Meeting Banner
Abstract #1680

Using GPUs to accelerate computational diffusion MRI: From microstructure estimation to tractography and connectomes

Moises Hernandez-Fernandez1,2, Istvan Reguly3,4, Saad Jbabdi1, Mike Giles3, Stephen Smith1, and Stamatios N. Sotiropoulos1,5

1Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, United Kingdom, 2Section for Biomedical Image Analysis (SBIA), University of Pennsylvania, Philadelphia, PA, United States, 3Oxford e-Research Centre, University of Oxford, Oxford, United Kingdom, 4Faculty of Information Technology and Bionics, Pazmany Peter Catholic University, Budapest, Hungary, 5Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom

The great potential of computational diffusion MRI (dMRI) relies on indirect inference of tissue microstructure and brain connections, as modelling and tractography frameworks map diffusion measurements to neuroanatomical features. This mapping however can be computationally expensive, particularly given the trend of increasing dataset sizes and/or the increased complexity in biophysical modelling. We present here a number of frameworks for accelerating dMRI computations using Graphics Processing Units (GPUs), for both microstructure estimation and tractography/connectome generation. We show that despite differences in challenges for parallelising these problems, GPU-based designs can offer accelerations of more than two orders of magnitude.

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.

Abstract

Keywords