MRI Reconstruction

59 papers with code • 5 benchmarks • 3 datasets

In its most basic form, MRI reconstruction consists in retrieving a complex-valued image from its under-sampled Fourier coefficients. Besides, it can be addressed as a encoder-decoder task, in which the normative model in the latent space will only capture the relevant information without noise or corruptions. Then, we decode the latent space in order to have a reconstructed MRI.

Greatest papers with code

Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction

facebookresearch/fastMRI 9 Dec 2020

Accelerating MRI scans is one of the principal outstanding problems in the MRI research community.

MRI Reconstruction SSIM

End-to-End Variational Networks for Accelerated MRI Reconstruction

facebookresearch/fastMRI 14 Apr 2020

The slow acquisition speed of magnetic resonance imaging (MRI) has led to the development of two complementary methods: acquiring multiple views of the anatomy simultaneously (parallel imaging) and acquiring fewer samples than necessary for traditional signal processing methods (compressed sensing).

MRI Reconstruction

GrappaNet: Combining Parallel Imaging with Deep Learning for Multi-Coil MRI Reconstruction

facebookresearch/fastMRI CVPR 2020

In this paper, we present a novel method to integrate traditional parallel imaging methods into deep neural networks that is able to generate high quality reconstructions even for high acceleration factors.

Fine-tuning MRI Reconstruction

Is good old GRAPPA dead?

zaccharieramzi/fastmri-reproducible-benchmark 1 Jun 2021

We perform a qualitative analysis of performance of XPDNet, a state-of-the-art deep learning approach for MRI reconstruction, compared to GRAPPA, a classical approach.

MRI Reconstruction

Density Compensated Unrolled Networks for Non-Cartesian MRI Reconstruction

zaccharieramzi/fastmri-reproducible-benchmark 5 Jan 2021

Deep neural networks have recently been thoroughly investigated as a powerful tool for MRI reconstruction.

MRI Reconstruction

XPDNet for MRI Reconstruction: an application to the 2020 fastMRI challenge

zaccharieramzi/fastmri-reproducible-benchmark 15 Oct 2020

We present a new neural network, the XPDNet, for MRI reconstruction from periodically under-sampled multi-coil data.

MRI Reconstruction

Deep Generative Adversarial Networks for Compressed Sensing Automates MRI

gongenhao/GANCS 31 May 2017

A multilayer convolutional neural network is then jointly trained based on diagnostic quality images to discriminate the projection quality.

MRI Reconstruction

Analysis of Deep Complex-Valued Convolutional Neural Networks for MRI Reconstruction

MRSRL/complex-networks-release 3 Apr 2020

Many real-world signal sources are complex-valued, having real and imaginary components.

MRI Reconstruction

Deep MRI Reconstruction with Radial Subsampling

directgroup/direct 17 Aug 2021

In spite of its extensive adaptation in almost every medical diagnostic and examinatorial application, Magnetic Resonance Imaging (MRI) is still a slow imaging modality which limits its use for dynamic imaging.

MRI Reconstruction