A deep learning approach to detect blood vessels in basal cell carcinoma.

Journal: Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
Published Date:

Abstract

PURPOSE: Blood vessels called telangiectasia are visible in skin lesions with the aid of dermoscopy. Telangiectasia are a pivotal identifying feature of basal cell carcinoma. These vessels appear thready, serpiginous, and may also appear arborizing, that is, wide vessels branch into successively thinner vessels. Due to these intricacies, their detection is not an easy task, neither with manual annotation nor with computerized techniques. In this study, we automate the segmentation of telangiectasia in dermoscopic images with a deep learning U-Net approach.

Authors

  • A Maurya
    Missouri University of Science &Technology, Rolla, Missouri.
  • R J Stanley
    Missouri University of Science &Technology, Rolla, Missouri.
  • N Lama
    Missouri University of Science &Technology, Rolla, Missouri.
  • S Jagannathan
    University of Missouri, Kansas City, Missouri.
  • D Saeed
    St. Louis University, St. Louis, Missouri.
  • S Swinfard
    Missouri University of Science &Technology, Rolla, Missouri.
  • J R Hagerty
    S&A Technology, Rolla, Missouri.
  • W V Stoecker
    Stoecker & Associates, Rolla, MO, USA.