Motion correction (MC) in PET brain studies may be based on the well-established multiple acquisition frame method (MAF) , , . For each position of the subject the separately framed list mode data are reconstructed in the frame of reference given by the scanner. Consequently, this method needs only minor modifications of the workflow compared to the available standard reconstruction. Only the attenuation of the subject has to be modified by calculating motion adapted attenuation correction factors (ACFs) for each position. Since no transmission scan of the subject is possible for the BrainPET scanner, ACFs are derived from a template-based approach using a co-registered subject MR image obtained by an MP-RAGE sequence. Additional attenuation due to the MR head coil in the field of view of the PET scanner is corrected using an attenuation image of the coil obtained from a Siemens ECAT EXACT HR+ PET scanner using a 68Ge transmission source. All other corrections applied to the data, e.g. normalisation and randoms correction, are applied in the same way as for the standard reconstruction. Finally, all reconstructed images are registered according to the known motion transformations. For the MAF method, the framing pattern of dynamic data is adjusted to the head movements. A drawback of this method is that multiple short frames must be separately reconstructed in the case of fast or frequent movement to minimise intra-frame motion.
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Although formally equivalent, and are substantially different operationally. Whereas all μ-values in the image constitute the unknowns of , only a small subset of pixels contribute to the unknowns of , with the majority of the attenuation parameters in being fixed by the transformed CT image. Furthermore, the few unknowns in may be clustered together into only a few artifacts with the concurrent expectation of similar attenuation values within each artifact, so that standard Gibbs distribution smoothing penalties are reasonable as additional constraints on the attenuation image. Hence, estimation may be considerably better conditioned with than with . In this work, we investigate the utility of PET emission data for correcting artifacts of limited spatial extent in CT-based 511-keV attenuation images.
MR-based Motion Correction for PET Imaging - NCBI - NIH
Bella is having some behavior challenges. Someone recommended the Pet Corrector Stop Barking can. It "emits a loud hissing sound to stop unwanted behaviors" according to the packaging. Not sure if it's a good option for a rescue when we don't know her history. Any experience with this product? With training? What do you think? Use or return?
I got it here -
Practical PET Respiratory Motion Correction in Clinical PET/MR.