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» Synthetic Magnetic Resonance Imaging Revisited
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NN
2000
Springer
170views Neural Networks» more  NN 2000»
13 years 5 months ago
Synthetic brain imaging: grasping, mirror neurons and imitation
The article contributes to the quest to relate global data on brain and behavior (e.g. from PET, Positron Emission Tomography, and fMRI, functional Magnetic Resonance Imaging) to ...
Michael A. Arbib, Aude Billard, Marco Iacoboni, Er...
ECCV
2006
Springer
14 years 7 months ago
Smooth Image Segmentation by Nonparametric Bayesian Inference
A nonparametric Bayesian model for histogram clustering is proposed to automatically determine the number of segments when Markov Random Field constraints enforce smooth class assi...
Peter Orbanz, Joachim M. Buhmann
SCALESPACE
2009
Springer
14 years 15 days ago
PDE-Driven Adaptive Morphology for Matrix Fields
Matrix fields are important in many applications since they are the adequate means to describe anisotropic behaviour in image processing models and physical measurements. A promin...
Bernhard Burgeth, Michael Breuß, Luis Pizarr...
ISMM
2009
Springer
14 years 15 days ago
A Directional Rouy-Tourin Scheme for Adaptive Matrix-Valued Morphology
In order to describe anisotropy in image processing models or physical measurements, matrix fields are a suitable choice. In diffusion tensor magnetic resonance imaging (DT-MRI),...
Luis Pizarro, Bernhard Burgeth, Michael Breuß...
CVPR
2010
IEEE
13 years 11 months ago
Group MRF for fMRI Activation Detection
Noise confounds present serious complications to accurate data analysis in functional magnetic resonance imaging (fMRI). Simply relying on contextual image information often resul...
Bernard Ng, Rafeef Abugharbieh, Ghassan Hamarneh