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CORR
2010
Springer
103views Education» more  CORR 2010»
13 years 6 months ago
Spatially-Adaptive Reconstruction in Computed Tomography Based on Statistical Learning
We propose a direct reconstruction algorithm for Computed Tomography, based on a local fusion of a few preliminary image estimates by means of a non-linear fusion rule. One such ru...
Joseph Shtok, Michael Zibulevsky, Michael Elad
ISBI
2002
IEEE
13 years 11 months ago
Segmentation-free statistical image reconstruction for polyenergetic X-ray computed tomography
This paper describes a statistical iterative reconstruction method for X-ray CT based on a physical model that accounts for the polyenergetic X-ray source spectrum and the measure...
Idris A. Elbakri, Jeffrey A. Fessler
IJCNN
2000
IEEE
13 years 10 months ago
Improved Rotational Invariance for Statistical Inverse in Electrical Impedance Tomography
In this paper we show that rotational invariance can be improved in a neural network based EIT reconstruction approach by a suitably chosen permutation of the input data. The inpu...
Jani Lahtinen, Tomas Martinsen, Jouko Lampinen
ECAI
2006
Springer
13 years 10 months ago
A Learning Classifier Approach to Tomography
Tomography is an important technique for noninvasive imaging: images of the interior of an object are computed from several scanned projections of the object, covering a range of a...
Kees Joost Batenburg
ICASSP
2011
IEEE
12 years 10 months ago
Sparsity-based Sinogram Denoising for low-dose Computed Tomography
We propose a sinogram restoration method which consists of a patch-wise non-linear processing, based on a sparsity prior in terms of a learned dictionary. An off-line learning pro...
Joseph Shtok, Michael Elad, Michael Zibulevsky