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The Reconstruction Problem
 in, Electrical Impedance Tomography, Methods, History and Applications, Ed. HOLDER, D.S, IOP Series in Medical Physics and Biomedical Engineering
, 2005
"... 1.1 Why is EIT so hard? In conventional medical imaging modalities, such as XRay computerized tomography, a collimated beam of radiation passes through the object in a straight line, and the attenuation of this beam is affected only by the matter which lies along its path. In this sense XRay CT is ..."
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Cited by 8 (4 self)
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1.1 Why is EIT so hard? In conventional medical imaging modalities, such as XRay computerized tomography, a collimated beam of radiation passes through the object in a straight line, and the attenuation of this beam is affected only by the matter which lies along its path. In this sense XRay CT is local, and it means that the pixels or voxels of our image affect only some (in fact a very small proportion) of the measurements. If the radiation were at lower frequency (softer Xrays) the effect of scattering would have to be taken into account and the effect of a change of material in a voxel would no longer be local. As the frequency decreases this nonlocal effect becomes more pronounced until we reach the case of direct current, in which a change in conductivity would have some effect on any measurement of surface voltage when any current pattern is applied. This nonlocal property of conductivity imaging, which still applies at the moderate frequencies used in EIT, is one of the principal reasons that EIT is difficult. It means that to find the conductivity image one must solve a system of simultaneous
reconstruction problem
"... Background: This paper describes the theory and implementation of a new software tool, called Jane, for the study of historical associations. This problem arises in parasitology (associations of hosts and parasites), molecular systematics (associations of orderings and genes), and biogeography (asso ..."
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Background: This paper describes the theory and implementation of a new software tool, called Jane, for the study of historical associations. This problem arises in parasitology (associations of hosts and parasites), molecular systematics (associations of orderings and genes), and biogeography
The reconstruction problem
 in Electrical Impedance Tomography: Methods, History, and Applications, Phys. Med. Biol. 50
, 2005
"... 1.1 Why is EIT so hard? In conventional medical imaging modalities, such as XRay computerized tomography, a collimated beam of radiation passes through the object in a straight line, and the attenuation of this beam is aected only by the matter which lies along its path. In this sense XRay CT is ..."
Abstract

Cited by 1 (0 self)
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1.1 Why is EIT so hard? In conventional medical imaging modalities, such as XRay computerized tomography, a collimated beam of radiation passes through the object in a straight line, and the attenuation of this beam is aected only by the matter which lies along its path. In this sense XRay CT is local, and it means that the pixels or voxels of our image aect only some (in fact a very small proportion) of the measurements. If the radiation were at lower frequency (softer Xrays) the effect of scattering would have to be taken into account and the eect of a change of material in a voxel would no longer be local. As the frequency decreases this nonlocal eect becomes more pronounced until we reach the case of direct current, in which a change in conductivity would have some eect on any measurement of surface voltage when any current pattern is applied. This nonlocal property of conductivity imaging, which still applies at the moderate frequencies used in EIT, is one of the principal reasons that EIT is dicult. It means that to nd the conductivity image one must solve a system of simultaneous
Combinatorial reconstruction problems
, 1989
"... A general technique for tackling various reconstruction problems is presented and applied to some old and some new instances of such problems. ..."
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Cited by 14 (0 self)
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A general technique for tackling various reconstruction problems is presented and applied to some old and some new instances of such problems.
Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems
 IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
, 2007
"... Many problems in signal processing and statistical inference involve finding sparse solutions to underdetermined, or illconditioned, linear systems of equations. A standard approach consists in minimizing an objective function which includes a quadratic (squared ℓ2) error term combined with a spa ..."
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Cited by 539 (17 self)
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Many problems in signal processing and statistical inference involve finding sparse solutions to underdetermined, or illconditioned, linear systems of equations. A standard approach consists in minimizing an objective function which includes a quadratic (squared ℓ2) error term combined with a
Surface reconstruction from unorganized points
 COMPUTER GRAPHICS (SIGGRAPH ’92 PROCEEDINGS)
, 1992
"... We describe and demonstrate an algorithm that takes as input an unorganized set of points fx1�:::�xng IR 3 on or near an unknown manifold M, and produces as output a simplicial surface that approximates M. Neither the topology, the presence of boundaries, nor the geometry of M are assumed to be know ..."
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Cited by 815 (8 self)
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to be known in advance — all are inferred automatically from the data. This problem naturally arises in a variety of practical situations such as range scanning an object from multiple view points, recovery of biological shapes from twodimensional slices, and interactive surface sketching.
The Polynomial Reconstruction Problem and its
"... The Polynomial Reconstruction Problem (PRP) has been introduced in 1999 as a new hard problem. Several cryptographic primitives established on this problem have been constructed. Then it has been studied from the point of view of robustness, and several important properties have been discovered and ..."
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The Polynomial Reconstruction Problem (PRP) has been introduced in 1999 as a new hard problem. Several cryptographic primitives established on this problem have been constructed. Then it has been studied from the point of view of robustness, and several important properties have been discovered
A comparison of bayesian methods for haplotype reconstruction from population genotype data.
 Am J Hum Genet
, 2003
"... In this report, we compare and contrast three previously published Bayesian methods for inferring haplotypes from genotype data in a population sample. We review the methods, emphasizing the differences between them in terms of both the models ("priors") they use and the computational str ..."
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Cited by 557 (7 self)
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individuals to assist in this endeavor, but in general such data may be either unavailable or only partially informative. We focus here on the problem of statistically inferring haplotypes from unphased genotype data for a sample of ("unrelated") individuals from a population. Several approaches
Photorealistic Scene Reconstruction by Voxel Coloring
, 1997
"... A novel scene reconstruction technique is presented, different from previous approaches in its ability to cope with large changes in visibility and its modeling of intrinsic scene color and texture information. The method avoids image correspondence problems by working in a discretized scene space w ..."
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Cited by 467 (21 self)
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A novel scene reconstruction technique is presented, different from previous approaches in its ability to cope with large changes in visibility and its modeling of intrinsic scene color and texture information. The method avoids image correspondence problems by working in a discretized scene space
Robust Uncertainty Principles: Exact Signal Reconstruction From Highly Incomplete Frequency Information
, 2006
"... This paper considers the model problem of reconstructing an object from incomplete frequency samples. Consider a discretetime signal and a randomly chosen set of frequencies. Is it possible to reconstruct from the partial knowledge of its Fourier coefficients on the set? A typical result of this pa ..."
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Cited by 2632 (50 self)
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This paper considers the model problem of reconstructing an object from incomplete frequency samples. Consider a discretetime signal and a randomly chosen set of frequencies. Is it possible to reconstruct from the partial knowledge of its Fourier coefficients on the set? A typical result
Results 1  10
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13,604