IRGN-TGV MATLAB Reconstruction Code

A high-quality reconstruction of accelerated MRI via joint estimation of image and coil sensitivities.

We are making available MATLAB reconstruction code for nonlinear parallel imaging that combines joint estimation of image content and coil sensitivities with variational regularization.

The algorithm provides accurate joint estimation of images and coil sensitivities through an iteratively regularized Gauss–Newton (IRGN) method. Integration of total generalized variation (TGV) penalties incorporates noise suppression and artifact removal, further enhancing the quality of reconstructed images. For more details, see the related publication.

Related Publication

Knoll F, Clason C, Bredies K, Uecker M, Stollberger R.
Parallel imaging with nonlinear reconstruction using variational penalties.
Magn Reson Med. 2012 Jan;67(1):34-41. doi: 10.1002/mrm.22964

Please cite this work if you are using IRGN-TGV reconstruction code 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 (Florian Knoll) 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”).


Questions about this resource may be directed to Florian Knoll, PhD.