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<div class="moz-cite-prefix">Dear all<br>
<br>
Summer is there (and vacations are coming) so it may not be the
perfect time to put it forward. But just in case ...<br>
<br>
Since I am playin with the very nice connectome data I can not
stop thinking : it would be great to have a multi shell version of
the odf within mrtrix.<br>
<br>
Have a look at connectome data It may give you the motivation ...
288 direction (with 3 shell 1000 2000 3000) 1.25 isotropic
resolution perfect corregistration with a T1 0.7iso volume, 40
subject easy to dowload. <br>
It is worth to try !<br>
<br>
All the best<br>
<br>
Romain<br>
<br>
<br>
<br>
<br>
Le 16/11/2012 02:31, Donald Tournier a écrit :<br>
</div>
<blockquote
cite="mid:CAPP9hqS8fADb7E5-miOSUT_jmEXqzTHmDo2aSBrJ8CfFSmYfYA@mail.gmail.com"
type="cite">Hi everyone,
<div><br>
</div>
<div>The DTI fit in MRtrix should handle multiple b-values fine.
The CSD approach however cannot currently handle such data, as
Thijs correctly stated. Luis, I'm surprised that you manage to
get convincing results simply by stripping off the b=0 image,
since it is ignored by csdeconv anyway (unless you use the
-normalise option which is not recommended). In any case, it is
definitely not designed to handle multiple b-values, so I would
not advise planning your study around it...</div>
<div><br>
</div>
<div>Cheers,</div>
<div><br>
</div>
<div>Donald.</div>
<div><br>
</div>
<div><br>
<div class="gmail_quote">On 16 November 2012 07:41, Luis Concha
<span dir="ltr"><<a moz-do-not-send="true"
href="mailto:lconcha@unam.mx" target="_blank">lconcha@unam.mx</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">I have a
similar data set to the one described by Romain (1x b=0, 32x
b=1000 and 32x b=2000; the 32 gradient directions are
identical for b1000 and b2000). <br>
<br>
Perhaps I _shouldn't_ be doing it, but cdsdeconv seems to
handle this data set perfectly when I strip off the b=0
image (my usual approach, as I am after CSF signal
elimination). However, I just tested csdeconv with all three
b values (0,1000 and 2000) and it seems to give similar
results, up to an lmax=6 (I did not test any further).<br>
<br>
The DTI maps look perfectly fine, with a slight increase in
FA in regions partial voluming with CSF (fornix, callosum
edges) in the non-b0 data set as compared to the
b=0,1000,2000 data set.<br>
<br>
Perhaps doing 2 shells is OK even in the absence of b=0, and
the argument of multi-shell CSD invalidity is only
applicable for >3 shells. Nonetheless, I would much
appreciate it if you could direct me to the right papers in
order to understand if I am doing things properly, as I plan
to use this approach for a longitudinal 4-year study that is
just about to begin.<br>
<br>
Below is the gradient table used for the b=0,1000,2000 data
set, and I am posting a snapshot of the orientation plots
for the data sets I mentioned here:<br>
<a moz-do-not-send="true" href="http://imgur.com/56Y8q"
target="_blank">http://imgur.com/56Y8q</a><br>
<br>
<br>
Thanks.<br>
<br>
<br clear="all">
Dr. Luis Concha<br>
Instituto de Neurobiología<br>
Laboratorio C-12<br>
UNAM, Campus Juriquilla<br>
Boulervard Juriquilla 3001<br>
Juriquilla, Querétaro.<br>
C.P. 76230<br>
México<br>
Tel <a moz-do-not-send="true"
href="tel:%28442%29%202%2038%2010%2053"
value="+524422381053" target="_blank">(442) 2 38 10 53</a><br>
Fax <a moz-do-not-send="true"
href="tel:%28442%29%202%2038%2010%2046"
value="+524422381046" target="_blank">(442) 2 38 10 46</a><br>
<a moz-do-not-send="true" href="http://www.inb.unam.mx"
