The strategy of elastic Motion corrections

The Motion in PET studies degrades image quality and introduces bias and partial volume artifacts, which are critical considerations for high resolution scanners. There are two kinds of motion, such as rigid (e.g. brain) and nonrigid (e.g. respiratory and cardiac). Elastic motion correction is neede...

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Bibliographic Details
Main Authors: Inki Hong, Furst, Sebastian, Jones, Judson, Casey, Michael
Format: Conference Proceeding
Language:English
Subjects:
Adaptive optics
Electromagnetic compatibility
Image motion analysis
Image reconstruction
Logic gates
Optical imaging
Positron emission tomography
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Summary:The Motion in PET studies degrades image quality and introduces bias and partial volume artifacts, which are critical considerations for high resolution scanners. There are two kinds of motion, such as rigid (e.g. brain) and nonrigid (e.g. respiratory and cardiac). Elastic motion correction is needed for nonrigid-motion artifacts. There are three basic steps in this approach, acquisition of a gating signal, extraction of elastic motion, and reconstruction. First, the gating signal is acquired by hardware, such as EKG, Belt, RPM, and MR, or from the analysis PET list-mode data. This is the most important step because, if the data are not properly gated, it is not possible to extract accurate motion vectors. Second, motion information for each gated signal can be extracted from CT for PET/CT or MRI for MR/PET. The motion information can also be extracted from the PET data themselves, and optical flow methods have been shown to be very robust in this approach. Third, image reconstruction with motion correction is commonly performed through summing gated images in a common reference frame. However, the combination of processed data with poor statistics generally results in high image noise and bias in the final image. A better approach is to incorporate motion information into the reconstruction process itself. Motion-correction reconstruction has been shown to produce less noise and bias in the image domain than conventional summing methods. The ideal method for motion correction in emission data should produce quantitatively accurate images which retain noise properties of conventional images, all while introducing no additional subject dose or inconvenience.
ISSN:1082-3654
2577-0829
DOI:10.1109/NSSMIC.2013.6829009