Hi Jacquie,<div><br></div><div>Defining a brain structure or ROI is usually performed by manual drawing. The manual definition is usually treated as a gold standard (if it is done by an experienced person). However, as you pointed out, it has several problems; it requires training, time consuming, poor reproducibility, etc. Therefore, more automated approaches are much needed. The issue you raised, low resolution or poor contrast, is a more fundamental issue, because it affects both manual and automated approaches. For example, if the resolution is poor to reliably delineate a structure manually, the chance is high that the automated method is not reliable either.</div>
<div><br></div><div>When you choose to use an automated method, you have to tell the computer which structure you want to define, like hippocampus. Here, there are several points I want to make;</div><div><br></div><div>1) There are often multiple ways to define a structure of interest. For example, different anatomist may define the hippocampus in slightly different ways. In literature, the size of the hippocampus could be different as much as twice. In this context, "well-known ROI" means "well-described definition by a famous neuroanatomist about how to define the hippocampus". You may find that there are surprisingly a small number of publications for this type of topics. For the hippocampus, I recommend you to go over some work by European consortium by Dr. Giovanni B. Frisoni</div>
<div>2) Some may want only a subregion of the hippocampus, like CA1, CA2, etc. As you try to define more and more detailed structures, you find that the smallest structure you can possibly define is the image pixels. Namely, you can theoretically define corresponding pixel coordinates across subjects. This is the idea of the voxel-based analysis. In this case, your ROI is one pixel. One of the most "well-known ROIs" in this case is the MNI coordinates. Instead of saying, "an ROI in the hippocampus", you can say, "MNI coordinate X, Y, Z".</div>
<div>3) However, usually, when one says, "ROI", that is not a single pixel, but a cluster of pixels that contain an anatomical representation, such as "the hippocampus". In this case, computer algorithms often require a prior definition. Many programs use a prior probabilistic map based on manual delineation. I believe a program like FreeSurfer comes with prior probabilistic maps. In this case, these maps serve as "well-known ROI".</div>
<div>4) Some other programs (like our MriStudio) use a pre-segmented atlas. As I mentioned above (#1), there is some degree of arbitrariness when we define a structure. However, once a structure is defined in an atlas, we can claim that we can apply a consistent definition to all images. There are widely used atlases for cortical ROIs (such as AAL and PickAtlas). The MriStudio program family (RoiEditor) comes with a pre-segmented atlas called, "white matter parcellation map (WMPM). This is a bit misnomer, because it also contains parcellation of the gray matter. I'm not sure if we can call it "well-known", but it is an option.</div>
<div>5) The approach I described in #4 is basically the same as the voxel-based approach (#2) because you need to warp the atlas (e.g. WMPM) to other subjects, which requires voxel-to-voxel mapping between the two images. The voxel-to-voxel mapping is performed independent of any structural definitions. This means, once voxel-to-voxel mapping (called image normalization or transformation) is completed, you can define any arbitrary structure in one brain and this definition is automatically transferred to the other. Therefore, you can define your own ROI (do not have to use the WMPM we provide). In this context, whether the ROI is "well-known" or not seems not a critical issue to me. What is more critical is if the voxel-to-voxel mapping is accurate or not.</div>
