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PIER PIER B PIER C PIER M PIER Letters
2011-05-04
3D Experimental Detection and Discrimination of Malignant and Benign Breast Tumor Using Nn-Based UWB Imaging System
By
Saleh Ali AlShehri,

    Dr. Saleh Ali AlShehri

    Department of Computer and Communication Systems Engineering

    Universiti Putra Malaysia

    Malaysia

    Homepage

Sabira Khatun,

    Prof. Sabira Khatun

    Department of Computer and Communication Systems Engineering

    Universiti Putra Malaysia

    Malaysia

    Homepage

Adznan B. Jantan,

    Dr. Adznan B. Jantan

    Department of Computer and Communication Systems Engineering

    Universiti Putra Malaysia

    Malaysia

    Homepage

Raja Syamsul Azmir Raja Abdullah,

    Dr. Raja Syamsul Azmir Raja Abdullah

    Department of Computer and Communication System Engineering

    Universiti Putra Malaysia

    Malaysia

    Homepage

Rozi Mahmud,

    Dr. Rozi Mahmud

    Department of Imaging

    Universiti Putra Malaysia

    Malaysia

    Homepage

Zaiki Awang

    Dr. Zaiki Awang

    Universiti Teknologi Mara

    Malaysia

    Homepage

Progress In Electromagnetics Research, Vol. 116, 221-237, 2011
doi:10.2528/PIER11022601
Abstract
This paper presents both simulation and experimental study to detect and locate breast tumors along with their classification 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 flour 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 classification, 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 specification 3D may lead to successful clinical implementation followed by saving of precious human lives in the near future.
Citation
Saleh Ali AlShehri, Sabira Khatun, Adznan B. Jantan, Raja Syamsul Azmir Raja Abdullah, Rozi Mahmud, and Zaiki Awang, "3D Experimental Detection and Discrimination of Malignant and Benign Breast Tumor Using Nn-Based UWB Imaging System," Progress In Electromagnetics Research, Vol. 116, 221-237, 2011.
doi:10.2528/PIER11022601
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