Statistically assisted fluid registration algorithm - SAFIRA
Brun, C. C., Lepore, N., Pennec, X., Chou, Y. Y., Lee, A. D., Barysheva, M., de Zubicaray, G. I., McMahon, K. L., Wright, M. J., & Thompson, P. M. (2010) Statistically assisted fluid registration algorithm - SAFIRA. In 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, Rotterdam, The Netherlands.
In this paper, we develop and validate a new Statistically Assisted Fluid Registration Algorithm (SAFIRA) for brain images. A non-statistical version of this algorithm was first implemented in  and re-formulated using Lagrangian mechanics in . Here we extend this algorithm to 3D: given 3D brain images from a population, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the non-statistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the regularizing (i.e., the non-conservative Lagrangian) terms, creating four versions of the algorithm. We evaluated the accuracy of each algorithm variant using the manually labeled LPBA40 dataset, which provides us with ground truth anatomical segmentations. We also compared the power of the different algorithms using tensor-based morphometry -a technique to analyze local volumetric differences in brain structure- applied to 46 3D brain scans from healthy monozygotic twins.
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|Item Type:||Conference Paper|
|Keywords:||Empirically-guided registration, Fluid, Lagrangian mechanics|
|Divisions:||Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
|Copyright Owner:||Copyright 2010 IEEE|
|Deposited On:||25 Aug 2015 03:21|
|Last Modified:||01 Sep 2015 01:38|
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