Hi,
my 2 cents on that take:
I absolutely agree with Mark on the possibility to normalize counts by relating them to the number of voxels in the original ROI.
However, shape may matter. Imagine, for example, a tumor pushing the motor strip forward so that it is more curved and bended than on the contralateral side. Or just think of the normal anatomical variability. Of course, you should incorporate that information and try to draw your ROIs to cover M1 as best as you can. Aside from the fact that motor mapping is rarely necessary to identify M1, activation studies are subject to their own localization errors / variability and anatomical differences are "smoothed" (also depending on the preprocessing of your FMRI). Dilated ROIs around activation peaks will completely attenuate / ignore the underlying anatomical shape. Btw - contrary to a widespread belief, it has NOT been shown conclusively that functional is superior to anatomic seeding for pyramidal tractography: As long as anatomic localization is well preserved and not concealed by a lesion’s mass effect or abnormalities of gyration, for example, precentral ROI placement according to pure structural criteria remains straight-forward and entirely sufficient. In these cases, benefits of functional ROI definitions cannot be expected. The study of Smits et al. [2007], which suggested a benefit of functional over anatomical guided tractography, was biased in that their FMRI-informed pyramidal tractography took advantage of a two-ROI approach whereas the anatomically guided counterpart employed just a single ROI in the peduncle. The single case illustrating anatomical landmark vs. FMRI-based pyramidal tractography in Schonberg et al. [2006] is not convincing because the anatomically defined ROI is only shown for the posterior limb of the internal capsule. Probably, it was also used in a single-ROI approach – otherwise the fibres rostral to the lesion should not have been extracted. Also, the particular lesion could well be of extra-axial origin, meaning that neither presurgical tractography nor FMRI would have been necessary.
So the question is: does the functional seeding makes sense for your particular tractography? (It may, for example, when you are tracking the arcuate fascicle.) And how do you preprocess your FMRI data? I.e., if you for some reason have to smooth by a rather large kernel, you may be fine dilating the peak activation voxel. It just depends;)
Cheers-
Andreas

-----Ursprüngliche Nachricht-----
Von: FSL - FMRIB's Software Library im Auftrag von Mark Jenkinson
Gesendet: Di 21.10.2008 14:14
An: [log in to unmask]
Betreff: Re: [FSL] How dilate ROI with fslmaths
 
Hi,

Now I see what you are trying to do.
There are two points worth mentioning:

  - Does it makes sense to have an area around your activation peak  
which,
	on average, goes further away from the peak just because it is near
	the edge of the brain mask?  Isn't there another way to normalise for
	what you want in your final output?  For instance, dividing by the  
number
	of voxels in the original ROI would normalise counts.  It depends on
	what your final objective is.

  - If you really do want to control the size of the ROI more  
sensitively then
	you are better off dilating directly from the original peak, rather  
than
	expanding from the boundary of an already large sphere.  This is  
because
	you have a large surface area of the 5mm sphere and the dilation cannot
	distinguish between different points on the surface.  However, if you  
use a
	large kernel directly on a single voxel (your activation peak) then  
you can
	distinguish between points based on how far they are (to sub-voxel  
precision)
	away from the original point.  For example, taking a one voxel seed  
point
	in 2mm space and dilating by spheres of radii 1,2,3,4,5,6,7,8 mm  
gives you
	outputs of size 1,7,19,33,81,123,179,257 voxels.  And you can use  
smaller
	changes, for instance a 7.3mm kernel gives 203 voxels and a 7.5mm  
kernel
	gives 251 voxels.  So, by trying different values (and masking  
afterwards) you
	can probably find a value for the kernel which gets you close.

However, I would think more about why you want the same number of  
voxels in
each ROI, and whether there are better ways of controlling for this,  
as comparing
things with ROIs of different shape is also probably not what you want.

All the best,
	Mark


	

On 21 Oct 2008, at 12:14, Markus Gschwind wrote:

