Least squares algorithm for region-of-interest evaluation in emission tomography

An accurate model of the nonstationary geometrical response of a camera-collimator system is discussed. The algorithm is compared to three other algorithms that are specialized for region-of-interest evaluation, as well as to the conventional method for summing the reconstructed quantity over the regions of interest. For noise-free data and for regions of accurate shape, least-squares estimates were unbiased within roundoff errors. For noisy data, estimates were still unbiased but precision worsened for regions smaller than resolution: simulating typical statistics of brain perfusion studies performed with a collimated camera, the estimated standard deviation for a 1-cm-square region was 10% with an ultra-high-resolution collimator and 7% with a low-energy all-purpose collimator. Conventional region-of-interest estimates show comparable precision but are heavily biased if filtered backprojection is used for image reconstruction. Using the conjugate-gradient iterative algorithm and the model of nonstationary geometrical response, bias of estimates decreased on increasing the number of iterations, but precision worsened, thus achieving an estimated standard deviation of more than 25% for the same 1-cm region.     

A stationary sampling scheme for multilayer positron tomographs

A stationary sampling scheme applicable to tomographic instruments incorporating two or more detector layers is described and tested. In this concept, the detectors in adjacent layers are angularly offset by half the interdetector distance. By reconstructing in one single slice all lines of response defined by two adjacent rings of detectors, a fourfold increase in the number of coincidence lines is obtained and a uniform sampling distance equal to one-quarter the interdetector spacing is achieved. Whereas this is obtained at the expense of a 100% degradation of the resolution in the axial direction, with the recent breed of PET (positron emission tomography) scanners using nearly square cross section detectors, the resolution loss may be tolerable in many situations. In addition, normal reconstruction of the individual coincidence planes is always possible. The sampling concept was investigated experimentally with the help of the Universite de Sherbrooke PET camera simulator.     

Area-efficient correlated double sampling scheme with single sampling capacitor for CMOS image sensors

An area-efficient correlated double sampling (CDS) circuit is proposed. In conventional designs, most of the area of CDS circuits is occupied by two large on-chip sampling capacitors. A new CDS scheme is devised using only one sampling capacitor. The proposed CDS circuit has been successfully realised in a small two column pitch of 7.2 /spl mu/m in a test chip fabricated using 0.18 /spl mu/m CMOS process and has demonstrated fixed pattern noise less than 0.46%.     

Region-of-interest tomography using exponential radial sampling

The authors combine several ideas, including nonuniform sampling and circular harmonic expansions, into a new procedure for reconstructing a small region of interest (ROI) of an image from a set of its projections that are densely sampled in the ROI and coarsely sampled outside the ROI. Specifically, the radial sampling density of both the projections and the reconstructed image decreases exponentially with increasing distance from the ROI. The problem and data are reminiscent of the recently formulated local tomography problem; however, the authors' algorithm reconstructs the ROI of the image itself, not the filtered version of it obtained using local tomography. The new algorithm has the added advantages of speed (it can be implemented entirely using the FFT) and parallelizability (each image harmonic is computed independently). Numerical examples compare the new algorithm to filtered backprojection.     

An efficient interlaced multi-shell sampling scheme for reconstruction of diffusion propagators

In this paper, we propose an interlaced multi-shell sampling scheme for the reconstruction of the diffusion propagator from diffusion weighted magnetic resonance imaging (DW-MRI). In standard multi-shell sampling schemes, sample points are uniformly distributed on several spherical shells in q-space. The distribution of sample points is the same for all shells, and is determined by the vertices of a selected polyhedron. We propose a more efficient interlaced scheme where sample points are different on alternating shells and are determined by the vertices of a pair of dual polyhedra. Since it samples more directions than the standard scheme, this method offers increased angular discrimination. Another contribution of this work is the application of optimal sampling lattices to q-space data acquisition and the proposal of a model-free reconstruction algorithm, which uses the lattice dependent sinc interpolation function. It is shown that under this reconstruction framework, the body centered cubic (BCC) lattice provides increased accuracy. The sampling scheme and the reconstruction algorithms were evaluated on simulated data as well as rat brain data collected on a 600 MHz (14.1T) Bruker imaging spectrometer.     

