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Proceedings Paper

Investigation of quantitative polychromatic x-ray phase-contrast tomography for tissue characterization
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Paper Abstract

At diagnostic X-ray energies, variations in the real component of the refractive index of tissues are several orders of magnitude larger than variations in the imaginary component, or equivalently, the X-ray attenuation coefficient. Consequently, X-ray phase-contrast imaging may permit the visualization of tissues that have identical, or very similar, X-ray absorption properties. Quantitative in-line phase-contrast tomography methods seek to reconstruct the three-dimensional (3D) complex X-ray refractive index distribution of tissue. Almost all existing image reconstruction algorithms for quantitative phase-contrast tomography make physical assumptions that are not consistent with benchtop or clinical implementations that employ an X-ray tube. Such assumptions include a monochromatic plane-wave X-ray beam that possesses perfect coherence properties. In this work, we implement and investigate a reconstruction theory for quantitative phase-contrast tomography that is suitable for use with polychromatic X-ray beams produced by a tube source. An image reconstruction algorithm is implemented that requires, as input data, two intensity measurements at each tomographic view that correspond to incident X-ray beams with distinct coherence properties. Computer-simulation studies that emulate polychromatic tube-based imaging conditions are conducted to assess the effectiveness of the reconstruction method for characterizing soft tissue structures.

Paper Details

Date Published: 14 March 2009
PDF: 6 pages
Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72584B (14 March 2009); doi: 10.1117/12.812335
Show Author Affiliations
Cheng-Ying Chou, National Taiwan Univ. (Taiwan)
Adam M. Zysk, Illinois Institute of Technology (United States)
Mark A. Anastasio, Illinois Institute of Technology (United States)


Published in SPIE Proceedings Vol. 7258:
Medical Imaging 2009: Physics of Medical Imaging
Ehsan Samei; Jiang Hsieh, Editor(s)

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