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Preliminary communication

Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network

Ahmet Aydin   ORCID icon orcid.org/0000-0003-2390-7556 ; Çukurova University, Department of Biomedical Engineering Sarıçam-Adana, Turkey
Emine Avşar Aydin   ORCID icon orcid.org/0000-0002-5068-2957 ; Adana Science and Technology University, Department of Aeronautics Engineering Adana, Turkey

Fulltext: english, pdf (761 KB) pages 50-54 downloads: 247* cite
APA 6th Edition
Aydin, A. & Avşar Aydin, E. (2017). Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network. Tehnički glasnik, 11 (1-2), 50-54. Retrieved from https://hrcak.srce.hr/183745
MLA 8th Edition
Aydin, Ahmet and Emine Avşar Aydin. "Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network." Tehnički glasnik, vol. 11, no. 1-2, 2017, pp. 50-54. https://hrcak.srce.hr/183745. Accessed 18 Oct. 2021.
Chicago 17th Edition
Aydin, Ahmet and Emine Avşar Aydin. "Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network." Tehnički glasnik 11, no. 1-2 (2017): 50-54. https://hrcak.srce.hr/183745
Harvard
Aydin, A., and Avşar Aydin, E. (2017). 'Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network', Tehnički glasnik, 11(1-2), pp. 50-54. Available at: https://hrcak.srce.hr/183745 (Accessed 18 October 2021)
Vancouver
Aydin A, Avşar Aydin E. Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network. Tehnički glasnik [Internet]. 2017 [cited 2021 October 18];11(1-2):50-54. Available from: https://hrcak.srce.hr/183745
IEEE
A. Aydin and E. Avşar Aydin, "Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network", Tehnički glasnik, vol.11, no. 1-2, pp. 50-54, 2017. [Online]. Available: https://hrcak.srce.hr/183745. [Accessed: 18 October 2021]

Abstracts
X-ray mammography is widely used for detection of breast cancer. Besides its popularity, this method did not have the potential of discriminating a tumor covered with limestone from a pure limestone mass. This might cause misdetection of some tumors covered with limestone or unnecessary surgery for a pure limestone mass. In this study, Ultra-Wide Band (UWB) signals are used for the imaging. A feed-forward artificial neural network (FF-ANN) is used to classify the mass in the breast whether it is a tumor or not by using the transmission coefficients obtained from UWB signals. A spherical tumor covered with limestone and pure limestone masses were designed and placed into the fibro-glandular layer of breast model using CST Microwave Studio Software. The radius of the masses for both cases is changed from 1 mm to 10 mm with 1 mm steps. Horn antennas were chosen to send and receive Ultra-Wide Band (UWB) signals between 2 and 18 GHz frequency range. The obtained results show that the proposed method, on the contrary of the mammogram, has the potential of discriminating the tumor covered with limestone from the pure limestone, for the mass sizes of 7, 8 and 10 mm. Consequently, the UWB microwave imaging can be used to distinguish these cases from each other.

Keywords
breast cancer; feed forward artificial neural network ((FF-ANN); limestone; microwave imaging

Hrčak ID: 183745

URI
https://hrcak.srce.hr/183745

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