<div><br></div><div>I hope you find this helpful.</div><div><br></div><div>Susumu</div><div><br></div><div><br></div><div><br><div class="gmail_quote">On Wed, Jul 20, 2011 at 4:33 PM, Jacquie Hodge <span dir="ltr"><<a href="mailto:Jacquie.Hodge@albertahealthservices.ca">Jacquie.Hodge@albertahealthservices.ca</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">Hello All,<br>
<br>
I have been going through older emails to try and answer my own questions and came across this email. Can someone please share with me a "well known Atlas" and maybe elaborate a bit on the uses for these, how it would help me and what I do with it?<br>
<br>
Thank you in advance :)<br>
<br>
Jacquie<br>
<br>
Jacquie Hodge MSc candidate in Neuroscience, BSc<br>
Neuroscience, University of Calgary<br>
Research Assistant, Calgary Pediatric Stroke Program<br>
Alberta Children's Hospital<br>
2888 Shaganappi Trail NW, Calgary, AB, Canada T3B 6A8<br>
Phone: <a href="tel:403-955-7733" value="+14039557733">403-955-7733</a> Fax: <a href="tel:403-955-2922" value="+14039552922">403-955-2922</a><br>
<a href="mailto:jacquie.hodge@albertahealthservices.ca">jacquie.hodge@albertahealthservices.ca</a><br>
Program website: <a href="http://www.perinatalstroke.com" target="_blank">www.perinatalstroke.com</a><br>
________________________________________<br>
From: <a href="mailto:mristudio-users-bounces@mristudio.org">mristudio-users-bounces@mristudio.org</a> [<a href="mailto:mristudio-users-bounces@mristudio.org">mristudio-users-bounces@mristudio.org</a>] On Behalf Of [Seongjin] [<a href="mailto:choisj70@gmail.com">choisj70@gmail.com</a>]<br>
Sent: February 28, 2011 10:15 AM<br>
To: DTI Studio, ROI Editor, DiffeoMap Questions/Support<br>
Subject: Re: [Mristudio-users] About loaded ROI into my Anatomy Image<br>
<div class="im"><br>
I believe that you should do spatial normalization of your data to a well known ATLAS first.<br>
<br>
SC<br>
<br>
<br>
<br>
</div><div class="im">On Mon, Feb 28, 2011 at 8:15 AM, Yibao Wang <<a href="mailto:cmuwyb@gmail.com">cmuwyb@gmail.com</a><mailto:<a href="mailto:cmuwyb@gmail.com">cmuwyb@gmail.com</a>>> wrote:<br>
<br>
<br>
Is there a method to load the well-known ROI into my Anatomy Image?<br>
I explain my question in detail,<br>
for example, the are lots of well-known ROI such as insular, hippocampus,<br>
it was diffcult to draw it in the anatomy image, sometimes because its poor resoultion.<br>
Could we loaded those ROI into my Image?<br>
I wonder is there any software could analysize the well-konwn interested ROI from the poor resolution anatomy image.<br>
<br>
<br>
_______________________________________________<br>
mristudio-users mailing list<br>
</div><a href="mailto:mristudio-users@mristudio.org">mristudio-users@mristudio.org</a><mailto:<a href="mailto:mristudio-users@mristudio.org">mristudio-users@mristudio.org</a>><br>
<div class="im"><a href="http://lists.mristudio.org/mailman/listinfo/" target="_blank">http://lists.mristudio.org/mailman/listinfo/</a><br>
</div>Unsubscribe, send a blank email to: <a href="mailto:mristudio-users-unsubscribe@mristudio.org">mristudio-users-unsubscribe@mristudio.org</a><mailto:<a href="mailto:mristudio-users-unsubscribe@mristudio.org">mristudio-users-unsubscribe@mristudio.org</a>><br>
<br>
<br>
<br>
<br>
<br>
<<<br>
ATT00001..c (0.3KB)<br>
<br>
(0.3KB)<br>
>><br>
<br>
This message and any attached documents are only for the use of the intended recipient(s), are confidential and may contain privileged information. Any unauthorized review, use, retransmission, or other disclosure is strictly prohibited. If you have received this message in error, please notify the sender immediately, and then delete the original message. Thank you.<br>
<div><div></div><div class="h5"><br>
_______________________________________________<br>
mristudio-users mailing list<br>
<a href="mailto:mristudio-users@mristudio.org">mristudio-users@mristudio.org</a><br>
<a href="http://lists.mristudio.org/mailman/listinfo/" target="_blank">http://lists.mristudio.org/mailman/listinfo/</a><br>
Unsubscribe, send a blank email to: <a href="mailto:mristudio-users-unsubscribe@mristudio.org">mristudio-users-unsubscribe@mristudio.org</a><br>
</div></div></blockquote></div><br></div>