Finetuning of GLIDE stable diffusion model for AI-based text-conditional image synthesis of dermoscopic images.

ABSTRACT:

Background

The development of artificial intelligence (AI)-based algorithms and advances in medical domains rely on large datasets. A recent advancement in text-to-image generative AI is GLIDE (Guided Language to Image Diffusion for Generation and Editing). There are a number of representations available in the GLIDE model, but it has not been refined for medical applications.

Methods

For text-conditional image synthesis with classifier-free guidance, we have fine-tuned GLIDE using 10,015 dermoscopic images of seven diagnostic entities, including melanoma and melanocytic nevi. Photorealistic synthetic samples of each diagnostic entity were created by the algorithm. Following this, an experienced dermatologist reviewed 140 images (20 of each entity), with 10 samples originati

SUBMITTER: Shavlokhova V 

PROVIDER: S-EPMC10623307 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature