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conference on Wavelet Applications in Signal and image Processing viii

作者： Feilner, M Blu, T Unser, M Swiss Fed Inst Technol IOA DMT Biomed Imaging Grp CH-1015 Lausanne Switzerland

ISBN: (纸本)0819437646

Ruttimann et al. have proposed to use the wavelet transform for the detection and localization of activation patterns in functional magnetic resonance imaging (fMRI). Their main idea was to apply a statistical test in the wavelet domain to detect the coefficients that are significantly different from zero. Here, we improve the original method in the case of non-stationary Gaussian noise by replacing the original z-test by a t-test that takes into account the variability of each wavelet coefficient separately. The application of a threshold that is proportional to the residual noise level, after the reconstruction by an inverse wavelet transform, further improves the localization of the activation pattern in the spatial domain. A key issue is to find out which wavelet and which type of decomposition is best suited for the detection of a given activation pattern. In particular, we want to investigate the applicability of alternative wavelet bases that are not necessarily orthogonal. For this purpose, we consider the various brands of fractional spline wavelets (orthonormal, B-spline, and dual) which are indexed by a continuously-varying order parameter alpha. We perform an extensive series of tests using simulated data and compare the various transforms based on their false detection rate (type I + type II errors). In each case, we observe that there is a strongly optimal value of alpha and a best number of scales that minimizes the error. We also find that splines generally outperform Daubechies wavelets and that they are quite competitive with SPM (the standard analysis method used in the held), although it uses much simpler statistics. An interesting practical finding is that performance is strongly correlated with the number of coefficients detected in the wavelet domain, at least in the orthonormal and B-spline cases. This suggest that it is possible to optimize the structural wavelet parameters simply by maximizing the number of wavelet counts, without any prior

关键词： functional imaging fMRI statistical analysis medical imaging wavelets fractional splines

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Segmented attenuation map reconstruction from incomplete transmission data

Segmented attenuation map reconstruction from incomplete tra...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： H. Kudo H. Nakamura Institute of Information Sciences and Electronics University of Tsukuba Tsukuba Japan Doctoral Program in Engineering University of Tsukuba Tsukuba Japan

Accurate reconstruction of attenuation maps from incomplete sinograms are required in some cases of SPECT and PET imaging. This paper proposes a new method to directly reconstruct segmented attenuation maps from the incomplete sinograms. The proposed method is based on an image labeling technique where an optimum label configuration minimizing some energy function is found by using a stochastic sampling with simulated annealing. Unlike ordinary image labeling techniques, however, the authors introduce a powerful constraint called the topology-preserving constraint. This constraint reduces the search space to a set of label configurations having the same topology as the known topology of the attenuation map in question. The experimental results demonstrate that the topology-preserving constraint is powerful enough to reconstruct accurate segmented attenuation maps from the incomplete sinograms. The proposed method is tested with simulated data and PET transmission data.

关键词： Attenuation image reconstruction image segmentation Positron emission tomography Labeling Topology Stochastic processes image sampling Simulated annealing Testing

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3D-FRP: Direct Fourier reconstruction with Fourier reprojection for fully 3D PET

3D-FRP: Direct Fourier reconstruction with Fourier reproject...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： S. Matej Department of Radiology University of Pennsylvania Philadelphia PA USA

The direct Fourier method for 3D reconstruction of a 3D volume is based on the relationship between the 3D Fourier transform of the volume and the 2D FT of a parallel-ray projection of the volume. The direct Fourier method has the potential for very fast reconstruction, but a straightforward implementation of the method leads to unsatisfactory results. This paper presents an implementation (3D-FRP) of the direct Fourier method for fully 3D PET data with incomplete oblique projections that gives results as good as (or better than) those of a much slower method (3DRP), and in the same time as a fast but less accurate method (Fourier rebinning followed by slice-by-slice reconstruction). In common with filtered backprojection (3DRP), the Fourier method (3D-FRP) is based on a discretization of an inversion formula (so it is geometrically accurate for large oblique angles), and the method involves reprojection of an initial image. The critical two steps in the method are the estimations of the samples of the 3D transform of the image from the samples of the 2D transforms of the projections on the planes through the origin of Fourier space, and vice versa for reprojection. These steps use a gridding strategy, combined with new approaches for weighting in the transform and image domains. The authors' experimental results confirm that good image accuracy can be achieved together with a short reconstruction time.

关键词： Positron emission tomography image reconstruction Fourier transforms Approximation error Design for manufacture Radiology USA Councils Single photon emission computed tomography image quality image resolution

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Modification of EIT algorithms using a pipeline multiprocessor algorithm

Modification of EIT algorithms using a pipeline multiprocess...

