Fast Marching Minimal Path Extraction in ITK
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/1332
This paper describes the ITK implementation of a minimal path extraction framework based on Fast Marching arrival functions. The method requires the user to provide three inputs: 1. a meaningful speed function to generate an arrival function, 2. path information in the form of start, end, and way-points (which the path must pass near), and 3. an optimizer which steps along the resultant arrival function perpendicular to the Fast Marching front. A number of perspectives for choosing speed functions and optimizers are given, as well as examples using synthetic and real images.
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Code
minus Automatic Testing Results by Insight-Journal Dashboard on Mon Jun 9 15:37:45 2008 for revision #6
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plus Automatic Testing Results by Insight-Journal Dashboard on Mon Jun 9 15:18:55 2008 for revision #5
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plus Automatic Testing Results by Insight-Journal Dashboard on Mon Jun 9 15:11:30 2008 for revision #4
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plus Automatic Testing Results by Insight-Journal Dashboard on Fri Mar 21 11:53:19 2008 for revision #1
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Reviews
minus Exhaustive minimal path seaching methods by Sergio Vera on 2012-07-17 06:18:13 for revision #6
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Summary:

The author provide a set of classes to find minimal paths in images. A set of optimization methods are provided. 

Hypothesis:

Minimal path can be extracted between two points using a speed image by means of the Fast marching fronts.

Evidence:

Code and tests are provided.

Open Science:

Code and data is provided. I've been able to use the method on my own data using my own speed functions.

Reproducibility:

I was able to run the code without problems.

Quality of the data :

The method is usable thanks to the multiple examples an tests provided.

Interest:

In  medical imaging, this method is very useful in the context of centerline generation. The author states concerns about possible patent violations if this code is used to generate centerlines.

Free comment :

A good contribution to ITK. Applicable to many fields and applications. Centerline generation being the most useful in medical imaging, must require caution as may be under a patent.

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Comment by Matthew Mccormick yellow
This article has been merged into ITK as a Remote module in 4.8.0 as the "MinimalPathExtraction" module.


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Categories: Feature extraction, Optimization, Path, Segmentation
Keywords: ITK, vessel segmentation, centerline, minimal path
Toolkits: ITK, CMake
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