Techniques and Applications in Skin OCT Analysis

Ai Ping Yow, Ruchir Srivastava, Jun Cheng, Annan Li, Jiang Liu, Leopold Schmetterer, Hong Liang Tey, Damon W.K. Wong

Research output: Chapter in Book/Conference proceedingBook Chapterpeer-review

6 Citations (Scopus)

Abstract

The skin is the largest organ of our body. Skin disease abnormalities which occur within the skin layers are difficult to examine visually and often require biopsies to make a confirmation on a suspected condition. Such invasive methods are not well-accepted by children and women due to the possibility of scarring. Optical coherence tomography (OCT) is a non-invasive technique enabling in vivo examination of sub-surface skin tissue without the need for excision of tissue. However, one of the challenges in OCT imaging is the interpretation and analysis of OCT images. In this review, we discuss the various methodologies in skin layer segmentation and how it could potentially improve the management of skin diseases. We also present a review of works which use advanced machine learning techniques to achieve layers segmentation and detection of skin diseases. Lastly, current challenges in analysis and applications are also discussed.

Original languageEnglish
Title of host publicationAdvances in Experimental Medicine and Biology
PublisherSpringer
Pages149-163
Number of pages15
DOIs
Publication statusPublished - 2020
Externally publishedYes

Publication series

NameAdvances in Experimental Medicine and Biology
Volume1213
ISSN (Print)0065-2598
ISSN (Electronic)2214-8019

Keywords

  • Basal cell carcinoma (BCC)
  • Deep learning
  • Dermal-epidermal junction (DEJ)
  • Dermis
  • Epidermis
  • Graph
  • Optical coherence tomography (OCT)
  • Roughness
  • Segmentation
  • Skin

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (all)

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