Skin Lesion Correspondence Localization in Total Body Photography

TL;DR

This paper introduces a new framework for accurately tracking skin lesions over time in total body photography by combining geometric and texture information on 3D body scans.

Contribution

It presents a novel method that integrates geometric and texture features for precise skin lesion correspondence localization in 3D total body images.

Findings

Success rates comparable to existing longitudinal studies at 10 mm criterion.

Framework effectively combines geometric and texture cues for lesion matching.

Evaluated on public and private datasets with promising results.

Abstract

Longitudinal tracking of skin lesions - finding correspondence, changes in morphology, and texture - is beneficial to the early detection of melanoma. However, it has not been well investigated in the context of full-body imaging. We propose a novel framework combining geometric and texture information to localize skin lesion correspondence from a source scan to a target scan in total body photography (TBP). Body landmarks or sparse correspondence are first created on the source and target 3D textured meshes. Every vertex on each of the meshes is then mapped to a feature vector characterizing the geodesic distances to the landmarks on that mesh. Then, for each lesion of interest (LOI) on the source, its corresponding location on the target is first coarsely estimated using the geometric information encoded in the feature vectors and then refined using the texture information. We evaluated the framework quantitatively on both a public and a private dataset, for which our success rates (at 10 mm criterion) are comparable to the only reported longitudinal study. As full-body 3D capture becomes more prevalent and has higher quality, we expect the proposed method to constitute a valuable step in the longitudinal tracking of skin lesions.