An age estimation method using brain local features for T1-weighted images

Chihiro Kondo, Koichi Ito, Kai Wu, Kazunori Sato, Yasuyuki Taki, Hiroshi Fukuda, Takafumi Aoki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

Previous statistical analysis studies using large-scale brain magnetic resonance (MR) image databases have examined that brain tissues have age-related morphological changes. This fact indicates that one can estimate the age of a subject from his/her brain MR image by evaluating morphological changes with healthy aging. This paper proposes an age estimation method using local features extracted from T1-weighted MR images. The brain local features are defined by volumes of brain tissues parcellated into local regions defined by the automated anatomical labeling atlas. The proposed method selects optimal local regions to improve the performance of age estimation. We evaluate performance of the proposed method using 1,146 T1-weighted images from a Japanese MR image database. We also discuss the medical implication of selected optimal local regions.

Original languageEnglish
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages666-669
Number of pages4
ISBN (Electronic)9781424492718
DOIs
Publication statusPublished - 2015 Nov 4
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: 2015 Aug 252015 Aug 29

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period15/8/2515/8/29

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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  • Cite this

    Kondo, C., Ito, K., Wu, K., Sato, K., Taki, Y., Fukuda, H., & Aoki, T. (2015). An age estimation method using brain local features for T1-weighted images. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 (pp. 666-669). [7318450] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2015-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2015.7318450