  DELIMIT is a framework extension for deep learning in diffusion imaging,
which extends the basic framework PyTorch towards spherical signals. Based on
several novel layers, deep learning can be applied to spherical diffusion
imaging data in a very convenient way. First, two spherical harmonic
interpolation layers are added to the extension, which allow to transform the
signal from spherical surface space into the spherical harmonic space, and vice
versa. In addition, a local spherical convolution layer is introduced that adds
the possibility to include gradient neighborhood information within the
network. Furthermore, these extensions can also be utilized for the
preprocessing of diffusion signals.
