Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases

Microwave tomographic imaging is an inexpensive, noninvasive modality of media dielectric properties reconstruction which can be utilized as a screening method in clinical applications such as breast cancer and brain stroke detection. For breast cancer detection, the iterative algorithm of struc...

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Main Authors: Natalia Irishina, Aurora Torrente
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Abstract and Applied Analysis
Online Access:http://dx.doi.org/10.1155/2013/412638
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spelling doaj-10fd5d6cd437456f88bf79c66a25d6dd2020-11-24T22:02:18ZengHindawi LimitedAbstract and Applied Analysis1085-33751687-04092013-01-01201310.1155/2013/412638412638Brain Stroke Detection by Microwaves Using Prior Information from Clinical DatabasesNatalia Irishina0Aurora Torrente1Instituto Gregorio Millán, Universidad Carlos III de Madrid, 28911 Leganés, Madrid, SpainDepartamento de Ciencia e Ingeniería de Materiales e Ingeniería Química, Universidad Carlos III de Madrid, 28911 Leganés, Madrid, SpainMicrowave tomographic imaging is an inexpensive, noninvasive modality of media dielectric properties reconstruction which can be utilized as a screening method in clinical applications such as breast cancer and brain stroke detection. For breast cancer detection, the iterative algorithm of structural inversion with level sets provides well-defined boundaries and incorporates an intrinsic regularization, which permits to discover small lesions. However, in case of brain lesion, the inverse problem is much more difficult due to the skull, which causes low microwave penetration and highly noisy data. In addition, cerebral liquid has dielectric properties similar to those of blood, which makes the inversion more complicated. Nevertheless, the contrast in the conductivity and permittivity values in this situation is significant due to blood high dielectric values compared to those of surrounding grey and white matter tissues. We show that using brain MRI images as prior information about brain's configuration, along with known brain dielectric properties, and the intrinsic regularization by structural inversion, allows successful and rapid stroke detection even in difficult cases. The method has been applied to 2D slices created from a database of 3D real MRI phantom images to effectively detect lesions larger than 2.5 × 10−2 m diameter.http://dx.doi.org/10.1155/2013/412638
collection DOAJ
language English
format Article
sources DOAJ
author Natalia Irishina
Aurora Torrente
spellingShingle Natalia Irishina
Aurora Torrente
Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases
Abstract and Applied Analysis
author_facet Natalia Irishina
Aurora Torrente
author_sort Natalia Irishina
title Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases
title_short Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases
title_full Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases
title_fullStr Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases
title_full_unstemmed Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases
title_sort brain stroke detection by microwaves using prior information from clinical databases
publisher Hindawi Limited
series Abstract and Applied Analysis
issn 1085-3375
1687-0409
publishDate 2013-01-01
description Microwave tomographic imaging is an inexpensive, noninvasive modality of media dielectric properties reconstruction which can be utilized as a screening method in clinical applications such as breast cancer and brain stroke detection. For breast cancer detection, the iterative algorithm of structural inversion with level sets provides well-defined boundaries and incorporates an intrinsic regularization, which permits to discover small lesions. However, in case of brain lesion, the inverse problem is much more difficult due to the skull, which causes low microwave penetration and highly noisy data. In addition, cerebral liquid has dielectric properties similar to those of blood, which makes the inversion more complicated. Nevertheless, the contrast in the conductivity and permittivity values in this situation is significant due to blood high dielectric values compared to those of surrounding grey and white matter tissues. We show that using brain MRI images as prior information about brain's configuration, along with known brain dielectric properties, and the intrinsic regularization by structural inversion, allows successful and rapid stroke detection even in difficult cases. The method has been applied to 2D slices created from a database of 3D real MRI phantom images to effectively detect lesions larger than 2.5 × 10−2 m diameter.
url http://dx.doi.org/10.1155/2013/412638
work_keys_str_mv AT nataliairishina brainstrokedetectionbymicrowavesusingpriorinformationfromclinicaldatabases
AT auroratorrente brainstrokedetectionbymicrowavesusingpriorinformationfromclinicaldatabases
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