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SPECT image reconstruction using compound models

SPECT image reconstruction using compound models

引用

IEEE International conference on Acoustics, Speech, and Signal Processing

作者： López, A Molina, R Katsaggelos, AK Mateos, J Univ Granada Dept Lenguajes & Sist Informat Granada 18071 Spain

ISBN: (纸本)0780370414

SPECT (Single Photon Emission Computed Tomography) is used in nuclear medicine to determine the distribution of a radioactive isotope within a patient from tomographic views or projection data. These images are severely degraded due to the presence of noise and several physical factors like attenuation and scattering. In this paper we use, within the Bayesian framework, a Compound Gauss Markov Random Field (CGMRF) as prior model to reconstruct such images. In order to find the Maximum a Posteriori (MAP) estimate we propose a new iterative method, which is stochastic for the line process and deterministic for the reconstruction. The proposed method is tested and compared with other reconstruction methods on both synthetic and real SPECT images.

关键词： image reconstruction

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Hierarchical adaptive regularisation method for depth extraction from planar recording of 3D-integral images

Hierarchical adaptive regularisation method for depth extrac...

引用

IEEE International conference on Acoustics, Speech, and Signal Processing

作者： Manolache, S McCormick, M Kung, SY De Montfort Univ Dept Engn & Technol Leicester LE1 9BH Leics England

ISBN: (纸本)0780370414

The paper presents a novel algorithm for object space reconstruction from the planar (2D) recorded data set of a 3D-integral image. The integral imaging system is described and the associated point spread function is given. The space data extraction is formulated as an inverse problem, which proves ill-conditioned, and tackled by using a hierarchical multiresolution strategy and imposing additional conditions to the sought solution. The hierarchisation strategy and the two-phase adaptive constrained 3D-reconstruction algorithm based on the use of two sigmoid functions are presented. Finally, illustrative simulation results are given.

关键词： image reconstruction

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Euclidean reconstruction and auto-calibration from continuous motion

Euclidean reconstruction and auto-calibration from continuou...

引用

8th International conference on Computer Vision

作者： Kahl, F. Heyden, A. Centre for Mathematical Sciences Lund University Box 118 SE-221 00 Lund Sweden

This paper deals with the problem of incorporating natural regularity conditions on the motion in an MAP estimator for structure and motion recovery from uncalibrated image sequences. The purpose of incorporating these constraints is to increase performance and robustness. Autocalibration and structure and motion algorithms are known to have problems with (i) the frequently occurring critical camera motions, (ii) local minima in the non-linear optimization and (iii) the high correlation between different intrinsic and extrinsic parameters of the camera, e.g. the coupling between focal length and camera position. The camera motion (both intrinsic and extrinsic parameters) is modelled as a random walk process, where the inter-frame motions are assumed to be independently normally distributed. The proposed scheme is demonstrated on both simulated and real data showing the increased performance.

关键词： image reconstruction

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from sinograms to surfaces: A direct approach to the segmentation of tomographic data 4th

引用

4th International conference on Medical image Computing and Computer-Assisted Intervention, MICCAI 2001

作者： Elangovan, Vidya Whitaker, Ross T. School of Computing University of Utah Salt Lake CityUT United States

ISBN: (纸本)3540426973

Under ideal circumstances the problem of tomographic reconstruction is well-posed, and measured data are sufficient to obtain accurate estimates of volume densities. In such cases segmentation and surface estimation from the reconstructed volume are justified. In other situations the reconstructed volumes are not suitable for subsequent segmentation. This can happen in the case of incomplete sinograms, noise in the measurement process, or misregistration of the views. This paper presents a direct approach to the segmentation of incomplete and noisy tomographic data. The strategy is to impose a fairly simple model on the data, and treat segmentation as a problem of estimating the interface between two substances of somewhat homogeneous density. The segmentation is achieved by simultaneously deforming a surface model and updating density parameters in order to achieve a best fit between the projected model and the input sinograms. The deformation is implemented with level-set surface models, calculated at the resolution of the input data. Several computational innovations make the approach feasible with state-of-the-art computers. The usefulness of the approach is demonstrated by reconstructing the shape of spiny dendrites from electron microscope tomographic data. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Deformation

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reconstruction of 3-D figure motion from 2-D correspondences

Reconstruction of 3-D figure motion from 2-D correspondences

引用

2001 IEEE Computer Society conference on Computer Vision and Pattern Recognition

作者： DiFranco, David E. Cham, Tat-Jen Rehg, James M. Dept. of EECS MIT Cambridge MA 02139 United States

We present a method for computing the 3D motion of articulated models from 2D correspondences. An iterative batch algorithm is proposed which estimates the maximum aposteriori trajectory based on the 2D measurements subject to a number of constraints. These include (i) kinematic constraints based on a 3D kinematic model, (ii) joint angle limits, (iii) dynamic smoothing and (iv) 3D key frames which can be specified the user. The framework handles any variation in the number of constraints as well as partial or missing data. This method is shown to obtain favorable reconstruction results on a number of complex human motion sequences.

关键词： image reconstruction

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High resolution 3D image reconstruction based on multistatic UWB phase processing

High resolution 3D image reconstruction based on multistatic...

引用

3rd International conference on Subsurface and Surface Sensing Technologies and Applications

作者： Sai, B Ligthart, L Delft Univ Technol Dept Elect Engn Int Res Ctr Telecommun Transmiss & Radar Fac Informat Technol & Syst NL-2628 CD Delft Netherlands

ISBN: (纸本)0819442054

This paper presents the first results on multistatic ultra wideband (UWB) ground penetrating radar (GPR) interferometry. It has been known that phase data may contain subtle information of the physical and geometrical properties. Most GPR antennas are used in near-field and/or Fresnel regions;the energy scattered from randomly rough surfaces appears diffusely and merely depends on the wavelength of the incident radiation and the incident angles. The random nature makes it a difficult task to determine the profile of the surfaces. Furthermore it is too time-consuming to solve this kind of three-dimensional inhomogeneous problems by using pure electromagnetic approaches, especially when real time applications are required. Therefore we initiated the research on near-field UWB GPR interferometry to profile randomly inhomogeneous rough surfaces as well as their shallow layers in three-dimensional space. In this paper we discuss the first results based on practically measured multistatic UWB phase data scattered from curved objects. An initial algorithm that was developed for image reconstruction in the surface height domain (SHD) has been applied to the measured data. The image patterns show good agreement with the geometries of the practical curved objects. The results demonstrate the applicability of the phase information to characterization of the curved objects.

关键词： UWB GPR near-field multistatic high-resolution imaging 3D reconstruction phase processing topology

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Closed surface reconstruction in X-ray tomography

Closed surface reconstruction in X-ray tomography

引用

IEEE International conference on image Processing

作者： C. Soussen A. Mohammad-Djafari Laboratoire des Signaux et Systèmes CNRS-Supélec-Université Paris-Sud Gif-sur-Yvette France

We study the 3D reconstruction of a binary scene from X-ray tomographic data. In the special case of a compact and uniform object lying in a uniform background, the scene is entirely defined by the object surface. Then, we select parametric surface models, and we directly estimate their parameters from the data. After showing the ability of spherical harmonics and first order splines (polyhedra) to recover complex shapes, we develop an original method to estimate their parameters without using a voxel representation of the scene (object and background). reconstructions are based on the optimization of regularized criteria, which account for the surfaces local smoothness. We use local optimization schemes, and we put the stress on their algorithmic aspects. We finally show the performance of the method on a set of incomplete synthetic data.

关键词： Surface reconstruction X-ray tomography Layout image reconstruction Parameter estimation Shape Parametric statistics Uninterruptible power systems Stress Nondestructive testing

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Euclidean reconstruction and auto-calibration from continuous motion

Euclidean reconstruction and auto-calibration from continuou...

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International conference on Computer Vision (ICCV)

作者： F. Kahl A. Heyden Centre for Mathematical Sciences Lund University Lund Sweden

ISBN: (纸本)0769511430

This paper deals with the problem of incorporating natural regularity conditions on the motion in an MAP estimator for structure and motion recovery from uncalibrated image sequences. The purpose of incorporating these constraints is to increase performance and robustness. Auto-calibration and structure and motion algorithms are known to have problems with (i) the frequently occurring critical camera motions, (ii) local minima in the non-linear optimization and (iii) the high correlation between different intrinsic and extrinsic parameters of the camera, e.g. the coupling between focal length and camera position. The camera motion (both intrinsic and extrinsic parameters) is modelled as a random walk process, where the inter-frame motions are assumed to be independently normally distributed. The proposed scheme is demonstrated on both simulated and real data showing the increased performance.

关键词： Cameras image reconstruction image sequences Motion estimation Layout Maximum likelihood estimation Robustness Calibration Feature extraction reconstruction algorithms

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reconstruction of 3D figure motion from 2D correspondences

Reconstruction of 3D figure motion from 2D correspondences

引用

conference on Computer Vision and Pattern Recognition (CVPR)

作者： D.E. DiFranco Tat-Jen Cham J.M. Rehg Department of EECS MIT Cambridge MA USA School of Computer Engineering Nanyang Technological University Singapore Singapore College of Computing Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)0769512720

We present a method for computing the 3D motion of articulated models from 2D correspondences. An iterative batch algorithm is proposed which estimates the maximum a posteriori trajectory based on 2D measurements subject to a number of constraints. These include (i) kinematic constraints based on a 3D kinematic model, (ii) joint angle limits, (iii) dynamic smoothing, and (iv) 3D key frames which can be specified by the user. The framework handles any variation in the number of constraints as well as partial or missing data. This method is shown to obtain favorable reconstruction results on a number of complex human motion sequences.

关键词： image reconstruction Kinematics Humans Tracking Motion pictures image sequences State-space methods Cameras Educational institutions Iterative algorithms

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Matching, reconstructing and grouping 3D lines from multiple views using uncertain projective geometry

Matching, reconstructing and grouping 3D lines from multiple...

引用

conference on Computer Vision and Pattern Recognition (CVPR)

作者： S. Heuel W. Forstner Institute for Photogrammetry University of Bonn Germany

ISBN: (纸本)0769512720

We present a geometric method for (i) matching 2D line segments from multiple oriented images, (ii) optimally reconstructing 3D line segments and (iii) grouping 3D line segments to corners. The proposed algorithm uses two developments in combining projective geometry and statistics, which are described in this article: (i) the geometric entities points, lines and planes in 2D and 3D and their uncertainty are represented in homogeneous coordinates and new entities may be constructed including their propagated uncertainty. The construction can be performed directly or as an estimation. (ii) relations such as incidence, equality, parallelism and orthogonality between points, lines and planes can be tested statistically based on a given significance level. Using these tools, the resulting algorithm is straightforward and gives reasonable results. It is only based on geometric information and does not use any image intensities, though it can be extended to use other information. The matching of 3D lines does not need any thresholds other than a significance value for the hypotheses tests.

关键词： Testing Uncertainty image reconstruction image segmentation Geometry Computer vision Covariance matrix Statistics data mining Layout

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