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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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A lorentzian stochastic estimation for a robust and iterative multiframe super-resolution reconstruction

A lorentzian stochastic estimation for a robust and iterativ...

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IEEE Region 10 conference (TENCON 2006)

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

ISBN: (纸本)9781424405480

In the last decades, it has seen a great deal of work in the development of algorithms addressing the problem of super-resolution. Although many such algorithms have been proposed, the almost SRR (Super-Resolution reconstruction) estimations are based on Ll or L2 statistical norm estimation thus these SRR methods are usually very sensitive to their assumed model of data and noise that limits their utility. This paper reviews some of these SRR estimator methods and addresses their shortcomings. We propose a novel SRR approach based on the stochastic regularization technique of Bayesian MAP estimation by minimizing a cost function. The Lorentzian norm [10] 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 Ll and L2 norm for a several noise models such as noiseless, Additive White Gaussian Noise (AWGN) and Salt & Pepper Noise.

关键词： image reconstruction

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Entropy-based method to evaluate the data integrity

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2006年第2期569卷 412-415页

作者： Xu Peng Ma Tianyu Jin Yongjie Tsinghua Univ Dept Engn Phys Beijing 100084 Peoples R China

Projection stage of single photon emission computed tomography (SPECT) was discussed to analyze the characteristics of information transmission and evaluate the data integrity. Information is transferred from the source to the detector in the photon emitting process. In the projection stage, integrity of projection data can be assessed by the information entropy, which is the conditional entropy standing for the average uncertainty of the source object under the condition of projection data. Simulations were performed to study projection data of emission-computed tomography with a pinhole collimator. Several types of collimators were treated. Results demonstrate that the conditional entropy shows the data integrity, and indicate how the algorithms are matched or mismatched to the geometry. A new method for assessing data integrity is devised for those decision makers to help improve the quality of image reconstruction. (c) 2006 Elsevier B.v. All rights reserved.

关键词： data integrity entropy information theory SPECT

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The Quantitative Accuracy and Efficiency of the Dual reconstruction Scheme Including a Practical Scatter/Random Approximation in Dynamic PET Imaging

The Quantitative Accuracy and Efficiency of the Dual Reconst...

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15th International Workshop on Room-Temperature Semiconductor X- and Gamma-Ray Detectors/ 2006 IEEE Nuclear Science Symposium

作者： Cheng, Ju-Chieh (Kevin) Rahmim, Arman Blinder, Stephan Dinelle, Katherine Sossi, vesna Univ British Columbia Dept Phys & Astron Vancouver BC V6T 1Z1 Canada Johns Hopkins Univ Sch Med Dept Radiol Baltimore MD 21205 USA Pacific Parkinsons Res Ctr Vancouver BC V6T 1Z1 Canada

ISBN: (纸本)9781424405619

We describe a time-efficient reconstruction scheme with a practical approximate scatter and random correction for dynamic PET imaging on scanners with large data sets such as the High Resolution Research Tomograph (HRRT). This dual (histogram/list-mode) reconstruction scheme makes use of the efficiency advantage of both histogram and list-mode reconstructions (i.e. histogram-mode reconstruction is applied to the dynamic frames with a large number of counts, and list-mode reconstruction is applied to the frames with a low number of counts). The practical scatter and random approximation technique is based on a time averaged scatter and random estimate followed by scaling according to the global numbers of true and random events for each temporal frame. The quantitative accuracy of this dual reconstruction scheme including the scatter and random approximation was examined by comparing the time activity curves (TAC) obtained from the images reconstructed using the conventional histogram-mode algorithm and those obtained from applying the dual reconstruction scheme with the practical approximation. A representative dynamic C-11 non-human primate study with 14 temporal frames is presented here, and an excellent agreement between the conventional and the proposed scheme was found, while an overall gain of about 35% in time (which depends on the number of dynamic frames;the more frames with a similar spatial activity distribution there are, the more time we gain) and an over 4 times less storage cost for the scatter and random data sets (sinograms) was achieved in this case.

关键词： image reconstruction

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Incorporation of Axial System Response in Iterative reconstruction from Axially Compressed data of a Cylindrical Scanner using On-the-Fly Computing

Incorporation of Axial System Response in Iterative Reconstr...

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15th International Workshop on Room-Temperature Semiconductor X- and Gamma-Ray Detectors/ 2006 IEEE Nuclear Science Symposium

作者： Panin, v. Y. Kehren, F. Casey, M. E. Siemens Med Solut Mol Imaging Knoxville TN 37932 USA

ISBN: (纸本)9781424405619

The quality of images reconstructed by statistical iterative methods depends on an accurate model of the relationship between image space and projection space. Fast reconstruction is also an important aspect in the clinical environment. In previous work, we incorporated measured and modeled system response into iterative reconstruction. Since axial compression (span) was used in projection data, axial blurring was depth-dependent. We use pre-computed and stored axial components for a scanner without translation axial symmetry. For a scanner with translation symmetry, a fast line-of-response (LOR) line integral projector is available. In this case, axial blurring due to both geometrical and physics effects is implemented differently. Forward projection of axially blurred images is performed on-the-fly into LOR space, followed by axial compression of LOR data into scanner projection data formats. Our LOR projector is based on Joseph's method. The translation symmetry of the scanner is essential for its efficient and fast computing performance. LOR projection and span assembling are performed independently for each azimuthal angle and result in small additional memory allocation. Results show that an acceleration of the computing of the axial blurring is achievable without any component storage but with similar image quality.

关键词： data compression

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A novel model of the geometric and detector response for limited angular sampling pinhole SPECT - art. no. 614253

A novel model of the geometric and detector response for lim...

