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P M Marsili

Publications and source records attributed to P M Marsili.

6 recordsLinked to original sources
PubMed1996

Bioelectrical impedance techniques in medicine. Part III: Impedance imaging. Second section: reconstruction algorithms.

This section is devoted to the reconstruction algorithms published in the literature and developed for reconstructing the electrical conductivity and permittivity inside a body from measurements made on the body surface. These algorithms fall into two main categories. The first, based on linear approximations, are noniterative methods assuming that conductivity does not differ very much from a constant. Examples of noniterative methods are the Barber-Brown back-projection method and related methods, the Calderon's approach, the moment method, and one-step Newton methods. The second class of methods consists of iterative methods, which typically include output least squares for various functions. A related class includes the adaptive methods, in which the applied patterns of current are adjusted to get the best signal. A review of all these different alternatives is presented.

Algorithms↗
PubMed1994

A direct sensitivity matrix approach for fast reconstruction in electrical impedance tomography.

In electrical impedance imaging, several proposed reconstruction algorithms have employed the concept of a sensitivity matrix, which can be used to relate the magnitude of a boundary voltage change of a 2D object to the change in conductivity inside the object that has given rise to it. The search for an appropriate inversion of the sensitivity matrix is the key to these algorithms. In this work, a method called the direct sensitivity matrix (DSM) approach for fast image reconstruction is proposed. Both theoretical and experimental results showing the efficiency of this proposed method are also presented.

Algorithms↗
PubMed1994

Using the Hilbert uniqueness method in a reconstruction algorithm for electrical impedance tomography.

This paper presents a new version of the layer stripping algorithm in the sense that it works essentially by repeatedly stripping away the outermost layer of the medium after having determined the conductivity value in this layer. In order to stabilize the ill posed boundary value problem related to each layer, we base our algorithm on the Hilbert uniqueness method (HUM) and implement it with the boundary element method (BEM).

Algorithms↗
PubMed1992

Conductivity interface modelling with dipoles by means of optimal control and boundary element methods in impedance tomography.

Optimal control techniques have been combined with Alessandrini's singular perturbation method and Wexler's algorithm to reconstruct images in impedance imaging. We have also considered an integral formulation of the potential problem, which has led us to introduce an array of dipoles whose position, orientation and length can be optimised to model the conductivity discontinuities.

Algorithms↗