CT image segmentation of bone for medical additive manufacturing using a convolutional neural network.

Journal: Computers in biology and medicine
Published Date: Oct 16, 2018

Abstract

BACKGROUND: The most tedious and time-consuming task in medical additive manufacturing (AM) is image segmentation. The aim of the present study was to develop and train a convolutional neural network (CNN) for bone segmentation in computed tomography (CT) scans.

Authors

  • Jordi Minnema
    Amsterdam UMC and Academic Centre for Dentistry Amsterdam (ACTA), Vrije Universiteit Amsterdam, Department of Oral and Maxillofacial Surgery/Pathology, 3D Innovation Lab, Amsterdam Movement Sciences, de Boelelaan 1117, Amsterdam, the Netherlands. Electronic address: j.minnema@vumc.nl.
  • Maureen van Eijnatten
    Amsterdam UMC and Academic Centre for Dentistry Amsterdam (ACTA), Vrije Universiteit Amsterdam, Department of Oral and Maxillofacial Surgery/Pathology, 3D Innovation Lab, Amsterdam Movement Sciences, de Boelelaan 1117, Amsterdam, the Netherlands; Centrum Wiskunde & Informatica (CWI), Science Park 123, Amsterdam, the Netherlands.
  • Wouter Kouw
    Netherlands eScience Center, Science Park 140, Amsterdam, the Netherlands.
  • Faruk Diblen
    Netherlands eScience Center, Science Park 140, Amsterdam, the Netherlands.
  • Adriënne Mendrik
    Netherlands eScience Center, Science Park 140, Amsterdam, the Netherlands.
  • Jan Wolff
    Amsterdam UMC and Academic Centre for Dentistry Amsterdam (ACTA), Vrije Universiteit Amsterdam, Department of Oral and Maxillofacial Surgery/Pathology, 3D Innovation Lab, Amsterdam Movement Sciences, de Boelelaan 1117, Amsterdam, the Netherlands; Department of Oral and Maxillofacial Surgery, Division for Regenerative Orofacial Medicine, University Hospital Hamburg-Eppendorf, Hamburg, Germany.

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