Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification
Paper • 2607.12987 • Published
Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
textual_inversion
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/solar_lentigo")cgDDI: solar_lentigo
These are the textual inversion adaptation weights for stabilityai/stable-diffusion-2-1-base to generate dermatological imagery of solar lentigo.
This model is part of the cgDDI (Controllable Generation of Diverse Dermatological Imagery) framework introduced in the paper Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification.
Details & Links
- Paper: Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification
- Repository: GitHub - hectorcarrion/ControllableGenDDI
- Dataset: ControllableGenDDI Dataset
Citation
@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}
}
- Downloads last month
- 34
Model tree for hcarrion/solar_lentigo
Base model
stabilityai/stable-diffusion-2-1-base