[MINC-users] Classify

[Jason Lerch]

Hi Jon,

classify is based on using a training set to initialize the tissue  
classification - either based on probability maps or on manually  
selected tags. In other words, you could use Display to pick 100  
points or so that you think are grey matter, 100 that are white  
matter, etc., then use that to initialize the classification of every  
voxel. Once you've trained the classifier once you can also save the  
training data and apply it to new volumes without repicking individual  
points (though this is quite scanner specific - i.e. it usually works  
for one sequence from one site, not across sequences or sites - for  
that probability maps are better).

classify_clean uses classify but prunes those initial points first to  
remove any outliers - this can be a benefit when you use spatial  
priors based on probability maps.

Hope this helps,

Jason




On 25-Mar-09, at 12:18 PM, Jon Erik Ween wrote:

> Dear minclist.
>
> Sorry for the incremental posts, but then, how is one to learn??
>
> Anyway, thanks to help from the list, I'm now in the possession of
> skull-stripped, talairach registered, lesion masked 3DT1 images of a
> group of patients and would like to tissue classify these volumes (and
> hopefully label major lobes etc) so I can calculate tissue and lesion
> volumes (globally and in particular lobes, etc). Running
> "classify" (or classify_clean, I can't figure out the difference
> between these two, exactly) complains that I don't have a tag file (or
> in the case of classify_clean, that the tags are not in the volume). I
> was thinking that "classify" used the specified model to figure out
> which voxels were which tissue, or do I need to manually tag voxels in
> each of the target volumes?
>
> I, again, appreciate any guidance!
>
> Cheers
>
> Jon
>
> Soli Deo Gloria
>
> Jon Erik Ween, MD, MS
> Scientist, Kunin-Lunenfeld Applied Research Unit
> Director, Stroke Clinic, Brain Health Clinic, Baycrest Centre
> Assistant Professor, Dept. of Medicine, Div. of Neurology
>     University of Toronto Faculty of Medicine
>
> Kimel Family Building, 6th Floor, Room 644
> Baycrest Centre
> 3560 Bathurst Street
> Toronto, Ontario M6A 2E1
> Canada
>
> Phone: 416-785-2500 x3648
> Fax: 416-785-2484
> Email: jween at klaru-baycrest.on.ca
>
>
> Confidential: This communication and any attachment(s) may contain
> confidential or privileged information and is intended solely for the
> address(es) or the entity representing the recipient(s). If you have
> received this information in error, you are hereby advised to destroy
> the document and any attachment(s), make no copies of same and inform
> the sender immediately of the error. Any unauthorized use or
> disclosure of this information is strictly prohibited.
> _______________________________________________
> MINC-users at bic.mni.mcgill.ca
> http://www2.bic.mni.mcgill.ca/mailman/listinfo/minc-users