5 citations · 8 across the 8 of their papers we have counts for
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Deep learning water-unsuppressed MRSI at ultra-high field for simultaneous quantitative metabolic, susceptibility and myelin water imaging
Paul J. Weiser, Jiye Kim, Jongho Lee +6
Purpose: Magnetic Resonance Spectroscopic Imaging (MRSI) maps endogenous brain metabolism while suppressing the overwhelming water signal. Water-unsuppressed MRSI (wu-MRSI) allows…
Conditional Denoising Diffusion Model-Based Robust MR Image Reconstruction from Highly Undersampled Data
Mohammed Alsubaie, Wenxi Liu, Linxia Gu +3
Magnetic Resonance Imaging (MRI) is a critical tool in modern medical diagnostics, yet its prolonged acquisition time remains a critical limitation, especially in time-sensitive cl…
Missing Data Estimation for MR Spectroscopic Imaging via Mask-Free Deep Learning Methods
Tan-Hanh Pham, Ovidiu C. Andronesi, Xianqi Li +1
Magnetic Resonance Spectroscopic Imaging (MRSI) is a powerful tool for non-invasive mapping of brain metabolites, providing critical insights into neurological conditions. However,…
WALINET: A water and lipid identification convolutional Neural Network for nuisance signal removal in 1H MR Spectroscopic Imaging
Paul Weiser, Georg Langs, Stanislav Motyka +5
Purpose. Proton Magnetic Resonance Spectroscopic Imaging (1H-MRSI) provides non-invasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain 1H-M…
Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging
Paul Weiser, Georg Langs, Wolfgang Bogner +11
Introduction: Altered neurometabolism is an important pathological mechanism in many neurological diseases and brain cancer, which can be mapped non-invasively by Magnetic Resonanc…