Evaluation on Compressive Sensing-based Image Reconstruction Method for Microwave Imaging

Basari, Syahrul Ramdani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Microwave Imaging offers safe, low-cost, and portable method for medical imaging applications. These advantages make the microwave imaging convenient for early detection of tumor or cancer. The transmission method is one of the methods in microwave imaging which provides fast measurement and simple image reconstruction. However, this method requires a great number of measurements to obtain a well-reconstructed image. In order to reduce the number of measurements, this research proposes a Compressive Sensing (CS) approach for image reconstruction on microwave imaging. Compressive Sensing allows reconstruction of a signal with fewer measurements than the conventional approach. In this research, the scanning process is conducted on Computer Simulation Technology (CST) Microwave Studio software. Two dipole antennas with 3 GHz frequency are utilized as microwave transmitter and receiver. A two-layer cube phantom acts as the scanned object. Each layer has different relative permittivity which illustrates the healthy cell and abnormal cell. To meet the framework of Compressive Sensing, a weighted matrix of Discrete Radon Transform (DRT) is created as a projection matrix which delineates the data acquisition scheme in the scanning process. Discrete Cosine Transform (DCT) is selected as sparse dictionary matrix to represent the sparse basis while Basis Pursuit is selected as sparse reconstruction algorithm to reconstruct the sparse signal from measurement data. The measured S-{21} data are successfully reconstructed into an image using the Compressive Sensing approach. The reconstructed image is analyzed both qualitatively and quantitatively using image quality parameters such as Structural Similarity Index (SSIM) and Mean Squared Error (MSE).

Original languageEnglish
Title of host publication2019 PhotonIcs and Electromagnetics Research Symposium - Spring, PIERS-Spring 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3348-3352
Number of pages5
ISBN (Electronic)9781728134031
DOIs
Publication statusPublished - Jun 2019
Event2019 PhotonIcs and Electromagnetics Research Symposium - Spring, PIERS-Spring 2019 - Rome, Italy
Duration: 17 Jun 201920 Jun 2019

Publication series

NameProgress in Electromagnetics Research Symposium
Volume2019-June
ISSN (Print)1559-9450
ISSN (Electronic)1931-7360

Conference

Conference2019 PhotonIcs and Electromagnetics Research Symposium - Spring, PIERS-Spring 2019
CountryItaly
CityRome
Period17/06/1920/06/19

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  • Cite this

    Basari, & Ramdani, S. (2019). Evaluation on Compressive Sensing-based Image Reconstruction Method for Microwave Imaging. In 2019 PhotonIcs and Electromagnetics Research Symposium - Spring, PIERS-Spring 2019 - Proceedings (pp. 3348-3352). [9017424] (Progress in Electromagnetics Research Symposium; Vol. 2019-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PIERS-Spring46901.2019.9017424