Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification
Paper • 2607.12987 • Published
How to use hcarrion/actinic_keratosis with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda")
pipe.load_textual_inversion("hcarrion/actinic_keratosis")These are textual inversion adaptation weights for stabilityai/stable-diffusion-2-1-base to generate images of the dermatological condition actinic keratosis.
This model is part of the framework cgDDI (Controllable Generation of Diverse Dermatological Imagery), introduced in the paper Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification (MICCAI 2026).
If you use this model or code in your research, please cite:
@inproceedings{carrion2026cgddi,
title = {Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification},
author = {Carri{\'o}n, H{\'e}ctor and Norouzi, Narges},
booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI)},
year = {2026},
publisher = {Springer},
series = {Lecture Notes in Computer Science}
}
Base model
stabilityai/stable-diffusion-2-1-base