<div>Thank you Hangyi and Susumu for your quick and, as always, detailed replies, and my apologies for the unclear question. Please let me give some more details.</div>
<div> </div>
<div>Our current workflow is as follows:</div>
<div>DTI Studio: to create FA, ADC, etc. maps.</div>
<div>DiffeoMap: AIR registration of FA, ADC, etc., to JHU templates (which resamples), then LDDMM registration to JHU templates. Apply Kimap.</div>
<div>ROIEditor: Extract FA, ADC, etc on the subject image (now in template space) using the Type II WMPM atlas.</div>
<div> </div>
<div>One of the ROIs we found significiant was the Nigra. Our original image slice was 4.6mm thick with a .4mm gap. The Nigra from the Type II WMPM is only 6mm thick. After reading your comments, I would generalize my question as: is there a minimum ROI threshold size that I should be using, relative to the size of my acquisition voxels? If we can throw some of the smaller ROIs out, it would also help with multiple comparisons. If it was your paper, would you include the Nigra, considering the original slice dimensions? Perhaps this is one area where manual ROI placement would be superior to autamated placement.</div>
<div> </div>
<div>Thank you very much,<br>Jeff Sadino<br><br></div>
<div class="gmail_quote">On Fri, Mar 25, 2011 at 9:20 AM, susumu mori <span dir="ltr"><<a href="mailto:susumu@mri.jhu.edu" target="_blank">susumu@mri.jhu.edu</a>></span> wrote:<br>
<blockquote style="BORDER-LEFT: #ccc 1px solid; MARGIN: 0px 0px 0px 0.8ex; PADDING-LEFT: 1ex" class="gmail_quote">Hi Jeff,<br><br>Maybe I didn't quite understand your question, but if you are talking<br>about the LDDMM-based image segmentation, each ROI is 3D. So, I'm not<br>
sure if you encounter a situation where you deal with a ROI in one<br>slice, although maybe this is not relevant to your question.<br><br>Suppose your original image is 3mm and you resample it to 1mm. Then if<br>you draw one 2D ROI, you have a choice of 3 slices within the native<br>
3mm slice. The center slice could be identical to the original image<br>but the edge two slices may be interpolated if you used trilinear<br>interpolation option. If you use the nearest neighbor, you simply get<br>3 1mm copies of the original 3mm slice.<br>
<br>I believe your question can be generalized as "what is the effect of<br>interpolation". Interpolation is a difficult issue. If you have an FA<br>map and interpolate it, you get a different result from interpolating<br>
a tensor map and re-calculate a FA map from the interpolated tensor<br>map. There are also multiple options for interpolation. I would<br>recommend you to stick with one method and I don't think that we can<br>conclude one is better than the other.<br>
<br>You can also bring the pre-segmented atlas map all the way to your<br>original image space. In this way, you can at least forget about the<br>interpolation issue.<br><br>Susumu<br>
<div>
<div></div>
<div><br>On Fri, Mar 25, 2011 at 1:47 PM, Jeff Sadino <<a href="mailto:jsadino.queens@gmail.com" target="_blank">jsadino.queens@gmail.com</a>> wrote:<br>> Hello,<br>> I am wondering about how DiffeoMap upsamples the slice number when<br>
> performing linear registration to the JHU template. After doing the LDDMM<br>> process, I have some ROIs that look interesting. However, these ROIs are<br>> smaller than my slice thickness. I am wondering how valid it is to draw<br>
> conclusions about an ROI that exists entirely at sub-native voxel<br>> resolution.<br>> Thank you,<br>> Jeff Sadino<br></div></div>> _______________________________________________<br>> mristudio-users mailing list<br>
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