Parameter estimation and change-point detection from Dynamic Contrast Enhanced MRI data using stochastic differential equations

Mathematical Biosciences

Volumn 233, Issue 1, 2011, Pages 68-76

  Cuenod, Charles André ^a,b   Favetto, Benjamin ^a   Genon Catalot, Valentine ^a   Rozenholc, Yves ^a   Samson, Adeline ^a  

^a UNIVERSITÉ PARIS DESCARTES   (France)

^b PARIS CARDIOVASCULAR RESEARCH CENTER   (France)

Author keywords

Angiogenesis; DCE imaging; Kalman filter; Parameter estimation; Stochastic differential equation

Indexed keywords

ANGIOGENESIS; ARTERIAL INPUT FUNCTION; CAPILLARY PLASMA; CHANGE POINT DETECTION; CHANGE-POINTS; COMPARTMENTAL MODEL; CONTRAST AGENT; DCE-IMAGING; DCE-MRI; DELAY PARAMETERS; DYNAMIC CONTRAST ENHANCED MRI; DYNAMIC CONTRAST-ENHANCED IMAGING; DYNAMIC SIGNALS; ESTIMATION RESULTS; EXTRACTION OF INFORMATION; INPUT FUNCTIONS; LEAST SQUARES FITTING; MEASUREMENT NOISE; PHARMACOKINETIC MODEL; SIMULATION STUDIES; SOURCES OF VARIATION; STOCHASTIC DIFFERENTIAL EQUATIONS; TIME VARYING PARAMETER; UNKNOWN TIME DELAYS;

ESTIMATION; KALMAN FILTERS; MAGNETIC RESONANCE IMAGING; MAXIMUM LIKELIHOOD ESTIMATION; MEASUREMENT ERRORS; MEASUREMENT THEORY; ORDINARY DIFFERENTIAL EQUATIONS; PHARMACOKINETICS; SPURIOUS SIGNAL NOISE; STOCHASTIC SYSTEMS; TISSUE;

PARAMETER ESTIMATION;

GADOTERIC ACID;

DETECTION METHOD; ESTIMATION METHOD; IMAGE ANALYSIS; KALMAN FILTER; LEAST SQUARES METHOD; MAXIMUM LIKELIHOOD ANALYSIS; PARAMETERIZATION; STOCHASTICITY;

ARTICLE; CONTRAST ENHANCEMENT; CONTROLLED STUDY; DYNAMIC CONTRAST ENHANCED IMAGING; FEMALE; HUMAN; IMAGING; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MAXIMUM LIKELIHOOD METHOD; NORMAL HUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; SIMULATION; STATISTICS; STOCHASTIC DIFFERENTIAL EQUATION;

CONTRAST MEDIA; FEMALE; HETEROCYCLIC COMPOUNDS; HUMANS; LEAST-SQUARES ANALYSIS; MAGNETIC RESONANCE ANGIOGRAPHY; MAGNETIC RESONANCE IMAGING; MATHEMATICAL CONCEPTS; MICROCIRCULATION; MODELS, BIOLOGICAL; ORGANOMETALLIC COMPOUNDS; STOCHASTIC PROCESSES;

EID: 79961167853     PISSN: 00255564     EISSN: 18793134     Source Type: Journal    
DOI: 10.1016/j.mbs.2011.06.006     Document Type: Article

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