Abstract
Terahertz Computed Tomography (THz-CT) is a form of optical coherent tomography, which offers a promising approach for achieving non-invasive inspection of solid materials, with potentially numerous applications in industrial manufacturing and biomedical engineering. With traditional CT techniques such as X-ray tomography, full exposure data are needed to produce cross sectional images, even if the region of interest is small. For time-domain terahertz measurements, the requirement for full exposure data is impractical due to the slow measurement process. In this paper, we apply a wavelet-based algorithm to locally reconstruct THz-CT images with a significant reduction in the required measurements. The algorithm recovers an approximation of the region of interest from terahertz measurements within its vicinity, and thus improves the feasibility of using terahertz imaging to detect defects in solid materials and diagnose disease states for clinical practice.
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© 2007 Springer-Verlag Berlin Heidelberg
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Yin, XX., Ng, B.W.H., Ferguson, B., Abbott, D. (2007). Wavelet Based Local Coherent Tomography with an Application in Terahertz Imaging. In: Kropatsch, W.G., Kampel, M., Hanbury, A. (eds) Computer Analysis of Images and Patterns. CAIP 2007. Lecture Notes in Computer Science, vol 4673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74272-2_109
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DOI: https://doi.org/10.1007/978-3-540-74272-2_109
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74271-5
Online ISBN: 978-3-540-74272-2
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