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2016
DOI: 10.1097/rct.0000000000000387
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Correction of Motion Artifacts From Shuttle Mode Computed Tomography Acquisitions for Body Perfusion Imaging Applications

Abstract: Shuttling effects introduced during shuttle-mode CT acquisitions can be computationally corrected for body perfusion applications.

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Cited by 1 publication
(2 citation statements)
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“…CT perfusion parameters were obtained from the shuttle-mode scans using the commercially available CT perfusion software (CT Perfusion 4, GE Healthcare, Waukesha, WI). Before CT perfusion analysis was performed, the scans were non-rigidly registered using the NiftyReg software [15, 16] to the first phase of the acquisitions as described in our previous study [14]. This resulted in eight anatomically matched slices per table position for the ten shuttle mode phases.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…CT perfusion parameters were obtained from the shuttle-mode scans using the commercially available CT perfusion software (CT Perfusion 4, GE Healthcare, Waukesha, WI). Before CT perfusion analysis was performed, the scans were non-rigidly registered using the NiftyReg software [15, 16] to the first phase of the acquisitions as described in our previous study [14]. This resulted in eight anatomically matched slices per table position for the ten shuttle mode phases.…”
Section: Methodsmentioning
confidence: 99%
“…Clinical implementation of the shuttle-mode scanning technique to CT perfusion has been limited to the brain [9, 10] and cardiac [11, 12, 13] applications. In our previous paper [14], we discussed the feasibility of the shuttle-mode technology for body perfusion applications by computationally correcting artifacts induced due to shuttling motion using image registration techniques. In this paper, we extend the feasibility study to investigate the effect of shuttling on CT perfusion parameters obtained from registered and motion corrected images by comparing CTp mappings obtained from aortic inputs from both table positions.…”
Section: Introductionmentioning
confidence: 99%