Squamous Cell Carcinoma of Skin Cancer Margin Classification From Digital Histopathology Images Using Deep Learning.

Journal: Cancer control : journal of the Moffitt Cancer Center
Published Date: Jan 1, 2022

Abstract

OBJECTIVES: Now a days, squamous cell carcinoma (SCC) margin assessment is done by examining histopathology images and inspection of whole slide images (WSI) using a conventional microscope. This is time-consuming, tedious, and depends on experts' experience which may lead to misdiagnosis and mistreatment plans. This study aims to develop a system for the automatic diagnosis of skin cancer margin for squamous cell carcinoma from histopathology microscopic images by applying deep learning techniques.

Authors

  • Beshatu Debela Wako
    School of Biomedical Engineering, Jimma Institute of Technology, 107839Jimma University, Jimma, Ethiopia.
  • Kokeb Dese
    School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia-378.
  • Roba Elala Ulfata
    Department of Pathology, Jimma Institute of Health, 107839Jimma University, Jimma, Ethiopia.
  • Tilahun Alemayehu Nigatu
    Department of Biomedical Sciences (Anatomy Course Unit), Jimma Institute of Health, 107839Jimma University, Jimma, Ethiopia.
  • Solomon Kebede Turunbedu
    Department of Pathology, Jimma Institute of Health, 107839Jimma University, Jimma, Ethiopia.
  • Timothy Kwa
    School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia-378. Electronic address: tkwa@ucdavis.edu.

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