Cardiac material markers from tagged MR images

William S. Kerwin; Jerry L. Prince

doi:10.1016/S1361-8415(98)80015-7

Cardiac material markers from tagged MR images

William S. Kerwin, Jerry L. Prince

Whiting School of Engineering

Research output: Contribution to journal › Article › peer-review

50 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	339-353
Number of pages	15
Journal	Medical image analysis
Volume	2
Issue number	4
DOIs	https://doi.org/10.1016/S1361-8415(98)80015-7
State	Published - 1998

Keywords

Cardiac motion
MRI tagging
Magnetic resonance imaging
Thin-plate spline

ASJC Scopus subject areas

Radiological and Ultrasound Technology
Radiology Nuclear Medicine and imaging
Computer Vision and Pattern Recognition
Health Informatics
Computer Graphics and Computer-Aided Design

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10.1016/S1361-8415(98)80015-7

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@article{299bbd6262434bc5884e69726998a218,

title = "Cardiac material markers from tagged MR images",

abstract = "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.",

keywords = "Cardiac motion, MRI tagging, Magnetic resonance imaging, Thin-plate spline",

author = "Kerwin, {William S.} and Prince, {Jerry L.}",

note = "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.",

year = "1998",

doi = "10.1016/S1361-8415(98)80015-7",

language = "English (US)",

volume = "2",

pages = "339--353",

journal = "Medical image analysis",

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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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Cardiac material markers from tagged MR images

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Keywords

ASJC Scopus subject areas

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