Simulative Study of Two-Phase Homogenous and Isotropic Media Imaging using Magnetic Induction Tomography

2014 ◽  
Vol 69 (8) ◽  
Author(s):  
Zulkarnay Zakaria ◽  
Ibrahim Balkhis ◽  
Lee Pick Yern ◽  
Nor Muzakkir Nor Ayob ◽  
Mohd Hafiz Fazalul Rahiman ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Magnetic Induction ◽  
Optical Tomography ◽  
Reconstruction Algorithm ◽  
Projection Algorithm ◽  
Back Projection ◽  
Two Phase ◽  
Excitation Coil ◽  
Magnetic Induction Tomography ◽  
Linear Back Projection

Magnetic induction tomography is a new non-invasive technology, based on eddy current discovery of electromagnetic induction by Michael Faraday. Through this technique, the passive electrical properties distribution of an object can be obtained by the use of image reconstruction algorithm implemented in this system. There are many types of image reconstruction that have been developed for this modality, however in this paper only two algorithms discussed, Linear Back Projection and Eminent Pixel Reconstruction. Linear Back Projection algorithm is the most basic type of image reconstruction. It is the simplest and fast algorithm out of all types of algorithms, whereas Eminent Pixel Reconstruction algorithm is an improved algorithm which provided better images and has been implemented in other modalities such as optical tomography. This paper has implemented Eminent Pixel Reconstruction in magnetic induction tomography applications and the performance is compared to Linear Back Projection based on the simulation of the fourteen types of simulated phantoms of homogenous and isotropic conductivity property. It was found that Eminent Pixel Reconstruction has produced better images relative to Linear Back Projection, however the images are still poor when the objects are located near to the excitation coil or sensor and it is worse when the distance between objects are near to each other.

A Study on Forward and Inverse Problems for an Ultrasonic Tomography

2014 ◽  
Vol 70 (3) ◽  
Author(s):  
Mohd Hafiz Fazalul Rahiman ◽  
Ruzairi Abdul Rahim ◽  
Herlina Abdul Rahim ◽  
Zulkarnay Zakaria ◽  
Muhammad Jaysuman Pusppanathan
Keyword(s):  
Two Phase Flow ◽  
Reconstruction Algorithm ◽  
Projection Algorithm ◽  
Ultrasonic Tomography ◽  
Phase Flow ◽  
Back Projection ◽  
Two Phase ◽  
Tomographic Images ◽  
Linear Back Projection ◽  
Scanning Geometry

This paper studies the solution for inverse and forward problems for an ultrasonic tomography. Transmission-mode approach has been used for sensing the liquid/gas two-phase flow, which is a kind of strongly inhomogeneous medium. The imaging technique for two-phase flow using fan-shaped beam scanning geometry was presented. In this work, the tomographic images are derived from Back-Projection Algorithm. Some of the results based on the Linear Back-Projection algorithm (LBP) and the Hybrid Reconstruction algorithm (HR) was also presented.

An Improved Back-Projection Algorithm for Magnetic Induction Tomography Image Reconstruction

2013 ◽  
Vol 647 ◽  
pp. 630-635 ◽  
Author(s):  
Li Ke ◽  
Xiao Lin ◽  
Qiang Du
Keyword(s):  
Magnetic Field ◽  
Image Reconstruction ◽  
Magnetic Induction ◽  
Projection Algorithm ◽  
Projection Area ◽  
Homogeneous Field ◽  
Back Projection ◽  
Field Lines ◽  
Magnetic Induction Tomography ◽  
The Magnetic Field

Magnetic induction tomography (MIT) acted as a contactless and non-invasive medical imaging technology has aroused wide concern, while a large amount of calculation and a series of convergence problems in the solution of the inverse problem become technical difficulties for MIT. In order to solve these problems, an improved back-projection image reconstruction algorithm based on the magnetic field lines distribution is presented in this paper. Firstly, the eddy current problem of MIT was solved by the finite element method to obtain the magnetic field distribution. Secondly, the back-projection areas were divided according to the magnetic field lines distribution in the homogeneous field. Finally, image reconstruction was realized by projecting the phase shifts back along the corresponding projection area. The reconstruction results for perturbations with different conductivities appearing at different locations reveal that the improved back-projection algorithm for MIT owning the character of high speed performs well in reflecting location and shape information of the perturbation.

