1 citations · 1 across the 3 of their papers we have counts for
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Rapid 2D 23Na MRI of the calf using a denoising convolutional neural network
Rebecca R. Baker, Vivek Muthurangu, Marilena Rega +2
23Na MRI can be used to quantify in-vivo tissue sodium concentration (TSC), but the low 23Na signal leads to long scan times and/or noisy or low-resolution images. Reconstruction a…
Automatic Segmentation of the Great Arteries for Computational Hemodynamic Assessment
Javier Montalt-Tordera, Endrit Pajaziti, Rod Jones +7
Background: Computational fluid dynamics (CFD) is increasingly used to assess blood flow conditions in patients with congenital heart disease (CHD). This requires patient-specific…
Machine Learning aided k-t SENSE for fast reconstruction of highly accelerated PCMR data
Grzegorz Tomasz Kowalik, Javier Montalt-Tordera, Jennifer Steeden +1
Purpose: We implemented the Machine Learning (ML) aided k-t SENSE reconstruction to enable high resolution quantitative real-time phase contrast MR (PCMR). Methods: A residual U-ne…
Machine Learning in Magnetic Resonance Imaging: Image Reconstruction
Javier Montalt-Tordera, Vivek Muthurangu, Andreas Hauptmann +1
Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis, management and monitoring of many diseases. However, it is an inherently slow imaging technique. Over the last 20…
Memory reduced non-Cartesian MRI encoding using the mixed-radix tensor product on CPU and GPU
Jyh-Miin Lin, Grzegorz Kowalik, Jennifer A. Steeden +1
Multi-dimensional non-Cartesian MRI encoding using the precomputed interpolator can encounter the curse of dimensionality, in which the interpolator size exceeds the available memo…
Real-time Assessment of Right and Left Ventricular Volumes and Function in Children Using High Spatiotemporal Resolution Spiral bSSFP with Compressed Sensing
Jennifer A. Steeden, Grzegorz T. Kowalik, Oliver Tann +3
Background: Real-time (RT) assessment of ventricular volumes and function enables data acquisition during free-breathing. However, in children the requirement for high spatiotempor…