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Software @ CIS : lddmm-volume : Aboutabout | tutorial | user validation | manual | BIRN Portal | namespace | faq | credits | changelog | feedbackWhole brain anatomical atlases at sub-millimeter resolution are emerging from the Human Brain Mapping and National Partnership in Advanced Computational Infrastructure (NPACI) initiatives. Analysis and inferences based on these anatomical volumes present a challenge in the emerging field of computational anatomy.
The Large Deformation Diffeomorphic Metric Mapping (LDDMM) tool is an application
which aims to assign metric distances on the space of anatomical images in
Computational Anatomy thereby allowing for the direct comparison and quantization of
morphometric changes in shapes.
As part of these efforts the Center for Imaging Science at Johns Hopkins
University develop techniques to not only compare images, but also to
visualize the changes and differences.
This section will provide a
brief overview of some of the applications of LDDMM and present the general idea behind the principles used.
![]() Another possible use of the tool would be in image segmentation. Image segmentation involves labelling different parts of the given image. In medical imaging this is often required and precision is very important. The following graphic shows how LDDMM given a segmented template can produce the segmented target. ![]() LDDMM in more technical terms gives the user a computational framework to study shape and size via metrics on flows of diffeomorphisms in a computational anatomy environment. The metric distances calculated are geodesic. LDDMM uses MPI and the SPMD architecture.
Last Modified: Friday, 15-Dec-2006 07:55:15 EST |
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