Modelling the propagation of terahertz radiation through a tissue simulating phantom

WALKER, Gillian C., BERRY, Elizabeth, SMYE, Stephen W., ZINOV'EV, Nick N., FITZGERALD, Anthony J., MILES, Robert E., CHAMBERLAIN, Martyn and SMITH, Michael A. (2004). Modelling the propagation of terahertz radiation through a tissue simulating phantom. Physics in Medicine and Biology, 49 (10), 1853-1864.

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Link to published version:: https://doi.org/10.1088/0031-9155/49/10/002
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    Abstract

    Terahertz (THz) frequency radiation, 0.1 THz to 20 THz, is being investigated for biomedical imaging applications following the introduction of pulsed THz sources that produce picosecond pulses and function at room temperature. Owing to the broadband nature of the radiation, spectral and temporal information is available from radiation that has interacted with a sample; this information is exploited in the development of biomedical imaging tools and sensors. In this work, models to aid interpretation of broadband THz spectra were developed and evaluated. THz radiation lies on the boundary between regions best considered using a deterministic electromagnetic approach and those better analysed using a stochastic approach incorporating quantum mechanical effects, so two computational models to simulate the propagation of THz radiation in an absorbing medium were compared. The first was a thin film analysis and the second a stochastic Monte Carlo model. The Cole–Cole model was used to predict the variation with frequency of the physical properties of the sample and scattering was neglected. The two models were compared with measurements from a highly absorbing water-based phantom. The Monte Carlo model gave a prediction closer to experiment over 0.1 to 3 THz. Knowledge of the frequency-dependent physical properties, including the scattering characteristics, of the absorbing media is necessary. The thin film model is computationally simple to implement but is restricted by the geometry of the sample it can describe. The Monte Carlo framework, despite being initially more complex, provides greater flexibility to investigate more complicated sample geometries.

    Item Type: Article
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Centre for Health and Social Care Research
    Identification Number: https://doi.org/10.1088/0031-9155/49/10/002
    Page Range: 1853-1864
    Depositing User: Ann Betterton
    Date Deposited: 16 Mar 2011 15:29
    Last Modified: 19 Mar 2021 00:45
    URI: http://shura.shu.ac.uk/id/eprint/3403

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