Speaker
Matthew Spangler-Bickell
(GE HealthCare, Waukesha, WI, USA)
Description
Regularized PET reconstruction using anatomical priors has the potential to improve the resolution of the images while suppressing noise and Gibbs artifacts. An algorithm is investigated which calculates a similarity metric between an initial PET reconstruction and multiple MR contrasts, and penalizes the reconstruction in combination with a standard BSREM regularizer. The effect of the anatomically guided reconstruction is analyzed in the context of low dose imaging and found to produce images of a similar quality to the full dose images.
| Field | Software and quantification |
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Primary author
Matthew Spangler-Bickell
(GE HealthCare, Waukesha, WI, USA)
Co-authors
Mr
Jack McCarty
(GE HealthCare, Waukesha, WI, USA)
Dr
Daniel Litwiller
(GE HealthCare, Waukesha, WI, USA)
Dr
Elizabeth Mormino
(Department of Neurology, Stanford University, CA, USA)
Dr
M. Mehdi Khalighi
(Department of Radiology, Stanford University, CA, USA)
