Posted by
Jacqueline Ross on
Jan 09, 2018; 9:32pm
URL: http://imagej.273.s1.nabble.com/Weka-Trainable-Segmentation-alternative-tp5019833p5019861.html
Dear Adrián,
I suggest using an immunohistochemistry approach with fluorescence secondary antibodies so that you can specifically label the immune cells and also because segmentation of fluorescence images is much better.
Also, I'm a bit puzzled by your H&E images as they seem to be all the same shade of blue/purple whereas the eosin should be pink with the nuclei only stained in blue. Using the green channel seems like it coud potentially work for size measurements but that's not what you are looking for.
Kind regards,
Jacqui
-----Original Message-----
From: ImageJ Interest Group [mailto:
[hidden email]] On Behalf Of Adrián Villalba
Sent: Sunday, 7 January 2018 11:24 a.m.
To:
[hidden email]
Subject: Re: Weka Trainable Segmentation alternative
Dear Ignacio,
This is an example image with the different types of islets and insulitis.
The legend is the following:
A = grade 0, no insulitis; B = grade 1, peri-insular; C = grade 2, mild insulitis (<25% of the islet infiltrated); D = grade 3, moderate insulitis (25–75% of the islet infiltrated); E = grade 4, severe insulitis (>75% islet infiltration).
I would like to compare my template images against a new image automatically, so i do not have to do it manually in the microscope. But Weka has not been useful, first of all because Hematoxilin/Eosin staining is not very different between islets and the rest of tissue. Moreover, the different score of the 5 types of islets (scored from 0 to 4) is also tricky for the Weka algorithm. Do you think i can use a different approach?
Thank you very much for your time and attention,
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2018-01-06 0:39 GMT+01:00 Adrián Villalba <
[hidden email]>:
> Dear all,
>
> I am trying to use the Weka Trainable Segmentation plugin in order to
> classify islets of Langerhans in Hematoxilin/Eosin tissues. There are
> four different types of islets depending on insulitis (immune cell
> infiltration within the islet) as i show you in an attached
> JPG-picture (just to show you the expected result, not to manipulate).
>
> My goal is to do it automatically in imageJ, rather tan manual scoring
> of pictures. So i thought it would be a good idea to use the Trainable
> Weka Segmentation plugin just to train the algorithm to do it
> automatically but it fails. (I cannot attach the classifier.model
> archive because it is rejected by the mailing list conditions).
>
> I think that maybe it is not a proble for the Weka, instead being a
> conceptual problem and that maybe you could know another imageJ tool
> to pursuit that goal.
>
> Thank you very much in advance!
>
> --
>
> - Adrián Villalba Felipe.
>
https://es.linkedin.com/in/adrianvillalba>
>
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