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Cardiac MRI segmentation with conditional random fields

Thesis (PhD)-- Stellenbosch University, 2013. / ENGLISH ABSTRACT: This dissertation considers automatic segmentation of the left cardiac ventricle in short
axis magnetic resonance images. The presence of papillary muscles near the endocardium
border makes simple threshold based segmentation difficult.
The endo- and epicardium are modelled as two series of radii which are inter-related using
features describing shape and motion. Image features are derived from edge information
from human annotated images. The features are combined within a Conditional Random
Field (CRF) – a discriminatively trained probabilistic model. Loopy belief propagation
is used to infer segmentations when an unsegmented video sequence is given. Powell’s
method is applied to find CRF parameters by minimising the difference between ground
truth annotations and the inferred contours. We also describe how the endocardium centre
points are calculated from a single human-provided centre point in the first frame, through
minimisation of frame alignment error.
We present and analyse the results of segmentation. The algorithm exhibits robustness
against inclusion of the papillary muscles by integrating shape and motion information.
Possible future improvements are identified. / AFRIKAANSE OPSOMMING: Hierdie proefskrif bespreek die outomatiese segmentasie van die linkerhartkamer in kortas
snit magnetiese resonansie beelde. Die teenwoordigheid van die papillêre spiere naby
die endokardium grens maak eenvoudige drumpel gebaseerde segmentering moeilik.
Die endo- en epikardium word gemodelleer as twee reekse van die radiusse wat beperk
word deur eienskappe wat vorm en beweging beskryf. Beeld eienskappe word afgelei van
die rand inligting van mens-geannoteerde beelde. Die funksies word gekombineer binne ’n
CRF (Conditional Random Field) – ’n diskriminatief afgerigte waarskynlikheidsverdeling.
“Loopy belief propagation” word gebruik om segmentasies af te lei wanneer ’n ongesegmenteerde
video verskaf word. Powell se metode word toegepas om CRF parameters te
vind deur die minimering van die verskil tussen mens geannoteerde segmentasies en die
afgeleide kontoere. Ons beskryf ook hoe die endokardium se middelpunte bereken word
vanaf ’n enkele mens-verskafte middelpunt in die eerste raam, deur die minimering van ’n
raambelyningsfout.
Ons analiseer die resultate van segmentering. Die algoritme vertoon robuustheid teen
die insluiting van die papillêre spiere deur die integrasie van inligting oor die vorm en die
beweging. Moontlike toekomstige verbeterings word geïdentifiseer.

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/85847
Date12 1900
CreatorsDreijer, Janto Frederick
ContributorsHerbst, B. M., Du Preez, J. A., Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering .
PublisherStellenbosch : Stellenbosch University
Source SetsSouth African National ETD Portal
Languageen_ZA
Detected LanguageUnknown
TypeThesis
Formatxiv, 87 p. : ill.
RightsStellenbosch University

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