Cerebellum CNN

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Cerebellum Parcellation with Convolutional Neural Networks

This work originally appeared at Proceedings of SPIE Medical Imaging (SPIE-MI 2019), San Diego, CA, February 16 - 21, 2019. It can be downloaded as a Singularity image from Cerebellar CNN Segmentation Code.

What the Singularity image can do

The Singularity performs the following steps:

• ROBEX is used to estimate a brain mask. This mask is then smoothed to generate a brain weight image.
• N4 from ANTs is used to perform the bias field correction. The bias field is estimated using the weight image calculated above.
• The images are rigidly registered to the ICBM2009c nonlinear symmetric template using the ANTs package. The first MPRAGE image from the longitudinal series of a subject is registered to this template and other images with different contrasts/from the following sessions are registered to the first MPRAGE image.
• The cerebellum of an MNI-registered MPRAGE image is parcellated using the method described in "Shuo Han, et al., Cerebellum parcellation with convolutional neural networks, SPIE 2019 Medical Imaging Image Processing".

• Removing the neck should improve the results, such as using `robustfov` from fsl, but it is not done in this singularity image.

• (OPTIONAL) Generate a HTML report file. To generate the report, the images are converted to .png files which could occupy a large hard disk space.

• GNU Parallel is used to run jobs in parallel.