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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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2013/412638 |
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| _version_ | 1832558910936973312 |
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| author | Natalia Irishina Aurora Torrente |
| author_facet | Natalia Irishina Aurora Torrente |
| author_sort | Natalia Irishina |
| collection | DOAJ |
| 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. |
| format | Article |
| id | doaj-art-10fd5d6cd437456f88bf79c66a25d6dd |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-10fd5d6cd437456f88bf79c66a25d6dd2025-02-03T01:31:16ZengWileyAbstract 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 |
| spellingShingle | Natalia Irishina Aurora Torrente Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases Abstract and Applied Analysis |
| title | 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_short | Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases |
| title_sort | brain stroke detection by microwaves using prior information from clinical databases |
| url | http://dx.doi.org/10.1155/2013/412638 |
| work_keys_str_mv | AT nataliairishina brainstrokedetectionbymicrowavesusingpriorinformationfromclinicaldatabases AT auroratorrente brainstrokedetectionbymicrowavesusingpriorinformationfromclinicaldatabases |