CS_MoCo_LAB

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.

Acquistion

• 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)

Reconstruction

• CS and motion-resolved reconstruction system for Gadgetron (C++)
• CS reconstruction system in Matlab (including a GUI)

Applications

Compressed Sensing MRI

https://sites.google.com/site/kspaceastronauts/compressed-sensing/espresso
https://sites.google.com/site/kspaceastronauts/compressed-sensing/cslab

Motion MR imaging

https://sites.google.com/site/kspaceastronauts/motion-correction/4d-mr-imaging
https://github.com/thomaskuestner/4DMRImaging

PET/MR motion correction

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

Image Registration

https://sites.google.com/site/kspaceastronauts/motion-correction/mocogui

Installation

More information: https://sites.google.com/site/kspaceastronauts/compressed-sensing/cslab#TOC-Prerequisites

Gadgetron

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

Matlab

git clone https://github.com/thomaskuestner/CS_MoCo_LAB.git
cd CS_MoCo_LAB/matlab/CS_LAB_GUI
matlab CS_LAB_GUI

References

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]