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

doi:10.1109/AP-S/USNC-URSI47032.2022.9887012

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

Elektronik ve Hab.Müh.Bölümü

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

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 dil	İngilizce
Ana bilgisayar yayını başlığı	2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	697-698
Sayfa sayısı	2
ISBN (Elektronik)	9781665496582
DOI'lar	https://doi.org/10.1109/AP-S/USNC-URSI47032.2022.9887012
Yayın durumu	Yayınlandı - 2022
Etkinlik	2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Denver, United States Süre: 10 Tem 2022 → 15 Tem 2022

Yayın serisi

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

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022
Ülke/Bölge	United States
Şehir	Denver
Periyot	10/07/22 → 15/07/22

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.

Finansörler	Finansör numarası
European Cooperation in Science and Technology	CA17115
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu	118S074

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

Belgeye Erişim

10.1109/AP-S/USNC-URSI47032.2022.9887012

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Altintas, G., Yasar, H., Uslu, I. E., Demirel, Y., Joof, S., Akinci, M. N., Yilmaz, T., & Akduman, I. (2022). Antenna Array Optimization via Deep Learning for Breast Cancer Microwave Hyperthermia Application: Preliminary Results. In 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings (pp. 697-698). (2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AP-S/USNC-URSI47032.2022.9887012

Altintas, Gulsah ; Yasar, Halimcan ; Uslu, Ibrahim Enes et al. / Antenna Array Optimization via Deep Learning for Breast Cancer Microwave Hyperthermia Application : Preliminary Results. 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 697-698 (2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings).

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title = "Antenna Array Optimization via Deep Learning for Breast Cancer Microwave Hyperthermia Application: Preliminary Results",

abstract = "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.",

author = "Gulsah Altintas and Halimcan Yasar and Uslu, {Ibrahim Enes} and Yusuf Demirel and Sulayman Joof and Akinci, {Mehmet Nuri} and Tuba Yilmaz and Ibrahim Akduman",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 ; Conference date: 10-07-2022 Through 15-07-2022",

year = "2022",

doi = "10.1109/AP-S/USNC-URSI47032.2022.9887012",

language = "English",

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

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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

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Altintas, G, Yasar, H, Uslu, IE, Demirel, Y, Joof, S, Akinci, MN , Yilmaz, T & Akduman, I 2022, Antenna Array Optimization via Deep Learning for Breast Cancer Microwave Hyperthermia Application: Preliminary Results. in 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings. 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 697-698, 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022, Denver, United States, 10/07/22. https://doi.org/10.1109/AP-S/USNC-URSI47032.2022.9887012

Antenna Array Optimization via Deep Learning for Breast Cancer Microwave Hyperthermia Application: Preliminary Results. / Altintas, Gulsah; Yasar, Halimcan; Uslu, Ibrahim Enes et al.
2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. p. 697-698 (2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Antenna Array Optimization via Deep Learning for Breast Cancer Microwave Hyperthermia Application

T2 - 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

AU - Altintas, Gulsah

AU - Yasar, Halimcan

AU - Uslu, Ibrahim Enes

AU - Demirel, Yusuf

AU - Joof, Sulayman

AU - Akinci, Mehmet Nuri

AU - Yilmaz, Tuba

AU - Akduman, Ibrahim

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

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DO - 10.1109/AP-S/USNC-URSI47032.2022.9887012

M3 - Conference contribution

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T3 - 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings

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

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ER -

Altintas G, Yasar H, Uslu IE, Demirel Y, Joof S, Akinci MN et al. Antenna Array Optimization via Deep Learning for Breast Cancer Microwave Hyperthermia Application: Preliminary Results. In 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2022. p. 697-698. (2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings). doi: 10.1109/AP-S/USNC-URSI47032.2022.9887012

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

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Finansman

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

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Alıntı Yap