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

共 1581 条记录，以下是301-310 订阅

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Application-Driven MRI: Joint reconstruction and Segmentation from Undersampled MRI data

Application-Driven MRI: Joint Reconstruction and Segmentatio...

引用

17th International conference on Medical image Computing and Computer-Assisted Intervention (MICCAI)

作者： Caballero, Jose Bai, Wenjia Price, Anthony N. Rueckert, Daniel Hajnal, Joseph v. Imperial Coll London Dept Comp London SW7 2AZ England St. Thomas Hosp Kings Coll London Div Imaging Sci Biomed Engn Dept London England

ISBN: (纸本)9783319104041;9783319104034

Medical image segmentation has traditionally been regarded as a separate process from image acquisition and reconstruction, even though its performance directly depends on the quality and characteristics of these first stages of the imaging pipeline. Adopting an integrated acquisition-reconstruction-segmentation process can provide a more efficient and accurate solution. In this paper we propose a joint segmentation and reconstruction algorithm for undersampled magnetic resonance data. Merging a reconstructive patch-based sparse modelling and a discriminative Gaussian mixture modelling can produce images with enhanced edge information ultimately improving their segmentation.

关键词： Magnetic resonance imaging

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A robust iterative super-resolution reconstruction of image sequences using a Lorentzian Bayesian approach with fast affine block-based registration

A robust iterative super-resolution reconstruction of image ...

引用

IEEE International conference on image Processing (ICIP 2007)

作者： Patanavijit, v. Tae-O-Sot, S. Jitapunkul, S. Assumption Univ Fac Engn Bangkok Thailand Naresuan Univ Fac Engn Tha Pho Thailand Chulalongkorn Univ Fac Engn Bangkok Thailand

ISBN: (纸本)9781424414369

Although the topic of Super-Resolution reconstruction (SRR) has recently received considerable attention within the traditional research community, the SRR estimations are based on L1 or L2 statistical norm estimation. Therefore, these SRR methods are very sensitive to their assumed data and noise models, which limit their applications. The real noise models that corrupt the measure sequence are unknown;consequently, SRR algorithm using L1 or L2 norm may degrade the image sequence rather than enhance it. The robust norm applicable to several noise and data models is desired in SRR algorithms. This paper proposes an alternate SRR approach based on the stochastic regularization technique of Bayesian MAP estimation by minimizing a cost function. The Lorentzian norm is used for measuring the difference between the projected estimate of the high-resolution image and each low resolution image, removing outliers in the data. Tikhonov regularization is used to remove artifacts from the final result and improve the rate of convergence. In order to cope with real sequences and complex motion sequences, the fast affine block-based registration is used in the registration step of SRR. The experimental results show that the proposed reconstruction can be applied on real sequences such as Suzie sequence and confirm the effectiveness of our method and demonstrate its superiority to other super-resolution methods based on L1 and L2 norm for several noise models such as AWGN, Poisson and Salt & Pepper noise.

关键词： SRR stochastic regularization technique Lorentzian norm affine block-based registration

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A fast gradient projection method for 3D image reconstruction from limited tomographic data 7

A fast gradient projection method for 3D image reconstructio...

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7th International conference on New Computational Methods for Inverse Problems (NCMIP)

作者： Coli, v. L. Piccolomini, E. Loli Morotti, E. Zanni, L. Univ Modena & Reggio Emilia Dept Phys Informat & Math Modena Italy Univ Bologna Dept Math Bologna Italy Univ Padua Dept Math Padua Italy

We consider in this paper the problem of reconstructing 3D Computed Tomography images from limited data. The problem is modeled as a nonnegatively constrained minimization problem of very large size. In order to obtain an acceptable image in short time, we propose a scaled gradient projection method, accelerated by exploiting a suitable scaling matrix and efficient rules for the choice of the step-length. In particular, we select the step-length either by alternating Barzilai-Borwein rules or by exploiting a limited number of back gradients for approximating second-order information. Numerical results on a 3D Shepp-Logan phantom are presented and discussed.

关键词： image reconstruction

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image reconstruction in photoacoustic tomography with heterogeneous media using an iterative method

Image reconstruction in photoacoustic tomography with hetero...