A sampling scheme for estimating the reliability of a series system

The reliability estimation of a series system in which the component reliabilities are unknown is considered. The optimal sampling scheme depends on parameters that are typically unknown. A sequential sampling scheme is introduced and compared with both balanced allocation and optimal allocation. Numerical comparisons for a two-component series system are given. The results indicate that the proposed sequential sampling scheme is much better than balanced allocation and is nearly optimal     

Irregular sampling and local quantification scheme A-D converter

An analogue to digital converter architecture is presented. Statistical redundancy of signals such as audio allows the average number of cycles per sample to be reduced thanks to a local quantification scheme. The converter produces irregularly time spaced samples, without conversion error, at a higher speed than comparable architectures.     

A standardized blood sampling scheme in quantitative FDG-PETstudies

Quantitative estimation of brain glucose metabolism (rCMRGlc) with positron emission tomography and fluorodeoxyglucose involves arterial blood sampling to estimate the delivery of radioactivity to the brain. Usually, for an intravenous injection of 30 s duration, an accurate input curve requires a frequency of one sample every 5 s or less to determine the peak activity in arterial plasma during the first 2 min after injection. In this work, 13 standardized sampling times were shown to be sufficient to accurately define the input curve. This standardized input curve was subsequently fitted by a polynomial function for its rising part and by spectral analysis for its decreasing part. Using the measured, the standardized, and the fitted input curves, rCMRGlc was estimated in 32 cerebral regions of interest in 20 normal volunteers. Comparison of rCMRGlc values obtained with the measured and the fitted input curves showed that both procedures gave consistent results, with a maximal relative error in mean rCMRGlc of 1% when using the autoradiographic method and 2% using kinetic analysis of dynamic data. This input-curve-fitting technique, which is not dependent on the peak time occurrence, allows an accurate determination of the input-curve shape from reduced sampling schemes.     

A novel scheme for synchronous optical sampling based on multicast parametric process

We propose a novel scheme for synchronous optical sampling based on multicast parametric process. The linearly chirped and time-broadened pulses are utilized to replace the traditional mode-locked sampling pulses. An optical sampling rate of 80 Gbit/s is realized by using only one sampling source with repetition rate of 10 GHz.     

New time-discrete modulation scheme for matrix converters

While the known modulation strategies for matrix converters are based on pulsewidth modulation (PWM)-or vector modulation-this paper presents a novel time-discrete modulation method based on real-time prediction calculation to select the switching states. The decision about which switching state is to be set for the following sampling period is made by the use of a predictive quality function. Using this approach, unity displacement factor is seen at the supply side with minimum line current distortion while the load currents follow their reference values with good accuracy. The quality function is derived from a mathematical model of the matrix converter and the controlled system. Measurements taken on a model plant, consisting of a matrix converter and a standard induction machine with a rated output power of 11 kW, show that the matrix converter, equipped with the control method presented here, offers advantages over systems with conventional frequency converters, especially in terms of the input current distortion.     

New dynamic focusing scheme for ultrasound scanners

A new dynamic focusing scheme for ultrasound phased array sector scanners is proposed in which dynamic focusing control is performed by sampled-delay focusing after steering control and the transducer elements are grouped to minimise the focusing control complexity without loss of accuracy.     

Matching pursuit-based region-of-interest image coding.

Matching pursuit (MP) is a multiresolution signal analysis method and can be used to render a selected region of an image with a specific quality. A novel, scalable, and progressive MP-based region-of-interest image-coding scheme is presented. The method is capable of providing a trade off between rate, distortion, and complexity. The method also provides an interactive way of information refinement for regions of an image with higher receiver's priority. By selecting a proper subset of the huge initial MP dictionary, using the method described in this paper, the complexity burden of MP analysis can be adapted to the computational power of the image encoder.     

Gradient-based iterative image reconstruction scheme fortime-resolved optical tomography

Currently available tomographic image reconstruction schemes for optical tomography (OT) are mostly based on the limiting assumptions of small perturbations and a priori knowledge of the optical properties of a reference medium. Furthermore, these algorithms usually require the inversion of large, full, ill-conditioned Jacobian matrixes. In this work a gradient-based iterative image reconstruction (GIIR) method is presented that promises to overcome current limitations. The code consists of three major parts: 1) A finite-difference, time-resolved, diffusion forward model is used to predict detector readings based on the spatial distribution of optical properties; 2) An objective function that describes the difference between predicted and measured data; 3) An updating method that uses the gradient of the objective function in a line minimization scheme to provide subsequent guesses of the spatial distribution of the optical properties for the forward model. The reconstruction of these properties is completed, once a minimum of this objective function is found. After a presentation of the mathematical background, two- and three-dimensional reconstruction of simple heterogeneous media as well as the clinically relevant example of ventricular bleeding in the brain are discussed. Numerical studies suggest that intraventricular hemorrhages can be detected using the GIIR technique, even in the presence of a heterogeneous background.     

