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Hybrid spectral CT reconstruction.

Publication ,  Journal Article
Clark, DP; Badea, CT
Published in: PLoS One
2017

Current photon counting x-ray detector (PCD) technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID). In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM). Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with a spectral separation on the order of the energy resolution of the PCD hardware.

Duke Scholars

Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2017

Volume

12

Issue

7

Start / End Page

e0180324

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Soft Tissue Neoplasms
  • Sarcoma
  • Radiographic Image Interpretation, Computer-Assisted
  • Photons
  • Phantoms, Imaging
  • Mice
  • Iodine
  • General Science & Technology
  • Contrast Media
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Clark, D. P., & Badea, C. T. (2017). Hybrid spectral CT reconstruction. PLoS One, 12(7), e0180324. https://doi.org/10.1371/journal.pone.0180324
Clark, Darin P., and Cristian T. Badea. “Hybrid spectral CT reconstruction.PLoS One 12, no. 7 (2017): e0180324. https://doi.org/10.1371/journal.pone.0180324.
Clark DP, Badea CT. Hybrid spectral CT reconstruction. PLoS One. 2017;12(7):e0180324.
Clark, Darin P., and Cristian T. Badea. “Hybrid spectral CT reconstruction.PLoS One, vol. 12, no. 7, 2017, p. e0180324. Pubmed, doi:10.1371/journal.pone.0180324.
Clark DP, Badea CT. Hybrid spectral CT reconstruction. PLoS One. 2017;12(7):e0180324.

Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2017

Volume

12

Issue

7

Start / End Page

e0180324

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Soft Tissue Neoplasms
  • Sarcoma
  • Radiographic Image Interpretation, Computer-Assisted
  • Photons
  • Phantoms, Imaging
  • Mice
  • Iodine
  • General Science & Technology
  • Contrast Media