Speaker
Description
The advent of long axial field-of-view (LAFOV) PET has enabled simultaneous imaging of all organs with substantially higher sensitivity. However, motion remains an issue that degrades image quality, as the sensitivity of LAFOV-PET is insufficient to mitigate fast irregular motion at the subsecond timescale. We therefore propose to correct for motion in LAFOV-PET at high frequency (2 Hz) by directly processing list-mode data with the Maximum-Likelihood Motion and Activity (MLMA) reconstruction method, optimized for the large projection space of LAFOV-PET through data reduction. We demonstrate the method on the NEMA body phantom scanned at the IMAS Total-Body PET scanner (I3M Valencia, Oncovision). The results indicate that MLMA can be efficiently applied to LAFOV-PET, realizing the full potential of these high-sensitivity scanners.
| Track | TBPET |
|---|---|
| Presentation type | Oral |