1 citations · 1 across the 2 of their papers we have counts for
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The 2024 MRSI Data Processing and Quantification Challenge Synthetic Dataset
John T. LaMaster, Julian P. Merkofer, Dennis M. J. van de Sande +3
Synthetic data is central to magnetic resonance spectroscopy method development because they provide ground truths for software validation, reproducible benchmarking, and machine-…
A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge
Julian P. Merkofer, Dennis M. J. van de Sande, Sina Amirrajab +5
This work proposes a method to accelerate the acquisition of high-quality edited magnetic resonance spectroscopy (MRS) scans using machine learning models taking the sample covaria…
A Review of Machine Learning Applications for the Proton Magnetic Resonance Spectroscopy Workflow
Dennis M. J. van de Sande, Julian P. Merkofer, Sina Amirrajab +6
This literature review presents a comprehensive overview of machine learning (ML) applications in proton magnetic resonance spectroscopy (MRS). As the use of ML techniques in MRS c…