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Quantifying effects of deformable CT-MR registration
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Kvantifiering av effekter i deformabel MR-CT bildregistrering. (Swedish)
Abstract [en]

Rigid image registration is an important part of many medical applications. In order to make correct decisions from the registration process the un-certainty of the results should be included. In this thesis a framework for estimating and visualising the spatial uncertainty of rigid image registration without groundtruth measurements is presented. The framework uses a deformable registration algorithm to estimate the errors and a groupwise registration for collocating multiple image sets to generate multiple realisations of the error field. A mean and covariance field are then generated which allows a characterisation of the error field. The framework is used to evaluate errors in CT-MR registration and a statistically significant bias field is detected using random field theory. It is also established that B-spline registration of CT images to themselves exhibit a bias.

Abstract [sv]

Rigid bildregistrering är en viktig del i många medicinska system, för beslut som fattas med hjälp av bildregistrering så är det viktigt att kunna bedöma osäkerheten i registrerings processen. I denna uppsats presenteras en metod för att skatta och visualisera osäkerheten i rigid bildregistrering utan tillgång till det sanna felet. Metoden använder en deformerbar registrerings algorithm för att skatta felen och en gruppvis registrering för att samlokalisera flera bildmängder, med syfte att skapa flera utfall från fel-fördelningen. Ett medelvärdes och varians fält skapas därefter vilket tillåter en karakterisering av felet i varje punkt. Metoden används för att utvärdera felen i CT-MR registrering och ett statistiskt säkerställt systematiskt fel bekräftas med hjälp av ”random field theory”. Det etableras också att B-spline registrering genererar systematiska deformationer när en CT bild registreras till sig själv

Place, publisher, year, edition, pages
2016.
Series
TRITA-MAT-E, 2016:25
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-188346OAI: oai:DiVA.org:kth-188346DiVA: diva2:938521
External cooperation
Elekta
Subject / course
Mathematical Statistics
Educational program
Master of Science - Mathematics
Supervisors
Examiners
Available from: 2016-06-17 Created: 2016-06-09 Last updated: 2016-06-17Bibliographically approved

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CiteExportLink to record
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Citation style
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