A novel Skin lesion prediction and classification technique: ViT-GradCAM.

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: Sep 1, 2024

Abstract

BACKGROUND: Skin cancer is one of the highly occurring diseases in human life. Early detection and treatment are the prime and necessary points to reduce the malignancy of infections. Deep learning techniques are supplementary tools to assist clinical experts in detecting and localizing skin lesions. Vision transformers (ViT) based on image segmentation classification using multiple classes provide fairly accurate detection and are gaining more popularity due to legitimate multiclass prediction capabilities.

Authors

  • Muhammad Shafiq
    Department of Electrical & Computer Engineering, Sultan Qaboos University, Muscat, Oman. Electronic address: mshafiq@squ.edu.om.
  • Kapil Aggarwal
    Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India.
  • Jagannathan Jayachandran
    Department of Software and Systems Engineering, School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Katpadi, Vellore, India.
  • Gayathri Srinivasan
    Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India.
  • Rajasekhar Boddu
    Department of Software Engineering, College of Computing and Informatics, Haramaya University, Dire Dawa, Ethiopia.
  • Adugna Alemayehu
    Lecturer in Software Engineering, Wachemo University, Hosaina, Ethiopia.

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