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Results for “Parallel Algorithms”

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At least 505 records · Page 28Linked to original sources

PubMed1999

Digitally reconstructed radiographs from abdominal CT scans as a new tool for radiotherapy planning.

OBJECTIVE: Abdominal extended field radiotherapy requires exact field shaping. Conventional treatment planning is difficult to adapt to individual anatomy, whereas three-dimensional planning is time-consuming. The authors introduce a method with digitally reconstructed radiographs of spiral CT data to facilitate radiotherapy planning. METHODS: Twenty-two patients underwent imaging with a standardized CT protocol, and digitally reconstructed radiographs were calculated in central beam projection using a maximum intensity projection algorithm (MIP-DRR). For comparison, the expected error from parallel projection was calculated depending on object thickness and field length. RESULTS: The contrast-enhanced protocol used in spiral CT produces a good rendition of all relevant structures. The resulting MIP images have a geometry identical to standard simulation films and to the linear accelerator, whereas standard MIPs with parallel projection show significant distortion compared to the treatment process. CONCLUSIONS: Because of the integration of the geometry of the radiotherapy treatment, the described central beam projection method might be used as a new tool for abdominal radiotherapy planning. The CT protocol offers sufficient contrast enhancement in all relevant structures and provides all necessary anatomic information for individual beam shaping.

Adult↗

PubMed2002

Longitudinal aliasing in multislice helical computed tomography: sampling and cone-beam effects.

In this study, we examine longitudinal aliasing properties in multislice helical computed tomography (CT) volumes reconstructed under the multiple parallel fanbeam approximation by use of a 180LI-type algorithm. We focus on the differences between the multislice case and the single-slice case, which has been studied previously. Specifically, we examine longitudinal aliasing properties in four-slice scanners for helical pitches 3 and 6, which are sometimes called "preferred" in four-slice helical CT, because it is believed that the effective longitudinal sampling intervals at these pitches are equivalent to those in single-slice helical CT operating at pitches 1 and 2, respectively. While these equivalences have been supported by comparative studies of slice-sensitivity profiles in single- and multislice helical CT, artifacts have been observed in pitch-3 and pitch-6 multislice images that were not evident in their purported single-slice counterparts. We attribute these differences to aliasing arising in the multislice reconstructions that is not present in the single-slice counterparts. We find that the aliasing has two principal origins: sampling effects similar to those in the single-slice case and cone-beam effects. The difference between the multislice, pitch-3 and single-slice, pitch-1 results is attributed to the small cone angle in multislice helical CT, which introduces inconsistencies among the measurements of different detector rows. The difference between multislice, pitch-6 and single-slice, pitch-2 results is attributed to a combination of the cone angle and genuine differences in sampling patterns. It is argued, however, that the lack of strict equivalence with single-slice counterparts does not necessarily undermine the claim that pitches 3 and 6 are "preferred" relative to other pitches in multislice helical CT.

Artifacts↗

PubMed1992

[Online control of evaluation algorithms of the image applied to identification of deglutition function].

Comprehensive software and hardware have been developed for the processing of biosignals. Such automatic signal processing, however not only has advantages, but also drawbacks. The question as to the reliability of the evaluation algorithm arises when the signal is modified, in the presence of interindividual differences, and in particular when noise is superimposed. This is of great interest for long-term recording when the original signal can no longer be inspected visually. The aim of our work was to display the signals on the screen of a monitor simultaneously with lines marking the points (start, end, extreme value, etc.) processed by the specific signal processing algorithm. The program package permits the on-line recording and monitoring of signals, the parallel processing and marking of detected events on the monitor, as well as storage of the parameters extracted. It is a very effective tool for developing, improving and monitoring of algorithms and their efficiency for signal processing.

Algorithms↗

PubMed2005

Parametric reconstruction of generalized cylinders from limb edges.

The three-dimensional (3-D) reconstruction of generalized cylinders (GCs) is an important research field in computer vision. One of the main difficulties is that some contour features in images cannot be reconstructed by traditional stereovision because they do not correspond to reflectance discontinuities of surface in space. In this paper, we present a novel, parametric approach for the 3-D reconstruction of circular generalized cylinders (CGCs) only from the limb edges of CGCs in two images. Instead of exploiting the invariant and quasiinvariant properties of some specific subclasses of GCs in projections, our reconstruction is achieved by some general assumptions on GCs, and can, therefore, be applied to a broader subclass of GCs. In order to improve robustness, we perform the extraction and labeling of the limb edge interactively, and estimate the epipolar geometry between two images by an optimal algorithm. Then, for different types of GCs, three kinds of symmetries (parallel symmetry, skew symmetry, and local smooth symmetry) are employed to compute the symmetry of limb edges. The surface points corresponding to limb edges in images are reconstructed by integrating the recovered epipolar geometry and the properties induced from the assumptions that we make on the GCs. Finally, a homography-based method is exploited to further refine the 3-D description of the GC with a coplanar curved axis.

