Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network
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...
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doaj-da406079a8be4eda97bf435dec62823c2020-11-24T20:44:19ZengUniversity NorthTehnički Glasnik1846-61681848-55882017-01-01111-25054Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural networkAhmet Aydin0Emine Avşar Aydin1Çukurova University, Department of Biomedical Engineering Sarıçam-Adana, TurkeyAdana Science and Technology University, Department of Aeronautics Engineering Adana, TurkeyX-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.https://hrcak.srce.hr/file/270889breast cancerfeed forward artificial neural network ((FF-ANN)limestonemicrowave imaging |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ahmet Aydin Emine Avşar Aydin |
spellingShingle |
Ahmet Aydin Emine Avşar Aydin Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network Tehnički Glasnik breast cancer feed forward artificial neural network ((FF-ANN) limestone microwave imaging |
author_facet |
Ahmet Aydin Emine Avşar Aydin |
author_sort |
Ahmet Aydin |
title |
Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network |
title_short |
Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network |
title_full |
Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network |
title_fullStr |
Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network |
title_full_unstemmed |
Evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network |
title_sort |
evaluation of limestone layer’s effect for uwb microwave imaging of breast models using neural network |
publisher |
University North |
series |
Tehnički Glasnik |
issn |
1846-6168 1848-5588 |
publishDate |
2017-01-01 |
description |
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. |
topic |
breast cancer feed forward artificial neural network ((FF-ANN) limestone microwave imaging |
url |
https://hrcak.srce.hr/file/270889 |
work_keys_str_mv |
AT ahmetaydin evaluationoflimestonelayerseffectforuwbmicrowaveimagingofbreastmodelsusingneuralnetwork AT emineavsaraydin evaluationoflimestonelayerseffectforuwbmicrowaveimagingofbreastmodelsusingneuralnetwork |
_version_ |
1716817677180207104 |