<div dir="ltr">Hi Rafael,<div><br></div><div>I will try to find the information for you but I fear it will be difficult as these datasets are at least 4 years old and from an old 1.5T Siemens scanner.</div><div><br></div><div>You would want TE/TR, delta, Delta, etc? I know that I will not have delta, Delta. I might be able to find TR, TE and other basic parameters.</div><div><br></div><div>Best</div><div><br></div><div class="gmail_extra"><div><div class="gmail_signature"><div dir="ltr"><div>Max</div></div></div></div>
<br><div class="gmail_quote">On Wed, Jul 8, 2015 at 3:46 AM, Rafael Henriques <span dir="ltr"><<a href="mailto:rafaelnh21@gmail.com" target="_blank">rafaelnh21@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><span style="font-size:12.8000001907349px">Hi all,</span><div style="font-size:12.8000001907349px"><br></div><div style="font-size:12.8000001907349px">I am currently participating in Google Summer of Code and I am implementing on Dipy a module for diffusion kurtosis imaging, a technique useful to probe in vivo tissue heterogeneity and complexity. </div><div style="font-size:12.8000001907349px"><br></div><div><span style="font-size:12.8000001907349px">Our first results are looking very good (you can see them here: </span><a href="http://gsoc2015dipydki.blogspot.co.uk/2015/07/rnh-post-6-mid-term-summary.html" style="font-size:12.8000001907349px" target="_blank">http://gsoc2015dipydki.blogspot.co.uk/2015/07/rnh-post-6-mid-term-summary.html</a><span style="font-size:12.8000001907349px">), however when I try to process the Dipy's multi-shell dataset example </span><span style="font-size:12.8000001907349px">Sherbrooke 3 shells, kurtosis measures seem to be widely corrupted by implausible high negative values (black regions on the images of the following link:<a href="http://gsoc2015dipydki.blogspot.co.uk/2015/07/rnh-post-7-artifacts-in-dipys-sample.html" target="_blank"> http://gsoc2015dipydki.blogspot.co.uk/2015/07/rnh-post-7-artifacts-in-dipys-sample.html</a></span><span style="font-size:12.8000001907349px">). </span></div><div><span style="font-size:12.8000001907349px"><br></span></div><div><div style="font-size:12.8000001907349px"><span style="font-size:12.8000001907349px">Implausible high negative values of kurtosis are a common artifact on DKI, however, given the data’s b-value and number of gradient directions, I was not expecting having implausible negative values in almost all brain image voxels</span><span style="font-size:12.8000001907349px">. To try understanding why diffusion kurtosis is not working on this dataset</span><span style="font-size:12.8000001907349px">, I was wondering if anyone knows the</span><span style="font-size:12.8000001907349px"> full scanning parameters of this dataset?</span></div><div style="font-size:12.8000001907349px"><span style="font-size:12.8000001907349px"><br></span></div><div style="font-size:12.8000001907349px"><span style="font-size:12.8000001907349px">Many thanks in advance,</span></div><div style="font-size:12.8000001907349px"><span style="font-size:12.8000001907349px"><br></span></div><div style="font-size:12.8000001907349px"><span style="font-size:12.8000001907349px">Rafael</span></div></div></div>
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