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» Maximum Likelihood Estimators in Magnetic Resonance Imaging
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CIMAGING
2009
145views Hardware» more  CIMAGING 2009»
15 years 3 months ago
Wavelet-based Poisson rate estimation using the Skellam distribution
Owing to the stochastic nature of discrete processes such as photon counts in imaging, real-world data measurements often exhibit heteroscedastic behavior. In particular, time ser...
Keigo Hirakawa, Farhan A. Baqai, Patrick J. Wolfe
VIS
2008
IEEE
214views Visualization» more  VIS 2008»
16 years 3 months ago
Estimating Crossing Fibers: A Tensor Decomposition Approach
Diffusion weighted magnetic resonance imaging is a unique tool for non-invasive investigation of major nerve fiber tracts. Since the popular diffusion tensor (DT-MRI) model is limi...
Thomas Schultz, Hans-Peter Seidel
JMLR
2012
13 years 4 months ago
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
We consider the task of estimating, from observed data, a probabilistic model that is parameterized by a finite number of parameters. In particular, we are considering the situat...
Michael Gutmann, Aapo Hyvärinen
IPMI
1999
Springer
16 years 2 months ago
Continuous Time Dynamic PET Imaging Using List Mode Data
Abstract. We describe a method for computing a continuous time estimate of dynamic changes in tracer density using list mode PET data. The tracer density in each voxel is modeled a...
Thomas E. Nichols, Jinyi Qi, Richard M. Leahy
3DPVT
2006
IEEE
185views Visualization» more  3DPVT 2006»
15 years 8 months ago
A Probabilistic Method for Aligning and Merging Range Images with Anisotropic Error Distribution
This paper describes a probabilistic method of aligning and merging range images. We formulate these issues as problems of estimating the maximum likelihood. By examining the erro...
Ryusuke Sagawa, Nanaho Osawa, Yasushi Yagi