Feasibility study of ResNet-50 in the distinction of intraoral neural tumors using histopathological images.

Journal: Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
Published Date: Jun 4, 2024

Abstract

BACKGROUND: Neural tumors are difficult to distinguish based solely on cellularity and often require immunohistochemical staining to aid in identifying the cell lineage. This article investigates the potential of a Convolutional Neural Network for the histopathological classification of the three most prevalent benign neural tumor types: neurofibroma, perineurioma, and schwannoma.

Authors

  • Giovanna Calabrese Dos Santos
    Institute of Science and Technology, Federal University of São Paulo (ICT-UNIFESP), São Paulo, Brazil.
  • Anna Luíza Damaceno Araújo
    Oral Diagnosis Department, Piracicaba Dental School, University of Campinas (FOP-UNICAMP), Piracicaba, São Paulo, Brazil.
  • Henrique Alves de Amorim
    Institute of Science and Technology, Federal University of São Paulo, São José dos Campos, Brazil.
  • Daniela Giraldo-Roldán
    Oral Diagnosis Department, Piracicaba Dental School, University of Campinas (FOP-UNICAMP), Piracicaba, São Paulo, Brazil.
  • Sebastião Silvério de Sousa-Neto
    Departamento de Diagnóstico Oral, Faculdade de Odontologia de Piracicaba, Universidade Estadual de Campinas (FOP-UNICAMP), Piracicaba, São Paulo, Brazil.
  • Pablo Agustin Vargas
    Oral Diagnosis Department, Piracicaba Dental School, University of Campinas (FOP-UNICAMP), Piracicaba, São Paulo, Brazil.
  • Luiz Paulo Kowalski
    Department of Head and Neck Surgery and Otorhinolaryngology, AC Camargo Cancer Center, Sao Paulo, Brazil.
  • Alan Roger Santos-Silva
    Oral Diagnosis Department (Pathology and Semiology), Piracicaba Dental School, University of Campinas, Piracicaba, Brazil.
  • Márcio Ajudarte Lopes
    Oral Diagnosis Department (Pathology and Semiology), Piracicaba Dental School, University of Campinas, Piracicaba, Brazil.
  • Matheus Cardoso Moraes
    Institute of Science and Technology, Federal University of São Paulo (ICT-Unifesp), São José dos Campos, São Paulo, Brazil.

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