A PyTorch implementation of V-Net

Vnet is a PyTorch implementation of the paper V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation by Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi. This implementation is a work in progress. The official implementation is available in the faustomilletari/VNet repo on GitHub.

This implemenation relies on the LUNA16 loader and dice loss function from the Torchbiomed package.

What does the PyTorch compute graph of Vnet look like?

You can see the compute graph here, which I created with make_graph.py, which I copied from densenet.pytorch which in turn was copied from Adam Paszke's gist.

Credits

The train.py script was derived from the one in the densenet.pytorch repo.