Classification of the dermal-epidermal junction using in-vivo confocal microscopy

Julie Robic (1, 2) , Benjamin Perret (2) , Alex Nkengne (1) , Michel Couprie (2) , Hugues Talbot (2)

1 Clarins Laboratories
2 LIGM - Laboratoire d'Informatique Gaspard-Monge

Reflectance confocal microscopy (RCM) is a powerful tool to visualize the skin layers at cellular resolution. The dermal-epidermal junction (DEJ) is a thin complex 3D structure. It appears as a low-contrasted structure in confocal en-face sections , which is difficult to recognize visually, leading to uncertainty in the classification. In this article, we propose an automated method for segmenting the DEJ with reduced uncertainty. The proposed approach relies on a 3D Conditional Random Field to model the skin biological properties and impose regularization constraints. We improve the restitution of the epidermal and dermal labels while reducing the thickness of the uncertainty area in a coherent biological way from 16.9 µm (ground-truth) to 10.3 µm.

Mots clés: Conditional Random Fields; Reflectance confocal microscopy; image segmentation; skin modeling

Domaines: Traitement des images [eess.IV]

Julie Robic, Benjamin Perret, Alex Nkengne, Michel Couprie, Hugues Talbot. Classification of the dermal-epidermal junction using in-vivo confocal microscopy. International Symposium on Biomedical Imaging, Apr 2017, Melbourne, Australia. pp.252-255, ⟨10.1109/ISBI.2017.7950513⟩. ⟨hal-01548696⟩