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DOI

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.
Original languageEnglish
Article number179262
Pages (from-to)290-302
Number of pages13
JournalInternational Journal of Biomedical Engineering and Technology
Volume27
Issue number4
Early online date7 Aug 2018
DOIs
Publication statusPublished - Aug 2018

    Research areas

  • Magnetic induction tomography, movement estimation, movement compensation, Fast Fourier Transform (FFT), Independent Component Analysis (ICA)

ID: 1390396