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检索条件"任意字段=Conference on Image Reconstruction from Incomplete Data VIII"

共 418 条记录，以下是361-370 订阅

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data restoration in chromo-tomographic hyperspectral imaging

Data restoration in chromo-tomographic hyperspectral imaging

引用

conference on image reconstruction from incomplete data

作者： An, M Brodzik, AK Mooney, J Tolimieri, R Psypher Inc Boston MA 02134 USA

ISBN: (纸本)0819437689

Recently, a new approach to hyperspectral imaging, relying on the theory of computed tomography, was proposed by researchers at the Air Force Research Laboratory. The approach allows all photons to be recorded and therefore increases robustness of the imaging system to noise and focal plane array non-uniformities. However, as all computed tomography systems, the approach suffers from the limited angle problem, which obstructs reconstruction of the hyperspectral information. In this work we present a direct, one-step algorithm for reconstruction of the unknown information based on a priori knowledge about the hyperspectral image.

关键词： hyperspectral chromotomography computed tomography singular value decomposition

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Obtaining three dimensional probability density functions from projected data

Obtaining three dimensional probability density functions fr...

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conference on image reconstruction from incomplete data

作者： Jaffe, JS Univ Calif San Diego Scripps Inst Oceanog Marine Phys Lab La Jolla CA 92093 USA

ISBN: (纸本)0819437689

In many experimental observation systems where the goal is to record a 3-dimensional observation of an object, or a set of objects, a lower dimensional projection of the intended subject is obtained. In some situations only the statistical properties of such objects is desired: the three dimensional probablility density function. This article demonstrates that under special symmetries this function can be obtained from a two dimensional probability density function which, has been obtained from the observed, projected data. Standard tomographic theorems can be used to guarantee the uniqueness of this function and a natural basis set can be used in computing the three dimensional function from the two dimensional projection. Here, the theory of this inversion is explored from a theoretical and numerical point of view with some examples of data functions taken from scientific experiments

关键词： tomography probability density function inverse theory

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Evaluation of rotational kernel transformation technique for enhancement of coronary optical coherence tomography images

Evaluation of rotational kernel transformation technique for...

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conference on image reconstruction from incomplete data

作者： Rogowska, J Brezinski, ME Brigham & Womens Hosp Dept Orthoped Boston MA 02115 USA

ISBN: (纸本)0819437689

During the last few years, OCT has demonstrated considerable promise as a method of high-resolution intravascular imaging. The goal of this study was to apply and to test the applicability of the rotating kernel transformation (RKT) technique to the speckle reduction and enhancement of OCT images. The technique is locally adaptive. It is based on sequential application of directional masks and selection of the maximum of all outputs. This method enhances the image features by emphasizing thin edges while suppressing a noisy background. Qualitatively, the RKT algorithm provides noticeable improvement over the original image. All processed images are smoother and have better-defined borders of media, intima, and plaque. The quantitative evaluation of RKT performance showed that in terms of average contrast-to-noise ratio, there is a significant improvement in image quality between original and enhanced images. The RKT image enhancement technique shows great promise in improving OCT images for superior boundary identification.

关键词： optical coherence tomography image speckle rotating kernel transformation technique coronary plaque

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Maximum-likelihood density modification for X-ray crystallography

Maximum-likelihood density modification for X-ray crystallog...

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conference on image reconstruction from incomplete data

作者： Terwilliger, TC Univ Calif Los Alamos Natl Lab Los Alamos NM 87545 USA

ISBN: (纸本)0819437689

A likelihood-based approach to density modification for macromolecular crystallography is presented. The approach can be applied in many cases where some information is available about the electron density at various points in the unit cell. The most important aspect of the method consists of likelihood functions that represent the probability that a particular value of electron density is consistent with prior expectations for the electron density at that point in the unit cell. Such likelihood functions are combined with likelihood functions based on experiment and with any prior knowledge about structure factors to form a combined likelihood function for each structure factor. An approach for maximizing the combined likelihood function that is simple acid rapid is developed. The density modification approach is applied to real and model data and is shown to result in substantially greater improvement in map quality than existing methods.

关键词： Crystals X-rays Proteins Crystallography Chemical species Cesium Pattern recognition Selenium data modeling Macromolecules

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Numerical considerations when imaging penetrable highly scattering objects from incomplete data

Numerical considerations when imaging penetrable highly scat...

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conference on image reconstruction from incomplete data

作者： Morales-Porras, AE Testorf, ME McGahan, RV Fiddy, MA Univ Massachusetts Dept Elect & Comp Engn Lowell MA 01854 USA

ISBN: (纸本)0819437689

Over the last ten years progress has been made in developing inverse scattering algorithms that go beyond the range of applicability of the first Born and Rytov approximations. Our efforts have focussed on a nonlinear filtering technique which appears at first glance to be straightforward to implement and offer the possibility of recovering strongly scattering structures. Upon applying the method to various simulated and real data sets, its performance has been inconsistent. In this paper we discuss the various numerical concerns that have arisen from executing a nonlinear filter on limited sampled noisy data and clarify the potential advantages and limitations of this approach.

关键词： inverse scattering cepstral filtering PDFT phase unwrapping

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New Fourier reconstruction algorithms for computerized tomography

New Fourier reconstruction algorithms for computerized tomog...

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conference on Wavelet Applications in Signal and image Processing viii

作者： Potts, D Steidl, G Med Univ Lubeck Inst Math D-25360 Lubeck Germany

ISBN: (纸本)0819437646

In this paper, we propose two new algorithms for high quality Fourier reconstructions of digital N x N images from their Radon transform. Both algorithms are based on fast Fourier transforms for nonequispaced data (NFFT) and require only O(N-2 log N) arithmetic operations. While the first algorithm includes a bivariate NFFT on the polar grid, the second algorithm consists of several univariate NFFTs on the so-called linogram.

