VTrails Toolkit

A vectorial representation of the vascular network, which embodies quantitative features such as location, direction, scale, and bifurcations, has many potential cardio- and neuro-vascular applications.

VTrails stands as an end-to-end approach to extract geodesic vascular minimum spanning trees from angiographic data by solving a connectivity-optimised anisotropic level-set over a voxel-wise tensor field representing the orientation of the underlying vasculature.

VTrails has been presented at the biennial conference Information Processing in Medical Imaging (IPMI 2017) [1] Full-Text, and further published on the IEEE Transactions on Medical Imaging journal [2] Full-Text.

Open-Source Implementation

VTrails is available as Matlab toolkit.

VTrails on YouTube

Requirements:

Full Matlab R2016b or later
Correctly Configured Matlab Compiler (Coder and mex with most recent version gcc, clang, …)
Nifti Image I/O library (included) - original source
Boost_1_49_0 libraries (included) - original source
linterp libraries (included) - original source

Installation guide:

Install VTrails Toolkit from Matlab command window by typing:

>> INSTALL_VTrails;

Processing Pipeline:

After successfully installing the toolkit, process the angiographic image as follows:

Filter with SLoGS and synthesise the Riemannian Vesselness

Infer the Geodesic Vascular Graph with the Connectivity-optimised Anisotropic Level-Set

Extract the vascular Minimum Spanning Tree(s)

– For more details, see /main/PIPELINE.m –

Available Demos:

Two demos are included in the release:

>> /test_imgs/VTrailsDEMO_01;

>> /test_imgs/VTrailsDEMO_02;

Developing new Features - Coming Soon! -

Topologically aware evaluation framework: quantitative accuracy assessment;
Alignment and registration of vascular topologies [3] Full-Text;
Vessels morphology, lumen segmentation and clinical indices extraction;
Much more to come! … Stay Tuned :)

References

[1]

@InProceedings{Moriconi2017VTrails,
 title = {VTrails: Inferring Vessels with Geodesic Connectivity Trees},
 author = {Stefano Moriconi and 
           Maria A. Zuluaga and 
           Hans Rolf J{\"a}ger and 
           Parashkev Nachev and 
           S{\'e}bastien Ourselin and
           M. Jorge Cardoso},
  booktitle = {IPMI},
  year = {2017}}

[2]

@Article{Moriconi2018Inference,
 title = {Inference of Cerebrovascular Topology with Geodesic Minimum Spanning Trees},
 author = {Stefano Moriconi and 
           Maria A. Zuluaga and 
           Hans Rolf J{\"a}ger and 
           Parashkev Nachev and 
           S{\'e}bastien Ourselin and
           M. Jorge Cardoso},
 journal  = {IEEE Transactions on Medical Imaging},
 year = {2018}}

[3]

@InProceedings{Moriconi2018Elastic,
 title = {Elastic Registration of Geodesic Vascular Graphs},
 author = {Stefano Moriconi and 
           Maria A. Zuluaga and 
           Hans Rolf J{\"a}ger and 
           Parashkev Nachev and 
           S{\'e}bastien Ourselin and
           M. Jorge Cardoso},
 booktitle = {MICCAI},
 year = {2018}}

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Authors and Contributors

This project is currently maintained by Stefano Moriconi (@stefanomoriconi).