Tubular Geodesics using Oriented Flux: An ITK Implementation
| Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3398 |
Published in The Insight Journal - 2013 January-December.
Submitted by Engin Turetken on 02-01-2013.
This document describes an ITK implementation of an interactive method for tracing curvilinear structures.
The basic tools provided in this framework are an oriented flux-based tubularity measure and a geodesic path
tracer that uses the fast marching algorithm. The framework is efficient and requires minimal user
interaction to trace curvilinear structures such as vessels and neurites in 2D images and 3D image
stacks.
The basic tools provided in this framework are an oriented flux-based tubularity measure and a geodesic path
tracer that uses the fast marching algorithm. The framework is efficient and requires minimal user
interaction to trace curvilinear structures such as vessels and neurites in 2D images and 3D image
stacks.
Code
Automatic Testing Results
by Insight-Journal Dashboard
on Thu Sep 12 14:22:36 2013 for revision #1 
expertise: 5 sensitivity: 5 Reviews
Quick Comments
Comment by Xiaozhu Xiaomo
I have the same error:‘GetImageDimension’ is not a member of ‘itk'.How can I deal with it?
I have the same error:‘GetImageDimension’ is not a member of ‘itk'.How can I deal with it?
Comment by Jorge Pérez
The code does not compile with ITK 4.5
First error is:
itkOrientedFluxMatrixImageFilter.h:62:3: error: ‘GetImageDimension’ is not a member of ‘itk’
The code does not compile with ITK 4.5
First error is:
itkOrientedFluxMatrixImageFilter.h:62:3: error: ‘GetImageDimension’ is not a member of ‘itk’
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| Categories: | Data Representation, Feature extraction, Filtering, Mathematics, Optimization, Path, Segmentation, Surface extraction |
| Keywords: | Curvilinear Structures, Tubular structures, Optimally Oriented Flux, Tubularity, Tubular Geodesic, Tracing, Tree-like Structures, Reconstruction, Segmentation, Vessel Tracing, Neurite Tracing, Centerline Extraction, Minimal Path |
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