Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography

Abstract

We localize dynamic electrical conductivity changes and reconstruct their time evolution introducing the spatial filtering technique to electrical impedance tomography (EIT). More precisely, we use the unit-noise-gain constrained variation of the distortionless-response linearly constrained minimum variance spatial filter. We address the effects of interference and the use of zero gain constraints. The approach is successfully tested in simulated and real tank phantoms. We compute the position error and resolution to compare the localization performance of the proposed method with the one-step Gauss-Newton reconstruction with Laplacian prior. We also study the effects of sensor position errors. Our results show that EIT spatial filtering is useful for localizing conductivity changes of relatively small size and for estimating their time-courses. Some potential dynamic EIT applications such as acute ischemic stroke detection and neuronal activity localization may benefit from the higher resolution of spatial filters as compared to conventional tomographic reconstruction algorithms.

Narrowband array processing beamforming technique for electrical impedance tomography

“…While beamforming techniques are qualitative and are free from the inverse problems. Therefore, beamforming techniques can be used to solve the inverse problems [10]. However, we have considered the inverse problem more likely as a source localization algorithm instead of as an image reconstruction algorithm.…”

“…Prior computed tomographic (CT) images were used as a reference set in order to identify the regions of interest (ROI) of the object. Then, the impedance change was studied at different excitation frequencies (spectroscopy) [10]. Finally, beamforming technique was introduced to the EIT systems in order to study the conductivity changes.…”

MUSIC-Like Algorithm for Source Localization in Electrical Impedance Tomography

“…The MUSIC algorithm was also successfully applied for solving breast tumor detection and localization problem under quasi-static environment [14]. The LCMV algorithm was proposed for localizing conductivity changes in human head [15] which was later extended to an experimental study in a phantom tank [16].…”

Robust support identification for direction-of-arrival estimation and EIT application

“…The principle behind a calculation of steering vector/array response for EIT application can be considered as an estimation of array response based on small conductivity variation at each pixel/voxel. The steering vector n [54] a(ξ i ) ∈ R M ×1 used to construct the array manifold was estimated by an expected potential variation receiving on the array electrodes due to a variation at pixel ξ ith .…”

“…The MUSIC algorithm was also successfully adopted and used for solving target detection and localization problem of breast tumor under quasi-static environment [17]. The LCMV algorithm, a variation of MVDR algorithm, was also proposed for determining the area of conductivity changes in human head [53], where the simulation study was later expanded to an experimental study with phantom tank [54].…”