Atlas based automated segmentation of the quadratus lumborum muscle using non-rigid registration on magnetic resonance images of the thoracolumbar region

Jurcak,V., Fripp, J., Engstrom, C., Walker, D., Salvado, O., Ourselin, S. and Crozier, S. (2008). Atlas based automated segmentation of the quadratus lumborum muscle using non-rigid registration on magnetic resonance images of the thoracolumbar region. In: 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on Biomedical Imaging - From Nano to Macro, Paris, France, (113-116). 14-17 May 2008. doi:10.1109/ISBI.2008.4540945


Author Jurcak,V.
Fripp, J.
Engstrom, C.
Walker, D.
Salvado, O.
Ourselin, S.
Crozier, S.
Title of paper Atlas based automated segmentation of the quadratus lumborum muscle using non-rigid registration on magnetic resonance images of the thoracolumbar region
Conference name 5th IEEE International Symposium on Biomedical Imaging - From Nano to Macro
Conference location Paris, France
Conference dates 14-17 May 2008
Proceedings title 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008   Check publisher's open access policy
Journal name 2008 Ieee International Symposium On Biomedical Imaging: From Nano to Macro, Vols 1-4   Check publisher's open access policy
Place of Publication New York, USA
Publisher IEEE
Publication Year 2008
Sub-type Fully published paper
DOI 10.1109/ISBI.2008.4540945
ISBN 978-1-4244-2002-5
ISSN 1945-7928
Volume 1-4
Start page 113
End page 116
Total pages 4
Language eng
Abstract/Summary Large volume asymmetries of the quadratus lumborum (QL) muscle, determined from time- and expertise-intensive manual segmentation of axial magnetic resonance (MR) images, have been associated with an increased risk of developing pars interarticularis stress lesions in the lumbar spine of cricket fast bowlers. The purpose of the present study was to develop an atlas-based automated segmentation procedure to determine QL volume from MR images. An MR database of axial lumbar spine images from 15 fast bowlers and 6 athletic control subjects was used to generate the atlas-based segmentation procedures. Initially, all images were preprocessed with a bias field correction algorithm and reverse diffusion interpolation algorithm followed by affine and non-rigid registration methods to generate firstly an average shape atlas (AVG), then based on propagation of manually segmented QL data, develop a probability atlas for automated QL segmentation to calculate muscle volume. The Dice similarity metric (DSC) was used to compare between the QL volume data from the manual and automated segmentation procedures. The mean DICE similarity coefficients between the manual and atlas-based automated segmentation values for the right and left QL muscle volumes were 0.75 (sd=0.1) and 0.76 (sd=0.09), respectively. These preliminary results for the automated segmentation of the QL are encouraging. Further development of the atlas-based segmentation procedures will involve incorporating hierarchical probability atlases for adjacent thoracolumbar muscles to improve the robustness and accuracy of the morphometric analyses obtained by this statistical shape modeling approach.
Subjects 0903 Biomedical Engineering
Keyword quadratus lumborum
thoracolumbar musculature
automatic segmentation
atlas creation
MRI
Q-Index Code E1
Q-Index Status Provisional Code

 
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