[Mristudio-users] new option save fiber density

Zhang, Aifeng azhang at psych.uic.edu
Wed Aug 18 18:08:43 EDT 2010


Dear DtiStudio,

A further question on this topic:
Is the statistics (by clicking the statistics button in DtiStudio) given along the select fibers density-weighted or not?

thanks,
Aifeng
From: mristudio-users-bounces at mristudio.org [mailto:mristudio-users-bounces at mristudio.org] On Behalf Of susumu mori
Sent: Saturday, July 24, 2010 7:57 AM
To: DTI Studio, ROI Editor, DiffeoMap Questions/Support; Hangyi Jiang
Subject: Re: [Mristudio-users] new option save fiber density

Hi Venkat,

After fiber tracking, it is a common practice to quantify the results. For the quantification, the streamline information of the tractography needs to be converted to pixel information. For this conversion, the simplest way is to use 1/0 binarilzation. If a pixel contains a streamline, it becomes 1 and if not, remains 0. This is basically a masking, which can be applied to, for example, a FA map and get a FA value of the tract. You can also count the number of pixels with "1" and use it as the tract volume.

One problem of this simple approach is that even if a pixel contains 10 streamlines, the pixel becomes "1", which is the same as another pixel that contains only 1 streamline. Namely, during the binalization, information about the density of the streamline is lost. I believe (Hangyi, please correct me if I'm wrong) "fiber density map" tells how many streamlines were there in each pixel. You can potentially use it to get, for example, density-weighted FA value, in which pixels that contain more streamlines are more weighted than those contain only 1 streamline.
On Fri, Jul 23, 2010 at 6:19 PM, Rajagopalan, Venkateswaran <rajagov2 at ccf.org<mailto:rajagov2 at ccf.org>> wrote:


Dear All,

I am using DTIstudio_latest_x86.exe after fiber tractography I notices a new option named "save fiber density map" (normalized and non normalized). I am wondering what information does this fiber density map convey and how this information can be used for instance to compare between two groups. How the map is normalized.

Thanks

Venkat

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