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Improving spatial resolution with an edge-enhancement model for low-dose propagation-based X-ray phase-contrast computed tomography

  • Lin Zhang
  • , Huijuan Zhao
  • , Zhongxing Zhou
  • , Mengyu Jia
  • , Limin Zhang
  • , Jingying Jiang
  • , Feng Gao
  • Tianjin University
  • Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments

Research output: Contribution to journalArticlepeer-review

Abstract

Propagation-based X-ray phase-contrast computed tomography (PB-PCCT) has been increasingly popular for distinguishing low contrast tissues. Phase retrieval is an important step to quantitatively obtain the phase information before the tomographic reconstructions, while typical phase retrieval methods in PB-PCCT, such as homogenous transport of intensity equation (TIE-Hom), are essentially low-pass filters and thus improve the signal to noise ratio at the expense of the reduced spatial resolution of the reconstructed image. To improve the reconstructed spatial resolution, measured phase contrast projections with high edge enhancement and the phase projections retrieved by TIE-Hom were weighted summed and fed into an iterative tomographic algorithm within the framework of the adaptive steepest descent projections onto convex sets (ASD-POCS), which was employed for suppressing the image noise in low dose reconstructions because of the sparse-view scanning strategy or low exposure time for single phase contrast projection. The merging strategy decreases the accuracy of the linear model of PB-PCCT and would finally lead to the reconstruction failure in iterative reconstructions. Therefore, the additive median root prior is also introduced in the algorithm to partly increase the model accuracy. The reconstructed spatial resolution and noise performance can be flexibly balanced by a pair of antagonistic hyper-parameters. Validations were performed by the established phase-contrast Feldkamp-Davis-Kress, phase-retrieved Feldkamp-Davis-Kress, conventional ASD-POCS and the proposed enhanced ASD-POCS with a numerical phantom dataset and experimental biomaterial dataset. Simulation results show that the proposed algorithm outperforms the conventional ASD-POCS in spatial evaluation assessments such as root mean square error (a ratio of 9.78%), contrast to noise ratio (CNR) (a ratio of 7.46%), and also frequency evaluation assessments such as modulation transfer function (a ratio of 66.48% of MTF50% (50% MTF value)), noise power spectrum (a ratio of 35.25% of f50% (50% value of the Nyquist frequency)) and noise equivalent quanta (1-2 orders of magnitude at high frequencies). Experimental results again confirm the superiority of proposed strategy relative to the conventional one in terms of edge sharpness and CNR (an average increase of 67.35%).

Original languageEnglish
Pages (from-to)37399-37417
Number of pages19
JournalOptics Express
Volume29
Issue number23
DOIs
StatePublished - 8 Nov 2021

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