Compressed Sensing and Motion Correction LAB: An MR acquisition and reconstruction system
Generate a Compressed Sensing (CS) accelerated MR sequence and reconstruct the acquired data online on the scanner by means of Gadgetron or offline on an external workstation.
- Generic subsampling class for Compressed Sensing acquisitions
- CS accelerated gradient echo sequence (2D, 2D+time, 3D, 3D+time): CS_FLASH (Siemens, VB20P)
- MR motion imaging sequence (4D, 5D): CS_Retro (Siemens, VB20P, VE11C, VE11P)
- CS and motion-resolved reconstruction system for Gadgetron (C++)
- CS reconstruction system in Matlab (including a GUI)
https://sites.google.com/site/kspaceastronauts/compressed-sensing/espresso
https://sites.google.com/site/kspaceastronauts/compressed-sensing/cslab
https://sites.google.com/site/kspaceastronauts/motion-correction/4d-mr-imaging
https://github.com/thomaskuestner/4DMRImaging
https://sites.google.com/site/kspaceastronauts/motion-correction/pet-mr-motion-correction
- acquisition: CS_Retro (Siemens, VB20P, VE11C, VE11P)
- reconstruction: CS_LAB in gadgetron + data emitters and injectors
https://sites.google.com/site/kspaceastronauts/motion-correction/mocogui
More information: https://sites.google.com/site/kspaceastronauts/compressed-sensing/cslab#TOC-Prerequisites
standalone
git clone https://github.com/thomaskuestner/CS_MoCo_LAB.git
mkdir build
cd build
cmake ../
make
sudo make install
docker
docker pull kspaceastronauts/cs_moco_lab
docker run -it --volume $(pwd):/opt/data kspaceastronauts/cs_moco_lab
git clone https://github.com/thomaskuestner/CS_MoCo_LAB.git
cd CS_MoCo_LAB/matlab/CS_LAB_GUI
matlab CS_LAB_GUI
MR-based respiratory and cardiac motion correction for PET imaging.
Medical Image Analysis, 2017.
Thomas Küstner, Martin Schwartz, Petros Martirosian, Sergios Gatidis, Ferdinand Seith, Christopher Gilliam, Thierry Blu, Hadi Fayad, Dimitris Visvikis, F. Schick, B. Yang, H. Schmidt and N.F Schwenzer.
[doi] [BibTeX] [Endnote]
Compressed Sensing LAB: An MR acquisition and reconstruction system.
Proceedings of the ISMRM Workshop on Data Sampling and Reconstruction. Sedona, AZ, USA, 2016.
Thomas Küstner, Martin Schwartz, Christian Würslin, Petros Martirosian, Nina F. Schwenzer, Bin Yang and Holger Schmidt.
[BibTeX] [Endnote]
Image Reconstruction System for Compressed Sensing Retrospective Motion Correction for the Application in Clinical Practice.
Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM). Singapore, 2016.
Martin Schwartz, Thomas Küstner, Christian Würslin, Petros Martirosian, Nina F. Schwenzer, Fritz Schick, Bin Yang and Holger Schmidt.
[BibTeX] [Endnote]
Please read LICENSE file for licensing details.
Detailed information and installation instructions are available at:
https://sites.google.com/site/kspaceastronauts/compressed-sensing/cslab