Automated 3D mapping & shape analysis of the lateral ventricles via fluid registration of multiple surface-based atlases

Chou, Y. Y., Leporè, N., de Zubicaray, G., Rose, S. E., Carmichaet, O. T., Becker, J. T., Toga, A. W., & Thompson, P. M. (2007) Automated 3D mapping & shape analysis of the lateral ventricles via fluid registration of multiple surface-based atlases. In 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, IEEE, Arlington, Virginia, United States, pp. 1288-1291.

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We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles, designed for monitoring degenerative disease effects in clinical neuroscience studies and drug trials. First we used a set of parameterized surfaces to represent the ventricles in a manually labeled set of 9 subjects' MRIs (atlases). We fluidly registered each of these atlases and mesh models to a set of MRIs from 12 Alzheimer's disease (AD) patients and 14 matched healthy elderly subjects, and we averaged the resulting meshes for each of these images. Validation experiments on expert segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease-related alterations monotonically improved as the number of atlases, N, was increased from 1 to 9. We then combined the segmentations with a radial mapping approach to localize ventricular shape differences in patients. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases, and we formulated a statistical stopping criterion to determine the optimal value of N. Anterior horn anomalies in Alzheimer's patients were only detected with the multi-atlas segmentation, which clearly outperformed the standard single-atlas approach.

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ID Code: 85712
Item Type: Conference Paper
Refereed: Yes
DOI: 10.1109/ISBI.2007.357095
ISBN: 1424406722
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Copyright Owner: Copyright 2007 IEEE
Deposited On: 01 Sep 2015 01:25
Last Modified: 03 Sep 2015 03:59

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