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Mediterranean Electrotechnical conference (MELECON)

作者： M. Kacarska S. Loskovska Faculty of Electrical Engineering University Sts. Kiril and Metodij Skopje Macedonia

Electrical impedance tomography (EIT) is relatively new medical imaging modality that produces images by computing electrical properties within the human body. In EIT, sinusoidal electric currents are applied to the body using electrodes attached to the skin, and voltage measurements that are developed on the electrodes are used. Using these data, a reconstruction algorithm computes the conductivity and permittivity distribution within the body. Several algorithms for EIT reconstruction that is able to track fast changes from incomplete data set in the impedance distribution are proposed. A modification to the EIT imaging systems proposed in the Kalman filter approach is presented. In the Kalman filter approach speedup is achieved by reduction of the parameter space. This paper presents modifications to the EIT imaging systems that allow continuously display conductivity, permittivity or magnitude of admittivity distributions in a subject for indefinite time intervals without any reduction of data. To achieve higher frame rates a pipeline multiprocessor algorithm (PMA) is used to solve an EIT inverse problem. The real-time imaging system proposed by Edic et al. (1995), and the Kalman filter approach proposed by Vauhkonen et al. (see IEEE Trans. on Biomedical Engineering, vol.45, no.4, p.486-93, 1998), are compared with proposed PMA. With proposed improvement we can obtain 2.8 times faster reconstruction than the Kalman filter approach, which means that the global reconstruction rate is approximately 90 times faster than with the conventional methods.

关键词： Pipelines Tomography image reconstruction Impedance Biomedical imaging Biomedical electrodes Conductivity Permittivity Humans Current

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Bayesian restoration of crack images in welds from incomplete and noisy X-ray data

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AIP conference Proceedings 2000年第1期509卷 635-642页

作者： Valery L. Vengrinovich Yuri B. Denkevich Gerd-Rüdiger Tillack Uwe Ewert Bernhard Redmer Institute of Applied Physics of Belarussian Academy of Science F. Scorina str. 16 Minsk 220072 Belarus Federal Institute for Materials Research and Testing (BAM) Unter den Eichen 87 12205 Berlin Germany

The restoration of crack images in welds calculated from few x-ray projections only is connected with uncertainties which may corrupt the final images, namely: lack of admissible x-ray projections, lack on the projections of data, which definitely indicate the presence of crack, the crack appearance in the projection is frequently hidden by the images of other defects like undercuts, lack of fusion, etc. A complete Bayesian based technique was developed for a multi-step reconstruction of 3D crack images from limited number of 2D projections and checked using simulated and experimental data. A specific equipment for simultaneous circular rotation and out-of-plane tube positioning in connection with a photo diode line camera was developed and tested for in-field inspection and used for measuring the x-ray projections. The Bayesian quasi-3D restoration with Gibbs prior is applied at the last step being preprocessed by the following procedure: estimate the noise level in the 2D images of the object and select for further processing those projections at which the crack indication exceeds the noise level, extract the crack indications from all selected 2D images, apply the “first step technique” to the extracted crack indications. The efficiency of the developed technique is demonstrated using the crack image restoration from real experimental data of a 168×8 mm welded steel pipe with a crack concomitant by an undercut.

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Bidirectional optimization for reconstructing 3D shape from an image sequence with missing data

Bidirectional optimization for reconstructing 3D shape from ...

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International conference on image Processing (ICIP'99)

作者： Maruyama, Minoru Kurumi, Satoshi Shinshu Univ Nagano Japan

reconstruction of 3D structure from a 2D image sequence is very important for image understanding, image based rendering etc. Especially, in practice, reconstruction algorithms that can handle occlusion are necessary. In this paper we extend the factorization algorithm and propose a method to reconstruct 3D shape from an image sequence with missing data. In our method, treating missing elements as unknown parameters, parametric representation of a measurement matrix is given. Since the rank of the ideal measurement matrix should be three, parameter values should be specified so that the discrepancy between the parametric matrix and its associated `closest' rank three matrix is minimized. We describe an iterative algorithm to determine the unknown parameter so as to give rise to the decreasing sequence of the discrepancy. The procedure is nothing but the iterative bidirectional projection between the model space and the observation space (parametric representation of incomplete data). Several experimental results are also provided.

关键词： image reconstruction

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Model-based reconstruction of organ surfaces from two-dimensional CT or MRT data of the head

Model-based reconstruction of organ surfaces from two-dimens...

