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العنوان
Early breast cancer detection using ultra
wideband antenna /
المؤلف
Farag, Fady Emad Asaad.
هيئة الاعداد
باحث / فادى عماد اسعد فرج بشارة
مشرف / هالة عبد القادر
مناقش / هشام عبدالهادي محمد
مناقش / محمود عبدالحليم مهنا
الموضوع
Early breast cancer detection using ultra wideband antenna.
تاريخ النشر
2023.
عدد الصفحات
92 P. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة الكهربائية والالكترونية
تاريخ الإجازة
18/2/2024
مكان الإجازة
جامعة بنها - كلية الهندسة بشبرا - الهندسة الكهربائية
الفهرس
Only 14 pages are availabe for public view

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from 103

Abstract

Microwave imaging occupies a notable portion of research interest due to its high sensitivity, being
a safe screening technique, cost efficiency, minimal power consumption, and a non-invasive
mechanism that can exploited to diagnose the presence of a tumor. In addition to the elimination
of breast compression and ionizing radiation and its capability to efficiently distinguish between
normal tissues and cancerous tissues in the microwave frequency range. The basic function of the
microwave technique is to localize tumors based on the difference between electrical properties
such as permittivity and conductivity between healthy and malignant tissues. As demonstrated
through the thesis, the microwave imaging system consists of an antenna, breast phantom and an
open-source MATLAB program called MERIT toolbox for image reconstruction. The most vital
part of the system is how to design a UWB antenna with certain characteristics to have the best
performance through the screening process. it was proven that an antenna array is the preferred
choice to get the desired characteristics for the best screening process. In this thesis an array of
eight elements of antipodal Vivaldi antenna is used for microwave imaging to detect cancerous
cells inside the breast phantom with different locations using MERIT toolbox. The proposed
system and the image reconstruction algorithm could identify tumors and distinguish between
healthy and malignant tissues. The system could also identify small tumor of a radius 10 mm in
different locations inside the breast phantom. In the future work, more complicated phantoms with
more layers could be implemented to test the system with more than one tumor. Artificial
intelligence algorithms could be harnessed in the detection process to increase the accuracy of the
proposed system.