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Experimental Breast Tumor Detection Using Nn-Based Uwb Imaging

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

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Abstract

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.

Item Type: Article
Additional Information: S. A. Alshehri Department of Computer and Communication Systems Engineering Faculty of Engineering, Universiti Putra Malaysia Serdang, Selangor 43400, Malaysia A. B. Jantan Department of Computer and Communication Systems Engineering Faculty of Engineering, Universiti Putra Malaysia Serdang, Selangor 43400, Malaysia R. S. A. Raja Abdullah Wireless & Photonic Networks Research Centre Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia R. Mahmood Department of Imaging, Faculty of Medicine and Health Sciences Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia Z. Awang Microwave Technology Center, Faculty of Electrical Engineering Universiti Teknologi Mara, Shah Alam, Selangor 40400, Malaysia
Uncontrolled Keywords: Breast tumor detection, Ultrawide-Band (UWB) transceivers, Neural Network (NN)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Zairi Ibrahim
Date Deposited: 28 Dec 2011 02:45
Last Modified: 11 Oct 2018 04:24
URI: http://umpir.ump.edu.my/id/eprint/2063
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