A skin lesion hair mask dataset with fine-grained annotations.

ABSTRACT: Occlusion of skin lesions in dermoscopic images due to hair affects the performance of computer-assisted lesion analysis algorithms. Lesion analysis can benefit from digital hair removal or realistic hair simulation techniques. To assist in that process, we have created the largest publicly available skin lesion hair segmentation mask dataset by carefully annotating 500 dermoscopic images. Compared to the existing datasets, our dataset is free of non-hair artifacts like ruler markers, bubbles, and ink marks. The dataset is also less prone to over and under segmentations because of fine-grained annotations and quality checks from multiple independent annotators. To create the dataset, first, we collected five hundred copyright-free CC0 licensed dermoscopic images covering different hair pat

SUBMITTER: Hossain SI 

PROVIDER: S-EPMC10293994 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature