| HAL-Inria | Publications, software ... of Inria's scientists |
Conference papers
A Log-Euclidean Statistical Analysis of DTI Brain Deformations
Abstract : Diffusion tensor images (DTIs) provide information about deep white matter anatomy that structural magnetic resonance images typically fail to resolve. Non-linear registration of DTIs provides a way to capture the deformations of these structures that would otherwise go unobserved. Here we use an existing method that fully incorporates a useful vector space parameterization of diffeomorphisms, thereby allowing simple and well defined calculation of deformation statistics. An initial analysis of the statistics produced by registration of a group of 37 HIV/AIDS patients illustrates principal modes of deformation that are anatomically meaningful and that corroborate with previous findings. The registration method is developed by incorporating these modes into a statistical regularization criterion. Even though initial results suggest this new criterion over-constrains the registration method, we discuss plausible ways to address this.
Cited literature [19 references]
https://hal.inria.fr/hal-01525407
Contributor : Project-Team Asclepios <>
Submitted on : Saturday, May 20, 2017 - 12:37:45 PM
Last modification on : Monday, August 31, 2020 - 1:06:16 PM
Long-term archiving on: : Tuesday, August 22, 2017 - 12:51:49 AM
Contributor : Project-Team Asclepios <>
Submitted on : Saturday, May 20, 2017 - 12:37:45 PM
Last modification on : Monday, August 31, 2020 - 1:06:16 PM
Long-term archiving on: : Tuesday, August 22, 2017 - 12:51:49 AM
File
cdmri2010.pdf
Files produced by the author(s)