A Stacked Generalization of 3D Orthogonal Deep Learning Convolutional Neural Networks for Improved Detection of White Matter Hyperintensities in 3D FLAIR Images.

Journal: AJNR. American journal of neuroradiology
Published Date: Feb 11, 2021

Abstract

BACKGROUND AND PURPOSE: Accurate and reliable detection of white matter hyperintensities and their volume quantification can provide valuable clinical information to assess neurologic disease progression. In this work, a stacked generalization ensemble of orthogonal 3D convolutional neural networks, StackGen-Net, is explored for improving automated detection of white matter hyperintensities in 3D T2-FLAIR images.

Authors

  • L Umapathy
    From the Departments of Electrical and Computer Engineering (L.U., A.B.).
  • G G Perez-Carrillo
    Medical Imaging (L.U., G.G.P.-C., M.B.K., J.A.R.-T., M.I.A., B.W., A.B.).
  • M B Keerthivasan
    Medical Imaging (L.U., G.G.P.-C., M.B.K., J.A.R.-T., M.I.A., B.W., A.B.).
  • J A Rosado-Toro
    Medical Imaging (L.U., G.G.P.-C., M.B.K., J.A.R.-T., M.I.A., B.W., A.B.).
  • M I Altbach
    Medical Imaging (L.U., B.W., L.M., M.H., M.I.A., A.B.).
  • B Winegar
    Medical Imaging (L.U., B.W., L.M., M.H., M.I.A., A.B.).
  • C Weinkauf
    Surgery (C.W.).
  • A Bilgin
    From the Departments of Electrical and Computer Engineering (L.U., A.B.) bilgin@email.arizona.edu.

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