Antenna Array Optimization via Deep Learning for Breast Cancer Microwave Hyperthermia Application: Preliminary Results

Gulsah Altintas, Halimcan Yasar, Ibrahim Enes Uslu, Yusuf Demirel, Sulayman Joof, Mehmet Nuri Akinci, Tuba Yilmaz, Ibrahim Akduman

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Özet

Microwave hyperthermia (MH) requires the effective calibration of the antenna for selective focusing of the microwave energy at the target region with a nominal effect on the surrounding tissue. Many different antenna calibration methods such as optimization techniques and lookup tables have been proposed. In this paper, we present the preliminary results of a CNN based phase and power optimization approach. To create the necessary dataset, we used the superposition method to combine the information from the individual antennas. The results of the CNN model are compared with lookup table results. The proposed approach is promising as it shows less hot spots in heating potential distributions.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar697-698
Sayfa sayısı2
ISBN (Elektronik)9781665496582
DOI'lar
Yayın durumuYayınlandı - 2022
Etkinlik2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Denver, United States
Süre: 10 Tem 202215 Tem 2022

Yayın serisi

Adı2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings

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???event.eventtypes.event.conference???2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022
Ülke/BölgeUnited States
ŞehirDenver
Periyot10/07/2215/07/22

Bibliyografik not

Publisher Copyright:
© 2022 IEEE.

Finansman

This work has received funding from Scientific and Technological Research Council of Turkey under grant agreement 118S074, and COST Action grant agreement CA17115.

FinansörlerFinansör numarası
European Cooperation in Science and TechnologyCA17115
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu118S074

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