Restricted Data Set Reconstruction Based On Respiration Quality to Improve Prospectively Gated in Vivo Micro-CT of Mice
L Burk*, Y Lee, J Lu, O Zhou, University of North Carolina at Chapel HillWE-C-217BCD-3 Wednesday 10:30:00 AM - 12:30:00 PM Room: 217BCD
Micro-CT is commonly employed for lung imaging of mice; prospective gating allows for in-vivo imaging of free-breathing subjects. While this technique is successfully executed for healthy animals, results are less consistent for some disease models whose symptoms include irregular or unstable respiration. The purpose of this work is to repair the quality of high-blur images that arise from respiration instability using a retrospective method of motion reduction which identifies the individual x-ray projection images contributing most to the motion blur. Reconstructions were performed after the exclusion of these projections (the so-called restricted set).
Sixteen mice were imaged using field emission cone beam micro-CT and prospective gating with a bellows-type respiration sensor. The scanner was operated in step-and-shoot mode; 400 projection images were acquired per scan. An algorithm was developed to analyze the respiration trace file and segment the individual breath corresponding to each projection image. We tested three different criteria to define a bad breath shape (correlation, mean breath height, or mode breath height), and restricted data set reconstructions were performed using each of these criteria to exclude projections corresponding to bad breaths. Each restricted set was compared against the full unrestricted data set image; the slope perpendicular to the diaphragm was used as a quantitative assessment of motion blur.
All image sets saw a reduction in motion blur with at least one restriction technique. In 22 of 27 images, improvement was measured regardless of the removal criterion. Five percent total projection removal is optimal; a more aggressive correction increases the likelihood of under-sampling artifacts.
Removing a subset of bad projections from otherwise complete image sets measurably decreases motion blur in respiratory-gated imaging. An approach based on breath height generally provides the best results. The technique is applicable to a variety of imaging modalities.