Fully Automatic Bone Age Estimation from Left Hand MR Images

Darko Stern, Thomas Ebner, Horst Bischof, Sabine Grassegger, Thomas Ehammer, Martin Urschler

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung

Abstract

There has recently been an increased demand in bone age estimation (BAE) of living individuals and human remains in legal medicine applications. A severe drawback of established BAE techniques based on X-ray images is radiation exposure, since many countries prohibit scanning involving ionizing radiation without diagnostic reasons. We propose a completely automated method for BAE based on volumetric hand MRI images. On our database of 56 male caucasian subjects between 13 and 19 years, we are able to estimate the subjects age with a mean difference of 0.85±0.58 years compared to the chronological age, which is in line with radiologist results using established radiographic methods. We see this work as a promising first step towards a novel MRI based bone age estimation system, with the key benefits of lacking exposure to ionizing radiation and higher accuracy due to exploitation of volumetric data.
Originalspracheenglisch
TitelMedical Image Computing and Computer-Assisted Intervention – MICCAI 2014
Untertitel17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part II
Redakteure/-innenPolina Golland, Nobuhiko Hata, Christian Barillot, Joachim Hornegger, Robert Howe
ErscheinungsortSwitzerland
Herausgeber (Verlag)Springer International Publishing AG
Seiten220-227
Band8674
ISBN (elektronisch)978-3-319-10470-6
ISBN (Print)978-3-319-10469-0
DOIs
PublikationsstatusVeröffentlicht - 2014

Publikationsreihe

NameLecture Notes in Computer Science
Band8674

Fields of Expertise

  • Information, Communication & Computing

Kooperationen

  • BioTechMed-Graz

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