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FA along a track

UserPost

11:12 am
March 11, 2010


cibuthomas

Member

posts 3

Hello

I am aware that Trackvis allows one to export the FA values within a track and also plot them using histograms.

The exported file contain 2 matrices: the first contain all the FA values and the second containsthe number of streamlines in each cell of the same matrix. So is the FA in a cell that contain 10 streamlines the average FA of the 10 streamlines?

Also, would it be possible to output the FA value for each streamline along its trajectory (for example anterior posterior) such that I can examine where the FA reduces or increases along individual streamlines? Since each slice is an n x n matrix, it should be possible to identify the location on the matrix through which the streamline passes through and therefore, one should be able to get the FA in that particular voxel. If this function is not incorporated in trackvis, is there some way I can unpack the .trk file to get this information?

 

Thank you

Cibu

2:17 pm
March 11, 2010


Ruopeng

Admin

posts 88

Hi Cibu,

Yes, the exported numbers are the histogram of the FA distribution in that track group.

TrackVis does not have the function to export individual scalar values along each streamline. Even if it does, it would be a little difficult to analyze. Because tracks are not in any specific order when grouped into a trackgroup. It is totally random. Once exported to a text file, it would be difficult to figure out which is which. In the case of finding FA values on a slice, doesn't the FA map tell it already?

TrackVis does have a visualization option that might be interesting to you in this case. In "color code" setting, there is an option called "scalar". You can use that to visualize the difference of the scalar value (such as FA) along each individual track.

Ruopeng

2:20 pm
April 7, 2010


michael

Member

posts 3

Hi, I just posted a similar request for a FA along the streamline in the Feedback section of the forum before I saw cibuthomas post. I also would be very interested in that kind of feature.

To make an across subject comparison possible one would have to do a two ROI tracking and then normalize the distance between the two ROIs.

There is a paper by Jan Klein describing that feature implemented in their software NeuroQlab

http://www.springerlink.com/co…..7455513w1/