Hi Kerstin,<div><br></div><div>I'm afraid there is no such option for csdeconv. In my experience, CSD is relatively robust to one or two corrupted images, but I've certainly not gone as far as validating that particular claim...</div>
<div><br></div><div>There are ways you could do the analysis, but they're not trivial. Essentially you'd need to do the full csdeconv run, then for each corrupted slice:</div><div>- generate a set of DWI with the relevant volumes taken out (mrconvert --coord);</div>
<div>- get the DW encoding (mrinfo --grad);</div><div>- edit it to remove the corresponding gradient for that volume;</div><div>- do the csdeconv analysis with the reduced DWI set and its corresponding encoding (csdeconv -grad).</div>
<div>Repeat as necessary for any other volumes/slices, and finally splice your data back together using various combinations of mrconvert --coord to extract the slices you want from the CSD outputs you trust for those slices, and mrcat to concatenate them back together in the right order...</div>
<div><br></div><div>Not sure that all makes sense. It might just be easier to add the functionality to csdeconv if you feel brave enough... </div><div><br></div><div>Cheers,</div><div><br></div><div>Donald.</div><div><br>
</div><div><br><div class="gmail_quote">On 1 April 2010 11:53, Kerstin Pannek <span dir="ltr"><<a href="mailto:k.pannek1@uq.edu.au">k.pannek1@uq.edu.au</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Hi all<br>
<br>
I have some datasets where a few slices have severe artifacts (1-2 slices out of the full dataset with 65 volumes). I was just wondering whether I should ignore these slices in csdeconv, and if so, how? dwi2tensor has an option ignoreslices, but csdeconv doesn't have this option.<br>
<br>
Cheers<br>
Kerstin<br>
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