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Towards Automatic Bone Age Estimation from MRI: Localization of 3D Anatomical Landmarks

  • Thomas Ebner
  • Darko Stern
  • Rene Donner
  • Horst Bischof
  • Martin Urschler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8674)

Abstract

Bone age estimation (BAE) is an important procedure in forensic practice which recently has seen a shift in attention from X-ray to MRI based imaging. To automate BAE from MRI, localization of the joints between hand bones is a crucial first step, which is challenging due to anatomical variations, different poses and repeating structures within the hand. We propose a landmark localization algorithm using multiple random regression forests, first analyzing the shape of the hand from information of the whole image, thus implicitly modeling the global landmark configuration, followed by a refinement based on more local information to increase prediction accuracy. We are able to clearly outperform related approaches on our dataset of 60 T1-weighted MR images, achieving a mean landmark localization error of 1.4±1.5mm, while having only 0.25% outliers with an error greater than 10mm.

Keywords

Detection Step Landmark Localization Landmark Position Landmark Detection Hand Bone 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Thomas Ebner
    • 1
    • 3
  • Darko Stern
    • 1
  • Rene Donner
    • 2
    • 1
  • Horst Bischof
    • 1
  • Martin Urschler
    • 1
    • 3
    • 4
  1. 1.Institute for Computer Graphics and Vision, BioTechMedGraz University of TechnologyAustria
  2. 2.Computational Image Analysis and Radiology Lab, Department of RadiologyMedical University ViennaAustria
  3. 3.Ludwig Boltzmann Institute for Clinical Forensic ImagingGrazAustria
  4. 4.Department of Legal MedicineMedical University of GrazAustria

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