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2nd conference on image reconstruction from incomplete data

作者： Bratsolis, E Sigelle, M Ecole Natl Super Telecommun Bretagne Dept Traitement Signal & Images F-75013 Paris France

ISBN: (纸本)0819445592

An iterative optimization algorithm which can be used for speckle reduction and segmentation of synthetic aperture radar (SAR) images is presented here. This method contains as a first step a fast restoration and as a second one the segmentation. We have worked in 3-look simulated and real ERS-1 amplitude images. The iterative filter is based on a membrane model Markov random field (MRF) approximation optimized by a synchronous local iterative method (SLIM). The final form of restoration gives a total sum preserving regularization (TSPR).

关键词： image segmentation speckle reduction restoration Markov random field (MRF) synchronous local iterative method (SLIM) synthetic aperture radar (SAR) total sum preserving regularization (TSPR)

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incomplete points cloud data surface reconstruction based on neural network

Incomplete points cloud data surface reconstruction based on...

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4th International conference on Intelligent Information Hiding and Multimedia Signal Processing

作者： Wu Xue-mei Li Gui-xian Zhao Wei-min Harbin Inst Technol Sch Mech & Elect Harbin 150001 Heilongjiang Pr Peoples R China Daquing Univ Dept Engn Mech Daqing 163318 Heilongjiang Peoples R China

ISBN: (纸本)9780769532783

Neural network arithmetic was employed in incomplete points cloud data surface reconstruction, Radial basis function neural network and simulated annealing arithmetic was combined. The new arithmetic can approach any nonlinear function by arbitrary precision, and also keep the network from getting into local minimum. Global optimization feature of simulated annealing was employed to adjust the network weights. MATLAB program was compiled, experiments on incomplete points cloud data have been done employing this arithmetic, the result shows that this arithmetic can efficiently approach the surface with 10(-4) mm error precision, and also the learning speed is quick and the reconstruction surface is smooth. Different methods have been employed to do surface reconstruction in comparison, the results illustrate the error employed algorithmic proposed in the paper is little and converge speed is quick.

关键词： Surface reconstruction Artificial neural networks image reconstruction Simulated annealing Training Meteorology Radial basis function networks

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Multiple image reconstruction for high-resolution optical imaging using structured illumination

Multiple image reconstruction for high-resolution optical im...

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conference on image reconstruction from incomplete data vI

作者： Usuki, S. Kudo, R. Takahashi, S. Takamasu, K. Shizuoka Univ Div Global Res Leaders 3-5-1 Johoku Hamamatsu Shizuoka 4328561 Japan Univ Tokyo Dept Precis Engn Tokyo 1138656 Japan

ISBN: (纸本)9780819482969

The resolving power in optical imaging is limited not only by optical diffraction but also by the sampling size, which in turn is determined by the optical magnification and pixel size of the imaging devices such as CCD or CMOS. In order to exceed these limits, we propose a method for improving the optical resolving power by using structured illumination shift and multiple image reconstruction. Theoretical and experimental verifications reveal that the use of structured light illumination together with successive approximation (which provides the extrapolation effect) causes the resolving power of the proposed method to exceed the optical diffraction limit. Furthermore, we focused on subpixel sampling using the structured illumination shift method. Subpixel image processing can improve the resolving power without narrowing the visual field of the imaging optics. In addition, the proposed method can provide subpixel resolving power without necessitating the mechanical displacement of the CCD camera. We investigated the relationship between the CCD pixel size and the resolving power provided by the proposed method. We found that the subpixel spatial shift of the structured illumination not only improves the optical resolving power but also enables sub-pixel sampling for optical imaging.

