Abstract
The objective of the study was to develop an optimized method for dynamic electrical impedance tomography (EIT) to image large area conductive perturbation (LACP), a new type of imaging target that we found during the monitoring and evaluation of the mannitol dehydration treatment of patients with brain edema based on brain EIT. Previously, we reconstructed LACP images with the commonly used NOSER algorithm with polar driven pattern. However, conductivity changes near the center of the LACP were blurred or remained undetected, and blocky artifacts appeared in the reconstructed images, making the interpretation of the results difficult. To solve this problem, we, for the first time, propose an optimized algorithm for imaging LACP. This algorithm comprises a modified sensitivity matrix to compensate for the blurred conductivity changes near the center. It also uses the Markov random field constraint to reduce blocky artifacts. To verify the performance of the proposed method, we conducted experiments based on head models and human subjects. Specific metrics, including shape error (SE) and image fluctuation (IF) artifacts, were also proposed to evaluate the image quality of the LACP. The experimental results demonstrated that, compared with the NOSER algorithm, the proposed method could respectively reduce SE and IF by 51.7% and 47.5%. Therefore, it can optimize the imaging of LACP and provide references for other applications at present or in the future which involve imaging LACP.
Highlights
Electrical impedance tomography (EIT) is a non-invasive and radiation free method that can continuously image the conductivity distribution within the human body [1]
We started EIT monitoring after the administer of mannitol and the results demonstrated that during the treatment, dynamic brain EIT could individually evaluate the efficacy of the treatment and noninvasively reflect intracranial pressure (ICP), a vital physiological parameter that could indirectly indicate the evolution of brain edema [5]
OPTIMIZED METHOD FOR IMAGING large area conductive perturbation (LACP) we propose an optimized algorithm with a modified sensitivity matrix and Markov constraint for imaging LACP
Summary
Electrical impedance tomography (EIT) is a non-invasive and radiation free method that can continuously image the conductivity distribution within the human body [1]. In EIT, safe currents are applied with electrodes on the surface of the body based on a predefined protocol. The resulting boundary voltages are measured and used for image reconstruction. Biomedical fields began to have use for EIT in the late 1970s and it was first applied to imaging the lung [2]. Other biomedical applications including monitoring gastric emptying, detecting breast cancer, imaging brain function, and analyzing cell growth emerged [3].
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