Hardware Design for Magnetic Induction Tomography Imaging System in Biomedical Application

2017 ◽  
Vol 7 (1) ◽  
pp. 88-93
Author(s):  
Dan Yang ◽  
Chengan Liu ◽  
Bin Xu ◽  
Xu Wang
Keyword(s):  
Magnetic Induction ◽  
Imaging System ◽  
Biomedical Application ◽  
Hardware Design ◽  
Tomography Imaging ◽  
Magnetic Induction Tomography

Initial Development On Magnetic Induction Tomography Imaging

2012 ◽  
Author(s):  
Nor Muzakkir Nor Ayob ◽  
Zulkarnay Zakaria ◽  
Mohd Hafiz Fazalul Rahiman ◽  
Ruzairi Abdul Rahim ◽  
Sazali Yaacob
Keyword(s):  
Magnetic Induction ◽  
Acceptable Result ◽  
Initial Development ◽  
Tomographic Images ◽  
Tomography Imaging ◽  
Tomographic Method ◽  
Imaging Research ◽  
Sensitivity Map ◽  
Imaging Instrument ◽  
Magnetic Induction Tomography

Sistem pengimejan yang tidak intrusif telah banyak menarik perhatian di dalam banyak aplikasi seperti pemprosesan, industri dan perubatan. Teknik elektrikal khususnya, terbukti menjadi instrumen pengimejan berkos rendah dengan kemampuan resolusi rendah tetapi memadai untuk pengimejan pemprosesan. Tomografi Induktansi Magnetik (TIM) adalah kaedah tomografi elektrikal berdasarkan penggunaan bacaan induktansi untuk memantau distribusi bahan konduksi elektrik dan magnetik dalam kawasan pemerhatian. Karya penyelidikan ini adalah berdasarkan pembangunan perisian untuk kegunaan pengimejan tomografi induktansi magnetik. Hasil penyelidikan tertumpu untuk menghasilkan peta sensitiviti yang diperlukan untuk rekonstruksi semula imej tomografi dari taburan elektromagnetik. Keputusan awal mengenai kajian simulatif telah menunjukkan hasil yang positif iaitu peta sensitiviti yang dihasilkan adalah bersesuaian untuk digunakan dalam pengimejan konduktiviti elektrik. Kata kunci: Tomografi induktansi magnetik; pengimejan tidak-intrusif; induktansi; peta sensitiviti Non–intrusive imaging systems have always been of much interest for use in many applications such as process, industrial and medical. Electrical techniques, in particular, are proving to be an inexpensive imaging instrument with low but sufficient resolution capability on imaging the internal distributions processes. Magnetic Induction Tomography (MIT) is an electrical tomographic method based on the use of inductance measurement for monitoring the distribution of electrically conductive and magnetically permeable material within the sensing area. This paper details the fundamental investigation of the software development for magnetic induction tomography imaging. Research works are concentrated on generating the sensitivity maps needed to reconstruct tomographic images of the electromagnetic distribution. Initial results on the simulative studies have shown acceptable result for using the generated sensitivity map for imaging electrical conductivities. Key words: Magnetic induction tomography; non-intrusive imaging; inductance; sensitivity map

scholarly journals Magnetic Induction Tomography Spectroscopy for Structural and Functional Characterization in Metallic Materials

Materials ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2639 ◽  
Author(s):  
Imamul Muttakin ◽  
Manuchehr Soleimani
Keyword(s):  
Magnetic Induction ◽  
Imaging System ◽  
Functional Characterization ◽  
Thermal Conditions ◽  
Reconstruction Algorithm ◽  
Rate Of Change ◽  
Variation Method ◽  
Metallic Materials ◽  
Functional Information ◽  
Magnetic Induction Tomography

Magnetic induction tomography (MIT) is a powerful imaging system for monitoring the state of metallic materials. Tomographic methods enable automatic inspection of metallic samples making use of multi-sensor measurements and data processing of eddy current-based sensing from mutual inductances. This paper investigates a multi-frequency MIT using both amplitude and phase data. The image reconstruction algorithm is based on a novel spectrally-correlative total variation method allowing an efficient and all-in-one spectral reconstruction. Additionally, the paper shows the rate of change in spectral images with respect to the excitation frequencies. Using both spectral maps and their spectral derivative maps, one can derive key structural and functional information regarding the material under test. This includes their type, size, number, existence of voids and cracks. Spectral maps can also give functional information, such as mechanical strains and their thermal conditions and composition.

scholarly journals Magnetic Induction Tomography: Receiver Circuit and Its Design Criteria

2013 ◽  
Vol 64 (5) ◽  
Author(s):  
Zulkarnay Zakaria ◽  
Muhammad Saiful Badri Mansor ◽  
Ruzairi Abdul Rahim ◽  
Ibrahim Balkhis ◽  
Mohd Hafiz Fazalul Rahiman ◽  
...  
Keyword(s):  
Magnetic Induction ◽  
Imaging System ◽  
Frame Rate ◽  
Projection Algorithm ◽  
Industrial Processes ◽  
System Component ◽  
High Quality ◽  
Tomography System ◽  
Component Selection ◽  
Magnetic Induction Tomography

This paper discusses the receiver circuit and criteria for component selection towards the application of a real-time magnetic induction tomography system. Component selection plays an important role since image reconstruction of the object of interest with high quality and at a higher frame rate cannot be achieved without the right parameter criteria. The demands for a high quality imaging system have recently been increasing, especially in industrial processes involving dynamic movement, thus this paper may provide valuable information on better magnetic induction tomography system implementation for industrial processes and biomedical imaging through the use of a coil as a transmitter and also a receiver. The linear back projection algorithm has been employed in this system and has proven capable of identifying the location and size of the object based on the reconstructed images.

Inspection of defects in CFRP by improved magnetic induction tomography

2019 ◽  
Vol 61 (3) ◽  
pp. 255-259
Author(s):  
Lipan Zhang ◽  
Qifeng Meng ◽  
Kai Song ◽  
Ming Gao ◽  
Zhiyuan Cheng
Keyword(s):  
Magnetic Induction ◽  
Magnetic Induction Tomography

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.

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