Hi Jan,<br><br>First of all, please make sure the following point;<br><br>1) The AIR (or Mutual information) in DtiStudio is for "intra-subject intra-DTI" image registration. DTI data consists of b0 images and diffusion-weighted images; typically there are tens of images, which need to be all co-registered before tensor calculation.<br>
<br>2) After tensor calculation, b0 and all tensor-derived maps (FA, color, eigenvalues) are all naturally co-registered each other and no further registration by AIR is not needed.<br><br>3) For intra-subject inter-contrast (e.g. T2 and b0/DTI) or inter-subject registration, you need to use DiffeoMap. This also include intra-subject but scanned at different time points.<br>
<br>4) In general, cross-contrast registration (e.g. b0 vs T1) is difficult.<br><br>Now, going back to your question, I'm not sure if you want intra-subject (+intra-DTI) or inter-data registration, but I guess the following steps are what you want;<br>
<br>> Get two b0s from subject A and B and load them into DiffeoMap. The first image you open (in this case A) will the the template.<br>> Do image registration by, for example, AIR, save the transformation matrix.<br>
> Load FA, trace, and other DTI-derived images of B and apply the transformation matrix.<br><br>Hope this will help.<br><br>Susumu<br><br><div class="gmail_quote">On Sat, Aug 7, 2010 at 12:53 PM, Jan Tillema <span dir="ltr"><<a href="mailto:Jan.Tillema@cchmc.org">Jan.Tillema@cchmc.org</a>></span> wrote:<br>
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<div>Dr. Mori,</div>
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<div>Thank you very much for your help on my last questions. In response to your answer on my questions from Jul 28 (regarding DTI data before/after intervention) - see below for details - I have a follow up question:</div>
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<div>I have only used DTIstudio and ROIEditor, and am not too comfortable with Diffeostudio yet. Since you mentioned to try linear transformation I tried the following using AIR in DTIstudio.</div>
<div>- I have all my processed data saved in analyze format - so I loaded these in DTIstudio.</div>
<div>- using rigid body transformation with AIR I get really nice results for co-registration of B0 images before & after treatment, but when I use the FA maps and individual val0,1&2 & color maps this (not fully surprising) don't always correlate well. </div>
<div>- I saved the AirMatrix.txt file from the B0 transformation </div>
<div>My questions:</div>
<div>--- How can I transform the other images (FA, val0, val1, val2, color map) using this Matrix???</div>
<div>--- Can this be done using DTIstudio or will that have to be done in Diffeomap</div>
<div>--- Is this an acceptable way to do it as long as the B0 images correspond (which they visually do nicely) and is there an easier way to do this using Diffeomap?</div>
<div> </div>
<div>Thanks</div>
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<div>JMT</div>
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<div>On Wed, Jul 28, 2010 at 4:01 PM, Jan Tillema <<a href="http://lists.mristudio.org/mailman/listinfo/mristudio-users" target="_blank">Jan.Tillema at cchmc.org</a>> wrote:<br><br>><i> I have a similar question.<br>
</i>><i> We have dataset of subjects before/after intervention, we have 15 dir DTI<br></i>><i> and 3D T1 data (GE) with same parameters both times, but orientation not<br></i>><i> exactly the same (clinical protocol). The brains are not normal at baseline<br>
</i>><i> with enlarged ventricles that may have changed minimally (due to treatment,<br></i>><i> e.g. smaller size). Normalization is not a possibility d/t abnormalities on<br></i>><i> brain to begin with, we just want to compare before/after. We are<br>
</i>><i> investigating the effect on white matter and would like to get best approach
</i>><i> to compare basic measurement before/after. We have manual (blinded) ROI<br></i>><i> showing differences before/after, but want to make sure we are in the exact<br></i>><i> same ROI. To co-register seems the best way, but tricky as the structure of<br>
</i>><i> the brain is not exactly the same. Any suggestions?<br></i>><i><br></i>><i> 1) would it be best to co-register DTI to T1 at both time points and then<br></i>><i> to co-register T1 in time point A to B followed by change of DTI with same<br>
</i>><i> matrix? If so, I assume this would have to be done with DiffeoMap, what<br></i>><i> would be the steps to do so?<br></i>><i><br></i><br>Unless there is a reason that you want T1-DTI be registered (e.g. ROI drawn<br>
in T1, FA measured in DTI), I think you can directly register DTI to DTI.<br>Yes, DiffeoMap should be able to do it.<br><br><br>><i> 2) is co-registration to "dangerous" for bias as there is the possibility<br>
</i>><i> that the brain is not exactly the same before and after (ventricle size<br></i>><i> change)<br></i>><i><br></i><br>First you have to decide if you want only linear transformation adjusting<br>the overall head positions or do non-linear to remove the tissue deformation<br>
due to the surgery. I suspect you want the former (I think the latter is<br>difficult).<br><br>Linear transformation is mostly driven by brain boundary. So, you can assume<br>that as long as the tissue deformation is mostly inside the brain and the<br>
brain boundary shape remains the same, the linear transformation should be<br>able to match the two brains. However, we have seen not-so-perfect linear<br>registration even between two images from the same person. Reason could be;<br>
the initial alignment was way off, there is an intense sinus signal in one<br>of them, etc. In the end, it is your subjective judgment if the linear<br>registration is satisfactory. If there is a good quantitative way to judge<br>
the alignment, we would have used such a metric to drive the linear<br>registration.<br><br>In your case, you may want to try the landmark function of DiffeoMap. You<br>need at least 3 point landmarks to define the corresponding structures<br>
between the two images. Unfortunately there are not many point landmarks<br>inside the brain. The exceptions are AC and PC. The third point could be<br>some easy-to-define structures in the brainstem at the mid-sagittal level<br>
such as the junction of the pons and midbrain. If you can clearly find these<br>3 points, place these landmarks in both images and use rigid alignment.<br><br>Let us know if this approach works.<br></div></div>
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