Image Reconstruction with the Fourier Coefficients for Magnetic Induction Tomography

2020 ◽  
Vol 16 (2) ◽  
pp. 156-163
Author(s):  
Jingwen Wang ◽  
Xu Wang ◽  
Dan Yang ◽  
Kaiyang Wang
Keyword(s):  
Inverse Problem ◽  
Image Reconstruction ◽  
Magnetic Induction ◽  
Fourier Coefficients ◽  
Signal Reconstruction ◽  
Reconstruction Algorithm ◽  
Reconstruction Method ◽  
Measurement Equation ◽  
Image Reconstruction Method ◽  
Magnetic Induction Tomography

Background: Image reconstruction of magnetic induction tomography (MIT) is a typical ill-posed inverse problem, which means that the measurements are always far from enough. Thus, MIT image reconstruction results using conventional algorithms such as linear back projection and Landweber often suffer from limitations such as low resolution and blurred edges. Methods: In this paper, based on the recent finite rate of innovation (FRI) framework, a novel image reconstruction method with MIT system is presented. Results: This is achieved through modeling and sampling the MIT signals in FRI framework, resulting in a few new measurements, namely, fourier coefficients. Because each new measurement contains all the pixel position and conductivity information of the dense phase medium, the illposed inverse problem can be improved, by rebuilding the MIT measurement equation with the measurement voltage and the new measurements. Finally, a sparsity-based signal reconstruction algorithm is presented to reconstruct the original MIT image signal, by solving this new measurement equation. Conclusion: Experiments show that the proposed method has better indicators such as image error and correlation coefficient. Therefore, it is a kind of MIT image reconstruction method with high accuracy.

Simulation Analysis of the Sensitivity in Magnetic Induction Tomography Based on Perturbation Theory

2013 ◽  
Vol 749 ◽  
pp. 371-376
Author(s):  
Yang Xuan ◽  
Xu Wang ◽  
Cheng An Liu ◽  
Dan Yang
Keyword(s):  
Perturbation Theory ◽  
Salt Solution ◽  
Magnetic Induction ◽  
Imaging Modality ◽  
Reconstruction Algorithm ◽  
Target Object ◽  
Back Projection ◽  
Filtered Back Projection ◽  
Projection Reconstruction ◽  
Magnetic Induction Tomography

Magnetic induction tomography (MIT) is a noninvasive and contactless imaging modality which aims at the reconstruction of the electrical conductivity in objects from alternating magnetic fields. Filtered back projection reconstruction algorithm is widely used in biomedical imaging field, and tried to use in MIT. Finite element analysis model has been established based on Scharfetter coil-coil model and perturbation theory, then simulated coaxial coil system by ANSYS software, the perturbation aroused by a target object moving on vertical coil axis. The sensitivity of a target object moves in vacuum and a salt solution were calculated respectively, the characteristics of the perturbation sensitivity in a salt solution were analyzed. The conditions of filtered back projection reconstruction algorithm in MIT were discussed.