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conference on Photons Plus Ultrasound - Imaging and Sensing

作者： Huang, Chao Wang, Kun Wang, Lihong v. Anastasio, Mark A. Washington Univ Dept Biomed Engn St Louis MO 63130 USA

ISBN: (纸本)9780819493507

There remains an urgent need to develop effective photoacoustic computed tomography (PACT) image reconstruction methods for use with acoustically inhomogeneous media. Transcranial PACT brain imaging is an important example of an emerging imaging application that would benefit greatly from this. Existing approaches to PACT image reconstruction in acoustically heterogeneous media are limited to weakly varying media, are computationally burdensome, and/or make impractical assumptions regarding the measurement geometry. In this work, we develop and investigate a full-wave approach to iterative image reconstruction in PACT for media possessing inhomogeneous speed-of-sound and mass density distributions. A key contribution of the work is the formulation of a procedure to implement a matched discrete forward and backprojection operator pair, which facilitates the application of a wide range of modern iterative image reconstruction algorithms. This presents the opportunity to employ application-specific regularization methods to mitigate image artifacts due to mea- surement data incompleteness and noise. Our results establish that the proposed image reconstruction method can effectively compensate for acoustic aberration and reduces artifacts in the reconstructed image.

关键词： Photoacoustic tomography optoacoustic tomography thermoacoustic tomography iterative image reconstruction acoustic heterogeneity k-space pseudospectral method

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Object reconstruction on 3D ultrasound images using simplex meshes

Object reconstruction on 3D ultrasound images using simplex ...

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MS'2004 - International conference on Modelling and Simulation

作者： Snezhko, E.v. Tuzikov, A.v. United Institute of Informatics Problems National Academy of Sciences of Belarus Surganova 6 220012 Minsk Belarus

ISBN: (纸本)9856107334

We present an algorithm for 3D object reconstruction on ultrasound images based on simplex meshes. The algorithm uses manually traced object boundaries on several representative non-parallel cross-sections of 3D US image. Simplex meshes are attracted to these contours under the influence of external forces, derived from the initial data. Several algorithms for external force generation are investigated.

关键词： image reconstruction

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Global optimization for shape fitting

Global optimization for shape fitting

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IEEE conference on Computer vision and Pattern Recognition

作者： Lempitsky, victor Boykov, Yuri Moscow MV Lomonosov State Univ Dept Math & Mech Moscow Russia Univ Western Ontario Dept Comp Sci London ON N6A 3K7 Canada

ISBN: (纸本)9781424411795

We propose a global optimization framework for 3D shape reconstruction from sparse noisy 3D measurements frequently encountered in range scanning, sparse feature-based stereo, and shape-from-X. In contrast to earlier local or banded optimization methods for shape fitting, we compute global optimum in the whole volume removing dependence on initial guess and sensitivity to numerous local minima. Our global method is based on two main ideas. First, we suggest a new regularization functional with a data alignment term that maximizes the number of (weakly-oriented) data points contained by a surface while allowing for some measurement errors. Second, we propose a touch-expand algorithm for finding a minimum cut on a huge 3D grid using an automatically adjusted band This overcomes prohibitively high memory cost of graph cuts when computing globally optimal surfaces at high-resolution. Our results for sparse or incomplete 3D data from laser scanning and passive multi-view stereo are robust to noise, outliers, missing parts, and varying sampling density.

关键词： image reconstruction

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A Robust Iterative Multiframe Super-Resolution reconstruction using a Huber Statistical Estimation Technique

A Robust Iterative Multiframe Super-Resolution Reconstructio...

引用

1st International conference on Communications and Networking in China

作者： Patanavijit, v Jitapunkul, S. Chulalongkorn Univ Fac Engn Elect Engn Dept Bangkok Thailand

ISBN: (纸本)1424404630

The traditional SRR (Super-Resolution reconstruction) estimations are based on L1 or L2 statistical norm estimation therefore these SRR methods are usually very sensitive to their assumed model of data and noise, which limits their utility. This paper reviews some of these methods and addresses their shortcomings. We propose an alternate SRR approach based on a statistical estimation technique. By minimizing a cost function, the Huber norm is used for measuring the difference between the projected estimate of the high-resolution image and each low resolution image, removing outliers in the data and Tikhonov regularization is used to remove artifacts from the final answer and improve the rate of convergence. The experimental results confirm the effectiveness of our method and demonstrate its superiority to other super-resolution methods based on L1 and L2 norm for a several noise models such as noiseless, AWGN, Poisson and Salt&Pepper Noise.

