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Spline-based cardiac motion tracking using velocity-encoded magnetic resonance imaging.

Bergvall, Erik LU ; Hedström, Erik LU ; Markenroth Bloch, Karin LU ; Arheden, Håkan LU and Sparr, Gunnar LU (2008) In IEEE Transactions on Medical Imaging 27(8). p.1045-1053
Abstract
This paper deals with the problem of tracking cardiac motion and deformation using velocity-encoded magnetic resonance imaging. We expand upon an earlier described method and fit a spatiotemporal motion model to measured velocity data. We investigate several different spatial elements both qualitatively and quantitatively using phantom measurements and data from human subjects. In addition, we also use optical flow estimation by the Horn-Schunk method as complementary data in regions where the velocity measurements are noisy. Our results show that it is possible to obtain good motion tracking accuracy in phantoms with relatively few spatial elements, if the type of element is properly chosen. The use of optical flow can correct some... (More)
This paper deals with the problem of tracking cardiac motion and deformation using velocity-encoded magnetic resonance imaging. We expand upon an earlier described method and fit a spatiotemporal motion model to measured velocity data. We investigate several different spatial elements both qualitatively and quantitatively using phantom measurements and data from human subjects. In addition, we also use optical flow estimation by the Horn-Schunk method as complementary data in regions where the velocity measurements are noisy. Our results show that it is possible to obtain good motion tracking accuracy in phantoms with relatively few spatial elements, if the type of element is properly chosen. The use of optical flow can correct some measurement artifacts but may give an underestimation of the magnitude of the deformation. In human subjects the different spatial elements perform quantitatively in a similar way but qualitative differences exists, as shown by a semiquantitative visual scoring of the different methods. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Heart: physiology, Heart: anatomy & histology, Image Enhancement: methods, Image Interpretation, Magnetic Resonance Imaging: methods, Computer-Assisted: methods, Movement: physiology, Pattern Recognition, Automated: methods
in
IEEE Transactions on Medical Imaging
volume
27
issue
8
pages
1045 - 1053
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • wos:000258260000005
  • pmid:18672422
  • scopus:48549084217
ISSN
1558-254X
DOI
10.1109/TMI.2008.917244
language
English
LU publication?
yes
id
44586e5c-5748-45c8-9b6a-0ebc4c3292e3 (old id 1223560)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/18672422?dopt=Abstract
date added to LUP
2008-09-10 11:56:31
date last changed
2017-08-27 04:22:24
@article{44586e5c-5748-45c8-9b6a-0ebc4c3292e3,
  abstract     = {This paper deals with the problem of tracking cardiac motion and deformation using velocity-encoded magnetic resonance imaging. We expand upon an earlier described method and fit a spatiotemporal motion model to measured velocity data. We investigate several different spatial elements both qualitatively and quantitatively using phantom measurements and data from human subjects. In addition, we also use optical flow estimation by the Horn-Schunk method as complementary data in regions where the velocity measurements are noisy. Our results show that it is possible to obtain good motion tracking accuracy in phantoms with relatively few spatial elements, if the type of element is properly chosen. The use of optical flow can correct some measurement artifacts but may give an underestimation of the magnitude of the deformation. In human subjects the different spatial elements perform quantitatively in a similar way but qualitative differences exists, as shown by a semiquantitative visual scoring of the different methods.},
  author       = {Bergvall, Erik and Hedström, Erik and Markenroth Bloch, Karin and Arheden, Håkan and Sparr, Gunnar},
  issn         = {1558-254X},
  keyword      = {Heart: physiology,Heart: anatomy & histology,Image Enhancement: methods,Image Interpretation,Magnetic Resonance Imaging: methods,Computer-Assisted: methods,Movement: physiology,Pattern Recognition,Automated: methods},
  language     = {eng},
  number       = {8},
  pages        = {1045--1053},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Transactions on Medical Imaging},
  title        = {Spline-based cardiac motion tracking using velocity-encoded magnetic resonance imaging.},
  url          = {http://dx.doi.org/10.1109/TMI.2008.917244},
  volume       = {27},
  year         = {2008},
}