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Analysis of Velocity Encoded Images --- With Applications in Cardiac MRI

Bergvall, Erik LU (2008)
Abstract
The topic of the thesis is the analysis of velocity encoded medical images, acquired using magnetic resonance imaging or other means. The application in mind is to use such data to determine the motion and deformation of the human heart, which is of clinical and physiological interest. As the velocity measurements are noisy and degraded, an important issue is the regularization of the measurements to obtain reliable estimates of the motion and deformation of the heart. Several methods for motion tracking are proposed and evaluated in the thesis. The methods can be classified either as Lagrangian, where the spatiotemporal deformation is explicitly constructed and adapted to measured data, or as Eulerian, where the velocity data is... (More)
The topic of the thesis is the analysis of velocity encoded medical images, acquired using magnetic resonance imaging or other means. The application in mind is to use such data to determine the motion and deformation of the human heart, which is of clinical and physiological interest. As the velocity measurements are noisy and degraded, an important issue is the regularization of the measurements to obtain reliable estimates of the motion and deformation of the heart. Several methods for motion tracking are proposed and evaluated in the thesis. The methods can be classified either as Lagrangian, where the spatiotemporal deformation is explicitly constructed and adapted to measured data, or as Eulerian, where the velocity data is regularized as a pre-processing step before temporal integration of the data is made. The methods are constructed using tools such as Fourier analysis, spline mappings and filtering using partial differential equations. It is concluded that Lagrangian methods are preferable due to better performance and flexibility. Another topic of the thesis is the generation of spatiotemporal models of the shape and motion of an object. A method that generates models that are physically admissible is presented. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Yang, Guang-Zhong, Imperial College of Science, Technology, and Medicine, London, UK
organization
publishing date
type
Thesis
publication status
published
subject
defense location
Lecture hall MH:C, Centre for Mathematical Sciences, Lund university, Faculty of Engineering
defense date
2008-06-09 13:15
ISBN
987-91-631-8997-5
language
English
LU publication?
yes
id
941d670d-8c66-49b8-b967-5347f6517fcb (old id 1058474)
date added to LUP
2008-05-13 15:22:06
date last changed
2016-09-19 08:45:17
@misc{941d670d-8c66-49b8-b967-5347f6517fcb,
  abstract     = {The topic of the thesis is the analysis of velocity encoded medical images, acquired using magnetic resonance imaging or other means. The application in mind is to use such data to determine the motion and deformation of the human heart, which is of clinical and physiological interest. As the velocity measurements are noisy and degraded, an important issue is the regularization of the measurements to obtain reliable estimates of the motion and deformation of the heart. Several methods for motion tracking are proposed and evaluated in the thesis. The methods can be classified either as Lagrangian, where the spatiotemporal deformation is explicitly constructed and adapted to measured data, or as Eulerian, where the velocity data is regularized as a pre-processing step before temporal integration of the data is made. The methods are constructed using tools such as Fourier analysis, spline mappings and filtering using partial differential equations. It is concluded that Lagrangian methods are preferable due to better performance and flexibility. Another topic of the thesis is the generation of spatiotemporal models of the shape and motion of an object. A method that generates models that are physically admissible is presented.},
  author       = {Bergvall, Erik},
  isbn         = {987-91-631-8997-5},
  language     = {eng},
  title        = {Analysis of Velocity Encoded Images --- With Applications in Cardiac MRI},
  year         = {2008},
}