Microwave Stepped Frequency Head Imaging Using Compressive Sensing With Limited Number of Frequency Steps

Guo, L. and Abbosh, A. M. (2015) Microwave Stepped Frequency Head Imaging Using Compressive Sensing With Limited Number of Frequency Steps. IEEE Antennas and Wireless Propagation Letters, 14 1133-1136. doi:10.1109/LAWP.2015.2396054


Author Guo, L.
Abbosh, A. M.
Title Microwave Stepped Frequency Head Imaging Using Compressive Sensing With Limited Number of Frequency Steps
Journal name IEEE Antennas and Wireless Propagation Letters   Check publisher's open access policy
ISSN 1536-1225
1548-5757
Publication date 2015-01
Year available 2015
Sub-type Article (original research)
DOI 10.1109/LAWP.2015.2396054
Open Access Status
Volume 14
Start page 1133
End page 1136
Total pages 4
Place of publication Piscataway, NJ United States
Publisher Institute of Electrical and Electronics Engineers
Collection year 2016
Language eng
Formatted abstract
Compressive sensing (CS) can be used to recover sparse data (signal) from limited measurements by solving a constrained convex optimization problem. If this approach is applied on microwave stepped frequency imaging technique, the required number of frequency steps to get clear images can be significantly reduced resulting in simple systems with fast data acquisition and real time results. To that end, three different CS techniques are applied on head imaging systems aiming at the detection of brain injuries by utilizing the sparse characteristic of the correlated time domain scattered signals. The presented measured results using a head imaging system indicate that the time domain correlation signals are indeed sparse and thus can be recovered using a limited number of frequency steps. Those recovered signals are then used to successfully generate clear images that show brain injuries. A comparison between using the proposed and the traditional approaches using two quality metrics indicates superiority of the presented CS-based approach in not just the limited needed frequency steps, but also in the quality of the obtained images.
Keyword Compressive sensing (CS)
Confocal algorithm
Head imaging
Microwave imaging
Time domain correlation signal
System
Brain
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Information Technology and Electrical Engineering Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 7 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Sun, 21 Jun 2015, 01:15:59 EST by System User on behalf of School of Information Technol and Elec Engineering