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Geometric sensitivity of ClearPET™ Neuro

NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2007年第1-2期571卷 235-238页

作者： Gundlich, Brigitte Weber, Simone Forschungszentrum Julich Cent Inst Elect D-52425 Julich Germany

ClearPET (TM) Neuro is a small-animal positron emission tomography (PET) scanner dedicated to brain studies on rats and primates. The design of ClearPET (TM) Neuro leads to a specific geometric sensitivity, characterized by inhomogeneous and, depending on the measurement setup, even incomplete data. With respect to reconstruction techniques, homogeneous and complete data sets are a 'must' for analytical reconstruction methods, whereas iterative methods take the geometrical sensitivity into account during the reconstruction process. Nevertheless, here a homogeneous geometric sensitivity over the field of view is highly desirable. Therefore, this contribution aims at studying the impact of different scanner geometries and measurement setups on the geometric sensitivity. A data set of coincident events is computed for certain settings that contains each possible crystal combination once. The lines of response are rebinned into normalizing sinograms and backprojected into sensitivity images. Both, normalizing sinograms and sensitivity images mirror the geometric sensitivity and therefore, provide information which setting enables most complete and homogeneous data sets. An optimal measurement setup and scanner geometry in terms of homogeneous geometric sensitivity is found by analyzing the sensitivity images. (c) 2006 Elsevier B.v. All rights reserved.

关键词： sensitivity image geometric sensitivity ClearPET (TM) Neuro

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MR image reconstruction from partial k-space using singularity function representation

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2007年第1-2期571卷 239-242页

作者： Miao, Peng Hiba, Bassem Luo, Jianhua Sappey-Marinier, Dominique Magnin, Isabelle Zhu, Yuemin Univ Lyon 1 CREATIS CNRS UMR5515 F-69365 Lyon France Univ Lyon 1 INSA INSERM U630 F-69365 Lyon France Shanghai Jiao Tong Univ Dept Biomed Engn Shanghai 200030 Peoples R China CERMEP Lyon France Animage Lyon France Harbin Inst Technol Sch Elect Engn & Automat Harbin Peoples R China

image reconstruction from partial k-space is an important matter in magnetic resonance imaging (MRI). The previously proposed methods are unable to cope with truncation artifacts without degrading' image quality. We present a method that is particularly suitable for reconstructing magnetic resonance (MR) images from partial k-space by reducing substantially truncation artifacts while maintaining the spatial resolution of the image. The proposed method is based on the use of a so-called singularity function representation determined by singular points and singularity degrees. With this model, our strategy consists in restricting the singularity degrees within some dynamic range, beyond which the corresponding singular points are set to zero. The proposed method was evaluated on both simulated and human brain MR data. The results showed that this new strategy has significantly improved the reconstruction quality of partial k-space data. (c) 2006 Elsevier B.v. All rights reserved.

关键词： partial k-space magnetic resonance imaging Fourier imaging reconstruction

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Full 3-D cluster-based iterative image reconstruction tool for a small animal PET camera

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2007年第1-2期571卷 219-222页

作者： valastyan, I. Imrek, J. Molnar, J. Novak, D. Balkay, L. Emri, M. Tron, L. Bukki, T. Kerek, A. Hungarian Acad Sci Inst Nucl Res H-4026 Debrecen Hungary Royal Inst Technol Stockholm Sweden Univ Debrecen PET Ctr Debrecen Hungary MEDISO Ltd Budapest Hungary

Iterative reconstruction methods are commonly used to obtain images with high resolution and good signal-to-noise ratio in nuclear imaging. The aim of this work was to develop a scalable, fast, cluster based, fully 3-D iterative image reconstruction package for our small animal PET camera, the miniPET. The reconstruction package is developed to determine the 3-D radioactivity distribution from list mode type of data sets and it can also simulate noise-free projections of digital phantoms. We separated the system matrix generation and the fully 3-D iterative reconstruction process. As the detector geometry is fixed for a given camera, the system matrix describing this geometry is calculated only once and used for every image reconstruction, making the process much faster. The Poisson and the random noise sensitivity of the ML-EM iterative algorithm were studied for our small animal PET system with the help of the simulation and reconstruction tool. The reconstruction tool has also been tested with data collected by the miniPET from a line and a cylinder shaped phantom and also a rat. (c) 2006 Elsevier B.v. All rights reserved.

关键词： medical imaging image reconstruction small animal PET

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Boundary effects on image reconstruction in photoacoustic tomography

Boundary effects on image reconstruction in photoacoustic to...

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8th conference on Biomedical Thermoacoustics, Optoacoustics and Acousto-optics

作者： Yang, Xinmai Wang, Lihong v. Washington Univ Dept Biomed Engn Opt Imaging Lab St Louis MO 63130 USA

ISBN: (纸本)9780819465504

Exact photoacoustic tomography requires scanning over a 4 pi solid angle in 3D. The ultrasound detection window, however, is often limited, which makes a full scan impossible. For example, when a boundary lies closely to an object, the scanning region can cover only less than 4 pi in 3D. Because of incomplete information, the resolution, SNR, and fidelity of the resulting image deteriorate. Boundaries, however, can be used to our advantage;we proposed post-processing algorithms in image reconstruction to make partially scanned data complete. Here, we show the efficacy of the post-processing algorithms with both numerical and experimental results. Indeed, the algorithms can improve the resolution, SNR, and fidelity.

