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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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