Publications by authors named "Kirsten M Kerkering"

Objective: The purpose of this study was to investigate an approach for motion-corrected T1 mapping of the abdomen that allows for free breathing data acquisition with 100% scan efficiency.

Materials And Methods: Data were acquired using a continuous golden radial trajectory and multiple inversion pulses. For the correction of respiratory motion, motion estimation based on a surrogate was performed from the same data used for T1 mapping.

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Objective: We propose a method for the reconstruction of parameter-maps in Quantitative Magnetic Resonance Imaging (QMRI).

Methods: Because different quantitative parameter-maps differ from each other in terms of local features, we propose a method where the employed dictionary learning (DL) and sparse coding (SC) algorithms automatically estimate the optimal dictionary-size and sparsity level separately for each parameter-map. We evaluated the method on a T-mapping QMRI problem in the brain using the BrainWeb data as well as in-vivo brain images acquired on an ultra-high field 7 T scanner.

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Purpose: To allow for T1 mapping of the myocardium within 2.3 s for a 2D slice utilizing cardiac motion-corrected, model-based image reconstruction.

Methods: Golden radial data acquisition is continuously carried out for 2.

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T1 mapping of the liver is time consuming and can be challenging due to respiratory motion. Here we present a prospective slice tracking approach, which utilizes an external ultra-wide band radar signal and allows for efficient T1 mapping during free-breathing.The fast radar signal is calibrated to an MR-based motion signal to create a motion model.

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. To provide 3D high-resolution cardiac T1 maps using model-based super-resolution reconstruction (SRR)..

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Objective: To provide respiratory motion correction for free-breathing myocardial T1 mapping using a pilot tone (PT) and a continuous golden-angle radial acquisition.

Materials And Methods: During a 45 s prescan the PT is acquired together with a dynamic sagittal image covering multiple respiratory cycles. From these images, the respiratory heart motion in head-feet and anterior-posterior direction is estimated and two linear models are derived between the PT and heart motion.

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