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Limited view cone-beam x-ray luminescence tomography based on depth compensation and group sparsity prior

  • Peng Gao
  • , Junyan Rong
  • , Tianshuai Liu
  • , Wenli Zhang
  • , Bin Lan
  • , Xiaoping Ouyang
  • , Hongbing Lu

科研成果: 期刊稿件文章同行评审

10 引用 (Scopus)

摘要

Significance: As a promising hybrid imaging technique with x-ray excitable nanophosphors, cone-beam x-ray luminescence computed tomography (CB-XLCT) has been proposed for in-depth biological imaging applications. In situations in which the full rotation of the imaging object (or x-ray source) is inapplicable, the x-ray excitation is limited by geometry, or a lower x-ray excitation dose is mandatory, limited view CB-XLCT reconstruction would be essential. However, this will result in severe ill-posedness and poor image quality. Aim: The aim is to develop a limited view CB-XLCT imaging strategy to reduce the scanning span and a corresponding reconstruction method to achieve robust imaging performance. Approach: In this study, a group sparsity-based reconstruction method is proposed with the consideration that nanophosphors usually cluster in certain regions, such as tumors or major organs such as the liver. In addition, depth compensation (DC) is adopted to avoid the depth inconsistency caused by a limited view strategy. Results: Experiments using numerical simulations and physical phantoms with different edge-to-edge distances were carried out to illustrate the validity of the proposed method. The reconstruction results showed that the proposed method outperforms conventional methods in terms of localization accuracy, target shape, image contrast, and spatial resolution with two perpendicular projections. Conclusions: A limited view CB-XLCT imaging strategy with two perpendicular projections and a reconstruction method based on DC and group sparsity, which is essential for fast CB-XLCT imaging and for some practical imaging applications, such as imaging-guided surgery, is proposed.

源语言英语
文章编号016004
期刊Journal of Biomedical Optics
25
1
DOI
出版状态已出版 - 1 1月 2020
已对外发布

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