DDPM based X-ray Image Synthesizer

Understand

Access to high-quality datasets in the medical industry limits machine learning model performance.

• To address this issue, we propose a Denoising Diffusion Probabilistic Model (DDPM) combined with a UNet architecture for X-ray image synthesis.
• Focused on pneumonia medical condition, our methodology employs over 3000 pneumonia X-ray images obtained from Kaggle for training.
• Results demonstrate the effectiveness of our approach, as the model successfully generated realistic images with low Mean Squared Error (MSE).