Synthetic Medical Data Generation using Conditional Diffusion Models
Denoising Diffusion Probabilistic Model (DDPM) generating high-resolution synthetic skin lesion dermoscopy images to balance rare disease datasets.
Project Overview
Solves severe class imbalance in dermatological AI. Trains a class-conditional diffusion model to generate photorealistic melanoma and dermatofibroma lesion images, complete with Frechet Inception Distance (FID) evaluation and privacy leak audit tests.
Solves severe class imbalance in dermatological AI. Trains a class-conditional diffusion model to generate photorealistic melanoma and dermatofibroma lesion images, complete with Frechet Inception Distance (FID) evaluation and privacy leak audit tests.
Denoising Diffusion Probabilistic Model (DDPM) generating high-resolution synthetic skin lesion dermoscopy images to balance rare disease datasets.
Core Project Objectives
Capture continuous analog/digital sensor readings with robust noise filtering and hardware calibration.