ipywidgets

cornerstone has native support for layers and transparency and it would be useful to output segmentations and heatmaps and show multi-modal images like PET-CT

relevant JS is https://github.com/cornerstonejs/cornerstone/blob/803dd7335e16de3cc398a3d42eda2552dd47cb1b/example/layers/index.html#L95-L152

Motivation

ipyannotator currently support image labeling. However, for data sets with a very large number of classes it's very difficult to
quickly match the image to the right class.

Showing an visual representation for all possible classes and there textual description right next to the image could considerable improve the process. Currently only a textual or a visual represen

See conversation on gitter: https://gitter.im/jupyter-widgets/Lobby?at=60622d0814188a5edfd21f6c

Some points to be included in the tutorial:

1. Views should use this.send rather than this.model.send (https://gitter.im/jupyter-widgets/Lobby?at=6062335c56debe325c4ca07d)
2. Register the method of your choice on the python using self.on_msg