The iToBoS dataset: skin region images extracted from 3D total body photographs for lesion detection
Journal:
arXiv
Published Date:
Jan 30, 2025
Abstract
Artificial intelligence has significantly advanced skin cancer diagnosis by
enabling rapid and accurate detection of malignant lesions. In this domain,
most publicly available image datasets consist of single, isolated skin lesions
positioned at the center of the image. While these lesion-centric datasets have
been fundamental for developing diagnostic algorithms, they lack the context of
the surrounding skin, which is critical for improving lesion detection. The
iToBoS dataset was created to address this challenge. It includes 16,954 images
of skin regions from 100 participants, captured using 3D total body
photography. Each image roughly corresponds to a $7 \times 9$ cm section of
skin with all suspicious lesions annotated using bounding boxes. Additionally,
the dataset provides metadata such as anatomical location, age group, and sun
damage score for each image. This dataset aims to facilitate training and
benchmarking of algorithms, with the goal of enabling early detection of skin
cancer and deployment of this technology in non-clinical environments.
