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» Maximum Likelihood Estimators in Magnetic Resonance Imaging
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MICCAI
2006
Springer
16 years 2 months ago
Fiber Bundle Estimation and Parameterization
Individual white matter fibers cannot be resolved by current magnetic resonance (MR) technology. Many fibers of a fiber bundle will pass through an individual volume element (voxel...
Marc Niethammer, Sylvain Bouix, Carl-Fredrik Westi...
KDD
2012
ACM
238views Data Mining» more  KDD 2012»
13 years 4 months ago
Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data
Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiativ...
Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A....
SAC
2011
ACM
14 years 9 months ago
A quasi-Newton acceleration for high-dimensional optimization algorithms
Abstract In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of ...
Hua Zhou, David Alexander, Kenneth Lange
MICCAI
2000
Springer
15 years 5 months ago
Estimating 3D Strain from 4D Cine-MRI and Echocardiography: In-Vivo Validation
The quantitative estimation of regional cardiac deformation from 3D image sequences has important clinical implications for the assessment of myocardial viability. The validation o...
Xenophon Papademetris, Albert J. Sinusas, Donald P...
CVPR
1997
IEEE
15 years 6 months ago
Motion estimation using ordinal measures
Wepresent a methodfor motion estimation using ordinal measures. Ordinal measures are based on relative ordering of intensity values in a image regioncalled rankpermutation. While ...
Dinkar N. Bhat, Shree K. Nayar, Alok Gupta