251 citations · 338 across the 13 of their papers we have counts for
4 papers · 1 filter
Investigating the use of publicly available natural videos to learn Dynamic MR image reconstruction
Olivier Jaubert, Michele Pascale, Javier Montalt-Tordera +6
Purpose: To develop and assess a deep learning (DL) pipeline to learn dynamic MR image reconstruction from publicly available natural videos (Inter4K). Materials and Methods: Learn…
Deep Learning Pipeline for Preprocessing and Segmenting Cardiac Magnetic Resonance of Single Ventricle Patients from an Image Registry
Tina Yao, Nicole St. Clair, Gabriel F. Miller +13
Purpose: To develop and evaluate an end-to-end deep learning pipeline for segmentation and analysis of cardiac magnetic resonance images to provide core-lab processing for a multi-…
CLADE: Cycle Loss Augmented Degradation Enhancement for Unpaired Super-Resolution of Anisotropic Medical Images
Michele Pascale, Vivek Muthurangu, Javier Montalt Tordera +4
Three-dimensional (3D) imaging is popular in medical applications, however, anisotropic 3D volumes with thick, low-spatial-resolution slices are often acquired to reduce scan times…
HyperSLICE: HyperBand optimized Spiral for Low-latency Interactive Cardiac Examination
Olivier Jaubert, Javier Montalt-Tordera, Daniel Knight +3
PURPOSE: Interactive cardiac magnetic resonance imaging is used for fast scan planning and MR guided interventions. However, the requirement for real-time acquisition and near real…