-rays
Overview
CNN models trained to distinguish COVID-19 / Pneumonia chest X-rays from normal X-rays in a binary classification task. Multiple architectures and configurations were evaluated, with all code and findings published openly on GitHub. Outcome: Open-source reference implementation for COVID-19 X-ray detection, with full reproducible code and results.
Architecture & Pipeline
flowchart LR
n0["Chest X-rayImage input"]
n1["PreprocessingNormalize · resize"]
n2["CNN ModelPyTorch"]
n3["Probability ScoreSigmoid output"]
n4["ClassificationInfected / Normal"]
n0 --> n1
n1 --> n2
n2 --> n3
n3 --> n4
classDef step0 fill:#f1f5f9,stroke:#64748b,color:#1e293b,stroke-width:2px,rx:10,ry:10;
classDef step1 fill:#ecfeff,stroke:#06b6d4,color:#1e293b,stroke-width:2px,rx:10,ry:10;
classDef step2 fill:#f0fdfa,stroke:#0d9488,color:#1e293b,stroke-width:2px,rx:10,ry:10;
classDef step3 fill:#ecfdf5,stroke:#10b981,color:#1e293b,stroke-width:2px,rx:10,ry:10;
classDef step4 fill:#fffbeb,stroke:#f59e0b,color:#1e293b,stroke-width:2px,rx:10,ry:10;
class n0 step0;
class n1 step1;
class n2 step2;
class n3 step3;
class n4 step4;
End-to-end flow derived from this project's scope and tech stack. Tap View Fullscreen for a larger view, or scroll horizontally on small screens.
Key Features
- Binary classifier for "Infected" vs "Normal" chest X-rays
- Multiple CNN configurations evaluated and compared
- Open-source code and results on GitHub
- Tech Stack:** Python, PyTorch