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Biomedical subjects

M K Pidcock

Publications and source records attributed to M K Pidcock.

9 recordsLinked to original sources
PubMed2004

A method for the determination of flux in elementary modes, and its application to Lactobacillus rhamnosus.

In this article we address the question of how, given information about the reaction fluxes of a system, flux values can be assigned to the elementary modes of that system. Having described a method by which this may be accomplished, we first illustrate its application to a hypothetical, in silico system, and then apply it to fermentation data from Lactobacillus rhamnosus. This reveals substantial changes in the flux values assigned to elementary modes, and thus to the internal metabolism, as the fermentation progresses. This is information that could not, to our knowledge, be obtained by existing methods. The relationship between our technique and the well-known method of Metabolic Flux Analysis is also discussed.

Acetoin↗
PubMed2001

An image reconstruction algorithm for three-dimensional electrical impedance tomography.

Electrical impedance tomography (EIT) has been studied by many authors and in most of this work it has been considered to be a two-dimensional problem. Many groups are now turning their attention to the full three-dimensional case in which the computational demands become much greater. It is interesting to look for ways to reduce this demand and in this paper we describe an implementation of an algorithm that is able to achieve this by precomputing many of the quantities needed in the image reconstruction. The algorithm is based on a method called NOSER introduced some years ago by Cheney et al. [3]. In this paper we have significantly extended the method by introducing a more realistic electrode model into the analysis. We have given explicit formulae for the quantities involved so that the reader can reproduce our results.

Algorithms↗
PubMed2000

A one step image reconstruction algorithm for electrical impedance tomography in three dimensions.

The move from two to three dimensions in the study of electrical impedance tomography (EIT) has generated a great increase in computational demands. It is therefore interesting to investigate ways in which this demand can be reduced, and in this paper we have presented some results of one such approach. The NOSER algorithm was introduced some years ago and we have extended it to include more realistic electrode models. The main feature of the method is that by starting from a uniform conductivity distribution many quantities can be pre-calculated.

Algorithms↗
PubMed1993

An adaptive current tomography using voltage sources.

This paper describes the development of an adaptive electric current tomography system which contains a novel front-end analog architecture. Programmable voltage sources have been used to deliver currents into the study object and to avoid the difficulties of obtaining high quality current sources. Through inverting an admittance matrix, the system is capable of achieving a desired current drive pattern by applying a computed voltage pattern. The tomograph, operating at 9.6 kHz, comprises 32 driving electrodes and 32 voltage measurement electrodes. The study of system noise performance shows high SNR in the data acquisition which is enhanced by a digital demodulation scheme. In vitro reconstruction images have been obtained with the data collected by the tomograph.

Electrodes↗
PubMed1988

Data errors and reconstruction algorithms in electrical impedance tomography.

In electrical impedance tomography the reconstruction problem is a non-linear inverse problem and can only be solved by iterative methods. This paper describes two such algorithms, one based on the regularised Newton's method of Levenburg and Marquardt, and a second modified version of this algorithm which uses optimal current drive patterns. The second algorithm is shown to give superior reconstruction in a simulation study. Some effects of errors in the knowledge of boundary shape and electrode position are also discussed.

Algorithms↗
PubMed1987

Mathematical aspects of impedance imaging.

The mathematical problem of reconstructing the unknown variable conductivity of an isotropic medium from a knowledge of boundary currents and voltages is an active area of mathematical research. In terms of impedance imaging the analytical problem is essentially the question 'is there only one conductivity distribution which could have produced this set of measurements?' In mathematical parlance this is an 'identification problem' or 'inverse problem' for an unknown coefficient in an elliptic partial differential equation. Recent results have come close to settling the analytical problem. Kohn and Vogelius have shown that the piece-wise analytic conductivity distributions can be identified by boundary measurements and Sylvester and Uhlmann have shown that a smooth conductivity can be identified in the three-dimensional case and, provided the conductivity is close enough to uniformity, in the two-dimensional case also. The practical numerical problem of designing a numerical algorithm is far from completely understood. Mathematically the problem is one of solving a non-linear functional equation. A common numerical technique for tackling this type of problem is to employ the Newton-Raphson method. This approach is considered in this paper and compared with some of the algorithms appearing in the bioengineering literature. It is observed that, to varying degrees, these methods approximate the Newton-Raphson method.

Algorithms↗