Oct 5, 2022 � In this paper, we present a new approach to this problem that iteratively fuses the information of k-space and MRI images using novel dual Squeeze-Excitation�...
Dual-Domain Cross-Iteration Squeeze-Excitation Network for ...
xiongchaochen.github.io › publications
Dual-Domain Cross-Iteration Squeeze-Excitation Network for Sparse Reconstruction of Brain MRI. Published in arXiv preprint arXiv:2210.02523, 2022.
Abstract. Magnetic resonance imaging (MRI) is widely employed for diagnostic tests in neurology. However, the utility of MRI is largely limited by its long�...
Apr 28, 2023 � In this paper, we present a novel Dual-Domain Cross-Iteration Squeeze and Excitation Network (DD-CISENet) for accelerated sparse MRI reconstruction.
Oct 5, 2022 � This study included 720 clinical multi-coil brain MRI cases adopted from the open-source deidentified fastMRI Dataset. 8-folder downsampling�...
This repository contains the PyTorch implementation of Dual-domain Iterative residual sqeze-excitaton network for sparse-view reconstruction of MRI. Citation.
Results showed that the average reconstruction error over 120 testing cases by our proposed method was 2.28%, which outperformed the existing image-domain�...
Apr 28, 2023 � In this paper, we present a novel Dual-Domain Cross-Iteration Squeeze and Excitation Network (DD-CISENet) for accelerated sparse MRI�...
It utilizes multiple receiver coils to simultaneously acquire the multi-coil information. The other potential approach is downsampling the k-space measurements.
This paper provides a deep learning based strategy by simultaneously optimizing both the raw kspace data and undersampled image data for reconstruction that�...