Algorithms↗

PubMed2006

Watermarking mesh-based representations of 3-D objects using local moments.

A new methodology for fingerprinting and watermarking three-dimensional (3-D) graphical objects is proposed in this paper. The 3-D graphical objects are described by means of polygonal meshes. The information to be embedded is provided as a binary code. A watermarking methodology has two stages: embedding and detecting the information that has been embedded in the given media. The information is embedded by means of local geometrical perturbations while maintaining the local connectivity. A neighborhood localized measure is used for selecting appropriate vertices for watermarking. A study is undertaken in order to verify the suitability of this measure for selecting vertices from regions where geometrical perturbations are less perceptible. Two different watermarking algorithms, that do not require the original 3-D graphical object in the detection stage, are proposed. The two algorithms differ with respect to the type of constraint to be embedded in the local structure: by using parallel planes and bounding ellipsoids, respectively. The information capacity of various 3-D meshes is analyzed when using the proposed 3-D watermarking algorithms. The robustness of the 3-D watermarking algorithms is tested to noise perturbation and to object cropping.

Algorithms↗

PubMed1986

Comprehensive health assessment: an algorithmic model.

Most professional communities advocate and employ an assessment of some kind before initiating an action of change. The closer that health promotion programs parallel such models, the easier it will be for their products to be accepted in the health community. This article describes such a comprehensive algorithmic health assessment model, applicable to therapeutic recreation. The focus of the model is on the conceptual interplay between health assessment and the design of prescriptive health promotion plans that are tailored to the individual client. References and general recommendations for applying this model to special populations are provided.

Health Promotion↗

PubMed2006

Approximation properties of haplotype tagging.

BACKGROUND: Single nucleotide polymorphisms (SNPs) are locations at which the genomic sequences of population members differ. Since these differences are known to follow patterns, disease association studies are facilitated by identifying SNPs that allow the unique identification of such patterns. This process, known as haplotype tagging, is formulated as a combinatorial optimization problem and analyzed in terms of complexity and approximation properties. RESULTS: It is shown that the tagging problem is NP-hard but approximable within 1 + ln((n2 - n)/2) for n haplotypes but not approximable within (1-epsilon) ln(n/2) for any epsilon > 0 unless NP subset DTIME(n(log log n)). A simple, very easily implementable algorithm that exhibits the above upper bound on solution quality is presented. This algorithm has running time O(np/2(2m-p+1)) < or = O(m(n2-n)/2) where p < or = min(n, m) for n haplotypes of size m. As we show that the approximation bound is asymptotically tight, the algorithm presented is optimal with respect to this asymptotic bound. CONCLUSION: The haplotype tagging problem is hard, but approachable with a fast, practical, and surprisingly simple algorithm that cannot be significantly improved upon on a single processor machine. Hence, significant improvement in computational efforts expended can only be expected if the computational effort is distributed and done in parallel.

Algorithms↗

PubMed2005

Fast SVM training algorithm with decomposition on very large data sets.

Training a support vector machine on a data set of huge size with thousands of classes is a challenging problem. This paper proposes an efficient algorithm to solve this problem. The key idea is to introduce a parallel optimization step to quickly remove most of the nonsupport vectors, where block diagonal matrices are used to approximate the original kernel matrix so that the original problem can be split into hundreds of subproblems which can be solved more efficiently. In addition, some effective strategies such as kernel caching and efficient computation of kernel matrix are integrated to speed up the training process. Our analysis of the proposed algorithm shows that its time complexity grows linearly with the number of classes and size of the data set. In the experiments, many appealing properties of the proposed algorithm have been investigated and the results show that the proposed algorithm has a much better scaling capability than Libsvm, SVMlight, and SVMTorch. Moreover, the good generalization performances on several large databases have also been achieved.

Algorithms↗

PubMed2004

Comparison of dose calculation algorithms in phantoms with lung equivalent heterogeneities under conditions of lateral electronic disequilibrium.

