[Mrtrix-discussion] multiple bvalue

[Luis Concha]

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).

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).

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.

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.

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:
http://imgur.com/56Y8q


Thanks.


Dr. Luis Concha
Instituto de Neurobiología
Laboratorio C-12
UNAM, Campus Juriquilla
Boulervard Juriquilla 3001
Juriquilla, Querétaro.
C.P. 76230
México
Tel (442) 2 38 10 53
Fax (442) 2 38 10 46
www.inb.unam.mx

0.000000    0.000000    0.000000    0
-1.000000    0.000000    0.000000    1000
0.000000    -1.000000    0.000000    1000
0.000000    0.000000    1.000000    1000
0.042400    0.114601    -0.992506    1000
-0.174909    0.200511    -0.963951    1000
-0.232290    0.162593    -0.958960    1000
-0.367520    -0.026101    -0.929649    1000
-0.190192    -0.374383    -0.907560    1000
0.116799    -0.833394    -0.540196    1000
0.200489    -0.252686    -0.946548    1000
0.495782    -0.134495    -0.857969    1000
0.014100    0.628102    -0.778003    1000
0.744490    0.147698    -0.651091    1000
0.760877    -0.320390    -0.564283    1000
0.180892    -0.924660    -0.335085    1000
0.679628    0.422417    -0.599725    1000
-0.777100    -0.470700    -0.417800    1000
-0.924162    0.103596    -0.367685    1000
-0.468485    0.767376    -0.437786    1000
-0.881688    0.189298    -0.432194    1000
-0.690404    -0.706204    -0.156901    1000
-0.239096    -0.757087    -0.607990    1000
0.057800    -0.983696    0.170299    1000
0.536773    -0.836058    -0.113494    1000
0.991788    0.120698    -0.042299    1000
0.996763    -0.070897    -0.037899    1000
0.872425    -0.478114    -0.101403    1000
0.248714    -0.933552    0.258114    1000
-0.118295    -0.991861    -0.047098    1000
-0.337598    -0.841495    0.421798    1000
-0.528585    -0.840876    0.116297    1000
-0.996853    -0.054997    -0.057097    1000
-1.000000    0.000000    0.000000    2000
0.000000    -1.000000    0.000000    2000
0.000000    0.000000    1.000000    2000
0.042400    0.114601    -0.992506    2000
-0.174909    0.200511    -0.963951    2000
-0.232290    0.162593    -0.958960    2000
-0.367520    -0.026101    -0.929649    2000
-0.190192    -0.374383    -0.907560    2000
0.116799    -0.833394    -0.540196    2000
0.200489    -0.252686    -0.946548    2000
0.495782    -0.134495    -0.857969    2000
0.014100    0.628102    -0.778003    2000
0.744490    0.147698    -0.651091    2000
0.760877    -0.320390    -0.564283    2000
0.180892    -0.924660    -0.335085    2000
0.679628    0.422417    -0.599725    2000
-0.777100    -0.470700    -0.417800    2000
-0.924162    0.103596    -0.367685    2000
-0.468485    0.767376    -0.437786    2000
-0.881688    0.189298    -0.432194    2000
-0.690404    -0.706204    -0.156901    2000
-0.239096    -0.757087    -0.607990    2000
0.057800    -0.983696    0.170299    2000
0.536773    -0.836058    -0.113494    2000
0.991788    0.120698    -0.042299    2000
0.996763    -0.070897    -0.037899    2000
0.872425    -0.478114    -0.101403    2000
0.248714    -0.933552    0.258114    2000
-0.118295    -0.991861    -0.047098    2000
-0.337598    -0.841495    0.421798    2000
-0.528585    -0.840876    0.116297    2000
-0.996853    -0.054997    -0.057097    2000
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