Exploring Respiratory Motion Tracking Through Electrical Impedance Tomography

Abstract

Motion tracking is an effective approach for the management of respiratory motion during the medical imaging process, which has always been a major concern in diagnostic imaging, interventional, and non-invasive therapy. However, the low imaging speed of traditional medical imaging techniques limits the practical application of real-time motion tracking. Electrical impedance tomography (EIT) is proved to be an effective tool for continuous monitoring of lung activity/status. However, the respiratory motion has never been studied in the medical EIT field before. In this paper, preliminary research of lung movement during the respiratory process is first studied based on EIT. Multi-ring electrode thorax models under different respiratory statuses were constructed to obtain simulation data of EIT. A modified TV algorithm is used for the estimation of lung volume and movement based on 3D EIT images, which improve the quality of reconstruction by approximately 30% and 20% compared with the traditional Tikhonov method and the total variation (TV) method, respectively. Both simulations and experiments were conducted to show the potential of respiratory motion tracking through 3D EIT reconstruction.

Advances in Electrical Impedance Tomography Inverse Problem Solution Methods: From Traditional Regularization to Deep Learning

“…The TV optimization problem defined by ( 25) and ( 32) can be solved using several techniques, such as the primal-dual interior point method (PD-IPM) [23]- [25], the alternating direction method of multipliers (ADMM) [25], [32] and the split-Bregman distance method [33]- [35], [132]- [134]. Since the problem is non-linear, these techniques require iterative procedures without the existence of a closed-form solution.…”

3-D Electrical Impedance Imaging of Lung Injury

“…To obtain the 3D reconstruction result, the images could be reconstructed onto multiple voxel layers perpendicular to the z-axis with the measurements from the single-ring electrode plane [33]. Considering the memory limits and speed requirements, there are 45 reconstruction layers in the 3D reconstructed image, and each layer has a resolution of 32 × 32.…”

“…The Structural Similarity Index Measurement (SSIM) is used to calculate the similarity between the true model and the reconstructed image [33]:…”

Electrical Tomography Hardware Systems for Real-Time Applications: a Review

“…Nevertheless, the reconstruction algorithm was also executed on a sequential PC-based platform. In a similar work on respiratory motion tracking in [74], authors used mesh elements with 111 layers of 32x32 resolution each. The reconstruction was carried out using modified TV (MTV) and compared with the TV and traditional Tikhonov method, which showed an improvement in the image quality by 20% and 30% respectively in terms of lung regional ratio (LRR) defined as,…”