Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/28363
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Type: Conference paper
Title: Terahertz imaging of biological tissue using a chirped probe pulse
Author: Ferguson, B.
Wang, S.
Gray, D.
Abbott, D.
Zhang, X.
Citation: Electronics and structures for MEMS II : 17-19 December, 2001, Adelaide, Australia / Neil W. Bergmann (ed.), pp. 172-184
Publisher: THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Publisher Place: PO BOX 10 BELLINGHAM WASHINGTON USA
Issue Date: 2001
Series/Report no.: Proceedings of SPIE--the International Society for Optical Engineering ; 4591.
ISBN: 0819443212
Conference Name: Electronics and Structures for MEMS II (2nd : 2001 : Adelaide, Australia)
Statement of
Responsibility: 
Bradley Ferguson, Shaohong Wang, Douglas A. Gray, Derek Abbott, and Xi-Cheng Zhang
Abstract: There is increasing interest among research groups around the world in the terahertz portion of the electromagnetic spectrum. T-ray systems, driven by ultrafast THz pulses, offer a number of unique advantages over other techniques and are under investigation for a wide range of applications. Biomedical diagnostics is an area of particular emphasis. The sub-millimetre spectroscopic measurements obtained from T-ray systems contain a wealth of information about the sample under test. A number of hurdles, however, hinder the application of T-ray technology. One of the major hurdles to be overcome is the slow acquisition speed of modern THz systems. The chirped probe pulse technique offers a significant improvement in this context. We present results demonstrating the terahertz responses of biological samples measured using a chirped probe pulse, and discuss the problem of data processing and extracting sample characteristics. We show that different types of tissue can be classified based on their terahertz response measured with the chirped probe pulse technique. We consider chicken and beef samples and differentiate between bone and normal tissue. We demonstrate the performance of linear filter models for feature extraction and show that these models are significantly more accurate than a number of intuitive features.
Description: © 2003 COPYRIGHT SPIE--The International Society for Optical Engineering.
RMID: 0020012101
DOI: 10.1117/12.449147
Appears in Collections:Electrical and Electronic Engineering publications

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