|Schmid, Volker J. (2. March 2010): Spatio-Temporal Modelling of Perfusion Cardiovascular MRI. Department of Statistics: Technical Reports, No.77|
Myocardial perfusion MRI provides valuable insight into how coronary artery and microvascular diseases affect myocardial tissue. Stenosis in a coronary vessel leads to reduced maximum blood flow (MBF), but collaterals may secure the blood supply of the myocardium but with altered tracer kinetics. To date, quantitative analysis of myocardial perfusion MRI has only been performed on a local level, largely ignoring the contextual information inherent in different myocardial segments. This paper proposes to quantify the spatial dependencies between the local kinetics via a Hierarchical Bayesian Model (HBM). In the proposed framework, all local systems are modelled simultaneously along with their dependencies, thus allowing more robust context-driven estimation of local kinetics. Detailed validation on both simulated and patient data is provided.
|Item Type:||Paper (Technical Report)|
|Keywords:||Myocardial Perfusion MRI, Bayes, Spatio-temporal modelling, P-Splines,Markov random fields|
Mathematics, Computer Science and Statistics > Statistics > Technical Reports
|Subjects:||500 Science > 510 Mathematics|
|Deposited On:||03. Mar 2010 08:55|
|Last Modified:||08. Jan 2013 16:56|
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