Electrical impedance imaging method based on movable deformation component, device and system

Abstract

The invention provides an electrical impedance imaging method based on a movable deformation component, a device and a system. The electrical impedance imaging method first establishes a finite element electrode model for a target field and acquires a measured voltage value of each electrode corresponding to an object to-be-imaged; a plurality of movable deformation components are initially placed for each object to-be-imaged as an initial value of a Gauss-Newton iteration method, an iterative process is performed, a target conductivity distribution is obtained, and a target voltage value is calculated; and the reconstructed image is determined by iteratively solving the minimization of the preset loss function based on the Gauss-Newton method. The scheme is based on the movable deformation component for image reconstruction, and utilizes the flexibility control of the movable deformation component in structural topology optimization, and the resolution and imaging precision of the electrical impedance reconstruction image can be improved.

Description

technical field [0001] The present invention relates to the technical field of electrical impedance tomography, in particular to an electrical impedance imaging method, device and system based on a movable deformable component. Background technique [0002] Electrical Impedance Tomography (EIT) is a medical imaging technology. Its basic principle is that different tissues in the human body have different electrical impedances under different physiological and pathological conditions. By applying a small safe driving current to the human body (or voltage), and measure the response voltage (or current) signal in vitro to reconstruct the electrical impedance distribution or its change image inside the human body. Electrical impedance imaging technology is widely used in industrial, medical and other fields, such as lung function monitoring, breast cancer detection, brain activity imaging, etc. [0003] The electrical impedance reconstruction algorithm determines the quality of...

AI Technical Summary

Problems solved by technology

Although this algorithm can eliminate noise such as part of the measurement data in the case of subtraction of two sets of values, it cannot be imaged when the electrical impedance distribution has no change or little change at two moments, and the algorithm is difficult to be extended to three-dimensional space

However, the static impedance imaging algorithm has poor anti-noise performance, is sensitive to electrode installation and model design, and has defects such as low resolution and large imaging noise in the reconstructed image.

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