<div dir="ltr"><div><div>Hi Dan<br><br></div>No worries at all; it can take a little while to wrap your head around having things operate in scanner space, most people are used to either voxel coordinates or MNI space; but for multi-modality per-subject data it makes a lot of sense.<br>
<br></div>As long as the seed image 'overlaps' with the diffusion data in scanner space, then yes, a ROI drawn on the anatomical image can be used directly in streamtrack; it doesn't matter if the voxel grids are oriented differently with respect to the scanner axes, or the voxel sizes are different. The overlay tool in MRview is handy for assessing image alignment in such circumstances. I will raise two more points here however:<br>
<ol><li>At least some form of image registration is required, to account for inter-sequence subject motion and/or scanner re-calibration. Personally I register the anatomical image to the diffusion images before deriving any other images (e.g. seeding masks) from it; that way, all derived images have the same header transform as the anatomical image, and therefore also align with the diffusion data in scanner space. Alternatively, you can use the transform derived from registration and apply it to the relevant ROI as you have been, but omit the step where the ROI data is re-gridded to match the diffusion images.</li>
<li>Due to the presence of susceptibility-induced geometric distortions in EPI, a simple linear transform (whether rigid-body or affine) is generally not adequate to achieve good alignment between the structural and diffusion images. Therefore, although you can in principle use a high-resolution seed image, in reality the anatomical structure you have delineated in the high-resolution image may not map to the correct anatomical location in the diffusion images, unless you have explicitly performed susceptibility distortion correction. Personally I am a big advocate of the reversed phase-encode method for estimating the inhomogeneity field and subsequently correcting for these distortions, and always recommend to people that they should commence acquiring the relevant data in all of their studies.</li>
</ol><p>With regards to tracks2prob, as long as the T1 and diffusion image data overlap in scanner space, then again yes, you can use the T1 image as the template image for tracks2prob. You can even use both the -template and -vox options in conjunction to produce a TDI where the voxel grid is aligned with that of the T1 image, but the voxel size is smaller.</p>
<p><br></p><p>Happy tracking!<br>Rob</p></div><div class="gmail_extra"><br clear="all"><div><div dir="ltr"><br>--<br><br><span style="color:rgb(255,102,0)"><b>Robert Smith, Ph.D</b><br>Research Officer, Imaging Division</span><br>
<br>The Florey Institute of Neuroscience and Mental Health<br>Melbourne Brain Centre - Austin Campus<br>245 Burgundy Street<br>Heidelberg Vic 3084<br>Ph: +61 3 9035 7128<br>Fax: +61 3 9035 7301<br><a href="http://www.florey.edu.au" target="_blank">www.florey.edu.au</a><br>
<span style="font-size:9pt;font-family:"Times New Roman","serif";color:red"></span></div></div>
<br><br><div class="gmail_quote">On Mon, Jan 13, 2014 at 6:14 AM, Daniel Lumsden <span dir="ltr"><<a href="mailto:doclumsden@hotmail.com" target="_blank">doclumsden@hotmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div><div dir="ltr">Rob<br><br>Thank you for a very helpful answer - apologies for slow acknowledgement and reply!<br><br>Given that mrtrix generates streamlines in "real space", does this mean that I could create a seed region from an anatomical image converted from the dicom to nifti using mrconvert, then supply that mask directly to streamtrack?<br>
<br>I've been creating mask images from reasonably high resolution T1 images, then using the linear transform generated by flirt in FSL (transform of structural scan to diffusion scan) to transform these mask images into the much lower resolution diffusion space. <br>
<br>If I can supply the seed directly, could I then use my T1 image as the template for tracks2prob to visualise the track density on the scans without needing to apply any transformation?<br><br>I hope this isn't a hopelessly naive question!<br>
