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Automatic registration of myocardial perfusion images

Svensson, Daniel LU (2012) In Master Thesis in Mathematical Science FMA820 20121
Mathematics (Faculty of Technology) and Numerical Analysis
Abstract
Myocardial perfusion is an indicator of heart health that can be used to locate damaged areas of the heart. It can be measured by an imaging modality such as magnetic resonance imaging (MRI).

When measuring myocardial perfusion in a living human we must align images
over time to correct for motion caused by breathing. In this thesis we will introduce a version of the normalized gradient fields similarity method, modifed to improve noise robustness and decrease computational complexity. Furthermore we will use a segmentation in the reference time-frame as a priori information.

The results of this thesis is the development of a registration method that aligns the myocardium in perfusion MRI images. The myocardial alignment, measured... (More)
Myocardial perfusion is an indicator of heart health that can be used to locate damaged areas of the heart. It can be measured by an imaging modality such as magnetic resonance imaging (MRI).

When measuring myocardial perfusion in a living human we must align images
over time to correct for motion caused by breathing. In this thesis we will introduce a version of the normalized gradient fields similarity method, modifed to improve noise robustness and decrease computational complexity. Furthermore we will use a segmentation in the reference time-frame as a priori information.

The results of this thesis is the development of a registration method that aligns the myocardium in perfusion MRI images. The myocardial alignment, measured by the Dice coefficient, increased from 0.79+-0.11 before registration to 0.89+-0.028 after registration. The resulting perfusion curves looks like we would expect from previous studies of myocardial perfusion. (Less)
Please use this url to cite or link to this publication:
author
Svensson, Daniel LU
supervisor
organization
course
FMA820 20121
year
type
H1 - Master's Degree (One Year)
subject
publication/series
Master Thesis in Mathematical Science
report number
LUTFMA-3231-2012
ISSN
1404-6342
other publication id
2012:E21
language
English
id
3124652
date added to LUP
2014-11-03 15:10:42
date last changed
2014-11-03 15:10:42
@misc{3124652,
  abstract     = {Myocardial perfusion is an indicator of heart health that can be used to locate damaged areas of the heart. It can be measured by an imaging modality such as magnetic resonance imaging (MRI).

When measuring myocardial perfusion in a living human we must align images
over time to correct for motion caused by breathing. In this thesis we will introduce a version of the normalized gradient fields similarity method, modifed to improve noise robustness and decrease computational complexity. Furthermore we will use a segmentation in the reference time-frame as a priori information.

The results of this thesis is the development of a registration method that aligns the myocardium in perfusion MRI images. The myocardial alignment, measured by the Dice coefficient, increased from 0.79+-0.11 before registration to 0.89+-0.028 after registration. The resulting perfusion curves looks like we would expect from previous studies of myocardial perfusion.},
  author       = {Svensson, Daniel},
  issn         = {1404-6342},
  language     = {eng},
  note         = {Student Paper},
  series       = {Master Thesis in Mathematical Science},
  title        = {Automatic registration of myocardial perfusion images},
  year         = {2012},
}