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Applies four different minimum norm estimations with common regularization techniques, often used in biomedical applications to the solution of the biomagnetic inverse field problem. Magnetic field data measured with a multi‐channel biomagnetometer sensor system in a magnetically shielded room were used to reconstruct the current density distributions generated by an extended current source which was placed inside a human torso phantom. No one of the tested methods is able to estimate the extension of the source. To improve the results as much as possible a priori information of the source space should be taken into account.

We have prepared a human body phantom for experimental verification of inverse solution techniques which are applied to magnetic (and electric) measuring data. Physical models of extended primary current sources were used to generate these fields. Magnetic field maps closed to the phantom surface were recorded by means of multi-channel biomagnetic measuring systems. Different deterministic optimization techniques were applied to both measured and simulated data to reconstruct the impressed current density distribution. We have found that all common used minimum norm methods (L/sub p/-norms, 1/spl les/p/spl les/2) cannot reconstruct the extension of current source distributions satisfactorily. The physical phantom was found to be a suitable tool for validation of source reconstruction techniques.

The influence of lung inhomogeneities on focal source localizations in electrocardiography (ECG) and magnetocardiography (MCG) is investigated. A realistically shaped physical thorax phantom with cylindrical lung inhomogeneities is used for electric and magnetic measurements. The lungs are modelled with a special ionic exchange membrane which allows different conductivity compartments without influencing the free ionic current flow. The dipolar current sources are composed of platinum wire and located at different depths and directions between the lung inhomogeneities. We localized the current dipoles with different boundary element method (BEM) models, based on electrical data and simultaneous electrical and magnetic data. Our results indicate the possibility of superadditive information gain by combining electrical and magnetic data for source reconstructions. We found a significant influence of the inhomogeneities on both the calculated source location and the calculated source strength. Mislocalizations of up to 16 mm and wrong dipole strengths of up to 52% were obtained when the lung inhomogeneities were not taken into account for source localization. Dipoles parallel to the lungs showed a larger localization error in depth than dipoles perpendicular to the lungs. We conclude that the incorporation of lung inhomogeneities will improve source localization accuracy in ECG and MCG.

Source localization in the human brain based on EEG and MEG data becomes more and more important in the field of clinical research and routine. Thus, information about source localization accuracy is indispensable. Source localization accuracy has been tested with various artificial source and volume conductor models. However, there are a number of limitations inherent to these artificial models. Thus, we address source localization accuracy with an animal model. Furthermore, most investigations have been performed with artificial and physiological sources of a tangential orientation. However, 20 percent of the sources of the human brain have a radial orientation. Hence, an animal model with a lissencephalic cerebrum (flat cortical surface) with radial oriented physiological sources would take this into account.

Biomagnetic measurements using multichannel systems provide magnetic data sets for functional localization of heart or brain activity non-invasively. The interpretation of measured magnetic fields generated by the electrical active organs requires special algorithms to localize or reconstruct the sources. Numerous optimization algorithms to solve this inverse problem are under consideration, deterministic as well as stochastic one. In most cases non-linear, deterministic optimization procedures like Levenberg-Marquardt algorithm are used. We have found that Marquardt algorithm combined with Gauss-Seidel-iteration is the best inverse Solution method in least-squares sense to localize up to three single dipoles [1]. But there appear problems with convergence of this method if deep lying or extended sources have to be localized. For these cases we developed a new version of the well-known minimum-norm Solution based on the Linear Estimation Theory [2,3]. We introduced some modifications which enable us to reconstruct distributed sources too [4]. Therefore, the aim of this paper is to propose a new method for reconstruction of extended sources and estimating their extension.

Artificial dipolar sources were applied inside a physical thorax phantom to experimentally investigate the accuracy obtainable for non-invasive magnetocardiographic equivalent current dipole localisation. For the measurements, the phantom was filled with saline solution of electrical conductivity 0.21 S m-1. A multichannel cardiomagnetometer was employed to record the magnetic fields generated by seven dipolar sources at distances from 25 mm to 145 mm below the surface of the phantom. The inverse problem was solved using an equivalent current dipole in a homogeneous boundary element torso model. The dipole parameters were determined with a non-linear least squares fitting algorithm. The signal-to-noise ratio (SNR) and the goodness of fit of the calculated localisations were used in assessing the quality of the results. The dependence between the SNR and the goodness of fit was derived, and the results were found to correspond to the model. With SNR between 5 and 10, the average localisation error was found to be 9 +/- 8 mm, while for SNR between 30 and 40 and goodness of fit between 99.5% and 100%, the average error reduced to 3.2 +/- 0.3 mm. The SNR values obtained in this study were also compared with typical clinical values of SNR.

A computer simulation study of the biomagnetic forward and inverse problem was performed. A realistically shaped, multicompartment boundary element model of the human thorax was used to reconstruct dipolar and extended current sources. The numerical results were proved using magnetic field measurements taken from a physical thorax phantom. A new technique of modelling extended sources was developed which enables the authors to validate the accuracy of inverse methods for source reconstruction. The same technique used for source modelling can be applied to model the thorax inhomogeneities too.