metadata

license: mit
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': Actinic keratoses
            '1': Basal cell carcinoma
            '2': Benign keratosis-like lesions
            '3': Chickenpox
            '4': Cowpox
            '5': Dermatofibroma
            '6': HFMD
            '7': Healthy
            '8': Measles
            '9': Melanocytic nevi
            '10': Melanoma
            '11': Monkeypox
            '12': Squamous cell carcinoma
            '13': Vascular lesions
  splits:
    - name: train
      num_bytes: 11781822388.236
      num_examples: 29322
    - name: validation
      num_bytes: 1129580056.38
      num_examples: 3660
    - name: test
      num_bytes: 1166877801.52
      num_examples: 3674
  download_size: 9960809758
  dataset_size: 14078280246.136002
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*

Skin Lesions Dataset

A dataset for 14 types of skin lesions classification consisted of merging HAM10000(2019) and MSLDv2.0

The dataset consisted of 14 categories:

Actinic keratoses
Basal cell carcinoma
Benign keratosis-like-lesions
Chickenpox
Cowpox
Dermatofibroma
Healthy
HFMD
Measles
Melanocytic nevi
Melanoma
Monkeypox
Squamous cell carcinoma
Vascular lesions

Load the dataset

from datasets import load_dataset

dataset = load_dataset("ahmed-ai/skin-lesions-dataset")

Citation for the original datasets

MSLDv2.0

@article{Nafisa2023,
title={A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial Diversity},
author={Ali, Shams Nafisa and Ahmed, Md. Tazuddin and Jahan, Tasnim and Paul, Joydip and Sani, S. M. Sakeef and Noor, Nawshaba and Asma, Anzirun Nahar and Hasan, Taufiq},
journal={arXiv preprint arXiv:2306.14169},
year={2023}
}

HAM10000 (2019)

BCN_20000 Dataset: (c) Department of Dermatology, Hospital Clínic de Barcelona

HAM10000 Dataset: (c) by ViDIR Group, Department of Dermatology, Medical University of Vienna; https://doi.org/10.1038/sdata.2018.161

MSK Dataset: (c) Anonymous; https://arxiv.org/abs/1710.05006; https://arxiv.org/abs/1902.03368