LiFE (Linear Fasicle Evaluation) predicts the measured diffusion signal using the orientation of the fascicles present in a connectome. LiFE uses the difference between the measured and predicted diffusion signals to measure prediction error. The connectome model prediction error is used to compute two metrics to evaluate the evidence supporting properties of the connectome.
We have recently made a new datatype that generalizes streamline weight data better than the life datatype. Would it be possible to output the life weights to the new streamline-weights datatype?
The format of the datatype: 1 x N streamlines, where each row is a weight:
example:
0.5
0.23
0.10
0
0.0015
...
This will make the output from this app more generalizable and incoporatable into apps such as Structural Connectome MRTrix3 (SCMRT) apps.
We have recently made a new datatype that generalizes streamline weight data better than the life datatype. Would it be possible to output the life weights to the new streamline-weights datatype?
The format of the datatype: 1 x N streamlines, where each row is a weight:
example: 0.5 0.23 0.10 0 0.0015 ...
This will make the output from this app more generalizable and incoporatable into apps such as Structural Connectome MRTrix3 (SCMRT) apps.