Fully Automatic Bone Age Estimation from Left Hand MR Images

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

doi:10.1007/978-3-319-10470-6_28

Fully Automatic Bone Age Estimation from Left Hand MR Images

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

Institute of Computer Graphics and Vision (7100)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
Subtitle of host publication	17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part II
Editors	Polina Golland, Nobuhiko Hata, Christian Barillot, Joachim Hornegger, Robert Howe
Place of Publication	Switzerland
Publisher	Springer International Publishing AG
Pages	220-227
Volume	8674
ISBN (Electronic)	978-3-319-10470-6
ISBN (Print)	978-3-319-10469-0
DOIs	https://doi.org/10.1007/978-3-319-10470-6_28
Publication status	Published - 2014

Publication series

Name	Lecture Notes in Computer Science
Volume	8674

Fields of Expertise

Information, Communication & Computing

Cooperations

BioTechMed-Graz

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-319-10470-6_28

YOUTH - Adolescent Age Estimation from Magnetic Resonance Images
Urschler, M. & Bischof, H.
1/05/13 → 30/04/15
Project: Research project
Klinisch-Forensische Bildgebung - Developing methods to standardize computer-assisted medical MRI datas [Original in Deutsch: Klinisch-Forensische Bildgebung] - Standard_MRT
Urschler, M., Bornik, A. & Bischof, H.
1/12/08 → 31/05/15
Project: Research project

Cite this

Stern, D., Ebner, T., Bischof, H., Grassegger, S., Ehammer, T., & Urschler, M. (2014). Fully Automatic Bone Age Estimation from Left Hand MR Images. In P. Golland, N. Hata, C. Barillot, J. Hornegger, & R. Howe (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014: 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part II (Vol. 8674, pp. 220-227). (Lecture Notes in Computer Science; Vol. 8674 ). Springer International Publishing AG . https://doi.org/10.1007/978-3-319-10470-6_28

Fully Automatic Bone Age Estimation from Left Hand MR Images. / Stern, Darko; Ebner, Thomas; Bischof, Horst et al.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014: 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part II. ed. / Polina Golland; Nobuhiko Hata; Christian Barillot; Joachim Hornegger; Robert Howe. Vol. 8674 Switzerland: Springer International Publishing AG , 2014. p. 220-227 (Lecture Notes in Computer Science; Vol. 8674 ).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Stern, D, Ebner, T, Bischof, H, Grassegger, S, Ehammer, T & Urschler, M 2014, Fully Automatic Bone Age Estimation from Left Hand MR Images. in P Golland, N Hata, C Barillot, J Hornegger & R Howe (eds), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014: 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part II. vol. 8674, Lecture Notes in Computer Science, vol. 8674 , Springer International Publishing AG , Switzerland, pp. 220-227. https://doi.org/10.1007/978-3-319-10470-6_28

Stern D, Ebner T, Bischof H, Grassegger S, Ehammer T, Urschler M. Fully Automatic Bone Age Estimation from Left Hand MR Images. In Golland P, Hata N, Barillot C, Hornegger J, Howe R, editors, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014: 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part II. Vol. 8674. Switzerland: Springer International Publishing AG . 2014. p. 220-227. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-10470-6_28

Stern, Darko ; Ebner, Thomas ; Bischof, Horst et al. / Fully Automatic Bone Age Estimation from Left Hand MR Images. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014: 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part II. editor / Polina Golland ; Nobuhiko Hata ; Christian Barillot ; Joachim Hornegger ; Robert Howe. Vol. 8674 Switzerland : Springer International Publishing AG , 2014. pp. 220-227 (Lecture Notes in Computer Science).

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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.",

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Fully Automatic Bone Age Estimation from Left Hand MR Images

Abstract

Publication series

Fields of Expertise

Cooperations

UN SDGs

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Projects

YOUTH - Adolescent Age Estimation from Magnetic Resonance Images

Klinisch-Forensische Bildgebung - Developing methods to standardize computer-assisted medical MRI datas [Original in Deutsch: Klinisch-Forensische Bildgebung] - Standard_MRT

Cite this