MRI

XPDNet @ CWI-Inria International Lab Workshop 2021

A presentation of my network for MRI reconstruction: the XPDNet.

XPDNet @ Le Seminaire Palaisien

A presentation of my network for MRI reconstruction: the XPDNet.

Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction

The SPARKLING algorithm was originally developed for accelerated 2D magnetic resonance imaging (MRI) in the compressed sensing (CS) context. It yields non-Cartesian sampling trajectories that jointly fulfill a target sampling density while each …

XPDNet @ NeurIPS 2020 Medical Imaging Workshop

A presentation of my network for MRI reconstruction: the XPDNet.

Denoising Score Matching for Uncertainty Quantification @ Machine Learning Club

A presentation of my network for Uncertainty Quantification in Inverse Problems with Denoising Score Matching.

fastMRI 2020 Brain MRI reconstruction Challenge

A competition organized by Facebook and NYU to foster the best reconstruction algorithms.

TF-GRAPPA

An implementation of the GRAPPA MRI reconstruction algorithm with a TensorFlow backend.

TFKBNUFFT

An implementation of the NUFFT in TensorFlow.

Benchmarking MRI reconstruction neural networks on large public datasets

Deep learning is starting to offer promising results for reconstruction in Magnetic Resonance Imaging (MRI). A lot of networks are being developed, but the comparisons remain hard because the frameworks used are not the same among studies, the …

Benchmarking proximal methods acceleration enhancements for CS-acquired MR image analysis reconstruction