Title
Multi-contrast large deformation diffeomorphic metric mapping for diffusion tensor imaging.
Abstract
Diffusion tensor imaging (DTI) can reveal detailed white matter anatomy and has the potential to detect abnormalities in specific white matter structures. Such detection and quantification are, however, not straightforward. The voxel-based analysis after image normalization is one of the most widely used methods for quantitative image analyses. To apply this approach to DTI, it is important to examine if structures in the white matter are well registered among subjects, which would be highly dependent on employed algorithms for normalization. In this paper, we evaluate the accuracy of normalization of DTI data using a highly elastic transformation algorithm, called large deformation diffeomorphic metric mapping. After simulation-based validation of the algorithm, DTI data from normal subjects were used to measure the registration accuracy. To examine the impact of morphological abnormalities on the accuracy, the algorithm was also tested using data from Alzheimer's disease (AD) patients with severe brain atrophy. The accuracy level was measured by using manual landmark-based white matter matching and surface-based brain and ventricle matching as gold standard. To improve the accuracy level, cascading and multi-contrast approaches were developed. The accuracy level for the white matter was 1.88±0.55 and 2.19±0.84 mm for the measured locations in the controls and patients, respectively.
Year
DOI
Venue
2009
10.1016/j.neuroimage.2009.04.057
NeuroImage
Keywords
Field
DocType
Human,White matter,Magnetic resonance imaging,Diffusion tensor,Normalization,LDDMM
Voxel,Computer vision,Diffusion MRI,Normalization (statistics),White matter,Transformation algorithm,Large deformation diffeomorphic metric mapping,Artificial intelligence,Landmark,Mathematics,Magnetic resonance imaging
Journal
Volume
Issue
ISSN
47
2
1053-8119
Citations 
PageRank 
References 
37
1.52
11
Authors
10
Name
Order
Citations
PageRank
Can Ceritoglu113910.15
Kenichi Oishi245623.56
Xin Li3442.78
Ming-Chung Chou4462.79
Laurent Younes51490120.48
Marilyn Albert631518.31
Constantine Lyketsos7422.03
Peter van Zijl8109073.41
Michael I Miller93123422.82
Susumu Mori1064543.22