CompanyName: Thayer School of Engineering
Abstract: Incorporating electrode
models in electrical impedance tomography: Modeling
and image reconstruction using in-vivo breast data
Nirmal K. Soni, Hamid Dehghani, Alex Hartov and Keith D. Paulsen
Thayer School of Engineering, Dartmouth College, Hanover NH 03755, USA
Nirmal.K.firstname.lastname@example.org, Hamid.Dehghani@Dartmouth.EDU, Alexander.Hartov@Dartmouth.EDU, Keith.D.Paulsen@Dartmouth.EDU
Electrical Impedance Tomography (EIT)
is a novel non-invasive technique for imaging breasts, which aims to identify
and characterize tumor within otherwise normal tissue. In EIT the electrical
properties of biological tissues are determined from boundary measurements of
voltages and currents. The image reconstruction algorithm uses this set of boundary
data to derive internal electrical properties of the region under investigation.
Therefore correct and accurate modeling of the current and voltage distributions
within the volume under investigation (the forward model) is an essential part
of the image reconstruction algorithm. Electrode models have been accepted as
an essential part of accurate forward modeling, but few practical results have,
to date, been reported with images reconstructed from in-vivo data. In this
work, our approach in modeling in EIT, incorporating the electrode model is
discussed together with our latest version of the image reconstruction algorithm.
e will show the effects of discretization and contact impedance choices on the electrode model. We will also present the images from both phantom and in-vivo clinical data acquired during breast exams on patients.