Hi! I am reading the paper "Neher, P. F., Côté, M.-A., Houde, J.-C., Descoteaux, M. & Maier-Hein, K. H. Fiber tractography using machine learning. Neuroimage 158, 417–429 (2017)" and am trying to understand the methodology using the MITK source code. But I am confused how the input raw signal is resampled to 100 directions? I couldn't locate the source code for this particular step. I need to know how mathematically this is done? For example if original data is (140x140x90) is acquired using 30 gradients (which makes the dMRI 140x140x90x30), resampling causes the dMRI to be of size 140x140x90x100? Guidance on the resampling will help me to understand the algorithm. Any help will be highly appreciated.
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