Synthetic Dermatology Dataset for Racial Bias Mitigation in Tumor Classification

The Synthetic Dermatology Dataset is a two-part collection created through generative image translation designed to facilitate the development of fair and robust skin disease classification models across the full spectrum of Fitzpatrick Skin Types (FST). This dataset was created for the data augmentation study in our paper, which explores the use of this synthetic data approach to mitigate racial bias in AI-assisted dermatologic diagnosis. Dataset Composition (Total 6,000 Images) - The dataset consists of two complementary subsets, derived from 3,000 manually-filtered clinical images: 3,000 Original Images (Simulated FST I–II): - Sourced from the publicly available SD-260 dataset (http://doi.org/10.1109/TNNLS.2019.2917524) - Manually filtered by a board-certified dermatologist to include only high-quality clinical photographs visually consistent with light skin tones (FST I–II). 3,000 Synthetic Images (Simulated FST V–VI): - Generated as synthetic counterparts of the original 3,000 images, translated to simulate darker skin tones (FST V–VI). - The translation was performed using the high-performing I²SB-based translation model (https://doi.org/10.48550/arXiv.2302.05872). Skin Lesion Content - The images are organized for binary classification of tumorous skin diseases (Benign vs. Malignant). - The Benign category includes 2,004 samples, consisting of Nevus (NV) with 926 samples and Seborrheic Keratosis (SK) with 1,078 samples. - The Malignant category includes 996 samples, composed of Basal Cell Carcinoma (BCC) with 395 samples, Squamous Cell Carcinoma (SCC) with 289 samples, and Malignant Melanoma (MM) with 312 samples.合成皮肤病数据集（Synthetic Dermatology Dataset）是一个由两部分组成的数据集，通过生成式图像转换技术构建，旨在助力开发适用于全谱系菲茨帕特里克皮肤分型（Fitzpatrick Skin Types, FST）的公平且鲁棒的皮肤病分类模型。本数据集为配套论文中的数据增强研究所构建，该研究探索了利用此类合成数据方法缓解AI辅助皮肤病诊断中种族偏见的路径。 数据集构成（总计6000张图像） 本数据集包含两个互补子集，均源自3000张经人工筛选的临床图像： - 3000张原始图像（模拟FST I–II型）： - 源自公开可用的SD-260数据集（链接：http://doi.org/10.1109/TNNLS.2019.2917524） - 经执业认证皮肤科医师人工筛选，仅保留视觉上符合浅肤色（FST I–II型）的高质量临床照片。 - 3000张合成图像（模拟FST V–VI型）： - 作为原始3000张图像的合成对应版本生成，经转换以模拟深肤色（FST V–VI型）。 - 该转换过程采用性能优异的基于I²SB的图像转换模型完成（链接：https://doi.org/10.48550/arXiv.2302.05872）。 皮损内容构成 本数据集的图像用于肿瘤性皮肤病的二分类任务（良性 vs 恶性）： - 良性类别包含2004个样本，具体包括926例痣细胞痣（Nevus, NV）与1078例脂溢性角化病（Seborrheic Keratosis, SK）。 - 恶性类别包含996个样本，分别由395例基底细胞癌（Basal Cell Carcinoma, BCC）、289例鳞状细胞癌（Squamous Cell Carcinoma, SCC）以及312例恶性黑色素瘤（Malignant Melanoma, MM）组成。