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20192021
most citedQuantitative Susceptibility Inversion Through Parcellated Multiresolution Neural Networks and K-Space Substitution

6 citations · 26 across the 10 of their papers we have counts for

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physics.med-ph2021

Unconstrained Kinematic MRI Tracking of Wrist Carpal Bones

Mohammad Zarenia, Volkan Emre Arpinar, Andrew S. Nencka +2

In this preliminary study technical methodology for kinematic tracking and profiling of wrist carpal bones during unconstrained movements is explored. Heavily under-sampled and fat…

physics.med-ph20205 cited

Optimization of hyperparameters for SMS reconstruction

L. Tugan Muftuler, Volkan Emre Arpinar, Kevin Koch +5

Simultaneous multi-slice (SMS) imaging accelerates MRI data acquisition by exciting multiple image slices simultaneously. Overlapping slices are then separated using a mathematical…

physics.med-ph2019

Meta-QSM: An Image-Resolution-Arbitrary Network for QSM Reconstruction

Juan Liu, Kevin M. Koch

Quantitative Susceptibility Mapping (QSM) can estimate the underlying tissue magnetic susceptibility and reveal pathology. Current deep-learning-based approaches to solve the QSM i…

physics.med-ph20193 cited

Deep Quantitative Susceptibility Mapping for Background Field Removal and Total Field Inversion

Juan Liu, Kevin M. Koch

Quantitative susceptibility mapping (QSM) utilizes MRI signal phase to estimate local tissue susceptibility, which has been shown useful to provide novel image contrast and as biom…

physics.med-ph20194 cited

MRI Tissue Magnetism Quantification through Total Field Inversion with Deep Neural Networks

Juan Liu, Kevin M. Koch

Quantitative susceptibility mapping (QSM) utilizes MRI signal phase to infer estimates of local tissue magnetism (magnetic susceptibility), which has been shown useful to provide n…

physics.med-ph20196 cited

Quantitative Susceptibility Inversion Through Parcellated Multiresolution Neural Networks and K-Space Substitution

Juan Liu, Andrew S. Nencka, L. Tugan Muftuler +3

Purpose: Quantitative Susceptibility Mapping (QSM) reconstruction is a challenging inverse problem driven by poor conditioning of the field to susceptibility transformation. State-…