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Rapid Estimation of Object Movements in Magnetic Induction Tomography. / Mamatjan, Yasin; Roula, Mohammed; Wubuli, Shabuerjiang.

In: International Journal of Biomedical Engineering and Technology, Vol. 27, No. 4, 179262, 08.2018, p. 290-302.

Research output: Contribution to journalArticlepeer-review

Harvard

Mamatjan, Y, Roula, M & Wubuli, S 2018, 'Rapid Estimation of Object Movements in Magnetic Induction Tomography', International Journal of Biomedical Engineering and Technology, vol. 27, no. 4, 179262, pp. 290-302. https://doi.org/10.1504/IJBET.2018.094297

APA

Mamatjan, Y., Roula, M., & Wubuli, S. (2018). Rapid Estimation of Object Movements in Magnetic Induction Tomography. International Journal of Biomedical Engineering and Technology, 27(4), 290-302. [179262]. https://doi.org/10.1504/IJBET.2018.094297

Vancouver

Mamatjan Y, Roula M, Wubuli S. Rapid Estimation of Object Movements in Magnetic Induction Tomography. International Journal of Biomedical Engineering and Technology. 2018 Aug;27(4):290-302. 179262. https://doi.org/10.1504/IJBET.2018.094297

Author

Mamatjan, Yasin ; Roula, Mohammed ; Wubuli, Shabuerjiang. / Rapid Estimation of Object Movements in Magnetic Induction Tomography. In: International Journal of Biomedical Engineering and Technology. 2018 ; Vol. 27, No. 4. pp. 290-302.

BibTeX

@article{4c014fb4f9d84f2e91830b0653b84b88,
title = "Rapid Estimation of Object Movements in Magnetic Induction Tomography",
abstract = "Magnetic induction tomography (MIT) is a contactless, inexpensive and non-invasive technique for imaging the conductivity distribution inside a body. A time-difference imaging can be used for monitoring the progression of stroke or oedema. However, MIT signals are more sensitive to body movements than the conductivity changes inside the body, because small movements during data acquisition can overwhelm the signals of interest and cause significant image artefacts. Thus, it is crucial to accurately estimate and compensate body movements for image reconstruction or alert clinicians to avoid misinterpretation. We propose frequency domain analysis and statistical approaches for identifying and estimating object movements from MIT data prior to the image reconstruction step. Results show that high amounts of movements totally distorted the images, whereas the proposed approaches produced good performance on elimination of image artefacts and its estimation while maintaining good computational efficiency for patient monitoring.",
keywords = "Magnetic induction tomography, movement estimation, movement compensation, Fast Fourier Transform (FFT), Independent Component Analysis (ICA) ",
author = "Yasin Mamatjan and Mohammed Roula and Shabuerjiang Wubuli",
note = "Special Issue on: Developments and Issues in Medical Imaging ",
year = "2018",
month = aug,
doi = "10.1504/IJBET.2018.094297",
language = "English",
volume = "27",
pages = "290--302",
journal = "International Journal of Biomedical Engineering and Technology",
issn = "1752-6418",
publisher = "Inderscience",
number = "4",

}

RIS

TY - JOUR

T1 - Rapid Estimation of Object Movements in Magnetic Induction Tomography

AU - Mamatjan, Yasin

AU - Roula, Mohammed

AU - Wubuli, Shabuerjiang

N1 - Special Issue on: Developments and Issues in Medical Imaging

PY - 2018/8

Y1 - 2018/8

N2 - Magnetic induction tomography (MIT) is a contactless, inexpensive and non-invasive technique for imaging the conductivity distribution inside a body. A time-difference imaging can be used for monitoring the progression of stroke or oedema. However, MIT signals are more sensitive to body movements than the conductivity changes inside the body, because small movements during data acquisition can overwhelm the signals of interest and cause significant image artefacts. Thus, it is crucial to accurately estimate and compensate body movements for image reconstruction or alert clinicians to avoid misinterpretation. We propose frequency domain analysis and statistical approaches for identifying and estimating object movements from MIT data prior to the image reconstruction step. Results show that high amounts of movements totally distorted the images, whereas the proposed approaches produced good performance on elimination of image artefacts and its estimation while maintaining good computational efficiency for patient monitoring.

AB - Magnetic induction tomography (MIT) is a contactless, inexpensive and non-invasive technique for imaging the conductivity distribution inside a body. A time-difference imaging can be used for monitoring the progression of stroke or oedema. However, MIT signals are more sensitive to body movements than the conductivity changes inside the body, because small movements during data acquisition can overwhelm the signals of interest and cause significant image artefacts. Thus, it is crucial to accurately estimate and compensate body movements for image reconstruction or alert clinicians to avoid misinterpretation. We propose frequency domain analysis and statistical approaches for identifying and estimating object movements from MIT data prior to the image reconstruction step. Results show that high amounts of movements totally distorted the images, whereas the proposed approaches produced good performance on elimination of image artefacts and its estimation while maintaining good computational efficiency for patient monitoring.

KW - Magnetic induction tomography

KW - movement estimation

KW - movement compensation

KW - Fast Fourier Transform (FFT)

KW - Independent Component Analysis (ICA)

U2 - 10.1504/IJBET.2018.094297

DO - 10.1504/IJBET.2018.094297

M3 - Article

VL - 27

SP - 290

EP - 302

JO - International Journal of Biomedical Engineering and Technology

JF - International Journal of Biomedical Engineering and Technology

SN - 1752-6418

IS - 4

M1 - 179262

ER -

ID: 1390396