5 papers · 1 filter
A multi-dynamic low-rank deep image prior (ML-DIP) for 3D real-time cardiovascular MRI
Chong Chen, Marc Vornehm, Zhenyu Bu +6
Purpose: To develop a reconstruction framework for 3D real-time cine cardiovascular magnetic resonance (CMR) from highly undersampled data without requiring fully sampled training…
An unsupervised method for MRI recovery: Deep image prior with structured sparsity
Muhammad Ahmad Sultan, Chong Chen, Yingmin Liu +3
Objective: To propose and validate an unsupervised MRI reconstruction method that does not require fully sampled k-space data. Materials and Methods: The proposed method, deep imag…
Groupwise Image Registration with Edge-Based Loss for Low-SNR Cardiac MRI
Xuan Lei, Philip Schniter, Chong Chen +1
Purpose: To perform image registration and averaging of multiple free-breathing single-shot cardiac images, where the individual images may have a low signal-to-noise ratio (SNR).…
Deep Image prior with StruCtUred Sparsity (DISCUS) for dynamic MRI reconstruction
Muhammad A. Sultan, Chong Chen, Yingmin Liu +2
High-quality training data are not always available in dynamic MRI. To address this, we propose a self-supervised deep learning method called deep image prior with structured spars…
Surface Coil Intensity Correction for MRI
Xuan Lei, Philip Schniter, Chong Chen +2
Modern MRI scanners utilize one or more arrays of small receive-only coils to collect k-space data. The sensitivity maps of the coils, when estimated using traditional methods, dif…