Electrical impedance imaging method based on tissue space distribution characteristics and frequency-dependent impedance characteristics

Abstract

The invention discloses an electrical impedance imaging method based on tissue space distribution characteristics and frequency-dependent impedance characteristics. The method comprises the followingsteps: constructing frequency difference EIT positive problem mathematical description by utilizing boundary measurement voltages of multiple different frequencies at the same moment; solving a frequency difference EIT inverse problem by adopting a one-step linear Gaussian Newton method to obtain a frequency difference EIT sequence image; according to the spatial independent distribution characteristics of the tissues in the imaging area, extracting the electrical impedance images of different types of tissues at one moment and the change characteristics of the electrical impedance along withthe frequency from the frequency difference EIT sequence image by adopting a high-order statistical magnitude signal extraction method; repeating the operation, respectively reconstructing N target tissues with representative positions and sizes, and constructing an electrical impedance identification model of the target tissues by taking the obtained electrical impedance change characteristics ofthe N target tissues along with the frequency as a training set by adopting a machine learning method. According to the method, the electrical impedance distribution image of the selected target in the measured body at one moment can be reconstructed according to the data of multiple frequencies.

Description

technical field [0001] The invention belongs to the field of electrical impedance imaging, and relates to an electrical impedance imaging method, in particular to an electrical impedance imaging method based on tissue spatial distribution characteristics and impedance variation characteristics with frequency. Background technique [0002] Electrical impedance tomography (EIT) is an imaging method developed in recent years. It secures the electrodes on the surface of the measured body, and regularly applies current excitation to the measured target, while sequentially measuring the voltage on the electrodes. , and finally use the measured voltage to reconstruct the impedance or impedance change distribution inside the measured body. According to the imaging method, EIT is divided into static imaging, time difference imaging and frequency difference imaging. Static imaging uses the voltage data at a certain moment to reconstruct the impedance distribution in the measured body...

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Problems solved by technology

Dynamic imaging uses the differential results of voltage data at two different times to reconstruct the distribution of impedance changes over time in the measured body. Because it can reduce the influence of system errors such as noise through differential methods, it has strong practicability and has been widely used at present; However, according to the imaging principle, dynamic imaging cannot reconstruct the electrical impedance distribution inside the measured body at a certain moment, and cannot meet the actual needs of obtaining the electrical impedance distribution of the target tissue inside the measured body at a certain moment.

Frequency difference imaging uses the voltage difference results of multiple frequencies at the same time to reconstruct the impedance distribution inside the measured body. image, and the inability to obtain the electrical impedance distribution of the target tissue inside the measured body has become a bottleneck restricting the practical application of frequency difference imaging

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