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NIPS
2008
13 years 5 months ago
Bayesian Experimental Design of Magnetic Resonance Imaging Sequences
We show how improved sequences for magnetic resonance imaging can be found through optimization of Bayesian design scores. Combining approximate Bayesian inference and natural ima...
Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann,...
SIAMIS
2011
12 years 11 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
ICRA
2006
IEEE
95views Robotics» more  ICRA 2006»
13 years 10 months ago
Numerical Simulations and Lab Tests for Design of MR-compatible Robots
— A numerical simulation of the magnetic field in the imaging volume of a magnetic resonance imaging (MRI) scanner and a method for quick searches for electromagnetic noise sour...
Kiyoyuki Chinzei, Kiyoshi Yoshinaka, Toshikatsu Wa...
WSCG
2003
167views more  WSCG 2003»
13 years 5 months ago
Vector-valued Image Restoration with Applications to Magnetic Resonance Velocity Imaging
The analysis of blood flow patterns and the interaction between salient topological flow features and cardiovascular structure plays an important role in the study of cardiovascul...
Yin-Heung Pauline Ng, Guang-Zhong Yang
CVPR
2005
IEEE
14 years 6 months ago
Machine Learning for Clinical Diagnosis from Functional Magnetic Resonance Imaging
Functional Magnetic Resonance Imaging (fMRI) has enabled scientists to look into the active human brain. FMRI provides a sequence of 3D brain images with intensities representing ...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, No...