Stomach electrical impedance tomography method based on adaptive genetic algorithm
A technology of electrical impedance tomography and genetic algorithm, which is applied in the generation, diagnosis, and calculation of 2D images, and can solve problems such as slow convergence speed, pathological nonlinear inverse of electrical impedance tomography, and many iterations
Pending Publication Date: 2022-07-15
GUILIN UNIV OF ELECTRONIC TECH
View PDF0 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0003] The purpose of the present invention is to provide a gastric electrical impedance tomography method of an adaptive genetic algorithm, which is used to solve the problem that the traditional genetic algorithm has many iterations and slow convergence speed; the ill-conditioned nonlinear inverse problem of electrical impedance tomography; the traditional genetic algorithm The algorithm is easy to get stuck in the problem of local optimal solution
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0029] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and examples.
[0030] The invention provides a gastric electrical impedance tomography imaging method based on an adaptive genetic algorithm. The algorithm flow is as follows figure 1 shown. First establish a two-dimensional model of the stomach, then set the coding and population parameters, and then calculate the fitness function f, perform the selection operator, adaptive crossover operator, and mutation operator of the stomach EIT genetic algorithm, and implement the elite retention strategy , to decode and calculate the positive problem, and finally reconstruct the stomach EIT image based on the iterative results. The invention improves the convergence speed and global search ability of the traditional genetic algorithm.
[0031] S101 Bui...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention discloses a stomach electrical impedance tomography method based on a self-adaptive genetic algorithm, and the method comprises the steps: building a stomach two-dimensional model, and designing the coding and group parameters of the genetic algorithm; designing a fitness function f of the genetic algorithm, selecting operator operation, adaptive crossover operator operation and mutation operator operation, and implementing an elitism strategy; decoding and calculating a positive problem; and finally, reconstructing a stomach electrical impedance image according to an iteration result. The method has the advantages of high search efficiency and higher global convergence speed; compared with a traditional genetic algorithm, the search speed and the imaging quality are improved.
Description
technical field [0001] The invention relates to the field of electrical impedance tomography, in particular to a gastric electrical impedance tomography imaging method based on an adaptive genetic algorithm. Background technique [0002] Electrical Impedance Tomography (Electrical Impedance Tomography, EIT) is a functional imaging technology. According to the different imaging targets, EIT can be divided into dynamic EIT and static EIT. Dynamic EIT is to image the variation of impedance distribution under different conditions; static EIT is to image the absolute value of impedance distribution. Dynamic imaging can suppress its common noise in the measurement process and is relatively simple to implement; static imaging is more susceptible to reconstruction model errors and measurement noise, and its implementation is more difficult than dynamic EIT. This paper mainly studies static EIT image reconstruction. EIT image reconstruction is a serious ill-conditioned nonlinear in...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More IPC IPC(8): G06T11/00G06N3/12A61B5/0536A61B5/00
CPCG06T11/005G06N3/126A61B5/0536A61B5/004A61B5/0073
Inventor 汪杰君李龙许川佩莫宜坚赵汝文董庆贺
Owner GUILIN UNIV OF ELECTRONIC TECH