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

Chou, Yi-Yu, Lepore, Natasha, de Zubicaray, Greig I., Rose, Stephen E., Carmichael, Owen T., Becker, James T., Toga, Arthur W. and Thompson, Paul 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 2007. 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro 2007, Arlington, VA, U.S.A., (1288-1291). 12-15 April 2007. doi:10.1109/ISBI.2007.357095


Author Chou, Yi-Yu
Lepore, Natasha
de Zubicaray, Greig I.
Rose, Stephen E.
Carmichael, Owen T.
Becker, James T.
Toga, Arthur W.
Thompson, Paul M.
Title of paper Automated 3D mapping & shape analysis of the lateral ventricles via fluid registration of multiple surface-based atlases
Conference name 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro 2007
Conference location Arlington, VA, U.S.A.
Conference dates 12-15 April 2007
Proceedings title 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro 2007   Check publisher's open access policy
Journal name 2007 4th Ieee International Symposium On Biomedical Imaging : Macro to Nano, Vols 1-3   Check publisher's open access policy
Place of Publication New York, U.S.A.
Publisher IEEE
Publication Year 2007
Sub-type Fully published paper
DOI 10.1109/ISBI.2007.357095
ISBN 1-4244-0672-2
ISSN 1945-7928
Start page 1288
End page 1291
Total pages 4
Language eng
Abstract/Summary 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.
Subjects 11 Medical and Health Sciences
Keyword Biological fluid dynamics
Biomedical MRI
Biomedical measurement
Brain
Diseases
Image matching
Image registration
Image segmentation
Medical image processing
Neurophysiology
Patient monitoring
Shape measurement
Statistical analysis
Q-Index Code E1

 
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