<br>Dan<br><div class="hm HOEnZb"><br></div><div><div class="hm HOEnZb"><hr>Date: Sun, 22 Dec 2013 10:37:52 +1100<br>Subject: Re: [Mrtrix-discussion] Question about filter_tracks command<br>From: <a href="mailto:r.smith@brain.org.au" target="_blank">r.smith@brain.org.au</a><br>
To: <a href="mailto:doclumsden@hotmail.com" target="_blank">doclumsden@hotmail.com</a><br>CC: <a href="mailto:mrtrix-discussion@www.nitrc.org" target="_blank">mrtrix-discussion@www.nitrc.org</a></div><div><div class="h5">
<br><br><div dir="ltr"><div><div><div><div>Hi Dan<br><br></div>If you use the -template option in tracks2prob with the FA image as the template, then yes, the transformation (at least the orientation component) will be identical to the FA image. The offset component of the transform will differ slightly if the voxel size is different in the TDI.<br>
<br></div>This question does however raise an important difference between MRtrix and other packages. The streamlines are generated and stored in 'real' / 'scanner' space, rather than with respect to any particular image space. To read an image value at a particular streamline position, the location is mapped according to the transform of that particular image. Therefore, it is not actually necessary for the ROI to be 'in the same space' (i.e. on the same voxel grid) as the image used to generate the streamlines; as long as the images are correctly aligned / registered, the streamline position in scanner space can be transformed to the appropriate location in the image volume.<br>
<br></div>Theoretically, you could have a ROI based on the FA image, a ROI based on the high-resolution TDI, and a ROI based on a (co-registered) anatomical image, and they could all be used in the same call to filter_tracks.<br>
<br>So if the purpose of the TDI is to identify a particular pathway and draw a ROI, it doesn't actually matter whether or not the -template option is provided to tracks2prob; the TDI will always be inherently aligned with the streamlines data, regardless of the alignment of the voxel grid. Though as an aside, you'll find the TDI file size will be much smaller if the -template option is <i>not</i> used, as it then uses the streamlines data to determine the required spatial extent of the image, so you don't get as much 'dead space' around the brain.<br>
<br></div>Happy holidays all<br>Rob<br></div><div><br clear="all"><div><br>--<br><br><span style="color:rgb(255,102,0)"><b>Robert Smith</b><br>Post-Doctoral Researcher, Imaging Division</span><br><br>The Florey Institute of Neuroscience and Mental Health<br>
Melbourne Brain Centre - Austin Campus<br>245 Burgundy Street<br>Heidelberg Vic 3084<br>Ph: <a href="tel:%2B61%203%209035%207128" value="+61390357128" target="_blank">+61 3 9035 7128</a><br>Fax: <a href="tel:%2B61%203%209035%207301" value="+61390357301" target="_blank">+61 3 9035 7301</a><br>
<a href="http://www.florey.edu.au" target="_blank">www.florey.edu.au</a><br><span style="font-size:9pt;font-family:"Times New Roman","serif";color:red"></span></div>
<br><br><div>On Sun, Dec 22, 2013 at 4:55 AM, Daniel Lumsden <span dir="ltr"><<a href="mailto:doclumsden@hotmail.com" target="_blank">doclumsden@hotmail.com</a>></span> wrote:<br><blockquote style="border-left:1px #ccc solid;padding-left:1ex">
<div><div dir="ltr">Dear All<br><br>I'm interested in using the improved resolution from track density images to help improve my ROI generation to select tracks from a whole brain tractography .tck file.<br><br>I can define, e.g., the PLIC much more sharply from the track density image generated from whole-brain tractography much more easily then from the standard colour coded FA maps. The orientation of the track density image depends upon the -template image supplied for tracks2prob step when generated. If I use the FA maps as the template, does this automatically put the ROI drawn from the resultant track density maps in diffusion space? If so I presume I can use these ROI to directly filter the streamlines I'm interested from the whole brain tractography .tck file without applying any transformation? <br>
<br>Many thanks in advance<br><br>Dan<br> </div></div>
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