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Magnetic Resonance Materials in Physics, Biology and Medicine

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01-10-2020 | Magnetic Resonance Imaging | Research Article

Automated multi-atlas segmentation of gluteus maximus from Dixon and T1-weighted magnetic resonance images

Authors: Martin A. Belzunce, Johann Henckel, Anastasia Fotiadou, Anna Di Laura, Alister Hart

Published in: Magnetic Resonance Materials in Physics, Biology and Medicine | Issue 5/2020

Abstract

Objective

To design, develop and evaluate an automated multi-atlas method for segmentation and volume quantification of gluteus maximus from Dixon and T1-weighted images.

Materials and methods

The multi-atlas segmentation method uses an atlas library constructed from 15 Dixon MRI scans of healthy subjects. A non-rigid registration between each atlas and the target, followed by majority voting label fusion, is used in the segmentation. We propose a region of interest (ROI) to standardize the measurement of muscle bulk. The method was evaluated using the dice similarity coefficient (DSC) and the relative volume difference (RVD) as metrics, for Dixon and T1-weighted target images.

Results

The mean(± SD) DSC was 0.94 ± 0.01 for Dixon images, while 0.93 ± 0.02 for T1-weighted. The RVD between the automated and manual segmentation had a mean(± SD) value of 1.5 ± 4.3% for Dixon and 1.5 ± 4.8% for T1-weighted images. In the muscle bulk ROI, the DSC was 0.95 ± 0.01 and the RVD was 0.6 ± 3.8%.

Conclusion

The method allows an accurate fully automated segmentation of gluteus maximus for Dixon and T1-weighted images and provides a relatively accurate volume measurement in shorter times (~ 20 min) than the current gold-standard manual segmentations (2 h). Visual inspection of the segmentation would be required when higher accuracy is needed.

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Title: Automated multi-atlas segmentation of gluteus maximus from Dixon and T1-weighted magnetic resonance images
Authors: Martin A. Belzunce
Johann Henckel
Anastasia Fotiadou
Anna Di Laura
Alister Hart
Publication date: 01-10-2020
Publisher: Springer International Publishing
Keywords: Magnetic Resonance Imaging
Magnetic Resonance Imaging
Published in: Magnetic Resonance Materials in Physics, Biology and Medicine / Issue 5/2020
Print ISSN: 0968-5243
Electronic ISSN: 1352-8661
DOI: https://doi.org/10.1007/s10334-020-00839-3

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Automated multi-atlas segmentation of gluteus maximus from Dixon and T1-weighted magnetic resonance images

Abstract

Objective

Materials and methods

Results

Conclusion

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Abstract

Objective

Materials and methods

Results

Conclusion

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