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Content Provider | IEEE Xplore Digital Library |
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Author | King, Michael A. Dey, Joyoni McNamara, Joseph E. Johnson, Karen Mitra, Joyeeta Pretorius, Hendrik Lehovich, Andre Gu, Songxiang Walvick, Ronn Sun, Yanping Ford, J. Chetley |
Copyright Year | 2008 |
Description | Author affiliation: Department of Radiology, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, 01655, USA (King, Michael A.; Dey, Joyoni; McNamara, Joseph E.; Johnson, Karen; Mitra, Joyeeta; Pretorius, Hendrik; Lehovich, Andre; Walvick, Ronn; Sun, Yanping; Ford, J. Chetley) |
Abstract | We have developed a visual-tracking-system (VTS) which uses stereo-imaging to track the motion of markers on patients during cardiac SPECT imaging with the goal of using the tracked motion to correct for patient motion. The aim of this study is to determine using MRI in volunteers if the rigid-body-motion (RBM) model can be used to predict the motion of the heart within the chest from the motion of markers on the surface of the chest. Our methodology for investigating body-motion separate from the influence of respiration is to have the volunteer hold their breath during the acquisition of a sequence of 2 sets of EKG-triggered MRI sagittal slices covering the heart, the first set pre-motion and the second post-motion. We link the acquisition of these studies such that this process takes ∼ 45 seconds from the initiation of the first acquisition till the volunteer is given the instruction to resume breathing. An analysis of the combined motion of the individual markers on the chest is used to obtain an estimate of the six-degree-of-freedom (6DOF) RBM motion of the volunteer. The motion of the heart within the slices is estimated by semi-automatic 3D segmentation of the heart region in the second set of slices and subsequent registration of this region to the first set of slices. Studies in which the volunteer did not intentionally move between the 2 acquisitions were used to establish a baseline for agreement between the 2 methods of motion estimation for small motions. The agreement between the VTS and MRI estimates of motion was good in this “no-motion” case with a maximum difference of ≪ 5 mm between the 2 for any translation component, and ≪2 deg for any rotational component. With body translations such as an axial-slide which might be expected to approximate RBM, the maximum difference in any translation estimate was also good being ≪ 6 mm, and the maximum rotational difference was ≪ 2.5 deg. Application of the VTS to correct non-RBM such as a counter-clock-wise (CCW) twist at the shoulders with the hips fixed, decreased the magnitude of the misalignment caused by motion but not to the same extent as for the previous classes of motion. The maximum differences for this class of motions was ≪11 mm for translation and ≪ 4.5 deg for angular. Thus use of the RBM model with VTS predictions of heart motion for use in motion correction during reconstruction should decrease the extent of artifacts for the types of patient motion studied, but less so for those which are better modeled as non-RBM. |
Starting Page | 4306 |
Ending Page | 4310 |
File Size | 5960799 |
Page Count | 5 |
File Format | |
ISBN | 9781424427147 |
ISSN | 10957863 |
DOI | 10.1109/NSSMIC.2008.4774236 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2008-10-19 |
Publisher Place | Germany |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Magnetic resonance imaging Heart Motion estimation Biomedical imaging Tracking Medical diagnostic imaging Cameras Sun Predictive models Motion analysis |
Content Type | Text |
Resource Type | Article |
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