Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imaging

Comput Methods Programs Biomed. 2023 Apr:232:107451. doi: 10.1016/j.cmpb.2023.107451. Epub 2023 Mar 2.

Abstract

Background and objectives: 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.

Methods: 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 interface includes built-in features such as mapping 2D skin lesions onto the corresponding 3D model.

Results: The proposed system is developed for skin lesion screening, the focus of this paper is to introduce the system instead of clinical study. Using synthetic and real images we demonstrate the effectiveness of the proposed system by providing multiple views of a target skin lesion, enabling further 3D geometry analysis and longitudinal tracking. Skin lesions are identified as outliers which deserve more attention from a skin cancer physician. Our detector leverages expert annotated labels to learn representations of skin lesions, while capturing the effects of anatomical variability. It takes only a few seconds to capture the entire skin surface, and about half an hour to process and analyse the images.

Conclusions: Our experiments show that the proposed system allows fast and easy whole body 3D imaging. It can be used by dermatological clinics to conduct skin screening, detect and track skin lesions over time, identify suspicious lesions, and document pigmented lesions. The system can potentially save clinicians time and effort significantly. The 3D imaging and analysis has the potential to change the paradigm of whole body photography with many applications in skin diseases, including inflammatory and pigmentary disorders. With reduced time requirements for recording and documenting high-quality skin information, doctors could spend more time providing better-quality treatment based on more detailed and accurate information.

Keywords: 3D human body reconstruction; 3D skin lesion surface map; Data-driven 3D meshes registration; Longitudinal tracking of skin lesions.

MeSH terms

  • Algorithms
  • Artificial Intelligence
  • Humans
  • Neural Networks, Computer
  • Skin Neoplasms* / diagnostic imaging
  • Whole Body Imaging*