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» A Riemannian Framework for Tensor Computing
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PAMI
2008
391views more  PAMI 2008»
13 years 8 months ago
Riemannian Manifold Learning
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Tong Lin, Hongbin Zha
MICCAI
2006
Springer
14 years 9 months ago
Improved Correspondence for DTI Population Studies Via Unbiased Atlas Building
Abstract. We present a method for automatically finding correspondence in Diffusion Tensor Imaging (DTI) from deformable registration to a common atlas. The registration jointly pr...
Casey Goodlett, Brad Davis, Remi Jean, John H. Gil...
MICCAI
2005
Springer
14 years 9 months ago
Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis
Diffusion tensor imaging (DTI) has become the major modality to study properties of white matter and the geometry of fiber tracts of the human brain. Clinical studies mostly focus ...
Isabelle Corouge, P. Thomas Fletcher, Sarang C. Jo...
IPMI
2007
Springer
14 years 9 months ago
A Fuzzy, Nonparametric Segmentation Framework for DTI and MRI Analysis
This paper presents a novel statistical fuzzy-segmentation method for diffusion tensor (DT) images and magnetic resonance (MR) images. Typical fuzzy-segmentation schemes, e.g. thos...
Suyash P. Awate, James C. Gee
CVPR
2006
IEEE
14 years 10 months ago
Affine Invariance Revisited
This paper proposes a Riemannian geometric framework to compute averages and distributions of point configurations so that different configurations up to affine transformations ar...
Evgeni Begelfor, Michael Werman