Posted by
Mohaja14 on
Oct 01, 2019; 1:37pm
URL: http://imagej.273.s1.nabble.com/Weka-Segmentation-Generating-ROI-from-semantic-segmentation-and-cropping-tp5022476.html
Hello I am Samuel,
I am trying to study fuel cells for my graduate degree, where I have to
study many images. I am trying to build a macro that will generate a ROI
around the top most layer and crop it. As you can see in the picture below,
the top most layer is called the CL layer.
<
http://imagej.1557.x6.nabble.com/file/t382438/Fig-SEM-Micrograph-of-Cross-section-of-SOFC-Single-Cell.png>
I would like this macro to run on a batch of images, but not every image is
the same. Sometimes the contact layer can be higher/lower, or
thinner/thicker. So I cannot simply hard code specific retangular ROI
dimensions, because it may capture not enough of the CL layer, or it may
capture some of the layer below it.
I am trying to use the Trainable Weka Segmentation, because it seemed best
suited for this task. Where I can train it to select only the CL layer.
<
http://imagej.1557.x6.nabble.com/file/t382438/trained.jpg>
In the image above I have cropped the CL layer and the layer below it, the
CFL layer. I then trained my classifier to segment the image into 3 parts,
the CL layer, the CFL layer, and the background. Now my real question is: In
a macro, how can I generate a ROI around the area with the most red traces,
and then crop it so it only contains the CL layer with a batch of images?
Thank you,
Samuel Sayed
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