Troubleshooting & Bug Reports

Troubleshooting hints and tips will be added here. If you are having a problem which cannot be solved by anything on this page, either try searching the FSL mailing list archives to see if somebody else has had the same problem, or send a email to the mailing list.

MRS specific questions may be better answered on the MRSHub forums.

Bug Reporting

Please report bugs on the public FSL-MRS GitHub Issue Tracker or via email to the developers.

Troubleshooting hints

  1. Unable to find example data

    If you installed FSL-MRS through conda the example data can be downloaded directly from the GitLab repository folder.

  2. Poor fits

    Two problems are commonly diagnosed when poor fits are seen:

    1. Basis spectra are inconsistently scaled. For example empirically derived macromolecular basis spectra can be orders of magnitude larger than the other basis spectra. Before fitting, fsl_mrs(i) scales the magnitude of the data and basis spectra to a known range. Relative scales are preserved within the basis spectra. To permit fsl_mrs(i) to apply different scales to individual basis spectra use the --ind_scale option with a list of basis names.

    2. The data might have parameters unlike a 7T or 3T human in vivo brain spectrum. I.e. the spectrum originates from a pre-clinical system or from phantom. In this case the MCMC priors which are suitable for in vivo human case can be disabled using the --disable_MH_priors option. Priors can be fine tuned by altering the values in fsl_mrs.utils.constants.

  3. Identifying the correct files for conversion

    Raw data files, especially DICOM files can have obscure naming conventions. It can be difficult to determine which files should be converted for use in FSL-MRS. Tools such as gdcmdump from GDCM can help in identifying the scans by giving you access to the DICOM headers.

  1. Data looks ‘wrong’ after conversion

    If when using mrs_tools vis you see no signal and just noise try conjugating the data using fsl_mrs_proc conj or try expanding the ppm range plotted --ppmlim -10 10. If you see a flat line, then conversion failed. The data might be corrupted - did the acquisition complete successfully?

_images/bad_data.png