关键词： photoacoustic tomography boundary condition image reconstruction

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Two approaches to implementing projector-backprojector pairs for 3D reconstruction from Compton scattered data

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2007年第1-2期571卷 255-258页

作者： Kim, Soo Mee Lee, Jae Sung Lee, Mi No Lee, Ju Hahn Lee, Chun Sik Kim, Chan-Hyeong Lee, Dong Soo Lee, Soo-Jin Seoul Natl Univ Dept Nucl Med Seoul South Korea Seoul Natl Univ Interdisciplinary Program Radiat Appl Life Sci Seoul South Korea Paichai Univ Dept Elect Engn Taejon South Korea Chung Ang Univ Dept Phys Seoul 156756 South Korea Hanyang Univ Dept Nucl Engn Seoul South Korea

Iterative image reconstruction for the Compton camera is computationally challenging since the projection and backprojection operations are performed on conical surfaces rather than along straight lines and there are many possible combinations of positions and energy measurements. Here, we note that implementing a computationally efficient projector-backprojector pair with good accuracy is an important factor to be considered in image reconstruction. In this study, two different approaches to conical surface integration were investigated for rapid calculations of projection and backprojection in 3D reconstruction;the ellipse-stacking method (ESM) and the ray-tracing method (RTM). Our experimental results indicated that while both methods produced equivalent reconstruction accuracies, RTM performed better than ESM in both computation time per iteration and total number of iterations for convergence. (c) 2006 Elsevier B.v. All rights reserved.

关键词： Compton camera projector image reconstruction emission tomography

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A new proposed method for image segmentation based on gray scale morphological transformations

A new proposed method for image segmentation based on gray s...

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International conference on Advanced Computing and Communications

作者： Nagaraju, C. Kumar, v. vijaya RGM Coll Engn & Tech Dept CSE Nandyal 518501 Andhra Pradesh India

ISBN: (纸本)9781424407156

image segmentation is one of the most important steps leading to the analysis of processed data. Its main goal is to divide an image into parts that have a strong correlation with Areas of the Real world contained in the image. image Segmentation by Mathematical Morphology is a Methodology based upon the notions of reconstruction and Gradient method of an image. reconstruction is a very useful operator for image Filtering, Segmentation, and Feature Extraction. In this paper a new Method is proposed based on the notion of regional maxima and makes use of Sequential reconstruction algorithm and Morphological Gradient The present paper has two main sections, first is reconstruction of original image from blurred image by eliminating noise. Second is segment the image by applying Morphological gradient method this method produced good result over conventional methods.

关键词： reconstruction segmentation raster scan gradient anti-raster scan dilation erosion

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Post-processing by total variation quasi-solution method for image interpolation

Post-processing by total variation quasi-solution method for...

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17th International conference on Computer Graphics and vision, GraphiCon 2007

作者： Nasonov, Andrey Krylov, Andrey S. Lukin, Alexey Moscow State University Moscow Russia

image restoration is one of classical inverse problems in image processing and computer vision, which consists of the recovering information about the original image from incomplete or degraded data. In this paper, we consider the problem of reduction of ringing that appears after image resampling. We introduce a novel method for image restoration, based on a quasi-solution method for a compact set of functions with bounded total variation. It is an alternative approach to using a total variation functional as a stabilizer in Tikhonov regularization, and it does not oversmooth or displace edges.

关键词： image reconstruction

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image reconstruction using em method in X-ray CT

Image reconstruction using em method in X-ray CT

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5th International conference on Wavelet Analysis and Pattern Recognition

作者： Dong, Bao-Yu Dalian Jiaotong Univ Sch Elect & Informat Dalian 116028 Peoples R China

ISBN: (纸本)9781424410651

Computed tomography (CT) is a technique for imaging cross-sections of an object using a series of X-ray Measurements taken from different angles around the object. It has been widely applied in diagnostic medicine and industrial non-destructive testing. Traditional CT reconstructions are limited by many kinds of artifacts, and they give dissatisfactory image. To reduce image noise and artifacts, the theory of maximum likelihood estimation is extended to v-ray scan in this paper, and expectation maximization (EM) algorithm is studied and implemented for image reconstruction of X-ray CT (XCT). Then the point spread function and modulation transfer function of the EM algorithm is analyzed. Last experimental results with computer simulated data and real CT data are presented to verify our method is effective.

关键词： EM algorithin maximum likelihood estimation image reconstruction X-ray CT

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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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Clouds removal from remotely sensed images by using a bandelet-based reconstruction technique

Clouds removal from remotely sensed images by using a bandel...

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conference on Wavelet Applications in Industrial Processing v

作者： Maalouf, Aldo Carre, Philippe Augereau, Bertrand Fernandez-Maloigne, Christine Univ Politiers Signal Image Communicat Lab F-86962 Futuroscope France

ISBN: (纸本)9780819469236

The recurrent presence of clouds and clouds shadows in aerial or remotely sensed images is an awkward problem that severely limits the regular exploitations capability of these images. Removing cloud-contaminated portions of the image and then filling in the missing data represent an important photo editing cumbersome task. The intent of this work is to propose a technique for the reconstruction of areas obscured by clouds in a remotely sensed image. To this end, a new efficient reconstruction technique for missing data synthesis is presented. This technique is based on the Bandelet transform and the multiscale geometrical grouping. It consists of two steps. In the first step, the curves of geometric flow of different zones of the image are determined by using the Bandelet transform with multiscale grouping. This step allows a better representation of the multiscale geometry of the image's structures. Having well represented this geometry, the information inside the cloud-contaminated zone is synthesized by propagating the geometrical flow curves inside that zone. This step is accomplished by minimizing, a functional whose role is to reconstruct the missing or cloud contaminated zone independently of the size and topology of the reconstruction or inpainting domain. Thus, the flow lines are well tied inside the cloud-contaminated zone. The proposed technique is illustrated with some examples on processing multispectral aerial images. The obtained results are compared with those obtained by other clouds removal techniques.

关键词： Clouds Wavelets image classification image processing reconstruction algorithms Wavelet transforms image segmentation Lithium Remote sensing Multispectral imaging

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