Anders Garpebring

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The arterial input function is crucial in pharmacokinetic analysis of dynamic contrast-enhanced MRI data. Among other artifacts in arterial input function quantification, the blood inflow effect and nonideal radiofrequency spoiling can induce large measurement errors with subsequent reduction of accuracy in the pharmacokinetic parameters. These errors were(More)
Dynamic contrast-enhanced magnetic resonance imaging (MRI) is a promising tool in the evaluation of tumor physiology. From rapidly acquired images and a model for contrast agent pharmacokinetics, physiological parameters are derived. One pharmacokinetic model, the tissue homogeneity model, enables estimation of both blood flow and vessel permeability(More)
BACKGROUND In recent years, there has been a considerable research effort concerning the integration of magnetic resonance imaging (MRI) into the external radiotherapy workflow motivated by the superior soft tissue contrast as compared to computed tomography. Image registration is a necessary step in many applications, e.g. in patient positioning and(More)
Front cover illustration: Tumor ࡷ ࢚࢘ࢇ࢔࢙ map in patient with glioblastoma multiforme. Morfar: " Ska en parvel som du bli elektriker som pappa när du blir stor? " Jag (5 år): " Nä morfar, när jag blir stor ska jag bli forskare. " i Abstract Background: Dynamic contrast-enhanced MRI (DCE-MRI) has the potential to produce images of physiological quantities such(More)
PURPOSE To compare methods for estimating B0 maps used in retrospective correction of high-resolution anatomical images at ultra-high field strength. The B0 maps were obtained using three methods: (1) 1D navigators and coil sensitivities, (2) field probe (FP) data and a low-order spherical harmonics model, and (3) FP data and a training-based model. (More)
PURPOSE The linear least squares (LLS) estimator provides a fast approach to parameter estimation in the linearized two-compartment exchange model. However, the LLS method may introduce a bias through correlated noise in the system matrix of the model. The purpose of this work is to present a new estimator for the linearized two-compartment exchange model(More)
UNLABELLED Compartmental modeling of dynamic PET data enables quantification of tracer kinetics in vivo, through the calculated model parameters. In this study, we aimed to investigate the effect of early frame sampling and reconstruction method on pharmacokinetic parameters obtained from a 2-tissue model, in terms of bias and uncertainty (SD). METHODS(More)
Using dynamic contrast-enhanced MRI (DCE-MRI), it is possible to estimate pharmacokinetic (PK) parameters that convey information about physiological properties, e.g., in tumors. In DCE-MRI, errors propagate in a nontrivial way to the PK parameters. We propose a method based on multivariate linear error propagation to calculate uncertainty maps for the PK(More)
PURPOSE The purpose of this study was to investigate, using simulations, a method for improved contrast agent (CA) quantification in DCE-MRI. METHODS We developed a maximum likelihood estimator that combines the phase signal in the DCE-MRI image series with an additional CA estimate, e.g. the estimate obtained from magnitude data. A number of simulations(More)
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