![]() |
Computational & Technology Resources
an online resource for computational,
engineering & technology publications |
Civil-Comp Proceedings
ISSN 1759-3433 CCP: 79
PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY Edited by: B.H.V. Topping and C.A. Mota Soares
Paper 96
An Improved Implementation of the Topology Optimization Method Applied to Electrical Impedance Tomography Imaging C.R. Lima and E.C.N. Silva
Department of Mechatronic and Mechanical Systems Engineering, University of São Paulo, Brazil Full Bibliographic Reference for this paper
C.R. Lima, E.C.N. Silva, "An Improved Implementation of the Topology Optimization Method Applied to Electrical Impedance Tomography Imaging", in B.H.V. Topping, C.A. Mota Soares, (Editors), "Proceedings of the Seventh International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 96, 2004. doi:10.4203/ccp.79.96
Keywords: topology optimization, electrical impedance tomography.
Summary
Electrical Impedance Tomography (EIT) is a recent monitoring technique that
allows us to obtain images of a transversal plane in any section of human body. In
this technique, images are related to the corresponding value of electrical
conductivity inside of human body section. Images are generated from voltage
values which are obtained by applying a sequence of low amplitude electrical
currents on electrodes positioned around of a transversal section of human body.
The EIT is based on an inverse problem, in which given the electrical potentials
measured on electrodes, this technique tries to find the conductivity distribution
inside a transversal section of the body. Technology of EIT is safer and cheaper than
other tomography techniques and although it has poor resolution, it has good
potential for clinical applications [1]. Moreover, an EIT device is short and portable,
which allows its installation close to a bedridden patient. In addition, the patient is
not exposed to any type of radiation in EIT.
In this work, a technique called the Topology Optimization Method (TOM) is applied to image reconstruction using the EIT. The TOM is an iterative method that finds systematically a material distribution inside of a design domain, satisfying an objective function requirement and specified constraints [2]. The problem of applying the topology optimization method to obtain an image of body section consists of finding a material distribution (related to conductivity distribution) in the body section domain that minimizes the difference between electrical potential measured on electrodes and electrical potential calculated by using a computational model. In TOM, the design domain (section of body) is divided in a finite number of elements, where each element can vary from a specified material to another material in a continuous way, according a material model called Density Method [2]. In addition, an electrode model, proposed by Hua [3], has been implemented to represent the contact impedance of interface electrode-skin. The solution of the topology optimization problem is obtained through an iterative computational algorithm that combines the Finite Element Method (FEM) and an optimization algorithm called Sequential Linear Programming (SLP). The SLP solves a non-linear optimization problem considering it as a sequence of linear sub-problems, which can be solved with Linear Programming. Furthermore, the SLP uses gradients of objective function and constraints, related to design variables, for obtaining the linear sub-problems. Mathematical formulation of these gradients can be obtained analytically by using the adjoint method [4].
The optimization algorithm that applies the TOM to obtain image in EIT is
implemented in software, which is programmed using C language. This software
was applied to image reconstruction of some 2D examples using numerical and
experimental data. In this work, 32 electrode elements are uniformly positioned
along the boundary of the design domain and their electrode parameter
( The computational algorithm of the TOM, which is studied in this work, could be seized for obtaining images of the lungs through an EIT device. Applied to EIT image reconstruction, the TOM allows us to include some constraints in the problem of image reconstruction limiting the solution space during tomography examination and avoiding images without clinical meaning. Moreover, it allows us to work with known areas inside of the body section (bone, heart, etc).
References
purchase the full-text of this paper (price £20)
go to the previous paper |
|