Deep learning-based diagnosis models for onychomycosis in dermoscopy.

Journal: Mycoses
Published Date: Apr 1, 2022

Abstract

BACKGROUND: Onychomycosis is a common disease. Emerging noninvasive, real-time techniques such as dermoscopy and deep convolutional neural networks have been proposed for the diagnosis of onychomycosis. However, deep learning application in dermoscopic images has not been reported.

Authors

  • Xianzhong Zhu
    Department of Dermatology and Venereology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
  • Bowen Zheng
    Department of Mechanical Engineering, University of California, Berkeley, CA, 94720, USA.
  • Wenying Cai
    Department of Dermatology and Venereology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
  • Jing Zhang
    MOEMIL Laboratory, School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu, China.
  • Sha Lu
  • Xiqing Li
    Department of Dermatology and Venereology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
  • Liyan Xi
    Department of Dermatology and Venereology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
  • Yinying Kong
    School of Statistics and Mathematics, Guangdong University of Finance and Economics, Guangzhou, China.

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