cgDDI: Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification

This repository contains the textual inversion adaptation weights for stabilityai/stable-diffusion-2-1-base representing the onychomycosis disease concept.

It was introduced in the paper Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification.

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}
}
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