Status: In production
The Center for Imaging Science (CIS) at Johns Hopkins University (JHU) has been successful in providing Shape Analysis tools to the BIRN community. These tools are able to compare complex-shaped brain structures and detect differences over the entire surface of the structure. Large-scale shape-analysis processing has been established through the use of Large Deformation Diffeomorphic Metric Mapping (LDDMM, http://cis.jhu.edu/software/lddmm-volume/index.html) and the use of the TeraGrid.
The Large Deformation Diffeomorphic Metric Mapping (LDDMM) tool aims to quantify metric distances on anatomical structures in medical images. This allows for the direct comparison and quantization of morphometric changes due to, for example, disease or aging. As part of these efforts, the Center for Imaging Science at Johns Hopkins University developed techniques to not only compare images, but also to visualize the changes and differences.
Aspects of this work have been published:
Faisal Beg, Michael Miller, Alain Trouve, and Laurent Younes. Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms. International Journal of Computer Vision, Volume 61, Issue 2; February 2005.
M.I. Miller and A. Trouve and L. Younes, On the Metrics and Euler-Lagrange Equations of Computational Anatomy, Annual Review of Biomedical Engineering, 4:375-405, 2002.)
A significant source of error in brain image data is spatial distortions due to inhomogeneities in the main magnetic field (B0), which can arise due to imperfect gradient non-linearity, shimming, magnetic susceptibility effects and chemical shift. These effects can become particularly important for longitudinal studies in which different shim settings can result in substantially different distortions between scan sessions. Although these distortions are most pronounced in functional or diffusion-weighted imaging using echo planar imaging (EPI) sequences, the effect can be significant (on the order of several millimeters) even in conventional structural images.
Work by Susumu Mori’s group at the JHU showed that landmark-based distortion correction using the Large Deformation Diffeomorphic Metric Mapping (LDDMM) algorithm can be a viable method to minimize B0 distortion. They have developed software to perform these operations. This software is currently in the testing phase.
To use this tool: http://www.nitrc.org/projects/lddmm-volume/
