AFNI: software for analysis and visualization of functional magnetic resonance neuroimages
Computers and Biomedical Research
Average brain models: a convergence study
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Isotropic Energies, Filters and Splines for Vector Field Regularization
Journal of Mathematical Imaging and Vision
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
Diffusion MRI Registration Using Orientation Distribution Functions
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Unbiased white matter atlas construction using diffusion tensor images
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Geodesic-loxodromes for diffusion tensor interpolation and difference measurement
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Nonlinear registration of diffusion MR images based on fiber bundles
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Improved correspondence for DTI population studies via unbiased atlas building
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
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We propose an unbiased group-wise diffeomorphic registration technique to normalize a group of diffusion tensor (DT) images. Our method uses an implicit reference group-wise registration framework to avoid bias caused by reference selection. Log-Euclidean metrics on diffusion tensors are used for the tensor interpolation and computation of the similarity cost functions. The overall energy function is constructed by a diffeomorphic demons approach. The tensor reorientation is performed and implicitly optimized during the registration procedure. The performance of the proposed method is compared with reference-based diffusion tensor imaging (DTI) registration methods. The registered DTI images have smaller shape differences in terms of reduced variance of the fractional anisotropy maps and more consistent tensor orientations. We demonstrate that fiber tract atlas construction can benefit from the group-wise registration by producing fiber bundles with higher overlaps.