关键词： SRR (Super-Resolution reconstruction) Robust Estimation Huber Norm Regularized ML

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SPECT Imaging With Resolution Recovery

SPECT Imaging With Resolution Recovery

引用

2nd International conference on Advancements in Nuclear Instrumentation, Measurement Methods and their Applications

作者： Bronnikov, Andrei v. Bronnikov Algorithms NL-6800 AB Arnhem Netherlands

ISBN: (纸本)9781457709258

Single-photon emission computed tomography (SPECT) is a method of choice for imaging spatial distributions of radioisotopes. Applications of this method are found in medicine, biomedical research and nuclear industry. This paper deals with improving spatial resolution in SPECT by applying correction for the point-spread function (PSF) in the reconstruction algorithm and optimizing the collimator. Several approaches are considered: the use of a depth-dependent PSF model for a parallel-beam collimator derived from experimental data, the extension of this model to a fan-beam collimator, a triangular approximation of the PSF for reconstruction acceleration, and a method for optimal fan-beam collimator design. An unmatched projector/backprojector ordered subsets expectation maximization (OSEM) algorithm is used for image reconstruction. Experimental results with simulated and physical phantom data of a micro-SPECT system show a significant improvement of spatial resolution with the proposed methods.

关键词： image quality nuclear medicine single photon emission computed tomography (SPECT)

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Patient evaluation of Breast Shape-corrected Tomosynthesis reconstruction

Patient evaluation of Breast Shape-corrected Tomosynthesis R...

引用

conference on Medical Imaging - Physics of Medical Imaging

作者： Michielsen, Koen Rangelova, Tsvetanka Sechopoulos, Ioannis Radboudumc Dept Radiol & Nucl Med Nijmegen Netherlands Dutch Reference Ctr Screening LRCB Nijmegen Netherlands

ISBN: (纸本)9781510625440

Iterative reconstruction is a good match with the sparsely sampled limited angle data generated by breast tomosynthesis systems. However, it suffers from a specific artifact near the breast edge where it overestimates the x-ray path length, resulting in a considerable underestimation of the reconstructed linear attenuation coefficients. In this work, we present the application of a method that uses the measured 3D breast shape to reduce these artifacts in patient data, by including this information as an additional constraint in the image reconstruction process. A series of 50 patients undergoing breast tomosynthesis were additionally imaged with a pair of structured light cameras placed left and right of the mammography unit. These 3D surfaces were then aligned with the help of the backprojected breast outline from the x-ray data to form a single contour following the true breast shape. This was then further processed to generate a binary 3D mask set to 1 inside and to 0 outside the breast, and used as constraint in the reconstruction. Due to incomplete coverage and image artifacts, this mask was created successfully for only 19 out of 50 cases. reconstructions were created with and without this constraint, and comparing attenuation profiles found that the artifact was almost completely corrected, bringing the reconstructed attenuation near the breast edge to the same level as the central region. Further visual inspection does show that higher quality optical 3D measurements and more precise alignment between optical and x-ray data are needed to avoid introducing new artifacts in the reconstruction.

关键词： Breast Signal attenuation Cameras X-rays data acquisition reconstruction algorithms 3D acquisition Digital breast tomosynthesis Structured light

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MAXIMUM LIKELIHOOD SCALE ESTIMATION FOR A CLASS OF MARKOv RANDOM FIELDS

MAXIMUM LIKELIHOOD SCALE ESTIMATION FOR A CLASS OF MARKOV RA...

引用

1994 IEEE International conference on Acoustics, Speech and Signal Processing

作者： BOUMAN, CA SAUER, K PURDUE UNIV SCH ELECT ENGNW LAFAYETTEIN 47907

This paper presents the exact maximum likelihood (ML) estimate of temperature for a class of Markov random fields (MRF) known as generalized Gaussian MRFs. The ML estimate has a simple closed form which is analogous to variance estimation for Gaussian random variables. This result is useful because the temperature parameter plays the important role of determining the amount of smoothing in problems such as Bayesian image reconstruction and restoration. Two extensions of the basic result are also given: 1) numerical scale estimation for the general class of continuous MRFs;and 2) parameter estimation from incomplete data using the EM algorithm. Preliminary numerical experiments support the usefulness of the technique. © 1994 IEEE.

关键词： image reconstruction

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