关键词： fast Fourier transform for nonequispaced data radon transform computerized tomography gridding linogram

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Tomographic blur identification using image edges

Tomographic blur identification using image edges

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conference on image reconstruction from incomplete data

作者： Bones, PJ Bretschneider, T Forne, CJ Millane, RP McNeill, SJ Univ Canterbury Dept Elect & Elect Engn Christchurch 1 New Zealand

ISBN: (纸本)0819437689

A method for estimating the point spread function of a remotely sensed image is described. The technique developed is based on locating and measuring blurred linear features in the imagery and tomographically reconstructing the point spread function. image features able to be modelled by a single step function or by a combination of two steps are located. For the latter cases a form of blind deconvolution is applied to extract the estimate of the line spread function (equivalent to the projection of the point spread function in the direction of the feature). The process is unsupervised and requires only that the image contains suitable linear features. Examples are given of the estimation of blur in satellite images.

关键词： blur identification point spread function step function deconvolution remote sensing

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Curvelets and reconstruction of images from noisy radon data

Curvelets and reconstruction of images from noisy radon data

引用

conference on Wavelet Applications in Signal and image Processing viii

作者： Candes, EJ Donoho, DL Stanford Univ Dept Stat Stanford CA 94305 USA

ISBN: (纸本)0819437646

The problem of recovering an input signal from noisy and linearly distorted data arises in many different areas of scientific investigation;e.g., noisy Radon inversion (tomography) is a problem of special interest and considerable practical relevance in medical imaging. We will argue that traditional methods for solving inverse problems - damping of the singular value decomposition (SVD) or cognate methods - behave poorly when the object to recover has edges. We apply a new system of representation, namely, the curvelets in this setting. Curvelets provide near-optimal representations of otherwise smooth objects with discontinuities along smooth C-2 edges. Inspired by some recent work on nonlinear estimation, we construct a curvelet-based biorthogonal decomposition of the Radon operator and build a reconstruction based on the shrinkage (or thresholding) of the noisy curvelet coefficients. This novel approach is shown to give a new theoretical understanding of the problem of edges in the Radon inversion problem.

关键词： ill-posed inverse problems regularization singular value decomposition Radon transform deconvolution edge edge-preserving regularization wavelet-vaguelette-decomposition

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Wide area image restoration using a new iterative registration method

Wide area image restoration using a new iterative registrati...

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conference on image reconstruction from incomplete data

作者： Fraser, D Lambert, A Univ New S Wales Australian Def Force Acad Sch Elect Engn Canberra ACT Australia

ISBN: (纸本)0819437689

Over a wide field of view (e.g., 100 arcsec in optical astronomy) the point spread function due to atmospheric effects is found to be far from position invariant, and appears as a combination of local warping and local blurring. Recently, we discussed a method in which the first step in restoration is to register all points in every frame of a movie sequence to the corresponding points in a prototype image. After registration, each frame is de-warped and summed to form an average, motion-blur corrected result. Previously, we applied a hierarchical, windowed cross correlation process to obtain local x and y registration information, similar to common methods in stereo cartography. We discuss a new approach to image registration for this purpose. Suppose two images to be registered differ mainly in varying random, but spatially coherent warping (such as occurs as one effect of a slowly varying wavefront tip-tilt over a wide field of view). Imagine that one image, the reference image, is represented by a solid "surface" corresponding to its intensity distribution. Imagine that the second image is also represented by a surface, but in the form of a flexible, "rubber" mould. If the two images are identical, then the mould fits the solid like a glove. If one image includes local warping relative to the other, then the mould or glove must be forced to fit through local distortions.

关键词： image restoration surveillance imaging astronomical imaging turbulence visualization image registration

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Optimizing wavelets for the analysis of fMRI data

Optimizing wavelets for the analysis of fMRI data

引用

conference on Wavelet Applications in Signal and image Processing viii

作者： Feilner, M Blu, T Unser, M Swiss Fed Inst Technol IOA DMT Biomed Imaging Grp CH-1015 Lausanne Switzerland

ISBN: (纸本)0819437646

Ruttimann et al. have proposed to use the wavelet transform for the detection and localization of activation patterns in functional magnetic resonance imaging (fMRI). Their main idea was to apply a statistical test in the wavelet domain to detect the coefficients that are significantly different from zero. Here, we improve the original method in the case of non-stationary Gaussian noise by replacing the original z-test by a t-test that takes into account the variability of each wavelet coefficient separately. The application of a threshold that is proportional to the residual noise level, after the reconstruction by an inverse wavelet transform, further improves the localization of the activation pattern in the spatial domain. A key issue is to find out which wavelet and which type of decomposition is best suited for the detection of a given activation pattern. In particular, we want to investigate the applicability of alternative wavelet bases that are not necessarily orthogonal. For this purpose, we consider the various brands of fractional spline wavelets (orthonormal, B-spline, and dual) which are indexed by a continuously-varying order parameter alpha. We perform an extensive series of tests using simulated data and compare the various transforms based on their false detection rate (type I + type II errors). In each case, we observe that there is a strongly optimal value of alpha and a best number of scales that minimizes the error. We also find that splines generally outperform Daubechies wavelets and that they are quite competitive with SPM (the standard analysis method used in the held), although it uses much simpler statistics. An interesting practical finding is that performance is strongly correlated with the number of coefficients detected in the wavelet domain, at least in the orthonormal and B-spline cases. This suggest that it is possible to optimize the structural wavelet parameters simply by maximizing the number of wavelet counts, without any prior

关键词： functional imaging fMRI statistical analysis medical imaging wavelets fractional splines

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