An extensive set of benchmark measurement of PDDs and beam profiles was performed in a heterogeneous layer phantom, including a lung equivalent heterogeneity, by means of several detectors and compared against the predicted dose values by different calculation algorithms in two treatment planning systems. PDDs were measured with TLDs, plane parallel and cylindrical ionization chambers and beam profiles with films. Additionally, Monte Carlo simulations by means of the PENELOPE code were performed. Four different field sizes (10 x 10, 5 x 5, 2 x 2, and 1 x 1 cm2) and two lung equivalent materials (CIRS, p(w)e=0.195 and St. Bartholomew Hospital, London, p(w)e=0.244-0.322) were studied. The performance of four correction-based algorithms and one based on convolution-superposition was analyzed. The correction-based algorithms were the Batho, the Modified Batho, and the Equivalent TAR implemented in the Cadplan (Varian) treatment planning system and the TMS Pencil Beam from the Helax-TMS (Nucletron) treatment planning system. The convolution-superposition algorithm was the Collapsed Cone implemented in the Helax-TMS. The only studied calculation methods that correlated successfully with the measured values with a 2% average inside all media were the Collapsed Cone and the Monte Carlo simulation. The biggest difference between the predicted and the delivered dose in the beam axis was found for the EqTAR algorithm inside the CIRS lung equivalent material in a 2 x 2 cm2 18 MV x-ray beam. In these conditions, average and maximum difference against the TLD measurements were 32% and 39%, respectively. In the water equivalent part of the phantom every algorithm correctly predicted the dose (within 2%) everywhere except very close to the interfaces where differences up to 24% were found for 2 x 2 cm2 18 MV photon beams. Consistent values were found between the reference detector (ionization chamber in water and TLD in lung) and Monte Carlo simulations, yielding minimal differences (0.4%+/-1.2%). The penumbra broadening effect in low density media was not predicted by any of the correction-based algorithms, and the only one that matched the experimental values and the Monte Carlo simulations within the estimated uncertainties was the Collapsed Cone Algorithm.

Algorithms↗

PubMed2005

FBP Algorithms for Attenuated Fan-Beam Projections.

A filtered backprojection (FBP) reconstruction algorithm for attenuated fan-beam projections has been derived based on Novikov's inversion formula. The derivation uses a common transformation between parallel-beam and fan-beam coordinates. The filtering is shift-invariant. Numerical evaluation of the FBP algorithm is presented as well. As a special application, we also present a shift-invariant FBP algorithm for fan-beam SPECT reconstruction with uniform attenuation compensation. Several other fan-beam reconstruction algorithms are also discussed. In the attenuation-free case, our algorithm reduces to the conventional fan-beam FBP reconstruction algorithm.

Journal Article↗

PubMed2001

A generalized approach to parallel magnetic resonance imaging.

Parallel magnetic resonance (MR) imaging uses spatial encoding from multiple radiofrequency detector coils to supplement the encoding supplied by magnetic field gradients, and thereby to accelerate MR image acquisitions beyond previous limits. A generalized formulation for parallel MR imaging is derived, demonstrating the relationship between existing techniques such as SMASH and SENSE, and suggesting new algorithms with improved performance. Hybrid approaches combining features of both SMASH-like and SENSE-like image reconstructions are constructed, and numerical conditioning techniques are described which can improve the practical robustness of parallel image reconstructions. Incorporation of numerical conditioning directly into parallel reconstructions using the generalized approach also removes a cumbersome and potentially error-prone sensitivity calibration step involving division of two distinct in vivo reference images. Hybrid approaches in combination with numerical conditioning are shown to extend the range of accelerations over which high-quality parallel images may be obtained.

Algorithms↗

PubMed2001

A biologically inspired neural network for dynamic programming.

An artificial neural network with a two-layer feedback topology and generalized recurrent neurons, for solving nonlinear discrete dynamic optimization problems, is developed. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. The neural network based algorithm is an advantageous approach for dynamic programming due to the inherent parallelism of the neural networks; further it reduces the severity of computational problems that can occur in methods like conventional methods. Some illustrative application examples are presented to show how this approach works out including the shortest path and fuzzy decision making problems.

Algorithms↗

PubMed2004

Self-shielding effects in neutron spectra measurements for neutron capture therapy by means of activation foils.

The design and optimisation of a neutron beam for neutron capture therapy (NCT) is accompanied by the neutron spectra measurements at the target position. The method of activation detectors was applied for the neutron spectra measurements. Epithermal neutron energy region imposes the resonance structure of activation cross sections resulting in strong self-shielding effects. The neutron self-shielding correction factor was calculated using a simple analytical model of a single absorption event. Such a procedure has been applied to individual cross sections from pointwise ENDF/B-VI library and new corrected activation cross sections were introduced to a spectra unfolding algorithm. The method has been verified experimentally both for isotropic and for parallel neutron beams. Two sets of diluted and non-diluted activation foils covered with cadmium were irradiated in the neutron field. The comparison of activation rates of diluted and non-diluted foils has demonstrated the correctness of the applied self-shielding model.

