update readme links
modified:   demos/BRATS17/README.md
This demo presents the brain tumor segmentation method described in
+
```
Wang et al., Automatic Brain Tumor Segmentation using
Cascaded Anisotropic Convolutional Neural Networks,
-https://arxiv.org/abs/1709.00382
```
+[https://arxiv.org/abs/1709.00382](https://arxiv.org/abs/1709.00382)
### Overview
The demo focuses on the first stage of the cascaded CNNs, i.e., automated
segmentation of whole tumor using the [WNet](anisotropic_nets/wt_net.py).
This folder (also zipped and downloadable via [dropbox link](http://link)) contains details for replicating the results [1], including:
- * [brats_segmentation.py](brats_segmentation.py) --
+ * [`brats_segmentation.py`](demos/BRATS17/brats_segmentation.py) --
an application built with NiftyNet, defines the main workflow of network
training and inference.
- * [wt_net.py](anisotropic_nets/wt_net.py) --
+ * [`wt_net.py`](demos/BRATS17/anisotropic_nets/wt_net.py) --
the network definitions.
- * .ini files --
+ * `.ini` files --
configuration files define system parameters for running
segmentation networks, the six files correspond to the combinations of
[training, inference] and networks in three orientations
[axial, coronal, sagittal] configurations.
- * [label_mapping_whole_tumor.txt](label_mapping_whole_tumor.txt) --
+ * [`label_mapping_whole_tumor.txt`](demos/BRATS17/label_mapping_whole_tumor.txt) --
mapping file used by NiftyNet, to convert the multi-class segmentations
into a binary problem.
- * [rename_crop_BRATS17.py](rename_crop_BRATS17.py) --
+ * [`rename_crop_BRATS.py`](demos/BRATS17/rename_crop_BRATS.py) --
utility script used to rename BRATS17 images into
`TYPEindex_modality.nii.gz` format and crop with a bounding box to remove
image background (voxels with intensity value zero).
