Pulmonary perfusion and ventricular ejection imaging by frequency domain filtering of EIT (electrical impedance tomography) images.

While EIT images can produce clinically useful qualitative information, the extraction of quantitative data is essential in clinical monitoring. In the case of imaging of the thorax the parameters available relate to cardiac activity and pulmonary perfusion. Imaging the relatively small changes in the resistivity of the lungs due to pulmonary perfusion in the presence of noise and the larger ventilation component is difficult.

The spectral expansion of a head model in electrical impedance tomography.

This paper examines whether electrical impedance tomography (EIT) can provide information of use to magneto-encephalographic modelling (MEG). The EIT image domain is expanded in a complete set of orthogonal basis images, the number of which is given by the number of independent measurements (104 for 16 electrodes). They are ordered according to their sensitivity to data noise, with more centrally located features and higher spatial frequency components appearing towards the higher terms in the series, in the case of uniform resistivity distribution.

A transputer implemented algorithm for electrical impedance tomography.

Electrical impedance tomography (EIT) offers a non-invasive technique of great scope for producing clinically important information in a number of medical applications. Initial work by Brown used an isopotential approach to solving the complex backprojection problem. In this study a less restrictive algorithm for EIT has been developed based on the work of Yorkey and of Kaczmarz.