Speaker
Gaspar Delso
(UniversitätsSpital Zürich)
Description
The goal of the present study was to assess the longitudinal repeatability of a novel bone identification method, based on a convolutional deep network trained to convert LAVA-Flex and zero echo-time MRI data into pseudo-CT density maps. The consistency of the bone maps -with potential applications in attenuation correction of PET data and MR-based radiotherapy planning- was evaluated for a number of clinically realistic variations of the ideal acquisition conditions.
Primary author
Gaspar Delso
(UniversitätsSpital Zürich)
Co-authors
Dr
Brice Fernandez
(GE Healthcare)
Dr
Florian Wiesinger
(GE Global Research)
Dr
Sandeep Kaushik
(GE Healthcare)
