How to avoid biased streamlines-based metrics for streamlines with variable step sizes

We show that metrics computed over streamlines can easily be biased or incorrect for streamlines with a step size that is too large or variable. The basic methods to compute those statistics, sometimes called Tractometry methods, generally only use the points of the streamlines to sample the corresponding image volumes. However, for streamlines where the step size is too large or variable, this sampling is skewed, and derived metrics are biased. We present a simple updated method that correctly handles those streamlines, and we show that metrics computed using this method are robust to the streamline sampling.

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.