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28 January 2015 A Matlab user interface for the statistically assisted fluid registration algorithm and tensor-based morphometry
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Proceedings Volume 9287, 10th International Symposium on Medical Information Processing and Analysis; 928710 (2015) https://doi.org/10.1117/12.2081295
Event: Tenth International Symposium on Medical Information Processing and Analysis, 2014, Cartagena de Indias, Colombia
Abstract
Tensor-Based Morphometry (TBM) is an increasingly popular method for group analysis of brain MRI data. The main steps in the analysis consist of a nonlinear registration to align each individual scan to a common space, and a subsequent statistical analysis to determine morphometric differences, or difference in fiber structure between groups. Recently, we implemented the Statistically-Assisted Fluid Registration Algorithm or SAFIRA,1 which is designed for tracking morphometric differences among populations. To this end, SAFIRA allows the inclusion of statistical priors extracted from the populations being studied as regularizers in the registration. This flexibility and degree of sophistication limit the tool to expert use, even more so considering that SAFIRA was initially implemented in command line mode. Here, we introduce a new, intuitive, easy to use, Matlab-based graphical user interface for SAFIRA’s multivariate TBM. The interface also generates different choices for the TBM statistics, including both the traditional univariate statistics on the Jacobian matrix, and comparison of the full deformation tensors.2 This software will be freely disseminated to the neuroimaging research community.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fernando Yepes-Calderon, Caroline Brun, Nishita Sant, Paul Thompson, and Natasha Lepore "A Matlab user interface for the statistically assisted fluid registration algorithm and tensor-based morphometry", Proc. SPIE 9287, 10th International Symposium on Medical Information Processing and Analysis, 928710 (28 January 2015); doi: 10.1117/12.2081295; https://doi.org/10.1117/12.2081295
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