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. In this work, a two-step sub-space reconstruction strategy is proposed and investigated for use in few-view D-XPCT image reconstruction. It is demonstrated that the resulting iterative algorithm can mitigate the high-frequency information loss caused by data incompleteness and produce images that have better preserved high spatial frequency content than those produced by use of a conventional penalized least squares (PLS) estimator.
Huifeng Guan and Mark A. Anastasio, "A resolution-enhancing image reconstruction method for few-view differential phase-contrast tomography," Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 1013216 (Presented at SPIE Medical Imaging: February 15, 2017; Published: 9 March 2017); https://doi.org/10.1117/12.2255543.
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