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Jbartlett6 / SDNet

SDNet, a model based deep learning method to estimate high quality FODs from indersampled DWI signal data.
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Extract performance measures from MRStats output once after ACC or FBA has been performed. #7

Closed Jbartlett6 closed 1 year ago

Jbartlett6 commented 2 years ago

Each time ACC and FBA are performed a measure is obtained for each of the voxels, the average is then calculated by averaging this over all the voxels in the brain or over some mask. However these are output into the shell but cannot be interpreted there. It is required to find a way to store these values so they can be processed, e.g. averaged over the subjects in a folder.

Jbartlett6 commented 2 years ago

The stats for each of the performance measures are now written to a text file. Each with a very specific structure.These text files should be able to be processed in python to extract the average over different subjects, or to conduct other tests. The files the stats are stored in are called acc_stats.txt, pae_stats.txt and afde_stats.txt respectively.