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    Ariel Rokem
    @arokem
    Hello!
    I <3 gitter
    :-)
    Franco Pestilli
    @francopestilli
    Yeah! This rocks!!
    Ariel Rokem
    @arokem
    I'm actually just writing you an email
    Franco Pestilli
    @francopestilli
    OK cool waiting for it.
    sepehrband
    @sepehrband
    Hi Franco,
    great work.
    I'm using Mrtrix for tractography and would like to compare the results using diffusion prediction error. How can I input Mrtrix tractography nifti files to your Matlab routine?
    Franco Pestilli
    @francopestilli
    Take a look at this: francopestilli.github.io/life A script called life_demo.m is introduced there and explains how to get started. Let me know if this helps.
    Ariel Rokem
    @arokem
    Also, mrtrix_tck2pdb.m will convert from the mrtrix format to the pdb format, which can then be read into memory using mtrImportFibers. When you save the resulting output of that function into a mat-file, you can feed it directly into the LiFE routines, as demonstrated here: https://github.com/francopestilli/life/blob/master/scripts/life_demo.m#L73
    sepehrband
    @sepehrband
    Thanks guys, I also found the DiPy version of your method pretty awesome. Thanks !
    Ariel Rokem
    @arokem
    Great to hear. Note that there's a somewhat faster version of the dipy implementation, coming here: nipy/dipy#575
    Franco Pestilli
    @francopestilli
    Good. Dipy is less tested and so far speed is comparable between matlab and python. Choose the one you prefer.
    I wrote a script that shows how to preprocess raw data in matlab all the way dow to running life. take a look: https://github.com/francopestilli/life_scripts/blob/master/tutorial/LiFEData_preprocess.m
    Franco Pestilli
    @francopestilli
    @sepehrband
    sepehrband
    @sepehrband
    Great. Thanks Franco.
    sepehrband
    @sepehrband
    One more question guys. In the Supp. figure 6b of your paper, there is a decreasing trend in the median RMSE moving from low b-value to high b-values. Does this mean that higher b-value outperform lower b-values, or it's because of increased attenuation with high b-value?
    sepehrband
    @sepehrband
    Correction: "Supplementary figure 5b"
    Franco Pestilli
    @francopestilli
    @sepehrband I am not sure I can answer the question as it is formulated. The RMSE goes down, this means that the model fits the data better. But I have not yet looked at how the SNR in the data interacts with the RMSE calculations.
    sepehrband
    @sepehrband
    Thanks for your helps!
    johncplass
    @johncplass
    Hello all. Thanks for the awesome software. Quick question from a dMRI beginner: can I use LiFE with DSI data? I wanted to get started using LiFE with some freely available data -- looks like WUMinn-HCP data has gradient non-linearities that MRTrix can't handle yet, so I was looking into trying out the MGH-USC (DSI) data using TrackVis (or something else).
    johncplass
    @johncplass
    Thanks for any help you can give! @francopestilli @arokem
    Franco Pestilli
    @francopestilli
    Hi John Thanks for the interest. We have software to read TrackVis fiber groups into formats that LIE can handle: https://github.com/vistalab/vistasoft/blob/5e40ca8bd08993212b43bfe027a3c85fd513d379/fileFilters/mrtrix/read_trk_to_fg.m I never tried using those but I would give it a try, let me know if it fails or not.
    johncplass
    @johncplass
    Awesome, thank you! I will take a look and let you know how it works out.
    Franco Pestilli
    @francopestilli
    God please keep me posted! I previously analyzed the HCP data set (StLouis) using a single b-value at the time. Never tried the MGH_USC data set I am curious to learn how it goes for you please!
    johncplass
    @johncplass
    Ok, I will keep you updated. Another quick question to clarify: I am still trying to understand how information is encoded in DSI and how that compares to other methods. Is it safe to assume that LiFE's forward modelling is agnostic as to whether I am providing DSI data or other types?
    김형섭
    @rehappydoc_twitter
    Hi! expert!
    I am a beginner of LiFE. I installed Life scripts in MATLAB pathway. I have run life_demo but I confront the error messages.

    Error using feComputeSignal (line 41)
    Inner matrix dimensions must agree.

    Error in feComputeVoxelSignal (line 21)
    voxDSig = feComputeSignal(S0, bvecs, bvals, voxTensors);
    Error in feConnectomeBuildModel>(parfor body) (line 82)
    voxelPSignal = feComputeVoxelSignal(fe,usedVoxels(vv));

    Error in feConnectomeBuildModel (line 78)
    parfor vv = 1:nVoxels

    Error in feConnectomeInit (line 95)
    fe = feConnectomeBuildModel(fe);

    Error in life_demo (line 84)
    fe = feConnectomeInit(dwiFile,fgFileName,feFileName,[],dwiFileRepeat,t1File);

    김형섭
    @rehappydoc_twitter
    I have not changed the scripts. What's wrong? If you have the solutions, plz let me know.
    Thank you~~~
    David Coynel
    @dcoynel
    @rehappydoc_twitter someone correct me if I'm wrong, but I think it's because the S0 signal in feComputeSignal.m should be averaged over all b0 images ?
    Franco Pestilli
    @francopestilli
    @dcoynel correct.
    Also I suggest you guys look into using the new code, faster, lighter at www.github.com/brain-life/encode
    @here please let me know if the new code works better, there are demos and instructions
    David Coynel
    @dcoynel
    @francopestilli yes this works perfectly, thanks !