Numerical simulation of X-ray luminescence optical tomography for small-animal imaging

Changqing Li, Arnulfo Martínez-Dávalos, Simon R Cherry

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


X-ray luminescence optical tomography (XLOT) is an emerging hybrid imaging modality in which X-ray excitable particles (phosphor particles) emit optical photons when stimulated with a collimated X-ray beam. XLOT can potentially combine the high sensitivity of optical imaging with the high spatial resolution of X-ray imaging. For reconstruction of XLOT data, we compared two reconstruction algorithms, conventional filtered backprojection (FBP) and a new algorithm, X-ray luminescence optical tomography with excitation priors (XLOT-EP), in which photon propagation is modeled with the diffusion equation and the X-ray beam positions are used as reconstruction priors. Numerical simulations based on dose calculations were used to validate the proposed XLOT imaging system and the reconstruction algorithms. Simulation results showed nanoparticle concentrations reconstructed with XLOT-EP are much less dependent on scan depth than those obtained with FBP. Measurements at just two orthogonal projections are sufficient for XLOT-EP to reconstruct an XLOT image for simple source distributions. The heterogeneity of X-ray energy deposition is included in the XLOT-EP reconstruction and improves the reconstruction accuracy, suggesting that there is a need to calculate the X-ray energy distribution for experimental XLOT imaging.

Original languageEnglish (US)
Article number046002
JournalJournal of Biomedical Optics
Issue number4
StatePublished - 2014


  • reconstruction algorithm
  • small animal imaging
  • tomographic imaging
  • X-ray luminescence

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biomaterials
  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics


Dive into the research topics of 'Numerical simulation of X-ray luminescence optical tomography for small-animal imaging'. Together they form a unique fingerprint.

Cite this