28 June 2018 Subspace-based resolution-enhancing image reconstruction method for few-view differential phase-contrast tomography
Huifeng Guan, Charlotte Klara Hagen, Alessandro Olivo, Mark A. Anastasio
Author Affiliations +
Abstract
It is well known that properly designed image reconstruction methods can facilitate reductions in imaging doses and data-acquisition times in tomographic imaging. The ability to do so is particularly important for emerging modalities, such as differential x-ray phase-contrast tomography (D-XPCT), which are currently limited by these factors. An important application of D-XPCT is high-resolution imaging of biomedical samples. However, reconstructing high-resolution images from few-view tomographic measurements remains a challenging task due to the high-frequency information loss caused by data incompleteness. In this work, a subspace-based reconstruction strategy is proposed and investigated for use in few-view D-XPCT image reconstruction. By adopting a two-step approach, the proposed method can simultaneously recover high-frequency details within a certain region of interest while suppressing noise and/or artifacts globally. The proposed method is investigated by the use of few-view experimental data acquired by an edge-illumination D-XPCT scanner.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2018/$25.00 © 2018 SPIE
Huifeng Guan, Charlotte Klara Hagen, Alessandro Olivo, and Mark A. Anastasio "Subspace-based resolution-enhancing image reconstruction method for few-view differential phase-contrast tomography," Journal of Medical Imaging 5(2), 023501 (28 June 2018). https://doi.org/10.1117/1.JMI.5.2.023501
Received: 27 July 2017; Accepted: 31 May 2018; Published: 28 June 2018
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Cited by 1 scholarly publication.
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KEYWORDS
Image restoration

Tomography

Reconstruction algorithms

Radon transform

Data acquisition

Imaging systems

Refractive index

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