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Generalized support constraint for three-dimensional reconstruction from incomplete Fourier spectra

JOURNAL OF ELECTRONIC IMAGING 1997年第4期6卷 426-438页

作者： Payot, E Preteux, FJ Trousset, Y Guillemaud, R CEA LETI DSYS F-38054 Grenoble 9 France Inst Natl Telecommun F-91011 Evry France G E Med Syst F-78533 Buc France

Many imaging systems involve a loss of information that requires the incorporation of prior knowledge in the restoration/reconstruction process. We focus on the typical case of 30 reconstruction from an incomplete set of projections. An approach based an constrained optimization is introduced This approach provides a powerful mathematical framework for selecting a specific solution from the set of feasible solutions;this is done by minimizing some criteria depending on prior densitometric information that can be interpreted through a generalized support constraint. We propose a global optimization scheme using a deterministic relaxation algorithm based on Bregman's algorithm associated with half-quadratic minimization techniques. When used for 30 vascular reconstruction from 2D digital subtracted angiography (DSA) data, such an approach enables the reconstruction of a well-contrasted 30 vascular network in comparison with results obtained using standard algorithms. (C) 1997 SPIE and IS&T.

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Self Tuning Kalman Filter Estimation of Atmospheric Warp

Self Tuning Kalman Filter Estimation of Atmospheric Warp

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conference on image reconstruction from incomplete data v

作者： Tahtali, Murat Lambert, Andrew Fraser, Donald UNSW ADFA Sch Aerosp Civil & Mech Engn Canberra ACT 2600 Australia UNSW ADFA Sch Informat Technol & Elect Engn Canberra ACT 2600 Australia

ISBN: (纸本)9780819472960

In our previous work we have demonstrated that the perceived wander of image intensities as seen through the windows" of each pixel due to atmospheric turbulence can be modelled as a simple oscillator pixel-by-pixel and a linear Kalman filter (KF) can be finetuned to predict to a certain extent short term future deformations. In this paper, we are expanding the Kalman filter into a Hybrid Extended Kalman filter (HEKF) to fine tune itself by relaxing the oscillator parameters at each individual pixel. Results show that HEKF performs significantly better than linear KF.

关键词： Kalman filter image registration shiftmaps atmospheric warp image restoration

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Dictionary Learning from incomplete data for Efficient image Restoration 25

Dictionary Learning from Incomplete Data for Efficient Image...

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25th European Signal Processing conference (EUSIPCO)

作者： Naumova, valeriya Schnass, Karin Simula Res Lab Sect Comp & Software Martin Linges 25 Fornebu Norway Univ Innsbruck Dept Math Technikerstr 13 A-6020 Innsbruck Austria

ISBN: (纸本)9780992862671

In real-world image processing applications, the data is high dimensional but the amount of high-quality data needed to train the model is very limited. In this paper, we demonstrate applicability of a recently presented method for dictionary learning from incomplete data, the so-called Iterative Thresholding and K residual Means for Masked data, to deal with high-dimensional data in an efficient way. In particular, the proposed algorithm incorporates a corruption model directly at the dictionary learning stage, also enabling reconstruction of the low-rank component again from corrupted signals. These modifications circumvent some difficulties associated with the efficient dictionary learning procedure in the presence of limited or incomplete data. We choose an image inpainting problem as a guiding example, and further propose a procedure for automatic detection and reconstruction of the low-rank component from incomplete data and adaptive parameter selection for the sparse image reconstruction. We benchmark the efficacy and efficiency of our algorithm in terms of computing time and accuracy on colour, 3D medical, and hyperspectral images by comparing it to its dictionary learning counterparts.

关键词： image reconstruction

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Three-dimensional image reconstruction in variable density acoustic tomography

Three-dimensional image reconstruction in variable density a...