target="_blank">www.inb.unam.mx</a><br>
<br>
0.000000 0.000000 0.000000 0<br>
-1.000000 0.000000 0.000000 1000<br>
0.000000 -1.000000 0.000000 1000<br>
0.000000 0.000000 1.000000 1000<br>
0.042400 0.114601 -0.992506 1000<br>
-0.174909 0.200511 -0.963951 1000<br>
-0.232290 0.162593 -0.958960 1000<br>
-0.367520 -0.026101 -0.929649 1000<br>
-0.190192 -0.374383 -0.907560 1000<br>
0.116799 -0.833394 -0.540196 1000<br>
0.200489 -0.252686 -0.946548 1000<br>
0.495782 -0.134495 -0.857969 1000<br>
0.014100 0.628102 -0.778003 1000<br>
0.744490 0.147698 -0.651091 1000<br>
0.760877 -0.320390 -0.564283 1000<br>
0.180892 -0.924660 -0.335085 1000<br>
0.679628 0.422417 -0.599725 1000<br>
-0.777100 -0.470700 -0.417800 1000<br>
-0.924162 0.103596 -0.367685 1000<br>
-0.468485 0.767376 -0.437786 1000<br>
-0.881688 0.189298 -0.432194 1000<br>
-0.690404 -0.706204 -0.156901 1000<br>
-0.239096 -0.757087 -0.607990 1000<br>
0.057800 -0.983696 0.170299 1000<br>
0.536773 -0.836058 -0.113494 1000<br>
0.991788 0.120698 -0.042299 1000<br>
0.996763 -0.070897 -<a moz-do-not-send="true"
href="tel:0.037899%C2%A0%C2%A0%C2%A0%201000"
value="+3780549991000" target="_blank">0.037899 1000</a><br>
0.872425 -0.478114 -0.101403 1000<br>
0.248714 -0.933552 0.258114 1000<br>
-0.118295 -0.991861 -0.047098 1000<br>
-0.337598 -0.841495 0.421798 1000<br>
-0.528585 -0.840876 0.116297 1000<br>
-0.996853 -0.054997 -0.057097 1000<br>
-1.000000 0.000000 0.000000 2000<br>
0.000000 -1.000000 0.000000 2000<br>
0.000000 0.000000 1.000000 2000<br>
0.042400 0.114601 -0.992506 2000<br>
-0.174909 0.200511 -0.963951 2000<br>
-0.232290 0.162593 -0.958960 2000<br>
-0.367520 -0.026101 -0.929649 2000<br>
-0.190192 -0.374383 -0.907560 2000<br>
0.116799 -0.833394 -0.540196 2000<br>
0.200489 -0.252686 -0.946548 2000<br>
0.495782 -0.134495 -0.857969 2000<br>
0.014100 0.628102 -0.778003 2000<br>
0.744490 0.147698 -0.651091 2000<br>
0.760877 -0.320390 -0.564283 2000<br>
0.180892 -0.924660 -0.335085 2000<br>
0.679628 0.422417 -0.599725 2000<br>
-0.777100 -0.470700 -0.417800 2000<br>
-0.924162 0.103596 -0.367685 2000<br>
-0.468485 0.767376 -0.437786 2000<br>
-0.881688 0.189298 -0.432194 2000<br>
-0.690404 -0.706204 -0.156901 2000<br>
-0.239096 -0.757087 -0.607990 2000<br>
0.057800 -0.983696 0.170299 2000<br>
0.536773 -0.836058 -0.113494 2000<br>
0.991788 0.120698 -0.042299 2000<br>
0.996763 -0.070897 -<a moz-do-not-send="true"
href="tel:0.037899%C2%A0%C2%A0%C2%A0%202000"
value="+3780549992000" target="_blank">0.037899 2000</a><br>
0.872425 -0.478114 -0.101403 2000<br>
0.248714 -0.933552 0.258114 2000<br>
-0.118295 -0.991861 -0.047098 2000<br>
-0.337598 -0.841495 0.421798 2000<br>
-0.528585 -0.840876 0.116297 2000<br>
-0.996853 -0.054997 -0.057097 2000<br>
<br>
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</blockquote>
</div>
<br>
<br clear="all">
<div><br>
</div>
-- <br>
<font color="#ff6600" size="1"><b>Dr Jacques-Donald Tournier<br>
</b></font>
<div><font color="#ff6600" size="1">Research Fellow</font></div>
<div><font size="1"><br>
</font></div>
<div><font size="1">The Florey Institute of Neuroscience and
Mental Health</font></div>
<div><font size="1">Melbourne Brain Centre - Austin Campus</font></div>
<div><font size="1">245 Burgundy Street</font></div>
<div><font size="1">Heidelberg Vic 3084</font></div>
<div><font size="1">Ph: +61 3 9035 7033</font></div>
<div><font size="1">Fax: +61 3 9035 7307</font></div>
<div><font size="1"><a moz-do-not-send="true"
href="http://www.florey.edu.au" target="_blank">www.florey.edu.au</a></font></div>
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