Applying an animal model to quantify the uncertainties of an image-based 4D-CT algorithm

Physics in Medicine and Biology
Greg PierceTing-Yim Lee

Abstract

The purpose of this paper is to use an animal model to quantify the spatial displacement uncertainties and test the fundamental assumptions of an image-based 4D-CT algorithm in vivo. Six female Landrace cross pigs were ventilated and imaged using a 64-slice CT scanner (GE Healthcare) operating in axial cine mode. The breathing amplitude pattern of the pigs was varied by periodically crimping the ventilator gas return tube during the image acquisition. The image data were used to determine the displacement uncertainties that result from matching CT images at the same respiratory phase using normalized cross correlation (NCC) as the matching criteria. Additionally, the ability to match the respiratory phase of a 4.0 cm subvolume of the thorax to a reference subvolume using only a single overlapping 2D slice from the two subvolumes was tested by varying the location of the overlapping matching image within the subvolume and examining the effect this had on the displacement relative to the reference volume. The displacement uncertainty resulting from matching two respiratory images using NCC ranged from 0.54 ± 0.10 mm per match to 0.32 ± 0.16 mm per match in the lung of the animal. The uncertainty was found to propagate in quadratu...Continue Reading

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Citations

Feb 16, 2017·International Journal of Computer Assisted Radiology and Surgery·Min LiXiaolin Zheng

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