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conference on image reconstruction from incomplete data Iv

作者： Anastasio, Mark A. Shi, Daxin IIT Dept Biomed Engn Chicago IL 60616 USA

ISBN: (纸本)0819463957

Diffraction tomography (DT) is an established imaging technique for use with diffracting wavefields, which represents a generalized form of x-ray tomography. In this work, we revisit the three-dimensional reconstruction problem of DT for variable density acoustic media. Novel reconstruction algorithms are developed for reconstructing separate images that depict a weakly scattering object's compressibility and density variations. If tomographic measurement data are acquired at four distinct temporal frequencies, we demonstrate that the effects of object dispersion can be accounted for completely by use of analytic reconstruction formulas. Computer-simulation studies are conducted to demonstrate the developed image reconstruction methods.

关键词： ultrasound tomography acoustic dispersion diffraction tomography image reconstruction

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Multi-spectral intensity diffraction tomography

Multi-spectral intensity diffraction tomography

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conference on image reconstruction from incomplete data v

作者： Anastasio, Mark A. Xu, Qiaofeng Shi, Daxin IIT Dept Biomed Engn Med Imaging Res Ctr Chicago IL 60616 USA Toshiba Med Res Inst USA Inc Vernon Hills IL USA

ISBN: (纸本)9780819472960

Intensity diffraction tomography (I-DT) is a, non-interferometric imaging method for reconstructing the complex-valued refractive index distribution of a, weakly scattering object. The original formulation of I-DT requires measurement of two in-line intensity measurements on parallel detector planes at each tomographic view angle. In this work, a reconstruction theory for multi-spectral is established and investigated for use with single material objects whose dispersion characteristics are known a priori. Unlike other I-DT methods, the temporal frequency of the illuminating plane-wave represents the degree-of-freedom of the imaging system that is varied to acquire two independent intensity measurements on a fixed detector-plane. Moreover, the proposed method accounts for object dispersion.

关键词： Diffraction tomography phase-contrast tomography three-dimensional image reconstruction

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Research on improved image reconstruction algorithms of OCT based on incomplete projection data - art. no. 68321H

Research on improved image reconstruction algorithms of OCT ...

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conference on Holography and Diffractive Optics III

作者： Tang, Xiaochun Gao, Yiqing Nanchang Hangkong Univ Minist Educ China Key Lab Nondestruct Test Nanchang 330063 Jiangxi Peoples R China

ISBN: (纸本)9780819470072

In order to improve the quality and solve the problem of low speed of image reconstruction in the traditional optical computerized tomography (OCT) when the data acquired is incomplete projection, the multiple constrained of genetic algorithm based on algebraic iterative was proposed. Generally speaking, under the condition of multiple-objective optimization, the common extreme point for all the objective functions doesn't exist. So we can achieve the preferable compromise in the contradictions of multiple objectives. In this article, there are three constrained conditions. The first one is the maximum entropy criterion which is used mostly to solve the problem of OCT image reconstruction when the data acquired is incomplete projection recently. The second one is the minimum criteria of peak value which is introduced to suppress noise effectively and ensure the gliding property of the image reconstruction, because of the first one leading to noise amplification during the iterative process. The last constrained condition is the minimum criteria of the difference between the projection again of image reconstruction and the original projection. The concept of penalize-function is introduced into the genetic algorithm, which would transform the constrained optimization problem to unconstrained. It is clearly demonstrated from the experiment results that the algorithm reconstruction technique can efficiently improve the quality of images reconstruction of the incomplete projection data.

关键词： incomplete projection data image reconstruction multiple constrained genetic algorithm

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Spectral image Estimation for Coded Aperture Snapshot Spectral imagers

Spectral Image Estimation for Coded Aperture Snapshot Spectr...

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conference on image reconstruction from incomplete data v

作者： Wagadarikar, Ashwin A. Pitsianis, Nikos P. Sun, Xiaobai Brady, David J. Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA Duke Univ Dept Comp Sci Durham NC 27708 USA

ISBN: (纸本)9780819472960

This paper describes numerical estimation techniques for coded aperture snapshot spectral imagers (CASSI). In a snapshot, a CASSI captures a two-dimensional (2D) array of measurements that is an encoded representation of both spectral information and 2D spatial information of a scene. The spatial information is modulated by a coded aperture and the spectral information is modulated by a dispersive element. The estimation process decodes the 2D measurements to render a three-dimensional spatio-spectral estimate of the scene, and is therefore an indispensable component of the spectral imager. Numerical estimation results, are presented.

