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CONF ON MEDICAL IMAGING 5 : image PROCESSING

作者： FIELDEN, J KWONG, H WILBRINK, J Hitachi Instruments Inc. (United States)

ISBN: (纸本)081940540X

Frequently MRI data does not cover completely the desired region of k space. We have investigated the reconstruction of MR images from incomplete data using the MEMSYS 3 maximum entropy algorithm. We compare conventional modulus images with the maximum entropy images. We show the importance of incorporating spatial correlation into the maximum entropy reconstructions in order to minimize truncation artifacts.

关键词： Correlation function image processing Computer programming Magnetic resonance imaging image resolution Signal processing reconstruction algorithms visualization Fourier transforms image restoration

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Effects of spectral amplitude and phase errors on image reconstruction

Effects of spectral amplitude and phase errors on image reco...

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conference on image reconstruction from incomplete data III

作者： Hsiao, WH Millane, RP Univ Canterbury Dept Elect & Comp Engn Christchurch 1 New Zealand

ISBN: (纸本)0819455008

The relative effects of spectral amplitude and phase errors on reconstructed images are studied in terms of the expected mean-square-error in the image. An appropriate mean-square-error appears to be that between reconstructed and original images that are scaled to have the same energy. Such an error metric appears to reflect the overall perceived quality of the images. Approximate relationships between spectral amplitude and phase errors that give rise to the same image mean-square-error are derived. For large amplitude errors saturation is significant and is studied by simulation. Simulations are used to illustrate these relationships. The relationship to phase dominance is discussed.

关键词： spectrum Fourier transform phase amplitude image reconstruction phase dominance

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MR images from fewer data

MR images from fewer data

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conference on image reconstruction from incomplete data vII

作者： vafadar, Bahareh Bones, Philip J. Univ Canterbury Dept Elect & Comp Engn Computat Imaging Grp Christchurch 1 New Zealand

ISBN: (纸本)9780819492173

There is a strong motivation to reduce the amount of acquired data necessary to reconstruct clinically useful MR images, since less data means faster acquisition sequences, less time for the patient to remain motionless in the scanner and better time resolution for observing temporal changes within the body. We recently introduced an improvement in image quality for reconstructing parallel MR images by incorporating a data ordering step with compressed sensing (CS) in an algorithm named 'PECS'.(1) That method requires a prior estimate of the image to be available. We are extending the algorithm to explore ways of utilizing the data ordering step without requiring a prior estimate. The method presented here first reconstructs an initial image x(1) by compressed sensing (with scarcity enhanced by SvD), then derives a data ordering from x(1), R'(1), which ranks the voxels of x(1) according to their value. A second reconstruction is then performed which incorporates minimization of the first norm of the estimate after ordering by R'(1), resulting in a new reconstruction x(2). Preliminary results are encouraging.

关键词： Parallel Magnetic Resonance Imaging (pMRI) Compressed Sensing (CS)

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image restoration techniques for partially coherent 2-D LADAR imaging systems

Image restoration techniques for partially coherent 2-D LADA...

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conference on image reconstruction from incomplete data III

作者： MacDonald, A Cain, S USAF Inst Technol Dept Elect Engn Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819455008

A new image reconstruction algorithm is constructed to remove the effect of atmospheric turbulence on motion-compensated frame averaged data collected by a laser illuminated 2-D imaging system. The algorithm simultaneously computes a high resolution image and Fried's seeing parameter via a MAP (Maximum a Priori) estimation technique. This blind deconvolution algorithm differs from other techniques in that it parameterizes the unknown component of the impulse response as an average short-exposure point spread function. The utility of the approach lies in its application to laser illuminated imaging where laser speckle and turbulence effects dominate other sources of error and the field of view of the sensor greatly exceeds the isoplanatic angle.

关键词： Speckle Imaging systems reconstruction algorithms image restoration Sensors Detection and tracking algorithms Coherence (optics) Optical transfer functions Signal detection LIDAR

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Investigation of limited-view image reconstruction in optoacoustic tomography employing a priori structural information

Investigation of limited-view image reconstruction in optoac...

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conference on image reconstruction from incomplete data vI

作者： Huang, Chao Oraevsky, Alexander A. Anastasio, Mark A. IIT Med Imaging Res Ctr Dept Biomed Engn Chicago IL 60616 USA TomoWave Labs Houston TX 77057 USA

ISBN: (纸本)9780819482969

Optoacoustic tomography (OAT) is an emerging ultrasound-mediated biophotonic imaging modality that has exciting potential for many biomedical imaging applications. There is great interest in conducting B-mode ultrasound and OAT imaging studies for breast cancer detection using a common transducer. In this situation, the range of tomographic view angles is limited, which can result in distortions in the reconstructed OAT image if conventional reconstruction algorithms are applied to limited-view measurement data. In this work, we investigate an image reconstruction method that utilizes information regarding target boundaries to improve the quality of the reconstructed OAT images. This is accomplished by developing boundary-constrained image reconstruction algorithm for OAT based on Bayesian image reconstruction theory. The computer-simulation studies demonstrate that the Bayesian approach can effectively reduce the artifact and noise levels and preserve the edges in reconstructed limited-view OAT images as compared to those produced by a conventional OAT reconstruction algorithm.

