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/ http://umpir.ump.edu.my/id/eprint/2062/ 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

id	ump-2062
recordtype	eprints
spelling	ump-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
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
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/ http://umpir.ump.edu.my/id/eprint/2062/ 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
first_indexed	2023-09-18T21:55:34Z
last_indexed	2023-09-18T21:55:34Z
_version_	1777414055700463616

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

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