Evaluating body composition by combining quantitative spectral detector computed tomography and deep learning-based image segmentation.

Journal: European journal of radiology
Published Date: Sep 1, 2020

Abstract

PURPOSE: Aim of this study was to develop and evaluate a software toolkit, which allows for a fully automated body composition analysis in contrast enhanced abdominal computed tomography leveraging the strengths of both, quantitative information from dual energy computed tomography and simple detection and segmentation tasks performed by deep convolutional neuronal networks (DCNN).

Authors

  • David Zopfs
    Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany.
  • Khaled Bousabarah
    University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Stereotactic and Functional Neurosurgery, Cologne, Germany. khaled.bousabarah@uk-koeln.de.
  • Simon Lennartz
    Faculty of Medicine and University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
  • Daniel Pinto Dos Santos
    University Cologne, Faculty of Medicine and University Hospital Cologne, Department of Diagnostic and Interventional Radiology, Kerpener Straße 62, 50937, Cologne, Germany.
  • Max Schlaak
    Department of Dermatology, Venereology and Allergology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany.
  • Sebastian Theurich
    Cancer- and Immunometabolism Research Group, Gene Center LMU, Ludwig-Maximilians-University, Munich, Germany; Department of Medicine III, University Hospital LMU, Ludwig-Maximilian University, Munich, Germany.
  • Robert Peter Reimer
    University Cologne, Faculty of Medicine and University Hospital Cologne, Department of Diagnostic and Interventional Radiology, Kerpener Straße 62, 50937, Cologne, Germany.
  • David Maintz
    Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany.
  • Stefan Haneder
    Faculty of Medicine and University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
  • Nils Große Hokamp
    Faculty of Medicine and University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany. Nils.Grosse-Hokamp@uk-koeln.de.

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