scholarly journals A Reconstruction Algorithm for Breast Cancer Imaging With Electrical Impedance Tomography in Mammography Geometry

2007 ◽  
Vol 54 (4) ◽  
pp. 700-710 ◽  
Author(s):  
Myoung Hwan Choi ◽  
Tzu-Jen Kao ◽  
David Isaacson ◽  
Gary J. Saulnier ◽  
Jonathan C. Newell
Keyword(s):  
Breast Cancer ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Cancer Imaging ◽  
Reconstruction Algorithm ◽  
Breast Cancer Imaging ◽  
Impedance Tomography

Patch-based sparse reconstruction for electrical impedance tomography

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 257-269 ◽  
Author(s):  
Qi Wang ◽  
Pengcheng Zhang ◽  
Jianming Wang ◽  
Qingliang Chen ◽  
Zhijie Lian ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Sparse Representation ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Inverse Operator ◽  
Reconstruction Algorithm ◽  
Impedance Tomography ◽  
Content Type ◽  
Ill Posed ◽  
High Level

Purpose Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise. Design/methodology/approach This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity. Findings Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages. Originality/value EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

Electrical impedance tomography in 3D flood embankments testing – elastic net approach

2019 ◽  
Vol 42 (4) ◽  
pp. 680-690
Author(s):  
Tomasz Rymarczyk ◽  
Edward Kozłowski ◽  
Grzegorz Kłosowski
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Visual Analysis ◽  
Measurement Techniques ◽  
Measurement Data ◽  
Reconstruction Algorithm ◽  
Elastic Net ◽  
Destructive Testing ◽  
Impedance Tomography ◽  
High Resolution Images

The article presents non-destructive testing based on electrical impedance tomography (EIT) for spatial (3D) monitoring of flood embankments. Therefore, to solve the inverse problem of the EIT, an effective algorithm based on multiple elastic nets has been developed. The originality of the solution is based on the application of many elastic net algorithms as functions, each of which, based on the vector of all measurements, generates the value of a single pixel for the reconstructed image. In this way, the set of elastic nets is equal to the resolution of the image output. Such an approach, although requiring more computing power, yields high resolution images. In addition, the presented algorithms are characterized by high noise immunity and distortion of measurement data. Five different electrode systems were tested in the samples and compared with each other in two measurement variants (stimulations). A reconstruction made on the basis of actual measurements obtained from the physical model was also presented. The presented solution provides a visual analysis of seepages and leaks, which allows for quick and effective intervention and possible prevention of dangers. The research proved that the use of tomographic measurement techniques in combination with the image reconstruction algorithm based on elastic net allows for non-invasive and very accurate spatial assessment of leaks and damages of flood embankments. The received results confirm the effectiveness of the presented research.

Sign in / Sign up

Export Citation Format

Share Document