title: Unsupervised delineation of stratum corneum using reflectance confocal microscopy and spectral clustering.
abstract: BACKGROUND
  Measuring the thickness of the stratum corneum (SC) in vivo is often required in pharmacological, dermatological, and cosmetological studies. Reflectance confocal microscopy (RCM) offers a non-invasive imaging-based approach. However, RCM-based measurements currently rely on purely visual analysis of images, which is time-consuming and suffers from inter-user subjectivity.
  
  
  METHODS
  We developed an unsupervised segmentation algorithm that can automatically delineate the SC layer in stacks of RCM images of human skin. We represent the unique textural appearance of SC layer using complex wavelet transform and distinguish it from deeper granular layers of skin using spectral clustering. Moreover, through localized processing in a matrix of small areas (called 'tiles'), we obtain lateral variation of SC thickness over the entire field of view.
  
  
  RESULTS
  On a set of 15 RCM stacks of normal human skin, our method estimated SC thickness with a mean error of 5.4 ± 5.1 μm compared to the 'ground truth' segmentation obtained from a clinical expert.
  
  
  CONCLUSIONS
  Our algorithm provides a non-invasive RCM imaging-based solution which is automated, rapid, objective, and repeatable.
authors: Electrical and Computer Engineering Department, Northeastern University, Boston, MA, USA.
authors: A
authors: http://orcid.org/0000-0002-3796-7296
authors: A
authors: Bozkurt
authors: Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors: K
authors: K
authors: Kose
authors: Caliber Imaging and Diagnostics, Rochester, NY, USA.
authors: C
authors: C
authors: Alessi-Fox
authors: Electrical and Computer Engineering Department, Northeastern University, Boston, MA, USA.
authors: J G
authors: JG
authors: Dy
authors: Electrical and Computer Engineering Department, Northeastern University, Boston, MA, USA.
authors: D H
authors: DH
authors: Brooks
authors: Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors: M
authors: M
authors: Rajadhyaksha
mesh_terms: D046169:Dermoscopy / Q000379:methods*; D000078404:Epidermal Cells; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D018613:Microscopy, Confocal / Q000379:methods*; D008857:Microscopy, Interference / Q000379:methods*; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D015595:Skin Aging / Q000473:pathology*; D000069558:Unsupervised Machine Learning
keywords: reflectance confocal microscopy; spectral clustering; stratum corneum; unsupervised segmentation