Semi-automated algorithm for localization of dermal/epidermal junction in reflectance confocal microscopy images of human skin Journal Article


Authors: Kurugol, S.; Dy, J. G.; Rajadhyaksha, M.; Gossage, K. W.; Weissmann, J.; Brooks, D. H.
Article Title: Semi-automated algorithm for localization of dermal/epidermal junction in reflectance confocal microscopy images of human skin
Title Series: Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XVIII
Abstract: The examination of the dermis/epidermis junction (DEJ) is clinically important for skin cancer diagnosis. Reflectance confocal microscopy (RCM) is an emerging tool for detection of skin cancers in vivo. However, visual localization of the DEJ in RCM images, with high accuracy and repeatability, is challenging, especially in fair skin, due to low contrast, heterogeneous structure and high inter- and intra-subject variability. We recently proposed a semi-automated algorithm to localize the DEJ in z-stacks of RCM images of fair skin, based on feature segmentation and classification. Here we extend the algorithm to dark skin. The extended algorithm first decides the skin type and then applies the appropriate DEJ localization method. In dark skin, strong backscatter from the pigment melanin causes the basal cells above the DEJ to appear with high contrast. To locate those high contrast regions, the algorithm operates on small tiles (regions) and finds the peaks of the smoothed average intensity depth profile of each tile. However, for some tiles, due to heterogeneity, multiple peaks in the depth profile exist and the strongest peak might not be the basal layer peak. To select the correct peak, basal cells are represented with a vector of texture features. The peak with most similar features to this feature vector is selected. The results show that the algorithm detected the skin types correctly for all 17 stacks tested (8 fair, 9 dark). The DEJ detection algorithm achieved an average distance from the ground truth DEJ surface of around 4.7μm for dark skin and around 7-14μm for fair skin. © 2011 SPIE.
Keywords: image acquisition; three dimensional; classification; confocal microscopy; image analysis; algorithms; skin; in-vivo; human skin; reflectance confocal microscopies; reflection; high contrast; diseases; skin cancers; texture features; image segmentation; ground truth; confocal reflectance microscopy; average distance; basal cells; basal layer; depth profile; detection algorithm; feature vectors; heterogeneous structures; localization method; low contrast; multiple-peak; semi-automated; visual localization; climate models; feature extraction
Journal Title: Proceedings of SPIE
Volume: 7904
ISSN: 0277-786X
Publisher: SPIE  
Publication Place: San Francisco, CA
Date Published: 2011-01-01
Start Page: epub
Language: English
DOI: 10.1117/12.875392
PROVIDER: scopus
PMCID: PMC3120112
PUBMED: 21709746
DOI/URL:
Notes: --- - Progress in Biomedical Optics and Imaging - Proceedings of SPIE - Progr. Biomed. Opt. Imaging Proc. SPIE - "Conference code: 84585" - "Export Date: 23 June 2011" - "Article No.: 79041A" - "Sponsors: The Society of Photo-Optical Instrumentation Engineers (SPIE)" - 24 January 2011 through 27 January 2011 - "Source: Scopus"
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