Enhancing Image Classification of Esophagogastroduodenoscopy Images through Synthetic Data Augmentation

Synthetic data augmentation using class-specific Variational Autoencoders (VAEs) and latent space interpolation can significantly improve the classification accuracy of esophagogastroduodenoscopy (EGD) images, especially for underrepresented classes, by addressing data scarcity and imbalance.