Abstract #2704
Reducing blurring artifacts in 3D-GRASE ASL by integrating new acquisition and analysis strategies
Ilaria Boscolo Galazzo 1 , Michael A Chappell 2 , David L Thomas 3 , Xavier Golay 3 , Paolo Manganotti 1 , and Enrico De Vita 3,4
1
Department of Neurological and Movement
Sciences, University of Verona, Verona, Italy,
2
Institute
of Biomedical Engineering, University of Oxford, Oxford,
United Kingdom,
3
Academic
Neuroradiological Unit, Department of Brain Repair and
Rehabilitation, UCL Institute of Neurology, London,
United Kingdom,
4
Lysholm
Department of Neuroradiology, National Hospital for
Neurology and Neurosurgery, London, United Kingdom
3D-GRASE is one of the most efficient readout schemes
for Arterial Spin Labeling (ASL) when whole brain
coverage is desired. Due to the length of the echo
train, single-shot 3D-GRASE images exhibit severe T2
blurring along the partition-encoding direction. We
present a procedure to reduce the blurring effect in
single inversion-time data, combining a multi-shot
3D-GRASE-ASL sequence with a post-acquisition deblurring
algorithm. The application of this algorithm allows a
reduction of the number of shots needed for each image.
As more averages can be collected for a fixed
acquisition time, this method improves the available
signal-to-noise ratio and data quality.
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.