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Medical Imaging 1999 conference - image Processing

作者： von Klinski, S Glausch, A Tolxdorff, T Free Univ Berlin Hosp Benjamin Franklin Dept Med Informat D-1000 Berlin Germany

ISBN: (纸本)0819431338

Surface-based interpolation and registration, radiation treatment, and three-dimensional visualization of two-dimensional sliced data from CT or MRT require a precise reconstruction of three-dimensional organ surfaces from two-dimensional segmentation results. Current surface-reconstruction algorithms are based on surface triangulations using heuristics to correlate and connect adjacent object slices. The approaches described in the literature can be divided into triangulations using optimization procedures, Delauny triangulations, and topology-based correlations. All approaches assume a global and invariant vertically oriented correlation strategy that can be applied equally to every organ and every slice. Surface and correlation characteristics vary greatly among bony structures and organs such as the eyes and the brain. An adjusted reconstruction of each organ according to its individual tissue characteristics is necessary to avoid errors in following processing steps such as interpolation, registration, and radiation treatment. To this end, we have designed a model-based surface-reconstruction algorithm that takes individual surface characteristics into account and allows the integration of anatomical knowledge. Three-dimensional surface models are generated from sliced data or any other source of anatomical knowledge. These models are later adjusted to the segmentations, compensating for artifacts and incomplete data.

关键词： reconstruction triangulation warping interpolation

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Bidirectional optimization for reconstructing 3D shape from an image sequence with missing data

Bidirectional optimization for reconstructing 3D shape from ...

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IEEE International conference on image Processing

作者： M. Maruyama S. Kurumi Department Information Engineering Shinshu University Nagano Japan

reconstruction of 3D structure from a 2D image sequence is very important for image understanding, image based rendering etc. especially, in practice, reconstruction algorithms that can handle occlusion are necessary. In this paper we extend the factorization algorithm and propose a method to reconstruct 3D shape from an image sequence with missing data. In our method, treating missing elements as unknown parameters, parametric representation of a measurement matrix is given. Since the rank of the ideal measurement matrix should be three, parameter values should be specified so that the discrepancy between the parametric matrix and its associated "closest" rank three matrix is minimized. We describe an iterative algorithm to determine the unknown parameter so as to give rise to the decreasing sequence of the discrepancy. The procedure is nothing but the iterative bidirectional projection between the model space and the observation space (parametric representation of incomplete data). Several experimental results are also provided.

关键词： image reconstruction Shape image sequences Matrix decomposition Position measurement Cameras Rendering (computer graphics) Iterative algorithms image recognition Robustness

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3D shape reconstruction using volume intersection techniques

3D shape reconstruction using volume intersection techniques

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Proceedings of the 1998 IEEE 6th International conference on Computer Vision

作者： Carr, Jonathan C. Fright, W.Richard Gee, Andrew H. Prager, Richard W. Dalton, Kevin J. Cambridge Univ Cambridge United Kingdom

Volume intersection algorithms are used to reconstruct incomplete objects from their silhouettes. An imagined light source is moved about the data and the cumulative amount of `light' seen at each point in space is interpreted as indicating the likelihood that the point is inside the object. The object data need not be uniformly distributed nor exclusively surface data. Explicit distinction between noise, surface and interior data is avoided. The novel concept of a localized viewing region is introduced to overcome the inherent inability of volume intersection algorithms to reconstruct concave surfaces. Algorithms for 2D pixel and 3D voxel data are described and applied to 3D ultrasound data.

关键词： image reconstruction

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3D shape reconstruction using volume intersection techniques

3D shape reconstruction using volume intersection techniques

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International conference on Computer Vision (ICCV)

作者： J.C. Carr R.W. Fright A.H. Gee R.W. Prager K.J. Dalton Department of Engineering University of Cambridge Cambridge UK Applied Research Associates NZ Limited Christchurch New Zealand Department Obstet rics & Gynaecology University of Cambridge Cambridge UK

Volume intersection algorithms are used to reconstruct incomplete objects from their silhouettes. An imagined light source is moved about the data and the cumulative amount of "light" seen at each point an space is interpreted as indicating the likelihood that the point is inside the object. The object data need not be uniformly distributed nor exclusively surface data. Explicit distinction between noise, surface and interior data is avoided. The novel concept of a localised viewing region is introduced to overcome the inherent inability of volume intersection algorithms to reconstruct concave surfaces. Algorithms for 2D pixel and 3D voxel data are described and applied to 3D ultrasound data.

关键词： Shape Surface fitting image reconstruction Surface reconstruction Scattering Surface emitting lasers Gynaecology Light sources Acoustic noise Robots

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