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3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system

This paper presents both simulation and experimental study to detect and locate breast tumors along with their classi¯cation as malignant and/or benign in three dimensional (3D) breast model.The contrast between the dielectric properties of these two tumor types is the main key. These dielectric pr...

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Main Author: Sabira, Khatun
Format: Article
Language:English
Published: 2011
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/2062/1/3D_Experimental_detection_and_discrimination_of_malignant_and_benign_breast_tumor_using_NN-Based_UWB_imaging_system_-_Dr.Sabira_Khatun-Journal-.PDF
http://umpir.ump.edu.my/id/eprint/2062/
http://www.jpier.org/PIER/pier.php?paper=11022601
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spelling my.ump.umpir.20622018-10-11T04:23:48Z http://umpir.ump.edu.my/id/eprint/2062/ 3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system Sabira, Khatun QA75 Electronic computers. Computer science This paper presents both simulation and experimental study to detect and locate breast tumors along with their classi¯cation as malignant and/or benign in three dimensional (3D) breast model.The contrast between the dielectric properties of these two tumor types is the main key. These dielectric properties are mainly controlled by the water and blood content of tumors. For simulation, electromagnetic simulator software is used. The experiment is conducted using commercial Ultrawide-Band (UWB) transceivers, Neural Network (NN) based Pattern Recognition (PR) software for imaging and homogenous breast phantom. The 3D homogeneous breast phantom and tumors are fabricated using pure petroleum jelly and a mixture of wheat °our and water respectively. The simulation and experimental setups are performed by transmitting the UWB signals from one side of the breast model and receiving from opposite side diagonally. Using discrete cosine transform (DCT) of received signals, we have trained and tested the developed experimental Neural Network model. In 3D breast model, the achieved detection accuracy of tumor existence is around 100%, while the locating accuracy in terms of (x, y, z) position of a tumor within the breast reached approximately 89.2% and 86.6% in simulation and experimental works respectively. For classi¯cation,the permittivity and conductivity detection accuracy are 98.0% and 99.1% in simulation, and 98.6% and 99.5% in experimental works respectively. Tumor detection and type speci¯cation 3D may lead to successful clinical implementation followed by saving of precious human lives in the near future. 2011 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/2062/1/3D_Experimental_detection_and_discrimination_of_malignant_and_benign_breast_tumor_using_NN-Based_UWB_imaging_system_-_Dr.Sabira_Khatun-Journal-.PDF Sabira, Khatun (2011) 3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system. Progress In Electromagnetics Research (PIER), 116. pp. 221-237. ISSN ISSN: 1070-4698, E-ISSN: 1559-8985 http://www.jpier.org/PIER/pier.php?paper=11022601
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Sabira, Khatun
3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system
description This paper presents both simulation and experimental study to detect and locate breast tumors along with their classi¯cation as malignant and/or benign in three dimensional (3D) breast model.The contrast between the dielectric properties of these two tumor types is the main key. These dielectric properties are mainly controlled by the water and blood content of tumors. For simulation, electromagnetic simulator software is used. The experiment is conducted using commercial Ultrawide-Band (UWB) transceivers, Neural Network (NN) based Pattern Recognition (PR) software for imaging and homogenous breast phantom. The 3D homogeneous breast phantom and tumors are fabricated using pure petroleum jelly and a mixture of wheat °our and water respectively. The simulation and experimental setups are performed by transmitting the UWB signals from one side of the breast model and receiving from opposite side diagonally. Using discrete cosine transform (DCT) of received signals, we have trained and tested the developed experimental Neural Network model. In 3D breast model, the achieved detection accuracy of tumor existence is around 100%, while the locating accuracy in terms of (x, y, z) position of a tumor within the breast reached approximately 89.2% and 86.6% in simulation and experimental works respectively. For classi¯cation,the permittivity and conductivity detection accuracy are 98.0% and 99.1% in simulation, and 98.6% and 99.5% in experimental works respectively. Tumor detection and type speci¯cation 3D may lead to successful clinical implementation followed by saving of precious human lives in the near future.
format Article
author Sabira, Khatun
author_facet Sabira, Khatun
author_sort Sabira, Khatun
title 3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system
title_short 3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system
title_full 3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system
title_fullStr 3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system
title_full_unstemmed 3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system
title_sort 3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system
publishDate 2011
url http://umpir.ump.edu.my/id/eprint/2062/1/3D_Experimental_detection_and_discrimination_of_malignant_and_benign_breast_tumor_using_NN-Based_UWB_imaging_system_-_Dr.Sabira_Khatun-Journal-.PDF
http://umpir.ump.edu.my/id/eprint/2062/
http://www.jpier.org/PIER/pier.php?paper=11022601
_version_ 1643664532133904384
score 13.222552

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