Abstract: Automated Segmentation of Bones for the Age Assessment in 3D MR Images using Convolutional Neural Networks

  • Markus Auf-der-Mauer
  • Paul-Louis Pröve
  • Eilin Jopp
  • Jochen Herrmann
  • Michael Groth
  • Michael M. Morlock
  • Ben Stanczus
  • Dennis Säring
Conference paper
First Online:
Part of the Informatik aktuell book series (INFORMAT)

Zusammenfassung

The age assessment is a complicated procedure used to determine the chronological age of an individual who lacks legal documentation. Actual studies show that the ossification degree of the growth plates in the knee joint represents a suitable indicator for the majority age. To verify this hypothesis a high number of datasets have to be analysed.

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Literatur

  1. 1.
    Dam EB, Lillholm M, Marques J, et al. Automatic segmentation of high- and lowfield knee MRIs using knee image quantification with data from the osteoarthritis initiative. J Med Imaging. 2015;2(2):024001.Google Scholar
  2. 2.
    Stern D, Ebner T, Bischof H, et al. Fully automatic bone age estimation from left hand MR images. Proc MICCAI. 2014;17:220–227.Google Scholar

Copyright information

© Springer-Verlag GmbH Deutschland 2018

Authors and Affiliations

  • Markus Auf-der-Mauer
    • 1
  • Paul-Louis Pröve
    • 1
  • Eilin Jopp
    • 2
  • Jochen Herrmann
    • 3
  • Michael Groth
    • 3
  • Michael M. Morlock
    • 4
  • Ben Stanczus
    • 1
  • Dennis Säring
    • 1
  1. 1.Medical and Industrial Image ProcessingUniversity of Applied Sciences of WedelWedelDeutschland
  2. 2.Department of Legal MedicineUniversity Medical Center Hamburg-EppendorfHamburgDeutschland
  3. 3.Pediatric Radiology DepartmentUniversity Medical Center Hamburg-EppendorfHamburgDeutschland
  4. 4.Institute of BiomechanicsHamburg University of TechnologyHamburgDeutschland

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