<commit_before># A PyTorch implementation of V-Net

Vnet is a [PyTorch](http://pytorch.org/) implementation of the
paper [V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation](https://arxiv.org/abs/1606.04797)
by <NAME>, <NAME>, and <NAME>.

It is currently a work in progress so no final error rate is yet
available.

![](images/diagram.png)

This implemenation relies on the LUNA16 loader and dice loss function from
the [Torchbiomed](https://github.com/mattmacy/torchbiomed) package.

## What does the PyTorch compute graph of Vnet look like?

You can see the compute graph [here](images/vnet.png),
which I created with [make_graph.py](https://github.com/mattmacy/vnet.pytorch/blob/master/make_graph.py),
which I copied from [densenet.pytorch](https://github.com/bamos/densenet.pytorch) which in turn was
copied from [<NAME>'s gist](https://gist.github.com/apaszke/01aae7a0494c55af6242f06fad1f8b70).
<commit_msg>add repo link and credits<commit_after># A PyTorch implementation of V-Net

Vnet is a [PyTorch](http://pytorch.org/) implementation of the paper
[V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation](https://arxiv.org/abs/1606.04797)
by <NAME>, <NAME>, and <NAME>. This implementation is a work in progress. The official
implementation is available in the [faustomilletari/VNet](https://github.com/faustomilletari/VNet) repo on GitHub.

![](images/diagram.png)

This implemenation relies on the LUNA16 loader and dice loss function from
the [Torchbiomed](https://github.com/mattmacy/torchbiomed) package.

## What does the PyTorch compute graph of Vnet look like?

You can see the compute graph [here](images/vnet.png),
which I created with [make_graph.py](https://github.com/mattmacy/vnet.pytorch/blob/master/make_graph.py),
which I copied from [densenet.pytorch](https://github.com/bamos/densenet.pytorch) which in turn was
copied from [<NAME>'s gist](https://gist.github.com/apaszke/01aae7a0494c55af6242f06fad1f8b70).

### Credits

The train.py script as well as the general presentation of this repo was copied from
[densenet.pytorch](https://github.com/bamos/densenet.pytorch).

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