Detection of Simulated Brain Strokes Using Microwave Tomography
Brain strokes are one of the leading causes of disability and mortality in adults in developed countries. Ischemic stroke (85% of total cases) and hemorrhagic stroke (15%) must be treated with opposing therapies, and thus, the nature of the stroke must be determined quickly in order to apply the app...
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| Vydané v: | IEEE journal of electromagnetics, RF and microwaves in medicine and biology Ročník 3; číslo 4; s. 254 - 260 |
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| Hlavní autori: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Piscataway
IEEE
01.12.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 2469-7249, 2469-7257 |
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| Abstract | Brain strokes are one of the leading causes of disability and mortality in adults in developed countries. Ischemic stroke (85% of total cases) and hemorrhagic stroke (15%) must be treated with opposing therapies, and thus, the nature of the stroke must be determined quickly in order to apply the appropriate treatment. Recent studies in biomedical imaging have shown that strokes produce variations in the complex electric permittivity of brain tissues, which can be detected by means of microwave tomography. Here, we present some synthetic results obtained with an experimental microwave tomography-based portable system for the early detection and monitoring of brain strokes. The determination of electric permittivity first requires the solution of a coupled forward-inverse problem. We make use of massive parallel computation from domain decomposition method and regularization techniques for optimization methods. Synthetic data are obtained with electromagnetic simulations corrupted by noise, which have been derived from measurements errors of the experimental imaging system. Results demonstrate the possibility to detect hemorrhagic strokes with microwave systems when applying the proposed reconstruction algorithm with edge preserving regularization. |
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| AbstractList | Brain strokes are one of the leading causes of disability and mortality in adults in developed countries. Ischemic stroke (85% of total cases) and hemorrhagic stroke (15%) must be treated with opposing therapies, and thus, the nature of the stroke must be determined quickly in order to apply the appropriate treatment. Recent studies in biomedical imaging have shown that strokes produce variations in the complex electric permittivity of brain tissues, which can be detected by means of microwave tomography. Here, we present some synthetic results obtained with an experimental microwave tomography-based portable system for the early detection and monitoring of brain strokes. The determination of electric permittivity first requires the solution of a coupled forward-inverse problem. We make use of massive parallel computation from domain decomposition method and regularization techniques for optimization methods. Synthetic data are obtained with electromagnetic simulations corrupted by noise, which have been derived from measurements errors of the experimental imaging system. Results demonstrate the possibility to detect hemorrhagic strokes with microwave systems when applying the proposed reconstruction algorithm with edge preserving regularization. Brain strokes are one of the leading causes of disability and mortality in adults in developed countries. The ischemic stroke (85% of total cases) and hemorrhagic stroke (15%) must be treated with opposing therapies, thus the nature of the stroke must be determined quickly in order to apply the appropriate treatment. Recent studies in biomedical imaging have shown that strokes produce variations in the complex electric permittivity of brain tissues, which can be detected by means of microwave tomography. Here we present some synthetic results obtained with an experimental microwave tomography-based portable system for the early detection and monitoring of brain strokes. The determination of electric permittivity first requires the solution of a coupled forward-inverse problem. We make use of massive parallel computation from domain decomposition method and regularization techniques for optimization methods. Synthetic data are obtained with electromagnetic simulations corrupted by noise, which have been derived from measurements errors of the experimental imaging system. Results demonstrate the possibility to detect hemorrhagic strokes with microwave systems when applying the proposed reconstruction algorithm with edge preserving regularization. |
| Author | Coli, Vanna Lisa Blanc-Feraud, Laure Dolean, Victorita Kanfoud, Ibtissam El Pichot, Christian Migliaccio, Claire Tournier, Pierre-Henri |
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| Cites_doi | 10.1109/MAP.2017.2731199 10.1016/j.neurad.2008.01.002 10.1109/MMM.2018.2801646 10.1016/0167-2789(92)90242-F 10.1109/TMTT.2002.800427 10.1109/TBME.2014.2307072 10.1109/TMTT.2018.2849060 10.1515/jnum-2012-0013 10.1109/CAMA.2014.7003417 10.1109/TAP.2018.2871266 10.1109/TMTT.2015.2513398 10.1109/MAP.2017.2732225 10.1155/2014/312528 10.2528/PIERB12022006 10.1002/9781119136941 10.1002/bem.22024 10.1080/10556780802370746 |
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| Keywords | Microwave theory and techniques Electromagnetics Permittivity Hemorrhaging Blood Microwave imaging |
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| Snippet | Brain strokes are one of the leading causes of disability and mortality in adults in developed countries. Ischemic stroke (85% of total cases) and hemorrhagic... Brain strokes are one of the leading causes of disability and mortality in adults in developed countries. The ischemic stroke (85% of total cases) and... |
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| SubjectTerms | Algorithms biomedical imaging Brain brain modeling brain stroke imaging Computational modeling Computer simulation dielectric constant Domain decomposition methods domain-specific language Electromagnetism Engineering Sciences gradient based minimization algorithm hemorrhagic brain stroke detection high-speed parallel computing Inverse problems iterative microwave tomographic imaging massively parallel computing mathematical programming medical image processing Medical imaging Microwave imaging numerical modeling open source FreeFem++ solver Optimization optimization methods Parallel processing parallel programming Permittivity Regularization regularization methods Signal reconstruction Stroke (medical condition) Strokes Tomography total variation whole-microwave measurement system |
| Title | Detection of Simulated Brain Strokes Using Microwave Tomography |
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