4 papers
Deep Unrolled Networks in Representation Space Applied to MRI Reconstruction
Efe Ilıcak, Baris Imre, Chloé Najac +4
Deep unrolled networks (DUNs) integrate physical forward models with learned regularization in cascaded network architectures, achieving exceptional performance in inverse problems…
Physics-Guided Dual-Domain Network with Attention-Based Fusion for Portable MRI Reconstruction
Efe Ilıcak, Baris Imre, Chloé Najac +4
Portable low-field magnetic resonance imaging (MRI) systems have gained renewed interest owing to their cost effectiveness and point-of-care imaging capabilities. Yet, portable MRI…
Design and performance of a Toroidal RF Volume Coil with Intrinsic Electromagnetic Interference Rejection for low-field Portable Halbach-Based MRI Systems
Jules Vliem, Najac Chloe, Beatrice Lena +2
Purpose: One of the intrinsic limitations of low-field MRI is low signal-to-noise ratio (SNR), which can be further reduced by electromagnetic interference (EMI) due to the lack of…
Deep learning of personalized priors from past MRI scans enables fast, quality-enhanced point-of-care MRI with low-cost systems
Tal Oved, Beatrice Lena, Chloé F. Najac +4
Magnetic resonance imaging (MRI) offers superb-quality images, but its accessibility is limited by high costs, posing challenges for patients requiring longitudinal care. Low-field…