Motion Correction of PET Data with a Joint Registration Functional for Multi-Modal Data

摘要

Respiratory motion is a known image degradation factor in PET imaging. A lot of research has been done in the field of motion correction of PET data. With the recent development of full-body PET/MRI, the morphological data provided by MRI is a promising source of motion information. MRI-based motion correction of PET data is a topic of active research. These approaches,however, usually do not take into account the available information provided by PET data. In this work we show results of a phantom study using a joint motion estimation approach that incorporates motion information from both PéT and MRI data.