关键词： optical imaging image reconstruction structured illumination super-resolution

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reconstruction of multiple line source attenuation maps

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 1997年第4期44卷 1503-1508页

作者： Celler, A Sitek, A Harrop, R UNIV BRITISH COLUMBIA DEPT PHYSVANCOUVERBC V5Z 1M9CANADA SIMON FRASER UNIV SCH COMP SCIBURNABYBC V5A 1S6CANADA

A simple configuration for a transmission source for single photon emission computed tomography (SPECT) is proposed, which utilizes a series of collimated line sources parallel to the axis of rotation of the camera. The detector is equipped with a standardparallel hole collimator. We have demonstrated that this type of source configuration can be used to generate sufficient data for the reconstruction of the attenuation map when using 8-10 line sources spaced by 3.5-4.5cm for a 30x40cm detector placed 65cm from the sources. Transmission data for a nonuniform thorax phantom was simulated, then binned and reconstructed using filtered backprojection (FBP) and iterative methods. It was found that optimum maps were obtained with data binned into 2-3 bins and FBP reconstruction. The activity in the source was investigated for uniform and exponential activity distributions. The effect of gaps and overlaps of the neighboring fan beams was also studied. A prototype of the line source system has been built and the experimental verification of the simulation results has started.

关键词： Attenuation Cameras Collimators Geometry Magnetic heads Detectors image reconstruction Biomedical imaging Medical diagnostic imaging Nuclear medicine

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SENSITIvITY TO ERROR OF THE TRUNCATED HILBERT TRANSFORM TECHNIQUE FOR INTERIOR reconstruction

SENSITIVITY TO ERROR OF THE TRUNCATED HILBERT TRANSFORM TECH...

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18th IEEE International conference on image Processing (ICIP)

作者： Opie, A. M. T. Bones, P. J. Univ Canterbury Dept Elect & Comp Engn Christchurch 1 New Zealand

ISBN: (纸本)9781457713033

Historically, computed tomography reconstructions from truncated projection data have been considered non-unique. However, several recent results suggest that if the density of the object is known on some small region within the region of interest (ROI) then a unique and stable reconstruction of the complete ROI may be possible. Unfortunately, prior knowledge of the exact density of an object being scanned is uncommon, and as such an experimentally determined estimate must be used in its place. This estimate will naturally contain errors. We have performed several reconstruction simulations to establish the sensitivity of the proposed algorithm to errors in the prior knowledge. Our results suggest that the most important element of the prior knowledge is its mean value, while perturbations of the details cause fewer problems in the reconstructed images.

关键词： Computed tomography incomplete data sensitivity to error

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Advanced Techniques for reconstruction of incomplete Network data 1

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7th International ICST conference on Digital Forensics and Cyber Crime (ICDF2C)

作者： Matousek, Petr Pluskal, Jan Rysavy, Ondrej vesely, vladimir Kmet, Martin Karpisek, Filip vymlatil, Martin Brno Univ Technol Bozetechova 2 CS-61090 Brno Czech Republic

ISBN: (数字)9783319255125

ISBN: (纸本)9783319255125;9783319255118

Network forensics is a method of obtaining and analyzing digital evidences from network sources. Network forensics includes data acquisition, selection, processing, analysis and presentation to investigators. Due to high volumes of transmitted data the acquired information can be incomplete, corrupted, or disordered which makes further reconstruction difficult. In this paper, we address the issue of advanced parsing and reconstruction of incomplete, corrupted, or disordered data packets. We introduce a technique that recovers TCP or UDP conversations so they could be further analyzed by application parsers. Presented technique is implemented in a new network forensic tool called Netfox Detective. We also discuss current challenges in parsing web mail communication, SSL decryption and Bitcoins detection.

关键词： Network forensic tools TCP reassembling Traffic reconstruction Web mail Bitcoin SSL encryption

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Null-Space Smoothing Of Tomographic images Using Tv Norm Minimization

Null-Space Smoothing Of Tomographic Images Using TV Norm Min...

