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Electrical impedance imaging method and device based on supervised descent method

An electrical impedance imaging and electrical impedance technology, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve the problems of slow image reconstruction, large amount of calculation, limited image reconstruction speed, etc., and achieve fast and good image reconstruction speed. The effect of noise immunity

Inactive Publication Date: 2020-04-24
BEIJING HUARUI BOSHI MEDICAL IMAGING TECH CO LTD
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Problems solved by technology

This greatly limits the range of prior information that can be selected
(2) The speed of image reconstruction is slow, which cannot meet the needs of some real-time monitoring applications
This process requires a lot of computation, which limits the speed of image reconstruction

Method used

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  • Electrical impedance imaging method and device based on supervised descent method
  • Electrical impedance imaging method and device based on supervised descent method
  • Electrical impedance imaging method and device based on supervised descent method

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Embodiment Construction

[0025] The drawings are for illustration only and should not be construed as limiting the invention. The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0026] Suppose the forward model of electrical impedance imaging (EIT) is s(σ), where σ is the conductivity distribution in the area to be imaged. The forward model reflects simulated boundary measurement data for a given excitation and conductivity distribution. Suppose the measured data of EIT is d. The EIT image reconstruction problem can be expressed as minimizing the following objective function:

[0027] C(σ)=||s(σ)-d|| 2 (1)

[0028] At the kth step of the iteration, we know the conductivity model σ of the k-1th step k-1 . The unknown conductivity distribution can be expressed as σ = σ k-1 +Δσ k . That is, introducing the difference Δσ k . Then the objective function (1) becomes:

[0029] C(σ k-1 +Δσ k )=||s(σ k...

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Abstract

The invention provides an electrical impedance imaging method and a device based on a supervised descent method. The electrical impedance imaging method (100) based on the supervised descent method comprises the following steps: obtaining a descent direction (110) for inverting new electrical impedance imaging measurement data through iteration based on electrical impedance distribution and electrical impedance imaging measurement data of a group of training samples; setting an initial model (120) of the electrical impedance distribution; and based on the initial model, the descending direction, an electrical impedance imaging forward model and actually measured electrical impedance imaging data, performing image reconstruction (130) of electrical impedance imaging through iteration. Compared with a traditional iterative method based on optimization, the image reconstruction method can flexibly introduce prior information in the inversion process. In addition, the image reconstructionmethod provided by the invention has good anti-noise performance and high image reconstruction speed.

Description

technical field [0001] The present invention relates to electrical impedance imaging technology, and more particularly to an electrical impedance imaging method and device based on a supervised descent method. Background technique [0002] Electrical impedance imaging (Electrical Impedance Tomography, EIT) is a non-invasive technology that aims at the electrical resistivity distribution inside the human body or other organisms to reconstruct tissue images in the body. The human body is a large bioelectrical conductor, and each tissue and organ has a certain impedance. When a local organ of the human body becomes diseased, the impedance of the local part must be different from that of other parts. Make a diagnosis. [0003] Traditional EIT image reconstruction methods are usually based on iterative optimization methods, such as the Gauss-Newton method. Such methods have the following disadvantages. (1) The accuracy of the reconstructed image is low, and it is easily affect...

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Application Information

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IPC IPC(8): A61B5/053
CPCA61B5/0536
Inventor 张可张昕王谊冰于洋
Owner BEIJING HUARUI BOSHI MEDICAL IMAGING TECH CO LTD
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