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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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