A reconstruction method that sorts dynamic data into motion states in accelerated MRI.

We are making available MATLAB code for XD-GRASP reconstruction.

Extra-dimensional golden-angle radial sparse parallel (XD-GRASP) reconstruction sorts dynamic, continuously acquired MRI data into multiple motion states. The technique produces clear images in the presence of ordinary motion—a development of particular significance for patients who may have trouble complying with instructions to hold their breath.

XD-GRASP reconstruction can be sorted by multiple dimensions of motion, including respiratory states, stages of the cardiac cycle, and phases of contrast enhancement. The technique makes it possible to freeze one kind of periodic motion while retaining another—for example, cardiac images can be sorted along the respiratory dimension so that the beating heart may be viewed as if unaffected by the inflations and deflations of the lungs.

Related Publications

Feng L, Grimm R, Tobias Block K, Chandarana H, Kim S, Xu J, Axel L, Sodickson DK, Otazo R.
Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI
Magn Reson Med. 2014 Sep;72(3):707-17. doi: 10.1002/mrm.24980

Feng L, Axel L, Chandarana H, Block KT, Sodickson DK, Otazo R.
XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing.
Magn Reson Med. 2016 Feb;75(2):775-88. doi: 10.1002/mrm.25665

Please cite these works if you are using XD-GRASP in your research.

Get the Code

The software available on this page is provided free of charge and comes without any warranty. CAI²R and NYU Grossman School of Medicine do not take any liability for problems or damage of any kind resulting from the use of the files provided. Operation of the software is solely at the user’s own risk. The software developments provided are not medical products and must not be used for making diagnostic decisions.

The software is provided for non-commercial, academic use only. Usage or distribution of the software for commercial purpose is prohibited. All rights belong to the author (Li Feng) and NYU Grossman School of Medicine. If you use the software for academic work, please give credit to the author in publications and cite the related publications.

Please spell out your affiliation (e.g. "New York University" rather than "NYU").


The source code uses the following external packages:


Questions about this resource may be directed to Li Feng, PhD at