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AcneAI: A New Acne Severity Assessment Method Using Digital Images and Deep Learning

  • Léa Gazeau,
  • Hang Nguyen,
  • Zung Nguyen,
  • Mariia Lebedeva,
  • Thanh Nguyen,
  • Tat-Dat To,
  • Jimmy Le Digabel,
  • Jérome Filiol,
  • Gwendal Josse,
  • Clifford Perlis,
  • Jonathan Wolfe

摘要

In this paper we present a new AcneAI system that automatically analyses facial acne images in a precise way, detecting and scoring every single acne lesion within an image. Its workflow consists of three main steps: 1) segmentation of all acne and acne-like lesions, 2) scoring of each acne lesion, 3) combining individual acne lesion scores into an overall acne severity score for the whole image, that ranges from 0 to 100. Our clinical tests on the Acne04 dataset shows that AcneAI has an Intraclass Correlation Coefficient (ICC) score of 0.8 in severity classification. We obtained an area under the curve (AUC) of 0.88 in detecting inflammatory lesions in a clinical dataset obtained from a multi-centric clinical trial.