29 citations · 104 across the 9 of their papers we have counts for
9 papers
Contrast-Optimized Basis Functions for Self-Navigated Motion Correction in Quantitative MRI
Elisa Marchetto, Sebastian Flassbeck, Andrew Mao +1
Purpose: The long scan times of quantitative MRI techniques make motion artifacts more likely. For MR-Fingerprinting-like approaches, this problem can be addressed with self-naviga…
Magnetization transfer explains most of the variability in the MRI literature
Jakob Assländer
Purpose: To identify the predominant source of the variability described in the literature, which ranges from 0.6-1.1 s for brain white matter at 3 T. Methods: 25 -mappi…
Bias-Reduced Neural Networks for Parameter Estimation in Quantitative MRI
Andrew Mao, Sebastian Flassbeck, Jakob Assländer
Purpose: To develop neural network (NN)-based quantitative MRI parameter estimators with minimal bias and a variance close to the Cramér-Rao bound. Theory and Methods: We generaliz…
Cramér-Rao Bound Optimized Subspace Reconstruction in Quantitative MRI
Andrew Mao, Sebastian Flassbeck, Cem Gultekin +1
We extend the traditional framework for estimating subspace bases that maximize the preserved signal energy to additionally preserve the Cramér-Rao bound (CRB) of the biophysical p…
Unconstrained quantitative magnetization transfer imaging: disentangling T1 of the free and semi-solid spin pools
Jakob Assländer, Andrew Mao, Elisa Marchetto +5
Since the inception of magnetization transfer (MT) imaging, it has been widely assumed that Henkelman's two spin pools have similar longitudinal relaxation times, which motivated m…
Rapid quantitative magnetization transfer imaging: utilizing the hybrid state and the generalized Bloch model
Jakob Assländer, Cem Gultekin, Andrew Mao +7
Purpose: To explore efficient encoding schemes for quantitative magnetization transfer (qMT) imaging with few constraints on model Theory and Methods: We combine two recently propo…
Minimization of Eddy Current Artifacts in Sequences with Periodic Dynamics
Sebastian Flassbeck, Jakob Assländer
Purpose: To minimize eddy current artifacts in periodic pulse sequences with balanced gradient moments as, e.g., used for quantitative MRI. Theory and Methods: Eddy current artifac…
Cramér-Rao bound-informed training of neural networks for quantitative MRI
Xiaoxia Zhang, Quentin Duchemin, Kangning Liu +4
Neural networks are increasingly used to estimate parameters in quantitative MRI, in particular in magnetic resonance fingerprinting. Their advantages over the gold standard non-li…
Generalized Bloch model: a theory for pulsed magnetization transfer
Jakob Assländer, Cem Gultekin, Sebastian Flassbeck +2
Purpose: The paper introduces a classical model to describe the dynamics of large spin-1/2 ensembles associated with nuclei bound in large molecule structures, commonly referred to…