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Fast T2 mapping with improved accuracy using undersampled spin-echo MRI and model-based reconstructions with a generating function.

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons39417

Sumpf,  T.
Biomedical NMR Research GmbH, MPI for biophysical chemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons15943

Uecker,  M.
Biomedical NMR Research GmbH, MPI for biophysical chemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons15082

Frahm,  J.
Biomedical NMR Research GmbH, MPI for biophysical chemistry, Max Planck Society;

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Citation

Sumpf, T., Petrovic, A., Uecker, M., Knoll, F., & Frahm, J. (2014). Fast T2 mapping with improved accuracy using undersampled spin-echo MRI and model-based reconstructions with a generating function. IEEE Transactions on Medical Imaging, 33(12), 2213-2222. doi:10.1109/TMI.2014.2333370.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0024-54A5-3
Abstract
A model-based reconstruction technique for accelerated T2 mapping with improved accuracy is proposed using undersampled Cartesian spin-echo magnetic resonance imaging (MRI) data. The technique employs an advanced signal model for T2 relaxation that accounts for contributions from indirect echoes in a train of multiple spin echoes. An iterative solution of the nonlinear inverse reconstruction problem directly estimates spin-density and T2 maps from undersampled raw data. The algorithm is validated for simulated data as well as phantom and human brain MRI at 3T. The performance of the advanced model is compared to conventional pixel-based fitting of echo-time images from fully sampled data. The proposed method yields more accurate T2 values than the mono-exponential model and allows for retrospective undersampling factors of at least 6. Although limitations are observed for very long T2 relaxation times, respective reconstruction problems may be overcome by a gradient dampening approach. The analytical gradient of the utilized cost function is included as Appendix . The source code is made available to the community.