The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.

ABSTRACT: Training of neural networks for automated diagnosis of pigmented skin lesions is hampered by the small size and lack of diversity of available datasets of dermatoscopic images. We tackle this problem by releasing the HAM10000 ("Human Against Machine with 10000 training images") dataset. We collected dermatoscopic images from different populations acquired and stored by different modalities. Given this diversity we had to apply different acquisition and cleaning methods and developed semi-automatic workflows utilizing specifically trained neural networks. The final dataset consists of 10015 dermatoscopic images which are released as a training set for academic machine learning purposes and are publicly available through the ISIC archive. This benchmark dataset can be used for machine learni

SUBMITTER: Tschandl P 

PROVIDER: S-EPMC6091241 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature