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MRI Signals Simulation for Validation of a New Microvascular Characterization
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Simulering av MR-signaler för validering av en ny mikrovaskulär karakterisering (Swedish)
Abstract [en]

Conventional MRI techniques are not convenient when it comes to study cerebral microvascularization due to the length of the scans needed. A technique called Magnetic Resonance Fingerprinting (MRF) is an excellent candidate to solve this problem as it requires much shorter scan durations. It relies on the ability to simulate a large amount of MR signals coming from virtual voxels of controlled parameters. This thesis addresses this simulation aspect. Coding implements were made on a simulation tool called MRVox2D to improve its realism and flexibility. In particular, the voxel geometry generation algorithm was reworked to allow simulations in line with what can be obtained from a scanner. Having a variable vessel size within a simulated voxel is now possible and the Vessel Size Index can be computed accordingly. MRF applications were made on mice data using these implementations, showing encouraging but perfectible results.

Abstract [sv]

Konventionella MR-tekniker är inte praktiska när det gäller att studera cerebral mikrovaskularisering på grund av längden på de skanningar som krävs. En teknik som kallas Magnetic Resonance Fingerprinting (MRF) är en utmärkt kandidat för att lösa detta problem eftersom den kräver mycket kortare skanningsvaraktigheter. Metoden baseras på förmågan att simulera en stor mängd MR-signaler som kommer från virtuella voxels av kontrollerade parametrar. Det här examensarbetet behandlar denna simuleringsaspekt. Kodningsredskap gjordes på ett simuleringsverktyg som heter MRVox2D för att förbättra dess realism och flexibilitet. I synnerhet omarbetades algoritmen för generering av voxelgeometri för att tillåta simuleringar i linje med vad som kan erhållas från en skanner. Att ha en variabel kärlstorlek inom en simulerad voxel är nu möjligt och Vessel Size Index kan beräknas i enlighet därmed. MRF-applikationer gjordes på mössdata med användning av dessa implementationer, vilket visade uppmuntrande men ännu inte perfekta resultat.

Place, publisher, year, edition, pages
2019. , p. 31
Series
TRITA-CBH-GRU ; 2019:108
Keywords [en]
MRI, fingerprinting, simulations, MRVox2D
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-260257OAI: oai:DiVA.org:kth-260257DiVA, id: diva2:1355024
External cooperation
Grenoble Institute of Neurosciences
Educational program
Master of Science - Medical Engineering
Supervisors
Examiners
Available from: 2019-10-04 Created: 2019-09-26 Last updated: 2019-10-04Bibliographically approved

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CiteExportLink to record
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