Convolutional Neural Networks Promising in Lung Cancer T-Parameter Assessment on Baseline FDG-PET/CT.

Journal: Contrast media & molecular imaging
Published Date: Oct 30, 2018

Abstract

AIM: To develop an algorithm, based on convolutional neural network (CNN), for the classification of lung cancer lesions as T1-T2 or T3-T4 on staging fluorodeoxyglucose positron emission tomography (FDG-PET)/CT images.

Authors

  • Margarita Kirienko
    Department of Biomedical Sciences, Humanitas University, Milan, Pieve Emanuele, Italy.
  • Martina Sollini
    Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (Milan), Italy.
  • Giorgia Silvestri
    Orobix Srl, Bergamo, Italy.
  • Serena Mognetti
    Orobix Srl, Bergamo, Italy.
  • Emanuele Voulaz
    Thoracic Surgery, Humanitas Clinical and Research Center, Milan, Rozzano, Italy.
  • Lidija Antunovic
    Nuclear Medicine, Humanitas Clinical and Research Center, Milan, Rozzano, Italy.
  • Alexia Rossi
    Department of Biomedical Sciences, Humanitas University, Milan, Pieve Emanuele, Italy.
  • Luca Antiga
    Orobix Srl, Bergamo, Italy.
  • Arturo Chiti
    Vita-Salute San Raffaele University, Milan, Italy.

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