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Proceedings Paper

Joint reconstruction of absorption and refractive properties in propagation-based x-ray phase-contrast tomography via a non-linear image reconstruction algorithm
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Paper Abstract

Propagation-based X-ray phase-contrast tomography (XPCT) provides the opportunity to image weakly absorbing objects and is being explored actively for a variety of important pre-clinical applications. Quantitative XPCT image reconstruction methods typically involve a phase retrieval step followed by application of an image reconstruction algorithm. Most approaches to phase retrieval require either acquiring multiple images at different object-to-detector distances or introducing simplifying assumptions, such as a single-material assumption, to linearize the imaging model. In order to overcome these limitations, a non-linear image reconstruction method has been proposed previously that jointly estimates the absorption and refractive properties of an object from XPCT projection data acquired at a single propagation distance, without the need to linearize the imaging model. However, the numerical properties of the associated non-convex optimization problem remain largely unexplored. In this study, computer simulations are conducted to investigate the feasibility of the joint reconstruction problem in practice. We demonstrate that the joint reconstruction problem is ill-posed and sensitive to system inconsistencies. Particularly, the method can generate accurate refractive index images only if the object is thin and has no phase-wrapping in the data. However, we also observed that, for weakly absorbing objects, the refractive index images reconstructed by the joint reconstruction method are, in general, more accurate than those reconstructed using methods that simply ignore the object’s absorption.

Paper Details

Date Published: 29 March 2016
PDF: 8 pages
Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97835H (29 March 2016); doi: 10.1117/12.2217443
Show Author Affiliations
Yujia Chen, Washington Univ. in St. Louis (United States)
Kun Wang, Washington Univ. in St. Louis (United States)
Doga Gursoy, Argonne National Lab. (United States)
Carmen Soriano, Argonne National Lab. (United States)
Francesco De Carlo, Argonne National Lab. (United States)
Mark A. Anastasio, Washington Univ. in St. Louis (United States)

Published in SPIE Proceedings Vol. 9783:
Medical Imaging 2016: Physics of Medical Imaging
Despina Kontos; Thomas G. Flohr, Editor(s)

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