Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/121221
Campo DC | Valor | idioma |
---|---|---|
dc.contributor.author | Amdaouch, Ibtisam | en_US |
dc.contributor.author | Saban, Mohamed | en_US |
dc.contributor.author | El Gueri, Jaouad | en_US |
dc.contributor.author | Chaari, Mohamed Zied | en_US |
dc.contributor.author | Vazquez Alejos, Ana | en_US |
dc.contributor.author | Ruiz Alzola, Juan Bautista | en_US |
dc.contributor.author | Rosado Muñoz, Alfredo | en_US |
dc.contributor.author | Aghzout, Otman | en_US |
dc.date.accessioned | 2023-03-16T07:43:13Z | - |
dc.date.available | 2023-03-16T07:43:13Z | - |
dc.date.issued | 2022 | en_US |
dc.identifier.issn | 2313-433X | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/121221 | - |
dc.description.abstract | In this article, a new efficient and robust approach—the high-resolution microwave imaging system—for early breast cancer diagnosis is presented. The core concept of the proposed approach is to employ a combination of a newly proposed delay-and-sum (DAS) algorithm and the specific absorption rate (SAR) parameter to provide high image quality of breast tumors, along with fast image processing. The new algorithm enhances the tumor response by altering the parameter referring to the distance between the antenna and the tumor in the conventional DAS matrices. This adjustment entails a much clearer reconstructed image with short processing time. To achieve these aims, a high directional Vivaldi antenna is applied around a simulated hemispherical breast model with an embedded tumor. The detection of the tumor is carried out by calculating the maximum value of SAR inside the breast model. Consequently, the antenna position is relocated near the tumor region and is moved to nine positions in a trajectory path, leading to a shorter propagation distance in the image-creation process. At each position, the breast model is illuminated with short pulses of low power waves, and the back-scattered signals are recorded to produce a two-dimensional image of the scanned breast. Several simulations of testing scenarios for reconstruction imaging are investigated. These simulations involve different tumor sizes and materials. The influence of the number of antennas on the reconstructed images is also examined. Compared with the results from the conventional DAS, the proposed technique significantly improves the quality of the reconstructed images, and it detects and localizes the cancer inside the breast with high quality in a fast computing time, employing fewer antennas. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Journal of Imaging | en_US |
dc.source | Journal of Imaging [ISSN 2313-433X], v. 8 (10), 264, (Septiembre 2022) | en_US |
dc.subject.other | Specific absorption rate | en_US |
dc.subject.other | Microwave imaging | en_US |
dc.subject.other | Breast cancer detection | en_US |
dc.subject.other | Vivaldi antenna | en_US |
dc.subject.other | Image reconstruction | en_US |
dc.subject.other | Confocal algorithm | en_US |
dc.title | A Novel Approach of a Low-Cost UWB Microwave Imaging System with High Resolution Based on SAR and a New Fast Reconstruction Algorithm for Early-Stage Breast Cancer Detection | en_US |
dc.type | info:eu-repo/semantics/article | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.3390/jimaging8100264 | en_US |
dc.identifier.scopus | 2-s2.0-85140580566 | - |
dc.identifier.isi | WOS:000873127300001 | - |
dc.contributor.orcid | 0000-0002-6578-012X | - |
dc.contributor.orcid | 0000-0003-3412-8574 | - |
dc.contributor.orcid | 0000-0001-8180-3398 | - |
dc.contributor.orcid | 0000-0002-8770-9420 | - |
dc.contributor.orcid | 0000-0003-3426-2909 | - |
dc.contributor.orcid | 0000-0002-3545-2328 | - |
dc.contributor.orcid | 0000-0002-0429-0573 | - |
dc.contributor.orcid | 0000-0001-9097-8069 | - |
dc.identifier.issue | 10 | - |
dc.relation.volume | 8 | en_US |
dc.investigacion | Ingeniería y Arquitectura | en_US |
dc.type2 | Artículo | en_US |
dc.description.notas | This article belongs to the Special Issue Advances in IoMT, Deep Learning and Computer Vision for Mammographic Image Analysis | en_US |
dc.utils.revision | Sí | en_US |
dc.identifier.ulpgc | Sí | en_US |
dc.contributor.buulpgc | BU-TEL | en_US |
dc.description.sjr | 0,595 | |
dc.description.jcr | 0,56 | |
dc.description.sjrq | Q2 | |
dc.description.jcrq | Q3 | |
dc.description.esci | ESCI | |
dc.description.miaricds | 9,3 | |
item.grantfulltext | open | - |
item.fulltext | Con texto completo | - |
crisitem.author.dept | GIR IUIBS: Patología y Tecnología médica | - |
crisitem.author.dept | IU de Investigaciones Biomédicas y Sanitarias | - |
crisitem.author.dept | Departamento de Señales y Comunicaciones | - |
crisitem.author.orcid | 0000-0002-3545-2328 | - |
crisitem.author.parentorg | IU de Investigaciones Biomédicas y Sanitarias | - |
crisitem.author.fullName | Ruiz Alzola, Juan Bautista | - |
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