Sentence examples for motion correction approaches from inspiring English sources

In current motion correction approaches in PET-MRI, motion information from PET data is neglected.

In contrast to other motion correction approaches, no second imaging modality or additional hardware is required.

The objective of this work is to use a generalized reconstruction by inversion of coupled systems (GRICS) approach, previously used for PET/MR respiratory motion correction, combined with a cardiac phase signal and a reconstruction incorporated PET motion correction approach in order to reconstruct motion free images from dual gated PET acquisitions.

The motion correction approach does not use a fixed reference volume, both volumes are transformed.

Finally, one can use the PET data itself to perform motion correction although these approaches are limited due to noise [23, 24].

Motion correction using this approach encompassed a rotation of 18° around the principle axis of the cylindrical phantom between two scans.

However, no approach to motion correction is perfect; it is therefore important also to note that, while common variation in data quality (e.g., due to head motion) could theoretically contribute to correlation between signals, we cannot envisage a mechanism by which the specificity of the relationships we report could be explained by such factors.

Intensity based methods do not need calculation intensive bulk motion correction algorithms as do phase sensitive approaches.

These results indicate that the groupwise registration approach can provide improved motion correction of dynamic brain PET data as compared to frame-by-frame registration approaches for receptor occupancy studies.

Despite a plethora of options to help address respiratory motion correction in PET, no clear optimal approach has emerged.

Functional data were motion corrected offline with the Siemens motion correction protocol.