Sensitivity maps in three-dimensional magnetic induction tomography

2006 ◽  
Vol 48 (1) ◽  
pp. 39-44 ◽  
Author(s):  
M Soleimani
Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1306
Author(s):  
Martin Klein ◽  
Daniel Erni ◽  
Dirk Rueter

Magnetic induction tomography (MIT) is a contactless technique that is used to image the distribution of passive electromagnetic properties inside a voluminous body. However, the central area sensitivity (CAS) of this method is critically weak and blurred for a low conductive volume. This article analyzes this challenging issue, which inhibits even faint imaging of the central interior region of a body, and it suggests a remedy. The problem is expounded via two-dimensional (2D) and three-dimensional (3D) eddy current simulations with different transmitter geometries. On this basis, it is shown that a spatially undulating exciter coil can significantly improve the CAS by >20 dB. Consequently, the central region inside a low conductive voluminous object becomes clearly detectable above the noise floor, a fact which is also confirmed by practical measurements. The improved sensitivity map of the new arrangement is compared with maps of more typical circular MIT geometries. In conclusion, 3D MIT reconstructions are presented, and for the same incidence of noise, their performance is much better with the suggested improvement than that with a circular setup.


2015 ◽  
Vol 77 (17) ◽  
Author(s):  
Zulkarnay Zakaria ◽  
Hafizi Suki ◽  
Masturah Tunnur Mohamad Talib ◽  
Ibrahim Balkhis ◽  
Maliki Ibrahim ◽  
...  

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.


Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7725
Author(s):  
Martin Klein ◽  
Daniel Erni ◽  
Dirk Rueter

Magnetic induction tomography (MIT) is a contactless, low-energy method used to visualize the conductivity distribution inside a body under examination. A particularly demanding task is the three-dimensional (3D) imaging of voluminous bodies in the biomedical impedance regime. While successful MIT simulations have been reported for this regime, practical demonstration over the entire depth of weakly conductive bodies is technically difficult and has not yet been reported, particularly in terms of more realistic requirements. Poor sensitivity in the central regions critically affects the measurements. However, a recently simulated MIT scanner with a sinusoidal excitation field topology promises improved sensitivity (>20 dB) from the interior. On this basis, a large and fast 3D MIT scanner was practically realized in this study. Close agreement between theoretical forward calculations and experimental measurements underline the technical performance of the sensor system, and the previously only simulated progress is hereby confirmed. This allows 3D reconstructions from practical measurements to be presented over the entire depth of a voluminous body phantom with tissue-like conductivity and dimensions similar to a human torso. This feasibility demonstration takes MIT a step further toward the quick 3D mapping of a low conductive and voluminous object, for example, for rapid, harmless and contactless thorax or lung diagnostics.


2002 ◽  
Vol 23 (1) ◽  
pp. 195-202 ◽  
Author(s):  
Hermann Scharfetter ◽  
Pere Riu ◽  
Marcos Populo ◽  
Javier Rosell

2004 ◽  
Vol 25 (1) ◽  
pp. 325-333 ◽  
Author(s):  
Hermann Scharfetter ◽  
Stephan Rauchenzauner ◽  
Robert Merwa ◽  
O Biró ◽  
Karl Hollaus

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

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