Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imaging
David Ahmedt-Aristizabal, Chuong Nguyen, Lachlan Tychsen-Smith, Ashley, Stacey, Shenghong Li, Joseph Pathikulangara, Lars Petersson, Dadong Wang

TL;DR
This paper introduces 3DSkin-mapper, a 3D whole-body imaging system utilizing AI for rapid detection, mapping, and tracking of pigmented skin lesions, aiming to improve dermatological screening and documentation.
Contribution
The paper presents a novel modular 3D imaging system with algorithms for skin lesion detection and tracking, enabling fast, comprehensive skin analysis without prior clinical studies.
Findings
System captures entire skin surface in seconds
Allows detailed 3D visualization and longitudinal tracking
Potential to streamline dermatological screening processes
Abstract
Advanced artificial intelligence and machine learning have great potential to redefine how skin lesions are detected, mapped, tracked and documented. Here, We propose a 3D whole-body imaging system known as 3DSkin-mapper to enable automated detection, evaluation and mapping of skin lesions. A modular camera rig arranged in a cylindrical configuration was designed to automatically capture images of the entire skin surface of a subject synchronously from multiple angles. Based on the images, we developed algorithms for 3D model reconstruction, data processing and skin lesion detection and tracking based on deep convolutional neural networks. We also introduced a customised, user-friendly, and adaptable interface that enables individuals to interactively visualise, manipulate, and annotate the images. The proposed system is developed for skin lesion screening, the focus of this paper is to…
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Taxonomy
TopicsCutaneous Melanoma Detection and Management · Cutaneous lymphoproliferative disorders research · Digital Imaging in Medicine
