Noise map estimation in diffusion MRI using Random Matrix Theory

We propose a new technique to estimate the spatially varying noise map based on diffusion MRI data to enable Rician bias correction. The technique makes use of a random matrix theorem, i.e. Marchenko-Pastors law, to estimate the noise level by exploiting the redundancy in multi-directional diffusion MR data.

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.