Depth perceptual region-of-interest based multiview video coding

MultiView Video (MVV) has attracted considerable attention recently since it is capable of providing users with three-dimensional perception and interactive functionalities. However, these MVV data require large mount of storage and bandwidth in network transmission. In this paper, we present a novel Depth Perceptual Region-Of-Interest (DP-ROI) based Multiview Video Coding (RMVC) scheme to extensively improve data compression efficiency by exploiting redundancies in depth perception. Firstly, we define DP-ROI according to the three-dimensional depth sensation of human visual system. Then, a framework of RMVC is developed to improve compression efficiency by properly segmenting the MVV into different macroblock wise DP-ROIs and encoding them separately. And then, we propose three fast depth based DP-ROI extraction and tracking algorithms by jointly using motion, texture, depth as well as previous extracted DP-ROIs. Finally, on the basis of the extracted DP-ROI, bit allocation optimization model is proposed to allocate more bits on DP-ROIs for high image quality and fewer bits on background regions for high compression ratio. Experimental results show that the presented RMVC scheme achieves significant coding gains at high rate while comparing with original joint multiview video model. To be specific, up to 14.22–23.32% bit-rate are saved while 0.16–0.68 dB coding gains are achieved in DP-ROIs at the cost of the image quality degradation in background.     

An approximation formula for the variance of PET region-of-interest values

An approximation formula for the variance of positron emission tomography (PET) region-of-interest (ROI) values has been developed, implemented, and evaluated. This formula does not require access to the original projection data and is therefore convenient for routine use. The formula was derived by applying successive approximations to the filtered-backprojection reconstruction algorithm. ROI variance is estimated from the product of mean pixel variance within the region and a term accounting for the intercorrelation of all pixel pairs inside the region. The formula accounts for radioactivity distribution, attenuation, randoms, scatter, deadtime, detector normalization, scan length, decay, and reconstruction filter. The algorithm was tested by comparison to the exact ROI variance as calculated with Huesman's algorithm. Tests with scan data from phantoms, animals, and humans obtained on the Scanditronix PC2048-15B tomograph showed the approximation formula to be accurate to within +/-10%     

Direct algebraic reconstruction and optimal sampling in vectorfield tomography

Vector field tomography has been proven to be a very powerful technique for the noninvasive determination of vector field distribution such as in the case of a fluid velocity field. We show that classical tomographic sampling conditions ran essentially be applied to vector field tomography. Thus, essentially the same sampling schemes are obtained, and the interlaced scheme is also shown to be the most efficient scheme in vector field tomography. We then propose a direct algebraic approach for vector field tomography, with an efficient and robust algorithm for interlaced schemes. Numerical experiments showing the superiority of interlaced schemes are provided     

无线多媒体传感器网络中能量高效的采样与传输方法

提出了一种多媒体传感器网络节能数据采样与传输方法。利用Voronoi图来调节节点的传感方向以提高网络覆盖度,并通过可变采样粒度的周期性传感,降低采样能耗。同时,基于色块匹配,进一步降低了数据传输开销。仿真结果表明,在延长网络生存时间方面表现出了较好性能。     

New synchronisation scheme for communication-satellite time-division multiple-access systems

A time-division multiple-access synchronisation scheme is described that uses a minimal bandwidth of a satellite global beam transponder with most traffic being transmitted through a spot beam transponder. Such a scheme is ideally suited to the next generation of communication satellites in which extensive use is likely to be made of spot beam antennas to achieve `frequency reuse?.     

New denoising scheme for magnetic resonance spectroscopy signals

A new scheme for denoising magnetic resonance spectroscopy (MRS) signals is presented. This scheme is based on projecting noisy MRS signals in different domains, consecutively, and performing noise filtering operations in these domains. The domains are chosen such that the noise portion, which is inseparable from the desired signal in one domain, is separable in the other. A set of stable, linear, time-frequency (SLTF) transforms with different resolutions was selected for these projections as an example. Scheme evaluation was performed using extensive MRS signals with various noise levels. Compared with one domain denoising, it was observed that the proposed scheme gives superior results that compensate for the excess computational requirements. The proposed scheme supersedes also the wavelet packet denoising schemes.     

New scheme for vector quantisation of speech signals

The design theory of a vector quantiser is valid only on some assumptions which are unfortunately not satisfied in most real-world cases. A decomposition procedure of speech signals is described which leads to a proposed method for designing the vector quantisers in a reasonable way.<>