> Hi Mark!
>
> Thanks a lot for your kind answer! OK, I will be more precise.
>
> I need ROIs (=binarised spheres around the activation peak) which  
> have about the same number of voxel (for fibertracking).
>
> The problem is that some peaks are quite close to the brain border  
> and thus the sphere (5mm radius) extends beyond the mask and gets  
> partially cut, which reduces its number of voxels (3x3x3 image  
> reslotion).
>
> I thus would like to dilate those ROIs in direction of inside the  
> brain in order to compensate for this.
> Now I found that when I am dilating a sphere of 170 voxels (this is  
> what the spm-script produced for that sphere of 5mm) with the  
> default kernel of 3, I get a sphere of about 450 voxels and not 200.  
> This is due to the small size. If I would be dilating a 1000 voxel  
> sphere, the increasing step could be a much smaller percentage.
> Maybe this is a principal problem... and I am thinking the wrong  
> direction...
>
> What I would like to achieve is that every ROI has finally about 200  
> +/- 10 voxels
>
> Thanks a lot for your help!
> All the best, Markus
>
>
>
>
> 2008/10/21 Mark Jenkinson <[log in to unmask]>
> Hi,
>
> What do you mean by "a tiny bit"?
> Is one voxel too much?
> For one voxel you can just use the default kernel.
>
> If you have a binary mask (or ROI mask) then it isn't
> really well defined to add less than one voxel onto the edge.
>
> Maybe if you describe what you are trying to achieve
> then we can work out what is the best thing to do.
>
> All the best,
>        Mark
>
>
>
>
> On 21 Oct 2008, at 10:25, Markus Gschwind wrote:
>
> Hello again!
>
> It seems that
>
> fslmaths INPUT  -kernel sphere 0.5 -dilD OUTPUT
>
> or
> fslmaths INPUT  -kernel sphere 1 -dilD OUTPUT
>
> is not possible.
>
> It begins at -kernel sphere 3.
>
> Is that right?
>
> How could I dilate my ROI only a tiny bit?
>
> Any hints would be greatly apreciated!
> Thanks,
> Markus
>
>
>
> 2008/10/17 Matthew Webster <[log in to unmask]>
> Hello,
>           The kernel needs to be set before the desired filtering  
> operation ( with the default kernel being a 3x3x3 box ).
>
> e.g. to dilate using a 5mm radius spherical kernel around each zero- 
> voxel use the following command:
>
> fslmaths INPUT  -kernel sphere 5 -dilD OUTPUT
>
> Unfortunately there is no specific option to dilate such that the  
> output image has a specific number of voxels...
>
> Many Regards
>
> Matthew
> Hi Steve!
>
> Thank you for the hint. However it is still not clear to me how to  
> use this command.
>
> fslmaths INPUT -dilD OUTPUT  >> dilates + 1 voxel all around
>
> fslmaths INPUT -dilD -kernel 5 OUPUT >> no effect
>
> fslmaths INPUT -kernel sphere 5 OUTPUT >> no effect
>
> How would be the correct command to dilate the input so as the  
> OUTPUT finally has 500 voxels?
>
> Thank you so much!
>
> All the best,
> Markus
>
>
>
>
> 2008/10/16 Steve Smith <[log in to unmask]>
> Hi - you can change the dilation kernel with the -kernel option  
> (type fslmaths to see the options).
> Cheers.
>
>
>
> On 16 Oct 2008, at 15:00, Markus Gschwind wrote:
>
> Hi experts!
>
> I have to dilate ROIs up to a certain voxelsize.
>
> I think this works with fslmaths -dilD or -dilM
>
> However I would like to know if there is a mean  to stop the  
> dilation at a given number of voxels.
> Does anybody know?
>
> Thanks a lot!
> Markus
>
>
>
> -- 
> Dr. med. Markus Gschwind, M.D.
> Laboratory for Neurology and Imaging of Cognition
> Dept of Neurosciences
> University Medical Center (CMU)
> 1 Michel-Servet - 1211 GENEVA - CH
>
> Tel 0041 (0) 22 379 5324
> Fax 0041 (0) 22 379 5402
> email: [log in to unmask]
> http://labnic.unige.ch
>
>
> ---------------------------------------------------------------------------
> Stephen M. Smith, Professor of Biomedical Engineering
> Associate Director,  Oxford University FMRIB Centre
>
> FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
> +44 (0) 1865 222726  (fax 222717)
> [log in to unmask]    http://www.fmrib.ox.ac.uk/~steve
> ---------------------------------------------------------------------------
>
>
>
> -- 
> Dr. med. Markus Gschwind, M.D.
> Laboratory for Neurology and Imaging of Cognition
> Dept of Neurosciences
> University Medical Center (CMU)
> 1 Michel-Servet - 1211 GENEVA - CH
>
> Tel 0041 (0) 22 379 5324
> Fax 0041 (0) 22 379 5402
> email: [log in to unmask]
> http://labnic.unige.ch
>
>
>
>
> -- 
> Dr. med. Markus Gschwind, M.D.
> Laboratory for Neurology and Imaging of Cognition
> Dept of Neurosciences
> University Medical Center (CMU)
> 1 Michel-Servet - 1211 GENEVA - CH
>
> Tel 0041 (0) 22 379 5324
> Fax 0041 (0) 22 379 5402
> email: [log in to unmask]
> http://labnic.unige.ch
>
>
>
> -- 
> Dr. med. Markus Gschwind, M.D.
> Laboratory for Neurology and Imaging of Cognition
> Dept of Neurosciences
> University Medical Center (CMU)
> 1 Michel-Servet - 1211 GENEVA - CH
>
> Tel 0041 (0) 22 379 5324
> Fax 0041 (0) 22 379 5402
> email: [log in to unmask]
> http://labnic.unige.ch