Microwave Tomography for Brain Imaging: Feasibility Assessment for Stroke Detection

There is a need for a medical imaging technology, that supplements current clinical brain imaging techniques, for the near-patient and mobile assessment of cerebral vascular disease. Microwave tomography (MWT) is a novel imaging modality that has this potential. The aim of the study was to assess th...

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Main Authors: Serguei Y. Semenov, Douglas R. Corfield
Format: Article
Language:English
Published: Wiley 2008-01-01
Series:International Journal of Antennas and Propagation
Online Access:http://dx.doi.org/10.1155/2008/254830
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author Serguei Y. Semenov
Douglas R. Corfield
author_facet Serguei Y. Semenov
Douglas R. Corfield
author_sort Serguei Y. Semenov
collection DOAJ
description There is a need for a medical imaging technology, that supplements current clinical brain imaging techniques, for the near-patient and mobile assessment of cerebral vascular disease. Microwave tomography (MWT) is a novel imaging modality that has this potential. The aim of the study was to assess the feasibility, and potential performance characteristics, of MWT for brain imaging with particular focus on stroke detection. The study was conducted using MWT computer simulations and 2D head model with stroke. A nonlinear Newton reconstruction approach was used. The MWT imaging of deep brain tissues presents a significant challenge, as the brain is an object of interest that is located inside a high dielectric contrast shield, comprising the skull and CSF. However, high performance, nonlinear MWT inversion methods produced biologically meaningful images of the brain including images of stroke. It is suggested that multifrequency MWT has the potential to significantly improve imaging results.
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spelling doaj-art-d588e895d7e94538823366cc64048bb52025-02-03T01:01:12ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772008-01-01200810.1155/2008/254830254830Microwave Tomography for Brain Imaging: Feasibility Assessment for Stroke DetectionSerguei Y. Semenov0Douglas R. Corfield1School of Medicine, Keele University, ISTM, Hartshill Campus, Thornburrow Drive, Hartshill, Stoke-on-Trent ST4 7QB, UKSchool of Medicine, Keele University, ISTM, Hartshill Campus, Thornburrow Drive, Hartshill, Stoke-on-Trent ST4 7QB, UKThere is a need for a medical imaging technology, that supplements current clinical brain imaging techniques, for the near-patient and mobile assessment of cerebral vascular disease. Microwave tomography (MWT) is a novel imaging modality that has this potential. The aim of the study was to assess the feasibility, and potential performance characteristics, of MWT for brain imaging with particular focus on stroke detection. The study was conducted using MWT computer simulations and 2D head model with stroke. A nonlinear Newton reconstruction approach was used. The MWT imaging of deep brain tissues presents a significant challenge, as the brain is an object of interest that is located inside a high dielectric contrast shield, comprising the skull and CSF. However, high performance, nonlinear MWT inversion methods produced biologically meaningful images of the brain including images of stroke. It is suggested that multifrequency MWT has the potential to significantly improve imaging results.http://dx.doi.org/10.1155/2008/254830
spellingShingle Serguei Y. Semenov
Douglas R. Corfield
Microwave Tomography for Brain Imaging: Feasibility Assessment for Stroke Detection
International Journal of Antennas and Propagation
title Microwave Tomography for Brain Imaging: Feasibility Assessment for Stroke Detection
title_full Microwave Tomography for Brain Imaging: Feasibility Assessment for Stroke Detection
title_fullStr Microwave Tomography for Brain Imaging: Feasibility Assessment for Stroke Detection
title_full_unstemmed Microwave Tomography for Brain Imaging: Feasibility Assessment for Stroke Detection
title_short Microwave Tomography for Brain Imaging: Feasibility Assessment for Stroke Detection
title_sort microwave tomography for brain imaging feasibility assessment for stroke detection
url http://dx.doi.org/10.1155/2008/254830
work_keys_str_mv AT sergueiysemenov microwavetomographyforbrainimagingfeasibilityassessmentforstrokedetection
AT douglasrcorfield microwavetomographyforbrainimagingfeasibilityassessmentforstrokedetection