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On 22 July 2012 11:27, Lúcia Garrido <[log in to unmask]> wrote:
Many thanks for your responses and all the information. It's all very helpful.

I varied the parameters you mentioned and, just in case this can be of interest to someone else, I summarize a few things below.

1. In my case, MRF seems to have worked better to clean up the segmentation. I used MRF of 2 as you suggested. I attach on example (example3_MRF2) and also how it compared with just the default setting of MRF = 0 (example3_default_MRF2). Overall, as far as I could tell increasing the MRF to 2 removed better non-brain tissue, or at least gave it lower intensities,  and didn't affect much the intensity values of actual grey matter. Although results from using MRF = 2 seemed better overall, results were still not perfect (see example4_MRF2 - sent in separate e-mail because of limit of size of attachments). 

2. Changing warping regularisation (I changed from 4 to 1) didn't seem to change things much. Is this expected?

3. Changing sampling distance from 3 to 1 (resolution in my scans is 1 mm) resulted in much longer segmentation (from about 10 mins to 2 hours and half) but not improved results for the specific problem I had. In fact, in a few cases, there's even more non-brain included.

Many thanks and bets regards,

Lucia

On 19 July 2012 07:28, John Ashburner <[log in to unmask]> wrote:
> I've been using new segmentation and had a few questions that I'd be very
> grateful if someone could answer or had any suggestions.
>
> I've done new segmentation and I think for many subjects it didn't work very
> well well. I've attached one example and there are many other subjects like
> this. It seems like the regions of the inferior temporal lobes were not
> segmented very well.

They look mostly OK to me, although there is a bit of non-brain included.

>
> I used the default options in new segment, so I used:
> - bias regularisation:  'very light regularisation (0.0001)
> - bias FWHM: 60mm cutoff
> - Used the tissue probability maps in TPM, 1 to 6, with these respective
> number of Gaussians: 2, 2, 2, 3, 4, 2.
> - MRF parameter: 0
> - Warping regularisation: 4
> - Sampling distance: 3
>
> So my questions are:
> 1. Do you have any suggestions about what I can do differently to get better
> segmentation?

Segmentation largely relies on voxel intensities, so MRI sequences can
be optimised to make the GM intensity as different from that of other
tissues as possible.  This is probably not so helpful for the data you
have collected already though.

Manual editing of the segmentation results would be another
possibility.  At the moment, manual segmentation is generally
considered to be as close to a gold standard as anything, so manual
editing should be considered acceptable - providing whoever is doing
the editing knows nothing about which subjects are in which group etc.

There are also many other segmentation approaches that may be a better
model for your data.  You could try some of these.


>
> 2. Has anyone varied the parameters above systematically and would be
> willing to share what they found with the list?

Try setting MRF parameter to 2, and see what happens.  This may clean
things up slightly.


> I know that any results are going to depend a lot on the data we have, but
> I'd appreciate any insights about the different parameters. The manual is
> very helpful in explaining the different parameters, but I'd like to get a
> better idea about the effects of each of them. Moreover, for certain
> parameters, I'm not sure even how to vary them. In particular, for the MRF
> parameter, warping regularisation, and sampling distance, I'm not sure
> within which intervals these parameters can vary...

MRF parameter was a late addition to spm8.  I didn't want it to change
the output from the previous updates of spm8, so I gave it a default
value of 0.  A value of 2 may give slightly cleaner results, but if
you go much higher, you may begin to lose some of the detail from the
segmentation results.

Warping regularisation can often be decreased slightly for T1w images.
 This controls the amount of freedom of the deformation part of the
model.  More regularisation gives less freedom.  I chose this for the
default setting of relatively heavy regularisation because with too
much freedom, the algorithm can begin to treat the liquid contents of
the eyeballs as CSF, and squash the eyes into the brain.  Really, I
should either include eyeballs as part of CSF tissue priors, or
introduce a new eyeball tissue class.  This would allow the
regularisation to be decreased in order to more closely match the
tissue priors with the scans.  The eyeball squashing problem is less
severe for T1w than it is for other contrasts (where CSF is more
clearly visible), so you may be able to decrease the amount of
regularisation by a factor of about 10.

Sampling distance is set to a default value of 3mm.  If you have 1mm
resolution, you could get slightly better segmentations by decreasing
this distance to 1mm.  This is not the default because it would result
in the algorithm taking 27 times (3 x 3 x 3) as long to run.

>
> 3. I also have a question about dartel, and I'm sorry if this sounds
> trivial... In the manual, it says that dartel takes about one week for 400
> subjects. But I've run dartel with around 200 subjects and it took about 8
> hours. I have an iMac with 2.8 GHz i7, and 16GB ram. It seems it should take
> longer than 8 hours, and was wondering if that estimation of a week was from
> a long time ago... I'm also happy that dartel takes more time if the
> registration results are better. So if someone has any advice about this,
> I'd really appreciate your help.

Maybe I should update the manual.  The one week result was for my five
year old laptop.

> The parameters I've been using for dartel are the default ones:
> - regularisation form: linear elastic energy
> - 6 outer iterations, each with 3 Gauss-Newton iterations, default
> regularisation parameters, time steps (varying from 1 to 64), and smoothing
> parameters
> - default optimisation settings
> Like for the segmentation case, I'd very much appreciate any information
> about the results of varying any of these parameters.

The default settings work reasonably well for most data.  There are a
couple of settings for the linear elasticity.  The first one is the
amount of penalty on length changes, whereas the second one penalises
volume changes.  I haven't fully explored the effects of changing the
settings - although I'm pretty sure that there is some room for
improvement.

Best regards,
-John



--
Lúcia Garrido
Post-Doctoral researcher
Vision Sciences Laboratory
Harvard University

[log in to unmask]

http://sites.google.com/site/garridolucia/




--
Lúcia Garrido
Post-Doctoral researcher
Vision Sciences Laboratory
Harvard University

[log in to unmask]

http://sites.google.com/site/garridolucia/