关键词： coded aperture snapshot spectral imager system modeling spectral image estimation

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Parallelized Bayesian inversion for three-dimensional dental X-ray imaging

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IEEE TRANSACTIONS ON MEDICAL IMAGING 2006年第2期25卷 218-228页

作者： Kolehmainen, v vanne, A Siltanen, S Järvenpää, S Kaipio, JP Lassas, M Kalke, M Univ Kuopio FIN-70211 Kuopio Finland PaloDEx Grp FIN-04301 Tuusula Finland Aalto Univ FIN-02015 Helsinki Finland

Diagnostic and operational tasks based on dental radiology often require three-dimensional (3-D) information that is not available in a single X-ray projection image. Comprehensive 3-D information about tissues can be obtained by computerized tomography (CT) imaging. However, in dental imaging a conventional CT scan may not be available or practical because of high radiation dose, low-resolution or the cost of the CT scanner equipment. In this paper, we consider a novel type of 3-D imaging modality for dental radiology. We consider situations in which projection images of the teeth are taken from a few sparsely distributed projection directions using the dentist's regular (digital) X-ray equipment and the 3-D X-ray attenuation function is reconstructed. A complication in these experiments is that the reconstruction of the 3-D structure based on a few projection images becomes an ill-posed inverse problem. Bayesian inversion is a well suited framework for reconstruction from such incomplete data. In Bayesian inversion, the ill-posed reconstruction problem is formulated in a well-posed probabilistic form in which a priori information is used to compensate for the incomplete information of the projection data. In this paper we propose a Bayesian method for 3-D reconstruction in dental radiology. The method is partially based on Kolehmainen et al. 2003. The prior model for dental structures consist of a weighted v and total variation (Tv)-prior together with the positivity prior. The inverse problem is stated as finding the maximum a posteriori (MAP) estimate. To make the 3-D reconstruction computationally feasible, a parallelized version of an optimization algorithm is implemented for a Beowulf cluster computer. The method is tested with projection data from dental specimens and patient data. Tomosynthetic reconstructions are given as reference for the proposed method.

关键词： Bayesian inversion dental radiology inverse problem parallel computing tomography total variation X-ray imaging

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3D image reconstruction algorithms for cryo electron microscopy images of virus particles

3D image reconstruction algorithms for cryo electron microsc...

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conference on image reconstruction from incomplete data

作者： Doerschuk, PC Johnson, JE Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

A statistical model for the object and the complete image formation process in cryo electron microscopy of viruses is presented. Using this model, maximum likelihood reconstructions of the 3D structure of viruses are ... 详细信息

ISBN: (纸本)0819437689

关键词： cryo electron microscopy expectation-maximization algorithm statistical inverse problems viruses

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Support estimation for phase retrieval image reconstruction from sparse-aperture interferometry data

Support estimation for phase retrieval image reconstruction ...

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conference on image reconstruction from incomplete data vII

作者： DeSantis, Zachary J. Fienup, James R. Univ Rochester Inst Opt Rochester NY 14627 USA

ISBN: (纸本)9780819492173

Imaging interferometry suffers from sparse Fourier measurements, and, at the visible wavelengths, a lack of phase information, creating a need for an image reconstruction algorithm. A support constraint is useful for optimization but is often not known a priori. The two-point rule for finding an object support from the autocorrelation is limited in usefulness by the sparsity and non-uniformity of the Fourier data and is insufficient for image reconstruction. Compactness, a common prior, does not require knowledge of the support. Compactness penalizes solutions that have bright pixels away from the center, favoring soft-edged objects with a bright center and darker extremities. With regards to imaging hard-edged objects such as satellites, a support constraint is desired but unknown and compactness may be unfavorable. Combining various techniques, a method of simultaneously estimating the object's support and the object's intensity distribution is presented. Though all the optimization parameters are in the image domain, we are effectively performing phase retrieval at the measurement locations and interpolation between the sparse data points.

关键词： image reconstruction imaging interferometry interpolation phase retrieval support constraint

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