Voxel-based morphometry in single subjects without a scanner-specific normal database using a convolutional neural network.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: Reliable detection of disease-specific atrophy in individual T1w-MRI by voxel-based morphometry (VBM) requires scanner-specific normal databases (NDB), which often are not available. The aim of this retrospective study was to design, train, and test a deep convolutional neural network (CNN) for single-subject VBM without the need for a NDB (CNN-VBM).

Authors

  • Julia Krüger
    Jung diagnostics, Hamburg, Germany.
  • Roland Opfer
    jung diagnostics GmbH, Hamburg, Germany.
  • Lothar Spies
    jung diagnostics GmbH, Hamburg, Germany.
  • Dennis Hedderich
    TUM-NIC Neuroimaging Center, Munich, Germany.
  • Ralph Buchert
    Department for Diagnostic and Interventional Radiology and Nuclear Medicine, University Hospital Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany. r.buchert@uke.de.