1
Both qualitative and quantitative approaches are described for assessing the results of spatial normalization.
2
A methodology for spatial normalization of image data is presented.
3
The automated method gave the best spatial normalization.
4
The approach is illustrated by spatial normalization of 10 DT-MRI data sets to a standard anatomical template.
5
An analysis method called targetless spatial normalization (TSN) was used to improve the sensitivity of statistical testing.
6
Here we present the first step towards realizing such a study, i.e., the spatial normalization of whole tensor data sets.
7
Validation experiments on an independent Indian structural and functional-MRI dataset show the appropriateness of IBTs for spatial normalization of Indian brains.
8
P-A analysis software was extended to include controls for variability in position and orientation to support individual structure spatial normalization (ISSN).
9
We form an iterative scheme that interleaves abnormality detection with deformable registration, gradually improving robustness of the spatial normalization and precision of the detection.
10
Spatial normalization is a crucial step in assessing patterns of neuroanatomical structure and function associated with health and disease.