Phase-constrained data extrapolation method for reduction of truncation artifacts

The authors present an improvement to a sigma-filter extrapolation method for the reconstruction of magnetic resonance (MR) images from symmetric discrete Fourier data. By making use of the phase information in the image data, the proposed method can overcome the data inconsistency problem of the original method for handling MR image data with large phase variations, such as those obtained in gradient-echo pulse sequences. Reconstruction results show that its performance is comparable with that of the modified complex sigma-filter method proposed previously to handle the inconsistency problem. However, the new approach has the advantage of reducing computation time by a factor of two with use of a sigma filter applied to real instead of complex images. It is expected that this method will be more practical for use in clinical MR imaging systems.     

Simulating realistic zero loop pedigrees using a bipartite Prufer code and graphical modelling.

Graph algorithms previously developed by the authors are adapted to simulate pedigrees similar to those used in genetic linkage studies which associate disease phenotypes with specific genomic locations. Pedigrees are chosen uniformly at random from the set of those with specified numbers of individuals and matings and which contain no loops. Summary statistics from pedigrees generated in this way can be used to check real pedigrees for anomalies due to biased sampling or phenotypic effects on the pedigree structure.     

Semi-automated analysis of manually reconstructed tracks of progressively motile human spermatozoa

Several alternative algorithms for computer-assisted derivationof measurements of movement characteristics from manually reconstructedtracks of progressively motile human spermatozoa were compared.Fifty tracks were reconstructed at 30 Hz from video recordingsand analysed using traditional manual methods and by four combinationsof computer algo rithms. The best algorithm set was identified(‘Video-mot.mdpt’) and the values for the curvilinear,average path and linear velocities (V_CVL, V_AVE and V_LIN respectively),the amplitude of lateral displacement of the sperm head aboutthe axis of progression (A_H) and the number of times the spermhead crossed the average path (the ‘beat/cross frequency’,BXF) obtained using it were compared to those obtained by manualanalysis. There was a considerable time saving when the computer-assistedmethod was used and the values it gave for the various movementcharacteristics showed good correspondence with those obtainedmanually. In addition, repeated data entry and analysis wasfound to be highly reproducible. When the tracks were re-plottedat 6 Hz (as used by the multiple-exposure photomicrography methodfor sperm motility analysis) insufficient information remainedin the tracks for reliable determination of anything other thanV_LIN We conclude that the Videomot.mdpt program provides reliablevalues for the movement characteristics of progressively motilehuman spermatozoa, and believe it will be of great value inthe validation of commercial systems providing automated spermmovement analysis and in laboratories which do not have accessto such costly equipment.     

Single dipole localization: Some numerical aspects and a practical rejection criterion for the fitted parameters

Summary There have been a number of attempts in the last years to localize the generators of brain electromagnetic activity, considering one current dipole as the source model. Single Dipole Localization (SDL) requires the selection of an optimization algorithm (OA). General aspects related with the selection, implementation and evaluation of some of the OA employed for SDL are discussed in this paper. Specifically the performance of two algorithms, those of Hooke-Jeeves and Levenberg-Marquardt, are tested by simulations. Suggestions for including restrictions to the dipole position and comments about some commonly used measures of the goodness of fit are given. Examples of erroneous implementations of these algorithms are also illustrated. A simple graphic rejection criterion, which can be easily used by inexperienced researchers, is introduced and tested in noisy and noise free simulations.The authors are grateful to Roberto D. Pascual Marqui for programming the Hooke-Jeeves algorithm.     

Mathematical model of volume kinetics and renal function after burn injury and resuscitation

This paper presents a mathematical model of blood volume kinetics and renal function in response to burn injury and resuscitation, which is applicable to the development and non-clinical testing of burn resuscitation protocols and algorithms. Prior mathematical models of burn injury and resuscitation are not ideally suited to such applications due to their limited credibility in predicting blood volume and urinary output observed in wide-ranging burn patients as well as in incorporating contemporary knowledge of burn pathophysiology. Our mathematical model consists of an established multi-compartmental model of blood volume kinetics, a hybrid mechanistic-phenomenological model of renal function, and novel lumped-parameter models of burn-induced perturbations in volume kinetics and renal function equipped with contemporary knowledge on burn-related physiology and pathophysiology. Using the dataset collected from 16 sheep, we showed that our mathematical model can be characterized with physiologically plausible parameter values to accurately predict blood volume kinetic and renal function responses to burn injury and resuscitation on an individual basis against a wide range of pathophysiological variability. Pending validation in humans, our mathematical model may serve as an effective basis for in-depth understanding of complex burn-induced volume kinetic and renal function responses as well as development and non-clinical testing of burn resuscitation protocols and algorithms.     

Iterative reconstruction algorithms

In this paper a survey of recent results on iterative reconstruction algorithms is given. These results, many of which have not yet appeared elsewhere, are applicable to a very general formulation of the reconstruction problem based on the series expansion approach. A set of optimization criteria and a number of iterative reconstruction algorithms are stated, together with theorems on the convergence of the algorithms to optimum images. The efficacy of the algorithms is compared to that of the convolution method. In particular, the falseness of the claim that ART and the backprojection method are the same is demonstrated.     

混合遗传算法在随机规划问题中的应用

以含有机会约束的生产管理动态规划问题为例,基于随机模拟技术的混合遗传算法实现最优化决策,构造了数学模型。采用ＶＢ编辑,计算机模拟结果显示该模型能很好解决生产过程中的最优化决策问题,它是简单的基于二进制编码的遗传算法所不能解决的。该算法具有很高的鲁棒性,避免了在局部最优解附近徘徊,且因为随机规划问题要求许多数学知识,而算法本身并不要求对优化问题的性质作一些深入的数学分析,从而对那些不太熟悉数学理论和