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CORR
2010
Springer
103views Education» more  CORR 2010»
13 years 4 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 9 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 9 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 8 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 8 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