Biomedical applications of electrical impedance tomography

Abstract

The papers on electrical impedance tomography (EIT) in this issue arise, as in last year's special issue, from a conference on Biomedical Applications of EIT held in London in April 2000. This was the second annual conference, organized as part of an Engineering and Physical Sciences Research Council 'engineering network' on biomedical EIT. The conference was attended by about 60 people, representing almost all of the groups in the world who actively work in this area. There were talks in all the traditional areas of reconstruction algorithms, hardware and clinical applications, but the field is clearly changing as there were two additional sections, magnetic induction tomography and EIT of brain activity, each with seven papers from four groups. Another new trend was a contribution from a company, showing their novel system for impedance scanning of breast cancer. New advances from all these areas are represented in the twenty-one EIT papers in this issue. The principal goals of the engineering network, and resulting conferences, are to enable transfer of ideas between groups and enhance collaboration. On both these counts, I think the conference was successful. There was clearly cross-fertilization of ideas between the conference delegates. In the final discussion, three interest groups were established in EIT of the breast, chest function and neonatal lung function. These groups have agreed to co-ordinate their activity, and so I hope this will further the need of our field as a whole to produce clinically convincing results. Another important outcome is the collaboration to produce EIDORS - electrical impedance and diffuse optical reconstruction software. This will be a library of reconstruction routines, written in the widely used MATLAB language. It will be freely available and will be of substantial advantage for anyone in the field who wishes to adapt or extend their reconstruction algorithms. One of the papers in this issue describes this software development. Finally, I would like to thank Professor Nick Avis, Salford University, who kindly acted as editor for manuscripts in the special issue submitted by my own research group, and Bill Lionheart, UMIST, who organized a workshop on reconstruction algorithms early last year and is the driving force behind EIDORS.