Convolutional neural network evaluation of over-scanning in lung computed tomography.

Journal: Diagnostic and interventional imaging
Published Date: Nov 27, 2018

Abstract

INTRODUCTION: The purpose of this study was to develop a convolutional neural network (CNN) to determine the extent of over-scanning in the Z-direction associated with lung computed tomography (CT) examinations.

Authors

  • M Colevray
    Department of radiology, hôpital de la Croix-Rousse, 103, Grande rue de la Croix-Rousse, 69004 Lyon, France.
  • V M Tatard-Leitman
    Unité CNRS UMR 5220, CREATIS, Inserm U1206, Insa Lyon, université Lyon 1, université Jean-Monnet Saint-Étienne, 7, avenue Jean-Capelle, 69100 Villeurbanne, France; Department of radiology, Louis-Pradel hospital, 59, boulevard Pinel, 69500 Bron, France.
  • S Gouttard
    Department of radiology, hôpital de la Croix-Rousse, 103, Grande rue de la Croix-Rousse, 69004 Lyon, France.
  • P Douek
    Department of radiology, hôpital de la Croix-Rousse, 103, Grande rue de la Croix-Rousse, 69004 Lyon, France; Department of radiology, Louis-Pradel hospital, 59, boulevard Pinel, 69500 Bron, France.
  • L Boussel
    Department of radiology, hôpital de la Croix-Rousse, 103, Grande rue de la Croix-Rousse, 69004 Lyon, France; Unité CNRS UMR 5220, CREATIS, Inserm U1206, Insa Lyon, université Lyon 1, université Jean-Monnet Saint-Étienne, 7, avenue Jean-Capelle, 69100 Villeurbanne, France. Electronic address: loic.boussel@chu-lyon.fr.

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