Deprecation of mtbin command and introduction of new mtnormalise command
Problems with the stability and some of the underlying theory of the method implemented by mtbin have become apparent, and the method has been radically overhauled to resolve these issues. Some of the issues with the original mtbin method could result in the introduction of extreme image intensity values in certain regions of the corrected images, which could in turn cause problems for subsequent steps in a typical fixel-based analysis pipeline (most notably the creation of or registration to a population template). When these issues manifested, the bias field and intensity estimation in the entire brain region was often affected as well.
After updating your MRtrix installation, the changes to take note of in this context are:
-
mtbinhas been deprecated. Running it will by default produce an error message to highlight this. The description lists an option to override this behaviour and allow to consciously run the method anyway. However, we recommend against continuing to use it in any (fixel-based) analysis. - A new alternative method is available via the
mtnormalisecommand. The interface and required inputs are similar to the previousmtbinmethod. The method has undergone thorough testing to perform up to expected standards. - The documentation of the multi-tissue fixel-based analysis pipeline has been updated to incorporate this new method.
We should also warn you that the previous version of MRtrix had an existing mtnormalise command, which implemented another method entirely. You should therefore take extra care to fully update your MRtrix installation before following the new (fixel-based analysis) instructions. The easiest way to check whether you are using the correct new mtnormalise command after updating, is to check for the presence of a “lognorm_scale” field/property in the header of the output images produced by mtnormalise. This can for instance be achieved by:
mrinfo wmfod_norm.mif -property lognorm_scale
This should produce a single number, which reflects the global scale detected (and corrected for) by the new mtnormalise method, assuming a log-normal distribution of the intensity normalisation factors (across the spatial domain). More information can also be found in the updated documentation of both the mtnormalise command and the multi-tissue fixel-based analysis pipeline.
Updated documentation for the multi-tissue fixel-based analysis pipeline
The fixel-based analysis pipeline has been updated / changed in a few places. The most notable change is the reintroduction of the dwibiascorrect bias field correction preprocessing step. Via experience in several (real) fixel-based analysis studies, we found that performing this correction early on in the pipeline has potentially important benefits for the subsequent dwi2mask brain mask computation, as well as the estimation of response functions for constrained spherical deconvolution. The new mtnormalise method, which sits further in the pipeline, is still essential for global intensity normalisation, but also accounts for further correction of (residual) intensity inhomogeneities. mtnormalise can automatically deal both with datasets that already underwent (partial) correction of bias fields, as well as datasets that are still entirely uncorrected for bias fields (and mtnormalise will in this scenario correct for those bias fields).
For dwibiascorrect, we still advise to use the ANTS N4 bias field correction algorithm via the -ants option, which requires an installation of the ANTS software. More information can be found in the documentation of dwibiascorrect and the updated multi-tissue fixel-based analysis pipeline. The default parameters used for the N4 algorithm have changed as well, in order to result in a more robust outcome (mostly beneficial for subsequent dwi2mask computation).