Farzi, M, Pozo, JM, McCloskey, E et al. (3 more authors) (2018) Spatio-temporal atlas of bone mineral density ageing. In: Lecture Notes in Computer Science. International Conference on Medical Image Computing and Computer-Assisted Intervention: MICCAI 2018, 16-20 Sep 2018, Granada, Spain. Springer Verlag , pp. 720-728. ISBN 9783030009274
Abstract
Osteoporosis is an age-associated bone disease characterised by low bone mass. An improved understanding of the underlying mechanism for age-related bone loss could lead to enhanced preventive and therapeutic strategies for osteoporosis. In this work, we propose a fully automatic pipeline for developing a spatio-temporal atlas of ageing bone. Bone maps are collected using a dual-energy X-ray absorptiometry (DXA) scanner. Each scan is then warped into a reference template to eliminate morphological variation and establish a correspondence between pixel coordinates. Pixel-wise bone density evolution with ageing was modelled using smooth quantile curves. To construct the atlas, we amalgamated a cohort of 1714 Caucasian women (20–87 years) from five different centres in North Western Europe. As a systematic difference exists between different DXA manufacturers, we propose a novel calibration technique to homogenise bone density measurements across the centres. This technique utilises an alternating minimisation technique to map the observed bone density measurements into a latent standardised space. To the best of our knowledge, this is the first spatio-temporal atlas of ageing bone.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2018. This is an author produced version of a conference paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Biomedical Imaging Science Dept (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Apr 2019 14:22 |
Last Modified: | 30 Apr 2019 14:22 |
Status: | Published |
Publisher: | Springer Verlag |
Identification Number: | 10.1007/978-3-030-00928-1_81 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:145304 |