Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging

This paper presents a system with experimental comple-ment to a simulation work for early breast tumor detection. The ex-periments are conducted using commercial Ultrawide-Band (UWB) transceivers, Neural Network (NN) based Pattern Recognition (PR) software for imaging and proposed breast phantoms f...

Full description

Bibliographic Details
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/2063/ http://umpir.ump.edu.my/id/eprint/2063/ http://umpir.ump.edu.my/id/eprint/2063/1/Experimental_Breast_Tumor_Detection_Using_NN-Based_UWB_Imaging_-_Dr.Sabira_Khatun-Journal-.PDF

id	ump-2063
recordtype	eprints
spelling	ump-20632018-10-11T04:24:17Z http://umpir.ump.edu.my/id/eprint/2063/ Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging Sabira, Khatun QA75 Electronic computers. Computer science This paper presents a system with experimental comple-ment to a simulation work for early breast tumor detection. The ex-periments are conducted using commercial Ultrawide-Band (UWB) transceivers, Neural Network (NN) based Pattern Recognition (PR) software for imaging and proposed breast phantoms for homogenous and heterogeneous tissues. The proposed breast phantoms (homoge-neous and heterogeneous) and tumor are constructed using available low cost materials and their mixtures with minimal e®ort. A speci¯c glass is used as skin. All the materials and their mixtures are con-sidered according to the ratio of the dielectric properties of the breast tissues. Experiments to detect tumor are performed in regular noisy room environment. The UWB signals are transmitted from one side of the breast phantom (for both cases) and received from opposite side diagonally repeatedly. Using discrete cosine transform (DCT) of these received signals, a Neural Network (NN) module is developed, trained and tested. The tumor existence, size and location detection rates for both cases are highly satisfactory, which are approximately: (i) 100%,95.8% and 94.3% for homogeneous and (ii) 100%, 93.4% and 93.1% for heterogeneous cases respectively. This gives assurance of early de- tection and the practical usefulness of the developed system in near future. 2011 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/2063/1/Experimental_Breast_Tumor_Detection_Using_NN-Based_UWB_Imaging_-_Dr.Sabira_Khatun-Journal-.PDF Sabira, Khatun (2011) Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging. Progress In Electromagnetics Research (PIER), 111. pp. 447-465. ISSN ISSN: 1070-4698, E-ISSN: 1559-8985 http://www.jpier.org/PIER/pier.php?paper=10110102
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 Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging
description	This paper presents a system with experimental comple-ment to a simulation work for early breast tumor detection. The ex-periments are conducted using commercial Ultrawide-Band (UWB) transceivers, Neural Network (NN) based Pattern Recognition (PR) software for imaging and proposed breast phantoms for homogenous and heterogeneous tissues. The proposed breast phantoms (homoge-neous and heterogeneous) and tumor are constructed using available low cost materials and their mixtures with minimal e®ort. A speci¯c glass is used as skin. All the materials and their mixtures are con-sidered according to the ratio of the dielectric properties of the breast tissues. Experiments to detect tumor are performed in regular noisy room environment. The UWB signals are transmitted from one side of the breast phantom (for both cases) and received from opposite side diagonally repeatedly. Using discrete cosine transform (DCT) of these received signals, a Neural Network (NN) module is developed, trained and tested. The tumor existence, size and location detection rates for both cases are highly satisfactory, which are approximately: (i) 100%,95.8% and 94.3% for homogeneous and (ii) 100%, 93.4% and 93.1% for heterogeneous cases respectively. This gives assurance of early de- tection and the practical usefulness of the developed system in near future.
format	Article
author	Sabira, Khatun
author_facet	Sabira, Khatun
author_sort	Sabira, Khatun
title	Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging
title_short	Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging
title_full	Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging
title_fullStr	Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging
title_full_unstemmed	Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging
title_sort	experimental breast tumor detection using nn-based uwb imaging
publishDate	2011
url	http://umpir.ump.edu.my/id/eprint/2063/ http://umpir.ump.edu.my/id/eprint/2063/ http://umpir.ump.edu.my/id/eprint/2063/1/Experimental_Breast_Tumor_Detection_Using_NN-Based_UWB_Imaging_-_Dr.Sabira_Khatun-Journal-.PDF
first_indexed	2023-09-18T21:55:34Z
last_indexed	2023-09-18T21:55:34Z
_version_	1777414055834681344

Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging

Similar Items