EVALUATION OF BRAIN IMAGE NONRIGID REGISTRATION ALGORITHMS BASED ON LOG-EUCLIDEAN MR-DTI CONSISTENCY MEASURES

Several nonrigid registration algorithms have been proposed for inter-subject alignment, used to construct statistical atlases and to identify group differences. Assessment of the accuracy of nonrigid registration algorithms is an essential and complex issue due to its intricate framework and its ap...

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Published in2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro pp. 45 - 48
Main Authors Castro, F.J.S., Clatz, O., Dauguet, J., Archip, N., Thiran, J.-Ph, Warfield, S.K.
Format Conference Proceeding
LanguageEnglish
Published 01.04.2007
Subjects
Biomedical imaging
Brain
Diffusion tensor imaging
Image registration
Imaging phantoms
Magnetic resonance imaging
Minimally invasive surgery
Radiology
Signal processing algorithms
Tensile stress
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Summary:Several nonrigid registration algorithms have been proposed for inter-subject alignment, used to construct statistical atlases and to identify group differences. Assessment of the accuracy of nonrigid registration algorithms is an essential and complex issue due to its intricate framework and its application-dependent behavior. We demonstrate that the diffusion MRI provides an independent means of assessing the quality of alignment achieved on the structural MRI. Diffusion tensor MRI (DT-MRI) enables the comparison of the local position and orientation of regions that appear homogeneous in conventional MRI. We carried out inter-subject alignment of conventional T1-weighted MRI with three different registration algorithms. Consequently, we projected DT-MRI of each subject through the same inter-subject transformation. The quality of the inter-subject alignment is assessed by estimating the consistency of the aligned DT-MRI using the Log-Euclidean framework
ISBN:1424406714
9781424406715
ISSN:1945-7928
1945-8452
DOI:10.1109/ISBI.2007.356784