Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging.

Journal: Advances in rheumatology (London, England)
Published Date: May 7, 2020

Abstract

BACKGROUND: Currently, magnetic resonance imaging (MRI) is used to evaluate active inflammatory sacroiliitis related to axial spondyloarthritis (axSpA). The qualitative and semiquantitative diagnosis performed by expert radiologists and rheumatologists remains subject to significant intrapersonal and interpersonal variation. This encouraged us to use machine-learning methods for this task.

Authors

  • Matheus Calil Faleiros
    São Carlos School of Engineering, University of São Paulo, Av. Trabalhador São-Carlense, 400, São Carlos, SP, 13566-590, Brazil.
  • Marcello Henrique Nogueira-Barbosa
    Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil. marcello@fmrp.usp.br.
  • Vitor Faeda Dalto
    Ribeirão Preto Medical School Musculoskeletal Imaging Research Laboratory, Ribeirão Preto, Brazil.
  • José Raniery Ferreira Júnior
    Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil.
  • Ariane Priscilla Magalhães Tenório
    Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (FMRP-USP), Ribeirão Preto, SP, Brazil.
  • Rodrigo Luppino-Assad
    Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil.
  • Paulo Louzada-Junior
    Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil.
  • Rangaraj Mandayam Rangayyan
    Electrical and Computer Engineering Schulich School of Engineering University of Calgary, Calgary, Alberta, Canada.
  • Paulo Mazzoncini de Azevedo-Marques
    Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil.

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