A New Method for Detection of Backscattered Signals from Breast Cancer Tumors: Hypothesis Testing Using an Adaptive Entropy-Based Decision Function

Introduction In recent years methods based on radio frequency waves have been used for detecting breast cancer. Using theses waves leads to better results in early detection of breast cancer comparing with conventional mammography which has been used during several years. Materials and Methods In th...

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Main Authors: Seyed Vahab Shojaedini, Rahman Kabiri
Format: Article
Language:English
Published: Mashhad University of Medical Sciences 2012-03-01
Series:Iranian Journal of Medical Physics
Subjects:
Online Access:http://ijmp.mums.ac.ir/article_330_319ed8a1159f31b690e6b11c12ad7dc6.pdf
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spelling doaj-9d885ed1152e42f6a814a0e7524290c92020-11-24T22:31:31ZengMashhad University of Medical SciencesIranian Journal of Medical Physics2345-36722345-36722012-03-0191516410.22038/ijmp.2012.330330A New Method for Detection of Backscattered Signals from Breast Cancer Tumors: Hypothesis Testing Using an Adaptive Entropy-Based Decision FunctionSeyed Vahab Shojaedini0Rahman Kabiri1Iranian Research Organization for Science and Technology, Tehran, IranCommunication Engineering Department, Tehran University, Tehran, IranIntroduction In recent years methods based on radio frequency waves have been used for detecting breast cancer. Using theses waves leads to better results in early detection of breast cancer comparing with conventional mammography which has been used during several years. Materials and Methods In this paper, a new method is introduced for detection of backscattered signals which are received by microwave breast radar. In this method, a decision function is constructed based on noise and signal cross-entropy, using hypothesis testing concept. Then noise and signal are separated using the calculated value for the decision function in each time frame. To estimate value of the decision function, discrete wavelet transform and discrete S transform are used. Results Performance of the proposed method was evaluated in two different scenarios, in which the breast was considered homogenous and heterogeneous, respectively. The obtained results showed that the proposed method detected breast backscattered signals 55% and 49% better than existing methods in two above scenarios. Conclusion Performance of S transform was 21% better than discrete wavelet transform in detection of weak backscattered signals. So it can be concluded that hypothesis testing method which uses S coefficients of received wave for construction of its decision function may be a suitable choice for detection of backscattered signals in breast radar.http://ijmp.mums.ac.ir/article_330_319ed8a1159f31b690e6b11c12ad7dc6.pdfBreast cancerHeterogeneous Breast LesionsHypothesis TestingS Transform
collection DOAJ
language English
format Article
sources DOAJ
author Seyed Vahab Shojaedini
Rahman Kabiri
spellingShingle Seyed Vahab Shojaedini
Rahman Kabiri
A New Method for Detection of Backscattered Signals from Breast Cancer Tumors: Hypothesis Testing Using an Adaptive Entropy-Based Decision Function
Iranian Journal of Medical Physics
Breast cancer
Heterogeneous Breast Lesions
Hypothesis Testing
S Transform
author_facet Seyed Vahab Shojaedini
Rahman Kabiri
author_sort Seyed Vahab Shojaedini
title A New Method for Detection of Backscattered Signals from Breast Cancer Tumors: Hypothesis Testing Using an Adaptive Entropy-Based Decision Function
title_short A New Method for Detection of Backscattered Signals from Breast Cancer Tumors: Hypothesis Testing Using an Adaptive Entropy-Based Decision Function
title_full A New Method for Detection of Backscattered Signals from Breast Cancer Tumors: Hypothesis Testing Using an Adaptive Entropy-Based Decision Function
title_fullStr A New Method for Detection of Backscattered Signals from Breast Cancer Tumors: Hypothesis Testing Using an Adaptive Entropy-Based Decision Function
title_full_unstemmed A New Method for Detection of Backscattered Signals from Breast Cancer Tumors: Hypothesis Testing Using an Adaptive Entropy-Based Decision Function
title_sort new method for detection of backscattered signals from breast cancer tumors: hypothesis testing using an adaptive entropy-based decision function
publisher Mashhad University of Medical Sciences
series Iranian Journal of Medical Physics
issn 2345-3672
2345-3672
publishDate 2012-03-01
description Introduction In recent years methods based on radio frequency waves have been used for detecting breast cancer. Using theses waves leads to better results in early detection of breast cancer comparing with conventional mammography which has been used during several years. Materials and Methods In this paper, a new method is introduced for detection of backscattered signals which are received by microwave breast radar. In this method, a decision function is constructed based on noise and signal cross-entropy, using hypothesis testing concept. Then noise and signal are separated using the calculated value for the decision function in each time frame. To estimate value of the decision function, discrete wavelet transform and discrete S transform are used. Results Performance of the proposed method was evaluated in two different scenarios, in which the breast was considered homogenous and heterogeneous, respectively. The obtained results showed that the proposed method detected breast backscattered signals 55% and 49% better than existing methods in two above scenarios. Conclusion Performance of S transform was 21% better than discrete wavelet transform in detection of weak backscattered signals. So it can be concluded that hypothesis testing method which uses S coefficients of received wave for construction of its decision function may be a suitable choice for detection of backscattered signals in breast radar.
topic Breast cancer
Heterogeneous Breast Lesions
Hypothesis Testing
S Transform
url http://ijmp.mums.ac.ir/article_330_319ed8a1159f31b690e6b11c12ad7dc6.pdf
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