216 citations · 352 across the 10 of their papers we have counts for
10 papers
Sensitivity of literature T1 mapping methods to the underlying magnetization transfer parameters
Jakob Assländer
Purpose: Magnetization transfer (MT) has been identified as the principal source of variability in the MRI literature. This study assesses the sensitivity of established $T_1…
Rational Approximation of Golden Angles: Accelerated Reconstructions for Radial MRI
Nick Scholand, Philip Schaten, Christina Graf +6
Purpose: To develop a generic radial sampling scheme that combines the advantages of golden ratio sampling with simplicity of equidistant angular patterns. The irrational angle bet…
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…
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…
Optimized Quantification of Spin Relaxation Times in the Hybrid State
Jakob Assländer, Riccardo Lattanzi, Daniel K Sodickson +1
Purpose: The analysis of optimized spin ensemble trajectories for relaxometry in the hybrid state. Methods: First, we constructed visual representations to elucidate the differenti…
Low Rank Alternating Direction Method of Multipliers Reconstruction for MR Fingerprinting
Jakob Assländer, Martijn A Cloos, Florian Knoll +3
Purpose The proposed reconstruction framework addresses the reconstruction accuracy, noise propagation and computation time for Magnetic Resonance Fingerprinting (MRF). Methods Bas…