Editorial: Derivation of respiratory gating signals from ECG signals

Klein, Ran

doi:10.1007/s12350-015-0192-6

Cited by 3 publications

(2 citation statements)

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“…Image decomposition has been used on dynamic nuclear medical images in the past. For example, several studies used factor analysis of dynamic PET images to create factor images and TACs to estimate parameters for kinetic modelling [61][62][63][64]. Another study investigated two factor analysis of dynamic structures (FADS) methods for use of semiautomatic estimation of activity in cardiac dynamic SPECT images [67].…”

Section: Resultsmentioning

confidence: 99%

“…As with dynamic imaging static imaging for MPI interpretation is performed over long time intervals (e.g. 6 min) in which patient motion can manifest itself as a directional blur which can produce uptake deficits consistent with CAD [62]. Thus this algorithm can have important QC implications on the most commonly used procedure in nuclear medicine.…”

Section: Other Applicationsmentioning

confidence: 99%

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Motion Detection in Dynamic Cardiac Positron Emission Tomography Images

Sritharan¹

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Dynamic PET is being increasingly utilized to quantify myocardial blood flow, leading to improved diagnostic and prognostic value for the management of coronary artery disease. MBF quantification assumes constant positioning of anatomical structures throughout image acquisition. This assumption is violated in the presence of patient motion and heart motion. This thesis discusses methods for motion detection in dynamic cardiac 82 Rb PET images.First, we determined if positron-emitting fiducial markers can be used as surrogate markers for heart motion in dynamic PET images. Second, algorithms were developed to track fiducial marker motion. Lastly, we tested the idea that principle component analysis may be able to detect heart motion in dynamic 82 Rb PET based on patterns in the residue image.Overall, this thesis proposes low-cost, fast, and vendor independent post-reconstruction dynamic 82 Rb PET motion detection methods which can be used to detect motion in a clinical environment as a quality assurance tool.ii Acknowledgements I would like to thank:Dr. Ran Klein for giving me this amazing opportunity. This work would not be possible without your help. I express my appreciation for your support, guidance and encouragement over the past few years.

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