Visualisation of segmentation results generated by this demo.
This demo employs a high resolution 3D network using the method described in
Li et al., On the Compactness, Efficiency, and Representation of 3D
Convolutional Networks: Brain Parcellation as a Pretext Task,
In: Information Processing in Medical Imaging (IPMI) 2017.
DOI: 10.1007/978-3-319-59050-9_28
This demo will download an MR volume and a trained network model, and then using the NiftyNet inference program to generate brain parcellation.
Please visit the NiftyNet model zoo entry for more information on running this demo.