Multi-factorial age estimation from skeletal and dental MRI volumes

Darko Štern; Philipp Kainz; Christian Payer; Martin Urschler

doi:10.1007/978-3-319-67389-9_8

Multi-factorial age estimation from skeletal and dental MRI volumes

Darko Štern, Philipp Kainz, Christian Payer, Martin Urschler^*

^*Corresponding author for this work

Institute of Computer Graphics and Vision (7100)

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

Abstract

Age estimation from radiologic data is an important topic in forensic medicine to assess chronological age or to discriminate minors from adults, e.g. asylum seekers lacking valid identification documents. In this work we propose automatic multi-factorial age estimation methods based on MRI data to extend the maximal age range from 19 years, as commonly used for age assessment based on hand bones, up to 25 years, when combined with wisdom teeth and clavicles. Mimicking how radiologists perform age estimation, our proposed method based on deep convolutional neural networks achieves a result of 1.14 \pm 0.96 years of mean absolute error in predicting chronological age. Further, when fine-tuning the same network for majority age classification, we show an improvement in sensitivity of the multi-factorial system compared to solely relying on the hand.

Original language	English
Title of host publication	Machine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Proceedings
Publisher	Springer-Verlag Italia
Pages	61-69
Number of pages	9
Volume	10541 LNCS
ISBN (Print)	9783319673882
DOIs	https://doi.org/10.1007/978-3-319-67389-9_8
Publication status	Published - 2017
Event	8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017 held in conjunction with the 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017: MLMI 2017 / MICCAI 2017 - Quebec City, Canada Duration: 10 Sept 2017 → 10 Sept 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10541 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017 held in conjunction with the 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
Country/Territory	Canada
City	Quebec City
Period	10/09/17 → 10/09/17

Keywords

Convolutional neural network
Forensic age estimation
Information fusion
Multi-factorial method
Random forest

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Fields of Expertise

Information, Communication & Computing

Cooperations

BioTechMed-Graz

Access to Document

10.1007/978-3-319-67389-9_8

Cite this

Štern, D., Kainz, P., Payer, C., & Urschler, M. (2017). Multi-factorial age estimation from skeletal and dental MRI volumes. In Machine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Proceedings (Vol. 10541 LNCS, pp. 61-69). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10541 LNCS). Springer-Verlag Italia. https://doi.org/10.1007/978-3-319-67389-9_8

Multi-factorial age estimation from skeletal and dental MRI volumes. / Štern, Darko; Kainz, Philipp; Payer, Christian et al.
Machine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Proceedings. Vol. 10541 LNCS Springer-Verlag Italia, 2017. p. 61-69 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10541 LNCS).

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

Štern, D, Kainz, P, Payer, C & Urschler, M 2017, Multi-factorial age estimation from skeletal and dental MRI volumes. in Machine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Proceedings. vol. 10541 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10541 LNCS, Springer-Verlag Italia, pp. 61-69, 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017 held in conjunction with the 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017, Quebec City, Canada, 10/09/17. https://doi.org/10.1007/978-3-319-67389-9_8

Štern D, Kainz P, Payer C, Urschler M. Multi-factorial age estimation from skeletal and dental MRI volumes. In Machine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Proceedings. Vol. 10541 LNCS. Springer-Verlag Italia. 2017. p. 61-69. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-67389-9_8

Štern, Darko ; Kainz, Philipp ; Payer, Christian et al. / Multi-factorial age estimation from skeletal and dental MRI volumes. Machine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Proceedings. Vol. 10541 LNCS Springer-Verlag Italia, 2017. pp. 61-69 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Multi-factorial age estimation from skeletal and dental MRI volumes

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Fields of Expertise

Cooperations

Access to Document

Other files and links

FWF - FAME - Fully Automatic MRI-based Age Estimation of Adolescents

Cite this

Multi-factorial age estimation from skeletal and dental MRI volumes

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Fields of Expertise

Cooperations

Access to Document

Other files and links

Projects

FWF - FAME - Fully Automatic MRI-based Age Estimation of Adolescents

Cite this