Hi users,
I am trying to find the tortuosity of a material(3D) In x,y,z directions. 1)As a first step I skeletonized the pores. 2)I used analyze skeleton in imagej to get the vertexes and the edges. How do i identify the shortest path from this ? how do i draw all the possible paths in a graph and find the tortuosity distribution in all three directions? 
Check http://fiji.sc/wiki/index.php/AnalyzeSkeleton and a comment about
tortuosity within the Detailed Information section. Good luck, Prof. Sidnei Paciornik Grupo de Análise de Imagens e Microscopia Digital DEMa <http://www.dema.pucrio.br/>  Departamento de Engenharia de Materiais PUCRio <http://www.pucrio.br/> Rua Marquês de São Vicente 225 Prédio Leme, Sala 501L Gávea  Rio de Janeiro  RJ 22451900  Brasil tel: (55)(21)35271243 On Fri, Jul 19, 2013 at 2:56 PM, prasanthriver <[hidden email]>wrote: > Hi users, > > I am trying to find the tortuosity of a material(3D) In x,y,z directions. > > 1)As a first step I skeletonized the pores. > 2)I used analyze skeleton in imagej to get the vertexes and the edges. > > How do i identify the shortest path from this ? how do i draw all the > possible paths in a graph and find the tortuosity distribution in all > three > directions? > > > >  > View this message in context: > http://imagej.1557.x6.nabble.com/tortuositytp5004032.html > Sent from the ImageJ mailing list archive at Nabble.com. > >  > ImageJ mailing list: http://imagej.nih.gov/ij/list.html >  ImageJ mailing list: http://imagej.nih.gov/ij/list.html 
In reply to this post by prasanthriver
I would suggest a different approach. Have a look at "Practical Methods for Measuring the Tortuosity of Porous Materials from Binary or GrayTone Tomographic Reconstructions", C.J. Gommes et.al.. AICHE Journal Vol. 55, No. 8. The iteration count for a 6 connected flooding kernel is used as an estimator for geodesic distance in the pore space. Dividing the resulting image by the Euclidean distance produces a tortuosity image. If you are flooding from the top slice to the bottom slice the Euclidean distance is simply the slice number.
If the image is sufficiently large and is a random network then the tortuosities should converge to a solution as distance increases from the seed point or seed plane (usually an image face). This process tends to overestimate the tortuosity but is still a useful metric. A plugin that does 6 connected 3D flood filling will work but you will need to modify it to report the iteration count. Regards, John D.

In reply to this post by Sidnei Paciornik
3d fractal analysis???
________________________________ Da: Sidnei Paciornik <[hidden email]> A: [hidden email] Inviato: Venerdì 19 Luglio 2013 15:54 Oggetto: Re: tortuosity Check http://fiji.sc/wiki/index.php/AnalyzeSkeleton and a comment about tortuosity within the Detailed Information section. Good luck, Prof. Sidnei Paciornik Grupo de Análise de Imagens e Microscopia Digital DEMa <http://www.dema.pucrio.br/>  Departamento de Engenharia de Materiais PUCRio <http://www.pucrio.br/> Rua Marquês de São Vicente 225 Prédio Leme, Sala 501L Gávea  Rio de Janeiro  RJ 22451900  Brasil tel: (55)(21)35271243 On Fri, Jul 19, 2013 at 2:56 PM, prasanthriver <[hidden email]>wrote: > Hi users, > > I am trying to find the tortuosity of a material(3D) In x,y,z directions. > > 1)As a first step I skeletonized the pores. > 2)I used analyze skeleton in imagej to get the vertexes and the edges. > > How do i identify the shortest path from this ? how do i draw all the > possible paths in a graph and find the tortuosity distribution in all > three > directions? > > > >  > View this message in context: > http://imagej.1557.x6.nabble.com/tortuositytp5004032.html > Sent from the ImageJ mailing list archive at Nabble.com. > >  > ImageJ mailing list: http://imagej.nih.gov/ij/list.html >  ImageJ mailing list: http://imagej.nih.gov/ij/list.html  ImageJ mailing list: http://imagej.nih.gov/ij/list.html 
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In reply to this post by Sidnei Paciornik
Hi Prof. Sidnei Paciornik,
I have read through it and it looks like it is a measure of 2d tortuosity and also it is a measure of distance (pixels)between the junction voxels and not the total number of pixels in the entire image Thanks, Prasanth 
In reply to this post by carlo bianco
Hi carlo bianco,
Can you attach some links of papers wheree i can take a look at the 3d fractla analysis?? Thanks, Prasanth 
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In reply to this post by Sidnei Paciornik
Hi everybody,
is the analyzeskeleton plugin also valid for 2D images? How can I have a number expressing tortuosity starting from the Euclidean distance number? Is there any range expressing for example 0 = low grade of tortuosity 1= high grade of tortuosity? Thanks a lot Matilde 
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