Abstract #4372
Prior Data Assisted Compressed Sensing - A Novel Strategy for Real Time Dynamic MRI
Eugene Yip 1 , Jihyun Yun 2 , Keith Wachowicz 1 , Zsolt Gabos 1 , Satyapal Rathee 1 , and Gino Fallone 1,2
1
Department of Oncology, University of
Alberta, Edmonton, AB, Canada,
2
Department
of Physics, University of Alberta, Edmonton, AB, Canada
Compressed Sensing (CS) can be beneficial to real time
MRI guided interventions by significantly improving
imaging frame rates. Spatial-temporal (k-t) CS can
increase the acceleration potential of conventional CS
but requires significantly longer reconstruction times.
We have devised a novel spatial-temporal CS imaging
strategy Prior Data Assisted Compressed Sensing
(PDACS), that is capable of near real time
reconstruction (0.3s), and improves the reconstruction
accuracy of conventional 2D-CS by using pre-acquired
data to support reconstruction. In this work, we
demonstrated the effectiveness of the PDACS technique in
a lung tumour tracking study of cancer patients
undergoing free breathing.
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