Detecting oesophageal-related changes using electrical impedance tomography

Propagation of measurement noise through backprojection reconstruction in electrical impedance tomography

A framework to analyze the propagation of measurement noise through backprojection reconstruction algorithms in electrical impedance tomography (EIT) is presented. Two measurement noise sources were considered: noise in the current drivers and in the voltage detectors. The influence of the acquisition system architecture (serial/semi-parallel) is also discussed. Three variants of backprojection reconstruction are studied: basic (unweighted), weighted and exponential backprojection. The results of error propagation theory have been compared with those obtained from simulated and experimental data. This comparison shows that the approach provides a good estimate of the reconstruction error variance. It is argued that the reconstruction error in EIT images obtained via backprojection can be approximately modeled as a spatially nonstationary Gaussian distribution. This methodology allows us to develop a spatial characterization of the reconstruction error in EIT images.

Subsurface electrical impedance imaging: measurement strategy, image reconstruction and in vivo results

In conventional cross-sectional electrical impedance tomography, most of the spatial information is concentrated at the periphery of the image, close to the measurement electrodes. Increasing the number of electrodes tends not to increase the poor resolution at the centre of the cross-sectional image due to the physics of three-dimensional current flow. In this work an alternative approach. INSEIT (imaging near the surface by electrical impedance tomography), is explored in which the image plane lies at a selected depth in the object parallel to a surface electrode array. This approach has been investigated using a prototype data measurement system. The preliminary in vivo results include subsurface images of respiration, the gastro-intestinal tract and limb blood flow.

Data processing techniques for serial EIT spectroscopy images: a review of some preliminary results

Mutlifrequency EIT imaging should allow specific organs within the body to be identified by their impedance spectrum, and the use of parametric imaging should lead to a much greater freedom from movement artefacts. This will make EIT more attractive as a monitoring technique, but the data rate will require automated processing of the images. The application of dynamic regions of interest, generated on a frame by frame basis, is described, with examples from the imaging of neonatal lungs and adult stomach. The lung can be objectively identified on a single frame from the fRSC, SC and RC images, but the stomach could only be identified on the dynamic images.