Image Reconstruction Algorithms For Ultrasonic Tomography

2012 ◽  
Author(s):  
Mohd Hafiz Fazalul Rahiman ◽  
Ruzairi Abdul Rahim ◽  
Herlina Abdul Rahim
Keyword(s):  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Ultrasonic Tomography ◽  
Back Projection ◽  
Reconstruction Algorithms ◽  
Tomography System ◽  
Tomography Image ◽  
Real Objects ◽  
Linear Back Projection ◽  
Image Reconstruction Algorithms

Kertas ini membincangkan algoritma pembangunan imej bagi kegunaan dalam tomografi ultrasonik. Terdapat tiga jenis algoritma pembangunan iaitu Linear Back Projection, Hybrid Reconstruction dan Hybrid Binary Reconstruction. Algoritma tersebut telah diuji ke atas sistem tomografi ultrasonik berdasarkan kepada beberapa bayang yang telah dikenalpasti dan objek–objek sebenar. Prestasi algoritma tersebut telah di analisa dan bincangkan pada bahagian akhir kertas ini. Kata kunci: Algoritma pembangunan; tomografi ultrasonic; pemprosesan image; mabuk This paper presented image reconstruction algorithms for use in ultrasonic tomography. There are three types of reconstruction algorithms namely Linear Back Projection, Hybrid Reconstruction and Hybrid Binary Reconstruction. The algorithms have been evaluated on ultrasonic tomography system based on several known phantoms and real objects. The performance of the algorithms have been analysed and discussed at the end of the paper. Key words: Reconstruction algorithm; ultrasonic tomography; image processing

Dual Modality Tomography: The Image Analysis Of Forward Problem

2012 ◽  
Author(s):  
Rasif Mohd Zain ◽  
Ruzairi Abdul Rahim ◽  
Siti Zarina Mohd Muji
Keyword(s):  
Image Fusion ◽  
Iterative Reconstruction ◽  
Optical Tomography ◽  
Reconstruction Algorithm ◽  
Sensor Data ◽  
Back Projection ◽  
Electrical Capacitance ◽  
Dual Modality ◽  
Iterative Reconstruction Algorithm ◽  
Linear Back Projection

Kertas kerja ini mempersembahkan satu idea yang baru di dalam proses tomografi iaitu kombinasi di antara dua modaliti; electrical capacitance dan optikal tomografi untuk mengawasi pengukuran aliran pepejal/gas. Sistem Dual Modality Tomography (DMT) mengandungi lapan sensor capacitance elektrod dan 16 pasang sensor optikal di dalam satu lapis sensor. Data yang diambil dari kedua–dua sensor dipindahkan sesiri ke PC dengan kawalan dan dipicu oleh sistem perolehan data. Data yang didapati daripada kedua–dua sensor akan distrukturkan semula kepada imej menggunakan Linear Back Projection atau Iterative Reconstruction Algorithm. Di dalam projek ini, DMT akan menghasilkan cantuman imej, yang mana dibangunkan berdasarkan penyesuaian nilai pixel dan kawasan pengesanan pada penstrukturan semula imej pixel di antara sensor capacitance dan optikal tomografi. Senarai analisis kesilapan akan menentukan kebolehlaksanaan sensor DMT untuk menentusahkan ia sebagai instrumen bagi melihat aliran pepejal. Kata kunci: Electrical capacitance tomografi; optikal tomografi; dua mod tomografi; cantuman imej; algoritma penstrukturan semula The paper presents the novel idea in process tomography which is the combination of dual modality; electrical capacitance and optical tomography for monitoring solid/gas flow measurement. Dual Modality Tomography (DMT) system consists of eight electrodes of capacitance sensor and 16 pairs of optical sensor in one sensor plane. The data obtained from both sensors were inseries transfer to PC with control and triggered by data acquisition system. The data obtained from both sensors will then be reconstructed into image using Linear Back Projection or Iterative Reconstruction Algorithm. In this project, the DMT produces an image fusion, which is developed based on the adjustment of pixel values and the detection region of pixel images reconstruction between capacitance and optical tomography sensor. Series of error analyses will determine the feasibility of the DMT sensors to perform as an instrument in solid flow visualization. Key words: Electrical capacitance tomography; optical tomography; dual mode tomography; image fusion; reconstruction algorithm