Absorption↗

PubMed2006

Pvclust: an R package for assessing the uncertainty in hierarchical clustering.

SUMMARY: Pvclust is an add-on package for a statistical software R to assess the uncertainty in hierarchical cluster analysis. Pvclust can be used easily for general statistical problems, such as DNA microarray analysis, to perform the bootstrap analysis of clustering, which has been popular in phylogenetic analysis. Pvclust calculates probability values (p-values) for each cluster using bootstrap resampling techniques. Two types of p-values are available: approximately unbiased (AU) p-value and bootstrap probability (BP) value. Multiscale bootstrap resampling is used for the calculation of AU p-value, which has superiority in bias over BP value calculated by the ordinary bootstrap resampling. In addition the computation time can be enormously decreased with parallel computing option.

Algorithms↗

PubMed2001

Form invariance and implicit parallelism.

Holland's schema theorem (an inequality) may be viewed as an attempt to understand genetic search in terms of a coarse graining of the state space. Stephens and Waelbroeck developed that perspective, sharpening the schema theorem to an equality. Of particular interest is a "form invariance" of their equations; the form is unchanged by the degree of coarse graining. This paper establishes a similar form invariance for the more general model of Vose et al. and uses the attendant machinery as a springboard for an interpretation and discussion of implicit parallelism.

Algorithms↗

PubMed1997

LASSAP, a LArge Scale Sequence compArison Package.

MOTIVATION: This paper presents LASSAP, a new software package for sequence comparison. LASSAP is a programmable, high-performance system designed to raise current limitations of sequence comparison programs in order to fit the needs of large-scale analysis. LASSAP provides an API (Application Programming Interface) allowing the integration of any generic pairwise-based algorithm. RESULTS: Whatever pairwise algorithm is used in LASSAP, it shares with all other algorithms numerous enhancements such as: (i) intra- and inter-databank comparisons; (ii) computational requests (selections and computations are achieved on the fly); (iii) frame translations on queries and databanks; (iv) structured results allowing easy and powerful post-analysis; (v) performance improvements by parallelization and the driving of specialized hardware. LASSAP currently implements all major sequence comparison algorithms (Fasta, Blast, Smith/Waterman), and other string matching and pattern matching algorithms. LASSAP is both an integrated software for end-users and a framework allowing the integration and the combination of new algorithms. LASSAP is used in different projects such as the building of PRODOM, the exhaustive comparison of yeast sequences, and the subfragments matching problem of TREMBL.

Algorithms↗

PubMed1990

Self-organising learning control and its application to muscle relaxant anaesthesia.

The concept of a self-organising control system is attractive in biomedicine because of the imprecise nature of available physiological models. In this paper a particular strategy called a self-organising controller (SOC) originating from the work of Barron on aerospace systems is applied to the control of muscle relaxant anaesthesia. The SOC algorithm, which requires no prior knowledge of system dynamics, is described, both in single variable and multivariable format. Simulation results are presented for SOC performance on a well-established pancuronium model. Three implementations are described, being the use of a general purpose language, a SUN workstation approach, and a parallel computer transputer solution. The latter approach becomes important for multivariable control because of the computing-intensive nature of SOC. The transputer is shown to be a suitable vehicle for implementation in terms of speed and parallelism for SOC.

Algorithms↗

PubMed1999

Kinetic parameter estimation from compartment models using a genetic algorithm.

Kinetic parameters were estimated from a three-compartment fluorodeoxyglucose model with three rate constants using a genetic algorithm. The performance of the genetic algorithm was investigated by simulation studies, in which brain time-activity data (TAD) were generated using cited mean values of rate constants and the plasma TAD obtained from positron emission tomographic studies. The accuracy of kinetic parameter estimation using the genetic algorithm was compared with that using the non-linear least-squares (NLSQ) method. The margin of error in the parameters estimated using the genetic algorithm tended to be smaller than that obtained by the NLSQ method. Although not statistically significant at a noise level of 5% in the brain TAD, the difference between the two methods became significant for all parameters at a noise level of 15% or higher. Our results suggest that the genetic algorithm is a promising means of estimating kinetic parameters from compartment models, because it is more robust against statistical noise than the NLSQ method and it can be rendered highly parallel for processing.

Algorithms↗