TY - JOUR
T1 - Cardiac material markers from tagged MR images
AU - Kerwin, William S.
AU - Prince, Jerry L.
N1 - Funding Information:
The authors thank Elliot McVeigh for data and insight, Gerard Meyer for consultation on algorithm convergence, Christina Vlattas for the stereo pair generation program and Nael Osman for upgrading the LV simulator. This work was supported by NIH grants (R01-HL45090; PI Elias Zerhouni; and R29-HL47405; PI Jerry Prince), an NSF grant (MIP93-50336; PI Jerry Prince), and a Whitaker Foundation Graduate Fellowship, held by the first author.
PY - 1998
Y1 - 1998
N2 - Tagged magnetic resonance imaging (MRI) has shown great promise in non-invasive analysis of heart motion. To replace implanted markers as a gold standard, however, tagged MRI must be able to track a sparse set of material points, so-called material markers, with high accuracy. This paper presents a new method for generating accurate motion estimates over a sparse set of material points using standard, parallel-tagged MR images. Each tracked point is located at the intersection of three tag surfaces, each of which is estimated using a thin-plate spline. The intersections are determined by an iterative alternating projections algorithm for which a proof of convergence is provided. The resulting data sets are compatible with applications developed to exploit implanted marker data. One set of these material markers from a normal human volunteer is examined in detail using several methods to visualize the markers. Numerical results that include additional studies are also discussed. Finally, an error analysis is presented using a computer-simulated left ventricle for which material markers are tracked with an RMS error of ∼0.2 mm for typical imaging parameters and noise levels.
AB - Tagged magnetic resonance imaging (MRI) has shown great promise in non-invasive analysis of heart motion. To replace implanted markers as a gold standard, however, tagged MRI must be able to track a sparse set of material points, so-called material markers, with high accuracy. This paper presents a new method for generating accurate motion estimates over a sparse set of material points using standard, parallel-tagged MR images. Each tracked point is located at the intersection of three tag surfaces, each of which is estimated using a thin-plate spline. The intersections are determined by an iterative alternating projections algorithm for which a proof of convergence is provided. The resulting data sets are compatible with applications developed to exploit implanted marker data. One set of these material markers from a normal human volunteer is examined in detail using several methods to visualize the markers. Numerical results that include additional studies are also discussed. Finally, an error analysis is presented using a computer-simulated left ventricle for which material markers are tracked with an RMS error of ∼0.2 mm for typical imaging parameters and noise levels.
KW - Cardiac motion
KW - MRI tagging
KW - Magnetic resonance imaging
KW - Thin-plate spline
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U2 - 10.1016/S1361-8415(98)80015-7
DO - 10.1016/S1361-8415(98)80015-7
M3 - Article
C2 - 10072201
AN - SCOPUS:0032241859
SN - 1361-8415
VL - 2
SP - 339
EP - 353
JO - Medical image analysis
JF - Medical image analysis
IS - 4
ER -