Statistical modeling and classification of reflectance confocal microscopy images

Abdelghafour Halimi, Hadj Batatia, Jimmy Le Digabel, Gwendal Josse, Jean-Yves Tourneret

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper deals with the characterization and classification of reflectance confocal microscopy images of human skin. A special attention will be given to the identification and characterization of the lentigo, a phenomenon that originates at the dermo-epidermic junction of the skin. Confocal images are acquired at different skin depths with a high resolution. For each depth, the histograms of pixel intensities are determined, and well statistically modelled with a generalized gamma distribution (GGD). The scale, shape and translation parameters associated with the GGD are estimated using a new natural gradient descent algorithm showing fast convergence properties when compared to state-of-the-art estimation methods. Results show that the estimated parameters can be used to classify clinical images of lentigo and healthy patients. They also show that the scale and shape parameters are good features to identify and characterize the presence of lentigo in skin tissues.

Original languageEnglish
Title of host publication2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
PublisherIEEE
ISBN (Electronic)9781538612514
DOIs
Publication statusPublished - 12 Mar 2018
Event7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing 2017 - Curacao, Curaçao
Duration: 10 Dec 201713 Dec 2017
http://www.cs.huji.ac.il/conferences/CAMSAP17/

Conference

Conference7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing 2017
Abbreviated titleCAMSAP 2017
Country/TerritoryCuraçao
CityCuracao
Period10/12/1713/12/17
Internet address

Keywords

  • lentigo characterization
  • maximum likelihood estimation
  • natural gradient
  • Reflectance confocal microscopy

ASJC Scopus subject areas

  • Signal Processing
  • Control and Optimization
  • Instrumentation

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