Sign determination methods for the respiratory signal in data-driven PET gating
Respiratory motion correction in PET imaging is of crucial importance in the thorax. On current scanners, respiratory gating is performed based on the signal of an external device. Recent methods extract a respiratory signal from raw PET data exploiting data driven (DD) methods, avoiding the use of external equipment and having potential increased fidelity to internal motion. However, many of these DD methods determine the signal up to an arbitrary scale factor: it is not known if maxima and minima in the signal are related to end-inspiration or end-expiration states, possibly causing inaccurate motion correction. The aim of this work is to propose methods based on PCA and compare their performance on clinical data with other existing methods based on registration of reconstructed gates.