关键词： optoacoustic tomography photoacoustic tomography limited-view tomography Bayesian image reconstruction

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Phase retrieval and phase-space tomography from incomplete data sets

Phase retrieval and phase-space tomography from incomplete d...

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conference on image reconstruction from incomplete data III

作者： Testorf, ME Semichaevsky, A Dartmouth Coll Hanover NH 03755 USA

ISBN: (纸本)0819455008

The problem of signal recovery from incomplete data is investigated in the context of phase-space tomography. Particular emphasis is given to the case where only a limited number intensity measurements can be performed, which corresponds to partial coverage of the ambiguity function of the signal. Based on numerical simulations the impact of incomplete knowledge of the ambiguity function on the performance of phase-space tomography is illustrated. Several schemes to address the limited data problem are evaluated. This includes the use of prior information about the phase retrieval problem. In addition, the redundancy of phase-space representations is investigated as the means to recover the signal from partial knowledge of phase space. A generalization of deterministic phase retrieval is introduced which allows one to obtain a model based phase estimate for bandlimited functions. This allows one to use prior information for improving the phase estimate in the presence of noise.

关键词： phase-space tomography phase retrieval deterministic phase retrieval phase-space Wigner distribution function ambiguity function

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Efficient MR image reconstruction for compressed MR imaging

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MEDICAL image ANALYSIS 2011年第5期15卷 670-679页

作者： Huang, Junzhou Zhang, Shaoting Metaxas, Dimitris Dept Comp Sci Piscataway NJ 08854 USA

In this paper, we propose an efficient algorithm for MR image reconstruction. The algorithm minimizes a linear combination of three terms corresponding to a least square data fitting, total variation (Tv) and L1 norm regularization. This has been shown to be very powerful for the MR image reconstruction. First, we decompose the original problem into L1 and Tv norm regularization subproblems respectively. Then, these two subproblems are efficiently solved by existing techniques. Finally, the reconstructed image is obtained from the weighted average of solutions from two subproblems in an iterative framework. We compare the proposed algorithm with previous methods in term of the reconstruction accuracy and computation complexity. Numerous experiments demonstrate the superior performance of the proposed algorithm for compressed MR image reconstruction. (C) 2011 Elsevier B.v. All rights reserved.

关键词： Convex optimization Compressive sensing MR image reconstruction

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Superresolution capabilities of 3D optical filters

Superresolution capabilities of 3D optical filters

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conference on image reconstruction from incomplete data v

作者： Fiddy, Michael A. Testorf, Markus E. Dartmouth Coll Thayer Sch Engn 8000 Cummings Hall Hanover NH 03755 USA Univ N Carolina Charlotte NC 28223 USA

ISBN: (纸本)9780819472960

Multichannel sampling strategies have been considered for a number of applications including feature specific imaging, and digital superresolution. Typically, channel coding is accomplished with a thin modulating mask, either in the focal plane, or in the aperture of the imaging system. In this contribution, we extend Hie concept of multichannel imaging to systems by suggesting the use of 3D structures for channel coding. A single pixel camera design and the single scattering approximation are used to obtain a Fourier space interpretation of 3D filters. The k-space analysis indicates that the dispersion relation of propagating plane wave modes set severe constraints if 3D filters are used for channel coding. We relate this to the broader questions about the fundamental limits of optical and computational imaging and propose 3D filters for wavelength coding and superresolution applications.

关键词： Computational Imaging Resolution Enhancement image reconstruction Multiple image Frames volume Holograms

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Imaging fluorescence parameters by Bayesian optical diffusion tomography

Imaging fluorescence parameters by Bayesian optical diffusio...

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2nd conference on image reconstruction from incomplete data

作者： Millane, RP Milstein, AM Zhang, Q Oh, S Webb, KJ Bouman, CA Boas, DA Univ Canterbury Dept Elect & Comp Engn Christchurch New Zealand

ISBN: (纸本)0819445592

A Bayesian optimization scheme is presented for reconstructing fluorescent yield and lifetime, the absorption coefficient, and-the scattering coefficient in turbid media, such as biological tissue. The method utilizes measurements at both the excitation and emission wavelengths for reconstructing all unknown parameters. The effectiveness of the reconstruction algorithm is demonstrated by simulation and by application to experimental data from a tissue phantom containing a fluorescent agent.

关键词： optical diffusion tomography fluorescence imaging Bayesian image reconstruction inverse problem nonlinear optimization

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Imaging from scattered fields: limited data and degrees of freedom

Imaging from scattered fields: limited data and degrees of f...

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conference on image reconstruction from incomplete data vII

作者： Ritter, R. Shane Fiddy, Michael A. Perigon Int Inc 931 Ind Dr Matthews NC 28105 USA Univ N Carolina Ctr Optoelect & Opt Commun Charlotte NC 28223 USA

ISBN: (纸本)9780819492173

We describe how the number of degrees of freedom associated with a scattering experiment provides a guide to the minimum number of source and receiver locations required to image the scattering target. Since the number of degrees of freedom is approximately fixed, additional measurements do not necessarily improve the image fidelity in the absence of any prior knowledge. We illustrate these observations using a fast nonlinear inverse scattering method.

关键词： Imaging inverse scattering degrees of freedom

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