Abstract
Respiratory motion is known to degrade image quality in PET imaging. The necessary acquisition time of several minutes per bed position will inevitably lead to a blurring effect due to organ motion. A lot of research has been done with regards to motion correction of PET data. As full-body PET-MRI became available recently, the anatomical data provided by MRI is a promising source of motion information. Current PET-MRI-based motion correction approaches, however, do not take into account the available information provided by PET data. PET data, though, may add valuable additional information to increase motion estimation robustness and precision.In this work we propose a registration functional that is capable of performing motion detection in gated data of two modalities simultaneously. Evaluation is performed using phantom data. We demonstrate that performing a joint registration of both modalities does improve registration accuracy and PET image quality.
Highlights
Respiratory motion is known to impair image quality as well as quantification in positron emission tomography (PET) [1]
We demonstrate that performing a joint registration of both modalities does improve registration accuracy and PET image quality
For all three lesion regions a significant decrease in averaged endpoint error (AEE) can be observed
Summary
Respiratory motion is known to impair image quality as well as quantification in positron emission tomography (PET) [1]. As the acquisition of PET takes several minutes per bed position, organ motion due to respiration cannot be avoided and will result in blurred images. Gating reduces the amount of motion contained within each gate to a large extent, yet at the expense of reduced statistics and thereby image quality [2,3]. Motion between gates can be estimated and subsequently be used to correct PET data for motion, resulting in a single image volume with reduced motion artifacts and full statistics. Various approaches for motion estimation of gated PET data have been studied, including optical flow [4], B-spline based methods [5], and registration methods including mass-preservation [6]
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