A Point Constrained Boundary Reconstruction Framework for Ultrasound Guided Electrical Impedance Tomography

Abstract

As a non-invasive and radiation-free imaging modality, electrical impedance tomography (EIT) has attracted much attention in the field of industrial measurement. However, image reconstruction with EIT is a non-linear and ill-posed inverse problem, causing it to suffer from low spatial resolution and high noise sensitivity. To overcome this problem, a point-constrained framework is proposed to guide inclusion boundary reconstruction in EIT with ultrasound point detection. The boundary reconstruction problem is formulized with an energy minimization approach. The energy function consists of the residual, point constraint, geometric and re-parameterisation terms. The residual term fits the actual EIT data by adjusting the inclusion shape and conductivity with a computable forward model. The point constraint term drags the estimated boundary toward the ultrasound detected ‘at-boundary’ points and pushes it away from the ultrasound detected ‘outside-inclusion’ points. The geometric and re-parameterisation terms regularize the boundary reconstruction problem and diffuse the point constraint energy along the inclusion boundary. According to the numerical results, the proposed method is robust to measurement noise, as well as the super parameter and initial boundary guess issues. An experimental phantom study with a water tank model further proved that the dual-modality shape reconstruction method outperforms the single-modality shape reconstruction method in both single-phase and multiphase conductivity cases.