This is the demo code for the following paper,

Benjamin Irving, Tania Douglas, Paul Taylor. 2D X-ray airway tree segmentation by 3D deformable model projection and registration

http://www.birving.com/papers/B_Irving_2D_Xray_airway_tree_segmentation_by_3D_deformable_model_projection_and_registration.pdf

To be presented at the Fifth International Workshop on Pulmonary Image Analysis (www.lungworkshop.org)

Note that only the mesh operations and not the optimisation method is included at the moment due to the challenge of finding 2D x-ray data that can be released. Please contact me if you would like the remainder of the code.

##Dependencies

Python libraries:

• time, copy, os
• pickle
• matplotlib
• numpy
• scipy
• mayavi

##Installation

The c++ component needs to first be compiled for your os and wrapped for python using swig. (Only tested on linux so far)

• Requirements: swig

Using linux:

cd mesh3D_mod
swig -c++ -python -o sc_wrap.cpp sc.i
gcc -fPIC $(python-config --includes) -c sc_wrap.cpp sc.cpp
g++ -shared sc_wrap.o sc.o -o _sc.so

sc.i - Settings that define the swig compilation sc.cpp -c++ class code. sc.py - Automatically created. Provides the link between the two languages.

This c++ object is now callable from the python 3D processing class.

##Running Examples Example 1 - Finding a mesh silhouette: python Example1_mesh_silhouette_and_projection.py (this example is slow because silhouette detection is applied to a very large mesh)

Example 2 - Plotting example variation of the statistical shape model: python Example2_pca_mesh.py

Example 3 - Projecting the mean statistical shape model along with landmark points and centreline: python Example3_centreline_landmark_projection.py

Example 4 - Rigid alignment

Example 5 - Shape optimisation

...

##Example Outputs

Example 1:

Example 2 - Example variation 3 standard deviations along the 2nd mode of variation:

Example 3: