Eigenspine: Computing the Correlation between Measures Describing Vertebral Pose for Patients with Adolescent Idiopathic Scoliosis
2014 (English)In: Computerized Medical Imaging and Graphics, ISSN 0895-6111, E-ISSN 1879-0771, Vol. 38, no 7, 549-557 p.Article in journal (Refereed) Published
This paper describes the concept of eigenspine, a concept applicable for determining the correlation between pair-wise combinationsof measures useful for describing the three-dimensional spinal deformities associated with adolescent idiopathic scoliosis. Theproposed data analysis scheme is based upon the use of principal component analysis (PCA) and canonical correlation analysis(CCA). PCA is employed to reduce the dimensionality of the data space, thereby providing a regularization of the measurements,and CCA is employed to determine the linear dependence between pair-wise combinations of different measures. The usefulness ofthe eigenspine concept is demonstrated by analyzing the position and the rotation of all lumbar and thoracic vertebrae as obtainedfrom 46 patients suffering from adolescent idiopathic scoliosis. The analysis showed that the strongest linear relationship is foundbetween the lateral displacement and the coronal rotation of the vertebrae, and that a somewhat weaker but still strong correlationis found between the coronal rotation and the axial rotation of the vertebrae. These results are well in-line with the generalunderstanding of idiopathic scoliosis. Noteworthy though is that the correlation between the anterior-posterior displacement and thesagittal rotation was not as strong as expected and that the obtained results further indicate the need for including the axial vertebralrotation as a measure when characterizing different types of idiopathic scoliosis. Apart from analyzing pair-wise correlationsbetween different measures, the method is believed to be suitable for finding a maximally descriptive low-dimensional combinationof measures describing spinal deformities in idiopathic scoliosis.
Place, publisher, year, edition, pages
Elsevier, 2014. Vol. 38, no 7, 549-557 p.
Spine imaging, Principal component analysis, Canonical correlation analysis, Pose estimation, idiopathic scoliosis
Medical Image Processing
IdentifiersURN: urn:nbn:se:liu:diva-108976DOI: 10.1016/j.compmedimag.2014.06.011ISI: 000343350100001OAI: oai:DiVA.org:liu-108976DiVA: diva2:734287