Abstract #0665
Novel acquisition scheme for diffusion kurtosis imaging based on compressed-sensing accelerated DSI yielding superior image quality
Tim Sprenger 1,2 , Jonathan I. Sperl 1 , Brice Fernandez 3 , Vladimir Golkov 1 , Ek Tsoon Tan 4 , Christopher Hardy 4 , Luca Marinelli 4 , Michael Czisch 5 , Philipp Saemann 5 , Axel Haase 2 , and Marion I. Menzel 1
1
GE Global Research, Munich, Germany,
2
Technical
University Munich, Munich, Germany,
3
GE
Healthcare, Munich, Germany,
4
GE
Global Research, Niskayuna, NY, United States,
5
Max
Planck Institute of Psychiatry, Munich, Germany
In Diffusion Kurtosis Imaging (DKI), the data is sampled
in a series of concentric shells in the diffusion
encoding space (q-space) and usu-ally suffers from low
SNR. In this work a novel acquisition scheme for
kurtosis imaging is presented, based on undersampled
diffusion spectrum imaging (DSI) followed by a
compressed sensing (CS) reconstruction of q-space. The
undersampling thereby yields a compara-ble number of
q-space sampling points as in standard DKI schemes
whereas the CS-based denoising is shown to improve
stability and accuracy of the kurtosis tensor
estimation.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Click here for more information on becoming a member.
