BRATS whole tumor segmentations

anisotropic_nets_brats_challenge_model_zoo.ini

+[config]
+version = 1.0
+
+[data]
+local_id = BRATS_examples
+url = https://www.dropbox.com/s/jyxnm3cqokjghje/BRATS_examples.tar.gz?dl=1
+action = expand
+destination = data
+
+[weights]
+local_id = anisotropic_nets_brats_challenge
+url = https://www.dropbox.com/s/cnbsszxa418xc1x/anisotropic_nets_brats_challenge_weights.tar.gz?dl=1
+action = expand
+destination = models
+
+[network_inference_config]
+local_id = anisotropic_nets_brats_challenge
+url = https://www.dropbox.com/s/fncslr3ink0jnup/anisotropic_nets_brats_challenge_code_config.tar.gz?dl=1
+action = expand
+destination = extensions
\ No newline at end of file

anisotropic_nets_brats_challenge_model_zoo.md

+# Automatic brain tumor segmentation on BRATS with anisotropic nets
+
+This page describes how to acquire and use the whole tumor segmentation network
+ as a part of the pipeline described in:
+
+Wang et al., Automatic Brain Tumor Segmentation using
+Cascaded Anisotropic Convolutional Neural Networks, MICCAI BRATS 2017
+
+[https://arxiv.org/abs/1709.00382](https://arxiv.org/abs/1709.00382)
+
+*[1] This implementation ranked the first (in terms of averaged Dice score 0.90499) according
+to the online validation leaderboard of [BRATS challenge 2017](https://www.cbica.upenn.edu/BraTS17/lboardValidation.html).*
+
+## Downloading model zoo files
+
+If you cloned the NiftyNet repository, 
+the network weights and examples data can be downloaded with the command
+```bash
+python net_download.py anisotropic_nets_brats_challenge_model_zoo
+```
+
+## Generating segmentations for example data
+
+Generate segmentations for the included example image with the command 
+```bash
+net_segment inference -c ~/niftynet/extensions/anisotropic_nets_brats_challenge/whole_tumor_axial.ini
+net_segment inference -c ~/niftynet/extensions/anisotropic_nets_brats_challenge/whole_tumor_coronal.ini
+net_segment inference -c ~/niftynet/extensions/anisotropic_nets_brats_challenge/whole_tumor_sagittal.ini
+```
+
+Replace `net_segment` with `python net_segment.py` if you cloned the NiftyNet repository. 
+
+Replace `~/niftynet/` if you specified a custom download path in the `net_download` command.
\ No newline at end of file

anisotropic_nets_brats_challenge_model_zoo_code.ini

+[config]
+version = 1.0
+
+[network_inference_config]
+local_id = anisotropic_nets_brats_challenge
+url = https://www.dropbox.com/s/fncslr3ink0jnup/anisotropic_nets_brats_challenge_code_config.tar.gz?dl=1
+action = expand
+destination = extensions
\ No newline at end of file

anisotropic_nets_brats_challenge_model_zoo_data.ini

+[config]
+version = 1.0
+
+[data]
+local_id = BRATS_examples
+url = https://www.dropbox.com/s/jyxnm3cqokjghje/BRATS_examples.tar.gz?dl=1
+action = expand
+destination = data
\ No newline at end of file

anisotropic_nets_brats_challenge_model_zoo_weights.ini

+[config]
+version = 1.0
+
+[weights]
+local_id = anisotropic_nets_brats_challenge
+url = https://www.dropbox.com/s/cnbsszxa418xc1x/anisotropic_nets_brats_challenge_weights.tar.gz?dl=1
+action = expand
+destination = models
\ No newline at end of file

model_zoo.md

@@ -7,3 +7,4 @@ This page lists NiftyNet networks pre-trained for specific tasks. Information ab
 | [dense_vnet_abdominal_ct_model_zoo](./dense_vnet_abdominal_ct_model_zoo.md) | Segment multiple organs from abdominal CT |
 | [ultrasound_simulator_gan_model_zoo](./ultrasound_simulator_gan_model_zoo.md) | Generate simulated ultrasound images at specified poses |
 | [highres3dnet_brain_parcellation_model_zoo](./highres3dnet_brain_parcellation_model_zoo.md) | Brain parcellation from T1 MR images |
+| [anisotropic_nets_brats_challenge_model_zoo](./anisotropic_nets_brats_challenge_model_zoo.md) | Brain tumor segmentation with anisotropic nets |