Abstract #0082
Simultaneous MR-PET Reconstruction using Multi Sensor Compressed Sensing and Joint Sparsity
Florian Knoll 1 , Thomas Koesters 1 , Ricardo Otazo 1 , Tobias Block 1 , Li Feng 1 , Kathleen Vunckx 2 , David Faul 3 , Johan Nuyts 2 , Fernando Boada 1 , and Daniel K Sodickson 1
1
Bernard & Irene Schwartz Center for
Biomedical Imaging, Department of Radiology, NYU School
of Medicine, New York, New York, United States,
2
Department
of Nuclear Medicine, K.U. Leuven, Leuven, Leuven,
Belgium,
3
Siemens
Medical Solutions USA, New York, United States
While both measurements can be performed simultaneously
with current state of the art PET-MR scanners, the data
sets are processed in two separate reconstruction
pipelines. The two different datasets are only combined
at the visualization stage. We propose a new iterative
reconstruction framework that treats MR and PET as one
single data acquisition, and jointly reconstructs both
image sets. In this way joint information of the
underlying anatomy is shared during the iterations
between both sets of images. In particular the lower
resolution and lower SRN PET reconstruction can benefit
from the superior soft tissue contrast of the MR.
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