This repository contains tutorials for the using the layered surface detection tool. Included is a Jupyter notebook entitled _LayeredSurfaceDetection_tutorial.ipynb_ which contains a short tutorial on applying the tool to a 2D dataset. A Python file containing some helper functions that are used in the tutorial is also included in _helpers.py_.
This repository contains tutorials for the using the layered surface detection tool. Included is a few Jupyter notebook tutorials that are designed to give you an idea on how to use the layered surface tool. You should start with the _LayeredSurfaceDetection_tutorial.ipynb_ notebook which discuss the basics of the layered surface tool and applies it to some synthetic data as well as a relatively simple example dataset. More complex examples are provided in the _NerveSegmentation2D_example.ipynb_ and _NerveSegmentation3D_example.ipynb_ notebooks which describe how to apply the layered surface tool to circular regions via radial unwrapping. A Python file containing some helper functions that are used in the tutorials is also included in utilsLS.py_. Some visualization functions are included in the _utilsVisualizationLS.py_.
These tutorials will give you an understanding of how to apply the Layered Surface tool to image data so that you can use the tool on your own datasets. You can open the the tutorials at [](https://mybinder.org/v2/git/https%3A%2F%2Flab.compute.dtu.dk%2FQIM%2Ftutorials%2Flayered-surfaces/HEAD).
