Flux driven medial curve extraction

Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/560
In this document it is described the implementation of the flux driven automatic centerline extraction
algorithm proposed by Bouix et al. in 2004. This is based on a skeletonisation algorithm initially
proposed by Siddiqi et al. in 2002, using properties of an average outward flux measure to distinguish
skeletal points from non-skeletal ones. This information is combined with a topology preserving thinning
procedure to obtain the final result. This implementation combines this skeletonisation algorithm with
other techniques as described in the paper of Bouix et al. to produce an ITK filter that generates as output
the skeleton, as a binary object represented in an image, of the input surface, represented as a distance
transform image. In this work is described this medial curve extraction procedure following the ITK
philosophy.
Data
minus 1 Dataset (24Mb)
Code
plus Automatic Testing Results by Insight-Journal Dashboard on Thu Sep 13 11:44:47 2007 for revision #2
starstarstarstarstar expertise: 5 sensitivity: 5

Reviews
minus A solid centerline extraction method by Sergio Vera on 2012-05-23 09:52:48 for revision #3
starstarstarstarstar expertise: 3 sensitivity: 5
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Summary:

Authors provide code to generate medial curve (centerlines) of binary volumes.  finary shapes by providing a medialness map based on the computation of the Average Outward Flux (AOF) followed by an iterative-ordered thinning algorithm. 


 

Hypothesis:

Work is based on works of Bouix et al and Sidiqqi et al. Those works describe the generation of medial axis using the AOF and ordered thinning.

Evidence:

Tests are included in thr source code, as well as data to run the method in several vascular structures

Open Science:

Source code and data are included with thee paper. The method is well explained and the original articles are referenced.

Reproducibility:

Code compiled smoothly with ITK 3.XX.


I would suggest to smooth distance maps with a gaussian kernel before using them with the method.


 

Open source Contributions:

Code is useable and can be integrated easily with other ITK filters easily.

Code Quality :

Code is commented and has the standard templated filter structure of ITK. I compiled it succesfully in Microsoft and GCC compilers.

Quality of the data :

Data includes sunthetic and real vascular volumes.

Interest:

A good amount of work in medical imaging relies on vascular analysis, so this method will be highly useful.


Also, medial curves can be used in several shape comparation techniques.

Free comment :

In the context of medical imaging I believe centerline calculation is a relevant task. ITK will greatly benefit of having a bunch of methods for centerline calculation.


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Categories: Filtering, Mathematical Morphology
Keywords: software, computer science, programming, image analysis, skeletonization, medial curve, centerline extraction, ITK filter
Toolkits: ITK
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