Hi Ertan<br><br>This has been the major subject of my PhD research, so I'll try to give you a coherent response without boring you with technical details or philosophical ramblings.<br><br>Although it seems a sensible thing to do, this reduction of tractography streamlines is technically challenging, and researchers have been trying to come up with an appropriate method for the last 10 years (a literature search for 'tractography clustering' should give you plenty of hits). It may seem trivial to label a pair of streamlines as 'similar' by somehow comparing their trajectories, but it is deceptively difficult to use this information to segment the streamlines data in a manner which is robust, reliable and in any way meaningful. There is also a scaling problem in dealing with the large number of streamlines that you need to achieve an adequate reconstruction of the white matter of the whole brain.<br>
<br>Depending on future developments, there is a chance that my more recent method (abstract 673 <a href="http://www.ismrm.org/11/Session67.htm">here</a>, apologies for the shameless self-reference) may be included in a distant version of MRtrix. If however you are using deterministic streamlines, and are looking to reduce the 'redundancy' associated with multiple deterministic streamlines reconstructing near-identical pathways, a method such as that by <a href="http://www.sciencedirect.com/science/article/pii/S1053811910013200">Guevara et al.</a> may be more appropriate. However I am not aware of any tractography clustering method which has been made available to the public thus far (probably because developers such as myself are not confident enough in their performance to release them).<br>
<br>So although the answer may be 'no', hopefully this provides some food for thought.<br><br>Regards<br>Rob<br clear="all"><br>--<br><br>Robert Smith<br>Melbourne Brain Centre<br>245 Burgundy Street<br>Heidelberg VIC 3084<br>
Telephone: (+61 3) 9035 7128<br>Fax: (+61 3) 9035 7301<br>Email: <a href="mailto:r.smith@brain.org.au" target="_blank">r.smith@brain.org.au</a><br><a href="http://www.fni.edu.au" target="_blank">www.florey.edu.au</a> <a href="http://www.brain.org.au" target="_blank">www.brain.org.au</a><br>
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<br><br><div class="gmail_quote">On Wed, Dec 7, 2011 at 9:43 AM, Ertan Cetingul <span dir="ltr"><<a href="mailto:ecetingul@yahoo.com">ecetingul@yahoo.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
Hello,<br>
<br>
I have a question on deterministic whole-brain tractography. Given a "seed mask" (e.g. FA-based thresholded mask), I presume that the algorithm considers each voxel in the mask as a starting seed point and performs streamlining. Now consider the following hypothetical scenario: Suppose we have 100 voxels (1x100 formation in 1D) with tensors indicating a linear fiber from left to right. If the algorithm is repeated at every voxels, theoretically one should obtain 100 copies of the same fiber. In reality, we are expected to find 100 similar fibers (in terms of spatial positions, length, etc.). I think one should not say that the remaining 99 copies are spurious but I believe there is a need to resolve this "dense" representation of the same structure. I was wondering whether the MRtrix contains a seed selection strategy to resolve this issue (and speed up the process) or a fiber similarity-driven filtering/pruning strategy after tractograpy. <br>
<br>
Thanks<br>
<br>
Ertan<br>
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