SENSITIVITY MAPS RECONSTRUCTION FOR MAGNETIC INDUCTION TOMOGRAPHY MODALITY USING EXPERIMENTAL TECHNIQUE

2015 ◽  
Vol 77 (17) ◽  
Author(s):  
Zulkarnay Zakaria ◽  
Hafizi Suki ◽  
Masturah Tunnur Mohamad Talib ◽  
Ibrahim Balkhis ◽  
Maliki Ibrahim ◽  
...  
Keyword(s):  
Finite Element ◽  
Image Reconstruction ◽  
Experimental Technique ◽  
Magnetic Induction ◽  
Reconstruction Algorithm ◽  
Finite Element Technique ◽  
Image Reconstruction Algorithm ◽  
Magnetic Induction Tomography ◽  
Element Technique ◽  
Sensitivity Maps

Magnetic induction tomography (MIT) is a relatively new non-contacting technique for visualization of passive electrical property distribution inside a media. In any tomography system, the image is reconstructed using image reconstruction algorithm which requires sensitivity maps. There are three methods of acquiring sensitivity maps; finite element technique, analytically or experimentally. This research will focus on the experimentally method. Normally sensitivity map is generates using finite element technique that usually ignore certain parameters in real setup which in turn contribute to errors or blur in the reconstructed image. Thus experimental technique needs to be explored as an improvement as it is based on real parameters exists in the experimental setup. This paper starts with general view of magnetic induction tomography, image reconstruction algorithm and finally on the experimental technique of generating sensitivity maps.

scholarly journals Electrical capacitance tomography two-phase oil-gas pipe flow imaging by the linear back-projection algorithm

2005 ◽  
Vol 44 (3) ◽  
pp. 265-273
Author(s):  
J. C. Gamio ◽  
C. Ortíz-Alemán ◽  
R. Martin
Keyword(s):  
Pipe Flow ◽  
Projection Algorithm ◽  
Electrical Capacitance Tomography ◽  
Flow Imaging ◽  
Back Projection ◽  
Electrical Capacitance ◽  
Two Phase ◽  
Linear Back Projection ◽  
Capacitance Tomography ◽  
Oil Gas

La Tomografía de Capacitancia Eléctrica (TCE) es una nueva tecnología capaz de lidiar con la complejidad de la medición de flujos bifásicos de gas-aceite, derivando la distribución de componentes en dos planos adyacentes a lo largo de un ducto. Una de sus aplicaciones más prometedoras es la visualización de flujos de gas y aceite. TCE ofrece algunas ventajas sobre otras modalidades tomográficas: no hay radiación, una respuesta rápida, bajo costo, es una técnica no intrusiva y no invasiva, y la posibilidad de operar con altas temperaturas y altas presiones. El método denominado "linear back-projection (LBP)" es una de las técnicas más populares que se emplean en la reconstrucción de imágenes a partir de datos de tomografía de capacitancia eléctrica. A pesar de su pobre exactitud, es un procedimiento simple y rápido capaz de operar en tiempo real en muchas aplicaciones y ha permanecido como una opción muy popular. Sin embargo, desde que fue propuesto por vez primera ha carecido de un suporte formal, en el contexto de esta aplicación. Su única justificación radica en que es una adaptación de un método comúnmente empleado en la tomografía médica de rayos X, así como en el hecho de que produce imágenes útiles (aunque sólo "cualitativamente" buenas). En este trabajo se presenta una forma ilustrativa de interpretar el método LBP. Se muestra cómo el método LBP está basado en la linealización de una forma normalizada del problema directo. Más específicamente, el problema directo normalizado se aproxima mediante una serie de hiperplanos. La matriz de reconstrucción utilizada en el método LBP resulta ser una transpuesta "ponderada" del operador lineal (matriz) que define el problema directo normalizado. Los renglones de esta última matriz contienen la información de los mapas de sensitividades empleados en el método LBP.

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