
Proceedings Paper
Creation of 3D digital anthropomorphic phantoms which model actual patient non-rigid body motion as determined from MRI and position tracking studies of volunteersFormat | Member Price | Non-Member Price |
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Paper Abstract
Patient motion can cause artifacts, which can lead to difficulty in interpretation. The purpose of this study is to create 3D
digital anthropomorphic phantoms which model the location of the structures of the chest and upper abdomen of human
volunteers undergoing a series of clinically relevant motions. The 3D anatomy is modeled using the XCAT phantom and
based on MRI studies. The NURBS surfaces of the XCAT are interactively adapted to fit the MRI studies. A detailed
XCAT phantom is first developed from an EKG triggered Navigator acquisition composed of sagittal slices with a 3 x 3
x 3 mm voxel dimension. Rigid body motion states are then acquired at breath-hold as sagittal slices partially covering
the thorax, centered on the heart, with 9 mm gaps between them. For non-rigid body motion requiring greater sampling,
modified Navigator sequences covering the entire thorax with 3 mm gaps between slices are obtained. The structures of
the initial XCAT are then adapted to fit these different motion states. Simultaneous to MRI imaging the positions of
multiple reflective markers on stretchy bands about the volunteer's chest and abdomen are optically tracked in 3D via
stereo imaging. These phantoms with combined position tracking will be used to investigate both imaging-data-driven
and motion-tracking strategies to estimate and correct for patient motion. Our initial application will be to cardiacperfusion
SPECT imaging where the XCAT phantoms will be used to create patient activity and attenuation distributions
for each volunteer with corresponding motion tracking data from the markers on the body-surface. Monte Carlo methods
will then be used to simulate SPECT acquisitions, which will be used to evaluate various motion estimation and
correction strategies.
Paper Details
Date Published: 1 March 2011
PDF: 8 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 79642G (1 March 2011); doi: 10.1117/12.878193
Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes III, Editor(s)
PDF: 8 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 79642G (1 March 2011); doi: 10.1117/12.878193
Show Author Affiliations
C. M. Connolly, Univ. of Massachusetts Medical School (United States)
A. Konik, Univ. of Massachusetts Medical School (United States)
P. K. R. Dasari, Univ. of Massachusetts Medical School (United States)
P. Segars, Duke Univ. Medical School (United States)
A. Konik, Univ. of Massachusetts Medical School (United States)
P. K. R. Dasari, Univ. of Massachusetts Medical School (United States)
P. Segars, Duke Univ. Medical School (United States)
S. Zheng, Univ. of Massachusetts Medical School (United States)
K. L. Johnson, Univ. of Massachusetts Medical School (United States)
J. Dey, Univ. of Massachusetts Medical School (United States)
M. A. King, Univ. of Massachusetts Medical School (United States)
K. L. Johnson, Univ. of Massachusetts Medical School (United States)
J. Dey, Univ. of Massachusetts Medical School (United States)
M. A. King, Univ. of Massachusetts Medical School (United States)
Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes III, Editor(s)
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