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Medical Imaging 2006 conference

作者： Wietholt, Christian Hsiao, Ing-Tsung Clough, Anne v. Chen, Chin-Tu Natl Hlth Res Inst Zhunan Taiwan

ISBN: (纸本)0819461857

reconstruction methodologies for data sets with reduced angular sampling (RAS) are essential for efficient dynamic or static preclinical animal imaging research using single photon emission computed tomography (SPECT). Modern iterative reconstruction methods can obtain 3D radiotracer distributions of the highest possible quality and resolution. Essential to these algorithms is an accurate model of the physical imaging process. We developed a new point-spread function (PSF) model for the pinhole geometry and compared it to a Gaussian model in a RAS setting. The new model incorporates the geometric response of the pinhole and the detector response of the camera by simulating the system PSF using the error function. reconstruction of simulated data was done with OS-EM and COS-EM: a new convergent OS-EM based algorithm. The reconstruction of projection data of a simulated point source using the novel method showed improved FWHM values compared to a standard Gaussian method. COS-EM delivers improved results for RAS data, although it converges slower than OS-EM. The reconstruction of Monte Carlo simulated projection data from a resolution phantom shows that as few as 40 projections are sufficient to reconstruct an image with a resolution of approximately 4 mm. The new pinhole model applied to iterative reconstruction methods can reduce imaging time in small animal experiments by a factor of three or reduce the number of cameras needed to perform dynamic SPECT.

关键词： small animal pinhole SPECT simulations reconstruction method reduced angular sampling

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Parallelism of iterative CT algorithm based on local reconstruction

Parallelism of iterative CT algorithm based on local reconst...

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5th conference on Developments in X-Ray Tomography

作者： Deng, Junjun Yu, Hengyong Ni, Jun Wang, Lihe Wang, Ge Univ Iowa Dept Radiol Iowa City IA 52242 USA Univ Iowa Dept Math Iowa City IA 52242 USA Univ Iowa Dept Comp Sci Iowa City IA 52242 USA

ISBN: (纸本)0819463973

An iterative algorithm is suited to reconstruct CT images from noisy or truncated projection data. However, as a disadvantage, the algorithm requires significant computational time. Although a parallel technique can be used to reduce the computational time, a large amount of communication overhead becomes an obstacle to its performance [1]. To overcome this problem, we proposed an innovative parallel method based on the local iterative CT reconstruction algorithm [2-3]. The object to be reconstructed is partitioned into a number of sub-regions and assigned to different processing elements (PEs). Within each PE, local iterative reconstruction is performed to recover the sub-region. Several numerical experiments were conducted on a high performance computing cluster. And the FORBILD head phantom [4] was used as benchmark to measure the parallel performance. The experimental results showed that the proposed parallel algorithm significantly reduces the reconstruction time, hence achieving a high speedup and efficiency.

关键词： computed tomography (CT) image reconstruction iterative reconstruction local iterative CT reconstruction parallel computing high performance computing MPI

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Perspecitve view reconstruction of partially occluded objects by using computational integral imaging

Perspecitve view reconstruction of partially occluded object...

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conference on Three-Dimensional Tv, video, and Display v

作者： Hwang, Yong Seok Hong, Seung-Hyun Javidi, Bahram Univ Connecticut Elect & Comp Engn Dept 371 Fairfield Rd U-2157 Storrs CT 06269 USA

ISBN: (纸本)9780819464903

In this paper, we present a system to reconstruct perspective view of a partially occluded object by using computational integral imaging. The system is analyzed to extract information of off-centered views from a elemental images set. To obtain unobstructed images with high resolution, low focus error, and large depth of focus, synthetic aperture integral imaging utilizing a digital camera has been adopted.

关键词： integral imaging optical data processing geometrical optics three-dimensional (3-D) image processing

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Accurate Estimation of Single Counts from Axially Compressed Random data

Accurate Estimation of Single Counts from Axially Compressed...

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15th International Workshop on Room-Temperature Semiconductor X- and Gamma-Ray Detectors/ 2006 IEEE Nuclear Science Symposium

作者： Panin, v. Y. Siemens Med Solut Mol Imaging Knoxville TN 37932 USA

ISBN: (纸本)9781424405619

The use of the ordinary Poisson iterative reconstruction algorithm requires the estimation of mean random counts. In a clinical environment, random data are acquired as separate scans. When axial compression (span) is used to produce projection data, the random equation is complicated by the axial rebinning of a few lines-of-response (LOR). Previously developed methods, which were designed for basic random equations as a product of single counts, are not directly applicable. The accurate estimation of single counts per crystal from random data (in the case of axial compression) is suggested. This method utilizes the fact that the border planes of the projection segments use only one axial LOR to form an axial projection plane. The Defrise method, which solves the system of nonlinear equations, is used for border planes. The next axial planes use more LORs, but the equations are linear, if crystal singles estimations are used from the previous step. Since the number of unknown singles is significantly lower than the number of random data, various systems of equations can be constructed. In this work, 2D data (segment zero) are used for random smoothing. Computer simulations are used to verify method performance.

关键词： image compression

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A robust iterative multiframe super-resolution reconstruction using a Bayesian approach with lorentzian norm

A robust iterative multiframe super-resolution reconstructio...

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10th IEEE Singapore International conference on Communications Systems, ICCS 2006

作者： Patanavijit, v. Jitapunkul, S. Computer Engineering Department Faculty of Engineering Assumption University Bangkok Thailand Electrical Engineering Department Faculty of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (纸本)1424404118

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 SRR methods and addresses their shortcomings. We propose an alternate SRR approach based on the stochastic regularizaron technique of Bayesian MAP estimation by minimizing a cost function. The Lorentzian norm [10] 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, Additive White Gaussian Noise (AWGN) and Salt & Pepper Noise. © 2006 IEEE.

关键词： Salt and pepper noise

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