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eess.IV2026
Data-Efficient Networks for Multi-Contrast MRI Reconstruction based on a Generalized Content/Style Prior
Chinmay Rao, Efe Ilıcak, Matthias J. P. van Osch +5
Multi-contrast MR scans contain redundant structural information that can be leveraged during reconstruction and potentially accelerate acquisition times. This idea has inspired en…
eess.IV2026
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…
eess.IV2024
A Plug-and-Play Method for Guided Multi-contrast MRI Reconstruction based on Content/Style Modeling
Chinmay Rao, Matthias van Osch, Nicola Pezzotti +8
Since the various MR contrasts of a given anatomy contain redundant information, one contrast can be used to guide the reconstruction of another undersampled contrast acquired subs…