Automated Age Estimation from Hand MRI Volumes Using Deep Learning

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Abstract

Biological age (BA) estimation from radiologic data is an important topic in clinical medicine, e.g. in determining endocrinological diseases or planning paediatric orthopaedic surgeries, while in legal medicine it is employed to approximate chronological age. In this work, we propose the use of deep convolutional neural networks (DCNN) for automatic BA estimation from hand MRI volumes, inspired by the way radiologists visually perform age estimation using established staging schemes that follow physical maturation. In our results we outperform the state of the art automatic BA estimation method, achieving a mean error between estimated and ground truth BA of 0.36±0.300.36±0.30 years, which is in line with radiologists doing visual BA estimation.
Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention – MICCAI 2016
Subtitle of host publication19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II
EditorsSebastien Ourselin, Leo Joskowicz, Mert R. Sabuncu, Gozde Unal, William Wells
PublisherSpringer International Publishing AG
Pages194-202
Number of pages9
Volume9901
ISBN (Electronic)978-3-319-46723-8
ISBN (Print)978-3-319-46722-1
DOIs
Publication statusPublished - 21 Oct 2016
Event19th International Conference on Medical Image Computing & Computer Assisted Intervention - Intercontinental Athenaeum, Athens, Greece
Duration: 17 Oct 201621 Oct 2016
http://www.miccai2016.org

Publication series

NameLecture Notes in Computer Science
PublisherSpringer

Conference

Conference19th International Conference on Medical Image Computing & Computer Assisted Intervention
Abbreviated titleMICCAI
CountryGreece
CityAthens
Period17/10/1621/10/16
Internet address

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Fields of Expertise

  • Information, Communication & Computing

Cooperations

  • BioTechMed-Graz

Cite this

Stern, D., Payer, C., Lepetit, V., & Urschler, M. (2016). Automated Age Estimation from Hand MRI Volumes Using Deep Learning. In S. Ourselin, L. Joskowicz, M. R. Sabuncu, G. Unal, & W. Wells (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II (Vol. 9901, pp. 194-202). (Lecture Notes in Computer Science). Springer International Publishing AG . https://doi.org/10.1007/978-3-319-46723-8_23