Vessel segmentation for time resolved phase contrast MRI
(2013) In Master's Theses in Mathematical Sciences FMA820 20122Mathematics (Faculty of Engineering)
- Abstract
- Quantication of cardiovascular flow and blood volumes are useful tools in diagnosing cardiovascular disease such as congenital heart defects and different kinds of valve leakage. Medical imaging techniques enables non-invasive analysis of anatomy and physiology. In order to perform flow quantification from medical image sequences, the boundaries of the
vessels of interest are usually delineated manually by medical professionals. This is a time consuming process and the result depends, to a high degree, on user experience. This thesis presents an automated vessel segmentation method for the main vessels around the
heart from velocity encoded Magnetic Resonance Imaging sequences. The proposed method only require a manual delineation in one... (More) - Quantication of cardiovascular flow and blood volumes are useful tools in diagnosing cardiovascular disease such as congenital heart defects and different kinds of valve leakage. Medical imaging techniques enables non-invasive analysis of anatomy and physiology. In order to perform flow quantification from medical image sequences, the boundaries of the
vessels of interest are usually delineated manually by medical professionals. This is a time consuming process and the result depends, to a high degree, on user experience. This thesis presents an automated vessel segmentation method for the main vessels around the
heart from velocity encoded Magnetic Resonance Imaging sequences. The proposed method only require a manual delineation in one image. The algorithm is based on an active contour, using the Euler-Lagrange equation together with internal and external forces designed from
a set of fundamental assumptions regarding vessel shape and behaviour. More specically, constraints were applied to the geometrical shape and elasticity of a vessel. Validation of the method was performed by comparing the detected stroke volume with manual delineation, and also by measuring the segmentation overlapping of the two methods. On a test set of 20 patients, 19 resulted in excellent segmentation agreement with manual delineations, with a mean Dice coefficient over 0.8. However, performance instability was observed when changing the values of two algorithm parameters, and one of the patients in the set constantly
resulted in segmentation failure for all tested parameter combinations. The relative variability in stroke volume between the proposed algorithm and manual delineations was, at best, 6 +- 3.6%. This is comparable to the interobserver variability from a previous physiological
study 1 of 3 +- 4%, which indicates the potential of the suggested method if improvements in robustness and stability is implemented. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/3802951
- author
- Bidhult, Sebastian LU
- supervisor
- organization
- alternative title
- Kärlsegmentering i tidsupplösta MRI sekvenser
- course
- FMA820 20122
- year
- 2013
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Medical image analysis, Active contours, Euler Lagrange equations, Expectation Maximization algorithm.
- publication/series
- Master's Theses in Mathematical Sciences
- report number
- LUTFMA-3243-2013
- ISSN
- 1404-6342
- other publication id
- E12
- language
- English
- id
- 3802951
- date added to LUP
- 2013-09-20 12:16:59
- date last changed
- 2013-09-20 12:16:59
@misc{3802951,
abstract = {{Quantication of cardiovascular flow and blood volumes are useful tools in diagnosing cardiovascular disease such as congenital heart defects and different kinds of valve leakage. Medical imaging techniques enables non-invasive analysis of anatomy and physiology. In order to perform flow quantification from medical image sequences, the boundaries of the
vessels of interest are usually delineated manually by medical professionals. This is a time consuming process and the result depends, to a high degree, on user experience. This thesis presents an automated vessel segmentation method for the main vessels around the
heart from velocity encoded Magnetic Resonance Imaging sequences. The proposed method only require a manual delineation in one image. The algorithm is based on an active contour, using the Euler-Lagrange equation together with internal and external forces designed from
a set of fundamental assumptions regarding vessel shape and behaviour. More specically, constraints were applied to the geometrical shape and elasticity of a vessel. Validation of the method was performed by comparing the detected stroke volume with manual delineation, and also by measuring the segmentation overlapping of the two methods. On a test set of 20 patients, 19 resulted in excellent segmentation agreement with manual delineations, with a mean Dice coefficient over 0.8. However, performance instability was observed when changing the values of two algorithm parameters, and one of the patients in the set constantly
resulted in segmentation failure for all tested parameter combinations. The relative variability in stroke volume between the proposed algorithm and manual delineations was, at best, 6 +- 3.6%. This is comparable to the interobserver variability from a previous physiological
study 1 of 3 +- 4%, which indicates the potential of the suggested method if improvements in robustness and stability is implemented.}},
author = {{Bidhult, Sebastian}},
issn = {{1404-6342}},
language = {{eng}},
note = {{Student Paper}},
series = {{Master's Theses in Mathematical Sciences}},
title = {{Vessel segmentation for time resolved phase contrast MRI}},
year = {{2013}},
}