As of this writing, SimpleITK version >=1.0.0 is required to run these notebooks. This version is available from PyPi and Source Forge.
We recommend setting up a separate Python virtual environment to run through these notebooks as a tutorial.
With Anaconda you can set up a virtual environment, named sitkpy, and install all dependencies including SimpleITK using a single command:
conda env create -f environment.yml
Install virtualenv and create the environment called sitkpy.
sudo pip install virtualenv
virtualenv ~/sitkpy --no-site-packages
Install all of the required packages and SimpleITK, and activate the ipywidgets notebook extension.
~/sitkpy/bin/pip install -r Python/requirements.txt
jupyter nbextension enable --py --sys-prefix widgetsnbextension
The requirements.txt file just lists the required packages (see).
The data is automatically downloaded to the "Data" directory when you execute the notebooks.
Alternatively, to download all the data before hand:
cd SimpleITK-Notebooks
Utilities/downloaddata.py Data/ Data/manifest.json
To launch:
cd SimpleITK-Notebooks/Python
~/sitkpy/bin/jupyter notebook
In some situations, such as a tutorial session, you may not have internet access. This requires that you:
- Download the data in advance - see above.
- 00 Setup
- 01 Image Basics
- 02 Pythonic Image
- 03 Image Details
- 10 matplotlib's imshow
- 20 Expand With Interpolators
- 21 Transforms and Resampling
- 22 Transforms
- 300 Segmentation Overview
- 30 Segmentation Region Growing
- 31 Levelset Segmentation
- 32 Watersheds Segmentation
- 33 Segmentation Thresholding Edge Detection
- 34 Segmentation Evaluation
- 41 Progress
- 51 VH Segmentation1
- 55 VH Resample
- 56 VH Registration1
- 60 Registration Introduction
- 61 Registration Introduction Continued
- 62 Registration Tuning
- 63 Registration Initialization
- 64 Registration Memory Time Tradeoff
- 65 Registration FFD
- 66 Registration Demons
- 67 Registration Semiautomatic Homework