<div dir="ltr"><div><div>Hi,<br></div>For scatter and assuming you have the planning CT, you could consider the <a href="http://www.openrtk.org/RTK/news/201507_press.php">solution of Yang et al</a> (that he implemented from Niu et al) that is much simpler than Monte Carlo. I know two teams that have already implemented it using RTK and we will try to do our own in the future.<br></div><div>For photon statistics, Cyril has recently been working on a weighted least square solution, see, e.g., <a href="https://github.com/SimonRit/RTK/commit/b133c0bb96bff6805dd28c7820a89310629ff031">this commit</a>. But I don't think it's mature yet.<br></div><div>Note that we discussed pre-processing in July in Lyon, the minutes are <a href="http://wiki.openrtk.org/index.php/RTK/Meetings/TrainingNov15#Pre-processing">here</a>.<br></div><div>Good luck, it's not an easy task,<br></div>Simon</div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Dec 1, 2015 at 9:50 AM, Jonathan Mason <span dir="ltr"><<a href="mailto:s1015431@staffmail.ed.ac.uk" target="_blank">s1015431@staffmail.ed.ac.uk</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div style="word-wrap:break-word">Thank you Simon and Chao,<div><br></div><div>I apologise for the confusion—I can see that my message was not very clear. I am essentially trying to compensate for low photon flux and scatter, but am finding it difficult with pre corrected data. I will certainly take time to look through your suggested publications, so thanks for that.</div><div><br></div><div>Without having access to low level physical data, I am considering simulating a scanner with MC, where I will have the ground truth for scatter field and photon statistics, and try to produce reconstructions on this.</div><div><br></div><div>Many thanks,</div><div><br></div><div>Jonathan</div><div><div class="h5"><div><br><div><blockquote type="cite"><div>On 1 Dec 2015, at 07:27, Simon Rit <<a href="mailto:simon.rit@creatis.insa-lyon.fr" target="_blank">simon.rit@creatis.insa-lyon.fr</a>> wrote:</div><br><div><div dir="ltr"><div><div><div><div>Hi Jonathan,<br></div>I'm not sure I fully get it either. What I can say is that I was a postdoc at the NKI until the end of 2009 where I was working on the Elekta reconstruction software. The way <a href="http://www.openrtk.org/Doxygen/classrtk_1_1ProjectionsReader.html" target="_blank">rtk::ProjectionsReader</a> works for Elekta projections is close to what they were doing at the time, i.e., Boellaard scatter correction, cropping and simple log to go to a line integral. I know they have been improving it since (with lag and scatter corrections) but I'm not sure what's commercialized what's not. In any case, they publish / present what they do (see publications of M. van Herk, J-J. Sonke and L. Ploeger).<br></div>I'm not expert of Varian data but for sure, when you get pre-corrected projections, it's hard to know what part you're correcting (uncorrected problems or miscorrections). Instead of reverse engineering, which can be tough because Varian does a lot of stuff on the raw data I believe (look at the publications of J. Star-Lack), I would start from the raw data if you can access them.<br></div>Good luck,<br></div>Simon<br></div><div class="gmail_extra"><br><div class="gmail_quote">On Mon, Nov 30, 2015 at 7:50 PM, Chao Wu <span dir="ltr"><<a href="mailto:wuchao04@gmail.com" target="_blank">wuchao04@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">Hi Jonathan,<div><br></div><div>I do not quite understand your problem.</div><div>I think most information can be retrieved by the relationship between flux (I) and attenuation (u):</div><div>I = I0 * exp (- integral(u * dL) )</div><div>Of course there are other effects like beam hardening and scattering involved but this model is the basic.</div><div><br></div><div>Regards,</div><div>Chao</div></div><div><div><div class="gmail_extra"><br><div class="gmail_quote">2015-11-30 17:29 GMT+01:00 Jonathan Mason <span dir="ltr"><<a href="mailto:j.mason@ed.ac.uk" target="_blank">j.mason@ed.ac.uk</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Good afternoon RTK users,<br>
<br>
I have access to "raw data" from a Varian OBI scanner, and have<br>
experimented with RTK for performing its reconstruction. However, it is<br>
not really "raw" in the sense that the coefficients are proportional to<br>
the photon flux recorded at a given sensor, but is instead proportional<br>
to the Hounsfield attenuation along that path. With this data, it means<br>
that one can reconstruct using FDK and other iterative techniques, which<br>
assume a linear model, but the connection to the underlying physics is<br>
abstract.<br>
<br>
The problem I then have when trying to develop reconstruction<br>
techniques, is that I do not know whether I am really correcting for<br>
physical distortions or just correcting for Varian's preprocessing,<br>
which has been finely tuned for its own FDK method.<br>
<br>
My question is whether anybody has dug into the steps that manufacturers<br>
such as Varian or Elekta perform to arrive at these projection images?<br>
And if they think that if reverse engineered, could provide a richer set<br>
of information to facilitate advanced strategies.<br>
<br>
Best wishes,<br>
<br>
Jonathan Mason<br>
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