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IEEE Nuclear Science Symposium / Medical Imaging conference / Room-Temperature Semiconductor Detector Workshop (NSS/MIC/RTSD)

作者： Smith, Bruce Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX USA

ISBN: (纸本)9781509016426

Smoothing is desirable in tomographic imaging when it reduces the effects of noise in the data and is undesirable when it smooths a small feature such as a tumor or a lesion so much that they become undetectable. Linear algebra can be used to identify a significant problem associated with reconstruction from incomplete data set;namely, the rank of the resulting system matrix is less then full. To maximize its benefit and to minimize its harm, when smoothing is used in this case, it seems desirable to give more credence to the row-space component of the reconstruction than the null-space because the tomographic data contains only information about the row-space component of the object. The objective of the work presented here is to propose and demonstrate a method, which is called null-space smoothing, for achieving this. The Methodology used involved computer generated data. ART is used to reconstruct the row-space component of the Shepp and Logan phantom. By solving a convex optimization problem, an image in the nullspace was added to the reconstruction so that the resulting image had a minimum Tv norm;thus, leaving the row-space component unchanged. It is concluded that although null-space smoothing can produce smooth images with an unchanged rowspace component, more work needs to be done in the future to demonstrate its usefulness with real data.

关键词： image reconstruction X-ray tomography reconstruction algorithms computed tomography

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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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Statistical inversion for medical x-ray tomography with few radiographs:: II.: Application to dental radiology

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PHYSICS IN MEDICINE AND BIOLOGY 2003年第10期48卷 1465-1490页

作者： Kolehmainen, v Siltanen, S Järvenpää, S Kaipio, JP Koistinen, P Lassas, M Pirttilä, J Somersalo, E Univ Kuopio Dept Appl Phys FIN-70211 Kuopio Finland Instrumentat Corp Imaging Div FIN-04301 Tuusula Finland Univ Helsinki Rolf Nevanlinna Inst FIN-00014 Helsinki Finland Invers Ltd FIN-99600 Sodankyla Finland Helsinki Univ Technol Inst Math FIN-02015 Helsinki Finland

Diagnostic and operational tasks in dental radiology often require three-dimensional information that is difficult or impossible to see in a projection image. A CT-scan provides the dentist with comprehensive three-dimensional data. However, often CT-scan is impractical and, instead, only a few projection radiographs with sparsely distributed projection directions are available. Statistical (Bayesian) inversion is well-suited approach for reconstruction from such incomplete data. In statistical inversion, a priori information is used to compensate for the incomplete information of the data. The inverse problem is recast in the form of statistical inference from the posterior probability distribution that is based on statistical models of the projection data and the a priori information of the tissue. In this paper, a statistical model for three-dimensional imaging of dentomaxillofacial structures is proposed. Optimization and MCMC algorithms are implemented for the computation of posterior statistics. Results are given with in vitro projection data that were taken with a commercial intraoral x-ray sensor. Examples include limited-angle tomography and full-angle tomography with sparse projection data. reconstructions with traditional tomographic reconstruction methods are given as reference for the assessment of the estimates that are based on the statistical model.

关键词： Projections and Predictions Tomography statistical Roentgen Rays Radiology Specialty 体层摄影术 Radiology Tomography PROJECTION Projection X-Ray Computed Tomography dental radiology X-rays statistical models (nuclear)

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APPROACH TO image reconstruction USING CUBIC SPLINE FUNCTIONS: ITS SIGNIFICANCE AND APPLICATIONS.

APPROACH TO IMAGE RECONSTRUCTION USING CUBIC SPLINE FUNCTION...

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Proceedings of the Thirteenth Annual Northeast Bioengineering conference.

作者： Cheung, Wang Kong Herman, Gabor T. Markoe, Andrew

In some imaging techniques, such as X-ray computerized tomography (CT) and magnetic resonance imaging (MRI), analytical formulas exist for reconstructing an image from a continuum of data which can only be approximated by measured data. A method of analytical image reconstruction using a special set of functions made up of combinations of cubic spline functions and trigonometric functions is described. The significance and advantages of this approach are presented. It is shown how the approach can easily accommodate image reconstruction problems with irregularly sampled data and incomplete data. Examples of applications of this approach to X-ray CT and MRI are given.

关键词： image PROCESSING

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