Open AccessInvestigation of discrete imaging models and iterative image reconstruction in differential X-ray phase-contrast tomography
Author(s) -
Qiaofeng Xu,
Emil Y. Sidky,
Xiaochuan Pan,
Marco Stampai,
Peter Modregger,
Mark A. Anastasio
Publication year - 2012
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.20.010724
Subject(s) - iterative reconstruction , radon transform , tomographic reconstruction , tomography , projection (relational algebra) , optics , phase contrast imaging , computer science , contrast (vision) , iterative method , computer vision , artificial intelligence , physics , algorithm , phase contrast microscopy
Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen.