Phase-selective image reconstruction of the lungs in small animals using Micro-CT.


Journal Article

Gating in small animal imaging can compensate for artifacts due to physiological motion. This paper presents a strategy for sampling and image reconstruction in the rodent lung using micro-CT. The approach involves rapid sampling of free-breathing mice without any additional hardware to detect respiratory motion. The projection images are analyzed post-acquisition to derive a respiratory signal, which is used to provide weighting factors for each projection that favor a selected phase of the respiration (e.g. end-inspiration or end-expiration) for the reconstruction. Since the sampling cycle and the respiratory cycle are uncorrelated, the sets of projections corresponding to any of the selected respiratory phases do not have a regular angular distribution. This drastically affects the image quality of reconstructions based on simple filtered backprojection. To address this problem, we use an iterative reconstruction algorithm that combines the Simultaneous Algebraic Reconstruction Technique with Total Variation minimization (SART-TV). At each SART-TV iteration, backprojection is performed with a set of weighting factors that favor the desired respiratory phase. To reduce reconstruction time, the algorithm is implemented on a graphics processing unit. The performance of the proposed approach was investigated in simulations and in vivo scans of mice with primary lung cancers imaged with our in-house developed dual tube/detector micro-CT system. We note that if the ECG signal is acquired during sampling, the same approach could be used for phase-selective cardiac imaging.

Full Text

Duke Authors

Cited Authors

  • Johnston, SM; Perez, BA; Kirsch, DG; Badea, CT

Published Date

  • February 15, 2010

Published In

Volume / Issue

  • 7622 /

Start / End Page

  • 76223G.1 - 76223G.9

PubMed ID

  • 21243034

Pubmed Central ID

  • 21243034

International Standard Serial Number (ISSN)

  • 0277-786X

Digital Object Identifier (DOI)

  • 10.1117/12.844359


  • eng

Conference Location

  • United States